The share of income that goes to top earners has reached levels not seen in over half a century, and addressing inequality has become a central issue for policymakers. Designing policies to alleviate income disparities requires a thorough understanding of how inequality affects the economy. Somewhat surprisingly, while several studies investigate the consequences of rising income inequality for households (Auclert and Rognlie 2017, 2020; Mian et al. 2020), much less is known about how inequality affects firms.

In a recent study (Doerr et al. 2022), we examine the important link between income inequality and firms’ job creation. Our analysis of US data reveals that a larger top income share hurts small firms, while benefiting larger firms. The reason is that households’ savings portfolios change with their income level. Higher income inequality leads to more household savings flowing into stocks and bonds – which are mostly used for financing by larger firms – rather than into bank deposits. In turn, as small businesses depend on banks for financing, their funding becomes more costly and they create fewer jobs. 

Complementing our analysis with a theoretical model, we show that by altering the allocation of household savings, rising income inequality not only hurts small firms, but suppresses overall employment. Income inequality has thereby contributed to two important macroeconomic trends: the decline in small business and the fall in the labor share, i.e., the share of total income that accrues to workers (Decker et al. 2016; Autor et al. 2020).

Figure 1: The allocation of financial assets across income groups

The effects of rising top incomes on job creation

The detrimental effect of inequality on job creation is explained by the fact that households’ savings behavior changes as they become richer. As Figure 1 shows, deposits (such as checking and savings accounts) make up more than 60% of the total financial wealth for the bottom 20% of the income distribution. Yet they account for less than 20% among the richest 10% of households. High-income earners instead invest directly in capital markets, for example by holding stocks and bonds. The negative link between income and deposit shares suggests that as the income share of top earners rises, a relatively larger share of total financial assets is held in the form of stocks and bonds. Meanwhile the share of bank deposits declines. 

We argue that more dollars in the hands of high-income rather than low-income households hence lead to fewer jobs created by small firms, while large firms expand. The reason is that greater inequality translates into lower funding costs for large firms but higher funding costs for small firms. It does so for two reasons. On the one hand, large firms have access to capital markets and hence benefit from a greater demand for stocks and bonds. On the other hand, banks’ access to deposits affects their cost of funds and ability to extend credit (Ivashina and Scharfstein, 2010; Drechsler, Savov and Schnabl, 2017), and small firms rely predominately on banks as a source of funding (Chodorow-Reich, 2014; Liberti and Petersen, 2019). As fewer savings are held in the form of deposits, rising top income shares increase banks’ cost of funds and thereby curtail credit supply. This hurts smaller bank-dependent firms.

Figure 2: The rise in top incomes and the decline in small business

The data show a strong negative relationship between top income shares and small firm job creation in the US. Panel (a) in Figure 2 shows that as the top 10% income share rose from around 30% in 1980 to almost 50% today, the job creation rate of small firms steadily declined. The negative association between top incomes and job creation is also present in individual states: Panel (b) shows that US states with higher top income shares experience systematically lower job creation by small firms. 

We conduct a formal empirical analysis using the variation across US states and time in net job creation of firms of different sizes. The idea behind our strategy is that equity and bond markets work nationwide, while banks’ deposit collection and lending to small firms occurs more locally. We find that a 10 percentage point increase in the top 10% income share leads to a 2.5 percentage point decline in the net job creation rate of small firms relative to larger firms. This effect is economically sizable: the top 10% income share has increased by about 10% between 1980 and 2015, while the average job creation rate at small firms in the 1980s was 4.2%. These effects are not driven by alternative explanations, such as technological change, lower spending on public goods, or changes in local real estate prices.

Consistent with the proposed portfolio channel, we find that rising top income shares reduce the amount of bank deposits, while increasing banks’ interest expense on deposits. That is, the cost of funds increases for banks – and thereby for small firms. We also find that the effect of rising income inequality on job creation is stronger the smaller the firm, reflecting that smaller firms rely more on banks due to higher informational frictions. When we further split industries into those that are more or less bank-dependent (following Doerr 2022), we find that small firms’ job creation in bank-dependent industries declines by more when top incomes rise. 

The decline of small business and consequences for wages and welfare 

How much of the overall decline in small business is due to the rise in income inequality? And to what extent can growing inequality explain other macroeconomic developments? Answering these questions requires us to combine our estimates with a theoretical model. We thus build a macroeconomic model that we calibrate to our empirical findings. The model shows that the increase in the top income share between 1980 and today, from 30% to 50%, accounts for about 1 percentage point of the decline in the share of employment at firms with fewer than 500 employees. Since this share has fallen by around 5 percentage points since 1980 in the US, rising top incomes, through their effect on firms’ funding conditions, explain almost 20% of this overall decline. 

Small firms further tend to operate with a higher labor ratio, as they employ more workers per unit of capital. The rise in the top income share and induced shift in economic activity towards larger firms hence suppressed aggregate employment and contributed to the decline in the labor share, a key trend in the US and globally (Karabarbounis and Neiman 2013; Autor et al. 2020).

Beyond the effects of rising top incomes on firms and aggregate activity, we find that ignoring the link between households’ savings decisions, the banking sector, and firms’ job creation understates the effects of redistributive policies on welfare. If income is redistributed to lower-income households, more resources flow to small firms via banks. In turn, wages – the main source of income among poorer households – increase. This feedback channel amplifies the positive effects of the policy on the incomes and welfare of lower-income households. In other words, policy proposals that aim at reducing income inequality have greater welfare consequences when taking the effects of inequality on job creation into account.

Conclusion

While existing studies have investigated the effects of rising top incomes on households, this policy brief discussed the important link between income inequality and job creation. An analysis of US data shows that growing inequality has contributed to the decline in small business and suppressed overall employment. The economic mechanism that we uncover in our study suggests that policy initiatives addressing the rise in inequality could benefit poorer households well beyond the effects that occur directly through redistribution. Indirect effects on firms’ job creation – and hence wages – also play an important role.

References

Auclert, Adrien and Matthew Rognlie (2017) “Aggregate Demand and the Top 1 Percent”, American Economic Review: Papers & Proceedings, 107 (5), pp. 588–592.

Auclert, Adrien and Matthew Rognlie (2020) “Inequality and Aggregate Demand”, Working Paper.

Autor, David, David Dorn, Lawrence F Katz, Christina Patterson, and John Van Reenen (2020) “The fall of the labor share and the rise of superstar firms”, The Quarterly Journal of Economics, 135 (2), pp. 645–709.

Chodorow-Reich, Gabriel (2014) “The employment effects of credit market disruptions: Firm-level evidence from the 2008–9 financial crisis”, The Quarterly Journal of Economics, 129 (1), pp. 1–59.

Decker, Ryan A., John Haltiwanger, Ron S. Jarmin, and Javier Miranda (2016) “Declining business dynamism: What we know and the way forward”, American Economic Review, 106 (5), pp. 203–07.

Doerr, Sebastian (2021) “Stress tests, entrepreneurship and innovation”, Review of Finance 25(5), pp 1609-1637.

Doerr, Sebastian, Thomas Drechsel and Donggyu Lee (2022) “Income Inequality and Job Creation”, Working Paper.

Drechsler, Itamar, Alexi Savov, and Philipp Schnabl (2017) “The Deposits Channel of Monetary Policy”, Quarterly Journal of Economics, 132 (4), pp. 1819–1876.

Ivashina, Victoria and David Scharfstein (2010) “Bank lending during the financial crisis of 2008”, Journal of Financial Economics, 97 (3), pp. 319–338.

Karabarbounis, Loukas and Brent Neiman (2014) “The Global Decline of the Labor Share”, The Quarterly Journal of Economics, 129 (1), pp. 61–103.

Liberti, José María and Mitchell A. Petersen (2019) “Information: Hard and Soft”, Review of Corporate Finance Studies, 8 (1), pp. 1–44.

Mian, Atif, Ludwig Straub, and Amir Sufi (2020) “The saving glut of the rich”, Working Paper.

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Without being overly prescriptive, macro research must meet two standards to keep the field moving in a productive direction: models must be tested empirically and researchers must think carefully about how underlying assumptions restrict the set of questions that can be answered with a given model. 

Models move knowledge forward through rigorous empirical testing.  Matching moments in model calibration is not enough—nor should it be considered true empirics. When economics is done well, theory and empirics are complements: empirical research disciplines models and theory disciplines empirical research.  In recent decades, macro research has tilted very heavily towards theory, forgoing the feedback generated by rigorous empirical testing and, as a consequence, dramatically reducing the ratio of insight to effort.

Macro as a field must value empirical contributions to flourish fully.  There has been significant progress in the last decade, but the balance still tilts heavily towards theory.  Macroeconomists must stop dismissing empirical contributions as trivial for macro theory to reach its potential.  It’s not an accident that many of today’s best macroeconomists stand out for their work in both theory and empirics: empirical work disciplines their theoretical research.    

Over the past 40-50 years, research in short-run macroeconomics has focused on the goal of creating unified, internally consistent models of the macroeconomy.  While this is a worthy goal, it has perhaps become too dominant—and imposes hidden costs on research.  The emphasis on developing a central baseline model to which idiosyncratic features are added for addressing a specific problem discourages many researchers from considering the suitability of the underlying model to the specific question being asked. 

As economists we are taught that every model is a simplification, so that the relevant question is not whether a model is good or bad but whether it is good or bad for answering a specific question.  Yet choosing a single baseline model of the macroeconomy tends to obscure the closeness of the relationship between the model and the question it is used to answer.  Often macroeconomists think carefully about the relationship between their question and the idiosyncratic features they add to the baseline model, but many of the assumptions underlying the baseline model become invisible and thus unquestioned.  This is understandable given the complexity of modern macro models, but it has high costs.  More careful consideration of the assumptions underlying baseline models and their appropriateness to individual research questions can help move the field forward.

Promising recent developments

Like a large ship, the direction of research in a field turns only slowly, but macro has seen promising developments in the last decade or so.  Many of these changes were driven by the failure of then-existing macro models to address the issues that emerged in the 2008 financial crisis and Great Recession. 

The greatest success of macro over the past decade has been the integration of the financial sector into macro models.  Understanding the macroeconomy in the Great Recession depended on understanding myriad financial linkages between banks, households, and firms.  The field has seen an explosion of outstanding research in macro finance—an area where integration between theory and empirics has developed beautifully.  Modern macro finance can serve as a model for other areas of macro. 

While less developed than macro finance, another area of macro that has seen significant progress in the last decade is more realistic modeling of household behavior.  The addition of liquidity constraints; heterogeneity; and limits to attention, information, and foresight have begun addressing key weaknesses in the standard models. 

These and other promising developments in recent macro research share a few key features: they incorporate insights from behavioral economics, they focus on mechanisms, and they are deeply influenced by empirical research using microeconomic data.

The value of micro data and macroeconomic history

One of the challenges of studying macroeconomics is that major macroeconomic events such as major recessions and financial crises are relatively rare.  In-depth study of a single episode (such as the Great Recession) can be immensely fruitful, but the sample of relevant episodes is often quite small.  Controlled experiments are usually unethical and/or impossible to implement (e.g. experimental design gets difficult when spillovers are significant).  These difficulties help explain how macro became so dominated by theory to begin with, but they are not insurmountable.

Using micro data to study macroeconomic mechanisms has gained popularity in recent years, particularly in research areas such as macro finance and macro labor.  Borrowing identification strategies from applied micro (and then considering general equilibrium effects) allows macroeconomists to do high-quality empirical work focused on a single macroeconomic episode.  This approach has dominated studies of the Great Recession and proved itself extremely fruitful, but it still has limits. 

For instance, macroeconomists use micro data to study how inflation expectations influence consumption in the Great Recession.  Papers such as such as Bachmann, Berg, and Sims (2015)  help illuminate a key mechanism for unconventional monetary policy, finding that inflation expectations have almost no effect on consumption at the ZLB.  The shortcoming of such studies (not specific to any paper, but applying to most studies of a single macroeconomic episode) is that they specifically address one institutional setting.  In this case, these studies tell us about the limited influence of inflation expectations on consumption in a setting where many households are highly indebted and inflation expectations are strongly anchored.  In theory, lower levels of household debt and more responsive inflation expectations could substantially increase the responsiveness of consumption—increasing the efficacy of unconventional monetary policy in other institutional settings.  Empirical studies of the Great Recession cannot on their own tell us how much these institutional details matter.

Macroeconomic history provides additional avenues for empirical research in two ways: by expanding macroeconomic data sets and by allowing researchers to analyze a larger array of macroeconomic events and settings using micro data. 

Going further back in time expands the sample of major macroeconomic events: recessions, financial crises, and major wars were quite frequent between 1800 and 1950 (the period usually excluded from modern macro research but for which substantial data is available).  Expanding the sample backwards allows for more complete analysis of macroeconomic data, though researchers must carefully consider changes in relevant institutions before choosing a sample period.

Analyzing an array of individual historical episodes using historical micro data complements macroeconomic research involving modern micro data.  Discovering how estimates of key macro parameters vary across macroeconomic episodes helps us discover which factors of the institutional environment we should focus on, and can help inform and refine theoretical models.

For example, Carola Binder and I study the effects of inflation expectations on consumption using household survey data from the Korean War.  In early 1951 the Fed wanted to raise interest rates to address rising inflation but was prevented by the Treasury. The American economy boomed, household debt levels were exceptionally low, and both actual inflation and inflation expectations varied substantially more across time than they do today.  We find modest intertemporal consumption shifting: a one standard deviation increase in inflation expectations is associated with a 3 percentage point increase in the likelihood that a household bought durables in the previous year, or a shift of $222 (about 7% of median income) from planned 1951 consumption to actual 1950 consumption.  Comparing our results to those of similar studies on the Great Recession provides a rough estimate for the influence of the institutional features which vary so dramatically between the two settings.

Careful empirical studies of specific macroeconomic episodes and careful consideration of the institutional similarities and differences between them has the potential to give us a much fuller picture of how the macroeconomy functions and can guide macroeconomic theory.  This empirical work can be used to improve calibration, but also to test and compare models.  Studying multiple macroeconomic episodes in depth provides opportunities for testing models’ out-of-sample forecasting capabilities.  Using macroeconomic history to expand the boundaries of empirical research in macroeconomics can in turn contribute to better macroeconomic theory.  

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The most important problem with macro over the past few decades has been that it has been too theoretical. When I say this, I don‘t at all mean to say that theory is useless. To the contrary, theory is an essential element of a healthy science. But a healthy science needs a balance between theory and empirical work. Macro lost this balance in the 1980s and is only regaining it now.

Most narratives about the evolution of macro focus on the evolution of macroeconomic theory and the rational expectations revolution in particular. An under-appreciated part of this story is that the rational expectations revolution shifted the field away from empirical work. This was partly because building models that met the higher standards of rigor set by Lucas and his co-revolutionaries was a challenging and therefore highly absorbing task. But that isn’t the only reason.

For reasons that are not entirely clear to me, a very substantial fraction of macroeconomists came to believe that the Lucas critique implied that quasi-experimental empirical methods could not be used in macro. The idea that changes in policy could radically alter empirical regularities (i.e., the Lucas critique) somehow came to be interpreted to mean that the only way to do empirical work in macro was to write down fully specified general equilibrium models of the whole economy and evaluate the entire model (either by full-information inference methods or moment matching). Sargent, for example, placed enormous emphasis on the idea of “cross-equation restrictions.“ It seems that this line of thinking led large numbers of macroeconomists astray in terms of how to think about empirical work in macro for several decades.

This misunderstanding was never complete. There were isolated pockets of empirical work in macro that employed instrumental variables methods — e.g., using lags as instruments when estimating Phillips curves or Euler equations. The structural VAR literature also managed to carve out some limited understanding of using “identifying assumptions” to move away from whole-model inference. And throughout, there was a small minority of empirical macro researchers that understood the value of quasi-experimental methods. But a large fraction of macroeconomists rejected such analysis as being un-sound and an even larger fraction of macroeconomists (including myself) were muddled and inconsistent in their thinking about when and how quasi-experimental methods could be used in macro (often rejecting these methods out of hand in unfamiliar settings while being perfectly happy to use them in other more familiar settings).

This misunderstanding seriously held back progress in empirical macroeconomics for a generation. Over this period, applied micro experienced a credibility revolution which led various types of quasi-experimental methods to become vastly more important in many subfields of economics. Macro was largely left behind on this front. Two things are worth noting about this. First, quasi-experimental work is particularly difficult in macro due to identification being difficult in a general equilibrium setting. Second, substantial parts of applied micro became pretty unbalanced in the other direction, with theory largely falling by the wayside. Recently, as macro has been catching up on the empirical side, it seems that more and more researchers in applied micro have also started embracing more thoroughly the complementarity of quasi-experimental methods and serious structural modelling – i.e., having “the best of both worlds” as Todd and Wolpin recently put it. In this regard, macro was probably ahead of the curve and may even have helped influence our applied micro colleagues.

During the time theory was dominant in macro, much progress was made on the theoretical front. But being so dominated by theory, the field was very exposed to another problem: models in which markets work well are (usually) easier to solve than models in which market work poorly. This simple fact has huge consequences because it imparts a bias on economic theory towards models in which markets work well. Since models in which markets work well are easier to solve, researchers tend to work with such models. The default assumption about a market is typically that it is perfectly competitive. Researcher will often introduce a carefully constructed friction in a critical place in their model and focus their analysis on the implications of this friction. But all other markets in the model are typically modeled as being perfectly competitive for simplicity.

The typical researcher is so used to assuming that virtually all markets are perfectly competitive that they are often completely blinded as to the consequences of these assumptions. They take as given certain implications of these perfect markets assumptions as though they were inevitable consequences of logic as opposed to the consequences of obviously false simplifying assumptions that they and everyone they know have made for years and years. One example of this that resonates strongly with me is the notion that MPCs are trivially small in many macro models. This has wide ranging consequences for the behavior of these models (e.g., stimulus checks are useless). For many years, I had never encountered a model where this was not true (or at least forgotten any such instances). So, I was largely brainwashed to believe that these features of these models were just how things must be. But then at some point I came to appreciate how differently models with uninsurable idiosyncratic risk behave and it was like being hit by a ton of bricks. How could I have not realized how critical the simplifying assumption of perfect markets was in this regard! (There are many other such examples. A high profile one in labor economics has to do with the implications of raising minimum wages.)

One of the critical roles of empirical work is to confront theorists and policymakers with facts that help them see that the models they are using are not well suited to analyze whatever feature of reality they are interested in. Macro’s muddled understanding of the value of quasi-experimental methods was a huge handicap for the development of the field in this regard. Some facts are simple and don’t need quasi-experimental methods to establish (the equity premium is a good example). But many critically important facts are beyond reach without quasi-experimental methods (e.g., estimates of MPCs, fiscal multipliers, the slope of the Phillips curve, the IES, the effects of monetary shocks, etc.). Without a robust set of such estimates to guide the development of theory, the theoretical literature is rudderless and is at risk of getting lost at sea.

Thankfully, things have now started to improve very rapidly on this front in macro. Especially among younger researchers, the cross-equation restriction fog is lifting and the value of quasi-experimental methods is starting to be understood more clearly and more generally. It is, for example, becoming better and better understood that with the help of an instrument (or some other source of exogenous variation) one can estimate various types of causal effects without specifying a full structural model of the whole economy. (Panel data methods and various non-traditional datasets have also helped a lot.)

One still sometimes faces questions along the following lines: “but aren’t X and Y endogenous variables that are jointly determined in general equilibrium” even when one has spent a huge amount of time explaining the nature of the exogenous variation that one is exploiting; and one still faces blank stares on occasion when one responds to such questions with a version of “Yes, so are P and Q in a supply and demand setting, but that doesn’t mean that estimating the slope of a demand curve by IV is impossible.” However, such instances are becoming less frequent.

The upside of this is that credible estimates of more and more critical empirical statistics are emerging in macro and this is starting to guide theoretical and policy work in a more and more serious way. Let me take a few examples: We now have a substantial body of high quality work indicating that MPCs are quite large. This is the basic empirical fact favoring HANK models over traditional NK models. But this fact also has important consequences when it comes to the macroeconomic effects of policies that supplement people’s incomes during recessions. We also have a substantial body of high quality work indicating that fiscal multipliers are large in the cross-section. This fact points in a similar direction as the high MPC fact: macro stimulus can raise output substantially in circumstances when monetary policy is accommodative (e.g., at the ZLB). Furthermore, we have more and more work indicating that the slope of the Phillips curve is modest. This implies that a boom that leads to overheating of the economy will have modest effects on inflation as long as inflationary expectations remain anchored. (There are many more good examples.)

Macro has a lot of lost time to make up for when it comes to making use of quasi-experimental empirical methods. This creates a stock-flow problem. The stock of empirical work using quasi-experimental methods in macroeconomics remains low, and the challenges of doing such work remain high due to the difficulties of identification in a general equilibrium setting. But the flow is very different from the stock: there is a substantial flow of high quality quasi-experimental empirical work in macro. Looking at this flow one can reasonably argue that the field is trending strongly towards a healthy balance between theory and empirical work. I am optimistic that this will over time result in more and more people concluding that macro has “found its way” again. I certainly think it has. 

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Both economists and political scientists have worked on the impact of electoral systems. Empirical methods from economics as well as economic analysis of the incentives created by different political systems have contributed to our understanding of the consequences of electoral systems on representation. Additionally, economists have estimated the impact of electoral system on fiscal expenditures, something we will discuss towards the end of the policy brief.

There are two main voting systems in modern democratic societies: majoritarian systems and proportional representation systems. Federal voting in the United States is majoritarian though some states such as Maryland have proportional representation at the state level. In a majoritarian system, also known as a winner-take-all system or a first-past-the-post system, the country is divided up into districts. Politicians then compete for individual district seats. The candidate who receives the highest vote share wins the election and represents the district.

The main alternative to a majoritarian system is a proportional representation system. In a proportional representation system, citizens vote for political parties instead of individual candidates.[1] Seats in a legislature are then allocated in proportion to votes shares. In an ideal proportional representation system, a party that receives 23% of the votes nationwide also gets approximately 23% of the seats in the legislature.

Redistricting

One important aspect of a majoritarian system is that representation occurs by geographical district. In each district of a pure majoritarian system, whichever candidate gets a plurality of the vote serves as representative for that district. However, people move in and out of districts and thus district sizes change. As a result, most majoritarian systems have a redistricting process. In the United States, redistricting happens every decade after the population is counted in the Census.

One large problem with redistricting is that how districts are drawn can have a large influence on representation. For example, imagine that a country has 50% right wing voters and 50% left wing voters. Suppose the left-wing party gets to draw the district boundaries and suppose that ten districts need to be created. The left-wing party could simply pack right wing votes into one district by being creative with how it draws maps. If the left-wing party did this, there would be one right-wing seat with 100% right-wing voters. In the remaining areas, 5/9 of voters would be left-wing. Thus, the left-wing party could end up with nine of the ten district seats despite only having 50% of the votes by drawing its maps creatively. This is called gerrymandering.

In a majoritarian political system, districts need to be drawn and redrawn and it is very easy to draw districts in order to benefit one political party over another. Unfortunately, in the United States, district maps are largely drawn by politicians. In most states, redistricting bills must be passed by state legislatures and signed by the Governor. All state legislature except for Nebraska have two chambers (an Assembly or House and a Senate). If a party has control over both chambers and the governorship, it can potentially redistrict without any input from the other political party. Coriale et al. (2020) show that in the past two decades, the average seat share gain in the House of Representatives from legal control by the Republican party over redistricting is an average of 8 percentage points over the subsequent three elections. Though we do not see a similar impact of Democratic control of redistricting on Democratic seat shares, we do for large Democratic states. Overall, these effects are sizable. They account for between 50% and 60% of the gap between the two parties in the House of Representatives in both the 2000s and the 2010s. Coriale et al. (2020)’s estimates of the impact of legal control are shown in Table 1.

Table 1: Average Aggregate Partisan Effects of Partisan Redistricting by Decade

A move away from majoritarian electoral systems to proportional representation systems would get rid of political districts and, as such, would get rid of gerrymandering.

Geographic Concentration

There is a second problem with majoritarian systems. Even without parties manipulating district boundaries for political advantage, majoritarian systems can lead to systemic over-representation of some parties at the expense of others. For example, it is possible for the Democratic party to win just over 50% of the seats with only slightly more than 25% of the votes if the Republican party’s voters are concentrated in 100% Republican districts. This extreme failure of representation in a majoritarian system is interesting in theory but is it a problem in practice?

As pointed out by Rodden (2019), this has, in fact, become endemic in modern majoritarian systems. Political parties, over time, have become geographically polarized by population density with more urban areas further on the left and rural areas further on the right. There is now a clear spatial gradient with urban areas voting heavily for parties on the left, suburban areas voting moderately for the right, and rural areas voting more heavily for the right. This is not just true in the United States but also in other countries as well, particularly ones with majoritarian systems such as the U.K. and France (Piketty, 2018).

Majoritarian systems with a spatially even mixing of left-wing and right-wing voters can be problematic in that small differences in popularity of a party can lead to huge differences in representation. A party’s share of Congressional seats could decrease from 100% to 0% with a very small change in votes if voters were homogeneously spread across districts. However, the problem faced by modern majoritarian systems is due to differential concentration of left-wing and right-wing voters. Jonathan Rodden, in his book, Why Cities Lose: The Deep Roots of the Urban-Rural Political Divide shows this differential concentration based upon work with Jowei Chen. They look at each person’s nearest 250,000 neighbors. They choose 250,000 neighbors because the average upper chamber district in Pennsylvania contains around 250,000 voters. They find that over 25% of Democrats’ nearest neighbors are more than 70% Democrats whereas no Republicans’ nearest neighbors are more than 70% Republican and only 10% have more than 60% of their neighbors being Republican.

In a recent paper, Chen and Rodden (2018) do the same analysis and present the average share of Democrats in the nearest 700,000 neighbors of each Democrat and the average share of Republicans in the nearest 700,000 neighbors of each Republican. They do this by state. The results are presented below. Republicans are more concentrated only in five states: Arkansas, Hawaii, Illinois, Mississippi, and New Hampshire. Moreover, in most states, Democrats are far more concentrated than Republicans.

Table 2: The Geographic Concentration of Democratic and Republican Voters

Why does the greater concentration of Democrats lead to a failure of representation? The best way to understand this is to use Nicholas Stephanopolous’ concept of the efficiency gap. Stephanopolous (2015) computes wasted votes (all votes in a district for any loser in the district and the number of votes above plurality for the winner in a district). The problem is that the greater concentration of Democrats in cities than Republicans in rural areas leads to more wasted votes by Democrats than by Republicans. Since Republicans waste fewer votes, they are able to win more districts. In other words, they get systematically greater representation given their vote shares. Idiosyncratic differences across parties in representation average out. However, the differences we see these days in the United States, the U.K. and France as well as in other majoritarian systems such as Australia’s House of Representatives display systemic over-representation of rural over urban voters.

Overall, proportional representation does a better job at representing the will of voters in that political preferences of voters more closely match seat shares in a proportional representation system.

Duverger’s Law

One additional consequence of having a majoritarian political system is that there tends to be fewer political parties. In any given district and sometimes overall at the national level, only two political parties emerge. In this sense, the United States, with its two main political parties is a textbook example of a majoritarian system. Why does the electoral system help determine the number of political parties?

In a majoritarian system, there is only one winner. With a plurality rule for deciding the winner, this gives parties which are ideologically closer to each other a reason to combine forces into one party. For example, suppose that there are two left wing parties each of which garners 30% of the vote and there is a right-wing party which garners 40% of the vote. In a majoritarian system, the right-wing party will win even though 60% of the people prefer a left-wing party. As a result, the two left-wing parties have strong incentives to combine and form one party or at least voters will have strong interests in coordinating on one of the two left-wing candidates. In a proportional representation system, by contrast, having two left wing parties may attract overall more left wing voters. Maybe some ideological voters would only vote for one of the two. In that case, having both will bolster turnout for the left and thus the left-wing seat share in parliament or Congress.

This empirical regularity about the number of parties in proportional representation as opposed to majoritarian systems as well as the logic behind it was first pointed out in Maurice Duverger’s book Political Parties: Their Organization and Activity in the Modern State (Duverger, 1954). Modern day Australia provides a natural experiment which illustrates Duverger’s law. Australia’s Senate is elected using state-level proportional representation whereas Australia’s House of Representatives is elected in majoritarian districts. Whereas ten different political parties are represented in the Senate, the House is dominated by the Australian Labor Party and the Liberal-National Coalition (Rodden, 2019).

Rank-Choice Voting

One increasingly popular alternative to proportional representation in multi-member districts is ranked-choice voting in single-member districts. In a rank-choice voting system, instead of voting for one person or one party, voters rank alternative candidates. Then, top-ranked votes are tabulated for each candidate after which the worst overall performer is eliminated. If no candidate has reached a majority of votes cast, the votes for the eliminated candidate are reallocated to the next preferred candidates listed by the eliminated candidates’ voters. This system has been implemented in Alaska, Maine and New York City among other places. Moreover, somewhat similar systems which eliminate candidates in two rounds exist in states such as California, Georgia and Louisiana. Though there is very limited theoretical work or empirical evidence on rank-choice voting, switching to rank-choice voting would likely tend to moderate candidates and thus improve representation relative to a single-member district system with plurality voting. This moderation would probably be large given the current electoral system in the United States with highly partisan districts and candidates selected in highly partisan primaries.

Let’s look at an example. Suppose there are 3 candidates: one far-right candidate with support from 40% of voters, one moderate-right candidate with support from 35% of voters, and one left wing candidate with support from 25% of voters. Moreover, lets assume that right wing supporters prefer the other right-wing candidate to the left-wing candidate and that supporters of the left-wing candidate prefer the moderate-right to the far-right candidate. In that case, in a majoritarian system with a primary, the far-right candidate would defeat the moderate-right candidate in a primary and then the left candidate in a general election. However, with rank-choice voting, the left-wing candidate would lose in the first round of counting. After that, the votes of the left voters would be transferred to the moderate-right candidate, who would then defeat the far-right candidate 60% to 40% in the second round of counting.

Though rank-choice voting sometimes would lead to a more moderate choice when that choice would be preferred in aggregate by voters, sometimes it would not. Let’s now reverse the support for the moderate-right and the left voters from our previous example. We thus get: 40% support for the far-right, 25% for the moderate-right and 35% for the left. Let’s assume that the secondary preferences of voters remain the same (right-wing voters prefer the other right-wing voter to the left-wing candidate and left-wing voters prefer the moderate-right candidate to the far-right candidate). In this case, in the first round, the moderate-right will be eliminated and in the second round, the moderate-right votes will be transferred to the far-right. Thus, even though a 60% majority of voters prefer the moderate-right to far-right, the far-right candidate will still win even with rank-choice voting.

In addition, since the rank-choice voting variant of single member districts is still a single member district system, it will not fundamentally eliminate the problems associated with over-representation of rural interests due to greater spatial concentration of urban voters; it also won’t solve the problem of parties strategically drawing district boundaries to increase the seat shares of their parties.

Economic Policy

We now discuss how the number of parties can affect voter turnout and the types of political coalitions that form. Proportional Representation systems having a greater number of parties likely increases voter turnout. Some voters are only motivated to turn out to vote if they are ideologically similar enough to a party. Citizens who do not vote are much likely to be lower income and are more likely to support greater economic redistribution. Funk and Gathmann (2013) demonstrate that when Swiss Cantons converted from majoritarian to proportional representation electoral systems, voter turnout increased, representation of left-wing parties rose, and social expenditures increased.

Redistributive economic policy may additionally be de-emphasized in a majoritarian system. A majoritarian system shapes coalition formation. As mentioned earlier, in the United States, the cities support the Democratic party, the rural areas support the Republican party and the suburban areas swing between the two. The Democratic party could seek alliances with suburban voters on social issues or rural voters on economic issues. Since the suburbs are more electorally competitive, the Democratic party has shifted towards more conservative economic policy and more liberal social policy. Since the Democratic party needs a plurality of votes, it largely abandons rural voters and the issues they care about. However, under a proportional voting rule, the Democratic party would instead orient its policy towards policies that would get the greatest support rather than towards voters in swing districts. Thomas Piketty (2018) shows that, over the past half a century, left-wing parties in France, the U.K. and the U.S. have shifted towards away from redistributive economic policy as more educated voters have increasingly voted for the left.

U.S. Legislation

In this policy brief, we have demonstrated that majoritarian systems allow political parties to increase their representation by controlling the redistricting process. We have also discussed research which shows that majoritarian systems over-represent rural interests and under-represent support for economic redistribution. In this final section, we discuss policy changes that are feasible in the United States.

Is proportional representation feasible in the United States? Currently, ten states use some form of proportional representation: Arizona, Idaho, Maryland, New Jersey, New Hampshire, North Dakota, South Dakota, Vermont, Washington and West Virginia. In these states, some state representatives serve in multi-member districts which allow multiple parties to represent a district. Though these multi-member districts are small and thus don’t capture the main benefits of proportional representation, it would be easy to enlarge state districts or just get rid of them entirely. Voters then would vote for all representatives simultaneously as one unified state and a proportional representation rule could easily allocate seats based upon votes.

At the federal level, the United States Senate is not easily changed as representation in the Senate is constitutionally mandated. Given the difficulty of passing constitutional reform, moving to rank-choice voting would likely at least improve representation. It would not, however, be difficult to change the voting rules for the House of Representatives in the United States. In particular, the Constitution would not have to be amended. In the 18th and 19th centuries, there were multiple predominant systems of electing representatives. For example, it was common in the early 19th century for states to elect members to the House of Representatives using at-large voting. In this system, whichever party received a plurality of the vote at the state level would get all of that states’ representatives. This practice was banned with the Apportionment Act of 1842. However, it was weakly enforced and at-large elections persisted. In 1967, this changed when Congress passed and President Johnson signed 2 U.S.C. § 2c. Since 1967, majoritarian district elections for the House of Representatives have been required. It would only take an act of Congress to change the voting system from single majoritarian district elections to proportional representation.

Endnotes

[1] In some more complex proportional representation systems, voters cast ballots for both parties and candidates. I focus here on the simplest of proportional representation systems. Also, many countries such as Japan and Germany have mixed systems where citizens cast ballots both for particular representatives of a local district as well as for a party. The party votes determine how many additional at-large seats a given party will have in parliament.

References

Chen, Jowei and Jonathan Rodden, “The Loser’s Bonus: Political Geography and Minority Representation” (2018), working paper.

Coriale, Kenneth, Ethan Kaplan and Daniel Kolliner (2020), “Political Control Over Redistricting and the Partisan Balance in Congress”, working paper.

Duverger, Maurice (1954), Political Parties: Their Organization and Activity in the Modern State, John Wiley & Sons.

Funk, Patricia, and Christina Gathmann (2013), “How do electoral systems affect fiscal policy? Evidence from cantonal parliaments, 1890–2000.” Journal of the European Economic Association 11.5: 1178-1203.

Piketty, Thomas (2018), “Brahmin Left vs Merchant Right: Rising Inequality and the Changing Structure of Political Conflict.” WID. world Working Paper 7.

Rodden, Jonathan (2019), Why Cities Lose: The Deep Roots of the Urban-Rural Political Divide, Basic Books.

Stephanopoulos, Nicholas O., and Eric M. McGhee (2015), “Partisan gerrymandering and the efficiency gap.” U. Chi. L. Rev. 82: 831

The post Majoritarian versus Proportional Representation Voting appeared first on Economics for Inclusive Prosperity.

One of the biggest challenges that countries face today is the very unequal distributions of opportunities, resources, income and wealth across people. Inclusive prosperity – whereby many people from different backgrounds can benefit from economic growth, new technologies, and the fruits of globalization – remains elusive. To address these issues, societies face choices among many different policies and institutional arrangements to try to ensure a proper supply of productive jobs and activities, as well as access to education, financial means, and other endowments that prepare individuals for their participation in the economy.

In this paper we offer a simple, organizing framework to think about policies for inclusive prosperity. We provide a comprehensive taxonomy of policies, distinguishing among the types of inequality they address and the stages of the economy where the intervention takes place. The taxonomy clarifies the differences among contending approaches to equity and inclusion and can help analysts assess the impacts and implications of different policies and identify potential gaps.

A 3 x 3 Matrix

The framework can be summarized by a 3 x 3 matrix, shown in Figure 1.[1] We consider that the discussion of policies can be organized around two questions or dimensions. First, which income group is the target of the policies intended to counter inequality or economic insecurity? Is it mainly the low-income households at the very bottom of the income distribution? Or is it rather the middle classes, who have traditionally had access to good jobs, but are increasingly facing reduced standards of living and growing economic insecurity in many nations? Is it instead the high-income or high wealth households at the very top that keep concentrating more economic power – as well as political power, possibly — individually and through stocks in large corporations? Policy priorities will naturally differ depending on whether the target is the poor at the bottom, the middle classes, or the top of the income distribution. This dimension of policy is captured by the rows of the matrix in Figure 1.

The second question relates to the stage of the economy where the intervention takes place. A useful and increasingly frequently used distinction, based on Hacker (2011), is between “pre-distribution” and “redistribution” policies. In this terminology, “redistribution” policies are ex post policies, that transfer income and wealth once they have been realized (e.g., redistributive transfers, progressive taxation, and social insurance). They reshape inequalities after the economic decisions regarding employment, investments, or innovations have been made. We will use the term post-production policies instead to denote these policies.

“Pre-distribution” policies are those that directly shape the working of and outcomes generated by markets. We find it useful to further split pre-distribution policies into two categories: pre-production and production stage policies. Pre-production policies determine the endowments that people bring to the market, such as education and skills, financial capital, social networks and social capital. Production-stage policies are those that directly shape the employment, investment, and innovation decisions of firms. Overall, the resulting classification entails a three-fold distinction between pre-production, production, and post-production policies. These are shown as the columns in Figure 1.

We note that the stage at which policies intervene is not the only stage at which the policies may have effects. In fact, there is a natural interdependence among the three columns. For instance, income taxes or social insurance transfers (post-production policies) can affect behaviors in the labor market and the effectiveness of active labor market policies or regulation.

Figure 1: The Policy Matrix

Traditional Welfare States: Pre- and Post-Production Intervention

Traditional welfare states have typically relied on the first (pre-production) and third (post-production) columns of this matrix, focusing on education and training on the one hand, and on progressive taxation and social insurance on the other hand. Production stage policies are generally considered separately, focused on market competition, physical investment, and R&D and innovation. This separation between the first and third columns on one side and the middle one on the other reflects the traditional dichotomy between social policies and economic growth or productivity policies. The former aim to correct inequality and insecurity, the latter to improve productivity, innovation, and growth.

Such a dichotomy is justifiable when the economy provides good jobs to all those with adequate education and skills and where most people can have a reasonable shot at a middle-class standard of living. But it is less justifiable in a world in which middle-class standards of living and good jobs are eroding, due to the secular trends of globalization and technological change. The disappearance of good jobs, the proliferation of bad jobs and depressed regional labor markets, as well as growing economic insecurity, would appear to be structural problems facing contemporary market economies. To address these, policy intervention in pre-production (column 1) and post-production (column 3) stages is necessary, but not nearly sufficient. It is also critical to tackle head on and directly the production stage (column 2). More precisely, it is essential to help the production stage contribute to reducing inequalities and insecurity rather than augment them.

Indeed, the production stage itself can perpetuate, dampen, or amplify existing inequalities and insecurity, through the employment, investment, and innovation decisions made by firms.

Why Should we Care about the Middle? The Costs of the Middle-Class Squeeze

“Good jobs” are traditionally defined as providing high enough a wage to afford decent living conditions, social benefits, and opportunities for career progression. A survey of French and U.S. citizens undertaken in Rodrik and Stantcheva (2021) shows that the most frequent terms which come to the minds of the respondents when asked to define good jobs are “good salary,” “a good environment/good feeling,” “good work conditions,” and “family life.” In short, good jobs are what allows citizens to live a typical middle-class life.

The availability of good jobs in adequate numbers is important not only for the workers themselves, but also for the broader impacts and spillovers it has on society (Rodrik and Sabel, 2019). A lack of good jobs and the hollowing-out of the middle class can have adverse social consequences: family breakdowns, crime, drug and opioid abuse. It can also have political costs in the form of a rise in authoritarian, ethno-nationalist populism and political polarization. Finally, as the productivity benefits of new technologies (e.g., automation, the knowledge economy, digital advances) remain bottled up in a few firms and sectors, and among some groups of workers in metropolitan areas, the concentration of good jobs reduces aggregate productivity growth in the economy as a whole.

This array of potential economic, political, and social costs is not necessarily taken into account when firms make their production and investment decisions. This opens up scope for public intervention to internalize these spillovers, for which our 3×3 matrix can be an organizing framework.

Acting on All Columns, an Integrative Approach

While production-stage policies are not a substitute for education, progressive taxation, or social protection policies, they are critical complements that more directly target the inequality and insecurity that arise in the course of production. Intervening there has the potential to ease the burden on overstretched social spending budgets.

Moreover, citizens and governments in many countries generally perceive that they are facing an undesirable trade-off between the quality and quantity of jobs, i.e., between having more good jobs and facing higher unemployment. Many countries take the stance of allowing dualistic labor markets to become entrenched (Temin, 2017): Small enclaves of productive, highly paid activities exist amidst many low-paying jobs and pockets of unemployment. There is fear that higher standards on overall working conditions would ineluctably come with higher unemployment and reduced work hours for those who remain employed. In countries where minimum wages and labor regulations prevent incomes from falling too low, as is the case in many Western European economies, unemployment ends up hitting young workers and new jobseekers who want to enter the labor market.

This tension is a real one, but it could be alleviated by increasing the supply of productive good jobs to include those who would otherwise be excluded. Historically, a growth in good jobs available was achieved thanks to economy-wide rises in productivity, which narrowed the gap between opportunities available for insiders and outsiders of the labor market. For instance, the mechanization of agriculture during the 19^th and early 20^th centuries created unemployment in rural areas, but surplus workers found employment in urban centers, in the manufacturing and related services sectors, with higher productivity and wages. This does not happen mechanically though: During the second half of the 20^th century, de-industrialization from labor productivity growth in manufacturing and import competition led to declines in production jobs available and to a shift towards employment in services, where wages and employment conditions were usually worse. The current technological trends are not automatically leading to more, highly paid good jobs either. Hence, action on column 2 is needed.

Importantly, good jobs and good firms can be complementary: Good firms produce good jobs – and perhaps vice versa. This provides a further clear argument for also targeting column 2 of the matrix and for looking at policies across columns in an integrated way. The productivity of low-wage, low-productivity firms has to be improved in order for them to be able to offer good, sufficiently high-paying jobs. Similarly, it is not sufficient to simply train or re-train workers, firms must also upgrade their capabilities. Such an approach – if successful – can enhance productivity and economic growth as well. Instead of having large unproductive and lagging sectors and groups of workers, these would join and contribute to the productive areas of the economy, benefitting from advances and technologies. To some extent, it can alleviate the tension between higher productivity and growth and more equal distribution of income and opportunities.

The largely separate tracks of social policies and economic productivity, competitiveness, and growth policies have thus to merge to some extent. The columns of the matrix have to be addressed in an integrated way, with employment policies that look more like innovation and industrial policies, and industrial and innovation policies that look more like labor market policies.

Filling the Matrix: Policy Examples

We now give examples from various countries about the types of policies that fit into each cell of this matrix, denoted by a letter. Obviously, when we use this matrix to characterize the policy landscape in different countries, we need to bear in mind that the scope and degree of intervention within each cell might vary.

Bottom incomes, pre-production stage (top left cell)

• Early childhood interventions
  • Compulsory early childhood education (France)
  • Childcare subsidies for low-income families (U.S.)
• Primary education policies
  • Compulsory education in primary and lower secondary schools (OECD countries)
  • Schools funded and managed by local authorities (Finland)

Bottom incomes, production stage (top center cell)

• Minimum wage regulations
  • Minimum wage set in national law (U.S., Most EU countries)
  • Minimum wage set under collective bargaining agreements (Austria, Belgium, Norway, Switzerland)
• Apprenticeships
  • National frameworks to regulate and promote apprenticeships (most UE countries)
  • Public funding to support apprenticeships, either to firms or apprentices (most UE countries)
  • National standards to identify high-quality apprenticeships (U.S.)
• Reduced social contributions for firms on low-income employees
  • Very low employer contributions on minimum wage employees (Ireland)
  • Tax breaks for recruiting unemployed workers (Hiring Incentives to Restore Employment Act, U.S)
• In-work subsidies
  • Earned Income Tax Credit (EITC, U.S.)
  • Prime pour l’emploi (PPE, France)

Bottom incomes, post-production stage (top right cell)

• Social transfers
  • Housing, family, child benefits (OECD countries)
• Guaranteed minimum income
  • Monthly transfer (Revenu de solidarité active, France)
  • Monthly transfer for the elderly and disabled (Supplemental Security Income, U.S.)

Middle incomes, pre-production stage (middle left cell)

• Investments in higher education
  • Public spending on tertiary institutions (1.0% of GDP in OECD countries on average)
  • Higher education as a legal right (France)
  • Pell Grants (U.S.)
• Schemes for adult learning and training
  • European Agenda for Adult Learning (EU)
  • Tax allowance for higher education expenses (American Opportunity Tax Credit, U.S.)
  • Adult education allowance (Finland)

Middle incomes, production-stage (middle center cell)

• Cluster policies to generate and disseminate innovation
  • Silicon Valley (USA), Toyota Cluster (Japan), Cambridge Technopole (UK), Sophia Antipolis (France) 
• SME support entities
  • KfW Mittelstandsbank, the SME arm of Germany’s public investment bank (17.2Bn€ of funding in 2018)
  • Small Business Administration (U.S.)
• Occupational licensing
  • Legal norms to determine job categories requiring government licensing (OECD countries)
• On- the job training
  • Personal activity account (Compte formation, France)
  • Workforce Innovation and Opportunity Act (U.S.)
• Collective bargaining and wage council
  • Swedish Jobs Council
  • Office of Labor-Management Standards (U.S.)
• Trade policies
  • U.S. tariffs in Chinese-made goods
  • EU free-trade agreements

Middle incomes, post-production stage (middle right cell)

• Unemployment benefits
  • National unemployment insurance (EU countries)
  • Unemployment benefits provided by local governments (U.S.)
• Pensions
  • Public pension system (France)
  • Tax exemptions for pension contributions (U.S.)

Top incomes, pre-production stage (bottom left cell)

• Inheritance taxation
  • Taxing any amount inherited or gift received during lifetime (Lifetime Beneficiary-based wealth transfer taxation, Ireland)
  • Differentiated tax rates based on relationship with the deceased (most EU countries)
  • Abolition of inheritance taxation (Norway, Sweden)
• Estate taxation
  • Based on estate of the deceased (UK, U.S.)
• Gift taxation
  • Gifts taxed using income rates (Lithuania)
  • Flat taxation of monetary gifts, progressive taxation of non-monetary ones (Greece)

Top incomes, production-stage (bottom center cell)

• R&D tax credits
  • Credit for Increasing Research Activities (U.S.)
  • Differentiated tax credit for SMEs and. large firms (Netherlands)
• R&D grants
  • European Innovation Fund (EU)
  • Grant to encourage SMEs to invest in R&D (Small Business Innovation Research Program, U.S)
• Antitrust policies
  • Investigation into abuse of market power for digital platforms (U.S., EU)
  • Regulation of mergers (e.g., Alstom-Siemens failed merger) (EU)
• Corporate Income taxation
  • Reduced Corporate income tax rates for SMEs (France, Belgium, Portugal)
  • Taxation of some of domestic firms’ foreign profits – (Global intangible low-taxed income, U.S.)

Top incomes, post-production stage (bottom right cell)

• Top income tax rates
  • Progressive income taxation (U.S., EU)
  • Flat tax on incomes (Hungary, Romania)
  • Tax treatment of pass-through corporations (U.S.)
• Capital gains taxation
  • Differentiated tax rates depending on duration of asset ownership (U.S.)
  • No taxes on capital gains (Belgium, Luxembourg, Slovakia)
• Wealth taxes
  • Proceeds of the wealth tax flowing to local governments (Norway)
  • Wealth tax on specific asset classes (Impôt sur la fortune immobilière, France)

Conclusion

The policy matrix is an organizing framework. It does not per se determine what the right policies are, but highlights that there are opportunities at each of the three stages of the economic process and at different segments of the income distribution. It can help streamline policy discussions, identify areas for intervention, reveal how different parts of an overall policy system fit together, and allow useful comparisons across policy regimes in different countries.

Endnotes

[1] The matrix was first used in the introduction of Blanchard and Rodrik (2021), and subsequently in Rodrik and Stantcheva (2020 ; 2021).

References

Blanchard, Olivier, and Dani Rodrik (2021). “Introduction,” in Combatting Inequality: Rethinking Government’s Role. MIT Press.

Hacker, Jacob S. (2011). “The Institutional Foundations of Middle-Class Democracy.” Progressive Governance, 33–37.

Rodrik, Dani, and Charles Sabel (2019). “Building a Good Jobs Economy,” in Danielle Allen, Yochai Benkler, and Rebecca Henderson, eds., Political Economy and Justice, University of Chicago Press, forthcoming.

Rodrik, Dani and Stefanie Stantcheva (2020). “Economic Inequality and insecurity: Policies for an inclusive economy,” Report for the Blanchard-Tirole Commission.

Rodrik, Dani and Stefanie Stantcheva (2021). “Fixing Capitalism’s Good Jobs Problem,” in Oxford Review of Economic Policy special issue on Capitalism: What has gone Wrong, What needs to change, and How can it be Fixed?  edited by Paul Collier, Diane Coyle, Colin Mayer, and Martin Wolf, forthcoming.

Temin, Peter (2017). The Vanishing Middle Class: Prejudice and Power in a Dual Economy. Cambridge, MA: MIT Press.

Contact

Written by Dani Rodrik and Stefanie Stantcheva (with the assistance of Adrien Foucault). We thank Bluebery Planterose for research assistance.

• Rodrik: The Harvard Kennedy School, dani_rodrik@hks.harvard.edu
• Stantcheva: Harvard Department of Economics, sstantcheva@fas.harvard.edu
• Foucault: Harvard Business School afoucault@mba2021.hbs.edu

The post A Policy Matrix for Inclusive Prosperity appeared first on Economics for Inclusive Prosperity.

I attended grad school at Yale in the late 1960s, when the New Economic History was on the ascendancy.  Although the NEH was mainly in economics, the broader field of economic history clearly included members of both parent disciplines.  At Yale, history grad students like Jan de Vries and Fred Carstensen could do an economic history track by taking a few core econ courses.  There was also fair amount of common cause with a movement called the New Social History, interested in pursuing quantification to write “history from the bottom up.” Membership and presidents of the Economic History Association were about equally divided between the two disciplines.  When I started at Michigan in 1972, there were two card-carrying economic historians in the history department (Sylvia Thrupp and Jacob Price), and similar lineups were not unusual elsewhere.

The era of coexistence came to an abrupt end with the publication of Time on the Cross by Fogel and Engerman in 1974.  The book was controversial not just because of its claims about slavery in the United States — that slavery was efficient, productive, and not all bad for the slaves — but because these claims were presented as a summation of research by cliometric economic historians over the previous decade or more.  Even though some of the most robust critiques came from within economic history — consolidated in Reckoning with Slavery, published in 1976 — many historians felt that any discipline that could generate such an offensive brand of history did not deserve respectful intellectual status.

In truth, History was probably going its own way towards the “cultural turn” anyway.  To the extent that economic history had something to do with this move, it would have been a reaction to the observation that much of the new work seemed drawn moth-like to the discovery of markets and market processes in history, concluding that “markets worked.”  Bill Parker remarked on this tendency in his presidential address to the EHA: “From Old to New to Old in Economic History” (JEH 1971), describing the NEH as “a gigantic test of the hypothesis of economic rationality of a system and of the behavior of individuals within it.” Robert Lucas wrote: “The central lesson of research in economic history is that neoclassical economics applies anytime, anywhere.”  This now seems like something of a caricature, but for the NEH roughly through the 1970s, Lucas was largely correct.  A case in point that mattered to many historians was the agricultural regime of the postbellum South.  Works published in the 1970s by Joseph Reid, Stephen DeCanio and Robert Higgs all concluded that sharecropping was not an exploitive economic form, and that any racial oppression that did occur was rooted in politics rather than markets. Small wonder that historians found little to attract them to this style of research.

True, One Kind of Freedom by Roger Ransom and Richard Sutch (published 1977) was an important counterweight.  But although this book was a major contribution to cliometrics, its analytical foundation did not seem especially powerful: Territorial monopoly in the rural credit market, a condition that applied as much to white as to black small farmers.  The role of race in their account remained underdeveloped.

A strong reaction to this state of affairs occurred during the 1980s.  One landmark was a session at the 1984 AEA meetings organized by Bill Parker, resulting in a slim volume Economic History and the Modern Economist (1986).  Contributors made the case that economic history should be understood as a distinct approach to the study of economic life, not merely “applied economics with old data.” Using the QWERTY typewriter keyboard as central metaphor, Paul David advanced the view that some historical economic processes are governed by increasing returns and “path dependence,” whereby events of the remote past exercise continuing influence on the present.  Also, encouraged by a rejuvenated Douglass North, economic historians began to rediscover the importance of “institutions” as “carriers of history.”

As an illustration of the changing worldview of economic historians, consider this statement by Claudia Goldin – who began her career as a Chicago-school economic historian – in the introduction to her 1990 book on the gender gap: “I began this study more as an economist but have ended with a fuller appreciation of how the distant past affects the present, how norms and expectations impede change, how discrimination can survive even in highly competitive markets, and how slow genuine change can be.”  I began my JEL review of the book with this statement: “Economic history is in the midst of a quiet revolution.  Two decades ago, cliometricians were bent on showing that economic analysis could be applied even to the study of far-off times and places…More recently, economic historians have begun to take a more assertive posture towards the discipline, defending the distinctiveness of historical approaches and advocating the essentiality of history to comprehending modern issues.”

Were we perhaps engaged in self-deluding wishful thinking? Perhaps so, but there were others who also saw significant progress.  Consider this 2002 statement by Howell Harris, a British historian with a specialty in American business history: “The Journal [of Economic History]’s editors have made a successful effort to require contributors to write clearly and to explain themselves.  There is a wealth of readable, novel work on, for example, invention during the nineteenth century industrial revolution, labor market behavior in the late nineteenth and early twentieth centuries, racial and other discrimination in urban-industrial labor markets, and the economics of depression and recovery in the 1930s and 1940s, to which other industrial historians and even regular historians should pay attention.”  The new self-image of economic history is perhaps best illustrated by this remark from a referee’s report that came in when I was editor of the Journal of Economic History: “This paper may be good enough for the AER, but it does not meet the standards of the JEH.”

Despite these ostensibly successful gains in goals and aspirations, history and economic history today are more divided than ever. What went wrong? Looking back, I can now see that most of our attention was devoted to historicizing the discipline of economics, rather than making the field itself truly interdisciplinary. It is not that we have lapsed back into the rigid world of economic orthodoxy: Economics today is far more eclectic and philosophically diverse than in earlier times. Economic historians, and economists more generally, are quite comfortable framing their interpretations in terms of culture, institutions, or politics. However, any progress we may have made in making economic history more palatable to historians has been swamped by a deep change in prevailing methodology: the rise and entrenchment of “identification econometrics,” whereby every empirical study is seen as the challenge of extracting “causal” relationships between variables, by locating exogenous variation somewhere in history or in the economic system.  This approach has become all-pervasive in economics, including among economic history students.  Bob Margo has documented the trends in his article “The Integration of Economics and Economic History” (Cliometrica 2018), but they are obvious to the naked eye, to anyone who attends seminars or meets with grad students to discuss research plans.

In my view, this approach is extremely constraining as a one-size-fits-all way of writing economic history.  Whatever else one may say about it, the resulting publications are deadly from the standpoint of fostering interdisciplinary communication.  To be sure, the very best economic history studies do it all: meet the professional standards of applied economics while fleshing out the historical context and building a narrative.  But even when well done, the outputs rarely promote productive conversations with historians.  

What can be done? I have three recommendations:

1. Economic historians and historians should co-organize joint seminars;
2. Economic historians should be encouraged to publish in history journals; and
3. Historians and economic historians should collaborate in research. 

To be successful, any such ventures will have to entail true shared sponsorship, not just putting out a notice declaring that “our meetings are open to all.”  Perhaps future intellectual historians will report that today’s EFiP session was the beginning of a return to the reintegration of economic history and history.

The post The Divide between Economic History and History: From Ideology to Methodology appeared first on Economics for Inclusive Prosperity.

The continued rise of economic inequality in the U.S. has been on the radar of economists and policymakers for the last few years. New initiatives and platforms like EfIP (Economics for Inclusive Prosperity) have emerged, where economists work on creating fresh and useful policy ideas to promote more “inclusive” models of generating prosperity. Yet, students still face a lot of confusion, “noise,” and disagreement when it comes to the topic of inequality.^[1] Especially in the age of easy access to information online, students not fully literate in economics struggle to sift through the literature and separate rigorous scientifically based research from opinion pieces. This article discusses a way to introduce some recent trends in U.S. inequality to students, and then delve into a specific topic (e.g., racial inequality) in a two-lecture module at the end of an introductory economics course.

After all, it is not that the students are not interested in this topic. But, left alone, many of them become confused. Students do not make distinctions between different broad types of inequalities, such as income inequality, wealth inequality, or inequality of opportunity. They do not understand differences in the underlying causes of inequality, which vary depending on whether the topic is inequality across educational groups, gender-based groups, or racial/ethnic groups. And, they make basic mistakes in reading articles or viewing data, such as mixing-up correlation with causation or looking at graphs with different scales. Fortunately, introductory economics courses have a chance to reach students early in their careers, and correct many of these deficiencies.

Indeed, recent events in the US compel us to cover inequality and its consequences in our introductory classes. The economic impact of the COVID-19 epidemic falls significantly more on minorities, women, people with lower income levels and people of color.^[2] And, the disparities in poverty and opportunity rates between black and non-black populations is at the root of racial discrimination which re-ignited the BLM movement.^[3] Indeed, economic inequality is also related to other disciplines in Social Sciences, such as Sociology, Political Science and even Liberal Arts courses such as History and English. However, Economics faculty are well-equipped to cover the empirical outcomes and the underlying economic models – and lay out their strengths as well as short-comings.

Given that teaching about economic inequality is an important task, this article will first discuss when it makes sense to teach it. The article will then spend the majority of its time providing some tips for covering the material, as well as some suggested assignments.

When should we teach inequality?

Many of the introduction to economics courses are structurally very similar, focusing on delivering basic fundamentals and simple economic models with “representative agents.” With respect to inequality, a brief discussion often occurs at the beginning of the semester about the trade-off between efficiency and equity, and about how markets, left alone, deliver the most efficient outcome. The rest of the semester typically covers efficient economic models and the behavior of an average (representative) household or firm, without touching the relevant and important topic of income and wealth distribution and what happens to economic agents that are “not average.”

The lack of emphasis on inequality is partly due to the time constraint of the faculty who is trying to cover a very wide variety of topics (especially in introduction to economics courses where micro and macro are taught together in one semester) and partly due to how the course material has been written and structured. Recently, there have been open discussions between high profile economics faculty on how an introduction to economics course should be (re)structured.^[4]

The good news is that during most introductory courses, students learn many tools that can help them understand the basics of economic inequality. For example, if the supply and demand for labor was covered, then the idea of productivity differences driving wage differences can be understood. As can discrimination, when identically productive workers are treated differently. And, if the idea of capital versus labor have been covered, wealth versus income inequality can be touched on. None of these ideas can be covered in a tremendous amount of detail, but the bones exist for a discussion.

Thus, our proposal is to add a short two-lecture module to the end of every introduction to economics course to provide basic information about the level and consequences of economic inequality in the US. The next section focuses on ways in which we have accomplished that in our classes.

How should we teach inequality?

This section lays out some of the basic logistics of the module, before turning to the meat of what exactly to cover. We conclude the discussion with some ideas for short empirical projects that can help students get their hands into data.

i) The Logistics and Design of a Module

This module is designed to be delivered in two 45-50 minute lectures. The first lecture will focus on several broad facts that describe the economy over the last four decades, the second will yield more detail on one of these facts, as chosen by the instructor. The lectures will not be a replacement for more in-depth “economics of inequality” courses, but rather a “preview”. Students who want to learn more on this topic will be encouraged to take the corresponding elective course in their department to advance their knowledge in this field. The module will equip the students with the necessary tools to navigate through available information and current (elementary) research in the field.

The following are some of the essential design properties of the proposed module:

• The module needs to be elementary. Since it will be part of an introductory class, the faculty cannot assume prior economic knowledge beyond that covered in the class.
•  It needs to be data driven and based on sound economic research. Faculty will curate carefully selected, up-to-date research on the topic.
• It needs to be relevant to students.
• It needs to contain a hands-on component (we have suggested exercises below), exposing intro-level students to cutting edge, applied empirical research.

ii) The Structure and the Content of Teaching Material

One of the biggest problems faced by an instructor teaching about inequality is what to cover in the first place. Students will jump to different places on hearing the word inequality. Some might think immediately about CEO pay, others about racial or gender inequality, and others about issues related to the fact that high-income kids go to higher-quality schools. It can therefore be helpful to begin with a quick discussion of what students think of when they hear the word “inequality.”

This discussion can be followed by the introduction of the concepts of inequality in economic outcomes versus inequality in opportunity. The gender wage gap or the growth of the income share going to the top 1 percent represent inequality in economic outcomes. The fact that parental income is correlated with child’s income is an example of inequality in opportunity. By the last two lectures of your intro class, students will probably be better equipped to think about inequality in outcomes – but many students default to the issue of opportunity. The discussion can help tease this issue out.

The next challenge is to cover some of the major inequalities students will encounter in the outside world. We suggest that during the first class you can accomplish cover some of these through the presentation of “stylized facts” – facts about the economy that are not controversial, even though the underlying causes and solutions to the inequality might be. For data reasons, it is often easiest to focus on the period since the mid-1970s, and we usually focus on the U.S. Four facts on economic outcomes and one fact on opportunity can introduce students to a world of economic thought.

1. The median male worker has not seen any real wage growth since the mid-1970s, while workers slightly higher up in the distribution (e.g., the 80th percentile) have seen growth.^[5]
2. The median woman, working full-time and full-year, still only makes 80 percent as much as the median male, with little progress in the last two decades.^[6]
3. The median Black worker has seen no progress in terms of earnings relative to the median white worker since the 1970s.
4. Very high-earning workers (often defined as the top 1 percent) have seen a large growth in income, much more than those around the 80th percentile and much, much more than those at the median.
5. A strong correlation exists between parent’s income and child’s educational attainment and income.

These five facts can be displayed quickly during the first class of the module in just five slides if desired (we have provided example slides with some sources in the Appendix). However, preceding these slides with a few key pieces of information can provide context.

First, depending on the mathematical prerequisites of the class, it can be useful to proceed the discussion with some information on measuring inequality. A primer on percentiles at least can be useful.

Second, a discussion of economic data can be useful. Data on workers from the main part of the income distribution can often be obtained from household surveys (we used the Current Population Survey) and discussion of these sorts of sources can be informative. For example, the CPS is a household-level survey of addresses, and ignores institutional populations. This precludes the data from allowing an analysis of inequality in incarceration, and the data will understate inequality in employment, since those in prison by definition are not working.

On the other hand, data on the Top 1 percent often come from estimates based on national accounts (we used the World Inequality Database), and students should know why a household survey is insufficient. In particular, pointing out that these household surveys are statistically unlikely to capture very high earners, and in any case top-code data would be important. Finally,

data on economic mobility will likely come from Opportunity Insights, and a discussion of the administrative data they use can also be helpful. Again, we have included some example course material on each of these points. At the end of the first class, it can be useful to have students chime in on what they think might be driving the facts discussed, and if any of the facts were particularly surprising.

For the second lecture in this two-lecture series, we recommend focusing on a single one of the facts of the instructor’s choosing. Focusing on a single fact allows an important nuance of research on inequality to shine through — economists do not always agree on causes. Using the lecture to present a few cutting-edge explanations can be more fruitful than providing a little detail on each fact.

Turning to what to cover, we have recommendations based on experiences teaching a full course on the Economics of Inequality in the U.S.

1. Falling Median Earnings among Men — The most common explanations for the absence of earnings growth for middle-income men are: 1) technological change/automation; 2) trade; and 3) declining bargaining power. If students have been exposed to the model of supply and demand for labor, then technology can be framed as having two effects. First, it increased the productivity and thus demand for higher earners more than lower-earning workers (“skill bias”). Second, it has tended to substitute and thus reduce demand for middle-income workers specifically (polarization).  Case studies from Fernandez (2001) and Autor et al. (2002) can provide examples for class, and Autor and Dorn (2013) can yield some empirics on the effect of automation.  On trade, the effect can be summarized most easily as a decrease in demand for domestic middle- and low-income workers who are more prevalent among our trading partners. Empirical work from Autor, Dorn, and Hanson (2016) providing some useful evidence from trade with China.  Talking about bargaining power can be the hardest in an intro class.  However, pointing out that unions negotiate for higher wages and providing data on the union wage premium and trends in unionization can make the point.  Recent work by Farber et al. (2018) is especially useful.
2. Gender Wage Gap — When teaching about the gender wage gap, it can be useful to talk about two phases in time: 1) when it closed from 60 to 80 percent between the 1970s and 2000; and 2) the period since then, what the gap has been stuck at 80 percent. The closing of the gap was fueled mainly by increased education and work experience among women. The effect can broadly be framed as an increase in productivity due to “Human Capital”, or a boost in labor demand.  Providing data from the census on women’s education and labor force participation is useful.  Goldin and Katz (2002) on the Power of the Pill can help students see an interesting cause of educational change, and provides a nice way for them to think about how technology can alter the costs and benefits of education.  Greenwood, Sehardi, and Yorukoglu (2005) can give good insight on how technological change in the household allowed married women to work more.  Regarding the remaining gap, women’s responsibilities as caregivers are the most common Goldin (2014) attributes this to compensating differentials in a way that can be intuitive to students. And, using BLS data on the labor force participation of young mothers to young fathers can make it clear there is a work experience gap that develops around motherhood.
3. The Racial Wage Gap – Here, discrimination and the Human Capital gap are important topics to hit. In an introductory course, pointing out that discrimination occurs when workers are paid less than their marginal product is the natural point to start. Empirically, this definition means workers with similar productive characteristics in similar jobs should get paid the same amount regardless of race. Covering a few studies can be helpful to show the existence of discrimination, but also the trouble economists go through to identify it. Bertrand and Mullainathan (2004) is a classic experimental example, and Fryer, Pager, and Spenkuch (2011) a nice regression example. Turning to the Human Capital gap, using Census Data to show racial graduation rates and the difference in earnings between graduates and non-graduates is a good place to start. The discussion can then be extended to get into some of the underlying reasons for the Human Capital Gap. A common focus point might be ability to pay as captured by loan inequality, and Scott-Clayton and Li (2016) have some interesting data. Housing discrimination, residential segregation, and school quality could involve a more detailed discussion. A recent Newsday study out of Long Island by Choi et al. (2019) provides recent examples of housing discrimination and the resulting exclusion out of neighborhoods that might have higher quality schools.
4. The Rise of the Very Rich – When discussing the rise of incomes for the top 1 percent, a key distinction to have your students make is between labor and capital income.  As Piketty, Saez, and Zucman (2019) point out, the rise in top income over the last several decades has been driven by both income sources, albeit at different times.  Through the 1990s, it was mostly growth in labor income. The underlying causes of growth in labor income are not fully understood, so we usually give two examples of causes. One is so-called “Superstar Theory,” namely that technology allows people with marginally higher productivity to capture larger shares of markets than in the past. Gabaix and Landier (2008) provide a nice discussion in the context of CEO pay.  The other is a potential failure of corporate governance, which has led to rising executive salaries often paid in the form of equity. More recently, Piketty, Saez, and Zucman point out that capital income growth has taken over.  Here, one main point worth making is that capital is extremely concentrated, and has become even more so, as in Saez and Zucman (2016). If you have time, highlighting the growth in the capital share that may occur as a result of slowing growth in developed countries — as highlighted in Piketty’s Capital — can give students a sense of the potential for future growth in inequality.
5. Opportunity – If focusing on inequality of opportunity, the first thing you want to establish is a definition of what equality of opportunity would look like. Having a discussion about what is within a person’s control and what is outside of it is key. In the opportunity literature, what is within control is often referred to as “effort” and outside of it “circumstances” (see Roemer and Trannoy, 2016). Discussing with students the kind of things they think of as circumstances is important, as is discussing the extent to which “effort” is really within someone’s control. For example, low-income kids tend to put less time into schoolwork, but more time into paid work (e.g., see Porterfield and Winkler, 2007). Would we say they are exerting less effort towards school work when their time must be split? Students will see that it’s complicated. In the end, when we say we want equal opportunity, we usually mean that circumstances do not dictate economic outcomes. So, parents’ income should not affect a child’s propensity to go to college or their income as an adult. Once these definitions are laid out, using data from OpportunityInsights.org can be used to illustrate the lack of Equality of Opportunity within the U.S. We have provided an example module in the Appendix, courtesy of the researchers at Opportunity Insights.

iii) Examples of Empirical Research Projects

The assignments below are designed to accomplish two things. First, they all expose students to newspaper articles, think tank pieces, and perhaps some academic writing on the topic. Second, they force students to work with data, and produce a visualization to make their arguments. Below, we lay out one assignment for each of the four facts on economic outcomes from the first lecture. We recommend picking the fact you focus on from the second lecture. If you focus on opportunity, we have included an assignment from Opportunity Insights in the Appendix.

Example Assignment: Occupational Wage Growth

• To the Instructor: This assignment gives the students a chance to see the effects of Skill-biased Technological Change and/or Polarization first hand. The goal of the assignment is to have the students identify one occupation that has been negatively impacted by automation, and one that has benefited from technology.  In completing the assignment, the student will be exposed to articles on economics, and will practice displaying data visually.
• Example Assignment Prompt: As we learned in class, median incomes for full-time workers have been stagnant over the last several decades, but at higher points in the distribution they have risen. Two related explanations put forward by economists to explain this phenomenon are Skill-biased Technological Change and Polarization. In this short-paper assignment, your goal is to find evidence of: 1) a middle-income occupation where automation has tended to replace workers (Polarization); and 2) a higher-income occupation where technology may make workers more productive.
• Example Assignment Details: The paper should include at most 2 pages of text 1.5 spaced, as well as one data-based figure.  As evidence for the two occupations you choose, you should one high-quality source each (i.e., two sources total).  These sources can include government websites, academic papers, or policy briefs from non-partisan think tanks (e.g, The Pew Charitable Trusts, The Brookings Institute).  The figure should show the trajectory of median earnings within the occupation over the last several decades, to see if the damaging or improving aspect of technology argued in your sources play out in the data (it is fine if they do not, although you may want to hypothesize as to why).  The figures do not count against the page limit, and should include clearly marked labels on the axes, a legend if necessary, and a clear title.

Example Assignment: The Gender Wage Gap…Closing then Stalling

• To the Instructor: The goal of this assignment is to expose students to economic articles and data, and familiarize them with constructing data visualizations in the context of the gender wage gap.  In general, students will likely find that the closing of the gender gap during the 1970s, 1980s, and 1990s was driven by increased education, increased work experience, and/or a decline in occupational segregation.  Explanations for the remaining gap often center on child care responsibilities (either by reducing work experience or by introducing a compensating differential for flexibility) or on outright discrimination.
• Example Assignment Prompt: Even today, the typical woman working full time makes about 80 cents for every dollar made by a full-time working man.  However, this gap was larger in the past.  In 1975, the median full-time working woman made about 58 cents for every dollar a man made.  In this short paper assignment, your goal is to offer: 1) an explanation as to why women have partially caught up to men; and 2) an explanation as to why women’s income still lags behind men’s. You should make an effort to tie your explanations to concepts learned during the semester.
• Example Assignment Details: The paper should include at most 2 pages of text 1.5 spaced, as well as two data-based figures, one for each argument.  To support your arguments and provide data, you need at least two high-quality sources.  These sources can include government websites, academic papers, or policy briefs from non-partisan think tanks (e.g, The Pew Charitable Trusts, The Brookings Institute).  The figures should augment the argument being made and can be drawn solely from the two sources required or from additional sources.  For example, if you are arguing women make more because they enter high-paying STEM fields at a higher rate today than in the past, your figure might show the share of men and women majoring in STEM majors over time.  The figures do not count against the page limit, and should include clearly marked labels on the axes, a legend if necessary, and a clear title.

Example Assignment: Identifying Discrimination

• To the Instructor: The goal of this assignment is to expose students to the definition of discrimination, and to how researchers go about identifying it. Students will be asked to find an article from a government source, think-tank, or academic journal on discrimination. They will then be asked to determine how the authors determined some effect (often lower income, but possibly something else like housing inequities) was discrimination. The assignment also allows the students to construct a data visualization.
• Example Assignment Prompt: Discrimination occurs when two people of nearly identical characteristics receive differential because of some group characteristic (e.g., race).  For example, a Black person with the same productive characteristics may be paid less than a similar white person. Identifying discrimination is difficult, because it requires comparing two otherwise similar individuals. Find a high-quality source purporting to identify discrimination, discuss how the authors attempted to identify, and argue whether or not you think they did a good job.
• Example Assignment Details: The paper should include at most 2 pages of text 1.5 spaced, as well as one data-based figure illustrating the nature of the discrimination.  Your source can include government websites, academic papers, or policy briefs from non-partisan think tanks (e.g, The Pew Charitable Trusts, The Brookings Institute).  The figure does not count against the page limit.

Example Assignment: The top 1% income inequality

• To the Instructor: The goal of this assignment is to expose students to economic articles and data, and familiarize them with constructing data visualizations in the context of income inequality at the top 1% level. The top 1% of American earners have nearly doubled their share of the national income since the 1970s, according to Saez’s analysis. Americans in the top 1 % average over 39 times more income than the bottom 90% and 85 times as much as the bottom 20% (CBO data). Even the after-tax income of the top 1% has been growing much faster than the rest, making this enormous gap even bigger.
• Example Assignment Prompt: There is a significant gap between the incomes of the top 1% and the median income of the American population. This discrepancy is also present, in varying degrees, across the US. This assignment will compare the income of a top 1% earner in your own county with the income of a median earner in your home county (or, if from abroad the county where your college sits). In this short paper assignment, you should: 1) determine the income gap between the 1-percent income in your county and the median; 2) determine how the median differs by race and gender within your county; 3) determine how a 1 percenter would need to spend their money in a day so that they did not accumulate any additional wealth (see DeLong (2019) for example); 4) determine how many minimum wage workers it would take in your county to hit the 1 percent income; and 5) analyze and critique a policy platform that attempts to address this sort of inequality.
• Assignment Details: The paper should include at most 2 pages of text 1.5 spaced.  You should also construct a data-based figure comparing income for the 1 percent in your county to the median Black female, white female, Black male, and white male.  The figures do not count against the page limit, and should include clearly marked labels on the axes, a legend if necessary, and a clear title. For this assignment you will need utilize the following data sources:
  1. Economic Policy Institute
  2. Opportunity Atlas
  3. Economic Policy Institute – Minimum Wage Tracker

Conclusion

Teaching about inequality in an introductory course is both imperative and difficult. We believe by focusing first on some agreed upon facts, and then focusing in on one of those facts you can achieve two goals. First, you can give your students some experience with data on inequality, and exposure to some statistics in a controlled environment. They may not agree on whether or not inequality is a problem, or what to do about it, but they will at least know the relevant trends and the current state of the world. Perhaps more importantly, you can show them how economics can help them think about one particular source of inequality. Hopefully the second lecture can push some students to think about economic policy options and how economics can be used for inclusive prosperity.

Endnotes

^[1] Disagreements stem from disagreements over trends in inequality to whether or not inequality should be a focus of discussion. For example, see articles by Piketty, Chancel, Alvaredo, Saez, Zucman (2019), Henderson (2020), Bershidsky (2020), or Gramm and Early (2019). We even had a student e-mailing me a link to a YouTube video of Milton Friedman from 1979 as a
counterpoint, without really understanding the point being made.
^[2] See Kapadia (2020), Sanzenbacher (2020), and Fisher and Bubola (2020) for some analyses that illustrate these points.
^[3] Chetty, Raj, Nathaniel Hendren, Maggie R. Jones, and Sonya Porter (2020).
^[4] Matthews (2019) – The radical plan to change how Harvard teaches economics
^[5] One note: keeping the fact simple and focusing on males eliminates many other moving parts, and highlights the deteriorating position of workers who have not seen many other fundamental changes (unlike women, who achieved higher levels of
education and work experience over this time period).
^[6] Again, focusing on those working full-time and full-year eliminates the moving part of growing hours.

Selected Resources, Readings and Data Sources to Build Your Own Module

There are many other excellent, publicly available sources for faculty to utilize when they are building their own modules. Some of the ones below may be helpful as readings an assignment to students. These are selected with considering that the students are in an introductory class and don’t have much prior background in economics. We found them to be accessible, insightful and useful for a module like the one proposal in our policy brief.

See the appendix of the attached PDF for an example of how such a module can be successfully integrated into a large introduction to economics course. The complete set of course material can be found here.

1. CORE-US – Chapter 19 – Economic Inequality This is an excellent source for anybody who wants to cover economic inequality in an introduction to economics course. It provides many teaching tools and also addresses difficult questions like “what (if anything) is wrong with inequality?” and “how much inequality is too much (or too little)?” – these are questions most of the introduction students are struggling with. Economic analyzes as well as empirical data are utilized to answer each question.
2. Economic Policy Institute
3. Washington Center for Equitable Growth
4. https://inequality.org
5. Combating Inequality: Rethinking Policies to Reduce Inequality in Advanced Economies, Peterson Institute for International Economics Webcast, 2019
6. How economic inequality harms societies, TED talk by Richard Wilkinson, 2011
7. The Triumph of Injustice, by Gabriel Zucman, March 20^th, 2020, Social Europe, podcast
8. Tackling Inequality from the Middle, Dani Rodrik, Project Syndicate, 2019
9. Why some countries grew rich, Suresh Naidu, 2015
10. Good and Bad Inequality, Dani Rodrik, Project Syndicate, 2014
11. The Inequality Trust
12. The Spirit Level: Why More Equal Societies Almost Always Do Better, Kate Pickett and Richard Wilkinson, 2009 – Powerpoint slides
13. Suresh Naidu on Capitalism, Monopsony, and Inequality, MindScape Podcast, 2020
14. Should we worry about income gaps within or between countries?, Dani Rodrik, Social Europe, 2019
15. The New Economics: Data, Inequality and Politics, 2019, John Cassidy, The New Yorker
16. Inequality is
17. https://www.millionairesforhumanity.com
18. How Pandemics Leave the Poor Even Farther Behind, IMF Blog, 2020
19. https://www.project-syndicate.org/commentary/inequality-data-and-denialism-by-facundo-alvaredo-et-al-2019-12?barrier=accesspaylog
20. https://reason.com/2020/01/25/the-truth-about-income-inequality/
21. https://www.bloomberg.com/opinion/articles/2020-01-07/economists-debating-piketty-care-too-much-about-inequality
22. https://www.wsj.com/articles/the-truth-about-income-inequality-11572813786
23. https://www.barrons.com/articles/the-pandemic-is-weakening-americans-retirement-security-51588086298
24. https://progressless.org/2020/05/21/the-covid-19-recession-versus-the-great-recession-in-one-chart/

The post Why, When, and How to Teach the Fundamentals of Inequality in Principles appeared first on Economics for Inclusive Prosperity.

Contemporary racial inequality can be thought of as the product of a long historical process with at least two reinforcing sets of policies. The first would be policies governing the spatial distribution of the black population. The second would be policies that had a disparate impact on black individuals because of their locations. Understanding current black-white gaps in income, wealth and education require understanding the complex relationship between regional inequality, race and policies at the local, state, and national levels. In this article, we outline the ways that the spatial distribution of the black population has evolved over time and the ways that spatial distribution has interacted with policy to, at times, reduce and exacerbate levels of inequality. Recognizing the ways that past policies explicitly stymied black economic mobility and how current policies have explicitly or inadvertently done the same provides a basis for understanding how to craft future policies to reduce racial inequalities. Furthermore, recognizing the interconnection of discrimination and the spatial distribution of the black population is important for understanding certain components of regional and spatial inequality.

The difference in location within regions makes it inevitable that policies that differentially affect urban and rural areas will have disparate effects by race. A recent example of this is the proposed Medicaid work requirement in Michigan. The original version of Michigan Senate Bill 897 exempted individuals from this work requirement conditional on residing in a county with an unemployment rate above 8.5 percent. The spatial distribution of the white and black populations of Michigan meant that this exemption would have racially disparate impacts; given that poor white individuals disproportionately live in rural areas and black individuals live in urban areas, the higher unemployment rates in rural counties would disproportionately exempt white Medicaid recipients from the work requirement within the bill.

Although—after considerable negative press—the exemption was dropped from the final version of the work requirement bill, this incident reveals the complex interplay between policy, inequality across space, and inequality between races. Even if a policy like the unemployment rate exemption in the Michigan bill is crafted without discriminatory intent, it can nonetheless increase racial inequality. In the following sections we explore the how policy has shaped the geographic and economic mobility of the black population over the past century and a half, drawing from the large literatures on regional inequality and racial discrimination that have all too often been treated in isolation from one another.

Historical Roots

With the abolition of slavery in 1865, the Civil War marked an end to the starkest form of institutionalized discrimination but left a black population that, while free from legal bondage, faced considerable economic hardship. Immediately after emancipation, the black population found itself disadvantaged both by general regional inequality and by racial discrimination. The geographic distribution of slavery and constraints on the mobility of free blacks in the antebellum period resulted in large concentrations of the black population in the cotton-growing regions of the South at the time of emancipation, an area that corresponds quite closely to the areas with high black population shares today. By 1880, 90 percent of the black population still lived in the South and 87 percent of the black population lived in a rural area. In contrast, only 24 percent of the white population lived in the South, and 72 percent of the white population lived in rural areas. This meant that black individuals were disproportionately affected by constraints on economic opportunity in the rural South. Over the second half of the nineteenth century, Southern and Northern incomes diverged significantly, with average income in the South only half of the national average by 1900 (see Margo and Kim (2004) for extensive discussion of historical trends in regional income patterns). The destruction of the Civil War and the emergence of Northern manufacturing while the Southern economy remained predominantly agricultural contributed to these trends.

Even more, policies which could address racial inequality were never realized. While Southern whites had been able to avail themselves to land via Land Acts, public land sales, and lotteries for land ceded by treaty with Native American tribes, African Americans had no share in this wealth redistribution. Black politicians in Reconstruction attempted to use tax policy to redistribute wealth (Logan 2018), where land which was currently held in inventory would be taxed to encourage land sales. This policy did not result in land redistribution, however, even for land which was seized by the state for non-payment of property taxes (Foner 1988). The end of Reconstruction also signaled the end of black political participation in the South, and the resulting laws on labor mobility, wages, and worker’s rights were configured in non-democratic processes.

Beyond this, education in the South was segregated and, after Reconstruction, differentially funded (Logan 2018). This left the majority of the black population in the US in schools which were underfunded in two relative terms. First, Southern schools were underfunded overall relative to school expenditures nationwide. Second, black funding dramatically trailed white funding within the South. This left blacks in the South in the last- last place when it came to investments in human capital.

The black population therefore found itself in a region with far less economic opportunity than the rest of the nation. More importantly, that economic opportunity was further restricted by individual and institutionalized racism and political disenfranchisement. Discrimination in hiring by employers and intimidation of black workers through violence placed black workers at a direct disadvantage in the labor market.

Discrimination

Discriminatory practices negatively affecting economic outcomes were not limited to the South when consumer-side discrimination began to increase in tandem with Jim Crow laws. African American inventors (Cook 2010; 2012; 2014, Fouché, 2005) found it harder to practice invention and to commercialize their inventions (Cook 2011, 2012). From newspapers (Cook 2014) to photographers to furniture makers (Kusmer 1976) African American entrepreneurs lost their businesses and could not grow due to constraints imposed by redlining and other practices of the local, state, and federal government (Baradaran 2017). Athletes from golfers (Dawkins 1996) to baseball players (JBHE 2001, Mackenna 2011) to jockeys (Leeds and Rockoff 2017) were barred from participating in the organized sports in which they were trained and participated.

This discrimination can be seen at its worst in the relationship between lynchings, or extralegal killings, and economic conditions. Until 1905, this type of mob violence against Southern blacks was higher when the price of cotton was declining and inflationary pressures were rising, making the economic conditions of white agricultural workers more precarious (Beck and Tolnay 1990). This violence also extended to attacks on economically successful black communities. The most infamous case was the destruction of the Greenwood community, “Black Wall Street,” during the Tulsa race riot in 1921. However, violence against African Americans that resulted in devalued or confiscated property and, in some cases, precipitated migration was commonplace and widespread. “Whitecapping” was the lawless practice of confiscating land that resulted in many African Americans losing their land (Holmes 1980, Whayne 1996, and Winbush 2003). Similarly, sundown towns were found all over the country and were the outcome when black families were given two days or so to leave town or be killed (Loewen 2005, Jaspin 2007).

Beyond labor markets, blacks also faced discrimination in credit markets, for example the discrimination in merchant credit documented by Olney (1998). Insurers and mortgage lenders refused to underwrite African American households and entrepreneurs (Baradaran 2017). The inability to acquire property and business loans is currently at the root of the racial wealth gap. (See Dymski 2006 for a general overview of the theory and empirical evidence for racial discrimination in credit and housing markets).

Compounding this discrimination by individuals was the state-sanctioned segregation brought about through Jim Crow laws. Approximately 290 laws imposing segregation primarily in education, voting, and public accommodations, were promulgated by states between 1870 and 1940. Most were passed in the South prior to 1900 and outside the South after 1900 (Cook 2014). This segregation impacted every aspect of life. Most directly related to black economic opportunity is the impact of Jim Crow on education. Segregated schools led to inferior educational opportunities for black children relative to white children, with black schools and teachers routinely underfunded relative to white schools (Baker 2017; Card and Krueger 1992; Carruthers and Wanamaker 2013; Margo 1982). With segregated schools, hospitals, libraries, and other facilities, black individuals living in the same cities and towns as white individuals had access to far fewer resources.

Jim Crow laws devastated existing economic and social ties that crossed racial lines. Social networks related to invention, which were critical for bringing inventions to market (Thomson 2010), were severed during this period, and African Americans bore the brunt of this cost (Cook 2010, 2011, 2014). Even African American “great inventors,” such as Lewis Latimer, Garrett Morgan, and Granville T. Woods, and were subjected to this disruption in innovative activities due to a disruption in social ties (Cook 2010, 2011, 2012). During the age of Jim Crow, black inventors were not able to fully participate in fairs – confined to “Negro days” or “Negro buildings” – where much information was exchanged and many social and financial ties relevant for invention were made.

Part of what enabled this discrimination in economic and social spheres of life were discriminatory restrictions on the right to vote, making the United States a very limited democracy until the 1960s. Despite large black populations in the South at the start of the 20th century, that population had no political power due to disenfranchisement and voter intimidation. Without the power of the ballot box, black Southerners remained subjected to overtly racist policies constraining their economic opportunities.

Racial Wealth Inequality

These issues carry over to this day, where blacks have the most tenuous connection with wealth. While blacks did make gains in wealth acquisition after chattel slavery was ended, the pace was slow and started from a base of essentially nothing. The gains that were made took place in a system that was politically rigged, and where whites could use violence to force blacks from their property via the terrorism of whitecapping – including the race riots as in Memphis in 1866 and Tulsa in 1921, which systematically destroyed or stole the wealth blacks had acquired, and lowered the rate of black innovation.  It is not surprising that 1899 remains to date the year of the highest per capita patenting activity by African Americans (Cook 2014). Black wealth was tenuous without the rule of law to prevent unlawful seizures. Even so, by 1915 black property owners in the South had less than one tenth of the wealth of white landowners (Margo 1984, Higgs 1982). If one factors in the relative lack of black landownership more generally, the ratio quickly declines significantly. If anything, this trend remained stable for the next fifty years. In 1965, one hundred years after Emancipation, blacks were more than 10% of the population but held less than 2% of the wealth in the United States, and less than 0.1% of the wealth in stocks (Browne 1974). Black wealth had remained fundamentally unchanged and structurally out of reach of the vast majority of blacks.

Aided by a complicit Federal Housing Administration (FHA), the use of restrictive covenants, redlining, and general housing and lending discrimination extended these racially exclusionary and wealth extracting structures well into the 20th Century. Moreover, blacks were largely excluded from the New Deal and World War II public policies, which were responsible for the asset creation of an American middle class. Even with efforts designed to mitigate the consequences of these policies, such as the building of the model city Soul City, NC, promising efforts which attracted blacks from poor and segregated urban areas in the North, were thwarted by segregationists like Senator Jesse Helms before take-off. In addition to housing, the professional and management class that the GI Bill generated is one example of several postwar policies in which the federal government invested heavily in the greatest growth of a white asset- based American middle class, at the exclusion of blacks. While the GI bill did result in educational advances, most American colleges and universities were closed to blacks, or open to only but a few in token numbers. This, along with a racist distribution of GI benefits towards whites coupled with a truncated housing supply resulting from a Jim Crow segregated South that limited the ability of Historically Black Colleges and Universities (HBCUs) to accommodate the education and housing needs of black veterans.

When blacks did move North the circumstances of the escape from the South have been revised. While blacks migrating North did do better than blacks who remained in terms of wages, their relative position actually declined. Indeed, new research shows that black migratory patterns were well correlated with increased expenditures on law enforcement (Derenencourt 2018), which points to mass incarceration as one mechanism which explains the large and negative mobility of black males in particular. In both cases, policies in both regions uniquely target blacks and inhibit their economic opportunities.

Another dimension of racial wealth inequality appears in the innovation economy. Cook and Kongcharoen (2010) and Cook (2019) show that, despite advances in education and training in the innovation economy, there are not commensurate increases in participation at the stage of wealth accumulation – commercialization and entrepreneurship. Less than one percent of founders receiving venture capital funding for their startups are African American. Although entrepreneurship remains a traditional pathway to the middle class and wealth accumulation in the U.S., the ratio of white entrepreneurs to Black entrepreneurs remains 50:1. And African Americans are largely missing from the initial public offerings of tech firms and other firms in the innovation economy.

The racial gaps that we see today are not a function of black underinvestment in education, cultural or genetic deficits among blacks, nor unobserved societal factors. They are the product of historical processes and policies, many of them regionally specific to the places that African Americans live, which create not limit opportunities for blacks but which also created opportunities for whites.

Policies

The three dimensions of racial inequality above: segregation, discrimination, and wealth inequality are intertwined in complicated ways, and making progress on eliminating them will require both political and cultural changes, as well as policies. We outline a few here:

1. Desegregating housing and schools. America remains starkly segregated despite the progress of the Civil Rights movement. Much of this segregation occurs via private markets in housing and schooling, where richer, white families sort into high priced neighborhoods with good schools (or private schools). This results in Black Americans being in poorer school districts, in lower-housing-value, high-crime, neighborhoods, and generally cut-off from the spatial privileges and local public goods accessible to white Americans.
2. Anti-discrimination policies, particularly around criminal justice. There is an important role for representation and other policies to combat racial stereotypes and other forms of racism. There is also an important role for transforming organizational cultures and institutions that reproduce white supremacy. The expansion of police in Northern cities after the 1960s also solidified racially unequal treatment into a large number of police departments and police practices. Active anti-discrimination policies and policies and practices that address workplace climate should also be extended to and enforced in every sector of the economy, but particularly the innovation economy, where wealth has become increasingly concentrated in the U.S.
3. Redistribution and reparations. Finally, there has been a longstanding debate in the United States about reparations and race-specific redistribution. Darity and Mullen estimate the bill to be between 14 and 18 trillion dollars, and redistribution of this amount of wealth from whites to blacks would almost completely erase the black white wealth gap. Exactly what form this redistribution would take, along with determining eligibility for reparations remains actively debated.

References

Baker, Richard B. “School Resources and Labor Market Outcomes: Evidence from Early Twentieth-Century Georgia.” Economics of Education Review 70 (2019): 35-47.

Baradaran, Mehrsa. The Color of Money: Black Banks and the Racial Wealth Gap. Harvard University Press, 2017.

Browne, Robert S. “Economics and the Black Community in America.” The Review of Black Political Economy 5.3 (1975): 302-313.

Card, David, and Alan B. Krueger. “School Quality and Black-White Relative Earnings: A Direct Assessment.” The Quarterly Journal of Economics 107.1 (1992): 151-200.

Carruthers, Celeste K., and Marianne H. Wanamaker. “Separate and Unequal in the Labor Market: Human Capital and the Jim Crow Wage Gap.” Journal of Labor Economics 35.3 (2017): 655-696.

Cook, Lisa D. “Inventing Social Capital: Evidence from African American Inventors, 1843–1930.” Explorations in Economic History 48.4 (2011): 507-518.

Cook, Lisa D. “Converging to a National Lynching Database: Recent Developments and the Way Forward.” Historical Methods: A Journal of Quantitative and Interdisciplinary History 45.2 (2012): 55-63.

Cook, Lisa D. “Violence and Economic Activity: Evidence from African American Patents, 1870–1940.” Journal of Economic Growth 19.2 (2014): 221-257.

Cook, Lisa D., and Chaleampong Kongcharoen. “The Idea Gap in Pink and Black.” No. w16331. National Bureau of Economic Research, 2010.

Darity Jr, William A., and A. Kirsten Mullen. From Here to Equality: Reparations for Black Americans in the Twenty-First Century. UNC Press Books, 2020.

Dawkins, Marvin P. “African American Golfers in the Age of Jim Crow.” The Western Journal of Black Studies 20.1 (1996): 39.

Derenoncourt, Ellora. “Can you Move to Opportunity? Evidence from the Great Migration.” [Job Market Paper] (2019).

Dymski, Gary A. “Discrimination in the Credit and Housing Markets: Findings and Challenges.” Handbook on the Economics of Discrimination 215 (2006): 220.

Foner, Eric. Reconstruction. New York: Harper & Row, 1988.

Fouché, Rayvon. Black Inventors in the Age of Segregation: Granville T. Woods, Lewis H. Latimer, and Shelby J. Davidson. JHU Press, 2003.

Holmes, William F. “Whitecapping in Georgia: Carroll and Houston Counties, 1893.” The Georgia Historical Quarterly 64.4 (1980): 388-404.

Higgs, Robert. “Accumulation of Property by Southern Blacks Before World War I.” The American Economic Review 72.4 (1982): 725-737.

Jaspin, Elliot. Buried in the Bitter Waters: The Hidden History of Racial Cleansing in America. Basic Books, 2008.

Kim, Sukkoo, and Robert A. Margo. “Historical Perspectives on US Economic Geography.” Handbook of Regional and Urban Economics. Vol. 4. Elsevier, 2004. 2981-3019.

Kusmer, Kenneth L. A Ghetto Takes Shape: Black Cleveland, 1870-1930. Vol. 82. University of Illinois Press, 1976.

Logan, Trevon D. “Do Black Politicians Matter?” No. w24190. National Bureau of Economic Research, 2018.

Loewen, James W. “Sundown Towns: A Hidden Dimension of Racism in America.” (2005).

Leeds, Michael, and Hugh Rockoff. “Beating the Odds: Black Jockeys in the Kentucky Derby, 1870-1911.” Historical Perspectives on Sports Economics. Edward Elgar Publishing, 2019.

Margo, Robert A. “Race Differences in Public School Expenditures: Disfranchisement and School Finance in Louisiana, 1890-1910.” Social Science History 6.1 (1982): 9-33.

Margo, RA “Accumulation of Property By Southern Blacks Before World War One: Comment and Further Evidence,” American Economic Review 74 (September 1984): 768-776.

McKenna, Brian. “Alex Pompez: From the Rackets to Respectability. A Hall of Fame Scout.” Can He Play? A Look at Baseball Scouts and Their Profession (2011).

Olney, Martha L. “When your Word is not Enough: Race, Collateral, and Household Credit.” Journal of Economic History (1998): 408-431.

Thomson, Ross. “The Continuity of Innovation: The Civil War Experience.” Enterprise & Society 11.1 (2010): 128-165.

Tolnay, Stewart Emory, and Elwood M. Beck. A Festival of Violence: An Analysis of Southern Lynchings, 1882-1930. University of Illinois Press, 1995.

Winbush, Raymond. “The Earth Moved: Stealing Black Land in the United States.” Should America Pay? Slavery and the Raging Debate on Reparations (2003): 46-56.

Whayne, Jeannie M. A New Plantation South: Land, Labor, and Federal Favor in Twentieth-Century Arkansas. University of Virginia Press, 1996.

The post Racial Inequality appeared first on Economics for Inclusive Prosperity.

If there is one common lesson argued by most environmental economists today regarding the design of environmental policy, it is: the best way to correct the market failure caused by pollution is Pigouvian pricing.  According to this argument, a price should be levied on pollution equal to the value of the damages it causes to society.  The price can be directly applied via a pollution tax, or indirectly via a cap-and-trade system where the permit price becomes the Pigouvian price on pollution.  If the price is correct, then the most efficient outcome will be realized, and it will be achieved at the lowest possible cost to society.  A corollary is that environmental policies other than price policies, for example technology mandates or performance standards (what economists often call “command-and-control” policies), are inferior and should not be used.

This standard economic justification of pollution pricing is exemplified by the “Economists’ Statement on Carbon Dividends,” an open appeal drafted by the Climate Leadership Council and signed by more than 3,500 economists (this author included).  This letter argues for a tax on carbon dioxide, the pollutant most responsible for climate change.  “A carbon tax offers the most cost-effective lever to reduce carbon emissions at the scale and speed that is necessary. By correcting a well-known market failure, a carbon tax will send a powerful price signal that harnesses the invisible hand of the marketplace to steer economic actors towards a low-carbon future.” (Economists’ Statement on Carbon Dividends 2020).  The argument is also nicely summarized in David Klenert and Linus Mattauch’s Economists for Inclusive Prosperity policy brief on carbon pricing: “The intuition behind pricing greenhouse gas emissions is straightforward: since the real cost to society is not reflected in market prices, emissions are too cheap and too much greenhouse gas is emitted. Setting a price on emissions that corrects for this increases the price of carbon-intensive production and carbon-intensive consumption goods.” (Klenert and Mattauch 2019).

The 100-year-old Pigouvian justification for pollution pricing is compelling.  But, there are other compelling issues in the real world that complicate Pigou’s straightforward and intuitive justification.  In this policy brief, I argue that these other issues provide strong justification for pursuing policies other than pollution pricing.  This does not mean that pollution pricing is bad or that we should discontinue it where it exists and is working.  Rather, non-price policies, which economists often argue against, should be pursued as well, and may in fact be preferable to pricing.  I begin by briefly summarizing the standard justification for pollution pricing in the next section.   Then, I describe three sets of issues that weaken the case for price-based policies.  First, political constraints make efficient pollution pricing difficult to implement, at least in the near term.  Second, caring about equity or distributional outcomes may lead one to prefer alternatives to price-based policies.  Third, other characteristics of the world, including other market failures and behavioral anomalies, can make alternative policies more efficient than pollution pricing.    Because of these concerns, non-price-based policies, like command-and-control performance standards or technology mandates, are more appropriate.  These policies ought to be considered alongside price-based policies, and perhaps even ought to be preferred to price-based policies.

The Standard Justification for Pollution Pricing

Pollution is a textbook example (literally) of a negative externality – a cost to society of an economic exchange that neither the buyer nor the seller takes into account.  An unregulated market for a good or service with a negative externality attached to it will result in an over-supply of that good or service relative to the efficient level.

The solution offered by Pigou is intuitive: because the costs of the negative externality are not borne by participants in the market, make them bear those costs by putting a price on the externality.  This intuition explains why pricing of externalities is often called “internalizing” the externality.[1]  Pigou’s analysis is not primarily about pollution; pollution is just one example of a negative externality. He discusses at length other sources for the divergence of private and social incentives, including tenancy issues that give rise to principal-agent-type problems.  Only in one sentence does he directly address problems of pollution.[2]

The standard justification of pollution pricing is pervasive throughout much of the policy writing done by environmental economists.  The Environmental Protection Agency has a website that expounds the benefits of pollution pricing over command-and-control policies (EPA 2020). Alternative policies like command-and-control standards or mandates are often argued against, because they fail to live up to the ideal of the externality tax.

The advantage of pricing is more limited in scope than is sometimes acknowledged.  An important distinction arises between efficiency and cost-effectiveness.  The theory claims that a price will yield the efficient level of the negative externality, where the total economic well-being of society is maximized, only when the price equals the marginal external damages so that those negative externalities are fully internalized.[3]  If the tax is not set at the efficient level, then the efficient level of pollution will not be realized.  However, even without achieving the efficient level of pollution, a price on pollution will theoretically achieve a given level of pollution at its lowest possible cost. This is called cost-effectiveness.  According to theory, achieving 1 million tons of reduction in carbon through a command-and-control policy like a technology mandate will be costlier than achieving the same 1 million tons of reduction through a carbon price.[4]

Cost-effectiveness and efficiency are important goals, but they are not the only goals that environmental policy should seek to attain.  Another important goal is equity, or fairness in the distribution of the costs and benefits of policy (Field and Field 2017).  A large literature studies equity issues in environmental policy, a topic often called “environmental justice” (Banzhaf et al. 2019). As I argue below, some command-and-control policies dominate pricing policies on equity grounds.

Another goal of policy is implementability.  The theoretically ideal policy is unhelpful if in practice it is impossible to pass or to enforce.  A key feature inhibiting the implementability of pollution pricing is the presence of political economy constraints.  Pollution pricing, especially pollution taxation, is very unpopular.  Command-and-control policies are less unpopular.

Political Economy Justifications for Alternatives to Pollution Pricing

Command-and-control pollution policies have been successfully reducing emissions for decades throughout the world.  By contrast, policies that put a price on carbon or other pollutants are rarer and very unpopular, throughout the world and across the political spectrum.  Perhaps the most prominent exemplar of their unpopularity lies in the French protest movement known as the yellow vests (mouvement des gilets jaunes).  While the causes of the protest movement are varied, the initial spark behind the movement was French President Emmanuel Macron’s announcement on 1 January 2018 of a tax on motor fuels to reduce carbon emissions (Cigainero 2018).  This opposition to carbon pricing exists despite general support among the French population of measures to battle climate change (Douenne and Fabre 2020), in the country that birthed the Paris Agreement in 2016.

Likewise, in the United States, though climate change is increasingly seen as a threat, support of carbon pricing is quite low.  A 2019 poll of US residents conducted by the Washington Post and the Kaiser Family Foundation found that, while a larger percentage of Americans see climate change as a crisis that must be addressed, support for policies that would increase energy costs is low.  For example, 76% of respondents said that climate change is a “crisis” or a “major problem,” and 85% said that addressing climate change will require Americans to make major or minor sacrifices, but only 25% support increasing the federal gas tax by 25 cents per gallon, and only 27% support a $10 per month increase in home electricity bills.  Americans show more support for command-and-control policies: 66% oppose President Trump’s plan to roll back automobile fuel economy standards (Dennis et al. 2019).

The lack of public support in the United States is reflected at the ballot box.  Proposals to enact carbon taxes have never passed in the United States.  Washington State has had two ballot initiatives to enact a carbon tax.  In 2016, Initiative 732 was placed on the November election ballot after garnering 350,000 signatures in support.  It would have phased in a carbon tax, starting at $15 per metric ton, and in turn reduced the sales tax rate by 1%, reduced taxes on manufacturing firms, and expanded the state’s earned income tax credit.  It was opposed by environmental organizations including the Sierra Club and was defeated at the polls 59.3% to 40.7%.  Two years later, Initiative 1631 was placed on the ballot.  It too would introduce a carbon tax starting at $15 per ton, but it would have used the carbon tax revenues to invest in projects aimed at reducing pollution.  Though it garnered more establishment support from the likes of the Sierra Club, it too failed, 56.6% to 43.4%.  Anderson et al. (2019) study the determinants of the votes on these two initiatives and find that political ideology is the major driver.

This lack of political support for pricing carbon is a real constraint that should be considered in economic models.  Some economists may argue that political economy considerations are not the domain of economists, but rather of political scientists or others.  However, political constraints are constraints, and economists solve constrained optimization problems.  It is just as inappropriate to rule out considering political constraints as it is to rule out constraints based on technology or abatement costs.  Just like technological constraints, political constraints are constraints on the set of instruments that are possible.

The argument for non-price-based policies justified by political constraints is hinted at in a recent essay by Lawrence Goulder (Goulder 2020).  Goulder argues that the urgent need for climate policy soon is of such vital importance that the potential for near-term implementation needs to be part of any assessment of price-based policies.  Alternative policies “that economists might otherwise tend to dismiss” (p. 144), like a command-and-control Clean Energy Standard (CES), could potentially dominate price policies if they have sufficiently greater likelihood of being passed in the near term.  On what Goulder calls a “narrower, conventional” (p. 153) cost-effectiveness analysis, the CES is dominated by a carbon tax.  But when the prospect of near-term implementation is also considered, the CES could dominate a tax.

Another argument for non-price-based climate policies based on political economy grounds comes from Joseph Stiglitz (Stiglitz 2019).[5]  Stiglitz argues that time-consistency problems with carbon pricing and technology innovation policy create unique political constraints.  For example, an initially-announced high price path may not be credible, since the endogenous technological change induced by the policy will reduce the social cost of carbon and thus reduce support for the high price path (Helm et al. 2003).  Furthermore, Stiglitz (2019) argues that policies can affect coalition forming and thus agents’ future interests.

Jenkins (2014) discusses several political economy constraints that affect carbon pricing.  Jenkins argues that the presence of these constraints can be analyzed in a traditional second-best setting, where the first-best carbon tax is unattainable or costly.  The constraints identified include low willingness-to-pay of citizens, opposition by producers where costs will be concentrated, and principal-agent problems.  Given these and other constraints, it is likely that if carbon pricing is passed, the level of the tax will be lower than the efficient level.  This creates a significant opportunity for improvement.  A non-price policy might offer efficiency gains even if it’s not efficiency-maximizing.

Of course, proponents of carbon pricing are aware of political economy constraints and have carefully considered how the design of carbon pricing policies affects their possibility of being implemented (Baranzini et al. 2017).  Several studies show through surveys or choice experiments that the use of the carbon tax revenue has an impact on support for a tax; when revenues are used to fund mitigation projects the tax receives the highest support (Carattini et al. 2017, Carattini et al. 2019).  Klenert and Mattauch (2019) cite public support as a crucial factor in designing an effective carbon tax.  Their proposition for encouraging public support is to emphasize the use of the tax revenues and how it can offset the distributional burden of the price increases. (I address these distributional burdens in the next section.)  Carbon tax proponents will also argue that support for carbon pricing is growing; it is implemented in 60 jurisdictions covering 20% of world emissions (World Bank 2019).  Political economy considerations should certainly play a part in designing a carbon price, but I also contend that they are serious enough to lead us to consider alternatives to carbon pricing.

Equity Justifications for Alternatives to Pollution Pricing

Barring political economy constraints, carbon pricing is likely more cost-effective than non-price policies.  However, the distribution of costs and benefits under the two types of policies will differ.  It may be the case that the distributional outcomes are more equitable under a non-price policy than they are under price policies.  The evidence here is decidedly mixed, with some studies finding price-based policies to be more progressive than non-price-based policies, and some finding the opposite.

One theoretical advantage of price-based policies is that they can raise revenue.  A carbon tax generates tax revenues, and a cap-and-trade program in which at least some of the permits are auctioned or sold rather than freely distributed also generates revenues.  These revenues can then be used to affect the net distributional burden of the policy.  For example, if the revenues are returned in a lump-sum fashion, this revenue return will be highly progressive.  Even if the impact of the price itself is regressive, the progressive revenue return could offset that impact.  West and Williams (2004) simulate the effects of a $1 per gallon gasoline tax increase across income quintiles in the United States.  Without considering the return of revenues, the tax increase is regressive, with a Suits index (a measure of incidence, where a negative value indicates regressivity and a positive value indicates progressivity) ranging from ­–0.31% to –0.44%.  If instead the revenue is returned through lump-sum rebates, the outcome is progressive, with a Suits index ranging from 0.11% to 0.25%.  However, Fullerton and Monti (2013) develop a general equilibrium model with two labor skill types and show that even after returning all pollution tax revenues to low-skill workers through low-skill labor tax cuts, the pollution tax still disproportionately burdens them.

Non-price policies like command-and-control mandates or standards do not create revenues; instead they create scarcity rents which generally will be captured by regulated producers (Fullerton and Metcalf 2001).  Indeed, lump-sum return of revenue is a key component behind the proposal in the Economists’ Statement on Carbon Dividends; the “carbon dividends” refer to the lump-sum return of the carbon tax revenues.[6]

But is this theoretical equity advantage of revenue-raising price policies ever manifested in real-world policies?  In truth, there are relatively few examples real-world pollution price policies that recycle revenues in a way that aims to achieve more equitable outcomes.  Klenert et al. (2018) examine five real-world carbon taxes and report the uses of the tax revenues.  Only a minority of the revenues are recycled to households.  Most of the revenues are returned to firms, through tax cuts or transfers, or to general funds or green spending.  Carl and Fedor (2016) report that 70% of cap-and-trade program revenues are used on green spending, rather than for achieving distributional goals.

The story of Washington State’s proposed carbon tax illuminates the difficulty of using revenue recycling to achieve distributional goals.  The first proposal, in 2016, included a cut in the sales tax and an increase in the earned income tax credit, which primary benefit low-income households.  Because it did not include green spending, it was opposed by many environmental groups including the Sierra Club.  In response to this opposition, the second proposal, in 2018, included more green spending and less equity-targeting revenue return.  It too failed.  The two goals of equity and political attainability are not necessarily both served through the same instruments of policy design.

It may be difficult to design pricing policies to return revenue to offset regressive costs, but that does not necessarily imply that carbon price policies are more regressive than non-price policies. It may be the case that non-price policies are more regressive than price policies, or that price policies are more progressive than non-price policies, even without consideration of revenue return.  What does the evidence say?  Of course, the answer is “it depends;” different types of price and non-price policies will have different distributional outcomes.

Pizer and Sexton (2019) summarize the literature on the distributional impacts of energy taxes.  They conclude that, while these taxes are commonly assumed to be regressive, more recent literature shows that this is not always the case.  In fact, the direct incidence (ignoring the uses of the revenue) differs across type of tax and location.  For instance, Pizer and Sexton (2019) report that in the United States energy consumption is a higher fraction of total spending for the lowest expenditure decile (15% of spending) than it is for the highest expenditure decile (5% of spending), suggesting that a price policy increasing the costs of all energy for all consumers will be regressive.  But, this pattern does not hold for all types of energy; the consumption pattern across expenditure deciles of motor fuels is basically flat.  In other countries the pattern differs too.  Generally, carbon taxation may be progressive overall in poorer countries (Dorband et al. 2019).  There are also issues of horizontal equity in the burden of energy taxes; Rausch et al. (2011) find a large variation in the burden of these taxes within income groups, especially within the poorest groups.

The total distributional burden includes not just the “uses-side” effects of prices of good like gasoline and electricity, but also “sources-side” effects on the prices of inputs like labor and capital.  Some studies attempt to measure both sets of effects and generally find that the sources-side effects are progressive and may even fully offset regressive uses-side effects (Goulder et al. 2019, Rausch et al. 2011).

Two recent studies demonstrate the importance of considering labor market effects in distributional outcomes.  Hafstead and Williams (2018) study the unemployment effects of environmental policies using a general equilibrium model with labor market search-and-matching frictions.  They simulate the effects of a carbon tax and a command-and-control performance standard.  While the carbon tax is more efficient, the performance standard yields a smaller shift in employment, both in job losses in the polluting industries and job gains in other industries.  Given the distributional costs of these labor market transitions and unemployment, they conclude that the performance standard may be more attractive to policy makers on equity grounds despite its relative inefficiency.

Aubert and Chiroleu-Assouline (2019) also examine distributional issues related to unemployment effects of environmental policy, using a labor market search-and-matching model to generate unemployment.  Their model features both high- and low-skill labor.  They identify conditions where there is a trade-off between efficiency and equity; a pollution tax that reduces deadweight loss is regressive.  But they also find conditions where this trade-off does not exist, for instance when low-skill employment is more responsive than high-skill employment.

Davis and Knittel (2019) estimate the incidence of automobile fuel economy standards in the United States and find that, for the new car market, they are actually progressive overall. This is mainly because richer households are more likely to buy new cars. After including the used car market, the standards become mildly regressive.  Levinson (2019) compares fuel economy standards to a gasoline tax.  He simulates a fuel economy standard through a tax on low fuel economy (equivalent to a subsidy to high mpg).  For a given level of revenue raised (though not necessarily for a given reduction in gasoline consumption), he finds that the gas tax is more regressive than the fuel economy subsidy.

Bruegge et al. (2019) study the distributional effects of building energy code regulations, a commonly employed command-and-control energy policy.  The energy savings from these regulations tend to be greater for low-income households, which is a progressive distributive outcome.  However, the regulations are also found to distort home attributes at a higher rate for low-income households, notably by reducing the square footage and the number of bedrooms.  This is a regressive distributive outcome.

In summary, the distributional rationale for price policies or non-price policies is unclear.  In theory, an advantage of price policies is the revenue they generate, which can be used to achieve distributional goals.  In practice, such use of revenue return is rare and may be politically difficult to enact, especially in places where support for redistributive policies in general is low.  Even if revenue recycling is distributionally neutral, the difference in the incidence between price policies and non-price policies is ambiguous; in some cases a price policy is more regressive than an equivalent non-price policy, and in some cases vice versa.  Nevertheless, the consideration of distributional or equity goals in policy optimization may provide support for pursuing non-price-based policies.

Efficiency-Based Justifications for Alternatives to Pollution Pricing

The standard argument for pollution pricing assumes that the pollution externality is the only market failure.  When there are multiple market failures the argument is more complicated.  The theory of the second best (Lipsey and Lancaster 1956) tells us that, in the presence of multiple market failures, a policy that targets only one market failure does not necessarily increase efficiency.  In the real world, pollution externalities exist alongside other market failures, like knowledge spillovers (Stiglitz 2019, Jaffe et al. 2005) and imperfect competition (Kennedy 1994).  A price on pollution, with no other policy to address the other market failure(s), does not necessarily dominate non-price policies.

Command-and-control non-price policies may dominate price policies under incomplete regulation.  As argued by Holland (2012), incomplete regulation can result in leakage, where emissions reductions from the regulated sector or economy are partially or totally offset by emissions increases in unregulated places.  With the possibility of leakage, a non-price intensity standard can dominate a price because the implicit output subsidy in the intensity standard prevents or reduces leakage.

Another efficiency-based justification for intensity standards over pollution prices is based on business cycle volatility.  Fischer and Springborn (2011) develop a real business cycle general equilibrium model that includes pollution.  They compare an emissions tax, cap-and-trade, and an intensity standard, and they show in their preferred calibration that the intensity standard dominates.  The standard yields higher levels of output and labor and lower costs than a tax with equivalent emissions reductions, because the standard allows the economy to more efficiently adjust to the changing conditions brought about by the productivity shock.

Barrage (2020) provides another dynamic model of optimal pollution policy, extending the DICE integrated assessment model to include pre-existing distortionary taxes on labor, capital, and output.  Though Barrage’s (2020) model does not consider non-price policies, it shows that the presence of other pre-existing policies like capital and labor taxes alters the efficient carbon price; it is no longer equal to the Pigouvian level of marginal external damages.  This research shows that other efficiency considerations affect the optimal pollution price, which suggests that these considerations may also affect the ranking between price and non-price policies.

A final set of efficiency justifications for non-price policies comes from behavioral economics.  The standard neoclassical argument for pollution pricing assumes that all agents rationally respond to incentives.  Growing evidence from behavioral economics suggests that people often do not respond to incentives according to the predictions of rational choice theory.  If so, this calls into question the efficiency advantage of price over non-price pollution policy.

This is precisely what is found in several research papers.  Tsvetanov and Segerson (2013) provide a behavioral model featuring temptation and self-control, based on Gul and Pesendorfer (2001).  They find that Pigouvian taxes do not maximize efficiency in this environment. In fact, a policy that combines a price on pollution with a command-and-control standard can yield higher efficiency than a pollution price alone, depending on the parameters.

Fischer et al. (2007) ask whether automobile fuel economy standards, a command-and-control non-price policy, should be tightened based on efficiency grounds, in a model where consumers may undervalue fuel costs.  Their main result is that either conclusion could be reached depending on the model’s specifications and parameters, so there are cases where tightening the non-price policy increases efficiency.  Sallee (2014) provides evidence that consumers exhibit “rational inattention” to fuel economy when purchasing cars.  This behavioral phenomenon likely affects the cost-effectiveness of price policies, though Sallee’s paper does not consider policy analysis.  Li et al. (2014) show that consumers respond differently to a change in the gasoline tax rate than they do to other changes in gasoline price.

This small literature relating behavioral economics to environmental policy, along with other papers that study pollution externalities alongside other distortions or market failures, provide justification for non-price-based policies dominating price-based policies on efficiency grounds alone, without appealing to political economy or equity concerns.

Conclusion

The standard neoclassical argument in favor of price-based policies to address externalities like pollution is convincing, in theory.  In a perfect world (or at least a world in which the only imperfection is pollution), establishing a carbon price through a tax or a cap-and-trade system is the preferred way to address climate change; it will reduce emissions at the lowest possible cost.  If the price is right, it will achieve the efficient level of pollution reductions.

But the real world is complicated.  Political economy constraints make pollution pricing difficult to enact at socially efficient levels, at least in the near term.  Distributional outcomes from pollution pricing may be regressive.  Other market failures or behavioral anomalies can make pollution pricing inefficient.  All of these reasons weaken the standard argument that price-based policies dominate non-price-based policies.

Admittedly, proponents of pollution pricing are aware of these limitations and advocate designing price-based policies with these limitations in mind.  However, I contend that the limitations of carbon pricing, though surmountable, are dire, and thus they provide a strong justification for supporting alternatives to price policies, like command-and-control performance standards and technology mandates.

In fact, the history of environmental policy in the United States is more or less a history of successful command-and-control policies.  Flagship laws like the Clean Air Act and the Clean Water Act are predominantly composed of non-price regulations, which have created large net benefits for society (EPA 2011).  The command-and-control corporate average fuel economy (CAFE) standards that apply to new cars have effectively reduced tailpipe pollution (National Research Council 2002).  None of these policies is perfect, but they have been enacted, and they have helped the environment.

Going forward, non-price policies like a federal Clean Energy Standard are likely to continue the tradition of successful command-and-control environmental policies (Goulder 2020, Goulder et al. 2016).  The Obama administration’s proposed Clean Power Plan, if enacted, would have reduced carbon emissions through a combination of price and non-price policies (Fowlie et al. 2014).  The replacement for the Clean Power Plan will likely feature a similar combination.

Environmental economists and other advocates for environmental policy should continue to argue in favor of pollution pricing policies and work to design such policies to increase their effectiveness.  But in doing so we should not rule out alternatives to price-based policies like command-and-control mandates.  These non-price-based policies may in fact have advantages over price-based policies when it comes to equity considerations or political feasibility.  To solve climate change and other environmental crises, the optimal solution will consist of a multiplicity of tools and not a silver bullet.

Endnotes

[*] Many thanks to Stefano Carattini, David Klenert, Lawrence Goulder, and Linus Mattauch for helpful comments.

[1] As Pigou writes: “When there is a divergence between these two sorts of marginal net products, self-interest will not, therefore, tend to make the national dividend a maximum; and, consequently, certain specific acts of interference with normal economic processes may be expected, not to diminish, but to increase the dividend.” (Pigou 1920, Part II, Chapter IX) By “divergence between these two sorts of marginal net products,” Pigou means externalities, which make private and social incentives diverge. (Pigou never uses the term “externality” in the book.)  By “the national dividend,” Pigou means what we now call economic efficiency.

[2] “It [the presence of externalities] is true of resources devoted to the prevention of smoke from factory chimneys: for this smoke in large towns inflicts a heavy uncharged loss on the community, in injury to buildings and vegetables, expenses for washing clothes and cleaning rooms, expenses for the provision of extra artificial light, and in many other ways.” (Pigou 1920, Part II, Chapter IX).

[3] A microeconomics principles textbook states that pollution pricing “forces the firm to internalize the externality, meaning that the firm must take into account the external costs (or benefits) to society that occur as a result of its actions.” (Mateer and Coppock 2018, p. 219).

[4] An undergraduate environmental economics textbook describes this result: “As long as the control authority imposes the same emissions charge [price] on all sources, the resulting incentives are automatically compatible with minimizing the costs of achieving that level of control.” (Tietenberg and Lewis 2018, p. 343).

[5] Stiglitz incidentally is the only one of 16 living former chairs of the presidential Council of Economic Advisers who did not sign the Economists’ Statement on Carbon Dividends (Mufson 2020).

[6] Part of the statement reads: “To maximize the fairness and political viability of a rising carbon tax, all the revenue should be returned directly to U.S. citizens through equal lump-sum rebates. The majority of American families, including the most vulnerable, will benefit financially by receiving more in ‘carbon dividends’ than they pay in increased energy prices.” (Economists’ Statement on Carbon Dividends 2020)

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The post In Defense of Alternatives to Pollution Pricing appeared first on Economics for Inclusive Prosperity.

Rich and poor countries alike are facing an unprecedented economic crisis as they attempt to contain the impact of the COVID-19 pandemic. A downturn of this magnitude can cause tremendous long-term damage, with critical economic linkages between employees, businesses, and banks at risk of disappearing forever.  Scores of firms will close permanently unless urgent action is taken.  The threat is even more significant for emerging economies, where the economic costs of social distancing are likely to be higher, and where vulnerable small and medium sized enterprises with low cash reserves account for a much larger share of the economy than in rich countries, which can rely on extensive social and economic safety nets. Poor countries, moreover, have far more precarious health-care systems. The funds required to support vulnerable workers and businesses, and to care for COVID-19 patients, could be as high as 10% of their GDP. As a comparison, in the US the rescue measures passed in the last month alone account for at least 10% of GDP, and are likely to increase even more.^[1] A number of European countries have commited loans, equity injections and guarantees up to 35% of GDP.^[2]   

The COVID-19 crisis has led to a sudden collapse in capital flows to emerging and developing countries. According to estimates by the Institute of International Finance, non-resident portfolio outflows from emerging market countries amounted to nearly $100 billion over a period of 45 days starting in late February 2020. For comparison, in the three months that followed the explosion of the 2008 global financial crisis, outflows were less than $20 billion.^[3] 

Advanced economies can borrow large amounts at little extra cost. Moreover they benefit from flight-to-safety funding from foreign investors and from U.S. investors liquidating their foreign holdings. In other words, the financing that the U.S. and other advanced economies rely on comes in part from emerging market economies where, ironically, the financial needs are more pressing. What’s more, in contrast to the 2008 global financial crisis, every emerging and developing economy now confronts greater borrowing needs at exactly the same time. Even if a country like Mexico were able to issue bonds, it would be competing with many other countries at the same time. The reality is that countries have no one else to borrow from but other countries.

Left to their own devices financial markets will pick winners and losers. The winners will be those countries that already have enough borrowing capacity. They will be able to borrow large amounts at rock-bottom interest rates. The losers will be the world’s Mexicos or Cameroons.  These countries will be doubly punished: not only will they be unable to raise funds to deal with the crisis, but capital will also move away, as it has already started to, precisely because of the increase in borrowing by the US, China, and European countries.  

It is little wonder, then, that about 100 countries have already approached the International Monetary Fund for financial assistance. Fighting a global pandemic is all about strengthening the weakest links. Eradication of COVID-19 is a weakest link public good (Barrett 2006).

In response to this crisis, the Group of 20 leading economies agreed to a temporary debt service standstill on bilateral official loan repayments from a group of 76 of the poorest countries (the so-called IDA countries).^[4]  This is a positive first step, but the agreement needs to be extended along two dimensions. First, the exclusive focus on the poorest countries leaves out many low and middle income countries that already face severe economic strains. Second, a key constituency missing from the G20 plan is private creditors whose participation is sought only on a voluntary basis. Although they are not the most important creditors of IDA countries, they are crucial for middle income countries such as Mexico, where they hold the majority of the sovereign debt.

In the absence of private sector participation, official debt relief in middle income countries may partly be used to service private creditor claims. Given the expected size of the fiscal needs of these countries, any financial relief dissipated on debt servicing of private creditors claims will be very costly. Moreover, participation by private creditors cannot be wholly “voluntary”.  If participation is voluntary, relief provided by those private creditors that participate will simply subsidize the non-participants. And history teaches us that a significant number of private creditors will not volunteer to participate.  

In sum, for emerging and developing countries to be able to withstand the economic shock, it is imperative to include all private creditors as a part of a future debt standstill. We propose that multilateral institutions such as the World Bank or other multilateral development banks create a central credit facility allowing countries requesting temporary relief to deposit their stayed interest payments to official and private creditors for use for emergency funding to fight the pandemic. Principal amortizations occurring during that period would also be deferred, so that all debt servicing would be postponed.

The facility would be monitored by a multilateral lending institution to ensure that the payments that otherwise would have gone to creditors be used only for emergency funding related to the global pandemic. Our assumption is that all funding from this emergency facility and associated deferred principal payments would eventually be repaid by the country, and that investors would get their money after the crisis is over. We estimate that a 12 month debt standstill from both bilateral and private sector creditors would provide around $800 billion in resources for emerging and developing countries (ex-China), representing 4.7% of their annual income.

Domestic contract law regimes incorporate doctrines that allow the performance of a contract to be suspended (or occasionally avoided entirely) upon the occurrence of events that are wholly unforeseen, unpredictable and unavoidable. For its part, public international law recognizes, in a doctrine called “necessity”,  that states may sometimes need to respond to such exceptional circumstances even at the cost of suspending normal performance of their contractual or treaty undertakings.  COVID-19 meets all of the criteria for such an exceptional phenomenon.   Countries badly afflicted by this pandemic will need to deploy their available financial resources in immediate crisis amelioration measures. Those funds must be obtained from several sources—a diversion of budgetary amounts that had been earmarked for other purposes before the crisis, loans or grants from official sector institutions and a redirection of money that had been intended for scheduled debt service. In making these adjustments, the states concerned will not be acting in a discretionary or optional manner; in the truest sense of the word they will be acting out of necessity. We believe that everyone, and particularly the G-20 countries, should publicly acknowledge this fact in the context of recommending a standstill on debt service payments under bilateral and commercial credits for a limited period.

What is at Stake

In 2018 developing and emerging market countries (excluding China) had a stock of external debt of approximately $5.9 trillion. About 82% of this debt ($4.8 trillion) was classified as long-term (with original maturity greater than one year), with $2.1 trillion owed by the private sector and $2.7 trillion either owed to or guaranteed by the public sector. Of the public sector external debt, about 40% was owed to the official sector ($600 billion to multilateral creditors and $400 billion to bilateral) and the remaining 60% to private creditors (bonds amounted to $1.3 trillion and bank loans to $380 billion).^[5]

One way of estimating the effect of the COVID-19 crisis on the ability of emerging and developing countries to roll-over their external public debt is to assume that these countries will lose market access at least until the end of 2020.^[6] If official financing remains constant, net flows tied to long term debt with official creditors are expected to be $25 billion ($120b disbursements minus $71b principal repayment and $24b in interests) and net flows with private creditors amount to -$252 billion, as there will be principal and interest payments due ($170b and $82b, respectively) but no disbursements (which in 2018 amounted to $237b). Hence, the estimated shortfall on long term debt flows will be $227 billion. 

To this figure, we need to add short-term debt. We do not have detailed data on the share of short-term external debt owed by public sector borrowers, but it could be as high as $500 billion. Bringing the total shortfall to $735 billion (for details, see Table 1 in the Appendix). This total shortfall provides an estimate of the potential public sector sudden stop, while the total sudden stop would also include equity flows and lending to private debtors.

The recent G20 decision to grant debt relief to the poorest countries focuses on the bilateral debt of the group of countries which are eligible to borrow from the World Bank concessional window (the International Development, Association, IDA) plus Angola. The total shortfall for this group of countries (last column of Table 1 in the Appendix) is estimated at $36 billion. The principal and interest due by these countries to bilateral creditors (the focus of the G20 action) is $14 billion, less than 2% of our estimates for the public sector sudden stop associated with COVID-19 across all low and middle income countries. 

Figure 1 shows how this shortfall varies across geographical regions and income groups. The most affected region will be Latin America and the Caribbean, followed by Emerging Europe. For Emerging Europe about 50% of the sudden stop will be associated with the need to service and rollover long-term external debt and the remaining half related to short-term debt flows.^[7] For Latin America and the Caribbean about two-thirds of the sudden stop will be associated with short-term debt rollover needs.^[8]  The figure also shows that for middle income countries “business as usual” net-official inflows (which tend to be positive and hence have a negative value in our measure of shortfall) cannot be expected to compensate the expected sudden stop in bond and bank financing. The Figure also shows that the G20 debt relief of April 16, $14 billion, is very small compared to the total expected shortfall.

Figure 1: Potential public sector sudden stop

This figure plots the potential public sector sudden stop across geographical regions and borrowing groups. It assumes business as usual net flows from official creditors. The G20 Act. Bar plots the debt relief measure implemented by the Group of 20 on April 16, 2020.

As there is some uncertainty on the share of external short-term debt owed by the public sector, Figure 2 provides a detailed breakdown concentrating on the long-term component of this potential public sector sudden stop. In Emerging Europe, most of the potential public sector sudden stop on long-term debt (80%) is related to the need to rollover maturing bonds and loans, while in Latin America interest payments amount for more than 40% of financing needs (about the same as for the group of upper middle countries). 

Figure 2: Public sector external debt service (only long-term debt)

This figure plots the potential public sector debt service needs across geographical regions, borrowing groups, and creditor groups (Multilaterals, Bilaterals, Bond, Other Commercial Creditors). The dotted bars measure interest payments (Int.) and the solid bars repayment of principal (Princ.). The G20 Act. Bar plots the debt relief measure implemented by the Group of 20 on April 16, 2020.

Figures 3 plots country-specific estimates of the public sector sudden stop, expressed as a share of total government expenditures. There are 35 countries for which the public sector sudden stop will amount to more than 15% of government expenditures and 24 countries where the potential public sector sudden stop is greater than 20% of public expenditures.

Figure 3: Potential public sector sudden stop as a share of government expenditure

This figure plots the potential public sector sudden stop as a share of government expenditure for all countries where this share is larger than 1%, broken down into Official net flows (Off), Private creditors Interest Payments on long-term debt (Int.), Private creditors principal repayments on long-term debt (Princ.) and public sector short-term debt (ST). The dashed line plots the potential sudden stop including short-term debt and the solid line excludes short-term debt.  

We should interpret these figures with caution. On the one hand, they may overstate the problem since they assume a complete sudden stop in private sector financing. It is possible that not all short-term credit will collapse, and some countries may even be able to maintain access to long term debt. For instance, at the end of March, Panama managed to issue a $2.5 billion sovereign bond in the international debt market. Similarly, we may be overestimating the share of short-term debt owed by the public sector. On the other hand, these figures are likely to greatly understate the problem as they do not take into account funding gaps associated with: 

1. The collapse of international lending to the private sector (which accounts for 40% of total long-term external debt developing countries); 
2. The sudden stop in equity flows (both portfolio and FDI)
3. The currency depreciation which will increase the cost of serving foreign currency loans. 

An increase in official disbursement equal to all payments due to the official sector could close about 13%  of this shortfall ($71 billion in principal repayment and $24 billion in interests), but developing and emerging market countries will still need an additional $640 billion. One possibility would be to greatly scale-up official sector lending. Landers, Lee, and Morris (2020) estimate that the lending capacity of the multilateral development banks (MDBs) could increase by more than $1 trillion. 

Yet these figures assume a constant public sector expenditure and deficit. Hence they fail to recognize that the sudden stop comes while GDP in emerging and developing economies is expected to contract by 1% in 2020 (with contractions as large as 5% in Emerging Europe and Latin America) according to the April 2020 IMF World Economic Outlook projections, down from 3.7% output growth in 2019.  Lower economic activity will reduce tax revenues while government expenditures must increase to protect citizens and the economy. Overall, the IMF estimates that emerging economies’ funding needs will total $2.5 trillion, a figure that we find conservative.^[9]

Even a dramatic increase in MDB lending will not be sufficient and the private sector will have to be involved in offering relief. The G20 could enable a generalized private sector debt suspension by coordinating a stand-still that would apply to all sovereign-debt payments due by emerging and developing economies that requested such a freeze, and that would remain in place until the health crisis passes (Gourinchas and Hsieh, 2020). Such a standstill could free up to $803 billion  corresponding to 4.7% of the total GDP of emerging and developing countries.^[10]

The standstill may well bring private lending to the countries that request it to a full stop, but for all intents and purposes such capital flows have already stopped or even been reversed. Perhaps the standstill may lock these countries out of international capital markets for some time, but the stigma from the suspension on this occasion should be feared much less given that it is a necessity brought about by a worldwide pandemic rather than the result of fiscal profligacy. The official sector’s endorsement of the necessity of such a generalized standstill would also minimize any reputational or legal risk. A key issue, as always is how to get the entire private sector involved and how to limit free riding.

For purposes of our analysis, we put aside short-term claims that are typically governed by the domestic laws of the issuer and, therefore, more pliable (see Buchheit and Gulati 2019). Our focus instead is on external debt issued under foreign laws.  Here, a coordinated effort by the G-20 to apply a generalized standstill to all debt payments due by an emerging or developing country that requests such a pause in payments would go a long way in addressing this issue. Our proposal provides a concrete roadmap to achieve an effective coordinated debt relief between the official and commercial sectors.   

The Proposal

Mechanics.  Implementation of an emergency standstill, particularly for commercial creditors of middle income countries, presents a challenge.  Some countries will have dozens of external debt instruments with hundreds or even thousands of individual creditors.  Attempting a bespoke standstill negotiation for each of those instruments is impractical.  It would take many weeks or months at the very time when the debt relief is needed most critically.  No individual commercial creditor or group of creditors will be in a position to prescribe eligible uses for the money that would otherwise have gone toward debt service much less be in a position to monitor and verify how those funds are actually spent.  Individually negotiated amendments to existing debt instruments will inevitably produce a welter of incongruent conditions, financial terms, covenants and so forth, probably at ruinous legal expense.  Therefore, all creditors will be asked for the same relief — a standstill on interest payments for a prescribed period.  Since a bespoke implementation of that request will result in choppy, inconsistent outcomes among affected creditors, we suggest a streamlined approach as follows:

• The World Bank or the multilateral development bank for the region concerned would open a central credit facility (a “CCF”) for each country requesting this assistance.  The CCF would specify the eligible crisis amelioration uses for drawings under the facility, as well as the arrangements for monitoring the use of proceeds.
• In view of the nature of this emergency, each CCF should have terms (interest rate and amortization) that will not aggravate the post-COVID-19 financial position of the beneficiary country.
• Once a CCF is in place for a country seeking this assistance, the debtor country would notify each of its bilateral and commercial creditors that interest payments on existing debt instruments falling due during the prescribed standstill period will be directed to (and reinvested in) the CCF.  Each lender would also receive a formal request from the debtor country seeking the lender’s acknowledgment that the reinvestment of the interest payment into the CCF (and the crediting to the lender’s account of a corresponding interest in the CCF) will constitute a full discharge and release of the borrower’s obligation in respect of the relevant interest payment.^[11]  For indebtedness in the form of international bonds, this acknowledgment will probably be sought through a consent solicitation addressed to all holders of each such bond.
• The threshold decision about whether to seek a standstill on interest payments for a limited period will, of course, rest in the discretion of each sovereign debtor. Some countries may be spared the worst of the pandemic and will not need this relief while others may continue to enjoy market access during this period and would not wish to jeopardize that status by deferring current interest payments. 

Principal amortizations.  Participating countries with principal amortizations falling due during the standstill period will need to defer those amounts.  It would obviously be inconsistent to seek a standstill on interest amounts while simultaneously paying principal.  Such deferral could be handled in one of several ways.  The official sector might encourage, perhaps even insist, that all participating countries with principal payments falling due during the standstill period enter into more or less simultaneous exchange offers at the beginning of the process to reschedule those principal amounts.  This would address the issue in a coordinated and possibly uniform manner at the outset.  Alternatively, some creditors may prefer voluntarily to reinvest their principal payments into the CCF, thereby taking advantage of both the de facto seniority of the CCF and the automatic monitoring of proceeds embedded in the CCF.  The other option would involve negotiating deferrals of principal payments on a case-by-case basis.  Only a subset of participating countries will have principal maturing during the standstill. The important task is to effect a deferral of those amounts so that they do not result in a diversion of funds intended for crisis amelioration measures.  The precise manner in which that objective is accomplished can be left to the debtor countries and the affected creditors.

Sustainability considerations.  Some countries will have had unsustainable debt positions before the COVID-19 crisis hit, others will have unsustainable debt positions after the crisis abates.  A standstill on interest payments for the balance of 2020 or slightly longer does not preclude or prejudge a more durable debt restructuring for one of these countries at the appropriate time.  A CCF, in light of its origin and purpose, ought to be considered a de facto senior instrument in such a debt restructuring, the equivalent of debtor-in-possession financing in a corporate insolvency.  Because the aggregate amounts redeployed through a CCF should for any given country be small (equal to interest accruals for +/- 12 months), the effect of such a recognition of seniority in a general debt restructuring should be negligible.^[12]

Necessity.  We perceive little political enthusiasm for a resurrection of proposals for an institutionalized sovereign bankruptcy regime, nor is there any time to design and implement such a regime in the middle of this crisis.  There is one measure, however, that the official sector could take that may assist debtor countries if legal challenges are raised by minority creditors to these arrangements.  In any public statement about these measures and the global emergency that gave rise to the measures, the G-20 could recognize that both official sector institutions and the debtor countries are acting out of necessity, referencing Article 25(1) of the Articles on State Responsibility promulgated by the International Law Commission in 2001.^[13]

Advantages.  Implementing a standstill on interest payments for a prescribed period through these arrangements would have the following advantages:

• All participating creditors in each country (bilateral and commercial) would be treated equally.  All would receive an identical instrument (an interest in that country’s CCF) corresponding to the amount of their reinvested interest payments. 
• All issues related to the identification of eligible crisis amelioration expenditures, conditions precedent to drawdowns and post-disbursement monitoring would be centralized in the CCF and administered by a multilateral institution.
• Amounts reinvested in a CCF would stand the best chance of being repaid even if the debtor country concerned eventually needs a full-scale debt restructuring.
• These arrangements can be implemented immediately after a CCF for the debtor country can be put in place, a feature that will be of critical importance as this crisis rages.

Motivation

There are two parts to the proposal. The first concerns the reinvestment of payments due into a central credit facility for the recipient country administered by a multilateral development bank or the World Bank. 

This is an expedient solution to quickly administer the redirection of interest payments towards more urgent needs in poor countries that are already faced with the dire consequences of the global COVID-19 health and economic crisis. This is the primary motivation for setting up such a facility. Moreover, it would make it easier to monitor the use of funds and to keep a record of all the interest payments that have been redirected in this way. 

The urgent problem is to give recipient countries immediate and comprehensive debt relief. To insist on these countries first getting consent of their creditors will introduce unnecessary and costly delay. It would largely defeat the purpose of providing debt relief. 

The first step of our proposal is for the recipient country to set up a CCF with an MDB and agree to a list of eligible expenditures as well as a timeline for the later repayment of the frozen debt obligations. Once the facility is in place all the sovereign debtor would be required to do is notify its commercial and bilateral creditors that the payments due have been paid into the CCF and that the custodian of the CCF has been instructed to record an interest in the CCF in the name of the creditor. At that point the affected creditor would simply acknowledge and agree that the crediting of the CCF in this manner constitutes a full discharge and release of the debtor’s obligation in respect of the debt obligation concerned. 

This procedure has several practical advantages. First and foremost it can be implemented quickly, essentially immediately upon activation of the CCF. Second, while the underlying debt instrument may be in technical default during the period between the diversion of the interest payment into the CCF and the receipt of the creditor’s consent to this action, that default should be of limited duration and may, depending on the terms of the debt instrument, be covered by the relevant grace period. Even if the commercial creditor were affirmatively to refuse to give an acknowledgment of discharge and release, the creditor’s resulting damages would be offset in large part by the value of that creditor’s corresponding interest in the CCF.  Third, by treating all creditors equally, the CCF in effect assures intercreditor equity. Fourth, by limiting the debt relief to a temporary suspension of debt payments, and by protecting interest payments from misappropriation through the channeling of payments into the CCF, one can reasonably expect that few creditors will choose to opt out and seek legal remedy. The reputational cost to such holdout creditors, acting against the common interest in times of exigency, would not be worth the benefit of receiving full payment of the temporarily suspended interest and principal payments.  

The second part of our proposal concerns our call to the official sector to provide some cover to debtor countries, which could face legal challenges from holdout creditors, by publicly stating the purpose of the debt relief, namely the necessary relief from debt obligations to help debtor countries face the global emergency engendered by the COVID-19 pandemic. By recognizing that the official sector creditors and the debtor countries are acting out of necessity, the G-20 would play an important certification role of the extreme and exigent circumstances they are facing. Depending on the law of the jurisdiction where a holdout creditor may elect to pursue its legal remedies, such a public statement by the G-20 may assist the sovereign debtor in defending its action as the minimally necessary to respond to the exigent circumstances of the pandemic.  

Past economic crises, whether in the US or elsewhere, have sometimes led to political interventions to suspend debt payments or to make other modifications to the terms of debt contracts. Such interventions may be necessary and do not automatically undermine credit markets. In some instances they have actually had the opposite effect, resurrecting debt markets following the intervention. The reason why debt markets recovered was that creditors had anticipated widespread default in the absence of any modification of the repayment terms, and they were pleasantly surprised by the intervention that had the effect of reducing the risk of default.^[14] Creditors on average preferred the certainty of receiving a reduced repayment to the very uncertain prospect of being made whole.   

To be sure, creditors generally do not expect that the promised repayment of their debt contracts will always be honored. They understand that there could be circumstances when it would be essentially impossible for the debtor to meet its obligations. Had they been able to clearly and precisely anticipate these circumstances they would have modified the terms of the contract to reflect these necessities and thereby avoided a wasteful and unnecessary default. 

For many reasons most debt contracts are highly incomplete and do not contain provisions prescribing how the parties will react to such contingencies. To name just one, it is very difficult to specify precisely in advance the exact form of a contingency such as a global pandemic that would merit lowering debt obligations in this event. Ex post it is easier, of course, to identify the contingency. The political intervention in debt contracts in these events serves the role of completing incomplete debt contracts. By certifying the event and by modifying the terms of the debt contract in ways that the contracting parties themselves would have wanted had they been able to, the intervention, far from undermining credit markets, helps support these markets.^[15]           

Not all interventions are beneficial in this way. It is important that they take place only in highly unusual and urgent circumstances that are outside the debtor’s control (“acts of God”). Unusual circumstances are precisely the ones that are hard to describe and include in a debt contract. By certifying that such an event has occurred and by acting accordingly, the G-20 would ensure that contract terms will be modified only when absolutely necessary and when the modifications are likely to support credit markets.^[16]  

To summarize, debt suspension in a crisis provides ex-post economic benefits by avoiding a costly default and by relaxing the liquidity constraint of debtors. These ex-post economic benefits do not negatively affect credit markets ex ante even when suspension in rare circumstances is anticipated. The reason is that the contracting parties themselves would have included lower debt obligations in these circumstances. It is the inability of the contracting parties to describe these circumstances ahead of time that explains the incompleteness of the debt contract. But the contracts can be completed through political intervention in times of exigency.   

Endnotes

^[1] The $2.3 trillion dollar rescue package in the US is 10.6% of US GDP in 2019 (https://www.bea.gov/news/2020/gross-domestic-product-fourth-quarter-and-year-2019-advance-estimate)

^[2] See IMF 2020,  Fiscal Monitor April 2020, Figure 1.1

^[3] https://www.iif.com/Publications/ID/3829/IIF-Capital-Flows-Tracker-The-COVID-19-Cliff

^[4] The group of countries targeted by the G20 also includes Angola, which is not an IDA country but it is classified as a Least Developed Country by the United Nations. 

^[5] Table A1 in the appendix provides a detailed breakdown. These values exclude IMF credit that in 2018 amounted to approximately $155 million. There are several caveats with the data reported here which are based on the World Bank’s International Debt Statistics (IDS). First, IDS may not include all the domestically issued bonds which are held by non-residents (and hence should be classified as external debt). For instance, Arslanalp and Tsuda (2014) track the ownership of central government bonds owned by non-residents in a group of 15 large emerging market countries and for many countries report values that are much larger than the values reported by IDS. Arslanalp and Tsuda (2014) also report larger share of local currency bonds owned by non-residents). For a detailed discussion of this issue see Panizza (2008) and Panizza and Taddei (2020). Second, IDS do not report detailed information on the breakdown of short-term debt (debt with initial maturity below one year). Therefore, we need to make some assumption to allocate some of his debt to the public sector (details are in the notes to Table A1). Third, Horn, Reinhart, and Trebesch (2019) suggest that only part of Chinese overseas lending is reported in the IDS. If we assume that only 50% of Chinese loans are reported in the IDS, the total stock of debt of developing and emerging market countries would increase by approximately $200 million. While this is less than 4% of total debt for the whole group of developing and emerging market countries, under-reporting linked to Chinese loans could be as high as 10% of the total debt of low income countries. Finally, IDS data do not report the amounts of World Bank borrowers which are now classified as high-income (for instance, Chile). 

^[6]As data on roll-over needs for 2020 are not available, we follow Gourinchas and Hsieh (2020) and use 2018 as a proxy. Interest payments for 2020 (which are reported by IDS) closely track interest payments for 2018. Hence, we assume that the composition of level of debt for 2020 is similar to that of 2018.

^[7] Short-term debt is classified on the basis of original maturity.

^[8] Note that we do not net out Argentina’s debt which is already in default.

^[9] https://www.imf.org/en/News/Articles/2020/03/27/tr032720-transcript-press-briefing-kristalina-georgieva-following-imfc-conference-call

^[10] This Figure includes principal and interest due to private creditors ($252 billion in long-term debt and $508 billion of estimated short-term debt) and principal and interest due to bilateral official creditors ($43 billion). It does not include $53 billion due to the multilateral development banks which are in the process of greatly scaling up their lending to emerging and developing countries to counteract the private sector sudden stop.

^[11] Communications addressed to creditors with an implicit “No RSVP Necessary” message have a long tradition in sovereign debt workouts. See Buchheit (1991). When the United Mexican States announced its moratorium on external debt payments in August of 1982 (generally thought to be the opening act in the Latin American debt crisis of the 1980s), the commercial bank lenders received a telex from Mexico asking them to roll over maturing principal amounts of their loans pending an eventual restructuring of those loans. The lenders were not asked to respond to the request. And any responses that did arrive declining the request and insisting on timely payment of maturing principal were simply ignored.

^[12] The de facto seniority of amounts lent through the CCF could be further enhanced by contributing to the CCF some amount of money (it really doesn’t matter how much) from an institution like the World Bank or a multilateral development bank that enjoys a widely-recognized preferred creditor status. As long as those funds are thoroughly commingled with other amounts in the CCF, the sovereign debtor could not default on payments due under the CCF without thereby placing itself in default to a recognized preferred creditor. Such an outcome would risk alienating the affections, and the funding, of all official sector institutions. A similar “co-financing” technique was used in the Greek debt restructuring of 2012 where amounts owed to commercial creditors were contractually linked to amounts due to official European agencies such as the European Stability Mechanism. See Zettelmeyer et al. (2013).  For a description of the development of the co-financing technique during the sovereign debt crises of the 1980s see Buchheit (1988). For an analysis of how debtor-in-possession financing could work in a sovereign debt context see Bolton and Skeel (2005).   

^[13] Article 25(1) Necessity: 

Necessity may not be invoked by a State as a ground for precluding the wrongfulness of an act not in conformity with an international obligation of that State unless the act: 

(a) is the only way for the State to safeguard an essential interest against a grave and imminent peril; and 

(b) does not seriously impair an essential interest of the State or States towards which the obligation exists, or of the international community as a whole. 

International Law Commission (2001).

^[14] See Kroszner (2003) and Edwards, Longstaff, and Marin (2015) on the positive effect on debt markets of the repudiation of the gold indexation clause in debt contracts during the Great Depression.

^[15]See Bolton and Rosenthal (2002) for an analysis of how ex post political intervention in debt contracts can be seen as a way of completing incomplete debt contracts.

^[16]Moral hazard and the concern that the doctrine of necessity will be liberally applied to future events should be allayed by the fact that COVID-19 is a truly exogenous once-in a generation event. The latter point is supported by the following facts: (i) official forecasts point to the deepest global recession since the Great Depression; (ii) global lockdown policies which are more stringent than those adopted during World War II; (iii) unprecedented monetary and fiscal policies adopted by all advanced economies and several emerging market countries.  

Appendix

Table 1: Baseline data by country groups

This table reports debt stocks, disbursements, principal repayments, and interest due by type of debt and creditor group for all developing and emerging market countries excluding China. The regional and income classification are those adopted by the World Bank (EAP: East Asia and Pacific; ECA: Emerging Europe; LAC: Latin America and the Caribbean; MNA: Middle East and North Africa; SAS: South Asia; SSA: Sub Saharan Africa; LIC: Low-income countries; LMIC: Lower-middle-income countries, UMIC: Upper-middle-income countries). The last column (G20 Action) includes all countries targeted by the debt-relief action decided by the Group of Twenty on April 16, 2020.

References

Arslanalp, Serkan and Takahiro Tsuda (2014) “Tracking Global Demand for Emerging Market Sovereign Debt,” IMF Working Paper 14/39.

Barrett, Scott (2006) “The Smallpox Eradication Game,” Public Choice 130:179–207.

Bolton, Patrick and Howard Rosenthal (2002) “Political Intervention in Debt Contracts,” Journal of Political Economy 110:1103-34.

Bolton, Patrick and David A. Skeel (2005) “Redesigning the International Lender of Last Resort,” Chicago Journal of International Law 6(1): 177-201.

Buchheit, Lee C. (1991) “Debt Restructuring-Speak: ‘¿Senor, Que Pasa?’,” International Financial Law Review, March, 10-11.

Buchheit, Lee C. (1988) “Alternative Techniques in Sovereign Debt Restructuring,” University of Illinois Law Review 1988: 371-399.

Buchheit, Lee C. and Mitu Gulati (2018) “Use of the Local Law Advantage in the Restructuring of European Sovereign Bonds,” University of Bologna Law Review 3(2): 172-179.

Sebastian Edwards, Sebastian, Francis A. Longstaff, and Alvaro Garcia Marin (2015) “The U.S. Debt Restructuring of 1933: Consequences and Lessons,” NBER Working Paper No. 21694.

Gourinchas, Pierre-Olivier and Chang-Tai Hsieh (2020) “The COVID-19 Default Time Bomb,” Project Syndicate April 9, https://www.project-syndicate.org/commentary/covid19-sovereign-default-time-bomb-by-pierreolivier-gourinchas-and-chang-tai-hsieh-2020-04

Horn, Sebastian, Carmen M. Reinhart and Christoph Trebesch (2019) “China’s Overseas Lending,” NBER Working Paper No. 26050.

International Law Commission (2001) “Responsibility of States for Internationally Wrongful Acts” https://legal.un.org/ilc/texts/instruments/english/draft_articles/9_6_2001.pdf

Kroszner, Randall (2003) “Is it Better to Forgive Than to Receive? Repudiation of the Gold Indexation Clause in Long-term Debt During the Great Depression,” Discussion Paper University of Chicago.

Landers, Clemence, Nancy Lee, and Scott Morris (2020) “More Than $1 Trillion in MDB Firepower Exists as We Approach a COVID-19 “Break the Glass” Moment,” Center for Global Development, https://www.cgdev.org/blog/more-1-trillion-mdb-firepower-exists-we-approach-covid-19-break-glass-moment

Panizza, Ugo and Filippo Taddei (2020) “Local Currency Denominated Sovereign Loans A Portfolio Approach to Tackle Moral Hazard and Provide Insurance,” IHEID Working Papers 09-2020, Economics Section, The Graduate Institute of International Studies.

Panizza, Ugo (2008). “Domestic and External Public Debt In Developing Countries,” UNCTAD Discussion Papers 188, United Nations Conference on Trade and Development.

Zettelmeyer, Jeromin, Christoph Trebesch and Mitu Gulati (2013) “The Greek Debt Restructuring: An Autopsy,” Economic Policy 28: 513-563.

The post Born Out of Necessity: A Debt Standstill for COVID-19 appeared first on Economics for Inclusive Prosperity.

We provide an overview of the policies that could form a comprehensive social protection strategy in developing countries, with examples of specific policies adopted around the developing world in recent days. Our core argument is that middle-income and lower-income countries can cast an emergency safety net with extensive coverage if they use a broader patchwork of solutions than higher-income countries. These strategies could include:

1. Expanding their social insurance system, which typically covers a much smaller share of the labour force than in higher-income countries;
2. Building on existing social assistance programmes, which reach a large share of households in many developing countries;
3. Involving local governments and non-state institutions to identify and assist vulnerable groups who may not be reached by 1) and 2).

The debate on social protection responses occurs as countries face both a public health and a public finance crisis. First, governments have to design a public health response to mitigate or suppress the virus, which balances provision of COVID19 health care against other health needs, and which can be implemented in contexts where strict social distancing is not practical.^[5] The strictness and duration of the restrictions imposed on mobility and economic activity will, to a large extent, determine the immediate impact on household incomes, and thus the scale of the social protection response needed to mitigate it. In turn, the support provided to help households could increase compliance with public health policies.^[6] Second, governments have to finance both health and economic measures, while experiencing shortfalls in tax revenues. Many developing countries were already heavily indebted before the crisis, and investors have sold emerging market assets, making borrowing on the open market difficult.^[7] Without novel solutions to allow governments to borrow internationally and secure additional aid quickly,^[8] the scale of their social protection response will be limited, and developing countries may not afford a public health response imposing strict restrictions on their economies.^[9]

Key features of developing countries^[10]

Low-income and middle-income countries share features that present specific challenges and opportunities for their social protection response, compared to higher-income countries.^[11]

1. The economic consequences of the crisis for households in developing countries will be severe. A larger share of workers are in occupations and industries less compatible with social distancing (e.g. construction, labour-intensive manufacturing, small retail). Households have more limited access to credit and hold limited savings or buffer stock. Their usual means of smoothing income shocks, casual work and migration, are not possible when economic activity and mobility are restricted. Support from social networks is also more limited when everyone experiences a simultaneous shock, which in the case of a global crisis is true even of the most extended networks (e.g. international remittances). Complying with public health guidelines will incur out-of-pocket costs (e.g. access to water in urban slums) that are high as a portion of available income. In this context, households may take short-term decisions out of necessity that leave them in long-term poverty, such as selling assets to finance food consumption. Moreover, firms often face more severe liquidity constraints in developing countries, limiting their ability to keep paying their workers during the crisis. The need for government intervention is thus particularly severe in developing countries today.
2. Yet, government programmes insuring against job or earnings loss have more limited scope in developing countries. First, a larger share of workers are in employment categories that are difficult to insure against such risks. Many employees work for informal (i.e. unregistered) businesses, which may not contribute to existing social insurance programmes, while others work for formal businesses on informal contracts. The self-employed — whose “regular” income is more difficult to assess even in richer countries – account for a larger share of employment, and many of them also carry out their activities informally. Second, government programmes insuring workers against such risks are more limited in developing countries even for formal (i.e. registered) employees. For instance, the share of developing countries in which these workers are eligible for some form of Unemployment Insurance is much lower than in higher-income countries (see Figure 1). Existing social insurance programmes will thus be less effective in supporting workers in developing countries.

Figure 1: Share of countries with unemployment Insurance

3. At the same time, many developing countries can build on large existing social assistance programmes. As Figure 2a shows, these cover a sizable share of the population, including contexts where informal work and self-employment are the norm. These programmes take various forms, such as conditional or unconditional cash transfers, work guarantees, or the direct delivery of food and other necessities (see Figure 2b). They target poor households and are not necessarily designed to mitigate job loss or income shocks. They can be made more generous in this time of crisis. They can also provide a base for emergency assistance, e.g. they often rely on detailed registries and effective infrastructure for transferring resources. Existing social assistance programmes thus provide invaluable mechanisms to provide emergency relief to many households.

Figure 2: Social assistance programs in developing countries

Source: ASPIRE (World Bank); data collected between 2008-2016 http://datatopics.worldbank.org/aspire/

4. Some vulnerable populations are not easily covered by social insurance and are usually outside the populations targeted by social assistance programmes (e.g. informal workers with volatile incomes, migrant workers), making them particularly hard to reach in an emergency. However, local governments in many developing countries are in a good position to assess unmet needs and to deliver direct assistance. The same is true of a range of non-state actors (e.g. NGOs, savings and loan associations, mutual insurance organisations), which are active in contexts where state capacity is limited (e.g. remote rural areas or urban slums). Involving local actors, especially non-state ones, is an opportunity but also a challenge, as their efforts need to be coordinated, and they need to be monitored by both citizens and national governments. Credible partners thus exist for central governments to help “harder-to-reach” segments of the population, as long as their actions are in line with the national effort and are accountable to the public they serve.

Expanding the social insurance system

Despite pervasive informality, formal employees constitute a major employment category in many developing countries, particularly in middle-income countries. Moreover, these workers are possibly even less well prepared than their counterparts in richer countries to cope with the economic impact of the crisis. Therefore, expanding the social insurance system to provide more support to formal employees could be an important pillar of the social protection strategy of developing countries, even if it will not be sufficient to reach all workers (e.g. informal workers).

Governments around the world have adopted new job retention schemes in the last few weeks. Such schemes already existed in some countries (e.g. Germany, Italy), including developing countries (e.g. Brazil), to help firms cope with temporary shocks (e.g. drop in demand, insolvency issues, natural disasters). They provide subsidies for temporary reductions in the number of hours worked, replacing a share of the earnings forgone by the worker due to the hours not worked, over a maximum period of time (a few weeks or months). Their advantage in the current crisis is to avoid the destruction of existing jobs (Giupponi and Landais, 2018), which should be viable again once the public health response is relaxed. Subsidizing these jobs could allow firms to continue to operate, even if at some reduced level, without imposing large pay cuts. Subsidizing the survival of jobs that must be temporarily suspended could also spare workers and firms the costs of finding a new job and replacing the worker, speeding up the economic recovery.

The argument in favor of job retention schemes is strong for developing countries. Without such schemes, many workers will be laid off with no unemployment insurance. Moreover, setting up a new job retention scheme might be logistically easier than setting up an unemployment insurance programme, as governments could use firms as intermediaries to channel the income support to their workers. Job retention schemes are also most valuable in labour markets where search frictions are high. Recent research shows (i) that finding the right workers is a major challenge to firm growth in developing countries (Hardy and McCasland, 2017); (ii) that workers struggle to find formal employment because of difficulties signalling their skills credibly to firms (Abebe et al., 2020, Carranza et al., 2020); (iii) and that displaced formal employees take much longer to find a new formal job than in higher-income countries (Gerard and Gonzaga, 2016). The destruction of existing jobs might thus have severe longer-term impacts on the size and productivity of developing countries’ formal sectors, which are a key policy focus (Levy, 2008).

Some implementation details might be particularly important in developing countries:^[12]

• Targeting. In Thailand, a recent job retention scheme covers a fixed share of workers’ monthly earnings;^[13] in Morocco, a new programme provides a fixed monthly amount to workers whose job must be temporarily suspended;^[14] the amount received under the Brazilian and South African schemes is not fixed but the share of forgone earnings that it replaces is lower for higher-wage workers.^[15] Targeting the income support to low-wage workers can help more workers for a given budget and leave more financial resources to help other worker categories. However, it will require higher-wage workers to make relatively larger adjustments and increase the risk that their jobs will not survive the crisis. Additionally, targeting support to low-wage workers may not necessarily target jobs for which search frictions are most important, which may slow down the economic recovery.
• Payment. In contrast to some pre-existing job retention schemes (e.g. in France), the above-mentioned schemes do not rely on firms advancing the payment of the earnings subsidy. Firms in developing countries may not have enough liquidity to make such advances or may not trust the government to reimburse them quickly, disincentivizing participation (see Levinsohn et al., 2014, on an earlier wage subsidy in South Africa).
• Other firm contributions. Job retention schemes sometimes require firms to contribute towards their workers’ compensation beyond the hours actually worked (e.g. for larger firms in the Brazil scheme). This could incentivize firms struggling to stay afloat to lay off their workers rather than to participate in the scheme. More generally, firms face other costs than their payroll and helping them cover these costs might be necessary for existing jobs to survive. Several countries have implemented a range of policies in this regard, such as low-interest loans, rent moratoriums, or tax relief.^[16]

Even with a job retention scheme, many workers will likely be laid off and developing countries with unemployment insurance programmes will be in a better place to support these workers. However, it might be important to adjust their programmes, such as by relaxing job search requirements and extending eligibility rules. For instance, in South Africa, workers are usually eligible for one day of unemployment insurance for every six days of employment. In Brazil, many workers must accumulate up to 12 months of employment to become eligible for any benefits. Such rules could leave laid-off workers who have limited job tenure (e.g. less than a year) with little income support throughout this crisis and no other employment options in the short run.

A policy that is more common than unemployment insurance in developing countries are mandatory severance payments that firms must pay to workers at layoff. The insurance value of such lump-sum payments is limited when workers cannot find new jobs quickly. Moreover, firms facing severe reductions in cash-flow might struggle to pay what they owe to their workers and governments may need to provide firms with low-interest loans to fund severance pay obligations. Governments could also consider topping up the severance amount and spreading its payment over time to avoid workers spending it too quickly after layoff (Gerard and Naritomi, 2019).

Another common component of the social insurance system in developing countries are mandatory contributions by firms or workers to forced (illiquid) savings accounts for long-term objectives, e.g. to fund a complementary severance payment at layoff or a complementary pension at retirement. Workers could be allowed to withdraw some amount from these accounts in the current crisis. For instance, the Indian government recently allowed formal workers to withdraw up to three months worth of salary (but no more than 75% of the amount in the account) from their Employee Provident Fund.^[17] The benefits for workers from such early withdrawals might greatly exceed their costs, particularly for younger workers who will be able to replenish their forced savings accounts in coming years.

Finally, some countries have considered extending the logic of these social insurance programmes to formal (i.e. registered) self-employed workers. However, it is more challenging to determine (a) their “usual” earnings level prior to the crisis and (b) the reduction in earnings caused by the crisis. These challenges will only be exacerbated in developing countries, as governments likely have less information about these workers’ past or current earnings than in higher-income countries, even for self-employed workers who are formally registered.^[18] In this context, developing country governments may be left with fewer options:

• One option is to make unconditional monthly transfers of a fixed amount. For instance, the Auxilio Emergencial in Brazil will provide self-employed workers with a monthly payment of 60% of the minimum wage for the next three months.^[19] It might be possible to design a more fine-grained payment scheme, e.g. based on some presumptive income varying across sectors of activity. However, the costs of designing a more complicated scheme might outweigh its benefits if it leads to long delays in disbursements (as in the UK^[20]).
• A complementary option is to provide emergency low-interest credit lines for self-employed workers, allowing them to borrow a maximum amount to pay themselves in the coming months. Such policies have been recently implemented in some countries to help small and medium firms pay their workers’ wages throughout the crisis,^[21] and could be extended to self-employed workers. Repayment of loans could be made contingent on self-employed workers’ future income or gross revenue crossing above a certain threshold, to mitigate concerns of taking on more debt at this time.

Building on existing social assistance programmes

Social insurance programmes will fail to reach a large share of households in developing countries, in particular those mostly active in the informal sector of the economy. However, many of these households could be reached through social assistance programmes. For example, South Africa’s child support grant reaches many poor households who are in informal jobs and will not be covered by its job retention scheme.^[22] Maintaining these programmes throughout the crisis will already provide some minimal support to many affected households, although some of their rules might need to be adapted. These programmes could also be made temporarily more generous to compensate current beneficiaires for income losses. Finally, these programmes could be temporarily extended to new households, e.g. to households whose information was collected to target these programmes, and who were deemed ineligible. In practice, these programmes take many forms and their key features determine how they can be used in response to the crisis.

The first feature is the type of assistance that these programmes provide. Some programmes dispense cash; some provide in-kind assistance (e.g. food, fuel); others subsidize access to essential goods and services (e.g. health services, housing). In cases where supply chains are impacted or prices rise, in-kind provision will be most powerful, and public procurement will support producers as well. For instance, the Indian government doubled the monthly foodgrain (wheat and rice) household allowance and added pulses to the ration provided by the Public Distribution System.^[23] When households can buy goods and services at reasonable prices, cash transfers are quicker to implement and more fungible than in-kind transfers. Many countries have temporarily topped up the amount received by the current beneficiaries of social assistance programmes. For instance, the Indonesian government increased both the benefit amounts of its cash transfer programme (PKH) and the frequency of its payments (from quarterly to monthly).^[24] Kenya has increased the amount of its pension and orphan and vulnerable children’s grant.^[25] Finally, in the case of subsidies, the government can offer free provision or delay payments, especially for utilities that are publicly owned (e.g. electricity bills or rents). Indonesia has recently granted three months of free electricity to 24 million customers with low power connections.

The second feature is the conditionality of the social assistance. Conditional Cash Transfers (CCT) programmes are a popular form of income support in developing countries (e.g. Mexico’s Prospera or Brazil’s Bolsa Familia). They make assistance conditional on a particular behaviour encouraged by the state, e.g. enrolling children at school or immunizing them. Public works programmes are also often used for anti-poverty relief in the developing world (e.g. India’s MG-NREGS or Ethiopia’s PSNP). These conditions cannot be fulfilled at the time when countries have closed schools and public works sites because of safety, or when hospitals are overwhelmed. To provide social protection in the current crisis, CCT and public works programmes need to become temporarily unconditional. Removing conditionalities may be legally or politically difficult. For instance, India’s relief package increases the wage for MG-NREGS workers, but it makes no provision to make public work sites compatible with social distancing. Other public works programmes, such as  Ethiopia’s PSNP (Berhane et al., 2015), already provide cash or food for those identified by communities as unable to work and could perhaps extend this feature to all programme recipients.

The third feature of social assistance programmes is the population that they target. Some programmes help specific socio-demographic groups (e.g. non-contributory social pensions for the elderly or grants for orphans and children). Some provide relief to specific occupational groups (e.g. farmer drought relief funds). Others are targeted according to economic indicators, such as transfer to households deemed poor based on their assets (e.g. Indonesia’s conditional cash transfer PKH). Developing countries can leverage all their programmes simultaneously to provide assistance to a wide range of vulnerable groups. Each of these programmes suffers from inclusion errors, with resources being diverted to non-eligible households or stolen by corrupt bureaucrats, and from exclusion errors, with eligible households deterred from applying (Hanna and Olken, 2018). In these times of emergency, governments will have to rely on social assistance programmes, even if their targeting is not perfect. Direct beneficiary payments, and transparency in how much is given to whom, may help keep “fund leakages’’ under control (Muralidharan et al., 2016; Banerjee et al., 2018).

Using existing programmes to extend assistance to new beneficiaries is possible, but requires both information on potential beneficiaries and payment infrastructure to reach them. Some countries have built digital infrastructures linking governments and poor citizens for various programmes that can now be used for emergency payments (see Rutkowski et al., 2020). For example, Chile has a national ID-linked basic account for most poor people, which will be used to pay more than 2 million low-income individuals a once-off grant. India also has sent money to Jan Dhan accounts linked to the Adhaar ID system, which were created to promote financial inclusion among the poor. Other countries have detailed censuses to identify the poorest citizens for social assistance. These censuses can now be used to extend assistance to people who were initially deemed too well-off for assistance. For example, the Peruvian programme Bono Yo Me Quedo en Casa^[26] offers an additional transfer equivalent to 50% of the minimum wage to 2.7 million poor households identified in a dataset created to target the Peruvian Juntos CCT. Beneficiaries can check their availability online, and payments are routed via a national bank. In countries in which no pre-existing databases are available, or where governments would not automatically enrol large parts of the population in emergency assistance programmes, they may prefer to ask people in need of assistance to opt in. For instance, Pakistan has announced a relief package with large transfers to the poor, but the emergency programme requires people to self-identify as vulnerable and to text the existing social programme Ehsass with their national identification number.

Enrolling new beneficiaries and paying them is a challenge in many settings. In non-crisis times, enrolling people and checking eligibility may be more effective to target the poorest than automatic enrolment (Atalas et al., 2016). But enrolment systems set up in times of emergency may not necessarily target the most vulnerable efficiently.^[27] For instance, the state of Bihar in India has announced a transfer to all migrant workers stranded in other states and plans to perform identity checks through a phone app.^[28] Households recorded in the Cadastro Unico — i.e. the Brazilian census of the poor — will be eligible for the same Auxilio Emergencial as formal self-employed workers (see above), but the government also created a new website to extend coverage of this emergency assistance programme to informal workers at large. The use of these technologies may prevent individuals without a computer or smartphone from enrolling, unless complementary systems are set up. Even if they successfully enrol, transferring money to these new beneficiaries can be difficult. Relying on digital payment infrastructures is quicker and safer in an epidemic, but it might exclude particularly vulnerable households: globally, only 69% of adults have any digital bank or mobile money account; only 30% have received wages or government transfer payments directly to an account (Findex, 2017). In this context, it will be necessary to set up physical collection points or direct delivery systems for these households while still respecting social distancing measures. In Peru, bank branches were overcrowded when recipients of the Bono Yo Me Quedo en Casa programme came to cash their benefits.^[29]

Involving local governments and non-state institutions

A strategy based on expanding social insurance and building on existing social assistance programmes will likely leave important needs unmet. For instance, informal workers with volatile incomes (especially in urban areas) or with weak ties to their place of residence (e.g. migrant workers) are often beyond the reach of social insurance and usually outside the populations targeted by social assistance. A comprehensive social protection response could involve local governments and a range of non-state actors to collect better information on these unmet needs and to deliver targeted assistance.

State and municipal governments may play a complementary role to national governments, who often have the main mandate for social insurance and assistance. Many developing countries have decentralised extensively over the last decades, and have devolved a range of government functions to lower echelons of government, including responsibilities  related to social assistance. For example, the responsibility for implementing India’s employment guarantee MG-NREGS is devolved from the central government to the state, the district, the block, down to the Gram Panchayat, a local government of about 500 households. It is common for developing countries to elect or select a large cadre of leaders at very local levels. In Kenya, each village of ~120-200 households has a volunteer village leader who reports to the lowest level of paid civil servant, the assistant chief, adjudicates disputes and spreads information from the state (Orkin and Walker, 2020, Walker, 2019).

These structures can play multiple roles during this crisis. First, local structures can channel information up to decision-making structures, which is important when travel is limited. Information could be movements of people, price and availability of food, whether new social protection measures have been successfully implemented, and whether specific groups remain unexpectedly not covered. In food-insecure countries like Malawi and Ethiopia, infrastructure has been built to collect local data on food security and channel food or cash to famine-affected areas^[30] and public works programmes to food-insecure areas (Berhane et al., 2015, Beegle et al., 2017). Similarly, for public health success against ebola, it was vital that local structures relayed data back to co-ordinating structures for better decisions.^[31]

Second, local structures could be involved in the identification of individuals in dire need of additional support. They were often involved in the targeting of social assistance programmes pre-crisis, both in the gathering of information on vulnerable populations for higher levels of government and in the prioritization of assistance to the most needed.  For example, censuses of the poor used to target CCT programmes are typically updated by local administrations in Latin American countries. Rwanda is using local structures to target in-kind food security packages, which will complement its existing social protection scheme. Vulnerable households are identified at the most local (isibo) level, with information on numbers of households relayed up to higher government structures.^[32] To avoid exclusion errors, the capital city government set up a toll free line for households who reported they missed out in the targeting.^[33]

These institutions have particular strengths that may complement a national government response. They may have funding or staff already in place at local level. Local authorities often receive block grant funding to address locally identified needs, with local structures in place to monitor how it is allocated. Funding could be temporarily repurposed or these structures could be used to channel any additional funds granted. For example, the Indian government allowed state governments to use disaster funds to provide shelter and food to migrants workers.^[34] Local governments also have networks of employees (e.g. for education, health, welfare) in contact with more remote communities and able to support them in accessing services. For example, South Africa’s network of early childhood community care givers primarily conduct health promotion and prevention activities; pre-crisis, government tapped this network to assist families in enrolling for child support grants (Hatipoğlu et al., 2018).

Local governments often have better information on local needs and preferences, so may be more responsive. As a result, their decisions may have more legitimacy.  For example, in Indonesia, leaders allocating cash transfer benefits via community targeting did reasonably well in terms of targeting the poor. Communities were also more satisfied with community targeting than an externally administered proxy means test (Atalas et al., 2012). They may also be more easily held accountable to communities and may feel pressure to be more responsive, provided the resources and functions devolved to them are clearly communicated to the public (Gadenne, 2017, Martinez, 2018). For example, the state government of Bihar (India) has felt pressure to extend its attention to migrants in this crisis, a segment of the population which it does not usually serve or respond to, and which was excluded from the central government relief package. On the other hand, local structures may be more open to capture. For example, after a serious drought in 2002 in Ethiopia, community-based targeting of food transfers was targeted to households with less access to support from relatives or friends but was also twice as likely to be targeted to households with close associates in official positions (Caeyers and Dercon, 2012).

A range of non-state institutions are also particularly active in giving voice to specific groups or serving populations beyond the reach of the state. Depending on the context, these institutions may be in a unique position to gather information on the needs of specific groups, and/or be credible partners for delivering assistance in an emergency.

There are a broad range of examples of such institutions. Illegal urban settlements sometimes have recognized local leaders who facilitate access to state services and social benefits and are accountable to local populations (e.g. in urban India^[35]). Recognized local NGOs also often provide a range of services and sometimes coordinate their efforts within a geographic area under an umbrella organization (e.g. in urban Brazil^[36]); they may have years of experience being accountable to both their donors and their beneficiaries. International NGOs (e.g. BRAC, Oxfam) have a strong presence across a range of contexts. There are also private associations with specific purposes, which can, in some instances, have wide coverage. For example, 24% of Africans participated in community-organised savings groups (Findex, 2014). Membership may be even higher in rural areas: 53% of a rural Kenyan sample were members of a rotating savings group (ROSCA) (Orkin and Walker, 2020). In Ethiopia, over 90% of villagers in two separate samples are members of burial associations (Dercon et al., 2006; Bernard et al., 2014). Another type of private associations are professional organizations, which may be active in sectors that employ many  informal or poor workers. For example, India’s relief package encourages Building and Other Construction Worker Welfare Funds to provide emergency assistance.^[37]

These institutions could play a range of roles. Some will likely repurpose themselves to provide emergency assistance in the current crisis spontaneously, an effort that could be leveraged and complemented by governments. Governments could leverage their infrastructure to gather information on the needs of their many beneficiaries. Many have a network of workers in remote areas, who are already part of public health responses, e.g. an NGO trained community volunteers, religious leaders and traditional healers in Senegal to monitor for common diseases in their villages.^[38] They could be used to recruit people into government programmes in environments where communication about new programmes is difficult. For instance, Kenya used ROSCAs to enroll participants into its new health insurance scheme (Oraro and Wyss, 2018). India used National Rural Livelihood Missions and their network of Self-Help-Groups (SHG) to advertise and enrol people into many development programmes, such as rural sanitation (Swachh Bharat Mission).

It may be unusual to involve non-state actors directly in provision of state assistance, but unprecedented times may call for exploring new opportunities. Although there may be justifiable concerns about a lack of accountability, institutions with a long history and broad base of membership may be particularly resistant to the capture of transfers (Dercon et al., 2006). They already need to be locally legitimate to sustain their work, as they have no formal legal authority and are regulated largely by social sanction (Olken and Singhal, 2011). The most important concern is that community institutions remain inclusive in times of crisis and share broadly the emergency resources given to them (Gugerty and Kremer, 2008). For example, rural communities need to provide support to returning migrants rather than banning them from coming home for fear of the contagion. Another concern is that non-state institutions enrolled in social protection efforts need also be onboard with governments’ public health strategy (e.g. some religious organisations have been promoting alternative ways of dealing with the pandemic^[39]).

Conclusion

Our analysis highlights that governments in developing countries will have to find creative solutions to build a comprehensive social protection response to the economic impacts of the COVID-19 epidemic. Job retention programmes already existed in some countries (e.g. Brazil) and could be used more widely to protect employment in the formal sector.^[40] Some governments, as in Chile or India, have leveraged id-linked bank accounts opened for financial inclusion purposes to provide direct support to the poor. Even populations that live at the margins of social protection systems, like migrant workers in the informal sector who are not registered where they work, can be reached through associations that work with them (like the Aajeevika Bureau for internal migrants in India).

Yet, any government response will be imperfectly targeted, with important inclusion and exclusion errors. Government responses based on social insurance programmes may reach many formal employees and registered self-employed (although coarsely), but will miss the informal sector, which is an important part of developing countries’ workforce. Social assistance programmes allow governments to broaden the base of their response, but their targeting is always specific to a particular dimension of poverty, and their delivery is often plagued with “leakages”. Involving local governments or non-state actors to help provide assistance presents clear opportunities, but also runs the risk of resources being diverted by local elites or used for clientelism. Together, these policies may reach some households through several channels at once while leaving others with no direct support. However, in an emergency, the benefits from improving targeting and reducing leakages may not exceed the costs if an improved process leads to long delays in implementation.

Fortunately, even imperfectly targeted transfers will reach some “left-behind” households through family, informal, or formal sharing structures. Existing social protection transfers are often widely shared in families and extended networks even outside times of crisis. For instance, South African pensions received by grandparents benefit grandchildren (Duflo, 2003) and young adults in the household (Ardington et al., 2009). Households ineligible for Progresa cash transfers still get loans and gifts from eligible households in the same village and have higher food consumption (Angelucci and di Giorgi, 2009). Government could acknowledge explicitly that their emergency response will not reach all households and encourage beneficiaries to share their resources with others whom they identify as being in need, possibly subsidizing means of money transfers (e.g. reducing fees for bank or mobile money transfers^[41]). Charitable giving could be encouraged in response to the crisis and channelled to vulnerable populations (e.g. zakat funds in Muslim communities in Bangladesh before Ramadam^[42]). In fact, national funds run by governments and businesses have already raised record amounts in some countries.^[43]

The challenge of mitigating the economic effects of the pandemic is enormous. Any solution will be flawed in many ways because speed is of the essence. But governments, donors and civil societies have made major gains in the last 30 years in building infrastructure to reach the poorest. If internal and external financing can be found, developing countries can use this to create the economic space for an effective public health response.

Endnotes

[*] The authors work on social insurance, social assistance, and informal structures of risk-sharing in a range of developing countries, including Brazil, Ethiopia, India, Kenya, and South Africa. We thank Arun Advani, Sebastian Axbard, Anne Brockmeyer, Ranil Dissanayake, Simon Franklin, Lucie Gadenne, Rema Hanna, Lukas Hensel, Mahreen Khan, Julien Labonne, Lorenzo Lagos, Axel Eizmendi Larrinaga, Gianmarco Leon, Winnie Mughogho, Joana Naritomi, Paul Niehaus, Barbara Petrongolo, Simon Quinn, Moizza Sarwar, Alex Solis, and Michael Walker for their thoughtful feedback and explanations of some of the policies implemented in different countries. All remaining errors are our own.

^[1] Financial Times, 2020, “Coronavirus Tracked: The Latest Figures as the Pandemic Spreads.”

^[2] Oxford COVID-19 Government Response Tracker; Nature News, 2 April 2020, “How Poorer Countries are Scrambling to Prevent a Coronavirus Disaster.”

^[3] UNU-WIDER, 2020, “Estimates of the Impact Of Covid-19 on Global Poverty.”

^[4] See http://www.ugogentilini.net/ for the World Bank and ILO’s updated list of policies adopted worldwide.

^[5] See for instance: Time, 7 April 2020, “Fewer Doctors, Fewer Ventilators: African Countries Fear They Are Defenseless Against Inevitable Spread of Coronavirus;” Dahab et al. (2020); World Politics Review, 20 March 2020, “Refugees Are Being Ignored Amid the COVID-19 Crisis.”

^[6] Financial Times, 6 April 2020, “Iran Steps Up Support for Citizens as it Eases Coronavirus Controls.”

^[7] The Economist, 2 April 2020, “Emerging-market Lockdowns Match Rich-world Ones. The Handouts Do Not.”

^[8] IMF, 9 March 2020, “How the IMF Can Help Countries Address the Economic Impact of Coronavirus.” Hausman, R., 24 March 2020, “Flattening the COVID-19 Curve in Developing Countries.”

^[9] Le Monde, 9 April 2020, “L’Iran Met Fin Au Confinement Pour Éviter L’effondrement Économique.”

^[10] For further reading, see the articles listed at the end of the reference section.

^[11] Conflict states face additional specific challenges (e.g. Dahab et al. 2020). See also OCHA, 30 March 2020, “Pooled Funds Response To COVID-19” on co-ordinated international responses.

^[12] See G. Giupponi and C. Landais, 1 April 2020, “Building Effective Short-time Work Schemes for the Covid-19 Crisis” for a discussion of key implementation details that are likely relevant in all countries.

^[13] The Nation, 9 April 2020, “Cabinet Okays Compensation for Employees of Suspended Hotel, Lodging Businesses.”

^[14] MapNews, 26 March 2020, “Covid-19: Net Monthly Flat-rate Allowance of MAD 2,000 for Employees Declared to Social Security Fund in Temporary Work Stoppage.”

^[15] Secretaria Especial de Previdência e Trabalho, 1 April 2020, “Programa Emergencial de Manutenção do Emprego e da Renda.” Department of Labour, 26 March 2020, “Disaster Management Act: Directive: Coronavirus Covid19 Temporary Employee / Employer Relief Scheme.”

^[16] For example, Kenya has implemented several policies to relieve firms’ tax burden (see the statement by President Uhuru Kenyatta on 25 March 2020).

^[17] The Economic Times, 31 March 2020, “Finance Minister Nirmala Sitharaman Announces Rs 1.7 Lakh Crore Relief Package For Poor.”

^[18] Self-employed workers are often not required to declare their income level for tax purposes. They may have to declare their gross revenue, but this may be a poor measure of their income, e.g. if they have sizable input cost or under-reported their past revenue to minimize tax liabilities.

^[19] O Globo, 7 April, 2020, “Tire Suas Dúvidas Sobre o Auxílio Emergencial de R$ 600.”

^[20] The Guardian, 2 April 2020, “Millions in UK ‘could slip through virus wage safety net.”

^[21] South Africa, for instance, quickly made available R500 million to assist small and medium enterpises (see the statement by President Cyril Ramaphosa on 24 March 2020).

^[22]Bassier, M., J. Budlender, M. Leibbrandt, R. Zizzamia, V. Ranchhod. 31 March 2020. “South Africa Can – And Should – Top Up Child Support Grants To Avoid A Humanitarian Crisis.”

^[23] The Economic Times, 31 March 2020. “FM Nirmala Sitharaman Announces Rs 1.7 Lakh Crore Relief Package For Poor.”

^[24] Tempo.Co, 5 April 2020, “Dampak Covid-19, PKH Disalurkan Bulanan Mulai April.”

^[25] See the statement by President Uhuru Kenyatta on 25 March 2020.

^[26] The name of the programme is “Bonus I stay at home”. Labeling assistance programmes may be an effective way to induce compliance to public health policies (Benhassine et al. 2015 show that labeling a cash transfer to promote children’s education is as effective as making it conditional on enrolment).

^[27] The Conversation, 1 April 2020, “Coronavirus: How Pakistan Is Using Technology To Disperse Cash To People In Need.”

^[28] India Today, 26 March 2020, “Bihar Govt To Bear Expenses Of Migrant Workers Stranded In Other States: Nitish Kumar.”

^[29]El Comercio, 1 April 2020, “¿Cómo Saber Quiénes Más Recibirán El Bono de 380 Soles por Coronavirus en Perú?.”

^[30] The World Food Programme and United Nations Office for the Coordination of Humanitarian Affairs collaborate on early warning systems for severe food insecurity https://hungermap.wfp.org/.

^[31] See interviews with Hans Rosling: Science, 2 December 2014. “Star Statistician Hans Rosling Takes on Ebola” and https://www.youtube.com/watch?v=60H12HUAb6M.

^[32] KT Press, 29 March 2020, “Rwanda: How COVID-19 Relief Distribution Will Work.” The usual social protection also involves communities in targeting to verify that applicants for social assistance are needy (see Republic of Rwanda, 3 February 2015, “Community-led Ubudehe Categorisation Kicks Off”).

^[33] IGIHE, 6 April 2020, “Coping: Kigali City Opens 3260 Toll–free Line to Address Food Needs Inquiries.”

^[34] News18, 28 March 2020, “Govt Changes Rules to Help Migrant Workers Amid Covid-19 Lockdown, State Disaster Funds to be Used for Providing Food, Shelter.”

^[35] Ideas for India, 20 July 2017, “India’s Slum Leaders.”

^[36] E.g. https://redesdamare.org.br/br/quemsomos/coronavirus for the Mare favela in Rio de Janeiro.

^[37] Economic Times, 26 March 2020, “Realtors Say Govt’s Directive to Use Welfare Fund to Help Labourers’ to Mitigate Epidemic Loss.”

^[38] Reuters, 25 March 2020, “Using Lessons from Ebola, West Africa Prepares Remote Villages for Coronavirus.”

^[39] The Diplomat, 25 March 2020, “Sociocultural and Religious Factors Complicate India’s COVID-19 Response.” Oxfam Blogs, 27 March 2020, “Across Africa, Covid-19 Heightens Tension Between Faith and Science.”

^[40] As a response to the crisis, China has helped firms but does not seem to have protected employment (South China Morning Post, 25 March 2020, “China is Winning the Covid-19 Fight but Losing the Economic War”).

^[41] Transfer fees for Kenya’s popular mobile money system were recently waived, although for a public health reason (Finextra, 16 March 2020, “Covid-19: M-pesa Waives Fees to Discourage Cash Usage”).

^[42] Atlantic Council, 30 March 2020, “Defusing Bangladesh’s Covid-19 Time Bomb.”

^[43] South Africa’s Solidarity Fund, a partnership of government and business, has raised £85 million in two weeks, £25 million from donations from ordinary citizens (https://www.solidarityfund.co.za/; Cape Talk, 2 April 2020, “Thousands of Ordinary South Africans Have Contributed to the Solidarity Fund”). Nigeria’s similar version, run by the central bank, raised £33 million in a week. CNBC Africa, 2 April 2020, “Nigeria’s Private Sector Coalition Raises N15.3bn to Fight Covid-19.”

The post Social Protection Response to the COVID-19 Crisis: Options for Developing Countries appeared first on Economics for Inclusive Prosperity.

To avoid a social debacle and stabilize workers’ labor income during the lockdown, two broad policy tools have been tested, sometimes simultaneously: job protection through soft credits and direct subsidies to firms conditioned on avoiding layoffs and, if the crisis is such that not all jobs can be preserved, income protection through the broadening and strengthening of unemployment insurance to workers.

Is this the right policy choice? In the developed world, yes. As a recent theoretical paper analyzing the economic impact of COVIC-19 suggests, in the event of a lockdown of contact-intensive sectors, “full insurance payments to affected workers can achieve the first-best allocation”.[1] However, although job protection (as opposed to income protection) may generally hinder the efficient allocation of resources (for example, by inhibiting labor turnover to accommodate changes in technology), in times of exceptional crisis a policy based solely on income protection can lead to an excessive volume of layoffs, generating permanent collateral damages from a transitory shock. Hence, the benefits of combining both employment and unemployment subsidies in the emergency.

Is this the right policy choice in the developing world? Probably, but it is not nearly enough. There is a critical shortcoming to these income-protection policies: by definition, they only cover formal salaried workers. And, in the developing world, this accounts for half of the labor force, at best. There is an important distinction, however, within this group of exclude outsiders. Whereas informal salaried workers are an anomaly that can, in principle, be contained with better monitoring, and lower labor taxes and administrative costs, the so-called “self-employed” or independent workers, is excluded legally, by design. And there are a lot of them.

Let’s put things in perspective: whereas in OECD countries only 15% of the employed is self-employed, in Latin America this number more than doubles: independents amount to 25% of total employment in Argentina, 28% in Chile and Uruguay 28%, 30% in Brazil and Mexico, and more than 50% in Peru and Colombia.

Unlike formal salaried workers, the self-employed are fully exposed to drops in their monthly earnings –in tranquil times and, much more so, during dramatic crises.

For starters, in most countries, labor benefits are tied to jobs. This makes historical sense: those benefits are the product of decades-old struggles between activity-specific unions and business chambers and, as a result, were instrumented for union insiders and, by extension, non-unionized salaried workers in the same activity. These benefits include working hours, licenses, on-the-job training and severance payments –and social security, which still is fundamentally contributory in nature in most countries and thus restricted to formal salaried employees who contribute through payroll taxes, thus deepening the inequality in access to the pension system.[2][3]

Moreover, the income instability of the independent worker is highly procyclical: in a context of a drastic activity collapse, not only do they see their hours worked –and the associated labor income– reduced; as noted, none of the income-stabilizing measures listed above protects them, pushing the independent worker to the welfare line.

Protect people, Austrian style

In 2003, Austria implemented a reform that abolished severance payments by replacing them with occupational pension accounts to which the employer generates monthly contributions (equal to 1.53 percent of the worker’s salary) to a segregated pension account that accrues to the worker only after a layoff or a quit, thus providing some limited income protection.

More precisely, upon termination of an employment relationship, the worker owns the accumulated “portable” pension wealth, which is transferred to the new employer if the worker is re-employed. Otherwise, access to the funds is regulated to avoid depleting the pension account in good times: they are available only after three years of tenure, and could be drawn in case of a layoff, when firm and worker agree to terminate the relationship, or after the end of a temporary contract. By contrast, when the worker quits her firm (or is dismissed for misconduct), he keeps the claim but cannot withdraw the money, to avoid misuse or fraud.

This scheme can be easily extended to independent workers, in a way that allow them to save for the rainy days much in the same way as the Austrian worker does while on the job. Indeed, the Corporate Staff and Self-Employment Provision Act of January 2008 broaden the coverage of the Austrian scheme to include self-employed and freelancers. Since January 1, 2008, Austrian employers are required to pay 1.53% contributions to a self-employment provision fund for freelance employees.

More in general, one could imagine a new Regime for Independent Workers under which registered workers set a benefits account to which, for each payment that the worker receives, a proportional sum is transferred directly by the payer. How much will depend on the scope of the coverage. For example, it would be natural to allocate some money for sick and maternity leaves and holidays, in addition to unemployment insurance. It should not be difficult to establish categories by, say, a 12-month moving average of labor earnings, and to estimate declining contribution factors based for each of those brackets to account for the fact that the pension account is meant to secure an income floor. Similarly, while a time tenure may not apply in all cases, withdrawing rules can emulate the Austrian model: money from this account would be withdrawn only if the worker´s registered income in a predetermined period of time falls below a threshold level.

A “grey zone” regime: The case of faux independents

A frequent problem in countries with a high proportion of independent work is the “false” or “bogus” self-employment which refers to cases in which firms misclassify what should otherwise be an employment relationship as a relationship between a firm and an independent contractor to avoid taxes and regulations. Many workers lie in this “grey zone” between employment and self-employment: presumably, they choose when and where to work but, in reality, they are economically dependent from a unique “client” in a liaison virtually indistinguishable from formal salaried employment. These situations are often the result of deliberate illegal practices to avoid employment-related charges and hiring bans, both in the private and the public sectors –it is also close, albeit not identical, to the particular case of the drivers working for raid-hailing companies.

Addressing this loophole, many countries have extended social protection to individuals in this situation (OECD, 2019). In 2012, Portugal broaden unemployment protection to “dependent” self-employed workers. The criteria established to determine a “dependent self-employed person” was that at least 80% of the worker’s annual income has come from a single client (and in 2018, the criterion was reduced to 50%, further expanding coverage). On the other hand, Spain has a labor category called “economically dependent self-employed worker” (TRADE, for its acronym in Spanish) that allows access to social protection like health and accident insurance, pensions and unemployment benefits to workers whose income depends on a single client in more than 75%.

The strengthening of these intermediate figures is the natural way to extend benefits to faux independents and, coupled with the new regime proposed here, should fill in gaps of a labor benefits net for the whole span of independent workers.

A badly needed second best

Remedies to include no salaried workers are not without their disadvantages. For example, the Austrian model can generate financial inefficiencies: if a worker maintains a long-term relationship with an employer, funds accumulate in an occupational pension account that could otherwise be used for consumption or investment decisions. However, if the regime addresses this caveat by allowing employees to withdraw funds after a certain contribution period while still employed, excessive withdrawals may weaken the income coverage upon termination of employment –something not unusual in the Austrian experience (Hofer, Schuh & Walch, 2012). Withdrawal conditions should carefully balance these two risks.

Similarly, a “grey zone” regime can be used perversely by firms to mask salaried relationships. Eligibility criteria must be clearly defined and easily identifiable since vague definitions of “dependent self-employment” come at the risk of creating two rather than just one gray zone: one between “employees” and this “third category” of workers; and one between this “third category” and the self-employed (OECD, 2019).

That said, nothing can be more damaging to the independent worker´s wellbeing than inaction. Indeed, the COVID-19 pandemic only highlighted the huge inequalities in the safety nets between developed and developing countries, in particular, those arising from the prevalence of independent workers in the latter group. This crisis will surely widen the schism between countries and, within countries, between insiders and outsiders of the labor force. This duality should not addressed as part of the policy response to the crisis. If not, regardless of the size of the income-protection policies that developing countries can afford, disparities in labor markets will deepen the toll of the corona crisis on poverty and inequality.

Endnotes

[1] Guerrieri et al. (2020), “Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?”, NBER Working Paper No. 26918.

[2] In those cases, the employee can choose between receiving the severance payment all at once or applying it toward a future pension. See Kettemann, Kramarz & Zweimüller (2017).

[3] More recently, as countries try to mitigate this inequality by introducing a pillar of universal benefits, the divide between contributing salaried workers and non-contributing independent ones deepens the structural imbalances between contributions and benefits within the system, increasing the contingent social security debt.

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