Research Database

This paper studies the role of credit constraints in accounting for the dynamics of firm exit during the Great Recession. We present novel firm-level evidence on the role of credit constraints on exit behavior during the Great Recession. Firms in financial distress, with tighter access to credit, are more likely to default than firms with more access to credit. This difference widened substantially in the Great Recession while, in contrast, default rates did not vary much by size, age, or productivity. We identify conditions under which standard models of firms subject to financial frictions can be consistent with these facts.

In this paper, we revisit the scope for macroprudential policy in production economies with pecuniary externalities and collateral constraints. We study competitive equilibria and constrained-efficient equilibria and examine the extent to which the gap between the two depends on the production structure and the policy instruments available to the planner. We argue that macroprudential policy is desirable regardless of whether the competitive equilibrium features more or less borrowing than the constrained-efficient equilibrium. In our quantitative analysis, macroprudential taxes on borrowing turn out to be larger when the government has access to ex-post stabilization policies.

We study the nonlinearities present in a standard monetary labor search model modified to have two groups of workers facing exogenous differences in the job finding and separation rates. We use our setting to study the racial unemployment gap between Black and white workers in the United States. A calibrated version of the model is able to replicate the difference between the two groups both in the level and volatility of unemployment. We show that the racial unemployment gap rises during downturns, and that its reaction to shocks is state-dependent. In particular, following a negative productivity shock, when aggregate unemployment is above average the gap increases by 0.6pp more than when aggregate unemployment is below average. In terms of policy, we study the implications of different inflation regimes on the racial unemployment gap. Higher trend inflation increases both the level of the racial unemployment gap and the magnitude of its response to shocks.

We analyze the magnitude and persistence of the racial wealth gap using a long-run model of heterogeneous dynasties with an occupational choice and bequests. Our innovation is to introduce endogenous beliefs about risky returns, reflecting differences in dynasties' investment experiences over time. Feeding the exclusion of Black dynasties from labor and capital markets into the model as the only driving force, we find that the model quantitatively reproduces current and historical racial gaps in wealth, income, entrepreneurship, mobility, and beliefs about risky returns. We explore how the future trajectory of the racial wealth gap might change in response to various policies. Wealth transfers to all Black dynasties that eliminate the average wealth gap today do not lead to long-run wealth convergence. The logic is that centuries-long exclusions lead Black dynasties to hold pessimistic beliefs about risky returns and to forgo investment opportunities after the wealth transfer. Investment subsidies toward Black entrepreneurs are more effective than wealth transfers in permanently eliminating the racial wealth gap.

Policies that reduce information on applicants have mixed results in the labor market. However, little is known about their impact in the housing market. We submitted fictitious email inquiries to publicly advertised rentals using names manipulated on perceived race and ethnicity before and after a policy that restricted the use of background checks, eviction history, income minimums, and credit history in rental housing applications in Minneapolis. After the policy was implemented, discrimination against African American and Somali American men increased. Triple difference analysis shows that discrimination increased in Minneapolis relative to St. Paul after the policy.

This paper examines how cash transfers that are not conditional on employment affect infant health. Leveraging variation in the amount of pandemic-era stimulus and child tax credit payments that families received based on household composition, I find that an additional $100 in transfers reduces the prevalence of low birthweight by 2-3 percent. Effects are larger for payments received later in pregnancy, but are of a similar magnitude across the population. These additional resources increased prenatal care and improved maternal health in ways that are consistent with families both increasing investments in children's health and improving the prenatal environment.

This paper studies the welfare effects of encouraging rural-urban migration in the developing world. To do so, we build and analyze a dynamic general-equilibrium model of migration that features a rich set of migration motives. We estimate the model to replicate the results of a field experiment that subsidized seasonal migration in rural Bangladesh, leading to significant increases in migration and consumption. We show that the welfare gains from migration subsidies come from providing better insurance for vulnerable rural households rather than correcting spatial misallocation by relaxing credit constraints for those with high productivity in urban areas that are stuck in rural areas.

Domestic abuse encompasses a range of damaging behaviours beyond physical violence, including economic and emotional abuse. This paper provides the first evidence on the impact of cohabiting with an abusive partner on victim’s economic outcomes. In so doing, we highlight the systematic role played by economic suppression and coercive control in such relationships. Using administrative data and a matched control event study design, along with a within-individual comparison of outcomes across relationships, we document three new facts. First, women who begin relationships with (eventually) physically abusive men suffer large and significant earnings and employment falls immediately upon cohabiting with the abusive partner, which translates into a total household income loss. Second, this decline in economic outcomes is non-monotonic in women’s pre-cohabitation outside options. Third, abusive men impose economic costs on all their female partners, even those who do not report physical violence. To rationalize these findings, we develop a new dynamic model of abusive relationships where women do not perfectly observe their partner’s type, and abusive men have an incentive to use coercive control to sabotage women’s outside options and their ability to later exit the relationship. We show that this model is consistent with all three empirical facts. We harness the model’s predictions to revisit some classic results on domestic violence and show that the relationship between domestic violence and women’s outside options is crucially linked to breakup dynamics.

I develop a heterogeneous-agent New-Keynesian model featuring racial inequality in income and wealth, and studies interactions between racial inequality and monetary policy. Black and Hispanic workers gain more from accommodative monetary policy than White workers mainly due to higher labor market risks. Their gains are larger also because of a larger proportion of them are hand-to-mouth, while wealthy White workers gain more from asset price appreciation. Monetary and fiscal policies are substitutes in providing insurance against cyclical labor market risks. Racial minorities gain even more from an accommodative monetary policy in the absence of income-dependent fiscal transfers.

We show that if the central bank operates without commitment and faces constraints on its balance sheet, helicopter drops can be a useful stabilization tool during a liquidity trap. In our model, even with balance sheet constraints, helicopter drops are at best irrelevant under commitment.

Parental investments significantly impact children’s outcomes. Exploiting panel data covering individuals from birth to retirement, we estimate child skill production functions and embed them into an estimated dynastic model in which altruistic mothers and fathers make investments in their children. We find that time investments, educational investments, and assortative matching have a greater impact on generating inequality and intergenerational persistence than cash transfers. While education subsidies can reduce inequality, due to an estimated dynamic complementarity between time investments and education, it is crucial to announce them in advance to allow parents to adjust their investments when their children are young.

Past research has provided evidence of clientelistic politics in delivery of program benefits by local governments (gram panchayats (GPs)), and manipulation of GP program budgets by legislators and elected officials at upper tiers in West Bengal, India. Using household panel survey data spanning 1998-2008, we examine the consequences of clientelism for distributive equity. We find that targeting of anti-poverty programs was progressive both within and across GPs, and is explained by greater 'vote responsiveness' of poor households to receipt of welfare benefits. Across-GP allocations were more progressive than a rule-based formula recommended by the 3rd State Finance Commission (SFC) based on GP demographic characteristics. Moreover, alternative formulae for across-GP budgets obtained by varying weights on GP characteristics used in the SFC formula would have improved pro-poor targeting only marginally. Hence, there is not much scope for improving pro-poor targeting of private benefits by transitioning to formula-based budgeting.

How does wealth taxation differ from capital income taxation? When the return on investment is equal across individuals, a well-known result is that the two tax systems are equivalent. Motivated by recent empirical evidence documenting persistent return heterogeneity, we revisit this question. With heterogeneity, the two tax systems typically have opposite implications for both efficiency and inequality. Under capital income taxation, entrepreneurs who are more productive and therefore generate more income pay higher taxes. Under wealth taxation, entrepreneurs who have similar wealth levels pay similar taxes regardless of their productivity, which expands the tax base, shifts the tax burden toward unproductive entrepreneurs, and raises the savings rate of productive ones. This reallocation increases aggregate productivity and output. In the simulated model parameterized to match the US data, replacing the capital income tax with a wealth tax in a revenue-neutral fashion delivers a significantly higher average welfare. Turning to optimal taxation, the optimal wealth tax (OWT) is positive and yields large welfare gains by raising efficiency and lowering inequality. In contrast, the optimal capital income tax (OKIT) is negative—a subsidy—and delivers lower welfare gains than OWT, owing to the welfare losses from higher inequality. Furthermore, when the transition path is considered, the gains from OKIT turn into significant welfare losses for existing cohorts, whereas OWT continues to deliver robust welfare gains. These results suggest that moderate wealth taxation may be a more appealing alternative than capital income taxation, which can be significantly more distorting under return heterogeneity than under the equal-returns assumption.

Applying the Foster, Haltiwanger, and Krizan (FHK) (2001) decomposition to plant-level manufacturing data from Chile and Korea, we find that the entry and exit of plants account for a larger fraction of aggregate productivity growth during periods of fast GDP growth. To analyze this relationship, we develop a model of firm entry and exit based on Hopenhayn (1992). When we introduce reforms that reduce entry costs or reduce barriers to technology adoption into a calibrated model, we find that the entry and exit terms in the FHK decomposition become more important as GDP grows rapidly, just as they do in the data from Chile and Korea.

The epidemiological literature suggests that virus transmission occurs only when individuals are in relatively close contact. We show that if society can control the extent to which economic agents are exposed to the virus and agents can commit to contracts, virus externalities are local, and competitive equilibria are efficient. The Second Welfare Theorem also holds. These results still apply when infection status is imperfectly observed and when agents are privately informed about their infection status. If society cannot control virus exposure, then virus externalities are global and competitive equilibria are inefficient, but the policy implications are very different from those in the literature. Economic activity in this version of our model can be inefficiently low, in contrast to the conventional wisdom that viruses create global externalities and result in inefficiently high economic activity. If agents cannot commit, competitive equilibria are inefficient because of a novel pecuniary externality.

We measure the importance of increasing returns to scale and trade in medical services. Using Medicare claims data, we document that “imported” medical care—services produced by a medical provider in a different region—constitute about one-fifth of US healthcare consumption. Larger regions specialize in producing less common procedures, which are traded more. These patterns reflect economies of scale: larger regions produce higher-quality services because they serve more patients. Because of increasing returns and trade costs, policies to improve access to care face a proximity-concentration tradeoff. Production subsidies and travel subsidies can impose contrasting spillovers on neighboring regions.

This paper develops a quantitative framework to study the impact of Unemployment Insurance (UI) expansions to workers earning below eligibility thresholds. A model of how UI affects welfare and labor supply is developed and calibrated with microeconomic data, including consumption. The model predicts that the current ineligible would choose to stay on UI longer than the current eligible and the margins of why this is the case are quantified. The model is applied to the Great Recession by identifying ineligible workers in the data using machine learning and to an actual expansion during COVID-19 using administrative data. The UI duration for newly eligible under the expansion was 1.7 times longer than the previous eligible but is one-third shorter than the model's economic incentives predict. This suggests caution in extrapolating from the COVID-19 data and the model is used to predict impacts of smaller scale expansions during non-pandemic times.

Many central banks whose exchange rate regimes are classified as flexible are reluctant to let the exchange rate fluctuate. This phenomenon is known as “fear of floating”. We present a simple theory in which fear of floating emerges as an optimal policy outcome. The key feature of the model is an occasionally binding borrowing constraint linked to the exchange rate that introduces a feedback loop between aggregate demand and credit conditions. Contrary to the Mundellian paradigm, we show that a depreciation can be contractionary, and letting the exchange rate float can expose the economy to self-fulfilling crises.

We develop a theory of labor markets in a monetary economy with four realistic features: search frictions, worker productivity shocks, wage rigidity, and two-sided lack of commitment. Due to the non-Coasean nature of labor contracts, inefficient job separations occur in the form of endogenous quits and layoffs that are unilaterally initiated whenever a worker’s wage-to-productivity ratio moves outside an inaction region. We derive sufficient statistics for the aggregate labor market response to a monetary shock based on the distribution of workers’ wage-to-productivity ratios. These statistics crucially depend on the incidence of inefficient job separations, which we show how to identify using readily available microdata on wage changes and worker flows between jobs.

We re-examine recent trends in regional income convergence, considering the full distribution of income rather than focusing on the mean. Measuring similarity by comparing each percentile of state distributions to the corresponding percentile of the national distribution, we find that state incomes have become less similar (i.e. they have diverged) within the top 20 percent of the income distribution since 1969. The top percentile alone accounts for more than half of aggregate divergence across states over this period by our measure, and the top five percentiles combine to account for 93 percent. Divergence in top incomes across states appears to be driven largely by changes in top incomes among White people, while top incomes among Black people have experienced relatively little divergence.

We study the COVID-19 epidemic in emerging markets that face financial frictions and its mitigation through social distancing and vaccination. We find that restricted vaccine availability in emerging markets, as captured by limited quantities and high prices, renders the pandemic exceptionally costly in these countries, compared with economies without financial frictions. Improved access to financial markets enables a better response to the delay in vaccine supplies, as it supports more stringent social distancing measures before wider vaccine availability. We show that financial assistance programs to such financially constrained countries can increase vaccinations and lower fatalities, at no present-value cost to the international community.

We develop a model of banking industry dynamics to study the quantitative impact of regulatory policies on bank risk taking and market structure. Since our model is matched to U.S. data, we propose a market structure where big banks with market power interact with small, competitive fringe banks as well as non-bank lenders. Banks face idiosyncratic funding shocks in addition to aggregate shocks which affect the fraction of performing loans in their portfolio. A nontrivial bank size distribution arises out of endogenous entry and exit, as well as banks' buffer stock of capital. We show the model predictions are consistent with untargeted business cycle properties, the bank lending channel, and empirical studies of the role of concentration on financial stability. We find that regulatory policies can have an important impact on banking market structure, which, along with selection effects, can generate changes in allocative efficiency and stability.

We present a simple open economy framework to study the transmission channels of monetary and macroprudential policies and evaluate the implications for international spillovers and global welfare. Using an analytical decomposition, we first identify three transmission channels: intertemporal substitution, expenditure switching, and aggregate income. Quantitatively, expenditure switching plays a prominent role for monetary policy, while macroprudential policy operates almost entirely through intertemporal substitution. Turning to the normative analysis, we show that the risk of a liquidity trap generates a monetary policy tradeoff between stabilizing output today and reducing capital flows to lower the likelihood of a future recession. However, leaning against the wind is not necessarily optimal, even in the absence of capital controls. Finally, we argue that contrary to emerging policy concerns, capital controls are not beggar-thy-neighbor and can enhance global macroeconomic stability.

We review methods used to numerically compute optimal Mirrleesian tax and transfer schedules in heterogeneous agent economies. We show that the coarseness of the productivity grid, while a technical detail in terms of theory, is critical for delivering quantitative policy prescriptions. Existing methods are reliable only when a very fine grid is used. The problem is acute for computational approaches that use a version of the Diamond-Saez implicit optimal tax formula. If using a very fine grid for productivity is impractical, then optimizing within a flexible parametric class is preferable to the non-parametric Mirrleesian approach.

This paper studies lockdown policy in a dynamic economy without government commitment. Lockdown imposes a cap on labor supply, which improves health prospects at the cost of economic output and consumption. A government would like to commit to the extent of future lockdowns in order to guarantee an economic outlook that supports efficient levels of investment into intermediate inputs. However, such a commitment is not credible, since investments are sunk at the time when the government chooses a lockdown. As a result, lockdown under lack of commitment deviates from the optimal policy. Rules that limit a government’s lockdown discretion can improve social welfare, even in the presence of noncontractible information. Quantitatively, lack of commitment causes lockdown to be significantly more severe than is socially optimal. The output and consumption loss due to lack of commitment is greater for higher intermediate input shares, higher discount rates, higher values of life, higher disease transmission rates at and outside of work, and longer vaccine arrival times.

We revisit the estimation of the welfare costs of inflation originating from lack of liquidity satiation. We use data for the United States and several other developed countries. Our computations are heavily influenced by the recent experience of very low, even negative, short-term rates observed in the countries we study. We obtain estimates that range between 0.20% and 1.5% of lifetime consumption for the United States and find even higher values for some European countries.

We develop a theory of exchange rate fluctuations arising from financial institutions’ demand for dollar liquid assets. Financial flows are unpredictable and may leave banks “scrambling for dollars.” Because of settlement frictions in interbank markets, a precautionary demand for dollar reserves emerges and gives rise to an endogenous convenience yield on the dollar. We show that an increase in the dollar funding risk leads to a rise in the convenience yield and an appreciation of the dollar, as banks scramble for dollars. We present empirical evidence on the relationship between exchange rate fluctuations for the G10 currencies and the quantity of dollar liquidity, which is consistent with the theory.

Iovino, La’O and Mascarenhas (forthcoming) ask two important questions regarding the optimal conduct of monetary policy: Should the central bank’s policy depend on information the central bank has that is not available to markets? And should the central bank disclose information that it has but market participants do not? Iovino, La’O and Mascarenhas answer these questions using a simple, stylized model with one-period price stickiness. They show that efficient equilibria can be sustained regardless of whether policy depends on the central bank’s information and regardless of its disclosure policy. We explain the logic behind their irrelevance result and show that if restrictions are imposed on equilibria, then monetary policy should in general depend on the central bank’s information. Finally, we offer some speculative answers to their questions and discuss the sense in which policy is converging towards theory.

We provide a simple framework to study the prudential use of capital controls and currency reserves that have been explored in the recent literature. We cover the role of both pecuniary externalities and aggregate demand externalities. The model features a central policy dilemma for emerging economies facing large capital outflows: the choice between increasing the policy rate to stabilize the exchange rate and decreasing the policy rate to stabilize employment. Ex ante capital controls and reserve accumulation can help mitigate this dilemma. We use our framework to survey the recent literature and provide an overview of recent empirical findings on the use of these policies.

It is well known that monetary and fiscal policy are connected by a common budget constraint. In this paper, we study how this manifests itself in the context of the Eurozone, where that connection links the European Central Bank, the 19 national central banks, the Treasuries of 19 countries, and the European Union. Our goal is twofold. First, we wish to clarify how seigniorage flows from the monetary authority to the budget of each country. Second, we seek to answer the question of how the taxpayers of each country are affected by a default of one of the participants to the union. In answering this question, we analyze the mechanisms that ensure (or do not ensure) that net liabilities across countries stay bounded, and we establish how the answer depends on the liquidity premium that each category of assets commands (cash, excess reserves within the Eurosystem, and government bonds). We find that the official risk-sharing provisions of the policy of quantitative easing (QE), whereby national central banks retain 90% of the risk intrinsic in bonds of their own country, only holds under restrictive assumptions; under plausible scenarios, a significantly larger fraction of the risk is mutualized.

We develop a restart algorithm based on Scarf’s (1973) algorithm for computing approximate Brouwer fixed points. We use the algorithm to compute all of the equilibria of a general equilibrium pure-exchange model with four consumers, four goods, and 15 equilibria. The mathematical result that motivates the algorithm is a fixed-point index theorem that provides a sufficient condition for uniqueness of equilibrium and a necessary condition for multiplicity of equilibria. Examining the structure of the model with 15 equilibria provides us with a method for constructing higher dimensional models with even more equilibria. For example, using our method, we can construct a pure-exchange economy with eight consumers and eight goods that has (at least) 255 equilibria.

The appendix accompanies Staff Report 581: Optimal Cooperative Taxation in the Global Economy.

We show that explicitly modeling primary commodities in an otherwise totally standard incomplete markets open economy model can go a long way in explaining the Mussa puzzle and the Backus-Smith puzzle, two of the main puzzles in the international economics literature.

We develop a framework with rich worker heterogeneity, firm monopsony power, and putty-clay technology to study the distributional impact of the minimum wage in the short and long run. Our production technology is disciplined to be consistent with the small estimated employment effects of the minimum wage in the short run and the large estimated elasticities of substitution across inputs in the long run. We find that in the short run, a large increase in the minimum wage has a small effect on employment and therefore increases the labor income of the workers who were earning less than the new minimum wage. In the long run, however, the minimum wage has perverse distributional implications in that it reduces the employment, income, and welfare of precisely the low-income workers it is meant to help. Nonetheless, these long-run effects take time to fully materialize because firms slowly adjust their mix of inputs. Existing transfer programs, such as the earned income tax credit (EITC), are more effective at improving long-run outcomes for workers at the low end of the wage distribution. But combining existing programs with a modest increase in the minimum wage generates even larger welfare gains for low-earning workers.

We consider an economy with perpetual youth and inelastic labor supply that grows endogenously. Consumers are subject to idiosyncratic capital accumulation risk and markets are incomplete. The government purchases consumption goods, makes transfers in the form of baby bonds, and it can use consumption and wealth taxes. The wealth distribution is given in closed form. When the intertemporal elasticity of substitution ɛ is equal to 1, the government can run a permanent primary deficit, up to a finite upper bound, if the coefficient of relative risk aversion is high enough and the factor share of labor is not too close to 1. This causes the risk-free rate r to be below the growth rate g of the economy. But the government can implement Pareto improvements when r - g does not exceed zero by enough. If ɛ ≠ 1, then there may not be an upper bound on the permanent primary deficits of the government. If ɛ Є (0,1), this happens when the economy is relatively unproductive, and then taking deficits to be very large makes all consumers worse off. If ɛ Є (1,∞), very large deficits are possible if the economy is sufficiently productive, and then they imply unbounded Pareto improvements.

This paper posits an information channel as the explanation for sudden inflations. Consumers saving via nominal government bonds face a choice whether to acquire costly information about future government surpluses. They trade off the cost of acquiring information about the surpluses that back bond repayment against the benefit of a more informed saving decision. Through the information channel, small changes in the economic environment can trigger large responses in consumers' behavior and prices. This setting explains why there can be long stretches of time during which government surpluses have large movements with little inflation response; yet, at some point, something snaps, and a sudden inflation takes off that is strongly responsive to incoming fiscal news.

Are unregulated capital flows excessive during a stagflation episode? We argue that they likely are, owing to a macroeconomic externality operating through the economy’s supply side. Inflows raise domestic wages through a wealth effect on labor supply and cause unwelcome upward pressure on marginal costs in countries where monetary policy is trying to drive down costs to stabilize inflation. Yet, market forces are likely to generate such inflows. Optimal capital flow management instead requires net outflows, suggesting topsy-turvy capital flows following markup shocks.

How should countries cooperate in setting fiscal and trade policies when government expenditures must be financed with distorting taxes? We show that even if countries cannot make explicit transfers to each other, every point on the Pareto frontier is production efficient, so that international trade and capital flows should be effectively free. Trade agreements must be supplemented with fiscal policy agreements. Residence-based income tax systems have advantages over source-based systems. Taxing all household asset income at a country-specific uniform rate and setting the corporate income tax to zero yield efficient outcomes. Value-added taxes should be adjusted at the border.

In the United States, both taxes and old age Social Security benefits depend on one's marital status and tend to discourage the labor supply of the secondary earner. To what extent are these provisions holding back female labor supply? We estimate a rich life cycle model of labor supply and savings for couples and singles using the method of simulated moments (MSM) on the 1945 and 1955 birth-year cohorts and use it to evaluate what would happen without these provisions. Our model matches well the life cycle profiles of labor market participation, hours, and savings for married and single people and generates plausible elasticities of labor supply. Eliminating marriage-related provisions drastically increases the participation of married women over their entire life cycle, reduces the participation of married men after age 60, and increases the savings of couples in both cohorts, including the later one, which has similar participation to that of more recent generations. If the resulting government surplus were used to lower income taxation, there would be large welfare gains for the vast majority of the population.

Between 1880 and 1920, the US agricultural employment share fell from 50% to 25%. However, despite aggregate demand shifting away from their sector of specialization, rural labor markets saw faster wage growth and industrialization than non-agricultural parts of the US. We propose a spatial model of the structural transformation to analyze the link between aggregate structural change and local economic development. The calibrated model shows that rural areas adapted to the decline of the agricultural sector by adopting technologies already in use in urban locations. Without such catchup growth, economic development would have been urban-biased and spatial inequality would have increased.

In this paper, we ask how to best allocate a given time-varying supply of vaccines across individuals of different ages during the second phase of the Covid-19 pandemic . Building on our previous heterogeneous household model of optimal economic mitigation and redistribution (Glover et al., 2021), we contrast the actual vaccine deployment path, which prioritized older, retired individuals, with one that first vaccinates younger workers. Vaccinating the old first saves more lives but slows the economic recovery, relative to inoculating the young first. Vaccines deliver large welfare benefits in both scenarios (relative to a world without vaccines), but the old-first policy is optimal under a utilitarian social welfare function. The welfare gains from having vaccinated the old first are especially significant once the economy is hit by a more infectious Delta variant in the summer of 2021.

We investigate the credibility of central bank research by searching for traces of researcher bias, which is a tendency to use undisclosed analytical procedures that raise measured levels of statistical significance (stars) in artificial ways. To conduct our search, we compile a new dataset and borrow 2 bias-detection methods from the literature: the p-curve and z-curve. The results are mixed. The p-curve shows no traces of researcher bias but has a high propensity to produce false negatives. The z-curve shows some traces of researcher bias but requires strong assumptions. We examine those assumptions and challenge their merit. At this point, all that is clear is that central banks produce results with patterns different from those in top economic journals, there being less bunching around the 5 per cent threshold of statistical significance.

Declining search frictions generate productivity growth by allowing workers to find jobs for which they are better suited. The return of declining search frictions on productivity varies across different types of workers. For workers who are "jacks of all trades" in the sense that their productivity is nearly independent from the distance between their skills and the requirements of their job—declining search frictions lead to minimal productivity growth. For workers who are "masters of one trade" in the sense that their productivity is very sensitive to the gap between their individual skills and the requirements of their job—declining search frictions lead to fast productivity growth. As predicted by this view, we find that workers in routine occupations have low wage dispersion and growth, while workers in non-routine occupations have high wage dispersion and growth.

Because firms invest heavily in R&D, software, brands, and other intangible assets—at a rate close to that of tangible assets—changes in GDP, which does not include all intangible investments, understate the actual changes in total output. If labor inputs are more precisely measured, then it is possible to observe little change in measured total factor productivity (TFP) coincidentally with large changes in hours and investment. The output mismeasurement leaves business cycle modelers with large and unexplained labor wedges accounting for most of the fluctuations in aggregate data. To address this issue, I incorporate intangible investments into a multi-sector general equilibrium model and use data from an updated U.S. input and output table to parameterize income and cost shares, with intangible investments reassigned from intermediate to final uses. I employ maximum likelihood methods and quarterly observations on sectoral gross outputs for the United States to estimate processes for latent sectoral TFPs that have common and sector-specific components. I do not use aggregate hours to estimate TFPs but find that the predicted hours series compares closely with the actual series and accounts for roughly two-thirds of its standard deviation. I find that sector-specific shocks and industry linkages play an important role in accounting for fluctuations and comovements in aggregate and industry-level U.S. data, and I find that at business-cycle frequencies, the model's common component of TFP is not correlated with the standard measures of aggregate TFP used in the macroeconomic literature. Adding financial frictions and stochastic shocks to financing constraints has a negligible impact on the results.

We develop a conceptual framework for analyzing the interactions between aggregate fiscal policy and monetary policy. The framework draws on existing models that analyze sovereign debt crises and balance-of-payments crises. We intend this framework as a guide for analyzing the monetary and fiscal history of a set of eleven major Latin American countries—Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Mexico, Paraguay, Peru, Uruguay, and Venezuela—from the 1960s until now.

We develop a theory of sweat equity—the value of business owners' time and expenses to build customer bases, client lists, and other intangible assets. We discipline the theory using data from U.S. national accounts, business censuses, and brokered sales to estimate a value for sweat equity in the private business sector equal to 1.2 times U.S. GDP, which is about the same magnitude as the value of fixed assets in use in these businesses. For a typical owner, 26 percent of the sweat equity is transferable through inheritance or sale. The equity values are positively correlated with business incomes and standard measures of markups based on accounting data, but not with owners' financial assets or standard measures of business total factor productivity. We use our theory to show that abstracting from sweat activity leads to a significant understatement of the impacts of lowering business income tax rates on private business activity for both the extensive and intensive margins. Despite finding larger responses, our model's implied tax elasticities of establishments and owner hours are in line with empirical estimates in the public finance literature. Allowing for financial constraints and superstar firms does not overturn our main findings.

This paper evaluates the role of rising income inequality in explaining observed growth in college tuition. We develop a competitive model of the college market, in which college quality depends on instructional expenditure and the average ability of admitted students. An innovative feature of our model is that it allows for a continuous distribution of college quality. We find that observed increases in US income inequality can explain more than half of the observed rise in average net tuition since 1990 and that rising income inequality has also depressed college attendance.

Although a credit tightening is commonly recognized as a key determinant of the Great Recession, to date, it is unclear whether a worsening of credit conditions faced by households or by firms was most responsible for the downturn. Some studies have suggested that the household-side credit channel is quantitatively the most important one. Many others contend that the firm-side channel played a crucial role. We propose a model in which both channels are present and explicitly formalized. Our analysis indicates that the household-side credit channel is quantitatively more relevant than the firm-side credit channel. We then evaluate the relative benefits of a fixed-sized transfer to households and to firms that improves each group's access to credit. We find that the effects of such a transfer on employment are substantially larger when the transfer targets households rather than firms. Hence, we provide theoretical and quantitative support to the view that the employment decline during the Great Recession would have been less severe if instead of focusing on easing firms' access to credit, the government had expended an equal amount of resources to alleviate households' credit constraints.

This paper studies asset pricing and labor market dynamics when idiosyncratic risk to human capital is not fully insurable. Firms use long-term contracts to provide insurance to workers, but neither side can fully commit; furthermore, owing to costly and unobservable retention effort, worker-firm relationships have endogenous durations. Uninsured tail risk in labor earnings arises as a part of an optimal risk-sharing scheme. In equilibrium, exposure to the tail risk generates higher aggregate risk premia and higher return volatility. Consistent with data, firm-level labor share predicts both future returns and pass-throughs of firm-level shocks to labor compensation.

We extend the baseline Susceptible-Exposed-Infectious-Recovered (SEIR) infectious disease epidemiology model to understand the role of testing and case-dependent quarantine. Our model nests the SEIR model. During a period of asymptomatic infection, testing can reveal infection that otherwise would only be revealed later when symptoms develop. Along with those displaying symptoms, such individuals are deemed known positive cases. Quarantine policy is case-dependent in that it can depend on whether a case is unknown, known positive, known negative, or recovered. Testing therefore makes possible the identification and quarantine of infected individuals and release of non-infected individuals. We fix a quarantine technology - a parameter determining the differential rate of transmission in quarantine - and compare simple testing and quarantine policies. We start with a baseline quarantine-only policy that replicates the rate at which individuals are entering quarantine in the US in March, 2020. We show that the total deaths that occur under this policy can be achieved under looser quarantine measures and a substantial increase in random testing of asymptomatic individuals. Testing at a higher rate in conjunction with targeted quarantine policies can (i) dampen the economic impact of the coronavirus and (ii) reduce peak symptomatic infections - relevant for hospital capacity constraints. Our model can be plugged into richer quantitative extensions of the SEIR model of the kind currently being used to forecast the effects of public health and economic policies.

The prevailing neo-Wicksellian view holds that the central bank's objective is to track the natural rate of interest (r *), which itself is largely exogenous to monetary policy. We challenge this view using a fixed-cost model of durable consumption demand, in which expansionary monetary policy prompts households to accelerate purchases of durable goods. This yields an intertemporal trade-off in aggregate demand as encouraging households to increase durable holdings today leaves fewer households acquiring durables going forward. Interest rates must be kept low to support demand going forward, so accommodative monetary policy today reduces r * in the future. We show that this mechanism is quantitatively important in explaining the persistently low level of real interest rates and r * after the Great Recession.

Recent critiques have demonstrated that existing attempts to account for the unemployment volatility puzzle of search models are inconsistent with the procylicality of the opportunity cost of employment, the cyclicality of wages, and the volatility of risk-free rates. We propose a model that is immune to these critiques and solves this puzzle by allowing for preferences that generate time-varying risk over the cycle, and so account for observed asset pricing fluctuations, and for human capital accumulation on the job, consistent with existing estimates of returns to labor market experience. Our model reproduces the observed fluctuations in unemployment because hiring a worker is a risky investment with long-duration surplus flows. Intuitively, since the price of risk in our model sharply increases in recessions as observed in the data, the benefit from creating new matches greatly drops, leading to a large decline in job vacancies and an increase in unemployment of the same magnitude as in the data.

This paper describes interactions between monetary and fiscal policies that affect equilibrium price levels and interest rates by critically surveying theories about (a) optimal anticipated inflation, (b) optimal unanticipated inflation, and (c) conditions that secure a "nominal anchor" in the sense of a unique price level path. We contrast incomplete theories whose inputs are budget-feasible sequences of government issued bonds and money with complete theories whose inputs are bond-money strategies described as sequences of functions that map time t histories into time t government actions. We cite historical episodes that conform the theoretical insight that lines of authority between a Treasury and a Central Bank can be ambiguous, obscure, and fragile.

Using a novel meta-analytical method, Brodeur et al. (2016) argue that hypothesis tests in top economic journals have exaggerated levels of statistical significance. Brodeur et al. (2020) apply the same method to another sample of hypothesis tests, obtaining similar results. We investigate the reliability of the method by highlighting questionable assumptions and compiling a dataset to examine their merits. Our findings support the original conclusions.

In this paper, we review the relationship between inflation rates, nominal interest rates, and rates of growth of monetary aggregates for a large group of OECD countries. If persistent changes in the monetary policy regime are accounted for, the behavior of these series maintains the close relationship predicted by standard quantity theory models. With an estimated model, we show those relationships to be relatively invariant to alternative frictions that can deliver quite different high-frequency dynamics. We also show that the low-frequency component of the data derived from statistical filters does reasonably well in capturing these regime changes. We conclude that the quantity theory relationships are alive and well, and thus they are useful for policy design aimed at controlling inflation.

We develop an ECON-EPI network model to evaluate policies designed to improve health and economic outcomes during a pandemic. Relative to the standard epidemiological SIR set-up, we explicitly model social contacts among individuals and allow for heterogeneity in their number and stability. In addition, we embed the network in a structural economic model describing how contacts generate economic activity. We calibrate it to the New York metro area during the 2020 COVID-19 crisis and show three main results. First, the ECON-EPI network implies patterns of infections that better match the data compared to the standard SIR. The switching during the early phase of the pandemic from unstable to stable contacts is crucial for this result. Second, the model suggests the design of smart policies that reduce infections and at the same time boost economic activity. Third, the model shows that reopening sectors characterized by numerous and unstable contacts (such as large events or schools) too early leads to fast growth of infections.

Today, monopolies inflict great harm on low- and middle-income Americans. One particularly pernicious way they harm them is by sabotaging low-cost products that are substitutes for the monopoly products. I'll argue that the U.S. housing crisis, legal crisis, and oral health crisis facing the low- and middle-income Americans are, in large part, the result of monopolies destroying low-cost alternatives in these industries that the poor would purchase. These results would not surprise those studying monopolies in the first half of the 20th century. During this period extensive evidence was developed showing monopolies engaging in these same activities and many others that harmed the poor. Models of monopoly were constructed by giants in economics and law, such as Henry Simons and Thurman Arnold, to explain these impacts of monopoly. These models are of sabotaging monopolies. Unfortunately, in the 1950s, the economics profession turned its back on this evidence, these models and these giants. It embraced the Cournot model of monopoly, that found in textbooks today. In this model the monopolist chooses its price, nothing more. Gone are the decisions on whether to sabotage substitutes or to employ any of the other weapons at the disposal of sabotaging monopolies. I'll call this Cournot monopoly the toothless monopoly. Using this model, the economics profession has concluded that the costs of monopoly are small. But the toothless monopoly model is ill-equipped to study the "costs of monopoly." By relying on it, the economics profession has made major errors in its study of monopoly.

We develop a simple dynamic economic model of epidemic transmission designed to be consistent with widely used SIR biological models of the transmission of epidemics, while incorporating economic benefits and costs as well. Our main finding is that targeted testing and isolation policies deliver large welfare gains relative to optimal policies when these tools are not used. Specifically, we find that when testing and isolation are not used, optimal policy delivers a welfare gain equivalent to a 0.6% permanent increase in consumption relative to no intervention. The welfare gain arises because under the optimal policy, the planner engineers a sharp recession that reduces aggregate output by about 40% for about 3 months. This sharp contraction in economic activity reduces the rate of transmission and reduces cumulative deaths by about 0.1%. When testing policies are used, optimal policy delivers a welfare gain equivalent to a 3% permanent increase in consumption. The associated recession is milder in that aggregate output declines by about 15% and cumulative deaths are reduced by .3%. Much of this welfare gain comes from isolating infected individuals. When individuals who are suspected to be infected are isolated without any testing, optimal policy delivers a welfare gain equivalent to a 2% increase in permanent consumption.

Studying the modern economic histories of eleven of the largest countries in Latin America teaches us that a lack of fiscal discipline has been at the root of most of the region's macroeconomic instability. The lack of fiscal discipline, however, takes various forms, not all of them measured in the primary deficit. Especially important have been implicit or explicit guarantees to the banking system; denomination of the debt in US dollars and short maturity of the debt; and transfers to some agents in the private sector, which are large in times of crisis and are not part of the budget approved by the national congresses. Comparing the histories of our eleven countries, we see that rather than leading to an economic contraction, fiscal stabilization generally leads to growth. On the other hand, rising commodity prices are no guarantee of economic growth, nor are falling commodity prices a guarantee of economic contraction.

I present a behavioral epidemiological model of the evolution of the COVID epidemic in the United States and the United Kingdom over the past 12 months. The model includes the introduction of a new, more contagious variant in the UK in early fall and the US in mid December. The model is behavioral in that activity, and thus transmission, responds endogenously to the daily death rate. I show that with only seasonal variation in the transmission rate and pandemic fatigue modeled as a one-time reduction in the semi-elasticity of the transmission rate to the daily death rate late in the year, the model can reproduce the evolution of daily and cumulative COVID deaths in the both countries from Feb 15, 2020 to the present remarkably well. I find that most of the end-of-year surge in deaths in both the US and the UK was generated by pandemic fatigue and not the new variant of the virus. I then generate forecasts for the evolution of the epidemic over the next two years with continuing seasonality, pandemic fatigue, and spread of the new variant.

Education services in the United States are determined predominantly by non-market institutions, the rules of which are defined by state constitutions. This paper empirically examines the effect of changes in constitutional provisions on education outcomes in the United States. To show causal effects, we exploit discontinuities in the procedure for adopting constitutional amendments to compare outcomes when an amendment passed with those when an amendment failed. Our results show that adoption of an amendment results in higher per-pupil expenditure, higher teacher salaries, smaller class size, and improvements in reading and math test scores. We examine the underlying mechanism driving these results by studying the actions of the legislature and the courts after an amendment is passed. We find that, on average, the legislature responds with a one-year lag in enacting education policies satisfying the minimum standards imposed by the amendment, and there is no increase in the number of education cases reaching appellate courts. Using school finance reforms, we also show that in situations where the legislature fails to enact education policies, courts intervene to enforce constitutional standards to improve outcomes. This enforcement mechanism is more impactful in states that have higher constitutional minimum standards. Taken together, the causal effects on education outcomes and the patterns in legislative bill enactments and court cases provide a novel test of the hypothesis that a strong constitutional provision improves the bargaining position of citizens vis-à-vis that of elected leaders. If citizens do not receive education services as mandated in the constitution, they can seek remedy in court.

This paper examines the reliability of widely used surveys on U.S. businesses. We compare survey responses of business owners with administrative data and document large inconsistencies in business incomes, receipts, and the number of owners. We document problems due to nonrepresentative samples and measurement errors. Nonrepresentativeness is reflected in undersampling of owners with low incomes. Measurement errors arise because respondents do not refer to relevant documents and possibly because of framing issues. We discuss implications for statistics of interest, such as business valuations and returns. We conclude that predictions based on current survey data should be treated with caution.

We show that a simple model of COVID-19 that incorporates feedback from disease prevalence to disease transmission through an endogenous response of human behavior does a remarkable job fitting the main features of the data on the growth rates of daily deaths observed across a large number countries and states of the United States from March to November of 2020. This finding, however, suggests a new empirical puzzle. Using an accounting procedure akin to that used for Business Cycle Accounting as in Chari et al. (2007), we show that when the parameters of the behavioral response of transmission to disease prevalence are estimated from the early phase of the epidemic, very large wedges that shift disease transmission rates holding disease prevalence fixed are required both across regions and within a region over time for the model to match the data on deaths from COVID-19 as an equilibrium outcome exactly. We show that these wedges correspond to large shifts in model forecasts for the long-run attack rate of COVID-19 both across locations and over time. Future research should focus on understanding the sources in these wedges in the relationship between disease prevalence and disease transmission.

This online appendix accompanies Staff Report 560: Sweat Equity in U.S. Private Business.

In this appendix, we provide details on the data sources and construction of variables for our analysis in "What Do Survey Data Tell Us about U.S. Businesses?" We also include the auxiliary tables and figures omitted from the main text.

We develop and calibrate an overlapping generations general equilibrium model of the U.S. economy with heterogeneous consumers who face idiosyncratic earnings and health risk to study the implications of exogenous trends in increasing college attainment, decreasing fertility, and increasing longevity between 2005 and 2100. While all three trends contribute to a higher old age dependency ratio, increasing college attainment has different macroeconomic implications because it increases labor productivity. Decreasing fertility and increasing longevity require the government to increase the average labor tax rate from 32.0 to 44.4 percent. Increasing college attainment lowers the required tax increase by 10.1 percentage points. The required tax increase is higher under general equilibrium than in a small open economy with a constant interest rate because the reduction in the interest rate lowers capital income tax revenues.

We provide new time-varying estimates of the housing wealth effect back to the 1980s. We use three identification strategies: OLS with a rich set of controls, the Saiz housing supply elasticity instrument, and a new instrument that exploits systematic differences in city-level exposure to regional house price cycles. All three identification strategies indicate that housing wealth elasticities were if anything slightly smaller in the 2000s than in earlier time periods. This implies that the important role housing played in the boom and bust of the 2000s was due to larger price movements rather than an increase in the sensitivity of consumption to house prices. Full-sample estimates based on our new instrument are smaller than recent estimates, though they remain economically important. We find no significant evidence of a boom-bust asymmetry in the housing wealth elasticity. We show that these empirical results are consistent with the behavior of the housing wealth elasticity in a standard life-cycle model with borrowing constraints, uninsurable income risk, illiquid housing, and long-term mortgages. In our model, the housing wealth elasticity is relatively insensitive to changes in the distribution of LTV for two reasons: First, low-leverage homeowners account for a substantial and stable part of the aggregate housing wealth elasticity; Second, a rightward shift in the LTV distribution increases not only the number of highly sensitive constrained agents but also the number of underwater agents whose consumption is insensitive to house prices.

We use a simple random growth model to study the role of changing dynamics of family firms in shaping the evolution of top wealth shares in the United States over the course of the past century. Our model generates a time path for top wealth shares. The path is remarkably similar to those found by Saez and Zucman (2016) and Gomez (2019) when the volatility of idiosyncratic shocks to the value of family firms is similar to that found for public firms by Herskovic, Kelly, Lustig, and Van Nieuwerburgh (2016). We also show that consideration of family firms contributes not only to overall wealth inequality but also to considerable upward and downward mobility of families within the distribution of wealth. We interpret our results as indicating that improving our understanding of how families found new firms and eventually diversify their wealth is central to improving our understanding of the distribution of great wealth and its evolution over time.

We assess the economic value of screening testing programs as a policy response to the ongoing COVID-19 pandemic. We find that the fiscal, macroeconomic, and health benefits of rapid SARS-CoV-2 screening testing programs far exceed their costs, with the ratio of economic benefits to costs typically in the range of 2-15 (depending on program details), not counting the monetized value of lives saved. Unless the screening test is highly specific, however, the signal value of the screening test alone is low, leading to concerns about adherence. Confirmatory testing increases the net economic benefits of screening tests by reducing the number of healthy workers in quarantine and by increasing adherence to quarantine measures. The analysis is undertaken using a behavioral SIR model for the United States with 5 age groups, 66 economic sectors, screening and diagnostic testing, and partial adherence to instructions to quarantine or to isolate.

To understand how best to combat COVID-19, we must understand how deadly is the disease. There is a substantial debate in the epidemiological literature as to whether the fatality rate is 1% or 0.1% or somewhere in between. In this note, I use an SIR model to examine why it is difficult to estimate the fatality rate from the disease and how long we might have to wait to resolve this question absent a large-scale randomized testing program. I focus on uncertainty over the joint distribution of the fatality rate and the initial number of active cases at the start of the epidemic around January 15, 2020. I show how the model with a high initial number of active cases and a low fatality rate gives the same predictions for the evolution of the number of deaths in the early stages of the pandemic as the same model with a low initial number of active cases and a high fatality rate. The problem of distinguishing these two parameterizations of the model becomes more severe in the presence of effective mitigation measures. As discussed by many, this uncertainty could be resolved now with large-scale randomized testing.

This online appendix accompanies Staff Report 620: Star Wars at Central Banks.

Supplemental data and code for replication.

This appendix contains the pre-registered analysis for our comment on “Star Wars: The Empirics Strike Back” by Brodeur et al (2016). To structure the analysis, we reproduce the pre-registration; our results appear in red under each of the relevant parts. The time-stamped version of the pre-registration is available from the Open Science Framework website at the address https://doi.org/10.17605/OSF.IO/58MNJ.

To understand this appendix deeply, we recommend carefully reading Brodeur et al (2016). The body of our comment paper outlines only the intuition of their method. In some of the figures presented in this appendix, we use labels that differ from those in Brodeur et al. (2016), and we do so to more clearly connect to the intuition we offer.

This note is intended to introduce economists to a simple SIR model of the progression of COVID-19 in the United States over the next 12-18 months. An SIR model is a Markov model of the spread of an epidemic in a population in which the total population is divided into categories of being susceptible to the disease (S), actively infected with the disease (I), and recovered (or dead) and no longer contagious (R). How an epidemic plays out over time is determined by the transition rates between these three states. This model allows for quantitative statements regarding the tradeoff between the severity and timing of suppression of the disease through social distancing and the progression of the disease in the population. Example applications of the model are provided. Special attention is given to the question of if and when the fraction of active infections in the population exceeds 1% (at which point the health system is forecast to be severely challenged) and 10% (which may result in severe staffing shortages for key financial and economic infrastructure) as well as the cumulative burden of the disease over an 18 month horizon.

Concentration of insured deposit funding among the top four commercial banks in the U.S. has risen from 15% in 1984 to 44% in 2018, a roughly three-fold increase. Regulation has often been attributed as a factor in that increase. The Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 removed many of the restrictions on opening bank branches across state lines. We interpret the Riegle-Neal act as lowering the cost of expanding a bank's funding base. In this paper, we build an industry equilibrium model in which banks endogenously climb a funding base ladder. Rising concentration occurs along a transition path between two steady states after branching costs decline.

We document that declining hours worked are the primary driver of widening inequality in the bottom half of the male labor earnings distribution in the United States over the past 52 years. This decline in hours is heavily concentrated in recessions: hours and earnings at the bottom fall sharply in recessions and do not fully recover in subsequent expansions. Motivated by this evidence, we build a structural model to explore the possibility that recessions cause persistent increases in inequality; that is, that the cycle drives the trend. The model features skill-biased technical change, which implies a trend decline in low-skill wages relative to the value of non-market activities. With this adverse trend in the background, recessions imply a potential double-whammy for low skilled men. This group is disproportionately likely to experience unemployment, which further reduces skills and potential earnings via a scarring effect. As unemployed low skilled men give up job search, recessions generate surges in non-participation. Because non-participation is highly persistent, earnings inequality remains elevated long after the recession ends.

We show that occupational licensing has significant negative effects on labor market fluidity defined as cross-occupation mobility. Using a balanced panel of workers constructed from the CPS and SIPP data, we analyze the link between occupational licensing and labor market outcomes. We find that workers with a government-issued occupational license experience churn rates significantly lower than those of non-licensed workers. Specifically, licensed workers are 24% less likely to switch occupations and 3% less likely to become unemployed in the following year. Moreover, occupational licensing represents barriers to entry for both non-employed workers and employed ones. The effect is more prominent for employed workers relative to those entering from non-employment, because the opportunity cost of acquiring a license is much higher for employed individuals. Lastly, we find that average wage growth is higher for licensed workers than non-licensed workers, whether they stay in the same occupation in the next year or switch occupations. We find significant heterogeneity in the licensing effect across different occupation groups. These results hold across various data sources, time spans, and indicators of being licensed. Overall, licensing could account for almost 8% of the total decline in monthly occupational mobility over the past two decades

We address this question in a heterogeneous-agent incomplete-markets model featuring exogenous idiosyncratic risk, endogenous skill investment, and flexible labor supply. The tax and transfer schedule is restricted to be log-linear in income, a good description of the US system. Rising inequality is modeled as a combination of skill-biased technical change and growth in residual wage dispersion. When facing shifts in the income distribution like those observed in the US, a utilitarian planner chooses higher progressivity in response to larger residual inequality but lower progressivity in response to widening skill price dispersion reflecting technical change. Overall, optimal progressivity is approximately unchanged between 1980 and 2016. We document that the progressivity of the actual US tax and transfer system has similarly changed little since 1980, in line with the model prescription.

We show that cities with higher population density specialize in high-skill service jobs that can be done remotely. The urban and industry bias of remote work potential shaped the recent pandemic’s economic impact. Many high-skill service workers started to work remotely, withdrawing spending from big-city consumer service industries dependent on their demand. As a result, low-skill service workers in big cities bore most of the recent pandemic’s economic impact. Our findings have broader implications for the distributional consequences of the U.S. economy’s transition to more remote work.

This paper studies the short- and long-run effects of large firms on economic development. We use evidence from one of the largest multinationals of the 20th century: the United Fruit Company (UFCo). The firm was given a large land concession in Costa Rica—one of the so-called "Banana Republics"—from 1899 to 1984. Using administrative census data with census-block geo-references from 1973 to 2011, we implement a geographic regression discontinuity design that exploits a quasi-random assignment of land. We find that the firm had a positive and persistent effect on living standards. Company documents explain that a key concern at the time was to attract and maintain a sizable workforce, which induced the firm to invest heavily in local amenities that can account for our result. Consistent with this mechanism, we show, empirically and through a proposed model, that the firm's welfare effect is increasing in worker mobility.

To measure labor market power in the US economy, we develop a tractable quantitative, general equilibrium, oligopsony model of the labor market. We estimate key model parameters by matching the firm-level relationship between labor market share and employment size and wage responses to state corporate tax changes. The model quantitatively replicates quasi-experimental evidence on (i) imperfect productivity-wage pass-through, (ii) strategic behavior of dominant employers, and (iii) the local labor market impact of mergers. We then measure welfare losses relative to the efficient allocation. Accounting for transition dynamics, we quantify welfare losses from labor market power relative to the efficient allocation as roughly 6 percent of lifetime consumption. An analytical decomposition attributes equal parts to dead-weight losses and misallocation. Lastly, we find that declining local concentration added 4 ppt to labor's share of income between 1977 and 2013.

This paper aims at an improved understanding of the relationship between monetary policy and racial inequality. We investigate the distributional effects of monetary policy in a unified framework, linking monetary policy shocks both to earnings and wealth differentials between black and white households. Specifically, we show that, although a more accommodative monetary policy increases employment of black households more than white households, the overall effects are small. At the same time, an accommodative monetary policy shock exacerbates the wealth difference between black and white households, because black households own less financial assets that appreciate in value. Over multi-year time horizons, the employment effects are substantially smaller than the countervailing portfolio effects. We conclude that there is little reason to think that accommodative monetary policy plays a significant role in reducing racial inequities in the way often discussed. On the contrary, it may well accentuate inequalities for extended periods.

COVID symptom screening, a new workplace practice, is likely to affect many millions of American workers in the coming months. Eleven states already require and federal guidance recommends frequent screening of employees for infection symptoms. This paper provides some of the first empirical work exploring the tradeoffs employers face in using daily symptom screening. First, we find that common symptom checkers will likely screen out up to 7 percent of workers each day, depending on the measure used. Second, we find that the measures used will matter for three reasons: many respondents report any given symptom, survey design affects responses, and demographic groups report symptoms at different rates, even absent fluctuations in likely COVID exposure. This last pattern can potentially lead to disparate impacts, and is important from an equity standpoint.

We examine the determinants of COVID-19 risk exposure in the context of the initial wave in New York City. During the beginning of the first wave of the pandemic, out-of-home activity related to commuting was strongly associated with COVID-19 cases at the ZIP code level and hospitalization at an individual level. After layoffs of workers decreased commuting, case growth continued through household crowding. A larger share of individuals in crowded housing, or commuting to essential and frontline work, are Black, Hispanic, and lower-income—which contributes to disparities in disease risk. As a result, our paper shows that structural socio-economic inequalities help determine the cross-section of COVID-19 risk exposure in urban areas.

We use panel data covering 118 million homes in the United States, merged with geolocation detail for 75,000 taxing entities, to document a nationwide "assessment gap" which leads local governments to place a disproportionate fiscal burden on racial and ethnic minorities. We show that holding jurisdictions and property tax rates fixed, black and Hispanic residents nonetheless face a 10-13% higher tax burden for the same bundle of public services. This assessment gap arises through two channels. First, property assessments are less sensitive to neighborhood attributes than market prices are. This generates racially correlated spatial variation in tax burden within jurisdiction. Second, appeals behavior and appeals outcomes differ by race. This results in higher assessment growth rates for minority residents. We propose an alternate approach for constructing assessments based on small-geography home price indexes, and show that this reduces inequality by at least 55-70%.

Workers are unequal in the face of the COVID-19 pandemic: Those who work in essential sectors face higher health risk whereas those in non-essential social-consumption sectors face greater economic risk. We study how these health and economic risks cascade into other sectors through supply chains and demand linkages. In the U.S., we find the cascading effects account for about 25-30% of the exposure to both risks. The cascading effect increases the health risk faced by workers in the transportation and retail sectors, and it increases the economic risk faced by workers in the textile and petroleum sectors. We provide sectoral estimates of the health and economic risk for 42 other countries in an online interactive document.

Does job loss cause less economic damage if your parents are higher-income, and what are the implications for intergenerational mobility? In this paper we show that following a layoff, adult children born to parents in the bottom 20% of the income distribution have almost double the unemployment compared with those born to parents in the top 20%, with 118% higher present discounted value losses in earnings. Next, we show that these disparate impacts of job loss have important implications for inequality and intergenerational mobility. They increase the 80:20 income inequality ratio for those impacted by 8% and increase the rank-rank coefficient by 34%, implying large reductions in intergenerational mobility. In a simulation based on our main results, we show that the age 40 rank-rank correlation is 3.9% higher due to the disparate impact and incidence of job loss over the preceding decade. In the last part of the paper, we explore mechanisms and show that "baked in" advantages play an important role in explaining these differences.

There have been growing concerns about long-haulers or individuals with long-term COVID-19 health complications (long-haul COVID). While the medical field has been investigating the health complications, there has been limited research on the relationship between long-haul COVID and labor market outcomes. To investigate this relationship, I used the University of Southern California Understanding America Study COVID-19 longitudinal survey to provide a snapshot of mid-2021. I first find about 24.1% of individuals who have had COVID are long-haulers and 25.9% of long-haulers reported that their long-haul COVID affected employment or work hours. I then find that a majority of these affected long-haulers remained employed and in same employment type. But I find that their mean change in work hours and paycheck declined. Afterwards, I tested whether long-haul COVID is associated with negative changes in labor market outcomes. When I combined long-haulers who reported that their health complications did or did not affect work, I failed to find that long-haulers are less likely to be employed relative to individuals without prior COVID infection. But, when I discern long-haulers by whether long-haul COVID affected work, I find that long-haulers who reported long-haul COVID affected work are 10 percentage points less likely to be employed and, on average, work 50% fewer hours than individuals without prior COVID infection. In contrast, I failed to find evidence that affected long-haulers receive a lower paycheck earning relative to individuals without prior COVID infection. Lastly, when comparing these affected long-haulers against similar individuals, I find evidence that they are more impacted in their employed status and work hours. Due to limitations, future data collection and research would provide a more robust picture.

We build a New Keynesian business-cycle model with rich household heterogeneity. In the model, systematic monetary stabilization policy affects the distribution of income, income risks, and the demand for funds and supply of assets: the demand, because matching frictions render idiosyncratic labor-market risk endogenous; the supply, because markups, adjustment costs, and the tax system mean that the average profitability of firms is endogenous. Disagreement about systematic monetary stabilization policy is pronounced. The wealth-rich or retired tend to favor inflation targeting. The wealth-poor working class, instead, favors unemployment-centric policy. One- and two-agent alternatives can show unanimous disapproval of inflation-centric policy, instead. We highlight how the political support for inflation-centric policy depends on wage setting, the tax system, and the portfolio that households have.

While the savings of retired singles tend to fall with age, those of retired couples tend to rise. We estimate a rich model of retired singles and couples with bequest motives and uncertain longevity and medical expenses. Our estimates imply that while medical expenses are an important driver of the savings of middle-income singles, bequest motives matter for couples and high-income singles, and generate transfers to non-spousal heirs whenever a household member dies. The interaction of medical expenses and bequest motives is a crucial determinant of savings for all retirees. Hence, to understand savings, it is important to model household structure, medical expenses, and bequest motives.

Tracking human activity in real time and at fine spatial scale is particularly valuable during episodes such as the COVID-19 pandemic. In this paper, we discuss the suitability of smartphone data for quantifying movement and social contact. We show that these data cover broad sections of the US population and exhibit movement patterns similar to conventional survey data. We develop and make publicly available a location exposure index that summarizes county-to-county movements and a device exposure index that quantifies social contact within venues. We use these indices to document how pandemic-induced reductions in activity vary across people and places.

For whom has earnings risk changed, and why? To answer these questions, we develop a filtering method that estimates parameters of an income process and recovers persistent and temporary earnings for every individual at every point in time. Our estimation flexibly allows for first and second moments of shocks to depend upon observables as well as spells of zero earnings (i.e., unemployment) and easily integrates into theoretical models. We apply our filter to a unique linkage of 23.5m SSA-CPS records. We first demonstrate that our earnings-based filter successfully captures observable shocks in the SSA-CPS data, such as job switching and layoffs. We then show that despite a decline in overall earnings risk since the 1980s, persistent earnings risk has risen for both employed and unemployed workers, while temporary earnings risk declined. Furthermore, the size of persistent earnings losses associated with full year unemployment has increased by 50%. Using geography, education, and occupation information in the SSA-CPS records, we refute hypotheses related to declining employment prospects among routine and low-skill workers as well as spatial theories related to the decline of the Rust-Belt. We show that rising persistent earnings risk is concentrated among high-skill workers and related to technology adoption. Lastly, we find that rising persistent earnings risk while employed (unemployed) leads to welfare losses equivalent to 1.8% (0.7%) of lifetime consumption, and larger persistent earnings losses while unemployed lead to a 3.3% welfare loss.

We offer causal evidence of higher returns to experience in big cities. Exploiting a natural experiment that settled refugees across labor markets in Denmark between 1986 and 1998, we find that refugees initially earn similar wages across locations. However, those placed in Copenhagen exhibit 35% faster wage growth with each additional year of experience. Faster sorting of workers towards the type of establishments, occupations, and industries typically found in cities accounts for the vast majority of this urban wage growth premium.

This paper uses a unique large-scale survey administered in April 2020 to assess disparities on several dimensions of wellbeing under rising COVID-19 infections and mitigation restrictions in the US. The survey includes three modules designed to assess different dimensions of well-being in parallel: physical health, mental and social health, and economic and financial security. The survey is unique among early COVID-19 data efforts in that provides insight on diverse dimensions of wellbeing and for subnational geographies. I find dramatic declines in wellbeing from pre-COVID baseline measures across both people and places. Place-level variation is not well explained by local characteristics that either precede or coincide with the pandemic. Analysis by demographic groups also shows large and unequal declines in wellbeing in the COVID era. Hispanic, younger, and lower-earning individuals all faced disproportionately worsening economic conditions, as did those with school-aged children. I conclude that place-based relief policies are unlikely to be efficient relative to support targeted to the neediest individuals. I also find that individual COVID-19 exposure and risk show concerning relationships with employment, protective behavior, and mental health. Those with direct COVID-19 exposure through their households continue working similar hours to others, and those with recent fever symptoms or elevated risk for COVID complications are not reducing their work hours or taking additional precautions, despite negative mental health status changes indicating concern. These findings suggest that some support policies might be directly targeted to households with confirmed infections or heighted risk.

We document new facts about risk in male wages and earnings, household earnings, and pre- and post-tax income in the Netherlands and the United States. We find that, in both countries, earnings display important deviations from the typical assumptions of linearity and normality. Individual-level male wage and earnings risk is relatively high at the beginning and end of the working life, and for those in the lower and upper parts of the income distribution. Hours are the main driver of the negative skewness and, to a lesser extent, the high kurtosis of earnings changes. Even though we find no evidence of added-worker effects, the presence of spousal earnings reduces the variability of household income compared to that of male earnings. In the Netherlands, government transfers are a major source of insurance, substantially reducing the standard deviation, negative skewness, and kurtosis of income changes. In the U.S. the role of family insurance is much larger than in the Netherlands. Family and government insurance reduce, but do not eliminate nonlinearities in household disposable income by age and previous earnings in either country.