Research Database

The empirical literature on the stability of the Phillips curve has largely ignored the bias that endogenous monetary policy imparts on estimated Phillips curve coefficients. We argue that this omission has important implications. When policy is endogenous, estimation based on aggregate data can be uninformative as to the existence of a stable relationship between unemployment and future inflation. But we also argue that regional data can be used to identify the structural relationship between unemployment and inflation. Using city-level and state-level data from 1977 to 2017, we show that both the reduced form and the structural parameters of the Phillips curve are, to a substantial degree, quite stable over time.

The interest rate on government debt is significantly lower than the rates of return on other assets. From the perspective of standard models of optimal taxation, this empirical fact is puzzling: typically, the government should finance expenditures either through contingent taxes, or by previously-issued state-contingent debt, or by labor taxes, with only minor effects arising from intertemporal distortions on interest rates. We study how this answer changes in an economy with financial frictions, where the government cannot directly redistribute towards the agents in need of liquidity, but has otherwise access to a complete set of linear tax instruments. We establish a stark result. Provided this is feasible, optimal policy calls for the government to increase its debt, up to the point at which it provides sufficient liquidity to avoid financial constraints. In this case, capital-income taxes are zero in the long run, and the returns on government debt and capital are equalized. However, if the fiscal space is insufficient, a wedge opens between the rate of return on government debt and capital. In this case, optimal long-run tax policy is driven by a trade-off between the desire to mitigate financial frictions by subsidizing capital and the incentive to exploit the quasi-rents accruing to producers of capital by taxing capital instead. This latter incentive magnifies the wedge between rates of return on publicly and privately-issued assets.

In the past three decades, governments in emerging markets have accumulated large amounts of international reserves, especially those with fixed exchange rates. We propose a theory of reserve accumulation that can account for these facts. Using a model of endogenous sovereign default with nominal rigidities, we show that the interaction between sovereign risk and aggregate demand amplification generates a macroeconomic-stabilization hedging role for international reserves. Reserves increase debt sustainability to such an extent that financing reserves with debt accumulation may not lead to increases in spreads. We also study simple and implementable rules for reserve accumulation. Our findings suggest that a simple linear rule linked to spreads can achieve significant welfare gains, while those rules currently used in policy studies of reserve adequacy can be counterproductive.

The extent to which households can self-insure and the government can help them to do so depends on the wage risk that they face and their family structure. We study wage risk in the UK and show that the persistence and riskiness of wages depends on one's age and position in the wage distribution. We also calibrate a model of couples and singles with two alternative processes for wages: a canonical one and a flexible one that allows for the much richer dynamics that we document in the data. We use our model to show that allowing for rich wage dynamics is important to properly evaluate the effects of benefit reform: relative to the richer process, the canonical process underestimates wage persistence for women and generates a more important role for in-work benefits relative to income support. The optimal benefit configuration under the richer wage process, instead, is similar to that in place in the benchmark UK economy before the Universal Credit reform. The Universal Credit reform generates additional welfare gains by introducing an income disregard for families with children. While families with children are better off, households without children, and particularly single women, are worse off.

Low-skilled immigrants indirectly affect public finances through their effect on native wages & labor supply. We operationalize this general-equilibrium effect in the workhorse labor market model with heterogeneous workers and intensive and extensive labor supply margins. We derive a closed-form expression for this effect in terms of estimable statistics. We extend the analysis to various alternative specifications of the labor market and production that have been emphasized in the immigration literature. Empirical quantifications for the U.S. reveal that the indirect fiscal benefit of one low-skilled immigrant lies between $770 and $2,100 annually. The indirect fiscal benefit may outweigh the negative direct fiscal effect that has previously been documented. This challenges the perception of low-skilled immigration as a fiscal burden.

We document four facts about the COVID-19 pandemic worldwide relevant for those studying the impact of non-pharmaceutical interventions (NPIs) on COVID-19 transmission. First: across all countries and U.S. states that we study, the growth rates of daily deaths from COVID-19 fell from a wide range of initially high levels to levels close to zero within 20-30 days after each region experienced 25 cumulative deaths. Second: after this initial period, growth rates of daily deaths have hovered around zero or below everywhere in the world. Third: the cross section standard deviation of growth rates of daily deaths across locations fell very rapidly in the first 10 days of the epidemic and has remained at a relatively low level since then. Fourth: when interpreted through a range of epidemiological models, these first three facts about the growth rate of COVID deaths imply that both the effective reproduction numbers and transmission rates of COVID-19 fell from widely dispersed initial levels and the effective reproduction number has hovered around one after the first 30 days of the epidemic virtually everywhere in the world. We argue that failing to account for these four stylized facts may result in overstating the importance of policy mandated NPIs for shaping the progression of this deadly pandemic.

We analytically characterize the aggregate productivity loss from allocative distortions in a setting that accounts for the sectoral linkages of production. We show that the effects of distortions and the role of sectoral linkages depend crucially on how substitutable inputs are. We find that the productivity loss is smaller if input substitutability is low. Moreover, with low input substitutability, sectoral linkages do not systematically amplify the effects of distortions. In addition, the impact of the sectors that supply intermediate inputs becomes smaller. We quantify these effects in the context of the distortions caused by market power, using industry-level data for 35 countries. With our benchmark calibration, which accounts for low input substitutability, the median aggregate productivity loss from industry-level markups is 1.3%. To assume instead unit elasticities of substitution (i.e., to use a Cobb-Douglas production function) would lead to overestimating the productivity loss by a factor of 1.8. Sectoral linkages do amplify the cost of markups, but the amplification factor is considerably weaker than with unit elasticities.

We build a dataset of harmonized rotating panel labor force surveys covering 42 countries across a wide range of development and document three new empirical findings on labor market dynamics. First, labor market flows (job-finding rates, employment-exit rates, and job-to-job transition rates) are two to three times higher in the poorest as compared with the richest countries. Second, employment hazards in poorer countries decline more sharply with tenure; much of their high turnover can be attributed to high separation rates among workers with low tenure. Third, wage-tenure profiles are much steeper in poorer countries, despite the fact that wage-experience profiles are flatter. We show that these facts are consistent with theories with endogenous separation, particularly job ladder and learning models. We disaggregate our results and investigate possible driving forces that may explain why separation operates differently in rich and poor countries.

What is the role of credit scores in credit markets? We argue that it is a stand in for a market assessment of a person's unobservable type (which here we take to be patience). We pose a model of persistent hidden types where observable actions shape the public assessment of a person's type via Bayesian updating. We show how dynamic reputation can incentivize repayment without monetary costs of default beyond the administrative cost of filing for bankruptcy. Importantly we show how an economy with credit scores implements the same equilibrium allocation. We estimate the model using both credit market data and the evolution of individual’s credit scores. We find a 3% difference in patience in almost equally sized groups in the population with significant turnover and a shift towards becoming more patient with age. If tracking of individual credit actions is outlawed, the benefits of bankruptcy forgiveness are outweighed by the higher interest rates associated with lower incentives to repay.

We measure the contribution of firm-embedded productivity to cross-country income differences. By firm-embedded productivity we refer to the components of productivity that differ across firms and that can be transferred internationally, such as blueprints, management practices, and intangible capital. Our approach relies on microlevel data on the cross-border operations of multinational enterprises (MNEs). We compare the market shares of the exact same MNE in different countries and document that they are about four times larger in developing than in high-income countries. This finding indicates that MNEs face less competition in less-developed countries, suggesting that firm-embedded productivity in those countries is scarce. We propose and implement a new measure of firm-embedded productivity based on this observation. We find a strong positive correlation between our measure and output per-worker across countries. In our sample, differences in firm-embedded productivity account for roughly a third of the cross-country variance in output per-worker.

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.

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.

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.

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.

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.

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.

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 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.

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 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.

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.

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.

I examine the impact of the COVID-19 shock on parents' labor supply during the initial stages of the pandemic. Using difference-in-difference estimation and monthly panel data from the Current Population Survey (CPS), I compare labor market attachment, non-work activity, hours worked, and earnings and wages of those in areas with early school closures and stay-in-place orders with those in areas with delayed or no pandemic closures. While there was no immediate impact on detachment or unemployment, mothers with jobs in early closure states were 68.8 percent more likely than mothers in late closure states to have a job but not be working as a result of early shutdowns. There was no effect on working fathers or working women without school age children. Mothers who continued working increased their work hours relative to comparable fathers; this effect, however, appears entirely driven by a reduction in fathers’ hours worked. Overall, the pandemic appears to have induced a unique immediate juggling act for working parents of school age children. Mothers took a week of leave from formal work; fathers working fulltime, for example, reduced their hours worked by 0.53 hours over the week. While experiences were different for mothers and fathers, each are vulnerable to scarring and stunted opportunities for career growth and advancement due to the pandemic.

In this paper, we ask how bankruptcy law affects the financial decisions of corporations and its implications for firm dynamics. According to current U.S. law, firms have two bankruptcy options: Chapter 7 liquidation and Chapter 11 reorganization. Using Compustat data, we first document capital structure and investment decisions of non-bankrupt, Chapter 11, and Chapter 7 firms. Using those data moments, we then estimate parameters of a general equilibrium firm dynamics model with endogenous entry and exit to include both bankruptcy options. Finally, we evaluate a bankruptcy policy change similar to one recommended by the American Bankruptcy Institute that amounts to a "fresh start" for bankrupt firms. We find that changes to the law can have sizable consequences for borrowing costs and capital structure which via selection affects productivity, as well as long run welfare.

Sudden Stops are financial crises defined by a large, sudden current-account reversal. They occur in both advanced and emerging economies and result in deep recessions, collapsing asset prices, and real exchange-rate depreciations. They are preceded by economic expansions, current-account deficits, credit booms, and appreciated asset prices and real exchange rates. Fisherian models (i.e. models with credit constraints linked to market prices) explain these stylized facts as an outcome of Irving Fisher's debt-deflation mechanism. On the normative side, these models feature a pecuniary externality that provides a foundation for macroprudential policy (MPP). We review the stylized facts of Sudden Stops, the evidence on MPP use and effectiveness, and the findings of the literature on Fisherian models. Quantitatively, Fisherian amplification is strong and optimal MPP reduces sharply the size and frequency of crises, but it is also complex and potentially time-inconsistent, and simple MPP rules are less effective. We also provide a new MPP analysis incorporating investment. Using a constant debt-tax policy, we construct a crisis probability-output frontier showing that there is a tradeoff between financial stability and long-run output (i.e., reducing the probability of crises reduces long-run output).

We develop and calibrate a search-theoretic model of the labor market in order to forecast the evolution of the aggregate US labor market during and after the coronavirus pandemic. The model is designed to capture the heterogeneity of the transitions of individual workers across states of unemployment and employment and across different employers. The model is designed also to capture the trade-offs in the choice between temporary and permanent layoffs. Under reasonable parametrizations of the model, the lockdown instituted to prevent the spread of the novel coronavirus is shown to have long-lasting negative effects on unemployment. This is because the lockdown disproportionately disrupts the employment of workers who need years to find stable jobs.

Social learning plays an important role in models of productivity dispersion and long-run growth. In economies with a continuum of producers and unbounded productivity distributions, social learning can sometimes leave long-run growth rates completely indeterminate. This paper modifies a model in which potential entrants attempt to imitate randomly selected incumbent firms by introducing an upper bound on how much entrants can learn from incumbents. When this upper bound is taken to infinity, a unique long-run growth rate emerges, even though the economy without upper bound has an unbounded continuum of balanced growth rates.

We develop and calibrate a search-theoretic model of the labor market in order to forecast the evolution of the aggregate US labor market during and after the coronavirus pandemic. The model is designed to capture the heterogeneity of the transitions of individual workers across states of unemployment and employment and across different employers. The model is designed also to capture the trade-offs in the choice between temporary and permanent layoffs. Under reasonable parametrizations of the model, the lockdown instituted to prevent the spread of the novel coronavirus is shown to have long-lasting negative effects on unemployment. This is because the lockdown disproportionately disrupts the employment of workers who need years to find stable jobs.

U.S. government concerns about great disparities in housing conditions are at least 100 years old. For the first 50 years of this period, U.S. housing crises were widely considered to stem from the failure of the construction industry to adopt new technology -- in particular, factory production methods. The introduction of these methods in many industries had already greatly narrowed the quality of goods consumed by low- and high-income Americans. It was widely known why the industry failed to adopt these methods: Monopolies in traditional construction blocked and sabotaged them. Very little has changed in the last 50 years. The industry still fails to adopt factory methods, with monopolies, like HUD and NAHB, blocking attempts to adopt them. As a result, the productivity record of the construction industry has been horrendous. One thing has changed. Today there is very little discussion of factory-built housing; of the very few that recognize the industry's failure to adopt factory methods, there is no realization that monopolies are blocking the methods. That these monopolies, in particular, HUD and NAHB, can cause so much hardship in our country, and through misinformation and deceit cover it up, seems almost beyond belief. But, unfortunately, it's a history that is not uncommon. There are many other industries where monopolies have inflicted great harm on Americans, like the tobacco industry, yet through misinformation and deceit cover up the great harm.

The Covid-19 crisis has exposed the vast inequalities that exist within the US economy. As the virus has spread silently, it has laid bare other crises that face our nation---especially the economic vulnerabilities of the country's poor and marginalized. Many of these vulnerabilities can, in fact, be traced back to a single cause that itself has spread silently, but over the last several decades, not months: Monopolies. That monopolies are "silent spreaders of poverty and economic inequality" was well known to economic and legal scholars of the 1930s and 1940s. Wendell Berge, who was Assistant Attorney General for Antitrust in the 1940s, wrote: "Monopoly conditions have often grown up almost unnoticed by the public until one day it is suddenly realized that an industry is no longer competitive but is governed by an economic oligarchy." The harm caused by these monopolies that have mostly avoided detection often exist in markets with small firms, low concentration levels, and small price-cost margins, as in residential construction, or wreak their harm in public institutions, where prices and concentration have no meaning. While there has been a very welcome resurgence in the concern about monopolies in the last decade or so, this has primarily involved vast corporations, and often about their threat to democratic institutions. Though greatly welcomed, we should not let apprehension with these larger companies distract us from the many hidden monopolies that have silently spread harm to the poor for the last 100 years -- not just the last 10 or so. We should stand on the shoulders of giants that taught us this about monopolies, not only Berge, but Thurman Arnold, Henry Simons, and others.

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. We conclude that the low-frequency behavior of these series maintains a close relationship, as predicted by standard quantity theory models. In an estimated model, we show those relationships to be relatively invariant to alternative frictions that can deliver very different high-frequency dynamics. We argue that these relationships are useful for policy design aimed at controlling inflation.

We modify a standard SIR epidemiological model to allow for testing and asymptomatic agents. We explore cross country variation's ability to allow for identification of key parameters of the model: the fatality rate and the evolution over time of the normalized transmission rate. We first show that as long as tests are applied only to agents who exhibit symptoms, those parameters cannot be identified. We briefly discuss which additional information may allow for identification. Finally, we also describe conditions under which the normalized transmission rate can be computed with very high accuracy, and how cross country evidence can be used to evaluate the effect of lockdowns on evolution of the effective transmission rate over time.

From introduction: This paper is intended to introduce economists to a simple SIR model of the progression of COVID-19 to aid understanding of how such a model might be incorporated into more standard macroeconomic models. An SIR model is a Markov model of the spread of an epidemic in which the total population is divided into categories of being susceptible to the disease (S); actively infected with the disease (I); and resistant (R), meaning those that have recovered, died from the disease, or have been vaccinated. The initial distribution of the population across these states and the transition rates at which agents move between these three states determine how an epidemic plays out over time. These transition rates are determined by characteristics of the underlying disease and by the extent of mitigation and social distancing measures. 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.

This note develops a framework for thinking about the following question: What is the maximum amount of consumption that a utilitarian welfare function would be willing to trade off to avoid the deaths associated with COVID-19? The answer depends crucially on the mortality rate associated with the coronavirus. If the mortality rate averages 0.81%, as projected in one prominent study, our answer is 41% of one year’s consumption. If the mortality rate instead averages 0.44% across age groups, as suggested by a recent seroprevalence study, our answer is 28%.