Recent Publications

Research

2024

(with Ayça Kaya), Repeated Trading: Transparency and Market Structure, American Economic Review (2024). []

Market transparency in the form of reliable records of past trading outcomes allows new buyers to learn about an existing seller’s product quality but the effect on market efficiency depends crucially on market structure and in particular, the ability of the seller to earn rents.

We analyze the effect of transparency of past trading volumes in markets where an informed long-lived seller can repeatedly trade with short-lived uninformed buyers. Transparency allows buyers to observe previously sold quantities. In markets with intraperiod monopsony (single buyer each period), transparency reduces welfare if the ex ante expected quality is low but improves welfare if the expected quality is high. The effect is reversed in markets with intraperiod competition (multiple buyers each period). This discrepancy in the efficiency implications of transparency is explained by how buyer competition affects the seller's ability to capture rents, which, in turn, influences market screening.
and , Embrace the Noise: It Is OK to Ignore Measurement Error in a Covariate, Sometimes Journal of the Royal Statistical Society, Series A (Forthcmoning). []

OLS can be more efficient than IV if a covariate is measured with error if the portion of the sample suffering from measurement error shrinks fast enough as the sample size grows.

In linear regression models, measurement error in a covariate causes Ordinary Least Squares (OLS) to be biased and inconsistent. Instrumental Variables (IV) is a common solution. While IV is also biased, it is consistent. Here, we undertake an asymptotic comparison of OLS and IV in the case where a covariate is mismeasured for N^{\delta} of N observations with \delta \in [0,1]. We show that OLS is consistent for \delta<1 and is asymptotically normal and more efficient than IV for \delta < 0.5. Simulations and an application to the impact of body mass index on family income demonstrate the practical usefulness of this result.
(with Luigi Manzetti), High-Tech Exports and Governance Institutions, Political Science & Politics (2024). []

Governance Institutions play an important role creating high-tech exports, thereby influencing economic growth
(with Ian McDonough), Food Security Dynamics and Measurement Error, American Journal of Agricultural Economics (Forthcmoning). []

It is important to account for measurement error in food security status when examining changes in household status over time.

We examine intra- and intergenerational food security dynamics in the United States using longitudinal data from the Panel Study of Income Dynamics (PSID) while accounting for measurement error. We apply recently developed methods on the partial identification of transition matrices and show that accounting for measurement error is crucial as even modest errors can dwarf the information contained in the data. Nonetheless, we find that much can be learned under fairly weak assumptions; the strongest and most informative assumption being that measurement errors are serially uncorrelated. In particular, while the evidence – both intragenerational and intergenerational – is consistent with significant mobility, we also find food security status to be persistent for at least some households in the tails of the distribution. We further document some heterogeneities in dynamics across households differentiated by race and education. Finally, the impact of measurement error in the context of underlying dynamics is widely applicable to other areas of applied microeconomics generally as well as to food security dynamics in less developed countries specifically.
Wookun Kim (with Hwanoong Lee and Changsu Ko), Local employment multiplier: Evidence from relocation of public-sector entities in South Korea, Labour Economics (2024). [ and ]
The introduction of one public sector employment position, increases local private sector employment by one unit.

We exploit a series of public-sector entity relocations in South Korea as an exogenous source of variation in public sector employment to estimate the local employment multiplier. We find that the introduction of one public sector employment position increases private sector employment by one unit, primarily driven by the service sector. Consistent with existing literature, we document that the effect of public employment on private employment is highly localized. In addition to changes in private employment, we also discover that the relocations led to a positive net influx of residents into the treated neighborhoods; this effect is also localized. Lastly, by estimating the local employment multiplier for each relocation site, we document the heterogeneity of the local employment multiplier and provide suggestive evidence that this heterogeneity is shaped by the local economic environment’s capacity to accommodate additional general equilibrium response
(with E. Glenn Dutcher, Regine Oexl, and Dmitry Ryvkin), Do competitive bonuses ruin cooperation in heterogeneous teams?, Journal of Economics and Management Strategy (2024). []

We examine whether competitive or cooperative incentives are better for team production settings when individuals have the opportunity to help or hinder their co-workers.

A debate among practicing managers is whether to use cooperative or competitive incentives for team production. While competitive incentives may drive individual effort higher, they may also lead to less help and more sabotage, with unclear consequences overall, especially when team members' abilities differ. Using a lab experiment, we examine how increasing competitive incentives affects performance as team composition changes. We find that competitive incentives generally under-perform noncompetitive incentives and a larger bonus does not generate enough effort to compensate for a loss in help. Our results help understand better how to balance out individual versus team rewards and how firms could structure teams when employees have heterogeneous abilities.
(with Ana Maria Santacreu and B. Ravikumar), Trade liberalization versus protectionism: Dynamic welfare asymmetries, European Economic Review, (2024) []

The losses from a protectionist trade policy can be less than the gains from a symmetric liberalization shock in the presence of a durable factor of production, like capital.

We investigate whether the losses from an increase in trade costs (protectionism) are equal to the gains from a symmetric decrease in trade costs (liberalization). We incorporate dynamics through capital accumulation into a multicountry trade model and show that the welfare changes are asymmetric: Losses from protectionism are smaller than the gains from liberalization. In contrast, standard static trade models imply that the losses equal the gains. The intuition for asymmetry in our model is that, following protectionism, the economy can coast on its previously accumulated capital stock, so higher trade costs do not imply large losses immediately. We develop an accounting device to decompose the source of welfare asymmetries into three time-varying contributions: share of income allocated to consumption, measured productivity, and capital stock. Asymmetry in capital accumulation is the largest contributing factor, and measured productivity is the smallest.
(with Xin Jin and Mine Yücel), The Shale Revolution and the Dynamics of the Oil Market, The Economic Journal (2024). []

We examine the effects of the shale revolution on the level and volatility of oil prices.

We build and estimate a dynamic, structural model of the world oil market to quantify the impact of the shale revolution. We model the shale revolution as a decrease in shale production costs and find that the resultant increase in shale production lowers oil prices by 24% in the short run and 48% once the shale oil transition is complete. Current oil price volatility is lowered by 8% to 23% depending on the horizon. We also find that OPEC core acts to keep its market share constant in the face of the dramatic increase in shale production.
Wookun Kim (with Rannveig Kaldager Hart, Janna Bergsvik, and Agnes Fauske), Causal Analysis of Policy Effects on Fertility, in the Handbook of Labor, Human Resources and Population Economics, edited by Klaus Zimmerman (2024). [ and ]

Studies from Europe, Northern America, Oceania and Asia indicate that pro-natalist policies generally have a positive causal effect on fertility, though the distributional effects across income levels depends on the nature of the policy.

This chapter reviews the literature on the causal effects of policies on fertility. It focuses on evidence from experiments and quasi-experiments in low fertility contexts, including studies from Europe, Northern America, Oceania and Asia. Making no a priori restrictions on policy type, the review encompasses evaluations of parental leave, childcare, health insurance, and financial incentives such as child transfers. Childcare expansions increase completed fertility. Financial incentives had positive effects on fertility across contexts, both in the short and long run. Expansions of parental leave rights in Central Europe, and introduction of parental leave in the U.S., also had positive effects. Distributional effects of these policies are very different, with parental leave compensation benefiting high-earning couples, while expansions of child care programs have potential to reduce social inequalities.

2023

(with Jennifer Alix-Garcia), Remotely Incorrect? Accounting for Nonclassical Measurement Error in Satellite Data on Deforestation, Journal of the Royal Statistical Society, Series A (2023). []

It is important to account for measurement error when relying on satellite imagery to measure deforestation.

Research relying on remotely sensed data on land use and deforestation has exploded in recent years. While satellite-based measures have clear advantages in terms of coverage, the presence of measurement error within these products is often overlooked. Here, we detail the econometric implications of these errors when analyzing the determinants of binary measures of deforestation or forest cover. We then discuss estimators that exploit knowledge of the remote sensing process to obtain consistent estimates. Finally, we assess our estimators via simulation and an impact evaluation of a conservation program in Mexico. We find that both geography and characteristics of the raw data can lead to systematic under-reporting of deforestation. However, accounting for these sources of error, which are common across many satellite-based metrics, can limit the bias from misclassification.
(with Wenhua Di), Industry Specialization and Small Business Lending Journal of Banking & Finance (2023). []

We then examine the impact of the recent rise in industry-specialized small business lending on credit availability and banking competition.

This paper examines the rise and competitive impact of industry-specialized small business lenders. Using loan-level data with detailed industry codes from the Small Business Administration (SBA), we document a recent increase in lenders that originate loans nationally but to a limited number of industries. We then examine the impact of these industry-specialized lenders on credit availability and banking competition. Exploiting the staggered entry of a large, specialized lender, we find significant increases in total SBA-backed lending with no evidence of substitution from other lenders. We then explore potential mechanisms behind the increase in lending.
(with Hao Li and Punarjit Roychowdhury), COVID-19 Severity: A New Approach to Quantifying Global Cases and Deaths, Journal of the Royal Statistical Society, Series A (2023). []

Accounting for measurement error in the survey-based measures of household welfare, we find little evidence that poor households in India are catching up over time.

We examine economic mobility in India while accounting for measurement error to better understand the welfare effects of the rise in inequality. To proceed, we extend recently developed methods on the partial identification of transition matrices. Allowing for modest misclassification, we find overall mobility has been remarkably low: at least 75 percent of poor households remained poor or at-risk of being poor between 2005 and 2012. We also find Muslims, lower caste groups, and rural households are in a more disadvantageous position compared to Hindus, upper caste groups, and urban households. These findings cast doubt on the conventional wisdom that marginalized households in India are catching up.
, Do competitive bonuses ruin cooperation in heterogeneous teams?, Regional Science and Urban Economics (2023). []

This article presents the case for why academic journals should require data archives for all empirical papers they publish.
(with Taisuke Otsu and Luke Taylor), Nonparametric estimation of additive models with errors-in-variables, Econometric Reviews (2023). []

This paper introduces two novel procedures for selecting bandwidths in nonparametric regression models where classical measurement error is present in the regressors.

We propose two novel bandwidth selection procedures for the nonparametric regression model with classical measurement error in the regressors. Each method evaluates the prediction errors of the regression using a second (density) deconvolution. The first approach uses a typical leave-one-out cross-validation criterion, while the second applies a bootstrap approach and the concept of out-of-bag prediction. We show the asymptotic validity of both procedures and compare them to the SIMEX method in a Monte Carlo study. As well as dramatically reducing computational cost, the methods proposed in this article lead to lower mean integrated squared error (MISE) compared to the current state-of-the-art.
(with Ana Maria Santacreu and B. Ravikumar) TFP, Capital Deepening, and Gains from Trade, St. Louis Fed Review (2023). []

While dynamic gains from trade vary a lot across countries, the dynamics of consumption are approximately similar up to a scalar.

Using a dynamic, multicountry model with capital accumulation, we compute the exact transition paths for 93 countries following a permanent, uniform, unanticipated trade liberalization and calculate the resulting welfare gains from trade. We find that while the dynamic gains are different across countries, consumption transition paths look similar except for scale. In addition, dynamic gains accrue gradually and are about 60 percent of steady-state gains for every country. Finally, the contribution of capital accumulation to dynamic gains is four times that of total factor productivity.

2022

(with Chris Parmeter), COVID-19 Severity: A New Approach to Quantifying Global Cases and Deaths, Journal of the Royal Statistical Society, Series A (2022). []

We estimate several stochastic frontier models to address under-reporting of COVID-19 cases and deaths early in the pandemic to predict its actual severity.

As the COVID-19 pandemic has progressed, so too has the recognition that cases and deaths have been underreported, perhaps vastly so. Here, we present an econometric strategy to estimate the true number of COVID-19 cases and deaths for 61 and 56 countries, respectively, from 1 January 2020 through 3 November 2020. Specifically, we estimate a ‘structural’ model based on the SIR epidemiological model extended to incorporate underreporting. The results indicate significant underreporting by magnitudes that align with existing research and conjectures by public health experts. While our approach requires some strong assumptions, these assumptions are very different from the equally strong assumptions required by other approaches addressing underreporting in the assessment of the extent of the pandemic. Thus, we view our approach as a complement to existing methods.
(with Logan Lewis, Ryan Monarch, and Jing Zhang), Structural Change and Global Trade, Journal of the European Economics Association (2022). []

Increased global demand for services since 1970 suppressed the ratio of trade to GDP by almost as much as declining trade costs have boosted it.

Services, which are less traded than goods, rose from 55% of world expenditure in 1970 to 75% in 2015. Using a Ricardian trade model incorporating endogenous structural change, we quantify how this substantial shift in consumption has affected trade. Without structural change, we find that the world trade to GDP ratio would be 13 percentage points higher by 2015, about half the boost delivered from declining trade costs. In addition, a world without structural change would have had about 40% greater welfare gains from the trade integration over the past four decades. Absent further reductions in trade costs, ongoing structural change implies that world trade as a share of GDP would eventually decline. Going forward, higher-income countries gain relatively more from reducing services trade costs than from reducing goods trade costs.
and (with Edmond Awad, Manuel Cebrián, Ángel Cuevas, Rubén Cuevas, Ignacio Martín, Nick Obradovich, Ignacio Ortuño-Ortín, and Iyad Rahwan), Expanding the Measurement of Culture with a Sample of Two Billion Humans, Journal of the Royal Society Interface (2022). []

Data on topic dimensions from two billion Facebook users allows for a way to measure cultural distances between countries, regions, and populations.

Culture has played a pivotal role in human evolution. Yet, the ability of social scientists to study culture is limited by the currently available measurement instruments. Scholars of culture must regularly choose between scalable but sparse survey-based methods or restricted but rich ethnographic methods. Here, we demonstrate that massive online social networks can advance the study of human culture by providing quantitative, scalable and high-resolution measurement of behaviourally revealed cultural values and preferences. We employ data across nearly 60 000 topic dimensions drawn from two billion Facebook users across 225 countries and territories. We first validate that cultural distances calculated from this measurement instrument correspond to traditional survey-based and objective measures of cross-national cultural differences. We then demonstrate that this expanded measure enables rich insight into the cultural landscape globally at previously impossible resolution. We analyse the importance of national borders in shaping culture and compare subnational divisiveness with gender divisiveness across countries. Our measure enables detailed investigation into the geopolitical stability of countries, social cleavages within small- and large-scale human groups, the integration of migrant populations and the disaffection of certain population groups from the political process, among myriad other potential future applications.
(with Ron Cheung and Kuangli Xie), Homeowner associations and city cohesion, Regional Science and Urban Economics (2022). []

We examine whether the rise of Homeowner Associations may help explain why wealthier parts of cities rarely attempt to secede and decrease their tax burden to support less wealthy segments of a city.

Homeowner Associations (HOAs) are an increasingly common form of attempts to provide localized public goods to a subset of residents in a city. As HOAs have increased in size and scope, there have been substantial debates about their benefit, and in particular, their impact on citizens who are not HOA members. One argument against HOAs has been a perception that they lessen city cohesion by setting some citizens o⁄ from others. We investigate one channel through which HOAs might improve city cohesion: their ability to dull the desire for wealthy city residents to attempt to leave or secede from a city. We also examine the degree to which poor residents might take the secession option of wealthy residents into account when they form their preferences regarding tax levels for the city. We conduct an economic experiment aimed at eliciting preferences people may have under these different circumstances. We find that HOA-like options can reduce the desire of the wealthy to exit a city and that the presence or absence of an exit option or an HOA option can also impact the tax requests by the poorer residents in a city. Both results suggest a previously unexamined benefit of allowing HOAs.
(with Tapan Mitra), Stochastic Growth, Conservation of Capital and Convergence to a Positive Steady State, Economic Theory (2022). []

In a general optimal stochastic growth model, we provide a tight condition for convergence to a positive stochastic steady state and show the non-monotone effect of increase in risk aversion on long run extinction of capital.

In a general one-sector model of optimal stochastic growth where the productivity of capital is bounded but may vary widely due to technology shocks, we derive a tight estimate of the slope of the optimal policy function near zero. We use this to derive a readily verifiable condition that ensures almost sure global conservation of capital (i.e., avoidance of extinction) under the optimal policy, as well as global convergence to a positive stochastic steady state for bounded growth technology; this condition is significantly weaker than existing conditions and explicitly depends on risk aversion. For a specific class of utility and production functions, a strict violation of this condition implies that almost sure long run extinction of capital is globally optimal. Conservation is non-monotonic in risk aversion; conservation is likely to be optimal when the degree of risk aversion (near zero) is either high or low, while extinction may be optimal at intermediate levels of risk aversion.
, Media Access, Bias and Public Opinion, Public Choice (2022). []

I develop a model in which an incumbent with reelection concerns seeks to influence public opinion by strategically controlling the media’s access to information.

I develop a model in which an incumbent with reelection concerns seeks to influence public opinion by strategically controlling the media’s access to information. I show that the incumbent’s optimal access strategy balances her demand for positive bias with the public’s demand for credible coverage. The media’s access increases with the competence of politicians over issues under public focus. Controlling media’s access can be instrumental in shaping public opinion, especially in the hands of popular incumbents. Persistence of key election issues, however, decreases the effectiveness of media access control by incumbents.
, Demographics and the Evolution of Global Imbalances, Journal of Monetary Economics (2022). []

Bilateral trade frictions influence the incidence of bilateral and aggregate external imbalances triggered by demographic-induced saving demand.

The age distribution influences capital flows through aggregate saving and labor supply. To quantify this, I build a dynamic model featuring overlapping generations and international trade among 28 countries since 1970. The equilibrium is replicated by a model with a representative household in each country that experiences an endogenous discount factor, which summarizes the co-evolution of demographics and relevant prices, affording computation of the exact transition. On average, a one-year increase a country's mean age boosts its current account by 0.4 percent of GDP. Bilateral trade frictions dictate the cross-country response of capital flows to changes in a country's demographics.
(with Taisuke Otsu and Luke Taylor), Nonparametric estimation of additive models with errors-in-variables, Econometric Reviews (2022). []

This paper introduces a novel estimator for nonparametric additive models designed for the situation where data is contaminated by classical measurement errors.

In the estimation of nonparametric additive models, conventional methods, such as backfitting and series approximation, cannot be applied when measurement error is present in a covariate. This paper proposes a two-stage estimator for such models. In the first stage, to adapt to the additive structure, we use a series approximation together with a ridge approach to deal with the ill-posedness brought by mismeasurement. We derive the uniform convergence rate of this first-stage estimator and characterize how the measurement error slows down the convergence rate for ordinary/super smooth cases. To establish the limiting distribution, we construct a second-stage estimator via one-step backfitting with a deconvolution kernel using the first-stage estimator. The asymptotic normality of the second-stage estimator is established for ordinary/super smooth measurement error cases. Finally, a Monte Carlo study and an empirical application highlight the applicability of the estimator.
(with Romain Wacziarg), Understanding Spatial Variation in COVID-19 across U.S. Counties, Journal of Urban Economics (2022). []

What factors explain spatial variation in the severity of COVID-19 across the United States? Counties with high effective density, more nursing homes, lower income, and a greater presence of African Americans and Hispanics are disproportionately impacted. Trump-leaning counties are less severely affected early on, but later suffer from a large severity penalty.

What factors explain spatial variation in the severity of COVID-19 across the United States? To answer this question, we analyze the correlates of COVID-19 cases and deaths across US counties. We document four sets of facts. First, effective density is an important and persistent determinant of COVID-19 severity. Second, counties with more nursing home residents, lower income, higher poverty rates, and a greater presence of African Americans and Hispanics are disproportionately impacted, and these effects show no sign of disappearing over time. Third, the effect of certain characteristics, such as the distance to major international airports and the share of elderly individuals, dies out over time. Fourth, Trump-leaning counties are less severely affected early on, but later suffer from a large severity penalty.
(with Maarten Janssen), Regulating Product Communication, American Economic Journal: Microeconomics (2022). []

While it can increase competition and improve information for consumers, the regulation of false advertising and other deceptive communication by firms can lead to unintended consequences, including excessive advertising and over disclosure, that hurt consumers.

Information regulation that penalizes deceptive communication by firms can have significant unintended consequences. We consider a market where competing firms communicate private information about product quality through a combination of pricing and direct communication (advertising or labeling) that may be false. A higher fine for lying reduces the reliance on price signaling, thereby lowering market power and consumption distortions; however, it may lead to excessive disclosure. Low fines are always worse than no fines. High fines are welfare improving only if communication itself is inexpensive. Penalizing false claims may reduce profits of both high- and low-quality firms.
(with Chris Parmeter), Accounting for Skewed or One-Sided Measurement Error in the Dependent Variable, Political Analysis (2022). []

We show that the stochastic frontier model may be used to analyze continuous outcomes that potentially suffer from one-sided or heavily skewed measurement error.

While classical measurement error in the dependent variable in a linear regression framework results only in a loss of precision, nonclassical measurement error can lead to estimates which are biased and inference which lacks power. Here, we consider a particular type of nonclassical measurement error: skewed errors. Unfortunately, skewed measurement error is likely to be a relatively common feature of many outcomes of interest in political science research. This study highlights the bias that can result even from relatively small" amounts of skewed measurement error, particularly if the measurement error is heteroskedastic. We also assess potential solutions to this problem, focusing on the stochastic frontier model and nonlinear least squares. Simulations and three replications highlight the importance of thinking carefully about skewed measurement error, as well as appropriate solutions.
Santanu Roy, Propensity to Consume and the Optimality of Ramsey-Euler Policies, Economic Theory (2022). [Published article]

In a stochastic growth model where the production technology may be globally unproductive or allow for unbounded growth, a continuous and co-monotone Ramsey-Euler policy function may not be optimal if the propensity to consume is small.

In a general one-sector optimal stochastic growth model where the production technology may be globally unproductive or allow for unbounded growth, we outline readily verifiable sufficient conditions for optimality that do not require checking the transversality condition. An interior policy function satisfying the Ramsey-Euler condition may not be optimal even if consumption and investment are continuous and increasing in output; our conditions for optimality require that the policy function must also satisfy a lower bound on the propensity to consume. For the case of production functions with multiplicative shocks, the consumption propensity needs to be bounded away from zero; a similar condition is su¢ client for more general production functions if the utility function belongs to a restricted class.

2021

(with Richard M. Hynes), A Modern Poor Debtor’s Oath? Virginia Law Review (forthcoming). []

Several states have passed laws that prohibit employers from using credit reports in hiring decisions. This paper evaluates the impact of these bans on the labor market outcomes of financially distressed job seekers.

Several U.S. states ban employers’ use of credit reports in hiring decisions. This paper evaluates whether these bans help financially distressed individuals find employment. In the Survey of Income and Program Participation, we identify individuals likely to directly benefit – unemployed individuals with recent trouble meeting expenses. Exploiting the staggered passage of state laws, we find that banning credit checks increases the job-finding rates among financially distressed job seekers by about 28 percent. We also find an increase in the subsequent employment duration of the financially distressed who do find jobs, suggesting that they obtain more stable and permanent positions. Finally, we find a small, insignificant change in job-finding rates among the non-distressed, but we cannot rule out that this group is harmed by pooling with the financially distressed.
(with Chris Busch, David Domeij, and Fatih Guvenen), Skewed Idiosyncratic Income Risk over the Business Cycle: Sources and Insurance, AEJ: Macroeconomics (forthcoming). []

Using panel data from the United States, Germany, Sweden, and France, we show that households experience higher downside risk and lower chances of upward surprises during recessions—the skewness of earnings changes is pro cyclical— even for continuously employed full-time workers. Within-household smoothing does not seem effective at mitigating skewness fluctuations but government tax-and-transfer policies blunt some of the largest declines in incomes.

Recent studies have shown that idiosyncratic labor income risk becomes more left-skewed during recessions. This pro cyclical skewness arises from a combination of higher downside risk and lower chances of upward surprises during recessions. While this much is known, some important open questions remain. For example, how robust are these patterns across countries that differ in their institutions and policies, as well as across genders, education groups, and occupations, among others? What is the contribution of wages versus hours to pro cyclical skewness of earnings changes? To what extent can skewness fluctuations in individual earnings be smoothed within households or with government policies? Using panel data from the United States, Germany, Sweden, and France, we find four main results. First, the skewness of individual income growth (before-tax/transfer) is pro cyclical while its variance is flat and a cyclical in all three countries. Second, this result holds even for full-time workers continuously employed in the same establishment, indicating that the hours margin is not the main driver; additional analyses of hours and wages confirm that both margins are important. Third, within-household smoothing does not seem effective at mitigating skewness fluctuations. Fourth, tax-and-transfer policies blunt some of the largest declines in incomes, reducing pro cyclical fluctuations in skewness.
(with Luke N. Taylor), Nonparametric significance testing in measurement error models, Econometric Theory (forthcoming). []

This paper develops the first nonparametric significance test for regression models with classical measurement error in the regressors, and shows that the test can detect a sequence of local alternatives converging to the null at the root-n rate.

We develop the first nonparametric significance test for regression models with classical measurement error in the regressors. In particular, a Cramér-von Mises test and a Kolmogorov–Smirnov test for the null hypothesis E[Y|X*,Z*] = E[Y|X*] are proposed when only noisy measurements of X* and Z* are available. The asymptotic null distributions of the test statistics are derived, and a bootstrap method is implemented to obtain the critical values. Despite the test statistics being constructed using deconvolution estimators, we show that the test can detect a sequence of local alternatives converging to the null at the root-n rate. We also highlight the finite sample performance of the test through a Monte Carlo study.
(with Ayça Kaya), Market Screening with Limited Records, Games and Economic Behavior (forthcoming). []

In markets with adverse selection and repeated sales, welfare may initially increase and then decline with the length of trading record i.e., the number of past time periods whose trading outcomes can be observed by current participants.

Markets differ in the availability of past trading records of their participants. In a repeated sale model with adverse selection, we study the impact of the availability of such records on trading outcomes. We consider regimes varying with respect to the length of the available records. We characterize a class of equilibrium in which the record length has direct welfare implications via the market’s need to re-screen the seller, as well as indirect implications via the low quality seller’s incentives to mimic the high quality seller. As the record length increases, the market needs to re-screen less frequently, which improves efficiency. In turn, less frequent screening makes mimicking more attractive and limits the market’s ability to learn. These considerations lead to a non-monotonic relationship between record length and overall gains from trade.
(with Huseyin Yildirim), Credit Attribution and Collaborative Work, Journal of Economic Theory (2021). []

We examine incentives in research teams where the market, such as the scientific community, attributes credit for success based on its inference of individual efforts.

We examine incentives in research teams where the market, such as the scientific community, attributes credit for success based on its inference of individual efforts. A social planner who could commit to credit ex ante would induce more effort from higher ability agents in exchange for less credit per unit effort. Lacking such commitment, the Bayesian market assigns credit proportional to perceived effort. This inability to distort credit per unit effort leads to an incentive reversal across projects. For “easy” projects with a concave marginal cost of effort, in the unique interior equilibrium, higher ability agents work less and receive lower credit/utility, while the opposite holds for “difficult” projects with a sufficiently convex marginal cost of effort. Moreover, equilibrium may involve over-investment by some team members who expect to receive most of the credit. The incentives to team up and the implications of effort observability on credit attribution are also investigated.
Wookun Kim (with Pablo Fajgelbaum, Amit Khandelwal, Cristiano Mantovani, and Edouard Schaal), Optimal Lockdown in a Commuting Network, American Economic Review: Insights (forthcoming). [ and ]

Relative to city-wide uniform lockdowns implemented to fight COVID-19 around the world, spatially targeted lockdowns taking into account the commuting patterns and the spatial distribution of economic activity substantially improve economic efficiency while saving more lives.

We study optimal dynamic lockdowns against Covid-19 within a commuting network. Our framework integrates canonical spatial epidemiology and trade models, and is applied to cities with varying initial viral spread: Seoul, Daegu and NYC-Metro. Spatial lockdowns achieve substantially smaller income losses than uniform lockdowns. In NYM and Daegu—with large initial shocks—the optimal lockdown restricts inflows to central districts before gradual relaxation, while in Seoul it imposes low temporal but large spatial variation. Actual commuting reductions were too weak in central locations in Daegu and NYM, and too strong across Seoul.
(with Leora Friedberg and Richard Hynes), Who Benefits from Bans on Employer Credit Checks? The Journal of Law and Economics (forthcoming). []

Several states have passed laws that prohibit employers from using credit reports in hiring decisions. This paper evaluates the impact of these bans on the labor market outcomes of financially distressed job seekers.

Several U.S. states ban employers’ use of credit reports in hiring decisions. This paper evaluates whether these bans help financially distressed individuals find employment. In the Survey of Income and Program Participation, we identify individuals likely to directly benefit – unemployed individuals with recent trouble meeting expenses. Exploiting the staggered passage of state laws, we find that banning credit checks increases the job-finding rates among financially distressed job seekers by about 28 percent. We also find an increase in the subsequent employment duration of the financially distressed who do find jobs, suggesting that they obtain more stable and permanent positions. Finally, we find a small, insignificant change in job-finding rates among the non-distressed, but we cannot rule out that this group is harmed by pooling with the financially distressed.
(with Kei-Mu Yi and Jing Zhang), Trade Integration, Global Value Chains, and Capital Accumulation, IMF Economic Review (2021). [ and ]

Participation in global value chains complements growth and capital accumulation in emerging economies through the ability to transition from upstream, labor-intensive stages of production to downstream, capital-intensive activities.

Motivated by increasing trade and fragmentation of production across countries, accompanied by income convergence by many emerging economies, we build a dynamic two-country model featuring sequential, multi-stage production and capital accumulation. As trade costs decline over time, global-value-chain (GVC) trade expands across countries, particularly more in the faster-growing country, consistent with the empirical pattern. Via Heckscher–Ohlin forces, GVC trade can generate back-and-forth feedback between comparative advantage and capital accumulation (growth). Moreover, GVC trade increases both steady-state and dynamic gains from trade.
(with Taisuke Otsu and Luke Taylor), Estimation of varying coefficient models with measurement error, Journal of Econometrics (2021). []

This paper proposes a semiparametric estimator for varying coefficient models when the regressors in the nonparametric components are measured with error, and show that the estimator is consistent and asymptotically normally distributed.

We propose a semiparametric estimator for varying coefficient models when the regressors in the nonparametric components are measured with error. Varying coefficient models are an extension of other popular semiparametric models, including partially linear and nonparametric additive models, and deliver an attractive solution to the curse-of-dimensionality. We use deconvolution kernel estimation in a two-step procedure and show that the estimator is consistent and asymptotically normally distributed. We do not assume that we know the distribution of the measurement error a priori. Instead, we suppose we have access to a repeated measurement of the noisy regressor and present results using the approach of Delaigle, Hall and Meister (2008) and, for cases when the measurement error may be asymmetric, the approach of Li and Vuong (1998) based on Kotlarski’s (1967) identity. We show that the convergence rate of the estimator is significantly reduced when the distribution of the measurement error is assumed unknown and possibly asymmetric. We study the small sample behavior of our estimator in a simulation study and apply it to a real dataset. In particular, we consider the role of cognitive ability in augmenting the effect of risk preferences on earnings.
(with Ding Liu), Bounding the Joint Distribution of Disability and Employment with Misclassification, Health Economics (2021). []

We assess what can be learned about the joint distribution of disability status and labor market status at different time periods using self-reported data, accounting for the fact that such data is known to contain significant measurement error.

Understanding the relationship between disability and employment is critical and has long been the subject of study. However, estimating this relationship is difficult, particularly with survey data, since both disability and employment status are known to be misreported. Here, we use a partial identification approach to bound the joint distribution of disability and employment status in the presence of contaminated data. Allowing for a modest amount of contamination leads to bounds on the labor market status of the disabled that are not overly informative given the relative size of the disabled population. Thus, absent further assumptions, even a modest amount of contamination creates much uncertainty about the employment gap between the non-disabled and disabled. However, additional assumptions considered are shown to have some identifying power. For example, under our most stringent assumptions, we find that the employment gap is at least 15.2% before the Great Recession and 22.0% afterwards.
(with Romain Wacziarg), The Cultural Divide, Economic Journal (2021). [Published article]

Using US data from 1972 to 2018, cultural divides have been increasing along lines of religion and political orientation, mildly U-shaped along income and racial lines, and flat or decreasing for gender and urbanicity.

We study the evolution of cultural divides both theoretically and empirically. We propose a model of cultural change where intergenerational transmission and forces of social influence determine the distribution of cultural traits in society. We conduct an empirical investigation of the evolution of cultural heterogeneity in the US between 1972 and 2018, using the GSS. In recent decades, cultural heterogeneity between individuals has risen. Cultural divides between identity groups display contrasted patterns: increasing along lines of religion and political orientation, mildly U-shaped along income and racial lines, and at or decreasing for gender and urbanicity. We interpret these empirical findings in light of our model, arguing that changes in modes of interaction within and across groups can explain the observed dynamics of cultural heterogeneity.
(with Christopher Parmeter), Accounting for Skewed or One-Sided Measurement Error in the Dependent Variable, Political Analysis (2021). []

This paper discusses the issues that arise in linear regression models when the dependent variable suffers from nonclassical measurement error due to the error being skewed or one-sided. The paper then shows via simulations and replications the usefulness of stochastic frontier analysis in addressing these issues.

While classical measurement error in the dependent variable in a linear regression framework results only in a loss of precision, non-classical measurement error can lead to estimates which are biased and inference which lacks power. Here, we consider a particular type of non-classical measurement error: skewed errors. Unfortunately, skewed measurement error is likely to be a relatively common feature of many outcomes of interest in political science research. This study highlights the bias that can result even from relatively "small" amounts of skewed measurement error, particularly if the measurement error is heteroskedastic. We also assess potential solutions to this problem, focusing on the stochastic frontier model and nonlinear least squares. Simulations and three replications highlight the importance of thinking carefully about skewed measurement error, as well as appropriate solutions.
(with Enrique Martinez-Garcia and Zheng Zeng), In No Uncertain Terms: The Effect of Uncertainty on Credit Frictions and Monetary Policy, Economic Modelling (2021). []

In this paper, we examine how credit market frictions and time varying uncertainty interact and result in nonlinear relationships such as asymmetry between interest rate spreads and economic activity.

We examine the interaction of uncertainty and credit frictions in a New Keynesian framework. The model considers credit frictions arising from costly-state verification in the provision of loans to fund the acquisition of capital by entrepreneurs and includes three types of time-varying stochastic volatility shocks related to monetary policy uncertainty, financial risk (micro uncertainty), and macro uncertainty. Key parameters are estimated by the simulated method of moments using data from the United States from 1984:Q1 until 2014:Q4. We find that (1) micro uncertainty has first-order effects that are significantly larger than the effects of macro uncertainty and monetary policy uncertainty; (2) poor credit conditions exacerbate the economic drag from micro uncertainty shocks, amplify the effects of monetary policy shocks, and mitigate the impact of total factor productivity (TFP) shocks; (3) a degree of asymmetry and nonscalability appears in response to monetary policy shocks depending on the degree of nominal rigidities and initial conditions; and (4) monetary policy uncertainty accounts for about one-third of business cycle volatility largely by affecting the size of monetary policy shocks.
(with David Cuberes and Jordan Rappaport), Urban Growth Shadows, Journal of Urban Economics (2021). []

Proximity to large urban centers was negatively associated with growth until 1920, and positively associated with growth thereafter.

Does a location’s growth benefit or suffer from being geographically close to large economic centers? Spatial proximity may lead to competition and hurt growth, but it may also improve market access and enhance growth. Using data on U.S. counties and metro areas for the period 1840–2017, we document this trade off between urban shadows and urban access. Proximity to large urban centers was negatively associated with growth between 1840 and 1920, and positively associated with growth after 1920. Using a two-city spatial model, we show that the secular evolution of inter-city and intracity commuting costs can account for this. Alternatively, the long-run decline in inter-city shipping costs relative to intra-city commuting costs is also consistent with these observed patterns.
(with Logan T Lewis, Ryan Monarch and Jing Zhang), Structural Change and Global Trade, Journal of European Economic Association (2021). []

The global expansion of expenditures on services relative to goods has impeded growth in global openness and mitigated the gains from further trade integration in goods markets.

Services, which are less traded than goods, rose from 55% of world expenditure in 1970 to 75% in 2015. Using a Ricardian trade model incorporating endogenous structural change, we quantify how this substantial shift in consumption has affected trade. Without structural change, we find that the world trade to GDP ratio would be 13 percentage points higher by 2015, about half the boost delivered from declining trade costs. In addition, a world without structural change would have had about 40% greater welfare gains from the trade integration over the past four decades. Absent further reductions in trade costs, ongoing structural change implies that world trade as a share of GDP would eventually decline. Going forward, higher-income countries gain relatively more from reducing services trade costs than from reducing goods trade costs.
(with Ren Zhang and Zheng Zeng), Identifying Credit Demand, Financial Intermediation, and Supply of Funds Shocks: A Structural VAR Approach, North American Journal of Economics and Finance (2021). []

In this paper, we find that shocks to financial intermediary lending played a significant role in the decline in economic activity experienced during the “Great Recession” of 2007-09; shocks to the demand for loans and shocks in the supply of funds to financial intermediaries were not important contributors to the “Great Recession”.

In this paper, we identify three exogenous shocks to credit market: demand for credit, supply of funds into the financial system, and the willingness to lend of financial institutions (financial intermediation), and also, determine the contribution of these shocks to fluctuations in the credit market and overall economic activity. We estimate a structural vector auto regression model where the three credit shocks are identified with a set of sign restrictions motivated by a simple partial equilibrium model of financial intermediation. We find that the credit demand shock explains significantly the variations in the long-term loan rate proxied by the Moody’s Baa corporate bond yield, while the supply of funds shock contributes to most of the fluctuations in the short-term commercial paper rate. The financial intermediation shock drives most of the fluctuations in the quantity of loans as well as the spread between the Baa and commercial paper rates. Of the credit shocks, we find that the financial intermediation shock has the largest impact on real economic activity. In fact, our analysis implies that the sharp decline in output during the 2007–2009 financial crisis is largely attributable to the financial intermediation shock, along with shocks originating outside of the financial system.

2020

(with Robert Kopp, Scott Kulp, David Nagy, Michael Oppenheimer, Esteban Rossi-Hansberg and Ben Strauss), Evaluating the Economic Cost of Coastal Flooding, American Economic Journal: Macroeconomics (forthcoming). []

A high-resolution dynamic model of the world economy projects that permanent flooding will reduce global GDP by 0.19% in present value terms; Ignoring the dynamic response of migration increases the loss in GDP in the year 2200 from 0.11% to 4.5%.

Sea-level rise and ensuing permanent coastal inundation will cause spatial shifts in population and economic activity over the next 200 years. Using a highly spatially disaggregated, dynamic model of the world economy that accounts for the dynamics of migration, trade, and innovation, this paper estimates the consequences of probabilistic projections of local sea-level changes under dierent emissions scenarios. Under an intermediate greenhouse gas concentration trajectory, permanent coding is projected to reduce global real GDP by an average of 0.19% in present value terms, with welfare declining by 0.24% as people move to places with less attractive amenities. By the year 2200 a projected 1.46% of world population will be displaced. Losses in many coastal localities are more than an order of magnitude larger, with some low-lying urban areas particularly hard hit. When ignoring the dynamic economic adaptation of investment and migration to coding, the loss in real GDP in 2200 increases from 0.11% to 4.5%. This shows the importance of including dynamic adaptation in future loss models.
(with Taisuke Otsu and Luke Taylor), Average Derivative Estimation Under Measurement Error, Econometric Theory (forthcoming). []

This paper derives the asymptotic distribution of the density-weighted average derivative when a regressor is contaminated with a classical measurement error, and shows that the asymptotic distribution of the estimator is the same irrespective of whether the error distribution is estimated or not when the error density is symmetric.

We derive the asymptotic properties of the density-weighted average derivative estimator when a regressor is contaminated with classical measurement error and the density of this error must be estimated. Average derivatives of conditional mean functions are used extensively in economics and statistics, most notably in semiparametric index models. As well as ordinary smooth measurement error, we provide results for supersmooth error distributions. This is a particularly important class of error distribution as it includes the Gaussian density. We show that under either type of measurement error, despite using nonparametric deconvolution techniques and an estimated error characteristic function, we are able to achieve a root-n rate of convergence for the average derivative estimator. Interestingly, if the measurement error density is symmetric, the asymptotic variance of the average derivative estimator is the same irrespective of whether the error density is estimated or not. The promising finite sample performance of the estimator is shown through a Monte Carlo simulation.
(with Maarten Janssen), Regulating Product Communication, American Economic Journal: Microeconomics (forthcoming). []

While it can increase competition and improve information for consumers, the regulation of false advertising and other deceptive communication by firms can lead to unintended consequences, including excessive advertising and over disclosure, that hurt consumers.

Information regulation that penalizes deceptive communication by firms can have significant unintended consequences. We consider a market where competing firms communicate private information about product quality through a combination of pricing and direct communication (advertising or labeling) that may be false. A higher fine for lying reduces the reliance on price signaling, thereby lowering market power and consumption distortions; however, it may lead to excessive disclosure. Low fines are always worse than no fines. High fines are welfare improving only if communication itself is inexpensive. Penalizing false claims may reduce profits of both high and low quality firms.
(with Marius Brulhart and Gian-Paolo Klinke), The Shrinking Advantage of Market Potential, Journal of Development Economics (2020). []

Data from 18,961 regions of the world show that as economies develop, market potential loses importance and local density gains importance as determinants of regional growth.

How does a country’s economic geography evolve along the development path? This paper documents recent employment growth in 18,961 regions in eight of the world’s main economies. Overall, market potential is losing importance, and local employment density is gaining importance, as correlates of local growth. In mature economies, growth is strongest in low-market potential areas. In emerging economies, the opposite is true, though the association with market potential is also weakening there. Structural transformation away from agriculture can account for some of the observed changes. The part left unexplained by structural transformation is consistent with a standard economic geography model that yields a bell-shaped relation between trade costs and the growth of centrally located regions.
Santanu Roy, Propensity to Consume and the Optimality of Ramsey-Euler Policies, Economic Theory (2020). [Published article]

In a stochastic growth model where the production technology may be globally unproductive or allow for unbounded growth, a continuous and co-monotone Ramsey-Euler policy function may not be optimal if the propensity to consume is small.

In a general one-sector optimal stochastic growth model where the production technology may be globally unproductive or allow for unbounded growth, we outline readily verifiable sufficient conditions for optimality that do not require checking the transversality condition. An interior policy function satisfying the Ramsey-Euler condition may not be optimal even if consumption and investment are continuous and increasing in output; our conditions for optimality require that the policy function must also satisfy a lower bound on the propensity to consume. For the case of production functions with multiplicative shocks, the consumption propensity needs to be bounded away from zero; a similar condition is su¢ cient for more general production functions if the utility function belongs to a restricted class.
(with Richard Hynes), Asset Exemptions and Consumer Bankruptcies: Evidence from Individual Filings, The Journal of Law and Economics (2020). [ and ]

Using detailed individual-level data on all bankruptcies filed over the last decade, we examine how more generous asset exemptions change the number and characteristics of households filing for bankruptcy.

Bankruptcy exemptions vary markedly across states, but the literature has failed to show a clear relationship between the generosity of exemptions and the bankruptcy filing rate. One reason for this failure is that many debtors lack sufficient assets to make differences in exemptions relevant; an “unlimited” homestead exemption does not help the household with no home or with a home that is underwater. Using detailed individual-level data on all bankruptcies filed over a decade, this paper shows that when states increase their homestead exemptions, more households with home equity file for bankruptcy. Moreover, this rise occurs in the exact month that the exemptions increase. However, due to the large number of bankrupt households with no home equity, our estimated effect is quite modest. We estimate that if every state increased its homestead exemption by ten percent, aggregate annual bankruptcy filings would increase by about 2,250 or 0.3%.
(with Emilio Depetris-Chauvin),The Origins of the Division of Labor in Pre-Industrial Times, Journal of Economic Growth (2020). []

Population diversity in intergenerational transmitted traits (e.g., preferences, values, abilities) is a fundamental determinant of the division of labor in pre-modern times, which in turn has had a major impact on the emergence of states and pre-industrial and contemporary economic development.

This research explores the historical roots of the division of labor in pre-industrial societies. Exploiting a variety of identification strategies and a novel ethnic level dataset combining geocoded ethnographic, linguistic and genetic data, it shows that higher levels of intra-ethnic diversity were conducive to economic specialization in the pre-industrial era. The findings are robust to a host of geographical, institutional, cultural and historical confounders, and suggest that variation in intra-ethnic diversity is a key predictor of the division of labor in pre-industrial times.
(with Jeffry Jacob), Democracy and Growth: A Dynamic Panel Data Study, The Singapore Economic Review (2020). []

Investigating the nexus between democracy and economic development in a new empirical framework, we find that we find that measures of democracy matter little for a country’s economic performance, in contrast to the growth effects of institutions, regime stability, openness, geography and macro-economic policy variables.

In this paper, we investigate the idea whether democracy has a direct effect on economic growth. We use a system GMM framework that allows us to model the dynamic aspects of the growth process and control for the endogenous nature of many explanatory variables. In contrast to the growth effects of institutions, regime stability, openness, geography and macro-economic policy variables, we find that measures of democracy matter little, if at all, for the economic growth process.
, Consumption Smoothing and Debtor Protections, Journal of Public Economics (2020). []

Consumption declines in years when borrowers default, indicating that the legal protection of delinquent borrowers may provide valuable insurance. Evaluating asset protections, however, I find that the interest rate cost exceeds the welfare benefit of the protection.

Protections for defaulting debtors are a widely used form of consumption insurance. This paper evaluates the costs and benefits of this insurance, both inside and outside of bankruptcy. First, I show that consumption declines by 6% upon default, revealing a potential role for greater debtor protections to smooth consumption. Second, I use changes in states’ laws to estimate the impact of one type of debtor protection, asset exemptions, on repayment in default and interest rates. While higher exemptions smooth consumption by reducing collection in default, the interest rate cost is large relative to the benefits. Adapting a sufficient statistics formula from the literature, the estimates imply that the cost of additional exemption protection exceeds what debtors are willing to pay.
(with Avner Greif and Stephen Parente), Spatial Competition, Innovation and Institutions: The Industrial Revolution and the Great Divergence, Journal of Economic Growth (2020). [ and ]

This paper argues that differences in the degree of inter-city competition can help us understand the timing of the Industrial Revolution and the Great Divergence between England and China in the 18th and 19th centuries.

This paper considers the possible contribution of spatial competition to the Industrial Revolution and the Great Divergence. Rather than exclusively focusing on the incentives of producers to adopt labor-saving technology, we also consider the incentives of factor suppliers’ organizations such as craft guilds to resist. Once we do so, industrialization no longer depends on market size per se, but on spatial competition between the guilds’ jurisdictions. We substantiate our theory’s claim of spatial competition being an important channel for industrialization (i) by providing historical evidence on the relation between spatial competition, craft guilds and innovation, and (ii) by showing that the calibrated model correctly predicts the timings of the Industrial Revolution and the Great Divergence.
(with Oded Galor and Assaf Sarid), Linguistic Traits and Human Capital Formation, AEA Papers and Proceedings. [ and ]

Exploiting variations in the languages spoken by children of migrants with identical ancestral countries of origin, we establish that the presence of periphrastic future tense, and its association with long-term orientation has a significant positive impact on educational attainment, whereas the presence of sex-based grammatical gender, and its association with gender bias, has a significant adverse impact on female educational attainment.

This research establishes the influence of linguistic traits on human behavior. Exploiting variations in the languages spoken by children of migrants with identical ancestral countries of origin, the analysis indicates that the presence of periphrastic future tense, and its association with long-term orientation has a significant positive impact on educational attainment, whereas the presence of sex-based grammatical gender, and its association with gender bias, has a significant adverse impact on female educational attainment.
(with Joseph Gomes and Ignacio Ortuño), The Geography of Diversity and the Provision of Public Goods, Journal of Development Economics (2020). [ and ]

This paper shows that local interaction between individuals of different ethnolinguistic groups improves educational, health and infrastructure outcomes at the national level.

This paper analyzes the importance of local interaction between individuals of diﬀerent ethnolinguistic groups for the provision of public goods at the national level. The conceptual framework we develop suggests that a country’s public goods (i) decrease in its overall ethnolinguistic fractionalization, and (ii) either increase or decrease in its local-global ethnolinguistic complementarity, a measure of how local interaction aﬀects antagonism towards other groups in the society at large. After constructing a 5 km by 5 km dataset on language use for 223 countries, we empirically explore these theoretical predictions. While overall fractionalization worsens public goods outcomes, local interaction mitigates this negative association. Conditional on a country’s overall diversity, public goods outcomes are maximized when there are a few large-sized groups and the diversity of each location mirrors that of the country as a whole
(with Angela de Oliveira, John Ledyard, Charles Plott and Louis Putterman), Introduction to the Symposium on Research on Social Dilemmas, Economic Inquiry (2020). []

This is the introduction to a special issue of Economic Inquiry associated the seventh in a series of workshops on social dilemmas begun by Elinor Ostrom in 2002 that attracted a large number of high quality submissions over a broad range of topics in the research area.

2019

(with Antonio Cabrales, Maia Güell and Analia Viola), Income Contingent University Loans: Policy Design and an Application to Spain, Economic Policy (2019) [ and ]

This paper offers a general analysis of the distributional effects of income-contingent loan systems to finance tertiary education, followed by an application to Spain.

In Europe, the need for additional funding coming from either budget cuts and/or increased costs due to increased competition has reopened the debate on the financing of university systems. An attractive alternative to the current general-tax-financed subsidies are Income Contingent Loans (ICL), a flexible scheme that puts more weight on private resources while enhancing progressivity. One challenge of the viability of ICL systems is the functioning of the labor market for university graduates. This paper offers a general analysis of the economics of ICL, followed by an application to Spain. We set up a loan laboratory in which we can explore the distributional effects of different loan systems to finance tertiary education at current costs as well as to increase university funding to improve in its quality. We use simulated lifetime earnings of graduates matching the dynamics of employment and earnings in the Spanish administrative social security data to calculate the burden of introducing ICL for individuals at different points of the earnings distribution and for the government. We find that (1) our proposed structure is highly progressive under all specifications, with the top quarter of the distribution paying close to the full amount of the tuition and the bottom 10\% paying almost no tuition; and (2) the share of total university education subsidized by the government is between 16 and 56 percentage points less than under the current system.
(with B. Ravikumar and Ana Maria Santacreu), Capital Accumulation and Dynamic Gains from Trade, Journal of International Economics (2019). []

We develop a gradient-free method to compute the welfare gains from trade in a multi-country, dynamic model of trade with capital accumulation and current account dynamics.

We compute welfare gains from trade in a dynamic, multi-country model with capital accumulation and trade imbalances. We develop a gradient-free method to compute the exact transition paths following a trade liberalization. We find that (i) larger countries accumulate a current account surplus, and financial resources flow from larger countries to smaller countries, boosting consumption in the latter, (ii) countries with larger short-run trade deficits accumulate capital faster, (iii) the gains are nonlinear in the reduction in trade costs, and (iv) capital accumulation accounts for substantial gains. The net foreign asset position before the liberalization is positively correlated with the gains. The tradable intensity in consumption goods production determines the static gains, and the tradable intensity in investment goods production determines the dynamic gains that include capital accumulation.
(with Rajashri Chakrabarti), Auto Credit and the 2005 Bankruptcy Reform: The Impact of Eliminating Cramdowns, The Review of Financial Studies (2019) []

Exploiting persistent historical variation in states’ bankruptcy patterns, we find that increased creditor protection from a major 2005 bankruptcy reform led to lower interest rates for consumers.

Auto lenders were perhaps the biggest winners of the 2005 Bankruptcy Reform, as Chapter 13 bankruptcy filers can no longer “cram down” the amount owed on recent auto loans. We estimate the causal effect of this anti-cram down provision on the price and quantity of auto credit. Exploiting historical variation in states’ usage of Chapter 13 bankruptcy, we find strong evidence that eliminating cram downs decreased interest rates and some evidence that loan sizes increased among subprime borrowers. The decline in interest rates is persistent and is robust to a battery of sensitivity checks. We rule out other reform changes as possible causes. Received September 29, 2016; editorial decision January 15, 2019 by Editor Philip Strahan. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
(Joint with Yu Chen and David Rietzke), Simple Contracts under Observable and Hidden Actions, Economic Theory (2019). []

Simple forcing contracts are both optimal and useful for general multitask moral hazard problems with both observable and hidden actions.

We consider a general framework for multitask moral hazard problems with observable and hidden actions. Ideally, the principle in out framework can design optimal contracts that depend on both observable (and verifiable) actions and realized outcomes. Given a mild assumption on the existence of a punishment scheme, we identify a general equivalence result, dubbed the "forcing principle", which states that every optimal contract in our framework is strategically equivalent to a simple forcing contract, which only specifies an outcome-contingent reward scheme and an action profile, and the agent receives the outcome-contingent reward only if he follows the recommended observable actions (and is otherwise punished severely). The forcing principle has useful implications: it confers analytical advantage for the existence and computation of optimal contracts in our setting. It also highlights and makes explicit the importance of the existence of the punishment scheme in characterizing first-best benchmarks in moral hazard problems.
(with Shawna Grosskopf, Laura Razzolini, and Lori Taylor), Kids or Cash? Exploring Charter School Responses to Declining Government Revenues, Economic Inquiry (2019) []

We find that charter schools typically increase enrollments, rather than increasing fundraising, in response to funding cuts.

While the literature is extensive on school districts' revenue sources, less research has been done on the impact of donations on school district funds. In this paper, we extend the theoretical literature on crowding out of private donations by government grants for one type of nonprofit firm, namely charter schools. The theoretical model leads us to focus on the key relationships among fundraising effort, enrollment (which is tied to federal and state funding) and donations. Using a dataset on Texas charter schools we adopt a two‐stage approach to examine the empirical relationship between changes in nondonor revenues and the donations received by charter schools. Like the extensive empirical estimates of the effects of government grants on donations for other types of nonprofit firms, we find evidence of crowding‐out with respect to our sample of charter schools. We also find a significant, positive effect of fundraising on donations with a $1 increase in fundraising associated to a $0.58 increase in donations, a pattern consistent with overinvestment in fundraising. Enrollments exhibit a robust inverse relationship to changes in nondonor revenues.
(with Hao Li and Punarjit Roychowdhury), Partial Identification of Economic Mobility, Journal of Business & Economic Statistics (2019). [ and ]

This paper discusses the partial identification of income mobility when using error-laden, self-reported data on income at two points in time.

The economic mobility of individuals and households is of fundamental interest. While many measures of economic mobility exist, reliance on transition matrices remains pervasive due to simplicity and ease of interpretation. However, estimation of transition matrices is complicated by the well-acknowledged problem of measurement error in self-reported and even administrative data. Existing methods of addressing measurement error are complex, rely on numerous strong assumptions, and often require data from more than two periods. In this paper, we investigate what can be learned about economic mobility as measured via transition matrices while formally accounting for measurement error in a reasonably transparent manner. To do so, we develop a nonparametric partial identification approach to bound transition probabilities under various assumptions on the measurement error and mobility processes. This approach is applied to panel data from the United States to explore short-run mobility before and after the Great Recession.
(with Adriana Piazza), Irreversibility and the Economics of Forest Conservation, Economic Theory (2019). []

Difficulty of regenerating forest on land used for non-forest economic activities can discourage expansion of forests and at the same time, make it optimal to conserve a minimal forested area; low reforestation cost can lead to cyclical fluctuations in optimal forest cover.

For the canonical one sector stochastic optimal growth model, we outline a new set of conditions for a policy function that satisfies the Ramsey-Euler equation to be optimal. An interior Ramsey-Euler policy function is optimal if, and only if, it is continuous or alternatively, if, and only if, both consumption and investment are non-decreasing in output. In particular, we show that under these conditions, the stochastic paths generated by the policy must satisfy the transversality condition; the implication is that in applying our result, one does not need to verify the transversality condition when checking for optimality of a policy function.
(with Adam Shniderman), Ambiguity in Criminal Punishment, Journal of Economic Behavior & Organization (2019). []

While many prior studies find evidence that individuals are strongly ambiguity averse, we investigate whether such preferences can be exploited by using increased ambiguity in punishments but find little evidence that behavior is driven by ambiguity aversion in this domain.

There has been substantial prior field research on how the incidence of criminal behavior responds to changes in the probability of punishment. The results of this research are at best mixed in regards to its conformance to the predictions of standard expected utility theory. One possible cause for these mixed results is that punishment probabilities in the field are typically unknown making the choice environment one of ambiguity rather than uncertainty. The presence of this ambiguity could in part explain some of these conflicting results. As a step towards investigating this link, we conduct an experiment framed as being on tax compliance intended to try to understand how individuals respond to ambiguous punishment probabilities and in particular to how they respond to shifts in ambiguous versus known probabilities. We find that when probabilities are known and shift, the standard model works well to explain the response. When the probabilities are ambiguous and shift, the behavioral response is minimal. We also use these experiments as a means of testing whether ambiguity aversion might be present in sufficient degree to be exploitable in how enforcement procedures are advertised to increase their effectiveness at minimal cost. We find at best weak evidence in favor of ambiguity aversion and thus little support for the notion that enforcement regimes could take advantage of ambiguity aversion.
(with Jared Warren), Retaliatory Antidumping by China: A New Look at the Evidence, Eastern Economic Journal (2019). []

Examining a large number of factors that may influence China’s decision to retaliate using antidumping filings from 1995 to 2015, we find, among others, that higher levels of China’s country-specific imports as well as lower growth rates of China’s GDP increase the likelihood of retaliation.

China is the most frequent target of antidumping (AD) filings and the sixth most frequent user of antidumping duties. In this paper, we investigate the factors that influence China’s decision to retaliate using AD filings from 1995 to 2015. We consider an AD filing by China to be retaliatory if it occurs within 1 year of an initial AD filing against them and determine the factors that explain retaliatory antidumping filings. We find that higher levels of China’s country-specific imports, lower growth rates of Chinese GDP, and China’s WTO membership increase the likelihood of retaliation. In contrast, higher import growth reduces AD retaliation.
Evolving Comparative Advantage, Sectoral Linkages, and Structural Change, Journal of Monetary Economics (2019) []

Input-output linkages systematically vary with income levels across countries, and these differences are important for explaining the hump shape in the share of industry in aggregate GDP across income levels.

Intermediate-input intensities vary systematically with economic development across countries. These cross-country differences in input–output linkages account for 74% of the curvature in the hump shape in industry’s share in value added across levels of income per capita. This is twice as much as can be accounted for by variation in the composition of final demand. Using a three-sector, open-economy model of structural change I find that this result is robust to general equilibrium effects.

2018

(with Piyusha Mutreja and B. Ravikumar), Capital Goods Trade, Relative Prices, and Economic Development, Review of Economic Dynamics (2018). []

Trade enables poor countries access to capital goods produced in rich countries, boosting their capital stock, and also improves their TFP by allowing them to specialize in the production of non-capital goods.

International trade in capital goods has quantitatively important effects on economic development through capital formation and TFP. Capital goods trade enables poor countries to access more efficient technologies, leading to lower relative prices of capital goods and higher capital–output ratios. Moreover, poor countries use their comparative advantage and allocate their resources more efficiently, and increase their TFP. We quantify these channels using a multisector, multicountry, Ricardian model of trade with capital accumulation. The model matches several trade and development facts within a unified framework. Frictionless trade in capital goods reduces the income gap between rich and poor countries by 40 percent. More than half of the reduction in the income gap is due to the TFP channel.
(with Dávid Krisztián Nagy and Esteban Rossi-Hansberg), The Geography of Development, Journal of Political Economy (2018) []

This paper develops a dynamic spatial growth model, calibrates it at the 1-degree by 1-degree geographic resolution for the whole world, and shows that fully liberalizing migration would increase global welfare about threefold.

We develop a dynamic spatial growth theory with realistic geography. We characterize the model and its balanced-growth path and propose a methodology to analyze equilibria with different levels of migration frictions. Different migration scenarios change local market size, innovation incentives, and the evolution of technology. We bring the model to the data for the whole world economy at a 1-degree by 1-degree geographic resolution. We then use the model to quantify the gains from relaxing migration restrictions. Our results indicate that fully liberalizing migration would increase welfare about threefold and would signiﬁcantly affect the evolution of particular regions of the world.
, Distance to the Pre-industrial Technological Frontier and Economic Development, Journal of Economic Growth (2018). []

This paper establishes that geographical isolation from the technological frontier during the pre-industrial era has had beneficial effects on countries' economic development in the long-run as it fostered a culture of entrepreneurship and innovation.

This research explores the effects of distance to the pre-industrial technological frontiers on comparative economic development in the course of human history. It establishes theoretically and empirically that distance to the frontier had a persistent non-monotonic effect on a country’s pre-industrial economic development. In particular, advancing a novel measure of the travel time to the technological frontiers, the analysis establishes a robust persistent U-shaped relation between distance to the frontier and pre-industrial economic development across countries. Moreover, it demonstrates that countries, which throughout the last two millennia were relatively more distant from these frontiers, have higher contemporary levels of innovation and entrepreneurial activity, suggesting that distance from the frontier may have fostered the emergence of a culture conducive to innovation, knowledge creation, and entrepreneurship.
and Raj Deb, The Role of Aggregate Information in a Binary Threshold Game, Social Choice and Welfare (2018). [ and ]

The minimal information (of previous contributions) required for full coordination in sequential contribution for a public good with a known threshold and no refund is not full observation but that the participants' observation is linked in an information chain with certain length.

We analyze the problem of coordination failure in the presence of imperfect information in the context of a binary-action sequential game with a tipping point. An information structure summarizes what each agent can observe before making her decision. Focusing on information structures where only aggregate information from past history can be observed, we characterize information structures that can lead to various (efficient and inefficient) Nash equilibria. When individual decision making can be rationalized using a process of iterative dominance (Moulin 1979), we derive a necessary and sufficient condition on information structures under which a unique and efficient dominance solvable equilibrium outcome is obtained. Our results suggest that if sufficient (and not necessarily perfect) information is available, coordination failure can be overcome without centralized intervention.
, Choosing a Media Outlet when Seeking Public Approval, Public Choice (2018). []

This paper considers the media outlet choice of a politician who seeks public approval for a political agenda and shows that (1) politicians who enjoy sufficient popularity are likely to avoid tough media outlets, and (2) when seeking approval for controversial agendas, politicians are more likely to appear in tougher outlets.

This paper considers the media outlet choice of a politician who seeks public approval for a political agenda in a broadcast interview. The available media outlets differ in their ‘‘toughness’’ towards the politician. An interview with a tougher media outlet is more informative, but is also more likely to yield a negative outcome. The choice of the media outlet determines the accuracy of the information that ﬂows to the public and the volume of citizens who consume that information. The analysis shows that (1) politicians who enjoy sufﬁcient popularity are likely to avoid tough media outlets, (2) when seeking approval for controversial agendas, politicians are more likely to appear in tougher outlets.
(with Stephen Brown), Oil Supply Shocks and the U.S. Economy: An Estimated DSGE Model, Energy Policy (2018). []

We quantify the responsiveness of the US economy to oil price increases brought about by oil supply disruptions abroad.

We develop and use a medium-sized DSGE model of the U.S. economy to evaluate how U.S. real GDP responds to oil price movements that originate from global oil supply shocks. The core of the model is a standard macroeconomic DSGE framework that includes nominal and real frictions. The model includes oil as an input in multiple domestic sectors (consumption, intermediate goods, and transportation services). We include a domestic oil production sector for the United States to reflect the recent development in shale oil technology. The model also captures international trade in goods and oil. The model parameters are set through a combination of calibration and Bayesian estimation using quarterly data for 1991 through 2015. Baseline estimation of the model finds the elasticity of U.S. real GDP with respect to an oil price shock of − 0.015, which is among the less elastic estimates in the literature. Using the model to conduct counterfactual analysis, we find that decreasing steady state U.S. oil consumption substantially reduces the response of real GDP to oil prices. Increasing U.S. domestic oil production only modestly reduces the response of real GDP to oil prices.
(with Jeffry Jacob), Democracy and Growth: A Dynamic Panel Data Study, Singapore Economic Review (2018). [ and ]

Investigating the nexus between democracy and economic development in a new empirical framework, we find that we find that measures of democracy matter little for a country’s economic performance, in contrast to the growth effects of institutions, regime stability, openness, geography and macro-economic policy variables.

In this paper we investigate the idea whether democracy has a direct effect on economic growth. We use a system GMM framework that allows us to model the dynamic aspects of the growth process and control for the endogenous nature of many explanatory variables. In contrast to the growth effects of institutions, regime stability, openness, geography and macro-economic policy variables, we find that measures of democracy matter little, if at all, for the economic growth process.
and (with Ian McDonough), Financial Capability and Food Security in Extremely Vulnerable Households, American Journal of Agricultural Economics (2018). []

Using original survey data collected from food pantry clients throughout North Texas, we find a statistically and economically meaningful causal effect of financial literacy on the food security status of households.

Food insecurity is among the most significant, nutrition-related public health issues facing the United States. Unfortunately, little is known about the determinants of food insecurity except that it is not synonymous with poverty. Many households above the poverty line are food insecure; many below are not. We investigate a lack of financial capability as a potential salient determinant of household-level food security. Using original survey data collected among food pantry clients in North Texas, we assess the impact of financial capacity on food security relying on family background as an exclusion restriction. Our results indicate a strikingly significant effect, both economically and statistically, of financial capability in general and financial behaviors in particular.
(with Pranavi Sreeramoju, Lucia Dura, Maria Fernandez, Abu Minhajuddin, Kristina Simacek, and Bradley Doebbeling), Using a Positive Deviance Approach to Influence Culture of Patient Safety Related to Infection Prevention, Open Forum Infectious Diseases (2018). []

A positive deviance approach appeared to have a significant impact on patient safety culture related to infection prevention among health care personnel who received the intervention.

Health care–associated infections (HAIs) are a socio-technical problem. We evaluated the impact of a social change intervention on health care personnel (HCP), called “positive deviance” (PD), on patient safety culture related to infection prevention among HCP. A positive deviance approach appeared to have a significant impact on patient safety culture among HCP who received the intervention. Social network analysis identified HCP who are likely to help disseminate infection prevention information. Systemwide interventions independent of PD resulted in HAI reduction in both intervention and control wards. Health care–associated infections (HAIs) are a socio-technical problem. We evaluated the impact of a social change intervention on health care personnel (HCP), called “positive deviance” (PD), on patient safety culture related to infection prevention among HCP.

2017

(with Ignacio Ortuño and Romain Wacziarg), Culture, Ethnicity, and Diversity, American Economic Review (2017). []

This paper empirically shows that only 1-2% of a country's overall heterogeneity occurs between ethnolinguistic groups, yet the degree of between-group cultural differences are a significant predictor of civil conflicts.

We investigate the empirical relationship between ethnicity and culture, defined as a vector of traits reflecting norms, values, and attitudes. Using survey data for 76 countries, we find that ethnic identity is a significant predictor of cultural values, yet that within group variation in culture trumps between-group variation. Thus, in contrast to a commonly held view, ethnic and cultural diversity are unrelated. Although only a small portion of a country’s overall cultural heterogeneity occurs between groups, we find that various political economy outcomes (such as civil conflict and public goods provision) worsen when there is greater overlap between ethnicity and culture.
James Lake and , Are Global Trade Negotiations Behind a Fragmented World of "Gated Globalization"?, Journal of International Economics (2017). [ and ]

Global tariff negotiations can prevent global free trade precisely because they are successful in lowering global tariffs.

We show that global trade negotiations can prevent global free trade. In a simple model where global tariff negotiations precede sequential Free Trade Agreements (FTAs), we show FTA formation can expand all the way to global free trade in the absence of global tariff negotiations but global free trade never emerges when global tariff negotiations precede FTA formation. This result arises precisely because global tariff negotiations successfully elicit concessions from negotiating countries. Moreover, global tariff negotiations can produce a fragmented world of gated globalization where some countries form FTAs that eliminate tariff barriers among themselves while outsiders continue facing higher tariffs.
(with Ani Harutyunyan), Culture, Diffusion, and Economic Development: The Problem of Observational Equivalence, Economics Letters (2017). []

This paper establishes the difficulty of determining whether cultural values affect economic development directly or by hindering adoption of improved technologies as the recent literature strives to do.

This research explores the direct and barrier effects of culture on economic development. It shows both theoretically and empirically that whenever the technological frontier is at the top or bottom of the world distribution of a cultural value, there exists an observational equivalence between absolute cultural distances and cultural distances relative to the frontier, preventing the identification of its direct and barrier effects. Since the technological frontier usually has the “right” cultural values for development, it tends to be in the extremes of the distribution of cultural traits, generating observational equivalence and confounding the analysis. These results highlight the difficulty of disentangling the direct and barrier effects of culture. The empirical analysis finds suggestive evidence for direct effects of individualism and conformity with hierarchy, and barrier effects of hedonism.
(with Ian McDonough), Missing Data, Imputation Accuracy, and Endogeneity, Journal of Econometrics (2017). [ and ]
This paper investigates various methods of addressing missing data on an endogenous covariate in a linear regression framework; recommendations for applied researchers are provided.

Bassmann (1957, 1959) introduced two-stage least squares (2SLS). In subsequent work, Basmann et al. (1971) investigated its finite sample performance. Here we build on this tradition focusing on the issue of 2SLS estimation of a structural model when data on the endogenous covariate is missing for some observations. Many such imputation techniques have been proposed in the literature. However, there is little guidance available for choosing among existing techniques, particularly when the covariate being imputed is endogenous. Moreover, because the finite sample bias of 2SLS is not monotonically decreasing in the degree of measurement accuracy, the most accurate imputation method is not necessarily the method that minimizes the bias of 2SLS. Instead, we explore imputation methods designed to increase the first-stage strength of the instrument(s), even if such methods entail lower imputation accuracy. We do so via simulations as well as with an application related to the medium-run effects of birth weight.
(with Tapan Mitra), Optimality of Ramsey-Euler Policy in the Stochastic Growth Model, Journal of Economic Theory (2017). [ and ]

A continuous (or monotonic) consumption function that satisfies the Euler equation is shown to be always optimal in the standard one sector stochastic growth model; there is no need to verify the cumbersome transversality condition separately.

For the canonical one sector stochastic optimal growth model, we outline a new set of conditions for a policy function that satisfies the Ramsey-Euler equation to be optimal. An interior Ramsey-Euler policy function is optimal if, and only if, it is continuous or alternatively, if, and only if, both consumption and investment are non-decreasing in output. In particular, we show that under these conditions, the stochastic paths generated by the policy must satisfy the transversality condition; the implication is that in applying our result, one does not need to verify the transversality condition when checking for optimality of a policy function.
(with Roberto Weber), Maintaining Efficiency While Integrating Entrants From Lower-Performing Environments: An Experimental Study, Economic Journal (2017). []

This study examines the efficacy of different rules on group formation mimicking immigration rules in allowing a highly coordinated group to maintain a high level of cooperation as new entrants join from a less successful group.

Efficiently growing a group often requires integrating individuals from lower performing entities. We explore the effectiveness of policies intended to facilitate such integration, using an experiment that models production as a coordination game. We create an efficient group and an inefficient one. We then allow individuals to move into the efficient group under different mechanisms. We investigate the use of an entry quota, an entry quiz and combinations of the two in order to try to understand if and why the institutions are effective. We find that both restrictions work to maintain efficient coordination but they are effective for different reasons.
Moral Hazard, Skin in the Game Regulation and CRA Performance, International Review of Economics and Finance (2017). []

This paper develops a theoretical model and shows that, requiring the seller to retain a stake on the security issued (skin in the game) also improves the rating accuracy of a Credit Rating Agency involved in the sale.

This paper investigates the implications of the “issuer skin in the game” regulation for the rating accuracy of a credit rating agency (CRA). The analysis shows that, as well mitigating a moral hazard problem on the issuer's side, skin in the game requirements can also improve the rating accuracy of a CRA involved in the sale. The results also link the accuracy of the CRA's ratings to the severity of the issuer's moral hazard problem. A more nuanced skin in the game rule that accounts for the specifics of the underlying security class can be more desirable rather than the proposed ”one size fits all” rule.
(with Debing Ni), Optimal Bundle Pricing under Correlated Valuations, International Journal of Industrial Organization (2017). []

For a multi-product monopolist, the correlation of consumers' component valuations crucially affects the form of the optimal bundle pricing scheme and can be exploited by the monopolist to improve revenue using a random selling mechanism.

We study optimal pricing issues for a monopolist selling two indivisible goods to a continuum of consumers with correlated private valuations over the goods, where the (positive or negative) correlation is modeled using copulas in the Frechet family. We derive explicit optimal pricing schemes and comparative statics results for various environments in our setting. The optimal pricing schemes can take several forms, including pure bundling, partial mixed bundling, and mixed bundling, depending jointly on the degrees of asymmetry and correlation of the consumers valuations. The explicit optimal pricing schemes also enable us to investigate whether and how the monopolists profit can be further improved via random assignments.
(with Mike Fulmer and Ren Zhang), Incorporating the Beige Book into a Quantitative Index of Economic Activity, Journal of Forecasting (2017). []

We show how information in the Beige Book can be used to improve forecasts of economy activity.

We apply customized text analytics to the written description of economic activity contained in the Beige Book (BB) in order to obtain a quantitative measure of current economic conditions. This quantitative BB measure is then incorporated into a dynamic factor index model that also contains other commonly used quantitative economic data. We find that at the time the BB is released it has information about current economic activity not contained in other quantitative data. This informational advantage is relatively short lived. By 3 weeks after their release date, ‘old’ BBs contain little additional information about economic activity not already contained in other quantitative data.
(with Kun Chang and Rong Chen), Prediction-based Adaptive Compositional Model for Seasonal Time Series Analysis, Journal of Forecasting (2017). ]

A new class of seasonal time series models where out-of-sample forecasts show forecasting accuracy at least as good as current state-of-the-art forecasting techniques.

In this paper we propose a new class of seasonal time series models, based on a stable seasonal composition assumption. With the objective of forecasting the sum of the next ℓ observations, the concept of rolling season is adopted and a structure of rolling conditional distributions is formulated. The probabilistic properties, estimation and prediction procedures, and the forecasting performance of the model are studied and demonstrated with simulations and real examples.
(with Shawna Grosskopf, Lori Taylor, and William Weber), Would Weighted-Student Funding Enhance Intra-District Equity in Texas? A Simulation Using DEA, Journal of the Operational Research Society (2017). []

We find that if school districts allocated their resources efficiently, then they would not allocate their resources to campuses according to the Texas School Finance Formula.

We use data envelopment analysis to model the educational production function, and then explore how a shift to weighted student funding using the student weights embedded in the Texas School Finance Formula would alter the allocation of inputs and potential outputs. School outputs are measured as value-added reading and math scores on standard achievement tests. We find that if school districts allocated their resources efficiently, then they would not allocate their resources to campuses according to the funding model weights. Policies that promote greater efficiency would also enhance equity in educational outcomes.
(with Jordan Rappaport), The Settlement of the United States, 1800-2000: The Long Transition to Gibrat’s Law, Journal of Urban Economics (2017). []

This paper analyzes the changing relation between local population growth and initial population in the U.S. between 1800 and 2000.

Gibrat’s law, the orthogonality of growth with initial levels, has long been considered a stylized fact of local population growth. But throughout U.S. history, local population growth has significantly deviated from it. Across small locations, growth was strongly negatively correlated with initial population throughout the nineteenth and early twentieth centuries. This strong convergence gave way to moderate divergence beginning in the mid-twentieth century. Across intermediate and large locations, growth became moderately positively correlated with initial population starting in the late nineteenth century. This divergence eventually dissipated but never completely. A simple-one sector model combining the entry of new locations, a friction from population growth, and a decrease in the congestion arising from the supply of land closely matches these and a number of other evolving empirical relationships.
(with Shlomo Weber), Immigration Policies, Labor Complementarities, and Cultural Frictions: Theory and Evidence, International Journal of Economic Theory (2017). []

This paper provides theoretical explanations and empirical evidence on how population size, labor complementarities between native and non-native workers as well as cultural frictions between immigrants and natives shape a country’s immigration policy.

In this paper we consider a model of international migration due to Fujita and Weber, with two heterogeneous countries, and show that in equilibrium the larger country attracts more immigrants, while choosing a lower quota. Moreover, a higher degree of labor complementarity and lower degree of cultural friction between natives and immigrants yield a higher immigration quota. We test the empirical validity of the model by using time-series country-level data. Even in the absence of direct evidence of strategic and non-cooperative choice of countries’ immigration quotas, both cross-section and panel data approaches indicate that cross-country immigration patterns are consistent with the majority of our theoretical ﬁndings.
(with Ian McDonough), Dynamic Panel Data Models with Irregular Spacing: with Applications to Early Childhood Development, Journal of Applied Econometrics (2017). [ and ]

This paper discusses the problems that arise when estimating dynamic panel data models using longitudinal data where the timing of the survey waves does not align with the data-generating process; solutions are proposed and an application to the determinants of student achievement in primary school is provided.

With the increased availability of longitudinal data, dynamic panel data models have become commonplace. Moreover, the properties of various estimators of such models are well known. However, we show that these estimators break down when the data are irregularly spaced along the time dimension. Unfortunately, this is an increasingly frequent occurrence as many longitudinal surveys are collected at non-uniform intervals and no solution is currently available when time-varying co variates are included in the model. In this paper, we propose two new estimators for dynamic panel data models when data are irregularly spaced and compare their finite-sample performance to the näive application of existing estimators.We illustrate the practical importance of this issue in an application concerning early childhood development.
(with Ignacio Ortuño and Shlomo Weber), Peripheral Diversity: Transfers versus Public Goods, Social Choice and Welfare (2017). []

This paper theoretically hypothesizes and empirically establishes that higher degrees of ethnolinguistic center-periphery tension are associated with less provision of public goods, but more transfers.

This paper advances the hypothesis that in societies that suffer from ethnolinguistic center-periphery tension it is harder to agree on public goods than on transfers. After micro-founding a new peripheral diversity index, it puts forth a simple theory in which the cost of public goods increases with peripheral ethnolinguistic diversity and tax compliance decreases with overall ethnolinguistic diversity. It then empirically explores the relation between public goods provision, transfers, peripheral diversity and overall diversity. Consistent with the theory, we ﬁnd that higher levels of peripheral diversity are associated with less provision of public goods, but more transfers, whereas higher levels of overall diversity have a negative association with transfers. Public goods and transfers are therefore substitutes in their reaction to a change in peripheral diversity.
(with Danila Serra), Corruption, Social Judgment and Culture: An Experiment, Journal of Economic Behavior & Organization (2017). []

Mechanisms involving social observability have been increasingly used in developing countries to work against corruption. We examine their effectiveness and the degree to which their effectiveness is culturally dependent.

Modern societies rely on both formal and social mechanisms to enforce social norms of behavior. Formal enforcement mechanisms rely on monetary or other tangible incentives while social enforcement mechanisms rely on some form of social judgment involving informal sanctions. We experimentally investigate the extent to which social observability and the possibility of social judgment affect individuals’ decisions to engage in corruption at the expense of others. We are also interested in the degree to which culture matters. We use a laboratory experiment with a sample of individuals who live in the U.S. but are also characterized by cultural heterogeneity due to the immigration of their ancestors to the U.S. We find that the possibility of social judgment reduces corruption only among individuals who identify culturally with countries characterized by low levels of corruption. Our findings suggest that the effectiveness of social enforcement mechanisms is at least partly dependent on the sociocultural norms prevailing in the target population.
(with Dávid Krisztián Nagy and Esteban Rossi-Hansberg), Asia’s Geographic Development, Asian Development Review (2017). []

This paper quantitatively explores the importance of transport costs and migration restrictions in the long-run development of Asia.

This paper studies the impact of spatial frictions on Asia’s long-term spatial development. Using the framework provided in Desmet, Nagy, and Rossi-Hansberg (2016), we analyze the evolution of Asia’s economy and the relative performance of speciﬁc regions and countries. We then perform a number of counterfactual experiments and ﬁnd that a worldwide drop in transport costs of 40% increases the present discounted value of real income by 70.7% globally and 78% in Asia.These ﬁgures are much larger than those found in standard quantitative trade models because they include dynamic effects and take into account intercountry transport costs. We also perform exercises in which we upgrade Asia’s road network or relax migratory restrictions between locations in Asia. These exercises emphasize the important role of spatial frictions in the development of Asia’s economy.

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