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Francisca Antman

��“When Beer is Safer than Water: Beer Availability and Mortality from Waterborne Illnesses” (with James M. Flynn). Journal of Development Economics, 171(2024), 103343. October 2024.
Abstract: We investigate the impact of beer on mortality during the Industrial Revolution. Due to the brewing process, beer represented an improvement over available water sources during this period prior to the widespread understanding of the link between water quality and human health. Using a wide range of identification strategies to derive measures of beer scarcity driven by tax increases, weather events, and soil quality, we show that beer scarcity was associated with higher mortality, especially in the summer months where mortality was more likely to be driven by water-borne illnesses. We also leverage variation in inherent water quality across parishes using two proxies for water quality to show that beer scarcity resulted in greater deaths in areas with worse water quality. Together, the evidence supports the hypothesis that beer had a major impact on human health during this important period in economic development.

Jeronimo Carballo

Yongmin Chen

“Search and Competition under Product Quality Uncertainty,”��Journal of Industrial Economics, Vol 72, Issue 2, p. 633-661, 2024.
Abstract: I review models of consumer search and competition when product quality is uncertain and differs across firms. Although firms are vertically—and possibly also horizontally—differentiated, an appropriate symmetric price equilibrium with optimal consumer search can be neatly characterized. I propose a “random-quality” framework that unifies these models and discuss their insights on the operation of consumer search markets, focusing on (i) online advertising and search through platforms, (ii) the welfare effects of entry in search markets, and (iii) the role of quality observability under search frictions. I��suggest directions for further research on these and related topics.

“Multimarket Firms and Product Liability: Uniform vs. Variable Rules,” (with X. Hua) Journal of Law, Economics, and Organization, forthcoming.
Abstract: When a multimarket firm's product causes harm to consumers, should the firm bear uniform or variable liability across markets? We analyze a two-market model, in which under the variable rule the firm's liability rises above the standard level in market 1 but falls below it in market 2, while under the uniform rule the standard liability is enforced in both markets. Allowing variation in product liability across markets has broad implications for the firm's incentive to invest in product safety, total output, and output allocation across markets, as well as for the optimal choice of the standard liability in the first place. We show that welfare is higher under uniform liability if demand elasticity is weakly higher and demand curvature is weakly lower in market 2 than in market 1, but welfare can be higher under variable liability otherwise.

"Search and Competition in Expert Markets,” (with C. Cao, Y. Ding, and T. Zhang) RAND Journal of Economics, forthcoming.
Abstract: We develop a model in which consumers sequentially search experts for recom- mendations and prices to treat a problem, and experts simultaneously compete in these two dimensions. Consumers have either zero or a positive search cost. In equilibrium, experts may “cheat” by recommending an unnecessary treatment with positive probabilities, prices follow distributions that depend on a consumer’s problem type and the treatment, and consumers search with Bayesian belief updating about their problem types. Remarkably, as search cost decreases, both expert cheating and prices can increase stochastically. However, if search cost is sufficiently small, competition forces all experts to behave honestly.

Murat Iyigun

"Resource Shocks and Conflict, 1400–1900 C," (with Joris Muller and Nancy Qian)��American Economic Review, May 2024.
Abstract:��This paper provides evidence of the long-run effects of a permanent increase in agricultural productivity on conflict. We construct a newly digitized and geo-referenced dataset of battles in Europe, the Near East and North Africa covering the period between 1400 and 1900 CE. For variation in permanent improvements in agricultural productivity, we exploit the introduction of potatoes from the Americas to the Old World after the Columbian Exchange. We find that the introduction of potatoes permanently reduced conflict for roughly two centuries. The results are driven by a reduction in civil conflicts.

Taylor Jaworski

"Economic Geography and Air Pollution Regulation in the United States," (with Alex Hollingsworth, Carl Kitchens, and Ivan Rudik) Journal of Political Economy: Microeconomics, conditionally accepted.
Abstract:��We develop a quantitative economic geography model with endogenous emissions, amenities, trade, and labor reallocation to evaluate the spatial impacts of the leading air quality regulation in the United States: the National Ambient Air Quality Standards (NAAQS). We find that the NAAQS generate over $50 billion in annual welfare gains. The gains are spatially concentrated in a small set of cities targeted by the NAAQS, and the improved amenities attract large numbers of nonmanufacturing workers into these areas. Despite the concentration of the benefits in cities, over $10 billion in benefits spill over into counties indirectly affected by the regulation. We use our model to analyze counterfactual policies and find that making the NAAQS more stringent could have increased welfare by another $13 billion annually, and that using emissions pricing could increase welfare by another $70 billion per year.

Xiaodong Liu

"Endogenous Technology Spillovers in R&D Collaboration Networks,"��(with��Chih-Sheng Hsieh and Michael Kӧnig)��The RAND Journal of Economics,��accepted.
Abstract:��We introduce a stochastic R&D network formation model where firms choose both R&D efforts and collaboration partners. Neighbors in the network benefit from each other’s R&D efforts through local technology spillovers, and there exists a global competition effect reflecting strategic substitutability in R&D efforts. We provide a complete equilibrium characterization of the network formation model and show that the model is consistent with empirically observed R&D networks. Based on the equilibrium characterization, we propose an estimation method that is computationally feasible even for large networks. With the estimated model we then conduct an analysis of R&D collaboration subsidies to demonstrate the policy relevance of this model. We find that a subsidy scheme targeting specific R&D collaborations in the network can be much more effective than a uniform subsidy, with a welfare gain up to five times larger than the cost of the subsidy.

“On Testing for Spatial or Social Network Dependence in Panel Data Allowing for Network Variability,” (with Ingmar R. Prucha) Journal of Econometrics 247, 105925, 2025.
Abstract: The paper introduces robust generalized Moran tests for network-generated cross-sectional dependence in a panel data setting where unit-specific effects can be random or fixed. Network dependence may originate from endogenous variables, exogenous variables, and/or disturbances, and the network dependence is allowed to vary over time. The formulation of the test statistics also aims at accommodating situations where the researcher is unsure about the exact nature of the network. Unit-specific effects are eliminated using the Helmert transformation, which is well known to yield time-orthogonality for linear forms of transformed disturbances. Given the specification of our test statistics, these orthogonality properties also extend to the quadratic forms that underlie our test statistics. This greatly simplifies the expressions for the asymptotic variances of our test statistics and their estimation. Monte Carlo simulations suggest that the generalized Moran tests introduced in this paper have the proper size and can provide substantial improvement in robustness when the researcher faces uncertainty about the specification of the network topology.

Richard Mansfield

"Who Benefits from a Smaller Honors Track," (with Zachary Szlendak) Journal of Human Resources, accepted.
Abstract: Most U.S. high school courses separate classrooms into standard and honors tracks. This paper characterizes the efficiency and distributional impact of changing the share of students enrolling in honors classrooms. Using a sorting model where students choose tracks by course but schools influence the share choosing honors, we show that administrators' optimal choices of honors track size require knowledge of treatment effect functions capturing the impact of alternative honors enrollment shares on different parts of the student predicted performance distribution. Using administrative data from North Carolina public high schools, we estimate these treatment effect functions by predicted performance quintile. Across various specifications, we find that smaller honors tracks (20%-30% of students) yield moderate performance gains for the top quintile (~.05-.07 test score SDs relative to no tracking) that decline monotonically across quintiles toward zero for the bottom quintile. However, expanding the honors share beyond 30-35% generates further (small) achievement increases only for the middle quintile, while reducing top quintile gains and causing substantial bottom quintile losses. Since many courses feature honors shares above 35% or do not track, we predict that enrolling ~25% of students in honors in each high school course would improve all quintiles’ statewide performance.

Adam McCloskey

"Critical Values Robust to P-hacking,"��(with Pascal Michaillat)��Review of Economics and Statistics, forthcoming.
Abstract:��P-hacking is prevalent in reality but absent from classical hypothesis testing theory. As a consequence, significant results are much more common than they are supposed to be when the null hypothesis is in fact true. In this paper, we build a model of hypothesis testing with p-hacking. From the model, we construct critical values such that, if the values are used to determine significance, and if scientists’ p-hacking behavior adjusts to the new significance standards, significant results occur with the desired frequency. Such robust critical values allow for p-hacking so they are larger than classical critical values. To illustrate the amount of correction that p-hacking might require, we calibrate the model using evidence from the medical sciences. In the calibrated model the robust critical value for any test statistic is the classical critical value for the same test statistic with one fifth of the significance level.

"Short and Simple Confidence Intervals when the Directions of Some Effects are Known,"��(with Philipp Ketz)��Review of Economics and Statistics,��forthcoming.
Abstract:�� We introduce adaptive confidence intervals on a parameter of interest in the presence of nuisance parameters, such as coefficients on control variables, with known signs. Our confidence intervals are trivial to compute and can provide significant length reductions relative to standard ones when the nuisance parameters are small. At the same time, they entail minimal length increases at any parameter values. We apply our confidence intervals to the linear regression model, prove their uniform validity and illustrate their length properties in an empirical application to a factorial design field experiment and a Monte Carlo study calibrated to the empirical application.

Sergey Nigai

Alessandro Peri

”Unintended Consequences of Money-Laundering Regulations,” (Fabrizio Colella and Keith E. Maskus) Economic Journal, conditionally accepted, 2025.
Abstract: Tighter money-laundering regulations in offshore financial havens may inadvertently spur incentives to launder money domestically. Our study exploits regulations targeting financially based money laundering in Caribbean jurisdictions to uncover the creation of front companies in the United States. We find that counties exposed via offshore financial links to these jurisdictions experienced an increase in business activities after the tightening of anti-money-laundering regulations. The effect is more pronounced among small firms, in sectors at high risk of money laundering, and in regions with high intensities of drug trafficking. Our work provides the first empirical evidence of the real effects of policy-induced money-laundering leakage.

“Programming FPGAs for Economics: An Introduction to Electrical Engineering Economics,"��(with Cheela, Bhagath, et al.) Quantitative Economics, vol. 16, .no 1, Econometric Society, 2025, pp. 49-87.
Abstract: We show how to use field‐programmable gate arrays (FPGAs) and their associated high‐level synthesis (HLS) compilers to solve heterogeneous agent models with incomplete markets and aggregate uncertainty (Krusell and Smith (1998)). We document that the acceleration delivered by one single FPGA is comparable to that provided by using 69 CPU cores in a conventional cluster. The time to solve 1200 versions of the model drops from 8 hours to 7 minutes, illustrating a great potential for structural estimation. We describe how to achieve multiple acceleration opportunities—pipeline, data‐level parallelism, and data precision—with minimal modification of the C/C++ code written for a traditional sequential processor, which we then deploy on FPGAs easily available at Amazon Web Services. We quantify the speedup and cost of these accelerations. Our paper is the first step toward a new field, electrical engineering economics, focused on designing computational accelerators for economics to tackle challenging quantitative models. Replication code is available on Github.

"Public Investment in a Production Network: Aggregate and Sectoral Implications,"��(with Omar Rachedi and Iacopo Varotto)��The Review of Economics and Statistics, forthcoming.
Abstract:��Aggregate and sectoral effects of public investment crucially depend on the inter- action between the output elasticity to public capital and intermediate inputs. We uncover this fact through the lens of a New Keynesian production network. This setting doubles the socially optimal amount of public capital relative to the one-sector model without intermediate inputs, leading to a substantial am- plification of the public-investment multiplier. We also document novel sectoral implications of public investment. Although public investment is concentrated in far fewer sectors than public consumption, its effects are relatively more evenly distributed across industries. We validate this model implication in the data.

Ernesto Rivera Mora

"Mechanism design with belief-dependent preferences," Journal of Economic Theory��216 (2024): 105782.
Abstract: This paper studies mechanism design when agents have belief-dependent preferences, in that utilities depend on the agents' hierarchical posterior beliefs about types. For instance, agents may be subject to temptation, shame, image concerns, or privacy concerns. In this setting, the textbook revelation principle does not hold, since mechanisms can provide agents with information that affects posterior beliefs. This paper uses a psychological game framework suited for mechanism design, and provides a novel version of the revelation principle for belief-dependent preferences. The new revelation principle makes use of extended direct mechanisms that map each reported type into material outcomes and private suggestions of what posterior beliefs the agents should have. The paper shows that it suffices to use extended direct mechanisms that satisfy three conditions: incentive compatibility, individual rationality, and a new condition called believability. The new revelation principle is used to find revenue-maximizing auctions when bidders have different types of image concerns. Moreover, it provides an alternate tool—distinct from Myerson's communication revelation principle—to study mechanism design with after-games.

Carol Shiue

"Social Mobility in the Long Run: An Analysis of Tongcheng, China, 1300 to 1900,"��Journal of Economic History, forthcoming.
Abstract: This paper studies intergenerational mobility with a population of families in central China over twenty generations. Employing genealogical data on individual lifetime achievements, I first find that while mobility was low initially there was a striking increase in mobility starting in the late 17th century. Through the lens of a Becker-Tomes (1979) model I explain this through a falling human capital earnings elasticity because the return to passing the civil service examinations, China's most important pathway to office and income at the time, declined over time. Second, as predicted by the model times of high human capital earnings elasticity are times of high cross-sectional inequality. Third, parent human capital affects child income for any given nonhuman parental investment and is estimated to have 2/3 of the effect of nonhuman investments on child income. Moreover, educational inequality is even more strongly correlated with social persistence than income inequality. Finally, much of the observed increase in mobility is accounted for by lower differences in average clan income, consistent with the hypothesis that part of the earnings elasticity of human capital is group-specific.

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