Knowledge that Transforms

I am requesting withdrawal of

This paper studies how to design experiments when the experimental units are large aggregate entities (e.g., markets), and only one or a small number of units can be treated. We propose a class of non-randomized experimental designs using the synthetic control method, which jointly selects treated units and untreated units to serve as a comparison group. We analyze the properties of estimators under these synthetic control designs and develop new inferential techniques. We show that, in experiments with aggregate units, synthetic control designs can substantially reduce estimation bias relative to randomized experiments.

We study the role of war bonds and inflation in post-WWII federal elections. After WWII, major bouts of inflation in 1946-48 and 1950-51 depressed the real returns of the bonds sold to households during the war. In a difference-in-differences framework, we find that counties with higher war bond purchases shifted their votes towards the Republican Party in postwar elections. To address the endogeneity of war bond purchases, we use an instrumental variables design, and obtain similar results. Bond ownership raised the saliency of inflation, and the severe rise in prices after the war triggered a backlash against the incumbent Democrats.

How do import tariffs affect employment? We develop an empirical strategy to identify the effects of tariffs using a difference-in-differences strategy, comparing antidumping (AD) investigations resulting in AD tariffs to those not resulting in AD tariffs. We find that an AD tariff decreases imports and increases employment in the protected sector. Moreover, employment in downstream firms decreases, while upstream firms are unaffected because the protected sector sources inputs abroad. Using a model to quantify the aggregate effects, we find that the Brazilian AD policy increased employment by 0.06% at a welfare loss of 2.4%.

After remaining flat for decades, labor productivity at U.S. restaurants surged 15% during the COVID pandemic. The surge has persisted. We explore this using mobile phone data tracking visits and spending at 100,000 limited-service restaurants. It cannot be explained by scale economies, market power, or mechanical consequences of COVID demand fluctuations. However, restaurants’ productivity growth is strongly correlated with the share of their customers visiting for 10 minutes or less, which rose considerably during COVID and persisted. This restaurant-level relationship between labor productivity and customer dwell time is large enough to explain most of the aggregate productivity increase.

We use administrative data to measure sibling spillovers on academic performance before and after the introduction of Free Secondary Education (FSE) in Tanzania. Prior to FSE, students whose older siblings narrowly passed the secondary school entrance exam were less likely to go to secondary school themselves; with FSE, the effect became positive. A triple-differences analysis, using geographic variation in FSE exposure, shows that FSE caused the reversal. Mechanism analyses suggest that changes in parental investments were a more likely channel for this reversal than direct sibling interactions. By alleviating financial constraints, FSE allowed households to invest in more children.

No. Elite institutions offer high salaries because they hire the most valued faculty. Moreover, in contrast to the broader labor market, faculty are equally likely to move up and down the prestige ladder, and they increase their salary either way. We speculate that these facts reflect the visible nature of faculty productivity and the sporadic nature of academic job openings.

This paper develops a semiparametric sieve approach to estimate impulse response functions of nonlinear time series models within a broad class of structural autoregressive specifications. A two-step procedure flexibly captures nonlinearities without imposing fixed parametric forms. We establish uniform estimation guarantees and propose an iterative algorithm that makes impulse response computation straightforward. Simulation results show robustness to misspecification with only modest efficiency losses. In an application to U.S. monetary policy, we find larger GDP responses to interest rate hikes than in linear models. We also examine oil supply news shocks of varying magnitudes to assess limitations when analyzing large shocks.

How do trade shocks affect welfare and inequality when human capital is endogenous? Using India’s IT boom and internal migration data, I document that IT employment and engineering enrollment increased with exports, especially in regions with larger college-age populations. I develop a spatial model featuring higher education choice and differential migration costs for college versus work. The IT boom increased welfare by 2.39%, but without educational mobility, gains would be 25% lower and regional inequality 1.5 times larger. Removing endogenous education further reduces gains by over one-third. Education policies like national scholarships could substantially reduce regional inequality from trade shocks.

We propose a restrictiveness measure for economic models based on how well they fit predefined synthetic data. This measure, together with a measure for how well the model fits real data, outlines a Pareto frontier, where models that rule out more regularities, yet capture the regularities that are present in real data, are preferred. To illustrate our approach, we evaluate the restrictiveness of models in two laboratory settings—certainty equivalents and initial play—and one field setting—takeup of microfinance in Indian villages. The restrictiveness measure reveals insights about each, including that some economic models with only a few parameters are very flexible.