Econometrica最新文献

Does self-governance, a hallmark of democratic societies, foster norms of generalized cooperation? Does this effect persist, and if so, why? I investigate these questions using a natural experiment in Switzerland. In the Middle Ages, the absence of an heir resulted in the extinction of a prominent noble dynasty. As a result, some Swiss municipalities became self-governing, whereas the others remained under feudalism for another 600 years. Evidence from a behavioral experiment, the World Values Survey and the Swiss Household Panel consistently show that individuals from historically self-governing municipalities exhibit stronger norms of cooperation today. Referenda data on voter-turnout allow me to trace these effects on individually costly and socially beneficial actions for over 150 years. Furthermore, norms of cooperation map into prosocial behaviors like charitable giving and environmental protection. Uniquely, Switzerland tracks every family's place of origin in registration data, which I use to demonstrate persistence from cultural transmission in a context of historically low migration.

Supply chain disturbances can lead to substantial increases in production costs. To mitigate these risks, firms may take steps to reduce their reliance on volatile suppliers. We construct a model of endogenous network formation to investigate how these decisions affect the structure of the production network and the level and volatility of macroeconomic aggregates. When uncertainty increases in the model, producers prefer to purchase from more stable suppliers, even though they might sell at higher prices. The resulting reorganization of the network tends to reduce macroeconomic volatility, but at the cost of a decline in aggregate output. The model also predicts that more productive and stable firms have higher Domar weights—a measure of their importance as suppliers—in the equilibrium network. We provide a basic calibration of the model using U.S. data to evaluate the importance of these mechanisms.

Freedman (2008a,b) showed that the linear regression estimator is biased for the analysis of randomized controlled trials under the randomization model. Under Freedman's assumptions, we derive exact closed-form bias corrections for the linear regression estimator. We show that the limiting distribution of the bias corrected estimator is identical to the uncorrected estimator. Taken together with results from Lin (2013), our results show that Freedman's theoretical arguments against the use of regression adjustment can be resolved with minor modifications to practice.

This paper proposes a model for, and investigates the consequences of, strong spatial dependence in economic variables. Our findings echo those of the corresponding “unit root” time series literature: Spatial unit root processes induce spuriously significant regression results, even with clustered standard errors or spatial HAC corrections. We develop large-sample valid unit root and stationarity tests that can detect such strong spatial dependence. Finally, we use simulations to study strategies for valid inference in regressions with persistent spatial data, such as spatial analogues of first-differencing transformations. Regressions from Chetty, Hendren, Kline, and Saez (2014) are used to illustrate the issues and methods.

The government budget constraint ties the market value of government debt to the expected present discounted value of fiscal surpluses. We find evidence that U.S. Treasury investors fail to impose this no-arbitrage restriction in the United States. Both cyclical and long-run dynamics of tax revenues and government spending make the surplus claim risky. In a realistic asset pricing model, this risk in surpluses creates a large gap between the market value of debt and its fundamental value, the PDV of surpluses, suggesting that U.S. Treasuries may be overpriced.