We present and estimate a model where the choice between entrepreneurship and wage work may be influenced by financial market imperfections. The model allows for limited liability, as in Evans and Jovanovic (1989), moral hazard, as in Aghion and Bolton (1996), and a combination of both constraints. The paper uses structural techniques to estimate the model and identify the source of financial market imperfections using data from rural and semi-urban households in Thailand. Structural, non-parametric and reduced form estimates provide independent evidence that the dominant source of credit market imperfections is moral hazard. We reject the hypothesis that limited liability alone can explain the data.

We evaluate the impact of government-mandated proof of vaccination requirements for access to public venues and non-essential businesses on COVID-19 vaccine uptake. We find that the announcement of a mandate is associated with a rapid and significant surge in new vaccinations (a more than 60% increase in weekly first doses), using the variation in the timing of these measures across Canadian provinces in a difference-in-differences approach. Time-series analysis for each province and for France, Italy and Germany corroborates this finding. Counterfactual simulations using our estimates suggest the following cumulative gains in the vaccination rate among the eligible population (age 12 and over) as of 31 October 2021: up to 5 percentage points (p.p.) (90% confidence interval, 3.9-5.8) for Canadian provinces, adding up to 979,000 (425,000-1,266,000) first doses in total for Canada (5 to 13 weeks after the provincial mandate announcements); 8 p.p. (4.3-11) for France (16 weeks post-announcement); 12 p.p. (5-15) for Italy (14 weeks post-announcement) and 4.7 p.p. (4.1-5.1) for Germany (11 weeks post-announcement).

We thank Hiro Kasahara and Kevin Schnepel for excellent comments and suggestions. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w27891.ack NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We estimate the impact of indoor face mask mandates and other non-pharmaceutical interventions (NPI) on COVID-19 case growth in Canada. Mask mandate introduction was staggered from mid-June to mid-August 2020 in the 34 public health regions in Ontario, Canada’s largest province by population. Using this variation, we find that mask mandates are associated with a 22 percent weekly reduction in new COVID-19 cases, relative to the trend in absence of mandate. Province-level data provide corroborating evidence. We control for mobility behaviour using Google geo-location data and for lagged case totals and case growth as information variables. Our analysis of additional survey data shows that mask mandates led to an increase of about 27 percentage points in self-reported mask wearing in public. Counterfactual policy simulations suggest that adopting a nationwide mask mandate in June could have reduced the total number of diagnosed COVID-19 cases in Canada by over 50,000 over the period July–November 2020. Jointly, our results indicate that mandating mask wearing in indoor public places can be a powerful policy tool to slow the spread of COVID-19.

We formulate and solve a range of dynamic models of constrained credit/insurance that allow for moral hazard and limited commitment. We compare them to full insurance and exogenously incomplete financial regimes (autarky, saving only, borrowing and lending in a single asset). We develop computational methods based on mechanism design, linear programming, and maximum likelihood to estimate, compare, and statistically test these alternative dynamic models with financial/information constraints. Our methods can use both cross‐sectional and panel data and allow for measurement error and unobserved heterogeneity. We estimate the models using data on Thai households running small businesses from two separate samples. We find that in the rural sample, the exogenously incomplete saving only and borrowing regimes provide the best fit using data on consumption, business assets, investment, and income. Family and other networks help consumption smoothing there, as in a moral hazard constrained regime. In contrast, in urban areas, we find mechanism design financial/information regimes that are decidedly less constrained, with the moral hazard model fitting best combined business and consumption data. We perform numerous robustness checks in both the Thai data and in Monte Carlo simulations and compare our maximum likelihood criterion with results from other metrics and data not used in the estimation. A prototypical counterfactual policy evaluation exercise using the estimation results is also featured.