Do natural resources benefit producer economies, or is there a “Natural Resource Curse”, perhaps as the crowd-out of manufacturing productivity spillovers reduces long-term growth? We combine new data on oil and gas endowments with Census of Manufactures microdata to estimate how oil and gas booms affect local economies in the U.S. Local wages rise during oil and gas booms, but manufacturing is not crowded out—in fact, the sector grows overall, driven by upstream and locally-traded subsectors. Tradable manufacturing subsectors do contract during resource booms, but their productivity is unaffected, so there is no evidence of foregone local learning-by-doing effects. Over the full 1969–2014 sample, a county with one standard deviation additional oil and gas endowment averaged about 1% higher real wages. Overall, the results provide evidence against a Natural Resource Curse within the U.S.

It is often argued that people might take on too much high-cost debt because they are present focused and/or over-optimistic about how soon they will repay. We measure borrowers’ present focus and over-optimism using an experiment with a large payday lender. Although the most inexperienced quartile of borrowers under-estimate their likelihood of future borrowing, the more experienced three quartiles predict correctly on average. This finding contrasts sharply with priors we elicited from 103 payday lending and behavioural economics experts, who believed that the average borrower would be highly overoptimistic about getting out of debt. Borrowers are willing to pay a significant premium for an experimental incentive to avoid future borrowing, which we show implies that they perceive themselves to be time inconsistent. We use borrowers’ predicted behaviour and valuation of the experimental incentive to estimate a model of present focus and naivete. We then use the model to study common payday lending regulations. In our model, banning payday loans reduces welfare relative to existing regulation, while limits on repeat borrowing might increase welfare by inducing faster repayment that is more consistent with long-run preferences.

We use natural experiments embedded in state-run lotteries and a new nationally representative survey to provide reduced-form and structural estimates of risk preferences and behavioural biases in lottery demand, and to explore the implications for optimal lottery design. We find that sales respond more to the expected value of the jackpot than to price but are unresponsive to variation in the second prize—a pattern that is consistent with probability weighting but is inconsistent with standard parameterizations. In the survey, we find that lottery spending decreases modestly with income and is strongly associated with measures of innumeracy, poor statistical reasoning, and other proxies for behavioural bias, which also decline with income. Regression predictions suggest that Americans would spend 43% less on lotteries if they were unbiased, while the remaining lottery demand is due to other factors such as anticipatory utility or entertainment value. We use these empirical moments to estimate a model of socially optimal lottery design. In the model, current multi-state lottery designs increase welfare but may harm heavy spenders.