We study electric vehicle (EV) tax credits in the US Inflation Reduction Act (IRA), the largest climate policy in US history, with three goals. First, we provide the first ex-post microeconomic welfare analysis of this central component of the IRA. Event studies around changes in eligibility for EV tax credits find that short-run economic incidence falls largely on consumers. Additionally, domestic content restrictions on tax credits for purchased vehicles have driven enormous shifts to leasing. Our equilibrium model shows that compared to pre-IRA policy, IRA EV credits generated $1.87 of US benefits per dollar spent in 2023, at taxpayer cost of $32,000 per additional EV sold. Compared to scenarios with no EV credits, however, the IRA EV credits created only $1.02 of benefits per dollar of government spending. Second, we characterize the gains from policies targeting heterogeneity in externalities across vehicles. We find that relative to uniform credits, differentiating credits across EVs according to their heterogeneous externalities would substantially increase policy benefits. Third, we quantify tradeoffs in the IRA EV credits between foreign and domestic welfare and between trade and the environment. We find that the IRA EV credits benefit the environment but undermine trade, since they decrease global carbon emissions but use profit shifting to decrease foreign producer surplus. A controversial IRA loophole that removes domestic content restrictions on tax credits for EV leases has negative domestic benefits.

We quantify and explain the firm responses and worker impacts of foreign demand shocks to domestic production networks. To capture that firms can be indirectly exposed to such shocks by buying from or selling to domestic firms that import or export, we use Belgian data with information on both domestic firm-to-firm sales and foreign trade transactions. Our estimates of firm responses suggest that Belgian firms pass on a large share of a foreign demand shock to their domestic suppliers, face upward-sloping labor supply curves, and have sizable fixed overhead costs in labor. Motivated and guided by these findings, we develop and estimate an equilibrium model that allows us to study how idiosyncratic and aggregate changes in foreign demand propagate through a small open economy and affect firms and workers. Our results suggest that the way the labor market is typically modeled in existing research on foreign demand shocks—with no fixed costs and perfectly elastic labor supply—would grossly understate the decline in real wages due to an increase in foreign tariffs.

In granular settings in which people choose from a large set of potential residence-workplace pairs, observed outcomes in part reflect idiosyncratic choices. Using both Monte Carlo simulations and event studies of neighborhood employment booms, we demonstrate that calibration procedures that equate observed shares and modeled probabilities perform very poorly in these high-dimensional settings. Parsimonious specifications of spatial linkages deliver better counterfactual predictions. To quantify the uncertainty about counterfactual outcomes induced by the idiosyncratic component of individuals' decisions, we introduce a quantitative spatial model with a finite number of individuals. Applying this model to Amazon's proposed second headquarters in New York City reveals that its predicted consequences for most neighborhoods vary substantially across realizations of the individual idiosyncrasies.