We use a novel retail panel with detailed transaction records to study the effect of the Supplemental Nutrition Assistance Program (SNAP) on household spending. We use administrative data to motivate three approaches to causal inference. The marginal propensity to consume SNAP-eligible food (MPCF) out of SNAP benefits is 0.5 to 0.6. The MPCF out of cash is much smaller. These patterns obtain even for households for whom SNAP benefits are economically equivalent to cash because their benefits are below their food spending. Using a semiparametric framework, we reject the hypothesis that households respect the fungibility of money. A model with mental accounting can match the facts.

We consider a linear panel event-study design in which unobserved confounds may be related both to the outcome and to the policy variable of interest. We provide sufficient conditions to identify the causal effect of the policy by exploiting covariates related to the policy only through the confounds. Our model implies a set of moment equations that are linear in parameters. The effect of the policy can be estimated by 2SLS, and causal inference is valid even when endogeneity leads to pre-event trends (“pre-trends”) in the outcome. Alternative approaches perform poorly in our simulations.

We study the competitive forces which shaped ideological diversity in the US press in the early twentieth century. We find that households preferred like-minded news and that newspapers used their political orientation to differentiate from competitors. We formulate a model of newspaper demand, entry, and political affiliation choice in which newspapers compete for both readers and advertisers. We use a combination of estimation and calibration to identify the model's parameters from novel data on newspaper circulation, costs, and revenues. The estimated model implies that competition enhances ideological diversity, that the market undersupplies diversity, and that optimal competition policy requires accounting for the two-sidedness of the news market.