Knowledge that Transforms

This paper develops a model of the nursing home industry to investigate the quality effects of policies that either raise regulated reimbursement rates or increase local competition. Using data from Pennsylvania, I estimate the parameters of the model. The findings indicate that nursing homes increase the quality of care, measured by the number of skilled nurses per resident, by 8.7% following a universal 10% increase in Medicaid reimbursement rates. In contrast, I find that pro-competitive policies lead to only small increases in skilled nurse staffing ratios, suggesting that Medicaid increases are more cost effective in raising the quality of care.

We study how health behaviors are shaped through family spillovers. We leverage administrative data to identify the effects of health shocks on family members’ consumption of preventive care and health-related behaviors, constructing counterfactuals for affected households using households that experience the same shock but a few years in the future. Spouses and adult children immediately improve their health behaviors and their responses are both significant and persistent. These spillovers are far-reaching as they cascade even to coworkers. While some responses are consistent with learning information about one’s own health, the evidence points to salience as a major operative explanation. (JEL D15, D83, I12, J12)

We study the informational events that trigger equilibrium shifts in coordination games with incomplete information. Assuming that the distribution of the changes in fundamentals has fat tails, we show that majority play shifts either if fundamentals reach a critical threshold or if there are large common shocks, even before the threshold is reached. The fat-tail assumption matters because it implies that large shocks make players more unsure about whether their payoffs are higher than others. This feature is crucial for large shocks to matter. (JEL C72, C73, D83)

We examine ways to measure the amount of information generated by a piece of news and the amount of uncertainty implicit in a given belief. Say a measure of information is valid if it corresponds to the value of news in some decision problem. Say a measure of uncertainty is valid if it corresponds to expected utility loss from not knowing the state in some decision problem. We axiomatically characterize all valid measures of information and uncertainty. We show that if measures of information and uncertainty arise from the same decision problem, then they are coupled in that the expected reduction in uncertainty always equals the expected amount of information generated. We provide explicit formulas for the measure of information that is coupled with any given measure of uncertainty and vice versa. Finally, we show that valid measures of information are the only payment schemes that never provide incentives to delay information revelation. (JEL D81, D83)

Sticky price models featuring heterogeneous firms and systematic firm-level productivity trends deliver radically different predictions for the optimal inflation rate than their popular homogenous-firm counterparts: (i) the optimal steady-state inflation rate generically differs from zero and (ii) inflation optimally responds to productivity disturbances. We show this by aggregating a heterogeneous-firm model with sticky prices in closed form. Using firm-level data from the US Census Bureau, we estimate the historically optimal inflation path for the US economy: the optimal inflation rate ranges between 1 percent and 3 percent per year and displays a downward trend over the period 1977–2015. (JEL C51, D24, D25, E31, E52)

We provide a revealed preference methodology for identifying beliefs and utilities that can vary across states. A notion of comparative informativeness is introduced that is weaker than the standard Blackwell ranking. We show that beliefs and state-dependent utilities can be identified using stochastic choice from two informational treatments, where one is strictly more informative than another. Moreover, if the signal structure is known, then stochastic choice from a single treatment is enough for identification. These results illustrate novel identification methodologies unique to stochastic choice. Applications include identifying biases in job hiring, loan approvals, and medical advice. (JEL D11, D82, D83, J23, M51)

We study stochastic choice as the outcome of deliberate randomization. We derive a general representation of a stochastic choice function where stochasticity allows the agent to achieve from any set the maximal element according to her underlying preferences over lotteries. We show that in this model stochasticity in choice captures complementarity between elements in the set, and thus necessarily implies violations of Regularity/Monotonicity, one of the most common properties of stochastic choice. This feature separates our approach from other models, e.g., Random Utility. (JEL D80, D81)

This paper studies equilibrium selection in the retail gasoline industry. We exploit a unique dataset that contains the universe of station-level prices for an urban market for 15 years, and that encompasses a coordinated equilibrium transition mid-sample. We uncover a gradual, three-year equilibrium transition, whereby dominant firms use price leadership and price experiments to create focal points that coordinate market prices, soften price competition, and enhance retail margins. Our results inform the theory of collusion, with particular relevance to the initiation of collusion and equilibrium selection. We also highlight new insights into merger policy and collusion detection strategies. (JEL G34, L12, L13, L71, L81, Q35)

This paper shows that a macro model with segmented financial markets can generate sizable movements in housing prices in response to changes in credit conditions. We establish theoretically that reductions in mortgage rates always have a positive effect on prices, whereas the relaxation of loan-to-value constraints has ambiguous effects. A quantitative version of the model under perfect foresight accounts for about one-half of the observed price increase in the United States in the 2000s. When we include shocks to expectations about housing finance conditions, the model’s ability to match house values improves significantly. The framework reconciles the observed disconnect between house prices and rents since, in general equilibrium, financial shocks can decrease rents and increase prices. (JEL E44, G21, R31)

We quantitatively identify the factors that drive wealth dynamics in the United States and are consistent with its skewed cross-sectional distribution and with social mobility. We concentrate on three critical factors: (i) skewed earnings, (ii) differential saving rates across wealth levels, and (iii) stochastic idiosyncratic returns to wealth. All of these are fundamental for matching both distribution and mobility. The stochastic process for returns which best fits the cross-sectional distribution of wealth and social mobility in the United States shares several statistical properties with those of the returns to wealth uncovered by Fagereng et al. (2017) from tax records in Norway. (JEL D31, E13, E21, E25)