Research Database

This paper develops a quantitative framework to study the impact of Unemployment Insurance (UI) expansions to workers earning below eligibility thresholds. A model of how UI affects welfare and labor supply is developed and calibrated with microeconomic data, including consumption. The model predicts that the current ineligible would choose to stay on UI longer than the current eligible and the margins of why this is the case are quantified. The model is applied to the Great Recession by identifying ineligible workers in the data using machine learning and to an actual expansion during COVID-19 using administrative data. The UI duration for newly eligible under the expansion was 1.7 times longer than the previous eligible but is one-third shorter than the model's economic incentives predict. This suggests caution in extrapolating from the COVID-19 data and the model is used to predict impacts of smaller scale expansions during non-pandemic times.

Many central banks whose exchange rate regimes are classified as flexible are reluctant to let the exchange rate fluctuate. This phenomenon is known as “fear of floating”. We present a simple theory in which fear of floating emerges as an optimal policy outcome. The key feature of the model is an occasionally binding borrowing constraint linked to the exchange rate that introduces a feedback loop between aggregate demand and credit conditions. Contrary to the Mundellian paradigm, we show that a depreciation can be contractionary, and letting the exchange rate float can expose the economy to self-fulfilling crises.

We develop a theory of labor markets in a monetary economy with four realistic features: search frictions, worker productivity shocks, wage rigidity, and two-sided lack of commitment. Due to the non-Coasean nature of labor contracts, inefficient job separations occur in the form of endogenous quits and layoffs that are unilaterally initiated whenever a worker’s wage-to-productivity ratio moves outside an inaction region. We derive sufficient statistics for the aggregate labor market response to a monetary shock based on the distribution of workers’ wage-to-productivity ratios. These statistics crucially depend on the incidence of inefficient job separations, which we show how to identify using readily available microdata on wage changes and worker flows between jobs.

We re-examine recent trends in regional income convergence, considering the full distribution of income rather than focusing on the mean. Measuring similarity by comparing each percentile of state distributions to the corresponding percentile of the national distribution, we find that state incomes have become less similar (i.e. they have diverged) within the top 20 percent of the income distribution since 1969. The top percentile alone accounts for more than half of aggregate divergence across states over this period by our measure, and the top five percentiles combine to account for 93 percent. Divergence in top incomes across states appears to be driven largely by changes in top incomes among White people, while top incomes among Black people have experienced relatively little divergence.

Are unregulated capital flows excessive during a stagflation episode? We argue that they likely are, owing to a macroeconomic externality operating through the economy’s supply side. Inflows raise domestic wages through a wealth effect on labor supply and cause unwelcome upward pressure on marginal costs in countries where monetary policy is trying to drive down costs to stabilize inflation. Yet, market forces are likely to generate such inflows. Optimal capital flow management instead requires net outflows, suggesting topsy-turvy capital flows following markup shocks.