Research Database

We develop a quantitative equilibrium model of financial crises to assess the interaction between ex-post interventions in credit markets and the buildup of risk ex ante. During a systemic crisis, bailouts relax balance sheet constraints and mitigate the severity of the recession. Ex ante, the anticipation of such bailouts leads to an increase in risk-taking, making the economy more vulnerable to a financial crisis. We find that moral hazard effects are limited if bailouts are systemic and broad-based. If bailouts are idiosyncratic and targeted, however, this makes the economy significantly more exposed to financial crises.

We study the optimal accumulation of international reserves in a quantitative model of sovereign default with long-term debt and a risk-free asset. Keeping higher levels of reserves provides a hedge against rollover risk, but this is costly because using reserves to pay down debt allows the government to reduce sovereign spreads. Our model, parameterized to mimic salient features of a typical emerging economy, can account for a significant fraction of the holdings of international reserves, and the larger accumulation of both debt and reserves in periods of low spreads and high income. We also show that income windfalls, improved policy frameworks, larger contingent liabilities, and an increase in the importance of rollover risk imply increases in the optimal holdings of reserves that are consistent with the upward trend in reserves in emerging economies. It is essential for our results that debt maturity exceeds one period.

This article is largely a description of the earnings, income, and wealth distributions in the United States in 2013 as measured by the Survey of Consumer Finances (SCF). We describe facts that lie at the joint distribution of the three variables. We look at inequality in relation to age, education, employer status, and marital status. We discuss the evolution of our results over the past 25 years (1989 - 2013), emphasizing the role played by the Great Recession. We pay special attention to the degree of income and wealth concentration at the top and discuss what the use of the SCF data can contribute to the ongoing debate on this topic. Finally, we look at which income sources and asset classes contribute most to income and wealth concentration.

Randomness in individual discovery tends to spread out productivities in a population, while learning from others keeps productivities together. In combination, these two mechanisms for knowledge accumulation give rise to long-term growth and persistent income inequality. This paper considers a world in which those with more useful knowledge can teach those with less useful knowledge, with competitive markets assigning students to teachers. In equilibrium, students who are able to learn quickly are assigned to teachers with the most productive knowledge. The long-run growth rate of this economy is governed by the rate at which the fastest learners can learn. The income distribution reflects learning ability and serendipity, both in individual discovery and in the assignment of students to teachers. Because of naturally arising indeterminacies in this assignment, payoff irrelevant characteristics can be predictors of individual income growth. Ability rents can be large when fast learners are scarce, when the process of individual discovery is not too noisy, and when overhead labor costs are low.

We use scanner data to estimate inflation rates at the household level. Households' inflation rates are remarkably heterogeneous, with an interquartile range of 6.2 to 9.0 percentage points on an annual basis. Most of the heterogeneity comes not from variation in broadly defined consumption bundles but from variation in prices paid for the same types of goods - a source of variation that previous research has not measured. The entire distribution of household inflation rates shifts in parallel with aggregate inflation. Deviations from aggregate inflation exhibit only slightly negative serial correlation within each household over time, implying that the difference between a household's price level and the aggregate price level is persistent. Together, the large cross-sectional dispersion and low serial correlation of household-level inflation rates mean that almost all of the variability in a household's inflation rate over time comes from variability in household-level prices relative to average prices for the same goods, not from variability in the aggregate inflation rate. We provide a characterization of the stochastic process for household inflation that can be used to calibrate models of household decisions.

This appendix contains additional results on using scanner data to estimate inflation rates at the household level. There are three sections. Section 1 shows cross-sectional distributions of Fisher and Paasche inflation rates. Section 2 shows the evolution over time of measures of dispersion of Fisher and Paasche inflation rates. Section 3 shows cross-sectional distributions of two-year inflation rates measured with Fisher and Paasche indexes.