More than two million U.S. households have an eviction case filed against them each year. Policymakers at the federal, state, and local levels are increasingly pursuing policies to reduce the number of evictions, citing harm to tenants and high public expenditures related to homelessness. We study the consequences of eviction for tenants using newly linked administrative data from two major urban areas: Cook County (which includes Chicago) and New York City. We document that prior to housing court, tenants experience declines in earnings and employment and increases in financial distress and hospital visits. These pre-trends pose a challenge for disentangling correlation and causation. To address this problem, we use an instrumental variables approach based on cases randomly assigned to judges of varying leniency. We find that an eviction order increases homelessness and hospital visits and reduces earnings, durable goods consumption, and access to credit in the first two years. Effects on housing and labor market outcomes are driven by impacts for female and Black tenants. In the longer run, eviction increases indebtedness and reduces credit scores.
This paper considers a linear panel model with interactive fixed effects and unobserved individual and time heterogeneities that are captured by some latent group structures and an unknown structural break, respectively. To enhance realism, the model may have different numbers of groups and/or different group memberships before and after the break. With preliminary nuclear norm regularized estimation followed by row- and column-wise linear regressions, we estimate the break point based on the idea of binary segmentation and the latent group structures together with the number of groups before and after the break by sequential testing K-means algorithm simultaneously. It is shown that the break point, the number of groups and the group memberships can each be estimated correctly with probability approaching one. Asymptotic distributions of the estimators of the slope coefficients are established. Monte Carlo simulations demonstrate excellent finite sample performance for the proposed estimation algorithm. An empirical application to real house price data across 377 Metropolitan Statistical Areas in the US from 1975 to 2014 suggests the presence both of structural breaks and of changes in group membership.
We study a dynamic contribution game where investors seek private benefits that are offered in exchange for contributions and a single, publicly-minded donor values project success. We show that donor contributions serve as costly signals that encourage socially-productive contributions by investors who face a coordination problem. Investors and the donor prefer different equilibria but all benefit in expectation from the donor’s ability to dynamically signal his valuation. We explore various contexts in which our model can be applied and delve empirically into the case of Kickstarter. We calibrate our model and quantify the coordination benefits of dynamic signaling in counterfactuals.
We analyze the welfare impact of a monopolist able to segment a multiproduct market and offer differentiated price menus within each segment. We characterize a family of extremal distributions such that all achievable welfare outcomes can be reached by selecting segments from within these distributions. This family of distributions arises as the solution to the consumer maximizing distribution of values for multigood markets. With these results, we analyze the effect of segmentation on consumer surplus and prices in both interior and extremal markets, including conditions under which there exists a segmentation benefiting all consumers. Finally, we present an efficient algorithm for computing segmentations.
We characterize the bidders' surplus maximizing information structure in an optimal auction for a single unit good and related extensions to multi-unit and multi-good problems. The bidders seeks to find a balance between participation (and the avoidance of exclusion) and efficiency. The information structure that maximizes the bidders surplus is given by a generalized Pareto distribution at the center of demand distribution, and displays complete information disclosure at either end of the Pareto distribution.
We analyze sorting in a frictional labor market when workers and jobs have multidimensional characteristics. We say that matching is positive assortative in dimension (j, k) if workers with higher endowment in skill k are matched to a job distribution with higher values of attribute j in the first-order stochastic dominance sense. Crucial for sorting is a single-crossing property of technology. Sorting is positive between worker-job attributes with strong complementarities but negative in other dimensions. Finally, sorting is based on comparative advantage: workers sort into jobs that suit their skill mix rather than their overall skill level.
Which information structures are more effective at eliminating first- and higher-order uncertainty and hence at facilitating efficient play in coordination games? We consider a learning setting where players observe many private signals about the state. First, we characterize multiagent learning efficiency, that is, the rate at which players approximate common knowledge. We find that this coincides with the rate at which first-order uncertainty disappears, as higher-order uncertainty vanishes faster than first-order uncertainty. Second, we show that with enough signal draws, information structures with higher learning efficiency induce higher equilibrium welfare. We highlight information design implications for games in data-rich environments.
Why do the prices of some products change little during business cycles while the prices of others vary wildly and tend to rise during economic booms and fall during recessions? In particular, why do the prices of some products not fall or fall only a little when the demand for them declines dramatically. It is not surprising that in highly competitive industries prices fluctuate with shifts in demand and supply, but what explains the stability of prices in markets where firms have more direct control of prices? These questions are central to an understanding of business cycles, and good answers would also help us predict how prices will behave.
Commitment to the behaviorist approach to utility theory, to the usefulness of mathematics in economic analysis, and to equalization of the marginal utility of income as a principle of just taxation brought Irving Fisher and Ragnar Frisch to attempt to measure the marginal utility of income and led them to collaborate in forming the Econometric Society and sponsoring the establishment of the Cowles Commission, institutions advancing economic theory in connection to mathematics and statistics, and led Frisch to pioneer an axiomatic approach to utility and microeconomic theory.
A number of producers of heterogeneous goods with heterogeneous costs compete in prices. When producers know their own production costs and consumers know their values, consumer surplus and total surplus are aligned: the information structure and equilibrium that maximize consumer surplus also maximize total surplus. We report when alignment extends to the case where either consumers are uncertain about their own values or producers are uncertain about their own costs, and we also give examples showing when it does not. Less information for either producers or consumers may intensify competition in a way that benefits consumers but results in inefficient production.