Many school and college admission systems use centralized mechanisms to allocate seats based on applicant preferences and school priorities. When tie-breaking uses non-randomly assigned criteria like distance or a test score, applicants with the same preferences and priorities are not directly comparable. The non-lottery setting does generate a kind of local random assignment that opens the door to regression discontinuity designs. This paper introduces a hybrid RD/propensity score empirical strategy that exploits quasi-experiments embedded in serial dictatorship, a mechanism widely used for college and selective K-12 school admissions. We use our approach to estimate achievement effects of Chicago's exam schools.
We study a linear interaction model with asymmetric information. We first characterize the linear Bayes Nash equilibrium for a class of one dimensional signals. It is then shown that this class of one dimensional signals provide a comprehensive description of the first and second moments of the distribution of outcomes for any Bayes Nash equilibrium and any information structure.
We use our results in a variety of applications: (i) we study the connections between incomplete information and strategic interaction, (ii) we explain to what extent payoff environment and information structure of a economy are distinguishable through the equilibrium outcomes of the economy, and (iii) we analyze how equilibrium outcomes can be decomposed to understand the sources of individual and aggregate volatility.
We develop a model of demand where consumers trade-off the utility of consumption against the disutility of expenditure. This model is appropriate whenever a consumer’s demand over a strict subset of all available goods is being analyzed. Data sets consistent with this model are characterized by the absence of revealed preference cycles over prices. The model is readily generalized to the random utility setting, for which we develop nonparametric statistical tests. Our application on national household consumption data provides support for the model.
We consider a principal-agent model to examine the relationship between risk and incentives of firms who invest in cost-reducing R&D and compete in the product market. We show that a change in risk may trigger opposite responses of rivals in the same industry: lower risk may induce some firms to strengthen, while other firms to weaken the incentives provided to their agents. This result holds regardless of the mode of competition in the product market, Cournot or Bertrand, as long as the rivals’ R&D decisions are strategic substitutes. Our model can generate new empirical implications and can provide an explanation for the lack of strong empirical support in the literature for a negative relationship between risk and incentives. It also has policy implications about the effect of risk on the incentives to innovate and welfare.
Several recent theories emphasize the negative effects of an aging population on economic growth, either because of the lower labor force participation and productivity of older workers or because aging will create an excess of savings over desired investment, leading to secular stagnation. We show that there is no such negative relationship in the data. If anything, countries experiencing more rapid aging have grown more in recent decades. We suggest that this counterintuitive finding might reflect the more rapid adoption of automation technologies in countries undergoing more pronounced demographic changes and provide evidence and theoretical underpinnings for this argument.