Philip Haile Publications

We study voting in general elections for the U.S. House of Representatives. Our data set includes demographics and turnout of all registered voters for the years 2016–2020, as well as vote shares at the precinct and contest level. We estimate a Downsian voting model incorporating rich observed and unobserved heterogeneity at the voter and contest level. We find that voters with high perceived voting costs tend to favor Democrats, as do marginal voters in most districts. Variation in state voting policies accounts for a modest share of overall estimated voting costs but is sufficient to determine the majority party in some years. We also find that many states’ district maps favor one party in converting votes to seats. On net these biases favor Republicans. For example, we estimate that winning 50% of votes in every state would give Republicans a 9 percentage point seat advantage in the House.

We examine identification of differentiated products demand when one has “micro data” linking the characteristics and choices of individual consumers. Our model nests standard specifications featuring rich observed and unobserved consumer heterogeneity as well as product/market-level unobservables that introduce the problem of econometric endogeneity. Previous work establishes identification of such models using market-level data and instruments for all prices and quantities. Micro data provides a panel structure that facilitates richer demand specifications and reduces requirements on both the number and types of instrumental variables. We address identification of demand in the standard case in which nonprice product characteristics are assumed exogenous, but also cover identification of demand elasticities and other key features when these product characteristics are endogenous and not instrumented. We discuss implications of these results for applied work.

We examine identification of differentiated products demand when one has “micro data” linking the characteristics and choices of individual consumers. Our model nests standard specifications featuring rich observed and unobserved consumer heterogeneity as well as product/market-level unobservables that introduce the problem of econometric endogeneity. Previous work establishes identification of such models using market-level data and instruments for all prices and quantities. Micro data provides a panel structure that facilitates richer demand specifications and reduces requirements on both the number and types of instrumental variables. We address identification of demand in the standard case in which non-price product characteristics are assumed exogenous, but also cover identification of demand elasticities and other key features when these product characteristics are endogenous and not instrumented. We discuss implications of these results for applied work.

Demand elasticities and other features of demand are critical determinants of the answers to most positive and normative questions about market power or the functioning of markets in practice. As a result, reliable demand estimation is an essential input to many types of research in Industrial Organization and other fields of economics. This chapter presents a discussion of some foundational issues in demand estimation. We focus on the distinctive challenges of demand estimation and strategies one can use to overcome them. We cover core models, alternative data settings, common estimation approaches, the role and choice of instruments, and nonparametric identification.