Methods

Recall food expenditure data, which is the basis of a great deal of empirical work, is believed to suffer from considerable measurement error.

Understanding the Effect of Measurement Error on Quantile Regressions

Quasi-experimental study designs series – Paper 7: assessing the assumptions

Peer effects in risky choices among adolescents

Economic theory often provides shape restrictions on functions of interest in applications, such as monotonicity, convexity, non-increasing (non-decreasing) returns to scale, or the Slutsky inequality of consumer theory; but economic theory does not provide finite-dimensional parametric models. This motivates nonparametric estimation under shape restrictions. Nonparametric estimates are often very noisy. Shape restrictions stabilize nonparametric estimates without imposing arbitrary restrictions, such as additivity or a single-index structure, that may be inconsistent with economic theory and the data. This paper explains how to estimate and obtain an asymptotic uniform confidence band for a conditional mean function under possibly nonlinear shape restrictions, such as the Slutsky inequality. The results of Monte Carlo experiments illustrate the finite-sample performance of the method, and an empirical example illustrates its use in an application.

This paper provides a framework for identifying preferences in a large network where links are pairwise stable.

Testing for homogeneity in mixture models

Quantile regression 40 years on

Rebayes: an R package for empirical bayes mixture methods

Bayesian deconvolution: an R vinaigrette

This paper studies inference in randomized controlled trials with covariate-adaptive randomization when there are multiple treatments. More specifically, we study in this setting inference about the average effect of one or more treatments relative to other treatments or a control. As in Bugni et al. (2017), covariate-adaptive randomization refers to randomization schemes that first stratify according to baseline covariates and then assign treatment status so as to achieve "balance" within each stratum. In contrast to Bugni et al. (2017), however, we allow for the proportion of units being assigned to each of the treatments to vary across strata.

The exponential GARCH (EGARCH) model introduced by Nelson (1991) is a popular model for discrete time volatility since it allows for asymmetric effects and naturally ensures positivity even when including exogenous variables.

Following the work of Gini, Dagum and Tukey, this paper extends Gini’s Transvariation measure for comparing two distributions to the simultaneous comparison of many distributions.

Oracle Estimation of a Change Point in High Dimensional Quantile Regression

Consideration set models relax the assumption that consumers are aware of all available options.

This article studies the non-parametric identification and estimation of voters’ preferences when voters are ideological. We establish that voter preference distributions and other parameters of interest can be identified from aggregate electoral data.

Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze identifcation of binary and multinomial choice models when the choice utilities are nonseparable in observed attributes and multidimen- sional unobserved heterogeneity with cross-section and panel data.

I study a game theoretic spatial model of elections with many heterogeneous constituencies in which both party and candidate behavior are modeled. Parties choose a platform and a ‘whip rate,’ representing the proportion of final policy that will be made by the party, as opposed to by the successful candidates. Candidates are office-motivated and can choose both a platform and a level of advertising in order to defeat their opponent. It is shown that the introduction of whipping as a choice variable can cause party platforms to diverge and that parties will whip on some but not all issues, reflecting the empirical reality of parties influencing rather than determining policy outcomes exclusively.

We study social learning in a continuous action space experiment.