Research methods

This paper studies inference of preference parameters in semiparametric discrete choice models when these parameters are not point-identified and the identified set is characterized by a class of conditional moment inequalities.

We provide a new full-commitment intertemporal collective household model to estimate resource shares, defined as the fraction of household expenditure enjoyed by household members.

This paper provides a method to construct simultaneous confidence bands for quantile functions and quantile effects in nonlinear network and panel models with unobserved two-way effects, strictly exogenous covariates, and possibly discrete outcome variables.

This paper demonstrates the use of bounds analysis for empirical models of market structure that allow for multiple equilibria.

In this paper we discuss the value of international comparative empirical studies within the broad field of the economics of ageing. We argue the value is particularly great when such comparative research is based on long life-history data on participants, collected using large-scale autobiographical life-history methods.

This paper examines the identifying power of instrument exogeneity in the treatment effect model.

We develop an analytically tractable method to estimate the fraction of unreported infections in epidemics with a known epicenter and estimate the number of unreported COVID-19 infections in the U.S. during the first half of March 2020.

We provide a finite sample inference method for the structural parameters of a semiparametric binary response model under a conditional median restriction originally studied by Manski (1975, 1985).

We propose a new nonparametric test of stochastic monotonicity which adapts to the unknown smoothness of the conditional distribution of interest, possesses desirable asymptotic properties, is conceptually easy to implement, and computationally attractive.

Datasets that are terabytes in size are increasingly common, but computer bottlenecks often frustrate a complete analysis of the data.

We investigate identification of causal parameters in case-control and related studies.

This chapter reviews the microeconometrics literature on partial identification, focusing on the developments of the last thirty years.

Across many fields in economics, a common approach to estimation of economic models is to calibrate a sub-set of model parameters and keep them fixed when estimating the remaining parameters.

This paper reconciles the asymptotic disagreement between Bayesian and frequentist inference in set-identified models by adopting a multiple-prior (robust) Bayesian approach.

We develop methods for robust Bayesian inference in structural vector autoregressions (SVARs) where the parameters of interest are set-identified using external instruments, or ‘proxy SVARs’.

We examine changes in inequality in socio-emotional skills very early in life in two British cohorts born 30 years apart.

It is often desired to rank different populations according to the value of some feature of each population.

Models of simultaneous discrete choice may be incomplete, delivering multiple values of outcomes at certain values of the latent variables and co-variates, and incoherent, delivering no values.

This paper studies identification and inference in transformation models with endogenous censoring.

We provide a general framework for investigating partial identification of structural dynamic discrete choice models and their counterfactuals, along with uniformly valid inference procedures.