Research methods

Better governance, better access: practising responsible data sharing in the METADAC governance infrastructure

We give a general construction of debiased/locally robust/orthogonal (LR) moment functions for GMM, where the derivative with respect to first step nonparametric estimation is zero and equivalently first step estimation has no effect on the influence function.

The multinomial logit model with random coefficients is widely used in applied research. This paper is concerned with estimating a random coefficients logit model in which the distribution of each coefficient is characterized by finitely many parameters.

This paper characterizes and proposes a method to correct for errors-in-variables biases in the estimation of rank correlation coeffcients (Spearman's ρ and Kendall's τ).

This paper studies the properties of the wild bootstrap-based test proposed in Cameron et al. (2008) in settings with clustered data.

This paper explores the effects of simulated moments on the performance of inference methods based on moment inequalities.

We propose simultaneous mean-variance regression for the linear estimation and approximation of conditional mean functions.

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.

This article reviews recent advances in fixed effect estimation of panel data models for long panels, where the number of time periods is relatively large.

This paper studies the properties of generalised empirical likelihood (GEL) methods for the estimation of and inference on partially identified parameters in models specified by unconditional moment inequality constraints.

This paper provides a method to construct simultaneous condfience 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.

In the regression discontinuity design (RDD), it is common practice to assess the credibility of the design by testing the continuity of the density of the running variable at the cut-off, e.g., McCrary (2008). In this paper we propose a new test for continuity of a density at a point based on the so-called g-order statistics, and study its properties under a novel asymptotic framework.

We set up an econometric model of persuasion and study identification of key parameters under various scenarios of data availability.

Economic data are often generated by stochastic processes that take place in continuous time, though observations may occur only at discrete times.

We derive necessary and sufficient conditions for a finite data set of price and demand observations to be consistent with an additively separable preference.

Since 1995, police forces in England and Wales have obtained the right to raise revenues locally to supplement central government grants in order to fund their activities.

We provide adaptive inference methods for linear functionals of L1-regularized linear approximations to the conditional expectation function.

We extend conformal inference to general settings that allow for time series data.

It is almost self-evident that social interactions can determine economic behavior and outcomes. Yet, information on social ties does not exist in most publicly available and widely used datasets. We present methods to recover information on the entire structure of social networks from observational panel data that contains no information on social ties between individuals.

We develop an approach to valuing non-market goods using nonparametric revealed preference analysis. We show how nonparametric methods can also be used to bound the welfare effects of changes in the provision of a non-market good.