Methods

This paper reviews econometric methods for dynamic panel data models, and presents examples that illustrate the use of these procedures.

ExpEnd is a Gauss programme for non-linear generalised method of moments (GMM) estimation of exponential models with endogenous regressors for cross section and panel data.

This paper describes an estimator of the additive components of a nonparametric additive model with a known link function.

We consider the identification of the average treatment effect in models with continuous endogenous variables whose impact is heterogeneous.

This paper discusses some issues related to specification estimation of nonlinear models using panel data.

The paper discusses the properties of a rule for adjusting scores in limited overs cricket matches to preserve probabilities of victory across interruptions by rain.

I study a simple, widely applicable approach to handling the initial conditions problem in dynamic, nonlinear unobserved effects models.

The impact of response measurement error in duration data is investigated using small parameter asymptotic approximations and compared with the effect of hazard function heterogeneity.

The goal of this paper is to use a semiparametric reduced form model to estimate the effects of various tuition subsidies.

In this paper we examine the panel data estimation of dynamic models for count data that include correlated fixed effects and predetermined variables.

This paper presents a revealed preference method for calculating a lower bound on the virtual or reservation price of a new good and suggests a way to improve these bounds by using budget expansion paths.

We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using Generalised Method of Moments (GMM).

This paper considers a panel duration model that has a proportional hazards specification with fixed effects.

This paper reviews econometric methods for dynamic panel data models, and presents examples that illustrate the use of these procedures.

Much empirical research in economics and other fields is concerned with estimating the mean of a random variable conditional on one or more explanatory variables (conditional mean function).

Conditions are derived under which there is local nonparametric identification of values of structural functions and of their derivatives in potentially nonlinear nonseparable models.

In this paper we consider conditions under which the estimation of a log-linearized Euler equation for consumption yields consistent estimates of preference parameters.