Research methods

An outcome is determined by a structural function in which theeect of variables of interest is transmitted through a scalar function of those vari-ables - an index. Multiple sources of stochastic variation are permitted to appear asarguments of the structural function, but not as arguments of the index. Conditionsare provided under which there is local identi?cation of ratios of partial derivativesof the index.

Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate.

This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model.

We suggest two nonparametric approaches, based on kernel methods and orthogonal series, respectively, to estimating regression functions in the presence of instrumental variables.

This paper studies the estimation of conditional quantiles of counts.

In this paper we examine the importance of heterogeneity and self-selection into schooling for the study of inequality.

This paper is concerned with identification of a competing risks model with unknown transformations of latent failure times.

The principal purpose of this paper is to adapt to the conditional moment context the GEL unconditional moment methods described in Smith(1997, 2001) and Newey and Smith(2004).

This paper shows that a power utility specification of preferences over total expenditure (ie. CRRA preferences) implies that intratemporal demands are in the PIGL/PIGLOG class.

This paper develops a class of first order equivalent semi-parametric efficient estimators and tests for conditional moment restrictions models based on a local or kernel-weighted version of the Cressie-Read power divergence family of discrepancies.

Initially this discussion briefly reviews the contributions of Andrews and Stock and Kitamura.

This paper uses revealed preference inequalities to provide tight nonparametric bounds on consumer responses to price changes.

This paper uses revealed preference inequalities to provide tight nonparametric bounds on consumer responses to price changes.

This paper examines the empirical analysis of treatment effects on duration outcomes from data that contain instrumental variation.

Current labour force counting relies on general guidelines set by the International Labour Office(ILO) to classify individuals into three labour force states: employment, unemployment and in activity. However, the resulting statistics areknown to be sensitive to slight variations of operational definitions prima facie consistent with the general guidelines. In this paper two alternative classification criteria are considered.

We investigate the performance of a class of semiparametric estimators of the treatment effect via asymptotic expansions.

This papers studies and compares the asymptotic bias of GMM and generalized empirical likelihood (GEL) estimators in the presence of estimated nuisance parameters

This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function that depends on a discrete endogenous variable and is nonseparable in latent variates.

This paper presents a new estimator for the mixed proportional hazard model that allows for a nonparametric baseline hazard and time-varying regressors. In particular, this paper allows for discrete measurement of the durations as happens often in practice.

This paper presents results from a Monte Carlo study concerning inference with spatially dependent data. It investigates the impact of location/distance measurement errors upon the accuracy of parametric and nonparametric estimators of asymptotic variances.