Research methods

n this paper the assumption of i.i.d. income innovations used in previous empirical studies is removed and the focus of the analysis placed on models for the conditional variance of income shocks, that is related to the approporiate measure of risk emphasized by the theory.

The approximate effects of measurement error on a variety of measures of inequality and poverty are derived.

This paper presents a unified model that integrates the theoretical literatue on Schumpeterian endogenous growth, the microeconometric literature on R&D and productivity, and the empirical literature on productivity convergence.

In this paper we examine the properties of a simple criterion-based, likelihood ratio type test of parameter restristions for standard GMM estimators in autoregressive panel data models.

This paper summarizes our recent research on evaluating the distributional consequences of social programs.

This article notes that it is now practical to use the method of enumeration to analyse the performance of estimators and hypothesis tests of fully parametric binary data models.

In a Monte Carlo study of a panel data model it is shown that the corrected variance estimate approximates the final sample variance well, leading to more accurate inference.

Analysts should correct for distributional differences before undertaking local progressivity comparisons between income tax or tax and benefit schedules. A transplant-and-compare procedure is advocated, involving 'importation' of the schedule from one regime into another, or from both into a reference scenario. The residual progression ordering over transplanted schedules then assures a global ordering of original regimes by Lorenz or Suits curves. The algorithm is advocated for use only when transplantation functions are isoelastic, and is illustrated for the Canadian, Israeli and UK tax and benefit systems.

This chapter reviews developments to improve on the poor performance of the standard GMM estimator for highly autoregressive panel series.

This paper presents a review of non-experimental methods for the evaluation of social programmes.

This paper analyses the trade-off between the incentive effects of increased uncertainty and the welfare benefits of risk-sharing in the design of optimal tax schedules.

This paper uses revealed preference restrictions and nonparametric statistical methods to bound true cost-of-living indices.