Research methods

This document describes the UK tax and benefit system between April 1990 and April 2010, as implemented in FORTAX.

We study the impact of misreported treatment status on the estimation of causal treatment effects, focusing on applications where no additional information or repeated measurements are available.

We develop an empirical search-matching model with productivity shocks so as to analyze policy interventions in a labour market with heterogeneous agents.

This paper compares partial and general equilibrium eects of alternative education policies on the distribution of education and earnings.

We develop a nonparametric empirical method for deriving welfare rankings for a social planner based on data envelopment, which avoids the need to specify a weighting scheme.

The aim of this report is to explore how the four-year findings from the experimental research relate to the impacts that would have been experienced, on average, by all the people who were eligible for ERA, had they participated in the programme.

We analyze equilibria in hedonic economies and study conditions that lead to identification of structural preference parameters in hedonic economies with both additive and nonadditive marginal utility and marginal product functions.

Social experiments are powerful sources of information about the effectiveness of interventions.

This paper develops a concrete formula for the asymptotic distribution of two-step, possibly non-smooth semiparametric M-estimators under general misspecification.

This paper provides estimators for moments and quantiles of the unknown distribution in this problem.

We estimate the effects of active labour market policies (ALMP) on subsequent employment by nonparametric instrumental variables and matching estimators.

Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, containing non stochastic explanatory variables and innovations suspected to be non-normal.

We consider the identification of a Markov process {W_t, X_t*} for t=1,2,...,T when only {W_t} for t=1, 2,..,T is observed.

This package accompanies a presentation given at the 2010 German Stata Users Group meeting in Berlin.

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

The most common approach to estimating conditional quantile curves is to fit a curve, typically linear, pointwise for each quantile.