This paper develops a rigorous econometric framework to investigate the structure of codependence between random variables and to test whether it changes over time. Our approach is based on the computation - over both a test and a benchmark period - of the conditional probability that a random...

Positive response density estimation from CV interval data affords efficiency gains which must be weighed against the risk of introducing potential bias during questions iteration. This study examines the effect of eliciting a third response on a set of often-used welfare measures derived in a...

Applying a method suggested by Woodruff (1971), we derive the sampling variances of Generalized Entropy and Atkinson inequality indices when estimated from complex survey data. It turns out that this method also greatly simpli?es the calculations for the i.i.d. case when compared to previous...

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that the duration framework in discrete time provides a fertile ground for effect evaluations. We suggest easy-to-use nonparametric survival function...

We consider both a parametric and a semiparametric method to account for classification errors on the dependent variable in an ordered response model. The methods are applied to the analysis of self-reported speaking fluency of male immigrants in Germany. We find that a parametric model which...

This paper reviews the main identification and estimation strategies for microeconomic policy evaluation. Particular emphasis is laid on evaluating policies consisting of multiple programmes, which is of high relevance in practice. For example, active labour market policies may consist of...

Applying a method suggested by Woodruff (1971), we derive the sampling variances of Generalized Entropy and Atkinson inequality indices when estimated from complex survey data. It turns out that this method also greatly simplifies the calculations for the i.i.d. case when compared to previous...

We consider the problem of estimating the conditional quantile of a time series at time t given observations of the same and perhaps other time series available at time t - 1. We discuss sieve estimates which are a nonparametric versions of the Koenker-Bassett regression quantiles and do not...

This paper considers the estimation problem of structural models for which empirical restrictions are characterized by a fixed point constraint, such as structural dynamic discrete choice models or models of dynamic games. We analyze the conditions under which the nested pseudo-likelihood (NPL)...

We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight...