Impact evaluations of development programmes usually focus on a comparison of participants with a control group. However, if the programme generates externalities for non-participants such an approach will capture only part of the programme’s impact. Based on a unique large-scale quantitative...

A Bayesian Spatial-Propensity Score Matching estimator is proposed to measure the regional impact of micro finance on poverty reduction and women's empowerment. The impact of micro finance in Bolivia was tested with this estimator, using census and household survey data. The results suggest that...

In instrumental variable regression, structural parameter estimation relies on knowledge of the correlation between the structural error and the instruments. The current practice is to assume that this correlation is zero. However, this assumption is unlikely to be satisfied in applied work. In...

In this paper we propose a general approach for estimating stochastic frontier models, suitable when using long panel data sets. We measure efficiency as a linear combination of a finite number of unobservable common factors, having coefficients that vary across firms, plus a time-invariant...

The Lee-Carter model is a basic approach to forecasting mortality rates of a single population. Although extensions of the Lee-Carter model to forecasting rates for multiple populations have recently been proposed, the structure of these extended models is hard to justify and the models are...

There are many alternative approaches to selecting mortality models and forecasting mortality. The standard practice is to produce forecasts using a single model such as the Lee-Carter, the Cairns-Blake-Dowd, or the Age- Period-Cohort model, with model selection based on in-sample goodness of...

This paper introduces the concepts of time-specific weak and strong cross section dependence. A double-indexed process is said to be cross sectionally weakly dependent at a given point in time, t, if its weighted average along the cross section dimension (N) converges to its expectation in...

The aim of the paper is to relax distributional assumptions on the error terms, often imposed in parametric sample selection models to estimate causal effects, when plausible exclusion restrictions are not available. Within the principal stratification framework, we approximate the true...

This collection of papers analyzes the versatility and predictive power of survey expectations data in asset pricing and macroeconomic forecasting. The first paper, Using Sentiment Surveys to Predict GDP Growth and Stock Returns sheds new light on the question of whether or not sentiment...

This paper introduces the concepts of time-specific weak and strong cross section dependence. A double-indexed process is said to be cross sectionally weakly dependent at a given point in time, t, if its weighted average along the cross section dimension (N) converges to its expectation in...