We study unrepresentative observational data in survival analysis. The first paper focuses on proportional hazards regressionwhen observed subjects have different selection probabilities. Wedevelop methods which are applicable when the selectionprobabilities are unknown but estimated using...

This paper outlines why program evaluation should follow well-respected scientific standards and why it should be performed by independent researchers.

Using a rich and unique combined administrative-survey dataset, this paper explores how sensitive propensity score (PS) matching estimates of Active Labor Market Policies (ALMPs) based on the selection-on-observables assumption are to typically unobserved covariates. Using a sample of German...

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified....

In observational studies, the non-parametric estimation of a binary treatment effect is often performed by matching each treated individual with a control unit which is similar in observed characteristics (covariates). In practical applications, the reservoir of covariates available may be...

This paper provides a survey of six widely used non-experimental methods for estimating the impact of programmes in the context of developing economies (instrumental variables, regression discontinuity, direct matching, propensity score matching, linear regression and non-parametric methods, and...

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified....

Purpose: The purpose of this article is to better understand the management challenges facing managers in small growing firms. Design/methodology/approach: Empirical data have been collected in Sweden through structured observations (approx. 20,000 min) of the working days of six top managers in...

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified....

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified....