This paper investigates the effect of grouping students by prior achievement into different classes (or schools) in settings where students are competing for admission to programs offering only a limited number of places. We first develop a model that identifies the conditions under which the...

In this paper we study doubly robust estimators of various average treatment effects under unconfoundedness. We unify and extend much of the recent literature by providing a very general identification result which covers binary and multi-valued treatments; unnormalized and normalized weighting;...

Many studies have used self-reported dyadic data without exploiting the pattern of discordant answers. In this paper we propose a maximum likelihood estimator that deals with mis-reporting in a systematic way. We illustrate the methodology using dyadic data on inter-household transfers (gifts...

Many studies estimate the impact of exposure to some quasi-experimental policy or event using a panel event study design. These models, as a generalized extension of 'difference-in-differences' or two-way fixed effect models, allow for dynamic lags and leads to the event of interest to be...

Many studies have used self-reported dyadic data without exploiting the pattern of discordant answers. In this paper we propose a maximum likelihood estimator that deals with mis-reporting in a systematic way. We illustrate the methodology using dyadic data on inter-household transfers (gifts...

This paper presents a convenient shortcut method for implementing the Heckman estimator of the dynamic random effects probit model using standard software. It then compares the three estimators proposed by Heckman, Orme and Wooldridge based on three alternative approximations, first in an...

In this paper we study doubly robust estimators of various average treatment effects under unconfoundedness. We unify and extend much of the recent literature by providing a very general identification result which covers binary and multi-valued treatments; unnormalized and normalized weighting;...

This paper extends the Baltagi et al. (2018, 2021) static and dynamic ?-contamination papers to dynamic space-time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the...

The paper argues that networked firms are likely to have an advantage in securing external finance in countries with weak legal and judicial institutions since it helps financial institutions to minimize the underlying agency costs of lending. An analysis of recent BEEPS data from fifteen...

We study the impact of and reward to middle management ability using data from 245 stores of a nationwide retailer. The company scores six broad areas of management practice, the most important of which turns out to be "commercial awareness", where able managers raise labour productivity by 17%...