This paper develops a nonparametric methodology for treatment evaluation with multiple outcome periods under treatment endogeneity and missing outcomes. We use instrumental variables, pre-treatment characteristics, and short-term (or intermediate) outcomes to identify the average treatment...

This paper uses the Italian income tax treatment of 2006/7 as a quasi-natural tax experiment to offer some fresh empirical evidence on how labour supply responds to exogenous income tax hikes. We adopt the identification strategy based on TWFE panel data Difference-in-Differences (DID) model to...

In this paper we provide an extensive comparison between commonly used linear econometric methods in the audit fee literature and explicitly address their underlying assumptions. As opposed to common practice in similar papers we explicitly consider violations of the strict exogeneity assumption...

We consider a linear panel event-study design in which unobserved confounds may be related both to the outcome and to the policy variable of interest. We provide sufficient conditions to identify the causal effect of the policy by exploiting covariates related to the policy only through the...

Measurement error causes a downward bias when estimating a panel data linear regression model. The panel data context offers various opportunities to derive moment conditions that result in consistent GMM estimators. We consider three sources of moment conditions: (i) restrictions on the...

We study transitions in and out of self-employment of older individuals using internationally comparable survey data from 13 OECD countries. We compute self-employment transitions as conditional probabilities arising from a discrete choice panel data model. We examine the influence on...

This paper studies panel data models with interactive fixed effects where the regressors are allowed to be correlated with the idiosyncratic error terms. We propose a two-step profile GMM estimation procedure to estimate the parameters of interest. In the first step we obtain a preliminary...

We present a unifying identification strategy of dynamic average treatment effect parameters for staggered interventions when parallel trends are valid only after controlling for interactive fixed effects. This setting nests the usual parallel trends assumption, but allows treated units to have...

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...