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...

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...

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...

Estimation of threshold parameters in (generalized) threshold regression models is typically performed by maximizing the corresponding profile likelihood function. Also, certain Bayesian techniques based on non-informative priors are developed and widely used. This article draws attention to...

A study that would otherwise be eligible is commonly excluded from a meta-analysis when the standard error of its treatment-effect estimator, or the estimate of the variance of the outcomes, is not reported and cannot be recovered from the available information. This is wasteful when the...