In this paper, we use a unique data set containing detailed information on all full-time teachers at Canadian universities over the period 1970 through 2001. The individual level data are collected by Statistics Canada from all universities in Canada and are used to analyze the evolution of...

We analyze the process of immigrant selection and occupational outcomes of International Medical Graduates (IMGs) in the US and Canada. We extend the IMG relicensing model of Kugler and Sauer (2005) to incorporate two different approaches to immigrant selection: employer nomination systems and...

We examine the impact of mandatory retirement on the retirement decisions of professors in Canada using administrative data. We find that the age distributions of professors at universities without mandatory retirement and those at universities with mandatory retirement at age 65 have diverged...

The cluster robust variance estimator (CRVE) relies on the number of clusters being large. The precise meaning of 'large' is ambiguous, but a shorthand 'rule of 42' has emerged in the literature. We show that this rule depends crucially on the assumption of equal-sized clusters. Monte Carlo...

Many empirical projects are well suited to incorporating a linear difference-in-differences research design. While estimation is straightforward, reliable inference can be a challenge. Past research has not only demonstrated that estimated standard errors are biased dramatically downwards in...

Inference using difference-in-differences with clustered data requires care. Previous research has shown that t tests based on a cluster-robust variance estimator (CRVE) severely over-reject when there are few treated clusters, that different variants of the wild cluster bootstrap can...

Inference based on cluster-robust standard errors is known to fail when the number of clusters is small, and the wild cluster bootstrap fails dramatically when the number of treated clusters is very small. We propose a family of new procedures called the sub- cluster wild bootstrap. In the case...

We study a cluster-robust variance estimator (CRVE) for regression models with clustering in two dimensions that was proposed in Cameron, Gelbach, and Miller (2011). We prove that this CRVE is consistent and yields valid inferences under precisely stated assumptions about moments and cluster...

Inference for estimates of treatment effects with clustered data requires great care when treatment is assigned at the group level. This is true for both pure treatment models and difference-in-differences regressions. Even when the number of clusters is quite large, cluster-robust standard...

The research on immigration has found falling labor market outcomes of immigrants in many Western countries. In Canada, one of the major causes has been the decline in the returns to foreign work experience. Using the 1991, 1996 and 2001 Canadian Census Master Datafiles and applying both...