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

The evolution of academic salaries and the gender earnings gap in Canadian universities is analysed using a unique Statistics Canada data set containing detailed information on all full-time teachers at Canadian universities over the period 1970 through 2001. Male salaries declined across...

The earnings and occupational task requirements of immigrants to Canada are analyzed. The growing education levels of immigrants in the 1990s have not led to a large improvement in earnings as one might expect if growing computerization was leading to a rising return to non-routine cognitive...

We examine the impact of mandatory retirement on the retirement decisions of professors in Canada using administrative data. Estimation of a discrete time hazard model indicates that faculty members at universities with mandatory retirement at age 65 have exit rates at age 65 that are around 30...

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...

The cluster robust variance estimator (CRVE) relies on the number of clusters being large. A shorthand "rule of 42'' has emerged, but we show that unbalanced clusters invalidate it. Monte Carlo evidence suggests that rejection frequencies are higher for datasets with 50 clusters proportional to...

Many empirical projects involve estimation with clustered data. While estimation is straightforward, reliable inference can be challenging. Past research has suggested a number of bootstrap procedures when there are few clusters. I demonstrate, using Monte Carlo experiments, that these bootstrap...