This paper asks whether adversity spurs the introduction of process innovations and increases the use of managerial incentives by firms. Using a large panel data set of workplaces in Canada, our identification strategy relies on exogenous variation in adversity arising from increased border...

Using a large longitudinal, nationally representative workplace-level dataset, we explore the productivity gains associated with computer use and organizational redesign. The empirical strategy involves the estimation of a production function, augmented to account for technology use and...

In this paper, we use linked employer-employee administrative tax data from Canada to estimate the impact of payroll taxes on a variety of firms and workers outcomes. At the firm level, we use geographic and time variations in tax rates to identify the effect of payroll taxes on wage growth at...

In this paper, we estimate returns to classroom and on-the-job firm-sponsored training in terms of value-added per worker using longitudinal linked employee-employer Canadian data from 1999 to 2006. We estimate a standard production function controlling for endogenous training decisions because...

We use longitudinal data from the income tax system to study the impacts of firms' employment and wage-setting policies on the level and change in immigrant-native wage differences in Canada. We focus on immigrants who arrived in the early 2000s, distinguishing between those with and without a...

Recent research has tried to quantify how firms contribute to the immigrant–native earnings gap. Findings from several countries show that around 20% of the gap is due to firm policies that lead to a systematic underrepresentation of immigrants at higher-paying firms. Results also show that...

Data on businesses collected by statistical agencies are challenging to protect. Many businesses have unique characteristics, and distributions of employment, sales, and profits are highly skewed. Attackers wishing to conduct identification attacks often have access to much more information than...