This paper estimates the distribution of wealth in Canada from 1990 to 2022 using the income capitalization method. It finds that the top 1% wealth share rose from 16.2% in 1990 to 21.3% in 2008, before falling and stabilizing at 19.3% by 2022. These estimates imply a lower level of wealth inequality than prior Canadian estimates based on Pareto-interpolation methods, largely reflecting differences in how the wealth of the top 0.1% is estimated. The results also reveal two distinct trends. The top 0.1% share is increasing, while strong wealth growth among middle-class households is compressing inequality across the remainder of the distribution, resulting in a lower overall Gini coefficient. Decomposition results show that the modest growth in top wealth shares in recent years reflects a weakening of the forces typically associated with rising wealth inequality, which were more pronounced earlier in the period.

As immigration becomes the primary driver of population growth in many countries, concerns persist regarding its implications for public finances. This paper examines the fiscal impact of immigration at the municipal level in Canada between 2004 and 2022, leveraging high-quality, annual immigration data and a shift-share instrumental variables (IV) approach. We find that immigration increases municipal revenues and expenditures per capita, with more positive net fiscal effects for low-skilled immigrants. These findings stand in contrast to recent evidence from the United States and to the common skill-based narrative that low-skilled immigrants impose disproportionate fiscal pressures on public finances. Overall, the results suggest that the fiscal impacts of immigration at the municipal-level can differ both from those at higher levels of government and across institutional settings, reflecting differences in local institutions and immigration patterns.

Greenbelts are a widespread policy tool used to protect natural spaces from urban sprawl. With rising housing costs in many metropolitan areas, numerous questions have been raised about the impact of greenbelts on housing markets. In this paper, I evaluate the impact that the introduction of the world’s largest contiguous greenbelt, which was formed around Toronto in the early-2000s, had on housing prices across the region. To capture the key dynamics of a greenbelt, I develop an estimable model of the housing market with heterogeneous supply elasticities and a nested logit demand system. Using rich transaction and project-level data on housing prices and developments from 2000-2010, I estimate housing supply and demand curves separately, where I address the endogeneity of housing prices with instrumental variables. Using the estimated model, I find that the Greenbelt led to an average increase in housing costs of 2.9% by 2010. Although non-trivial (C$600 a year in rent), this increase accounts for only 4% of the increase in prices during this period, suggesting that the Greenbelt does not explain much of the deterioration in housing affordability. Skyrocketing housing costs can instead be explained by the fact that strong housing demand within the urban footprint is met with highly inelastic housing supply.