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.

Measures of wealth inequality are important indicators, but only exist in a handful of countries. I am the first to estimate the distribution of wealth in Canada on an annual basis from 1990-2018. Using the income capitalization method of Saez & Zucman (2016), I find that while the top 1% wealth share rose from 15.3% in 1990 to 19.7% in 2008, the top 1% share has since fallen to 17.5% in 2018. I compare these results to those in the United States and France and find that Canada has much less wealth inequality compared to the US and is in line with France. Using linear decomposition methods, I show that this gap is driven by greater concentration across every asset class and is not driven by a single asset or a different composition of assets held in each country. I investigate this further using the concept of `synthetic savings' to decompose whether the fluctuations in the top 1% share were driven by changes in asset prices or changes to savings behaviour. I find evidence that changes in savings behaviour by the top 1% were more influential in driving the rise and then stagnation of the top 1% share than capital gains. Indications that the decline in the top 1% share is driven by reduced savings behaviour could have important implications for investment, future economic growth and policy.