According to a report published last February by United Way Toronto, Toronto has become Canada’s epicenter of income inequality. Based on studies conducted by Statistics Canada and Research Data Centre Toronto, between 1980 and 2005 income inequality grew by 31 percent. Once Canada’s second highest city in income inequality, Toronto has skyrocketed to first by surpassing Calgary.
Concentrated poverty, lack of quality jobs, and a shortage of educational opportunities have contributed to Toronto’s rapid increase in income inequality. Though the report surveyed inhabitants and their opinions on Toronto’s economic status, the study did not explore the impact income inequality has had on varying facets of different neighbourhoods such as their diversity, crime rates, and concentration of health providers.
To overcome this shortfall, I decided to use Toronto’s Open Data catalogue in order to explore the effects of income inequality on different neighbourhoods. Toronto’s Open Data website has a variety of datasets that the city has collected and shared publicly, which include the annual sum of parking fines and a collection of requests to 311, Toronto’s non-emergency service dispatcher.
One of the website’s most compelling sections is Wellbeing Toronto. By using the site’s interactive map and option sidebar, users can compare populations and the average price of a home between various neighborhoods.
After using Wellbeing Toronto’s data, I found some significant numbers that illustrate the burden of inequality as it touches people’s lives—not just in how much money they earn, but also in their neighbourhoods’ living conditions.
Though the dataset did not include the average income of neighbourhoods across Toronto, the best indicator of salary was seen through average home prices. Though property values may not always reflect the average income of a family, Lawrence Schembri, Deputy Governor of the Bank of Canada, said during a recent conference that the ratio of property price to income has changed dramatically in the last 20 years. In 2015, purchasing real estate is more financially straining than it was in 1995 due to the rate housing prices rose in comparison to the rate of income. Therefore, property prices can be seen as a good indicator of income distribution in Toronto because the ratio of salary to real estate rarely does not allow individuals to own property with a high value.
According to Wellbeing Toronto, the average price for a house in Toronto was $548 000 in 2011. In that same year, a neighbourhood in this price range would experience an average of 351 crime incidents.
Income inequality does not only dictate that residents have different salaries, but, as seen in the graph below, it indicates how living conditions can be different. Numbers collected by the City of Toronto indicated that a neighbourhood with higher than average home prices experienced less crime. This is in stark contrast to areas with below-average home prices, which witnessed far higher levels of crime.
Disparity continues between neighbourhoods above and below the average property price with the distribution of child care spaces. While areas with a greater real estate value have around 144 child care spaces on average, neighbourhoods with property prices below $548 000 only have 116. This clear inequality has an impact on residents of those areas. For instance, mothers that wish to reenter the workforce have a better opportunity to place their children in a child care space only if they live in a more prosperous neighbourhood. This also does not reflect demographic needs because areas below average home prices are more densely populated. Therefore, not only do these parents have less available options, they also have increased competition for spots in child care spaces.
The number of health providers per neighborhood is complex. While it may seem that neighbourhoods with lower than average house prices may have many health facilities, neighbourhoods with higher than average house price have a greater concentration of health Neighbourhoods below the average property price had around 34 health facilities, while areas above the average house price had about 39 health providers per neighbourhood. The repercussions of this are clear, communities with less health providers will have more difficulties accessing health services. Another added dimension to this issue is that the concentration of health facilities also does not reflect demographic needs.
Income inequality is not only a figure that should be used to measure economic prosperity, but it should also be used as an indicator on where to place more resources. Open data of this type can also direct future research that can help policy entrepreneurs in future decisions. Such studies can include linking density of health providers with health outcomes or concentration of child care spaces with employment of single mothers. Open data can provide so many different answers and should become a tool used more often by journalists and decision makers.
Mohamad Yaghi is a Master of Public Policy Graduate, 2017. He is interested in urban, foreign, and security policy and enjoys long-distance swimming. While Mohamad is not at the School of Public Policy and Governance, you can find him buying a bucket of coffee or reporting.