The changing determinants of housing affordability in oil-booming agglomerations: a quantile regression investigation from Canada, 1991–2011

Abstract

Growing evidence suggests that resource-led economic growth generates rising housing prices which make it difficult for low to mid income earners to find adequate, suitable, and affordable housing. This research explores how households' characteristics associated with housing stress evolve in relation to the commodity cycle, and their relative impact along the distribution of accessibility constraints in two resource-driven agglomerations in Canada: St. John's, Newfoundland, and Fort McMurray, Alberta. Using census microdata, we develop quantile regression models for households in the bottom, median, and top quartiles of the housing affordability stress spectrum between 1991 and 2011. We find differentiated effects for households with low, median, and high levels of housing stress. The young, lone females, lone parents, and people working in low-paid services face increasing housing stress, while this relation sharply degrades over time for households in the highest quartiles. These results provide evidence of emerging vulnerabilities, notably among renters, first-time homebuyers, and people outside the labour force.

How on Earth Did Spanish Banking Sell the Housing Stock?

“…There is no consensus among scholars in regard to the selection of percentiles used when conducting QR on housing studies. Among many options (Hodge, 2016;McMillen & Shimizu, 2020), some authors use only the quartiles (Okkola & Brunelle, 2018;Zhang & Yi, 2018) whereas others use the deciles (Liao & Wang, 2012;Zietz et al, 2007). Combining both approaches and using the same criteria of Chen et al (2007), Zahirovich-Herbert and Gibler (2014), and Mora-Garcia et al (2019, the quantile regression was carried out for three quartiles (the 25th, the 50th, and the 75th quantile) as well as for the first decile (the 10th quantile which represent the bottom segment) and the last decile (the 90th quantile which represent the top segment).…”

Detecting temporal anomalies with pseudo age groups: Homeownership in Canada, 1981 to 2016

“…Similar to previous studies on housing tenure in the Canadian context (Balakrishnan & Wu, 1992;Moore & Skaburskis, 2004;Okkola & Brunelle, 2018;Skaburskis, 1996), our analysis draws on the sociodemographic characteristics of primary household maintainers.…”

Mitigating housing glut: an application to the Malaysian housing market

“…In relation to this, affordable housing is broadly defined as housing which is adequate in quality and location, and is not so costly that it prevents its occupants from meeting other basic living needs (UN-HABITAT, 2011). There are numerous studies that have investigated housing affordability (see, for example, Gabriel et al, 2005;Paris, 2007;Hashim, 2010;Borrowman et al, 2017;Okkola and Brunelle, 2018;Lens, 2018;Owusu-Manu et al, 2018;Öztürk et al2018;Yap and Ng, 2018;Olanrewaju and Wong, 2020). However, the existing researches ignore an important aspect triggered by housing price, housing affordability and economic growth and this aspect is housing glut and its significant effect on the housing market.…”

“…Academic research on housing glut is relatively understudied as existing studies focus more on housing affordability (Gabriel et al, 2005;Paris, 2007;Borrowman et al, 2017;Okkola and Brunelle, 2018;Lens, 2018;Owusu-Manu et al, 2018;Öztürk et al, 2018;Yap and Ng, 2018;Olanrewaju and Wong, 2020), and another strand of studies focusing on housing supply (see for example, Mayo and Sheppard, 1996;Malpezzi and Mayo, 1997;Blackley, 1999;Tse et al, 1999;Malpezzi and Maclennan, 2001;Mayo and Sheppard, 2001;Harter-Dreiman, 2004;Ball et al, 2010;Caldera and Johansson, 2013). However, most of these literature on housing glut is conducted in the USA (Mcnulty, 2009) and Germany (Großmann et al, 2015).…”