Housing issues and the associated research objectives/ research questions: on housing affordability
Article 1: Eddie C.M. Hui a,*,
Francis K.W. Wong a, K.W. Chung b, K.Y. Lau c. “Housing affordability,
preferences and expectations of elderly with government intervention” Habitat
International 43 (2014) 11e21.
Housing concerns
“As Hong Kong approaches an ageing society,
its housing system needs to be redesigned in order to suit the needs of the
elderly people. The current housing system may not be suitable for them in the
future. Therefore, it is important to study their housing needs. So far, the
Hong Kong government is obligated to put the notion of “ageing
in place” as a leading principle of elderly service. It
means appropriate support should be provided for older people and their
families to allow them to grow old with minimal disruption. Government residential
care services or nursing homes are the last resorts to elderly. Therefore, to
uphold the principle of promoting the well-being of elderly in Hong Kong, it is
a must to have a deep understanding on and to identify what constitutes the housing
needs (preferences) of elderly”;
“This study reviews a variety of housing options to the elderly in both Hong Kong and the overseas and presents findings on elderly people’s housing preferences. Unlike most previous studies which examine factors directly affecting housing preferences, we adopt an indirect approach by investigating factors affecting elderly people’s expectation on their housing, which in turns affect their housing preferences. In particular, we include living time in current housing, which was often overlooked in previous studies (e.g. Phillips, Siu, Yeh, & Cheng, 2004), as a factor in our regression model. We use prospect theory to analyze how these factors influence their expectation on housing. This is the first study to apply prospect theory to investigate elderly housing.”;
Article 2: Yu-Ju Lin a,*,
Chin-Oh Chang a,1, Chien-Liang Chen “Why homebuyers have a high housing
affordability problem: Quantile regression analysis” Habitat International 43
(2014) 41e47.
Housing concerns
“Data published by the Demographia International
Housing Affordability Survey5 (2006) show that the housing PIRs of most
countries in Europe and America are less than 6. However, most of the housing
affordability of Asian countries in 2006 was over 6, even more than 9, showing
that housing affordability is heavier in Asia. Based on this boom in housing
prices, it is reasonable to expect that the housing affordability in Asia might
deteriorate more significantly than that in Europe and the United
States. Consequently, the heavy housing affordability in Asia is increasingly
deteriorating”;
“Considerable research has been conducted in
this field to seek for the best indicators to
measure housing affordability. Quigley and Raphael (2004) observed that housing
affordability involves many aspects, and is difficult
to measure. Linneman and Megbolugbe (1992) suggested that housing affordability
measures should consider income and price distribution simultaneously. Gan and
Hill (2009) accounted for the whole distribution of income and house prices,
and their results show that lower income households may have housing
affordability problems. However, research is limited on the housing
affordability of individual Households”;
“Although the literature on housing
affordability treats only the measuring problem, this study introduces the
concept of the individual household affordability problem. As previous studies
have shown, most housing affordability research uses qualitative research
methods to identify households who might have housing affordability problems.
To understand which household may have housing affordability problems, and what
types of households with high housing PIR still buy a house, we discuss the
household characteristic difference by individual household house PIR (micro PIR).
We used quantile regression to analyze different quantiles of households to
overcome the problem of measuring the median or mean”;
“This study presents a conceptual framework
for linking individual household PIR and housing affordability. The objective
of this study is to understand the individual household housing affordability
problem, and whether households with high housing PIR represent the heavy
housing affordability problem”;
“The recent economic boom in various
resource-driven regions in Canada has highlighted housing market failure to
provide suitable, adequate and affordable shelter for low to mid income earners
(Goldenberg et al.,
2010; Keogh 2015).
Narratives of rising homelessness and families struggling to find affordable
housing have been publicized in the media during a period when Canada has
experienced an unprecedented oil-driven economic growth”;
“Few studies have so far investigated how
resource booms (or bust) specifically change the distributions of affordability
constraints for households in resource-driven agglomerations. This adds to the
fact that most studies on housing affordability remain focused on the housing
stress of entire communities. However, the reality faced by individual
households is complex, and cannot be analysed using only average or median
housing price or income. Recent work on income inequality shows that
disparities are increasingly taking place in the upper and lower tails of the
income distribution, which entails a growing polarization in the housing
affordability distribution”;
“This study fills these knowledge gaps by
analysing the temporal trends taking place during the time of an oil boom,
specifically looking at the changing impacts of household characteristics on
housing stress at various points across the affordability spectrum”;
“In this study, our main research question is
how conditions of housing affordability change among households in relation to
a regional economic boom? We hypothesize that resource booms generate segmented
labour and housing markets which over time favour growing socio-economic
polarizations among households in these communities. If so, what are the characteristics
and types of households most impacted by housing stress over time?”
“This research relies on Statistics Canada’s
confidential microdata from the 1991 and 2006 census as well as the National
Household Survey (NHS) for 2011. The selected study period starts prior to the
most recent oil boom.1 The 2006 census reflects an approximate mid-boom point,
after which the global financial crisis of 2008 brought a sharp decline in oil
prices. By 2010, the market rebounded to almost the levels of 2007 (Federal
Reserve Bank of St. Louis 2016)”;
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