Abstract
The tenure statuses made by households (renter-occupancy or owner-occupancy) are influenced by a multitude of factors, some of which cannot be directly measured. However, economists are still interested in knowing the relative severity and patterns of influence these factors have on housing tenure status. The purpose of this research was to determine the effect of assuming joint dependency between housing tenure and affordability on the model results. The effect of model-mis-specification on severity and relative importance of the explanatory variables was also assessed. Joint bivariate binary regression was applied to multi-year cross-sectional General Household Survey (GHS) data from Statistics South Africa (STATSA). An assumption of a univariate model when modeling both housing affordability and tenure led to model mis-specification, because most of the coefficients between the univariate and bivariate joint models were significantly different. Model mis-specification also led to significant differences in rankings of the levels of influence of the explanatory variables. Bivariate joint modeling with appropriate error-model copulas improved the model results. Older households that were above 49 years were consistently more likely to be owner-occupiers, and the household head age variable for older households was the most influential factor for housing owner-occupancy and affordability.
Highlights
The housing tenure statuses by households are influenced by a multitude of factors, some of which cannot be directly measured [1]
The results showed that the probability of homeownership was increased by 4–6% when modeling is not controlled for endogeneity
The most important finding for this research is that the bivariate joint binary regression modeling in the presence of endogenous treatment due to inter-dependence is more suitable for modeling of housing affordability and housing tenure, when compared to the respective univariate models
Summary
The housing tenure statuses by households (renting or owner-occupancy) are influenced by a multitude of factors, some of which cannot be directly measured [1]. Among the factors that influence housing affordability include housing-tenure, demographic factors, migration, location, race, time, planning and zoning, living conditions, income inequalities, ownership of land, rents, government policy, income, race, education, and household size [13, 14]. Research done using multi-level logistic regression in China used age, marital status, education level of household head, household income, household size, number of workers in the household, building price, nature of job held and locational factors as the variables influencing tenure. Both market mechanisms and institutional factors affected housing tenure in urban areas of China. All factors were significant for all the models except the government employment factor concerning the two-stage least squares model and one of the ordinary least squares models
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