Application of Copulas to Improve the Modeling of Housing Tenure and Affordability

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 s...

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Main Authors: Emmanuel Kabundu, Brink Botha, Sijekula Mbanga, Gerrit Crafford
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-03-01
Series:Frontiers in Applied Mathematics and Statistics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fams.2022.805524/full
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author Emmanuel Kabundu
Brink Botha
Sijekula Mbanga
Gerrit Crafford
author_facet Emmanuel Kabundu
Brink Botha
Sijekula Mbanga
Gerrit Crafford
author_sort Emmanuel Kabundu
collection DOAJ
description 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.
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spelling doaj.art-d5e233f1afbb4c50a5bb906aeb6f4fe52022-12-22T00:04:44ZengFrontiers Media S.A.Frontiers in Applied Mathematics and Statistics2297-46872022-03-01810.3389/fams.2022.805524805524Application of Copulas to Improve the Modeling of Housing Tenure and AffordabilityEmmanuel Kabundu0Brink Botha1Sijekula Mbanga2Gerrit Crafford3Department of Building and Human Settlements Development, Nelson Mandela University, Port Elizabeth, South AfricaDepartment of Construction Management, Nelson Mandela University, Port Elizabeth, South AfricaDepartment of Building and Human Settlements Development, Nelson Mandela University, Port Elizabeth, South AfricaDepartment of Quantity Surveying, Nelson Mandela University, Port Elizabeth, South AfricaThe 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.https://www.frontiersin.org/articles/10.3389/fams.2022.805524/fullhousing affordabilityendogeneityhousing tenure-of-choicemulticollinearityassociation parameter
spellingShingle Emmanuel Kabundu
Brink Botha
Sijekula Mbanga
Gerrit Crafford
Application of Copulas to Improve the Modeling of Housing Tenure and Affordability
Frontiers in Applied Mathematics and Statistics
housing affordability
endogeneity
housing tenure-of-choice
multicollinearity
association parameter
title Application of Copulas to Improve the Modeling of Housing Tenure and Affordability
title_full Application of Copulas to Improve the Modeling of Housing Tenure and Affordability
title_fullStr Application of Copulas to Improve the Modeling of Housing Tenure and Affordability
title_full_unstemmed Application of Copulas to Improve the Modeling of Housing Tenure and Affordability
title_short Application of Copulas to Improve the Modeling of Housing Tenure and Affordability
title_sort application of copulas to improve the modeling of housing tenure and affordability
topic housing affordability
endogeneity
housing tenure-of-choice
multicollinearity
association parameter
url https://www.frontiersin.org/articles/10.3389/fams.2022.805524/full
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