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      Cointegrations in house price dynamics and ageing population risks

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          Abstract

          How does the riskiness of an ageing population change with house price dynamics of rural areas? Why do rural house prices increase faster than cities despite their ageing populations? Life cycle theory predicts working age households have higher demand for housing than retirement households. An issue that has seen much less attention in the literature is that rural house prices have been increasing despite their populations age rapidly. To answer these issues, our paper introduces an empirical cointegration-based framework designed to be flexible for empirical settings. Our cointegration framework reveals crucial information about rural housing and ageing which has not been found previously: the short-term deviation of house prices from cointegration restrictions is a strong predictor of future rural house prices and migration rate from 1 to 4 year ahead. This is not the case for urban areas nor where cointegration restrictions are being ignored. Rural house prices, not urban ones, are the key to understand this cointegration restriction. Our framework is pertinent to most ageing societies with available housing and demographic data. When a government formulates macroprudential policies internalizing these cointegration restrictions and supporting rural developments, migration into rural areas and population increases are possible. Our evidence highlights the importance of cointegration-based long-run ageing risks for rural housing markets.

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          Most cited references56

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          Co-Integration and Error Correction: Representation, Estimation, and Testing

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            Statistical analysis of cointegration vectors

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              Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                12 February 2024
                2024
                : 19
                : 2
                : e0296991
                Affiliations
                [001] Waseda Business School, Faculty of Commerce, Waseda University, Tokyo, Japan
                Royal Melbourne Institute of Technology, AUSTRALIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-7853-4393
                Article
                PONE-D-23-18539
                10.1371/journal.pone.0296991
                10861090
                38346072
                89ca4b50-ef19-4615-a68f-bf00197e4728
                © 2024 William M. Cheung

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 June 2023
                : 24 December 2023
                Page count
                Figures: 3, Tables: 6, Pages: 20
                Funding
                Funded by: Waseda University Grants for Special Research Projects
                Award ID: Research proposal No: 2023C-645
                Award Recipient :
                This paper is a part of the outcomes of research funded by Waseda University Grants for Special Research Projects (Research proposal No: 2023C-645). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Earth Sciences
                Geography
                Human Geography
                Housing
                Social Sciences
                Human Geography
                Housing
                Earth Sciences
                Geography
                Geographic Areas
                Rural Areas
                Earth Sciences
                Geography
                Human Geography
                Urban Geography
                Urban Areas
                Social Sciences
                Human Geography
                Urban Geography
                Urban Areas
                Earth Sciences
                Geography
                Geographic Areas
                Urban Areas
                Biology and Life Sciences
                Developmental Biology
                Organism Development
                Aging
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Aging
                People and Places
                Geographical Locations
                Asia
                Taiwan
                Earth Sciences
                Geography
                Human Geography
                Urban Geography
                Cities
                Social Sciences
                Human Geography
                Urban Geography
                Cities
                People and Places
                Population Groupings
                Age Groups
                Adults
                Young Adults
                Social Sciences
                Economics
                Macroeconomics
                Custom metadata
                The monthly and annual house price indices are included in the “ Supporting Information files”. Raw data sets of property transaction are available from the Department of Land Administration and can be accessed at https://plvr.land.moi.gov.tw/DownloadOpenData. The population age distributions and demographic data sets are available from the Statistical Bureau and can be accessed at https://eng.stat.gov.tw/. One needs to fill out a form and pay for data sets at https://www.stat.gov.tw/News.aspx?n=3090&sms=11159. The monthly and annual house price indices are included in the “Supporting Information files”.

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