• Journal of the Korean Regional Science Association
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• v.36 no.1
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• pp.51-67
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• 2020

The purpose of this study is to estimate the housing area per capita for verifying if the public Big Data, of the building ledger and resident registration ledger, can be used as well as the National Census and Housing Survey. The Mankiw and Weil (MW) model was constructed by extracting samples of general detached houses and flat houses from the public big data, and compared with the result from traditional survey method. Then, the MW models of 25 municipalities in Seoul was established. As a result, it can be confirmed that it is possible to establish MW models comparable to regular surveys using public big data, and to establish a model for each basic localities which was difficult to use as a regular survey method. Public Big Data has the advantage of expanding the knowledge frontier, but there are some limitations because it uses data generated for other original purposes. Also, the difficult process of accessing personal information is a burden to carry out analysis. It is expected that continuing research should be needed on how public Big Data would be processed to complement or replace traditional statistical surveys.

• The Journal of Economics, Marketing and Management
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• v.12 no.3
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• pp.23-33
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• 2024

This study aims to enhance the accuracy of effective demand analysis for publicly supported private rental housing by integrating the RIR into the traditional Mankiw-Weil (MW) model. Traditional models like the M-W model, which account for household income, housing costs, and household size, often fall short in estimating demand driven by large-scale development projects. By integrating the RIR factor, this study introduces a more accurate and practical approach to analyzing effective housing demand. Findings show that the modified M-W model incorporating RIR predicts effective demand with greater precision than traditional methods. This advancement allows developers to plan projects more efficiently and aids governments and local authorities in implementing more effective housing policies. Furthermore, the study assesses the real housing cost burden on households, elucidating their capacity to pay housing costs based on household size and income quintile. This information enables policymakers to design targeted housing support policies for specific demographic groups. Additionally, the research provides comprehensive policy recommendations tailored to various regions and housing types. Overall, this study lays a vital groundwork for the long-term analysis of the effects of economic changes and housing market trends on effective demand.