• Title/Summary/Keyword: housing loan

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Does the Real Estate Market affect the Unemployment Rate in Korea? (한국에서 부동산시장은 실업률에 영향을 미치는가?)

  • Myunghoon Han;Heonyong Jung
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.119-124
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    • 2023
  • This study analyzed the impact of the real estate changes on the unemployment rate in Korea. Using monthly data from January 2013 to February 2023, the study employed a multiple regression analysis model. The key findings are as follows: First, there was a significant causal relationship between the real estate changes and the unemployment rate. Specifically, an increase in the real estate market led to a significant decrease in the unemployment rate, while a decrease in the real estate market resulted in a significant increase in the unemployment rate. Second, an increase in the loan interest rate was found to significantly reduce the unemployment rate, while a rise in interest rates had positive effects on the employment. Furthermore, an increase in inflation was associated with a significant rise in the unemployment rate. Moreover, an increase in the number of permits issued for housing construction significantly reduced the unemployment rate. Lastly, conducting robustness tests by substituting variables did not significantly alter the analysis results, indicating the robustness of the impact of the real estate changes on the unemployment rate. Based on the above analysis, it can be inferred that the fluctuations in real estate prices in South Korea are linked to fluctuations in the unemployment rate, and stable management of the real estate market may contribute to the stability of the unemployment rate.

Determinants of Efficiency of Specialty Construction Companies Using DEA and Tobit Regression Models (DEA와 토빗회귀 모형을 이용한 전문건설기업 효율성 결정요인 분석)

  • Jung, Dae-Woon;Son, Young-Hoon;Kim, Kyung-Rai
    • Korean Journal of Construction Engineering and Management
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    • v.25 no.2
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    • pp.45-55
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    • 2024
  • This study analyzed the efficiency determinants of specialty construction companies by industry using the DEA model and the Tobit model. The analysis targets are 394 specialty construction companies as of 2022. As a result of analysis of efficiency determinants using 12 company characteristics as independent variables, the biggest problem for specialty construction companies was overall efficiency reduction due to rising labor costs. In addition, in a situation where construction companies' loan regulations are severe, the debt ratio was found to have a positive effect on efficiency. Company size had a different impact by industry, and the number of businesses held, credit score, and total capital turnover had an effect only on some industries. This study presents results that are an advance on existing research in that it strategically analyzes factors for improving the efficiency of specialty construction companies. However, it has limitations such as limiting the analysis to only specialty construction companies subject to external audit, insufficient number of companies subject to analysis by industry, and analyzing relative efficiency in the same category for each industry.