This study is originated from an idea that real estate prices can be affected by forms of employment and occupations, those which are the determinants of income. In the relationship between forms of employment and housing market, there seemed to be local and temporal rifle effects of housing price f...
This study is originated from an idea that real estate prices can be affected by forms of employment and occupations, those which are the determinants of income. In the relationship between forms of employment and housing market, there seemed to be local and temporal rifle effects of housing price fluctuations. Moreover, this study is to examine the correlation between local housing prices and employment variables relating to income, and to discover academic significances by combining the issues in the local house market and employment. Ultimately, this study is to suggest housing policies that suit the current market by analyzing structural changes in the housing market and current employment conditions. This study was conducted based on both literature research and empirical analysis. For literature research, researches were made on housing prices, employment variables, income classifications relating to employment, asset structures and conditions in employment characteristics, and an analysis on previous studies, journals and media references were made to establish the ground of the research background. For scopes and ranges of the research, the time scope was from January 2006 to July 2015 (total 115 months), and the spatial range was limited to the cosmopolitan area including Seoul, Incheon and Gyeonggi-do province. The number of cosmopolitan housing in Seoul, Incheon and Gyeonggi is 8.89million, which takes up 45.7% of the total, and the housing market in the region has a significance as an analytic data since it has the greatest impact on housing demand and prices in Korea. For housing price variables, the housing sales price index and the housing lease price index issued every month by Korea Appraisal Board was used. For employment variables, the number of the employed per occupation and the number of employed per status of workers determined by Ministry of Employment and Labor were used. The number of the employed per occupation is based on the categories of senior managers, professionals, technical specialists, office workers, service workers, sales workers, technical/equipment/machinery workers and technical laborers counted by the Ministry of Employment and Labor among the 10 Korean Standard Classification of Occupation. The number of the employed per status of workers is based of the numbers of non-wage workers (self-employed and unpaid family workers) and wage workers (regular employees, temporary workers and daily workers) counted by the Ministry of Employment and Labor to investigate the number of the employed. Classification between regular and temporary employments is made based on the definition of temporary workers settled in the Korea Tripartite Commission in 2002.
For the methods of analysis, the Granger Causality Test was conducted first to examine the primary cause and effect relationship on the impact of changes in number of the employed on housing price fluctuations. The time-series data used in the analysis may contain instabilities, and result in incorrect results of analysis. Thus, stability of the time-series data shall be achieved by testing the instabilities, and Augmented Dickey Fuller Test was conducted for the purpose.
Vector Autoregression(VAR) Model was used to examine the impact of changes in number of the employed on housing prices. VAR model is used when there is not a long-run equilibrium among the variables, and it was tested through the Johansen Cointegration Test.
Impulse Response Analysis, which is to determine whether the changes in number of the employed had a rising or falling effect on the housing prices, to supplement the significance interpretation of the VAR model estimation value.
Variance Decomposition Analysis is to determine if a certain variable is affected by changes in other variables. The impact of changes in employment variable on housing price fluctuations was determined and the rifle effect of employment was verified based on the result of the analysis.
The overall result of this study indicates that there is a significant correlation between professional management jobs, which is a high-paying profession, and sales prices in Seoul and Incheon.
Technical laboring jobs, which is relatively a low-paying profession, did not have any causality relationship with the sales markets of the three regions. It can be interpreted that housing affordability based on income to fixed expenses ratio is relatively low compared to other professions, and restrictions on secured loan can be converted to the lease market rather than the sales market.
It can also be explained with the results of the Impulse Response Analysis and the Variance Decomposition Analysis of the VAR model, and technical laboring jobs showed a mid to long-term rising effect on the lease prices in Seoul and Gyeonggi-do before ceasing. Service and sales jobs, which is a middle-income profession, showed causality relationships on most parts of the sales and lease prices to prove that it has a rising effect on the both housing markets.
On the aspect of employment security, regular employees had more significant causality relationship with sales prices compared to temporary workers. The results of the Impulse Response Analysis of the VAR model also suggest that the regular employees had a mid to long-term rising effect on sales prices of the three regions while impact effect of temporary workers rather reduced the sales prices.
Regular employees also had a higher level of contribution in sales price rise on the Variance Decomposition Analysis compared to temporary workers. Self-employed had a causality relationship with the sales prices in Seoul and Incheon, and showed a mid to long-term rising effect on the Impulse Response Analysis as well. However, it had a relatively low level of contribution in sales price rise compared to the other employment variables.
For lease prices, temporary workers had a more significant causality relationship
This study is originated from an idea that real estate prices can be affected by forms of employment and occupations, those which are the determinants of income. In the relationship between forms of employment and housing market, there seemed to be local and temporal rifle effects of housing price fluctuations. Moreover, this study is to examine the correlation between local housing prices and employment variables relating to income, and to discover academic significances by combining the issues in the local house market and employment. Ultimately, this study is to suggest housing policies that suit the current market by analyzing structural changes in the housing market and current employment conditions. This study was conducted based on both literature research and empirical analysis. For literature research, researches were made on housing prices, employment variables, income classifications relating to employment, asset structures and conditions in employment characteristics, and an analysis on previous studies, journals and media references were made to establish the ground of the research background. For scopes and ranges of the research, the time scope was from January 2006 to July 2015 (total 115 months), and the spatial range was limited to the cosmopolitan area including Seoul, Incheon and Gyeonggi-do province. The number of cosmopolitan housing in Seoul, Incheon and Gyeonggi is 8.89million, which takes up 45.7% of the total, and the housing market in the region has a significance as an analytic data since it has the greatest impact on housing demand and prices in Korea. For housing price variables, the housing sales price index and the housing lease price index issued every month by Korea Appraisal Board was used. For employment variables, the number of the employed per occupation and the number of employed per status of workers determined by Ministry of Employment and Labor were used. The number of the employed per occupation is based on the categories of senior managers, professionals, technical specialists, office workers, service workers, sales workers, technical/equipment/machinery workers and technical laborers counted by the Ministry of Employment and Labor among the 10 Korean Standard Classification of Occupation. The number of the employed per status of workers is based of the numbers of non-wage workers (self-employed and unpaid family workers) and wage workers (regular employees, temporary workers and daily workers) counted by the Ministry of Employment and Labor to investigate the number of the employed. Classification between regular and temporary employments is made based on the definition of temporary workers settled in the Korea Tripartite Commission in 2002.
For the methods of analysis, the Granger Causality Test was conducted first to examine the primary cause and effect relationship on the impact of changes in number of the employed on housing price fluctuations. The time-series data used in the analysis may contain instabilities, and result in incorrect results of analysis. Thus, stability of the time-series data shall be achieved by testing the instabilities, and Augmented Dickey Fuller Test was conducted for the purpose.
Vector Autoregression(VAR) Model was used to examine the impact of changes in number of the employed on housing prices. VAR model is used when there is not a long-run equilibrium among the variables, and it was tested through the Johansen Cointegration Test.
Impulse Response Analysis, which is to determine whether the changes in number of the employed had a rising or falling effect on the housing prices, to supplement the significance interpretation of the VAR model estimation value.
Variance Decomposition Analysis is to determine if a certain variable is affected by changes in other variables. The impact of changes in employment variable on housing price fluctuations was determined and the rifle effect of employment was verified based on the result of the analysis.
The overall result of this study indicates that there is a significant correlation between professional management jobs, which is a high-paying profession, and sales prices in Seoul and Incheon.
Technical laboring jobs, which is relatively a low-paying profession, did not have any causality relationship with the sales markets of the three regions. It can be interpreted that housing affordability based on income to fixed expenses ratio is relatively low compared to other professions, and restrictions on secured loan can be converted to the lease market rather than the sales market.
It can also be explained with the results of the Impulse Response Analysis and the Variance Decomposition Analysis of the VAR model, and technical laboring jobs showed a mid to long-term rising effect on the lease prices in Seoul and Gyeonggi-do before ceasing. Service and sales jobs, which is a middle-income profession, showed causality relationships on most parts of the sales and lease prices to prove that it has a rising effect on the both housing markets.
On the aspect of employment security, regular employees had more significant causality relationship with sales prices compared to temporary workers. The results of the Impulse Response Analysis of the VAR model also suggest that the regular employees had a mid to long-term rising effect on sales prices of the three regions while impact effect of temporary workers rather reduced the sales prices.
Regular employees also had a higher level of contribution in sales price rise on the Variance Decomposition Analysis compared to temporary workers. Self-employed had a causality relationship with the sales prices in Seoul and Incheon, and showed a mid to long-term rising effect on the Impulse Response Analysis as well. However, it had a relatively low level of contribution in sales price rise compared to the other employment variables.
For lease prices, temporary workers had a more significant causality relationship
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