경상북도 시군 패널데이터를 이용한도시민들의 귀농 유발요인 분석 (A Panel Data Analysis of Determinant Factor Affecting Return to Farming for Urban Residents in Gyeongsangbuk Province)

서지정보

· 발행기관 : 한국농식품정책학회
· 수록지 정보 : 농업경영.정책연구 / 45권 / 3호 / 438 ~ 456페이지
· 저자명 : 권오성, 여준호

초록

This study analyzed determinants of return to farming to use panel data analysis. To do this, we collected the data related to the return to farming over the period 2007 to 2014. First, we conducted F-test and LM-test for choosing a model that is considered a characteristics of the panels. As a result, tests show that panel data analysis is more suitable than the other.
Second, we conducted Unit Root Test to confirm stability of time series data because panel data include part of time series. The test shows the panel data has stability of time series. Third, we used Hausman-test to decide a suitable model is either Fixed Effects Model or Random Effects Model. The Hausman-test indicated that Fixed Effects Model is compatible. The Fixed Effects Model shows that if the subsidy for return to farming will increase ten millions won about policy variable, the number of households also increases one household. And a number of bed hospitals in every thousand people also positive effect(+) to the return to farming. And If the area has a number of house, it would be increase the number of household for returning to farming. The model has a positive coefficient about Gross regional domestic product of agriculture. This means that the people who move to area for farming thought conditions for agriculture. And urban people also consider the number of people who works in primary industry because they can get a job related to their work. And the number of pollution discharge facilities doesn’t influenced to return to farming. But the factor indicates a negative coefficient.

영어초록

This study analyzed determinants of return to farming to use panel data analysis. To do this, we collected the data related to the return to farming over the period 2007 to 2014. First, we conducted F-test and LM-test for choosing a model that is considered a characteristics of the panels. As a result, tests show that panel data analysis is more suitable than the other.
Second, we conducted Unit Root Test to confirm stability of time series data because panel data include part of time series. The test shows the panel data has stability of time series. Third, we used Hausman-test to decide a suitable model is either Fixed Effects Model or Random Effects Model. The Hausman-test indicated that Fixed Effects Model is compatible. The Fixed Effects Model shows that if the subsidy for return to farming will increase ten millions won about policy variable, the number of households also increases one household. And a number of bed hospitals in every thousand people also positive effect(+) to the return to farming. And If the area has a number of house, it would be increase the number of household for returning to farming. The model has a positive coefficient about Gross regional domestic product of agriculture. This means that the people who move to area for farming thought conditions for agriculture. And urban people also consider the number of people who works in primary industry because they can get a job related to their work. And the number of pollution discharge facilities doesn’t influenced to return to farming. But the factor indicates a negative coefficient.

참고자료

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