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.

Ⅰ. 서 론

Ⅱ. 분석 모형 및 자료

Ⅲ. 분석결과

Ⅳ. 요약 및 결론