본 연구는 지적공사의 행정구역 단위별 지사를 유형화하여 대표지사별(지역별) 영향요인 분석(Autoreg)을 통해 지역별 영향요인과 부동산시장 변수와의 영향관계를 도출하였다. 전국 지사(지역)의 세그멘테이션을 위해 스펙트럼 분석(주기 및 추세 분석) 방법을 이용하였으며, 지역별 영향요인 분석을 위해 자기회귀오차모형(Autoregressive error model)을 이용하여 분석하였다. 연구 성과물로는 행정구역 단위별 전국 지사를 샘플링하여 대표지사 12개를 추출하여 영향요인 모형분석에 적용하였다. 지사별(지역별) 영향관계를 분석한 결과 부동산구매계획이 공통적으로 대부분 지사에서 영향요인으로 나타났으며, 시·군·구별로 시지역은 부동산구매계획과 금리의 변화에 의해 지적측량 업무량에 영향을 미치며 군지역은 부동산구매계획과 지역토지거래량이, 구지역은 금리가 공통 요인으로 나타났으며 양(+), 음(-)의 영향관계에 있는 것으로 나타났다. 이는 향후 부동산 시장의 변화를 통해 지적측량 업무량과 시장의 변화, 정책 효과를 예측할 수 있는 변동예고지표로 활용 할 수 있다.

This study focuses on analyzing the regional factors and its primary factors that have an effect on the cadastral surveying workload and drawing a conclusion the main factors by applying Autoregressive error model. The analysis method is that the segmentation of the branch offices by analyzing the cycle and trend of cadastral workload which is applied to spectral analysis method and the regional main factors having an effect on Cadastral Surveying workload are applied to Autoregressive error model, GARCH model. The main result is that the segmentation of head office and 210 branch offices, which are made up developing offices, stable offices, upward offices, unstable offices which are typed 12 representative offices and that are applied to autoregressive error model. And also, the result of the regional main factors analysis is that the common factor is a real estate planning buying affected branch offices mainly but other factors are a little different regionally. But it has affected by Real Eastate Policy and Construction market factors, mostly.

This study focuses on analyzing the regional factors and its primary factors that have an effect on the cadastral surveying workload and drawing a conclusion the main factors by applying Autoregressive error model. The analysis method is that the segmentation of the branch offices by analyzing the cycle and trend of cadastral workload which is applied to spectral analysis method and the regional main factors having an effect on Cadastral Surveying workload are applied to Autoregressive error model, GARCH model. The main result is that the segmentation of head office and 210 branch offices, which are made up developing offices, stable offices, upward offices, unstable offices which are typed 12 representative offices and that are applied to autoregressive error model. And also, the result of the regional main factors analysis is that the common factor is a real estate planning buying affected branch offices mainly but other factors are a little different regionally. But it has affected by Real Eastate Policy and Construction market factors, mostly.

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Impact Relationship between Cadastral Surveying workload and Real Estate Market factors, Autoregressive error model, cadastral surveying work load regional factors