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An Analysis for the Structural Variation in the Unemployment Rate and the Test for the Turning Point

실업률 변동구조의 분석과 전환점 진단

  • Kim, Tae-Ho (Department of Information Statistics, Chungbuk National University) ;
  • Hwang, Sung-Hye (Department of Information Statistics, Chungbuk National University) ;
  • Lee, Young-Hoon (Department of Economics, Chungbuk National University)
  • 김태호 (충북대학교 정보통계학과) ;
  • 황성혜 (충북대학교 정보통계학과) ;
  • 이영훈 (충북대학교 경제학과)
  • Published : 2005.07.01

Abstract

One of the basic assumptions of the regression models is that the parameter vector does not vary across sample observations. If the parameter vector is not constant for all observations in the sample, the statistical model is changed and the usual least squares estimators do not yield unbiased, consistent and efficient estimates. This study investigates the regression model with some or all parameters vary across partitions of the whole sample data when the model permits different response coefficients during unusual time periods. Since the usual test for overall homogeneity of regressions across partitions of the sample data does not explicitly identify the break points between the partitions, the testing the equality between subsets of coefficients in two or more linear regressions is generalized and combined with the test procedure to search the break point. The method is applied to find the possibility and the turning point of the structural change in the long-run unemployment rate in the usual static framework by using the regression model. The relationships between the variables included in the model are reexamined in the dynamic framework by using Vector Autoregression.

회귀모형의 기본가정은 추정된 계수들이 표본 내의 모든 관측값에 대해 일정하다는 것이다. 그러나 자료의 구조적 변화로 인해 모형의 추정계수 중 최소한 일부는 상이한 부분집합으로 전체 표본을 분할해야 하는 경우가 현실적으로는 흔히 존재한다. 본 연구에서는 두 회귀모형 계수들간의 동일성을 검정하는 방법을 확대${\cdot}$일반화하여 자료의 분할시점을 탐색하는 검정절차와 결합시킨 후 이를 최근 가장 큰 사회적 문제가 되고 있는 실업률의 구조변화 발생 여부와 시점을 판별하는 실증분석에 적용시켜 보았다.

Keywords

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