수렴과 생산성 성장에 대한 인적자본의 효과: 국제 동적 패널
The Effects of Human Capital on Convergence and Productivity Growth: An International Dynamic Panel Analysis
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본고에서는 인적자본, 총요소 생산성 성장 및 수렴간의 관계에 대해 거시경제 지표와 교육적 성취에 대한 국제 패널 자료를 사용하여 연구하고자 한다. 확률적 솔로우 모형과 동적 패널 추정 기법을 사용하여 모형내에서 국가간 기술 성장률의 이질성이 명시적으로 허용된다. 따라서 본고에서의 수렴은 기존 문헌에서처럼 자료 집합내의 모든 국가들을 위한 공통적 균제 상태로의 수렴이 아니라, 개별 국가 자신의 특정 균제 상태로의 수렴이다. 분석 결과, 첫째, 기존의 성장 문헌에서 부재하는 것으로 보통 가정되어 온 국가간 기술 성장률의 이질성이 현저하다는 사실이 발견되었다. 둘째, 평균적 수렴 속도 추정치는 연간 27~32%로 기존의 횡단면 자료를 사용한 연구에서 보고된 추정치보다 훨씬 높게 추정되었다. 셋째, 다양한 교육적 성취 지표로 대리된 인적자본 변수가 포함된 모형이 포함되지 않은 모형보다 더 높은 수렴 속도 추정치를 보여주었다. 넷째, 인적자본이 있는 모형에서 없는 모형보다 기술 성장률의 평균 추정치가 더 높게 나타났다. 다섯째, 인적자본 수준이 국내 내생적 기술혁신과 기술추격 효과를 통해 총요소 생산성 성장에 영향을 줄 수 있는 구조 방정식을 추정한 결과, 기술추격 효과가 국내 기술혁신 효과보다 강력하다는 사실이 발견된다.
Abstract
This paper examines the relationship among human capital, total factor productivity growth and convergence using international panel data on macroeconomic indicators and educational attainment. It explicitly allows for the heterogeneity in technology growth across countries by use of the stochastic Solow model and dynamic panel estimation techniques. Thus the convergence in this paper is toward the steady state of the individual country, not toward the common steady state for all nations in the data set as in the existing literature. It reports the findings as follows. First, heterogeneity in technology growth across countries, which has been typically assumed to be nonexistent in the growth literature, is found to be prominent. Second, the average estimates of convergence rates are between 27% and 32% per annum, which are much higher than those reported in the researches using cross-section data. Third, the model with human capital proxied by various educational attainment measures gives higher convergence rate estimates than the model without it. Fourth, the average estimates for technology growth are higher in the model with human capital than in the model without it. Fifth, it estimates the structural equation in which human capital levels can influence total factor productivity growth by domestic endogenous innovation and technological catch-up effects. It finds that the catch-up effect is stronger than the domestic innovation effect.
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