• 한국산림과학회지
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• 제97권2호
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• pp.140-143
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• 2008

This study compared the plywood demand prediction accuracy of econometric and vector autoregressive models using Korean data. The econometric model of plywood demand was specified with three explanatory variables; own price, construction permit area, dummy. The vector autoregressive model was specified with lagged endogenous variable, own price, construction permit area and dummy. The dummy variable reflected the abrupt decrease in plywood consumption in the late 1990's. The prediction accuracy was estimated on the basis of Residual Mean Squared Error, Mean Absolute Percentage Error and Theil's Inequality Coefficient. The results showed that the plywood demand prediction can be performed more accurately by econometric model than by vector autoregressive model.

• 한국산림과학회지
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• 제95권2호
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• pp.203-208
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• 2006

This study compared the roundwood demand prediction accuracy of econometric and time-series models using Korean data. The roundwood was divided into softwood and hardwood by species. The econometric model of roundwood demand was specified with four explanatory variables; own price, substitute price, gross domestic product, dummy. The time-series model was specified with lagged endogenous variable. The dummy variable reflected the abrupt decrease in roundwood demand in the late 1990's in the case of softwood roundwood, and the boom of plywood export in the late 1970's in the case of hardwood roundwood. On the other hand, the prediction accuracy was estimated on the basis of Residual Mean Square Errors(RMSE). The results showed that the softwood roundwood demand prediction can be performed more accurately by econometric model than by time-series model. However, the hardwood roundwood demand prediction accuracy was similar in the case of using econometric and time-series model.

• 한국산림과학회지
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• 제95권5호
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• pp.601-604
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• 2006

This study compared the accuracy of partial multivariate and vector autoregressive models for lumber demand prediction in Korea. The partial multivariate model has three explanatory variables; own price, construction permit area and dummy. The dummy variable reflected the boom of lumber demand in 1988, and the abrupt decrease in 1998. The VAR model consists of two endogenous variables, lumber demand and construction permit area with one lag. On the other hand, the prediction accuracy was estimated by Root Mean Squared Error. The results showed that the estimation by partial multivariate and vector autoregressive model showed similar explanatory power, and the prediction accuracy was similar in the case of using partial multivariate and vector autoregressive model.

• 기술혁신학회지
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• 제9권2호
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• pp.236-259
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• 2006

본 연구는 기업의 자체 연구개발 활동과 외부 기술획득이 대체관계인지 보완관계인지를 실증적으로 검증하고자 한다. 구체적으로, 2002년 한국의 제조업을 대상으로 조사된 기술혁신조사를 바탕으로 구축된 자료를 사용하고, 준구조적(semi-structural) 실증분석모형의 개발하였다 . 이 모형을 헤크만(Heckman)의 2단계 추정방법으로 실증 분석한 결과, 기업의 연구개발 활동과 기술획득은 보완관계를 갖고 있으며, 기업의 연구개발에 영향을 마치는 여러 요인들 중 정부의 연구개발 지원 정책과 대기업 계열사 여부가 긍정적인 영향을 보이며, 기술획득에는 실패한 프로젝트의 존재가 중요한 요인으로 추정되었다.