Search
Search

연구성과물 검색 타이틀 이미지

HOME ICON HOME > Search by Achievements Type > Reports View

Reports Detailed Information

https://www.krm.or.kr/krmts/link.html?dbGubun=SD&m201_id=10013928&local_id=10017414
효율성의 그룹별 시간변동을 고려한 확률적 생산변경모형
Reports NRF is supported by Research Projects( 효율성의 그룹별 시간변동을 고려한 확률적 생산변경모형 | 2006 Year | 이영훈(한성대학교) ) data is submitted to the NRF Project Results
Researcher who has been awarded a research grant by Humanities and Social Studies Support Program of NRF has to submit an end product within 6 months(* depend on the form of business)
사업별 신청요강보기
  • Researchers have entered the information directly to the NRF of Korea research support system
Project Number B00278
Year(selected) 2006 Year
the present condition of Project 종료
State of proposition 재단승인
Completion Date 2007년 12월 05일
Year type 결과보고
Year(final report) 2007년
Research Summary
  • Korean
  • 본 논문은 보다 현실에 적합한 확률적 생산변경모형을 개발하려는 목적을 갖고 있다. 소위 기술적 효율성의 'group-specific" 시간변동 패턴을 추정하기에 적합한 계량모형을 개발한다. 기존에 그룹별 시간변동을 고려한 확률적 생산변경모형은 Lee(2006)에 의하여 발전되었으나 이 모형의 경우 횡단면 관찰치가 많고 시계열은 짧은 패널자료에 적합한 모형이다. 따라서 비교적 시계열이 긴 경우의 패널자료가 있는 경우에는 효율성의 그룹별 시간변동 패턴을 추정하여 비교하기에 적합한 계량모형이 없었다. 이에 본 연구에서는 장기 시계열과 횡단면 자료가 적은 패널자료에 적합한 효율성의 변동추세를 추정할 수 있는 계량모형인 확률변경모형을 설정하였다.. 그리고 이 모형에 대한 추정방법 및 추정랴의 특설을 도출하였으려 실제 데이터에 적용하여 기존 모형과 비교분석 함의로써 본 연구에서 개발한 모형의 유용성을 보여주었다.
  • English
  • In this paper, we have considered a stochastic frontier model which allows not only for group-specific temporal pattern of technical efficiency, but also for parametric function of the temporal pattern. This model is straight-forward extension of the BC model in the way to allow for a group-specific parameter in the exponential function. Unlike the Lee (2006) model which requires a data set with large N and small T, this model is also useful for a panel data set with large T. We treat the individual effects as "fixed." Following Lee (2006), the concentrated least squares estimator is developed along with its asymptotic properties.
    We also apply this stochastic frontier model along with other previous introduced models to the measurement of efficiency by using the Penn World data. Our empirical results can be summarized as follows. First, the four group-specific models (G-LS1, G-LS2, G-BC1 and G-BC2) generate similar production function estimates for this panel data set, but somewhat different estimates from the rest of the models (SS, LS and BC). Nonetheless, our specification tests suggest the G-BC1 model to be the most useful for this sample data. Second, the estimated efficiency scores are substantially different across different models with respect to not only average measures but also individual temporal pattern of efficiency. However, the four group-specific models generate similar estimates of efficiency score, indicating that the efficiency measures are not sensitive to grouping and to the assumption of (unrestricted parameter or parametric function). The insensitiveness to the assumption of is expected since the parametric function of G-BCs can not be rejected and the specification of G-LSs nests that of G-BCs. A somewhat eye-opening finding is that G-LSs with completely unrestricted specification of which has been known to yield unreasonably variable efficiency measures, present quite stable efficiency scores. Third, overall empirical results show the group-specific models yield much more variation in temporal pattern of efficiency across countries. This application demonstrates that the group-specific stochastic frontier model with a parametric function of temporal pattern can feasibly be applied in a real empirical analysis
Research result report
  • Abstract
  • This paper develops a stochastic frontier model that not only focuses more on group-specific temporal variations in technical efficiency rather than the individual temporal variations, but also allows a parametric function of the time-varying coefficient of the efficiency factor. We derive the concentrated least square estimator and its asymptotic properties. When applied to the Penn World dataset, the group-specific models yield much more variation in the temporal pattern of efficiency across countries. This application demonstrates that a group-specific stochastic frontier model with a parametric function of temporal pattern can feasibly be applied in a real empirical analysis.
  • Research result and Utilization method
  • 장기 시계열과 횡단면 자료가 적은 패널자료에 적합한 효율성의 변동추세를 추정할 수 있는 계량모형인 확률변경모형을 설정하였음. 그리고 이 모형에 대한 추정방법 및 추정랴의 특설을 도출하였음. 현대 SCI학술지인 European Journal of Operational Research에 투고하여 심사중임.
  • Index terms
  • time-varying technical efficiency, group-specific temporal pattern, stochastic frontiers, panel data,
  • List of digital content of this reports
데이터를 로딩중 입니다.
  • This document, it is necessary to display the original author and you do not have permission
    to use copyrighted material for-profit
  • In addition , it does not allow the change or secondary writings of work
데이터 이용 만족도
자료이용후 의견
입력
트위터 페이스북
NRF Daejeon
(34113) 201, Gajeong-ro, Yuseong-gu, Daejeon, Korea
Tel: 82-42-869-6114 / Fax: 82-42-869-6777
NRF Seoul
(06792) 25, Heonreung-ro, Seocho-gu, Seoul, Korea
Tel: 82-2-3460-5500 / Fax: 82-2-3460-5759
KRM Help Center
Tel : 042-710-4360
E-mail : krmcenter@nrf.re.kr / Fax : 042-861-4380