Earticle

초록

영어

This study proposes a Bayesian stochastic frontier model that is well-suited to productivity/efficiency analysis particularly using panel data. A unique feature of our proposal is that both production frontier and efficiency are estimable for each individual firm and their linkage to various firm characteristics enriches our understanding of the source of productivity/efficiency. Empirical application of the proposed analysis to Human Capital Corporate Panel data enables identification and quantification of the effects of Human Resource factors on firm efficiency in tandem with those of firm types on production frontier. A comprehensive description of the Markov Chain Monte Carlo estimation procedure is forwarded to facilitate the use of our proposed stochastic frontier analysis.

목차

Abstract
1. Introduction
2. Model Specification and Estimation
2.1 Production Function Specification
2.2 Hierarchical Structure
2.3 MCMC Estimation
3. Data Description
3.1 HCCP Balanced Panel Data
3.2 Description of Variables
4. Results and Discussions
4.1 First-Stage Parameter Estimates
4.2 Second-Stage Parameter Estimates
5. Conclusion
References

키워드

저자

• Sangwoo Shin [ Solbridge International School of Business, Woosong University, Daejun, South Korea ]
• Hyejung Chang [ Department of Management, Kyung Hee University, Seoul, South Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Culture Technology(IJACT)

• 간기

  계간

• pISSN

  2288-7202

• eISSN

  2288-7318

• 수록기간

  2013~2025

• 등재여부

  KCI 등재

• 십진분류

  KDC 600 DDC 700