DOI QR코드

DOI QR Code

The Effects of Human Resource Factors on Firm Efficiency: A Bayesian Stochastic Frontier Analysis

  • Shin, Sangwoo (Solbridge International School of Business, Woosong University) ;
  • Chang, Hyejung (Department of Management, Kyung Hee University)
  • Received : 2018.11.20
  • Accepted : 2018.11.30
  • Published : 2018.12.31

Abstract

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.

Keywords

E1GMBY_2018_v6n4_292_f0001.png 이미지

Figure 1. Shares of firm type variables

E1GMBY_2018_v6n4_292_f0002.png 이미지

Figure 2. Description of HR factors

E1GMBY_2018_v6n4_292_f0004.png 이미지

Figure 3. First-stage estimates

Table 1. Descriptive statistics for output and input variables (Unit: Korean billion won)

E1GMBY_2018_v6n4_292_t0001.png 이미지

Table 2. Estimates of second-stage production frontier parameters

E1GMBY_2018_v6n4_292_t0002.png 이미지

Table 3. Estimates of second-stage inefficiency parameters

E1GMBY_2018_v6n4_292_t0003.png 이미지

References

  1. C.D. Fisher, "Current and recurrent challenges in HRM," Journal of Management, Vol. 15, No. 2, pp. 157-180, June 1989. doi: 10.1177/014920638901500203
  2. P.M. Wright and G.C. McMahan, "Theoretical perspectives for strategic human resource management," Journal of Management, Vol. 18, No. 2, pp. 295-320, June 1992. doi: 10.1177/014920639201800205
  3. J.B. Arthur, "Effects of human resource systems on manufacturing performance and turnover," Academy of Management Journal, Vol. 37, No. 3, pp. 670-687, June 1994. doi: 10.5465/256705
  4. J. Barney, "Firm resources and sustained competitive advantage," Journal of Management, Vol. 17, No. 1, 99-120, March 1991. doi: 10.1177/014920639101700108
  5. A.A. Lado and M.C. Wilson, "Human resource systems and sustained competitive advantage: A competency-based perspective," Academy of Management Review, Vol. 19, No. 4, pp. 699-727, October 1994. doi: 10.5465/amr.1994.9412190216
  6. C.J. Collins and K.D. Clark, "Strategic human resource practices, top management team social networks, and firm performance: The role of human resource practices in creating organizational competitive advantage," Academy of Management Journal, Vol. 46, No. 6, pp. 740-751, December 2003. doi: 10.2307/30040665
  7. D. Aigner, C.A.K. Lovell, and P. Schmidt, "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Vol. 6, No. 1, pp. 21-37, July 1977. doi: 10.1016/0304-4076(77)90052-5
  8. W. Meeusen, and J. van den Broeck, "Efficiency estimation from Cobb-Douglas production functions with composed errors," International Economic Review, Vol. 18, No. 2, pp. 435-444, June 1977. doi: https://doi.org/10.2307/2525757
  9. P. Bauer, "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Vol. 46, No. 1/2, pp. 39-56, October-November 1990. doi: 10.1016/0304-4076(90)90046-V
  10. G.E. Battese and T.J. Coelli, "Frontier production functions, technical efficiency and panel data with application to paddy fanners in India," Journal of Productivity Analysis, Vol. 3, No. 1/2, pp. 153-169, June 1992. doi: 10.1007/BF00158774
  11. G.E. Battese and T.J. Coelli, "A model for technical inefficiency effects in a stochastic frontier production function for panel data," Empirical Economics, Vol. 20, No. 2, pp. 325-332, June 1995. doi: 10.1007/BF01205442
  12. J. van den Broeck, G. Koop, J. Osiewalski, and M.F.J. Steel, "Stochastic frontier models: a Bayesian perspective," Journal of Econometrics, Vol. 61, No. 2, pp. 273-303, March 1994. doi: 10.1016/0304-4076(94)90087-6
  13. G. Koop, J. Osiewalski, and M.F.J. Steel, "Bayesian efficiency analysis with a flexible form: the AIM cost function," Journal of Business and Economic Statistics, Vol. 12, No. 3, pp. 339-346, July 1994. doi: 10.1080/07350015.1994.10524549
  14. G. Koop, J. Osiewalski, and M.F.J. Steel, "Bayesian efficiency analysis through individual effects: hospital cost frontiers," Journal of Econometrics, Vol. 76, No. 1/2, pp. 77-105, January-February 1997. doi: 10.1016/0304-4076(95)01783-6
  15. G.M. Allenby and P.E. Rossi, "Hierarchical Bayes model." In R. Grover, and M. Vriens (Eds.), The handbook of marketing research: uses, misuses, and future advances (pp. 418-440). Thousand Oaks, CA: Sage, 2006
  16. A.E. Gelfand and A.F.M. Smith, "Sampling-based approaches to calculating marginal densities," Journal of the American Statistical Association, Vol. 85, No. 410, pp. 398-409, June 1990. doi: https://doi.org/10.1080/01621459.1990.10476213
  17. A.E. Gelfand, "Gibbs sampling." Journal of the American Statistical Association, Vol. 95, No. 452, pp. 1300-1304, June 2000. doi: 10.1080/01621459.2000.10474335
  18. S. Chib and E. Greenberg, "Understanding the Metropolis-Hastings algorithm," American Statistician, Vol. 49, No. 4, pp. 327-335, November 1995. doi: 10.1080/00031305.1995.10476177