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Do Stock Opiton Schemes Affect Technical Inefficiency? Evidence from Finland

  • Mäkinen, Mikko

In this paper we study whether stock option schemes affect firm technical inefficiency. We estimate Cobb-Douglas stochastic production frontier models using a novel panel data set on the publicly listed Finnish firms in the manufacturing and ICT sectors over the period from 1992 to 2002. We find evidence that the mean inefficiency estimates in the ICT sector are clearly higher than in the manufacturing sector. Furthermore, our empirical findings suggest that broad-based option firms may have higher mean inefficiency than selective and non-option firms in the manufacturing sector. The quantitative assessments of the marginal effects on the inefficiency support the view that especially broad-based schemes affect the mean and the variance of the inefficiency term uit in the manufacturing sector, but not in the ICT sector. Our findings do not provide empirical support for the view that stock option schemes reduce firm technical inefficiency

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Paper provided by The Research Institute of the Finnish Economy in its series Discussion Papers with number 1085.

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Length: 26 pages
Date of creation: 2007
Date of revision:
Handle: RePEc:rif:dpaper:1085
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  1. Derek Jones & Panu Kalmi & Mikko Mäkinen, 2010. "The productivity effects of stock option schemes: evidence from Finnish panel data," Journal of Productivity Analysis, Springer, vol. 33(1), pages 67-80, February.
  2. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
  3. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-11, January.
  4. Wang, Hung-Jen, 2002. "Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model," MPRA Paper 31076, University Library of Munich, Germany.
  5. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
  6. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
  7. Murphy, Kevin J., 1999. "Executive compensation," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 38, pages 2485-2563 Elsevier.
  8. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
  9. Martin Conyon & Richard B. Freeman, 2004. "Shared Modes of Compensation and Firm Performance U.K. Evidence," NBER Chapters, in: Seeking a Premier Economy: The Economic Effects of British Economic Reforms, 1980-2000, pages 109-146 National Bureau of Economic Research, Inc.
  10. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-63, July.
  11. William Greene, 2001. "Fixed and Random Effects in Nonlinear Models," Working Papers 01-01, New York University, Leonard N. Stern School of Business, Department of Economics.
  12. Jones, Derek C & Kato, Takao, 1995. "The Productivity Effects of Employee Stock-Ownership Plans and Bonuses: Evidence from Japanese Panel Data," American Economic Review, American Economic Association, vol. 85(3), pages 391-414, June.
  13. Hyytinen, Ari & Kuosa, Iikka & Takalo, Tuomas, 2002. "Law of finance: Evidence from Finland," Research Discussion Papers 8/2002, Bank of Finland.
  14. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-86, July.
  15. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-74, October.
  16. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
  17. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
  18. Jones, Derek C. & Kalmi, Panu & Mäkinen, Mikko, 2004. "The Determinants of Stock Option Compensation: Evidence from Finland," Discussion Papers 957, The Research Institute of the Finnish Economy.
  19. Anna Bottasso & Alessandro Sembenelli, 2004. "Does ownership affect firms’ efficiency? Panel data evidence on Italy," Empirical Economics, Springer, vol. 29(4), pages 769-786, December.
  20. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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