Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-08T00:03:43.513Z Has data issue: false hasContentIssue false
  • English
  • Français

Total Factor Productivity Decomposition and Unobserved Heterogeneity in Stochastic Frontier Models

Published online by Cambridge University Press:  15 September 2016

Magnus A. Kellermann
Magnus A. Kellermann*
Affiliation:
Environmental Economics and Agricultural Policy Group of Technische Universität in Muenchen, Germany
*
Correspondence: Environmental Economics and Agricultural Policy Group ▪ TUM School of Management ▪ Technische Universität Muenchen ▪ Alte Akademie 14, 85350 ▪ Freising GERMANY ▪ Phone +49.8161.71.3576 ▪ Email [email protected].
Get access

Abstract

This study examines in an empirical comparison how different econometric specifications of stochastic frontier models affect the decomposition of total factor productivity growth. We estimate nine stochastic frontier models, which have been widely used in empirical investigations of sources of productivity growth. Our results show that the relative contribution of components to total factor productivity growth is quite sensitive to the choice of econometric model, which points to the need to select the “right” model. We apply various statistical tests to narrow the range of applicable models and identify additional criteria upon which to base the choice of non-nested models.

Keywords

heterogeneitypanel datastochastic frontierTFP decomposition
Type
Research Article
Information
Agricultural and Resource Economics Review , Volume 44 , Issue 1 , April 2015 , pp. 124 - 148
Copyright
Copyright © 2015 Northeastern Agricultural and Resource Economics Association 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abdulai, A., and Tietje, H. 2007. “Estimating Technical Efficiency under Unobserved Heterogeneity with Stochastic Frontier Models: Application to Northern German Dairy Farms.” European Review of Agricultural Economics 34(3): 393–416.Google Scholar
Ahmad, M., and Bravo-Ureta, B. 1996. “Technical Efficiency Measures for Dairy Farms Using Panel Data: A Comparison of Alternative Model Specification.” Journal of Productivity Analysis 7(4): 399–415.Google Scholar
Aiello, F., Mastromarco, C., and Zago, A. 2011. “Be Productive or Face Decline. On the Sources and Determinants of Output Growth in Italian Manufacturing Firms.” Empirical Economics 41(3): 787–815.Google Scholar
Aigner, D., Lovell, C.A.K., and Schmidt, P. 1977. “Formulation and Estimation of Stochastic Frontier Production Function Models.” Journal of Econometrics 6(1): 21–37.CrossRefGoogle Scholar
Alvarez, A., Arias, C., and Greene, W. 2005. “Accounting for Unobservables in Production Models: Management and Inefficiency.” Efficiency Series Paper 7/2005, Department of Economics, University of Oviedo.Google Scholar
Baltagi, B., and Li, O. 1990. “A Lagrange Multiplier Test for the Error Components Model with Incomplete Panels.” Econometric Reviews 9(1): 103–107.Google Scholar
Battese, G.E., and Coelli, T.J. 1992. “Frontier Production Functions, Technical Efficiency, and Panel Data with Application to Paddy Farmers in India.” Journal of Productivity Analysis 3(1/2): 153–169.CrossRefGoogle Scholar
Battese, G.E., and Coelli, T.J. 1995. “A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data.” Empirical Economics 20(2): 325–332.Google Scholar
Bauer, P.W. 1990. “Decomposing TFP Growth in the Presence of Cost Inefficiency, Nonconstant Returns to Scale, and Technological Progress.” Journal of Productivity Analysis 1(4): 287–299.Google Scholar
Bayarsaihan, T, and Coelli, T.J. 2003. “Productivity Growth in Pre-1990 Mongolian Agriculture: Spiraling Disaster or Emerging Success?” Agricultural Economics 28(2): 121–137.Google Scholar
Brümmer, B., Glauben, T., and Thijssen, G.J. 2002. “Decomposition of Productivity Growth Using Distance Functions: The Case of Dairy Farms in Three European Countries.” American Journal of Agricultural Economics 84(3): 628–644.Google Scholar
Caves, D.W., Christensen, L.R., and Diewert, W.E. 1982. “The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity.” Econometrica 50(6): 1393–1414.Google Scholar
Coelli, T.J. 2000. “On the Econometric Estimation of the Distance Function Representation of a Production Technology.” Discussion Paper 2000/42, Center for Operations Research and Econometrics, Universite Catholique de Louvain.Google Scholar
Coelli, T.J., and Perelman, S. 1999. “A Comparison of Parametric and Non-parametric Distance Functions with Application to European Railways.” European Journal of Operational Research 117(2): 326–339.CrossRefGoogle Scholar
Coelli, T.J., Rahman, S., and Thirtle, C. 2003. “A Stochastic Frontier Approach to Total Factor Productivity Measurement in Bangladesh Crop Agriculture, 1961–92.” Journal of International Development 15(3): 321–333.Google Scholar
Cornwell, C., Schmidt, P., and Sickles, R.C. 1990. “Production Frontiers with Cross-sectional and Time-series Variation in Efficiency Levels.” Journal of Econometrics 46(1/2): 185–200.Google Scholar
Cuesta, R.A. 2000. “A Production Model with Firm-specific Temporal Variation in Technical Efficiency with Application to Spanish Dairy Farms.” Journal of Productivity Analysis 13(2): 139–158.CrossRefGoogle Scholar
Denny, M., Fuss, M., and Waverman, L. 1981. “The Measurement and Interpretation of Total Factor Productivity in Regulated Industries with an Application to Canadian Telecommunications.” In Cowing, T.G. and Stevenson, R.E., eds., Productivity Measurement in Regulated Industries. New York, NY: Academic Press.Google Scholar
Deprins, D., and Simar, L. 1989. “Estimating Technical Inefficiencies with Corrections for Environmental Conditions with an Application to Railway Companies.” Annals of Public and Cooperative Economics 60(1): 81–102.Google Scholar
Emvalomatis, G. 2012. “Productivity Growth in German Dairy Farming Using a Flexible Modelling Approach.” Journal of Agricultural Economics 63(1): 83–101.Google Scholar
Fan, S. 1991. “Effects of Technological Change and Institutional Reform on the Productivity Growth in Chinese Agriculture.” American Journal of Agricultural Economics 73(2): 266–275.Google Scholar
Farsi, M., Filippini, M., and Greene, W.H. 2005. “Efficiency Measurement in Network Industries. Application to the Swiss Railway Companies.” Journal of Regulatory Economics 28(1): 69–90.Google Scholar
Farsi, M., Filippini, M., and Kuenzle, M. 2005. “Unobserved Heterogeneity in Stochastic Cost Frontier Models. An Application to Swiss Nursing Homes.” Applied Economics 37(18): 2127–2141.Google Scholar
Fecher, F., and Pestieau, P. 1993. “Efficiency and Competition in OECD Financial Services.” In Fried, H.O., Lovell, C.A.K., and Schmidt, S.S., eds., The Measurement of Productive Efficiency: Techniques and Applications. Oxford, UK: Oxford University Press.Google Scholar
Filippini, M., Hrovatin, N., and Zoric, J. 2010. “Productivity Growth and Price Regulation of Slovenian Water Distribution Utilities.” Zbornik Radova Ekonomskog Fakulteta u Rijeci 28(1): 89–112.Google Scholar
Goto, M., and Sueyoshi, T. 2009. “Productivity Growth and Deregulation of Japanese Electricity Distribution.” Energy Policy 37(8): 3130–3138.CrossRefGoogle Scholar
Greene, W.H. 1993. “The Econometric Approach to Efficiency Analysis.” In Fried, H.O., Lovell, C.A.K., and Schmidt, S.S., eds., The Measurement of Productive Efficiency: Techniques and Applications. Oxford, UK: Oxford University Press.Google Scholar
Greene, W.H. 2003. Econometric Analysis, 5th ed. Upper Saddle River, NJ: Prentice Hall. Google Scholar
Greene, W.H. 2005. “Reconsidering Heterogeneity in Panel Data Estimators of the Stochastic Frontier Model.” Journal of Econometrics 126(2): 269–303.Google Scholar
Greene, W.H. 2007. LIMDEP version 9.0. Econometric Software, Plainview, NY.Google Scholar
Greene, W.H. 2008. “The Econometric Approach to Efficiency Analysis.” In Fried, H.O., Lovell, C.A.K., and Schmidt, S.S., eds., The Measurement of Productive Efficiency and Productivity Growth. Oxford, UK: Oxford University Press.Google Scholar
Griliches, Z., and Mairesse, J. 1998. “Production Functions: The Search for Identification.” In Griliches, Z., ed., Practicing Econometrics: Essays in Method and Application. Cheltenham, UK: Edward Elgar.Google Scholar
Grosskopf, S. 1993. “Efficiency and Productivity.” In Fried, H.O., Lovell, C.A.K., and Schmidt, S.S., eds., The Measurement of Productive Efficiency: Techniques and Applications. Oxford, UK: Oxford University Press.Google Scholar
Hallam, D., and Machado, F. 1996. “Efficiency Analysis with Panel Data: A Study of Portuguese Dairy Farms.” European Review of Agricultural Economics 23(1): 79–93.CrossRefGoogle Scholar
Hausman, J.A., and Taylor, E.E. 1981. “Panel Data and Unobservable Individual Effects.” Econometrica 49(6): 1377–1398.Google Scholar
Henningsen, A., and Henning, C. 2009. “Imposing Regional Monotonicity on Translog Stochastic Production Frontiers with a Simple Three-Step Procedure.” Journal of Productivity Analysis 32(3): 217–229.CrossRefGoogle Scholar
Huang, C.J., and Liu, T.J. 1994. “Estimation of a Non-neutral Stochastic Frontier Production Function.” Journal of Productivity Analysis 5(2): 171–180.CrossRefGoogle Scholar
Jin, S., Ma, H., Huang, J., Hu, R., and Rozelle, S. 2010. “Productivity, Efficiency, and Technical Change: Measuring the Performance of China's Transforming Agriculture.” Journal of Productivity Analysis 33(3): 191–207.CrossRefGoogle Scholar
Jondrow, J., Lovell, C.A.K., Materov, I.S., and Schmidt, P. 1982. “On the Estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model.” Journal of Econometrics 19(2/3): 233–238.CrossRefGoogle Scholar
Karagiannis, G., Midmore, P., and Tzouvelekas, V. 2004. “Parametric Decomposition of Output Growth Using a Stochastic Input Distance Function.” American Journal of Agricultural Economics 86(4): 1044–1057.Google Scholar
Karagiannis, G., and Tzouvelekas, V. 2005. “Explaining Output Growth with a Heteroscedastic Non-neutral Production Frontier: The Case of Sheep Farms in Greece.” European Review of Agricultural Economics 32(1): 51–74.Google Scholar
Karagiannis, G., and Tzouvelekas, V. 2010. “Parametric Measurement of Time-varying Technical Inefficiency: Results from Competing Models.” Agricultural Economic Review 10(1): 50–79.Google Scholar
Key, N., and McBride, W. 2007. “The Changing Economics of U.S. Hog Production.” ERR-52, Economic Research Service, U.S. Department of Agriculture, Washington, DC.Google Scholar
Key, N., McBride, W., and Mosheim, R. 2008. “Decomposition of Total Factor Productivity Change in the U.S. Hog Industry.” Journal of Agricultural and Applied Economics 40(1): 137–149.Google Scholar
Kim, S., and Han, G. 2001. “A Decomposition of Total Factor Productivity Growth in Korean Manufacturing Industries: A Stochastic Frontier Approach.” Journal of Productivity Analysis 16(3): 269–281.Google Scholar
Kumbhakar, S.C., Ghosh, S.N., and McGuckin, J.T. 1991. “A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms.” Journal of Business and Economic Statistics 9(3): 279–286.Google Scholar
Kumbhakar, S.C., and Hjalmarsson, L. 1993. “Technical Efficiency and Technical Progress in Swedish Dairy Farms.” In Fried, H.O., Lovell, C.A.K., and Schmidt, S.S., eds., The Measurement of Productive Efficiency: Techniques and Applications. Oxford, UK: Oxford University Press.Google Scholar
Kumbhakar, S.C., and Lovell, C.A.K. 2000. Stochastic Frontier Analysis. Cambridge, UK: Cambridge University Press.Google Scholar
Lovell, C.A.K. 1996. “Applying Efficiency Measurement Techniques to the Measurement of Productivity Change.” Journal of Productivity Analysis 7(2/3): 329–340.Google Scholar
Morrison Paul, C.J., Johnston, W.E., and Frengley, G.A. 2000. “Efficiency in New Zealand Sheep and Beef Farming: The Impacts of Regulatory Reform.” Review of Economics and Statistics 82(2): 325–337.CrossRefGoogle Scholar
Mundlak, Y. 1978. “On the Pooling of Time Series and Cross Section Data.” Econometrica 46(1): 69–85.Google Scholar
Mundlak, Y. 1996. “Production Function Estimation: Reviving the Primal.” Econometrica 64(2): 431–438.Google Scholar
Newman, C., and Matthews, A. 2006. “The Productivity Performance of Irish Dairy Farms 1984–2000: A Multiple Output Distance Function Approach.” Journal of Productivity Analysis 26(2): 191–205.Google Scholar
O'Donnell, C., and Coelli, T.J. 2005. “A Bayesian Approach to Imposing Curvature on Distance Functions.” Journal of Econometrics 126(2): 493–523.Google Scholar
Orea, L., and Kumbhakar, S.C. 2004. “Efficiency Measurement Using a Latent Class Stochastic Frontier Model.” Empirical Economics 29(1): 169–183.Google Scholar
Pitt, M., and Lee, L.F. 1981. “The Measurement and Sources of Technical Inefficiency in the Indonesian Weaving Industry.” Journal of Development Economics 9(1): 43–64.Google Scholar
Polachek, S., and Yoon, B. 1996. “Panel Estimates of a Two-tiered Earnings Frontier.” Journal of Applied Econometrics 11(2): 169–178.Google Scholar
Quantitative Micro Software. 2007. EViews version 6. Irvine, CA.Google Scholar
Rae, A.N., Ma, H., Huang, J., and Rozelle, S. 2006. “Livestock in China: Commodity-specific Total Factor Productivity Decomposition Using New Panel Data.” American Journal of Agricultural Economics 88(3): 680–695.Google Scholar
Rasmussen, S. 2010. “Scale Efficiency in Danish Agriculture. An Input Distance-Function Approach.” European Review of Agricultural Economics 37(3): 335–367.Google Scholar
Saal, D.S., Parker, D., and Weyman-Jones, T. 2007. “Determining the Contribution of Technical Change, Efficiency Change, and Scale Change to Productivity Growth in the Privatized English and Welsh Water and Sewerage Industry: 1985–2000.” Journal of Productivity Analysis 28(1/2): 127–139.Google Scholar
Sauer, J., Frohberg, K., and Hockmann, H. 2006. “Stochastic Efficiency Measurement: The Curse of Theoretical Consistency.” Journal of Applied Economics 9(1): 139–165.Google Scholar
Schmidt, P. 1988. “Estimation of a Fixed-effect Cobb-Douglas System Using Panel Data.” Journal of Econometrics 37(3): 361–380.Google Scholar
Schmidt, P., and Sickles, R.C. 1984. “Production Frontiers and Panel Data.” Journal of Business Economics and Statistics 2(4): 367–374.Google Scholar
Self, S.G., and Liang, K.Y. 1987. “Asymptotic Properties of Maximum Likelihood Estimators and Likelihood Ratio Tests under Nonstandard Conditions.” Journal of the American Statistical Association 82(398): 605–610.Google Scholar
Sherlund, S.M., Barrett, C.B., and Adesima, A.A. 2002. “Smallholder Technical Efficiency Controlling for Environmental Production Conditions.” Journal of Development Economics 69(1): 85–101.Google Scholar
Tovar, B., Ramos-Real, F.J., and de Almeida, E.F. 2011. “Firm Size and Productivity: Evidence from the Electricity Distribution Industry in Brazil.” Energy Policy 39(2): 826–833.Google Scholar
Tsionas, M. 2002. “Stochastic Frontier Models with Random Coefficients.” Journal of Applied Econometrics 17(2): 127–147.Google Scholar
Tzouvelekas, V., Pantzios, C.J., and Fotopoulos, C. 2001. “Technical Efficiency of Alternative Farming Systems: The Case of Greek Organic and Conventional Olive-growing Farms.” Food Policy 26(6): 549–569.Google Scholar
Wang, H.J., and Ho, C.W. 2010. “Estimating Fixed-effect Panel Stochastic Frontier Models by Model Transformation.” Journal of Econometrics 157(2): 286–296.Google Scholar
Wetzel, H. 2009. “Productivity Growth in European Railways: Technological Progress, Efficiency Change, and Scale Effects.” Working Paper Series in Economics, Leuphana Universität Lüneburg.Google Scholar
Wu, Y. 1995. “Productivity Growth, Technological Progress, and Technical Efficiency Change in China: A Three-sector Analysis.” Journal of Comparative Economics 21(2): 207–229.Google Scholar
Yao, S., Liu, Z., and Zhang, Z. 2001. “Spatial Differences of Grain Production Efficiency in China, 1987–1992.” Economics of Planning 34(1/2): 139–157.Google Scholar
Zellner, A., Kmenta, J., and Dreze, J. 1966. “Specification and Estimation of Cobb-Douglas Production Function Models.” Econometrica 34(4): 784–795.Google Scholar
Zhu, X., and Oude Lansink, A. 2010. “Impact of CAP Subsidies on Technical Efficiency of Crop Farms in Germany, the Netherlands, and Sweden.” Journal of Agricultural Economics 61(3): 545–564.Google Scholar