Investments, Technical Change and Efficiency: Empirical Evidence from Czech Food Processing

DOI 10.7160/aol.2019.110409
No 4/2019, December
pp. 93-103

Rudinskaya, T. and Kuzmenko, E. (2019) “Investments, Technical Change and Efficiency: Empirical Evidence from Czech Food Processing", AGRIS on-line Papers in Economics and Informatics, Vol. 11, No. 4, pp. 93-103. ISSN 1804-1930. DOI 10.7160/aol.2019.110409.

Abstract

This empirical study aims to shed light on the dynamic linkages among investments, technical efficiency and productivity of food processing at a sectoral level. We use data obtained from meat and milk processing firms operating in the Czech Republic. The data set covers a period from 2011 to 2015. Being based on a production function frontier framework and the Divisia index our study is focuses on the estimation of technical efficiency and productivity of Czech Food processing firms in connection with the received investments. The results of the conducted analysis have shown that investments, directed to a production process of meat and milk processing firms operating in the Czech Republic, do have a positive effect on their technical efficiency. Moreover, it provides an opportunity to increase the capacity of raw milk processing. Higher TFP in food processing industry may result in higher TFP in agriculture.

Keywords

Technical efficiency, Technical change, Investments, Czech food processing, Divisia index.

References

  1. Aigner, D., Lovell, C. K. and Schmidt, P. (1977) "Formulation and estimation of stochastic frontier production function models“, Journal of Econometrics, Vol. 6, No. 1, pp. 21-37. ISSN 0304-4076. DOI 10.1016/0304-4076(77)90052-5.
  2. Alvarez A., Arias C. and Greene W. (2003) "Fixed Management and time invariant technical efficiency in a random coefficient model“, Working Paper, Department of Economics, Stern School of Business, New York University
  3. 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, Vol. 20, No. 2, pp. 325-332. E-ISSN 1435-8921, ISSN 0377-7332. DOI 10.1007/BF01205442.
  4. Beck, M. and Dogot, T. (2006) "The Use of Impact Indicators for the Evaluation of Farm Investment Support – A Case Study Based on the Rural Development Programme for Wallonia 2000 – 2006“, Working Papers in Agricultural Economics, No. 3, pp. 69-77.
  5. Bergschmidt, A. Dirksmeyer, W., Efken J, Forstner, B. and Uetrecht, I. (2006) "Proceedings of the European Workshop on the Evaluation of Farm Investment Support, Investment Support for Improvement of Processing and Marketing of Agricultural Products", Braunschweig: FAL, 266 p, Working Paper Agric Econ 2006/03
  6. Bergschmidt, A. (2009) “Powerless Evaluation”, EuroChoices, No. 8, pp. 37–42. ISSN 1746-692X. DOI 10.1111/j.1746-692X.2009.00137.x.
  7. Bergström, F. (1998) “Capital subsidies and the performance of firm”, SSE/EFI Working Paper Series in Economics and Finance, No. 258.
  8. Bernini, C. and Pellegrini, G. (2011) “How are growth and productivity in private firms affected by public subsidy? Evidence from a regional policy”, Regional Science and Urban Economics, Vol. 41, No 3, pp. 253-265. ISSN: 0166-0462. DOI 10.1016/j.regsciurbeco.2011.01.005.
  9. Boudný, J. and Janotová, B. (2015) “Ekonomika výroby vepřového masa – postavení ČR v Evropě” (In Czech), Náš chov, Vol. 75, pp. 73-78. ISSN 0027-8068.
  10. Ciaian, P., Kancs, d'A., Michalek, J. (2015) “Investment Crowding-Out: Firm-Level Evidence from Germany (July 2015)”, LICOS Discussion Paper 370/2015. DOI 10.2139/ssrn.2634922.
  11. Coelli, T., Perelman, S. and Van Lierde, D. (2006) “CAP Reforms and Total Factor Productivity Growth in Belgian Agriculture: A Malmquist Index Approach”, International Association of Agricultural Economists (IAAE), Annual Meeting, Queensland, Australia.
  12. Čechura L. and Hockmann H. (2017) “Heterogeneity in Production Structures and Efficiency: An Analysis of the Czech Food Processing Industry”, Pacific Economic Review, Vol. 22, No. 4, pp. 702-719. ISSN 1468-0106. DOI 10.1111/1468-0106.12217.
  13. Čechura, L. and Malá, Z. (2014) “Technology and Efficiency Comparison of Czech and Slovak Processing Companies”, Procedia Economics and Finance, Vol. 12, pp. 93-102, ISSN 2212-5671. DOI 10.1016/S2212-5671(14)00324-4.
  14. Färe, R. (1975) "Efficiency and the production function“, Journal of Economics, Vol. 35, No. 3, pp. 317-324. E-ISSN 1617-7134, ISSN 0931-8658. DOI 10.1007/BF01284619.
  15. Farrell, M. J. (1957) "The measurement of productive efficiency“, Journal of the Royal Statistical Society. Series A (General), Vol. 120, No. 3, pp. 253-290. DOI 10.2307/2343100.
  16. Ferto, I., Bakucz, Z., Bojnec, S. and Latruffe, L. (2012) "Investment and Financial Constraints in European Agriculture: Evidence from France, Hungary and Slovenia“, IEHAS Discussion Papers 1213. [Online]. Available: https://ideas.repec.org/p/ags/eaae11/114357.html [Accessed: 15 August, 2019].
  17. Forstner, B., Bergschmidt, A., Dirksmeyer, W., Ebers, H., Fitschen-Lischewski A., Margarian, A. and Heuer, J. (2009) "Ex-post evaluation of the German farm-investment support programme from 2000–2006“, Länderübergreifender Bericht 98, Thünen Institut, Braunschweig
  18. Greene, W. (2005) "Reconsidering heterogeneity in panel data estimators of the stochastic frontier mode“, Journal of Econometrics, Vol. 126, No. 2, pp. 269-303. ISSN 0304-4076. DOI 10.1016/j.jeconom.2004.05.003.
  19. Hurňáková, J., Bartová, L. and Fandel, P. (2016) “Efficiency and productivity of the Slovak agricultural investment support beneficiaries”, International Scientific Days 2016, The Agri-Food Value Chain: Challenges for Natural Resources Management and Society, June, 2016, pp. 923-930. ISBN 978-80-552-1503-7. DOI 10.15414/isd2016.s12.03.
  20. Jondrow, J., Lovell, C. K., Materov, I. S. and Schmidt, P. (1982) "On the estimation of technical inefficiency in the stochastic frontier production function model“, Journal of Econometrics, Vol. 19, No, 2-3, pp. 233-238. ISSN 0304-4076. DOI 10.1016/0304-4076(82)90004-5.
  21. Jorgenson, D. (1995) “Productivity: Postwar U.S. Economic Growth“. Cambridge: MIT Press. ISBN 9780262512893.
  22. Kumbhakar, S. C. and Knox Lovell, C.A. (2000) "Stochastic Frontier Analysis", Cambridge University Press, Cambridge. ISBN 978-0521666633. DOI 10.1017/CBO9781139174411.
  23. Mezera, J. and Špička, J. (2013) “Economic Effects of Investment Support of Adding Value to Food”, Agris on-line Papers in Economics and Informatics, Vol. 5, No.1, pp. 39-49. ISSN 1804-1930. DOI 10.22004/ag.econ.148102.
  24. Ministry of Industry and Trade Czech Republic (2017) "Panorama of the food industry". [Online]. Available: https://www.mpo.cz/assets/en/industry/manufacturing-industry/panorama-of-themanufacturing- industry/2018/9/Panorama-2017-en.pdf [Accessed: 10 Julz, 2019].
  25. Pires, J. O. and Garcia, F. (2012) "Productivity of nations: a stochastic frontier approach to TFP decomposition", Economics Research International, Vol. 2012, 19 p. DOI 10.1155/2012/584869.
  26. Ratinger, T., Medonos, T. and Hruska, M. (2014) "The Assessment of the effects of the investment support scheme in the Czech Republic“, Poster paper prepared for presentation at the EAAE 2014 Congress Agri-Food and Rural Innovations for Healthier Societies.
  27. Rudinskaya, T. and Náglová, Z. (2018) “Impact of Subsidies on Technical Efficiency of Meat Processing Companies”, AGRIS on-line Papers in Economics and Informatics, Vol. 10, No. 1, pp. 61-70. ISSN 1804-1930. DOI 10.7160/aol.2018.100106.
  28. Špička, J. and Machek, O. (2015) “Change in the production efficiency of European specialized milk farming”, Agricultural Economics, Vol. 61, No 1, pp. 1-13. E-ISSN 1805-9295, ISSN 0139-570X. DOI 10.17221/112/2014-AGRICECON.

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