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Türkiye Gıda Sanayinde Kısa ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi

Year 2016, Volume: 6 Issue: 2, 67 - 84, 01.09.2016

Abstract

Bu çalışmanın amacı Türk Gıda Sanayinde faaliyet gösteren firmaların teknik etkinsizlik düzeylerini tahmin etmek ve etkinsizliğin kalıcı olup olmadığını araştırmaktır. Bu amaç doğrultusunda çalışmada “Türk gıda sanayinde faaliyet gösteren firmaların teknik etkinsizliği kalıcıdır” ve “Uzun dönemde firmaların etkinlik düzeyleri birbirine yakınsamamaktadır” şeklinde iki hipotez kurulmuş ve test edilmiştir. Türkiye İstatistik Kurumu tarafından hazırlanan Yapısal İş İstatistikleri anketinin kullanıldığı çalışmada, 2003-2011 dönemi için Stokastik Sınır Fonksiyonu tahmin edilmiştir. Çalışma sonuçlarına göre, gıda sanayinde teknik etkinsizliğin kalıcı olduğu ve uzun dönemde firmaların etkinlik düzeylerinin birbirine yakınsamadığı tespit edilmiştir.

References

  • Aigner, D., Lovell, C. A. K., ve Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21–37. http://doi.org/10.1016/0304-4076(77)90052-5
  • Amadou, D. I. (2011). STOCKCAPIT: Stata module to calculate physical capital stock by the perpetual-inventory method. Statistical Software Components. http://ideas.repec.org/c/boc/bocode/s457270.html
  • Battese, G. E. (1992). Frontier Production Functions and technical efficiency - A Survey of empirical applications in agricultural-economics. Agricultural Economics, 7, 185–208. http://doi.org/10.1016/0169-5150(92)90049-5
  • Battese, G. E., ve Coelli, T. G. (1995). A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data. Empirical Economics, 20, 325–332. http://doi.org/10.1007/BF01205442
  • Battese, G. E., ve 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.http://doi.org/10.1007/BF00158774
  • Berlemann, M., ve Wesselhöft, J.-E. (2012). Estimating Aggregate Capital Stocks Using the Perpetual Inventory Method – New Empirical Evidence for 103 Countries. Helmet Schmidt Universitat - Working Paper No. 125, 1–37.
  • Cobb, C., ve Douglas, P. (1928). A Theory of Production. American Economic Association. http://doi.org/10.1515/humr.1998.11.2.161
  • Cornwell, C., Schmidt, P., ve Sickles, R. C. (1990). Production frontiers with cross-sectional and time-series variation in efficiency levels. Journal of Econometrics, 46(1-2), 185–200. http://doi.org/10.1016/0304-4076(90)90054-W
  • Dudu, H. ve Kiliçaslan, Y. (2009). Concentration, Profitability and (In)Efficiency in Large Scale Firms. Productivity, Efficiency, and Economic Growth in the Asia-Pacific Region Contributions to Economics. 39-58. Berlin: Springer.
  • Filippini, M., ve W. H. Greene. (2014). “Persistent and transient productive inefficiency: a aaximum simulated likelihood approach.” CER-ETH–Center of Economic Research at ETH Zurich Working Paper, (14/197).
  • Greene, W. (2005). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics, 126(2), 269–303. http://doi.org/10.1016/j.jeconom.2004.05.003
  • Haji H. S. (2013). Türkiye İmalat Sanayisinde Ölçek Etkisi: Stokastik Meta-Frontier Analizi. (Yayınlanmamış Doktora Tezi). İzmir: Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü.
  • Jondrow, J., Knox Lovell, C. A., Materov, I. S., ve Schmidt, P. (1982). On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics, 19(2-3), 233–238. http://doi.org/10.1016/0304-4076(82)90004-5
  • Kalirajan, K. P., & Shand, R. T. (1999). Frontier Production Functions and Technical Efficiency Measures. Journal of Economic Surveys, 13(2), 149–172. http://doi.org/10.1111/1467-6419.00080
  • Kodde, D. a, ve Palm, F. C. (1986). Wald Criteria for Jointly Testing Equality and Inequality Restrictions. Econometrica, 54(5), 1243–1248. http://doi.org/10.1017/S0305000911000122
  • Kök, R ve M. E. Yeşilyurt (2006) .İlk Beş Yüz İmalat Sanayi Kuruluşunun Etkinlik Analizi ve Sigma Yakınsaması-Türkiye Örneği: 1993-2000. İktisat İşletme ve Finans, 21(249), 46-60.
  • Kumbhakar, S. C. (1990). Production frontiers, panel data, and time-varying technical inefficiency. Journal of Econometrics, 46(1-2), 201–211. http://doi.org/10.1016/0304-4076(90)90055-X
  • Kumbhakar, S. C., ve Heshmati, A. (1995). Efficiency Measurement in Swedish Dairy Farms: An Application of Rotating Panel Data, 1976-88. American Journal of Agricultural Economics. August, 77(3), 660–674.
  • Kumbhakar, S. C., Lien, G., ve Hardaker, J. B. (2014). Technical efficiency in competing panel data models: a study of Norwegian grain farming. Journal of Productivity Analysis, 41(2), 321–337. http://doi.org/10.1007/s11123-012-0303-1
  • Kumbhakar, S. C., ve Wang, H.-J. (2005). Estimation of growth convergence using a stochastic production frontier approach. Economics Letters, 88(3), 300–305. http://doi.org/10.1016/j.econlet.2005.01.023
  • Kumbhakar, S.C., H-J. Wang ve A. P Horncastle (2015). A Practitioner’s Guide to Stochastic Frontier Analysis Using Stata, Cambridge University Press, N.Y.
  • Meeusen, W., ve Broeck., J. van Den. (1977). Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error. International Economic Review, 18(2), 435–444. http://doi.org/10.1080/00420986820080431
  • Pitt, M. M., ve Lee, L. F. (1981). The measurement and sources of technical inefficiency in the Indonesian weaving industry. Journal of Development Economics, 9(1), 43–64. http://doi.org/10.1016/0304-3878(81)90004-3
  • Radam, A., Yacob, M.R. & Kamarulzaman Shah, S.A. (2008). The Technical Efficiency of Food Industry in Malaysia: An Application of Stochastic Frontier Model. International Applied Economics and Management Letters, 1(1): 19-23.
  • Schmidt, P., ve Sickles, R. C. (1984). Production frontiers and panel data. Journal of Business and Economic Statistics. http://doi.org/10.2307/1391278
  • Şentürk, S.S. (2010). Total Factor Productivity Growth in Turkish Manufacturing Industries: A Malmquist Productivity Index Approach, Yayınlanmamış Master Tezi. Stockholm: KTH Economics of Innovation and Growth.
  • Wang, H. J., ve Ho, C. W. (2010). Estimating fixed-effect panel stochastic frontier models by model transformation. Journal of Econometrics, 157(2), 286–296. http://doi.org/10.1016/j.jeconom.2009.12.006
Year 2016, Volume: 6 Issue: 2, 67 - 84, 01.09.2016

Abstract

References

  • Aigner, D., Lovell, C. A. K., ve Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21–37. http://doi.org/10.1016/0304-4076(77)90052-5
  • Amadou, D. I. (2011). STOCKCAPIT: Stata module to calculate physical capital stock by the perpetual-inventory method. Statistical Software Components. http://ideas.repec.org/c/boc/bocode/s457270.html
  • Battese, G. E. (1992). Frontier Production Functions and technical efficiency - A Survey of empirical applications in agricultural-economics. Agricultural Economics, 7, 185–208. http://doi.org/10.1016/0169-5150(92)90049-5
  • Battese, G. E., ve Coelli, T. G. (1995). A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data. Empirical Economics, 20, 325–332. http://doi.org/10.1007/BF01205442
  • Battese, G. E., ve 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.http://doi.org/10.1007/BF00158774
  • Berlemann, M., ve Wesselhöft, J.-E. (2012). Estimating Aggregate Capital Stocks Using the Perpetual Inventory Method – New Empirical Evidence for 103 Countries. Helmet Schmidt Universitat - Working Paper No. 125, 1–37.
  • Cobb, C., ve Douglas, P. (1928). A Theory of Production. American Economic Association. http://doi.org/10.1515/humr.1998.11.2.161
  • Cornwell, C., Schmidt, P., ve Sickles, R. C. (1990). Production frontiers with cross-sectional and time-series variation in efficiency levels. Journal of Econometrics, 46(1-2), 185–200. http://doi.org/10.1016/0304-4076(90)90054-W
  • Dudu, H. ve Kiliçaslan, Y. (2009). Concentration, Profitability and (In)Efficiency in Large Scale Firms. Productivity, Efficiency, and Economic Growth in the Asia-Pacific Region Contributions to Economics. 39-58. Berlin: Springer.
  • Filippini, M., ve W. H. Greene. (2014). “Persistent and transient productive inefficiency: a aaximum simulated likelihood approach.” CER-ETH–Center of Economic Research at ETH Zurich Working Paper, (14/197).
  • Greene, W. (2005). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics, 126(2), 269–303. http://doi.org/10.1016/j.jeconom.2004.05.003
  • Haji H. S. (2013). Türkiye İmalat Sanayisinde Ölçek Etkisi: Stokastik Meta-Frontier Analizi. (Yayınlanmamış Doktora Tezi). İzmir: Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü.
  • Jondrow, J., Knox Lovell, C. A., Materov, I. S., ve Schmidt, P. (1982). On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics, 19(2-3), 233–238. http://doi.org/10.1016/0304-4076(82)90004-5
  • Kalirajan, K. P., & Shand, R. T. (1999). Frontier Production Functions and Technical Efficiency Measures. Journal of Economic Surveys, 13(2), 149–172. http://doi.org/10.1111/1467-6419.00080
  • Kodde, D. a, ve Palm, F. C. (1986). Wald Criteria for Jointly Testing Equality and Inequality Restrictions. Econometrica, 54(5), 1243–1248. http://doi.org/10.1017/S0305000911000122
  • Kök, R ve M. E. Yeşilyurt (2006) .İlk Beş Yüz İmalat Sanayi Kuruluşunun Etkinlik Analizi ve Sigma Yakınsaması-Türkiye Örneği: 1993-2000. İktisat İşletme ve Finans, 21(249), 46-60.
  • Kumbhakar, S. C. (1990). Production frontiers, panel data, and time-varying technical inefficiency. Journal of Econometrics, 46(1-2), 201–211. http://doi.org/10.1016/0304-4076(90)90055-X
  • Kumbhakar, S. C., ve Heshmati, A. (1995). Efficiency Measurement in Swedish Dairy Farms: An Application of Rotating Panel Data, 1976-88. American Journal of Agricultural Economics. August, 77(3), 660–674.
  • Kumbhakar, S. C., Lien, G., ve Hardaker, J. B. (2014). Technical efficiency in competing panel data models: a study of Norwegian grain farming. Journal of Productivity Analysis, 41(2), 321–337. http://doi.org/10.1007/s11123-012-0303-1
  • Kumbhakar, S. C., ve Wang, H.-J. (2005). Estimation of growth convergence using a stochastic production frontier approach. Economics Letters, 88(3), 300–305. http://doi.org/10.1016/j.econlet.2005.01.023
  • Kumbhakar, S.C., H-J. Wang ve A. P Horncastle (2015). A Practitioner’s Guide to Stochastic Frontier Analysis Using Stata, Cambridge University Press, N.Y.
  • Meeusen, W., ve Broeck., J. van Den. (1977). Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error. International Economic Review, 18(2), 435–444. http://doi.org/10.1080/00420986820080431
  • Pitt, M. M., ve Lee, L. F. (1981). The measurement and sources of technical inefficiency in the Indonesian weaving industry. Journal of Development Economics, 9(1), 43–64. http://doi.org/10.1016/0304-3878(81)90004-3
  • Radam, A., Yacob, M.R. & Kamarulzaman Shah, S.A. (2008). The Technical Efficiency of Food Industry in Malaysia: An Application of Stochastic Frontier Model. International Applied Economics and Management Letters, 1(1): 19-23.
  • Schmidt, P., ve Sickles, R. C. (1984). Production frontiers and panel data. Journal of Business and Economic Statistics. http://doi.org/10.2307/1391278
  • Şentürk, S.S. (2010). Total Factor Productivity Growth in Turkish Manufacturing Industries: A Malmquist Productivity Index Approach, Yayınlanmamış Master Tezi. Stockholm: KTH Economics of Innovation and Growth.
  • Wang, H. J., ve Ho, C. W. (2010). Estimating fixed-effect panel stochastic frontier models by model transformation. Journal of Econometrics, 157(2), 286–296. http://doi.org/10.1016/j.jeconom.2009.12.006
There are 27 citations in total.

Details

Journal Section Research Article
Authors

Mustafa Bilik

Üzeyir Aydın

Hakan Kahyaoğlu

Publication Date September 1, 2016
Published in Issue Year 2016 Volume: 6 Issue: 2

Cite

APA Bilik, M., Aydın, Ü., & Kahyaoğlu, H. (2016). Türkiye Gıda Sanayinde Kısa ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi. Çankırı Karatekin Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 6(2), 67-84.
AMA Bilik M, Aydın Ü, Kahyaoğlu H. Türkiye Gıda Sanayinde Kısa ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. September 2016;6(2):67-84.
Chicago Bilik, Mustafa, Üzeyir Aydın, and Hakan Kahyaoğlu. “Türkiye Gıda Sanayinde Kısa Ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi”. Çankırı Karatekin Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi 6, no. 2 (September 2016): 67-84.
EndNote Bilik M, Aydın Ü, Kahyaoğlu H (September 1, 2016) Türkiye Gıda Sanayinde Kısa ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 6 2 67–84.
IEEE M. Bilik, Ü. Aydın, and H. Kahyaoğlu, “Türkiye Gıda Sanayinde Kısa ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi”, Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, vol. 6, no. 2, pp. 67–84, 2016.
ISNAD Bilik, Mustafa et al. “Türkiye Gıda Sanayinde Kısa Ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi”. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 6/2 (September 2016), 67-84.
JAMA Bilik M, Aydın Ü, Kahyaoğlu H. Türkiye Gıda Sanayinde Kısa ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2016;6:67–84.
MLA Bilik, Mustafa et al. “Türkiye Gıda Sanayinde Kısa Ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi”. Çankırı Karatekin Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, vol. 6, no. 2, 2016, pp. 67-84.
Vancouver Bilik M, Aydın Ü, Kahyaoğlu H. Türkiye Gıda Sanayinde Kısa ve Uzun Dönemli Etkinlik: Stokastik Sınır Analizi. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2016;6(2):67-84.