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Technical Efficieny Analysis over the Liberalization Period of the Turkish Air Transportation Case: A Stochastic Frontier Method Application

Year 2014, Volume: 18 Issue: 2, 49 - 73, 01.12.2014

Abstract

Efficiency can be defined as the rate of approach to optimal values. Technical efficiency, defined by functional forms, is often used in performance evaluations. Stochastic frontier method has been widely applied because it makes econometric estimations possible. Our study carries out a stochastic frontier application on Turkish air transportation case. The period studied here is important for Turkish air transportation. The striking success of the global air transportation sector couldn’t be mentionable for the local sector in Turkey for the same period. On the other hand, deregulations have been started to be applied at the beginning of the new century. Inspection of this important period is, therefore, being evaluated as important to evaluate success of later developments. Despite some methodical and emprical statistical insufficiencies, the efficiency level of mentioned period as 57 % is evaluated that there were a lot to do in terms of improving the efficiency level of the sector. This last point also can be accepted as supporting argument for the previous evaluation on the period of the Turkish air transportation.

References

  • Afriat, S.N. (1972). “Efficiency estimation of production functions”, International Economic Review,13, 568-598
  • Aigner, D.J. and Chu S. (1968). ‘On Estimating the Industry Production Function’, American Economic Review, 58: 826-835.
  • Aigner, D.J., Lovell, C.A.K. and Schmidt, P. (1977). “Formulation and Estimation of Stochastic Frontier Production Function Models”, Journal of Econometrics, 6, 21- 37.
  • Battese, G.E. and Broca, S.S. (1997). “Functional Forms of Stochastic Frontier Production Functions and Models for Technical inefficiency Effects: A Comparative Study for Wheat Farmers in Pakistan”, Journal of Productivity Analysis, 8, 395-414.
  • Battese, G.E. and Coelli, T.J. (1988). “Prediction of Firm-Level Technical Efficiencies With a Generalised Frontier Production Function and Panel Data”, Journal of Econometrics, 38, 387-399.
  • Battese, G.E. and Coelli, T.J. (1991). “Frontier Production Functions, Technical Efficiency And Panel Data: With Application To Paddy Farmers In Indiaa”. Working Papers in Econometrics and Applied Statistics. No.56, Department of Econometrics, University of New England, Armidale.
  • 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, 153-169.
  • 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, 325-332.
  • Battese, G.E. and Corra, G.S. (1977). “Estimation of a Production Frontier Model: With Application to the Pastoral Zone of Eastern Australia”, Australian Journal of Agricultural Economics, 21, 169-179.
  • Berg, S.A., Forsund, F.R., Hjalmarsson, L. and Suominen, M. (1993). “Banking Efficiency in the Nordic Countries”. Journal of Banking & Finance. (17) 2-3, 371–388.
  • Coelli, T.J. 1996. "A Guide to Frontier Version 4.1. A Computer Program for Stochastic Frontier Production and Cost Function Estimation." Working Paper 7/96, CEPA- Centre for Efficiency and Productivity Analysis. University of New England.
  • Coelli, T.J., Grifell-Tatje, E. and Perelman, S. (2002). “Capacity Utilisation and Profitability: A Decomposition of Short-Run Profit Efficiency”, International Journal of Production Economics, 79(3), 261-78.
  • Coelli, T.J., Perelman, S. and Romano, E. (1999). “Accounting for environmental influences in stochastic frontier models: With application to international airlines”, Journal of Productivity Analysis, 11, 251-273.
  • Cornwell, C., Schmidt, P. and Sickles, R.C. (1990). “Production Frontiers with Cross- Sectional and Time-Series Variation in Efficiency Levels”, Journal of Econometrics, vol. 46, 185-200.
  • Cullinane, K., Song, D.W. and Wang, T. (2005). “The Application of Mathematical Programming Approaches to Estimating Container Port Production Efficiency”, Journal of Productivity Analysis, 24(1), 73-92.
  • Das, A., A. Nag and S.C. Ray (2009). “Labor-use Efficiency in Indian Banking: A Branch-level Analysis”. Omega, 37 (2009) 411-425.
  • Dodson, M.E. and Garrett, T.A. (2004). “Inefficient Education Spending in Public School Districts: A Case for Consolidation”. Contemporary Economic Policy, 22(2), 270-280.
  • Dolton, P., Marcenaro, O.D. and Navarro, L. (2003). “The Effective Use of Student Time: A Stochastic Frontier Production Function Case Study”. Economics of Education Review, 22(6), 547-560.
  • Duke, J. and Torres, V. (2005). “Multifactor Productivity Change in the Air Transportion Industry”. Monthly Labor Review, 25(8), 32-45.
  • EC, (2001). White Paper: Time to Decide, European Comission, Brussels.
  • Farrel, M. (1957). ‘The Measurement of Productive Efficiency’, Journal of the Royal Statistical Society, A120: 253-81.
  • Fried, H.O., Lovell, C.A.K. and Schmidt, P.(eds.) (2008). The Measurement of Productive Efficiency and Productivity Growth, Oxford University Press, New York
  • Foroughi, A.A., Jones, D.F. and Tamiz, M. (2005). “A Selection Method for a Preferential Election”. Applied Mathematics and Computation, 163(1), 107- 116.
  • Fuiji, A. (2001). “Determinants and probability distribution of inefficiency in the stochastic cost frontier in Japanese hospitals”. Applied Economics Letters, 8, 807-812.
  • Fuller, J.W. (1983). Regulation and Competition in Transportation. Center for Transportation Studies, University of British Columbia. Vancouver, Canada.
  • Geddes, R.R. (2010). The Road to Renewal: Private investment in US Transportation Infrastructure. American Enterprise Institute, Washington, DC.
  • Good, D.H., Nadiri, M.I. and Sickles, R.C. (1991). “The structure of production, technical change and efficiency in a mutinational industry: An application to U.S. airlines”, National Bureau of Economic Research, NBER Workin Paper No:3939.
  • Greene, W.H. (2008). “The Econometric Approach to Efficiency Analysis” in H.O Fried, C.A.K Lovell and S.S Schmidt (eds) The Measurement of Productive Efficiency and Productivity Growth, 92-251, Oxford University Press, New York.
  • ICAO, (2004). The World of Civil Aviation, 2001-2004, Circular 291-AT/123 (11/02 E/P1/1400), ICAO HQ, Montreal
  • Jondrow, J., Lovell, C.A.K., Materov, I.S. and Schmidt, P. (1982). “On estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model”, Journal of Econometrics, 19, 233-238.
  • Kneip A., Sickles R. C. and Song W. (2011). “A new panel data Treatment for heterogeneity in time: Forthcoming in Econometric Theory”. Working Paper. Rice University, Houston .
  • Kodde, D.A. and Palm, F.C. (1986). “Wald criteria for jointly testing equality and inequality restrictions”, Econometrica, 54, 1243-1248.
  • Kumbhakar, S.C. (1987a). “The specification of technical and allocative inefficiency in stochastic production and profit frontiers”, Journal of Econometricsl, 34, 335- 348.
  • Kumbhakar, S.C. (1987b). “Production Frontiers, Panel Data: An Application of U.S. Class 1 Railroad”, Journal of Business and Economic Statistics, 5 (2): 249-255.
  • Kumbhakar, S.C. (1990). “Production frontiers, panel data and time-varying technical inefficiency”, Journal of Econometricsl, 46:1/2 (October /November), 201-12.
  • Kumbhakar, S.C. and Lovel,C.A.K. (2000). Stochastic Frontier Analysis, Cambrige University Press, New York.
  • Lee, R.D. (2012). “Economic Efficiency”. FEE-Foundation for Economical Education. http://www.fee.org/the_freeman/detail/economic- efficiency/#axzz2F1VAFZw1. Erişim tarhi: 13/08/2012.
  • Mairesse, F. and Vanden-Eeckaut, P. (2002). “Museum Assesment and FDH Technology: Towards a Global Approach”. Journal of Cultural Economics, 26 (4), 261-286.
  • Nelson, J.C. (1942). New Concepts in Transportation Regulation. In Transportation and National Policy (197-237). US Government Printing Office. Washington, DC.
  • Nelson, J.C. (1947). Some Problems of Postwar Air Transportation. American Economic Review. 2 (37), 492-97.
  • Nelson, J.C. (1962a). The Pricing of Highway, Waterways and airways Facilities. American Economic Review. 2 (52), 15-22; 426-33.
  • Nelson, J.C. (1962b). Government’s Role Toward Transportation. Transportation Journal. 4 (1), 15-22.
  • Nelson, J.C. (1973). A Critic of Governmental Intervention in Transport. In Joseph S. De Salvo (ed.) Perspectives on Regional Transportation Planning. Lexington Books, Lexington. Massachussets.
  • Nelson, J.C. ve Heaver, T.D. (1977). Railway Pricing Under Commercial Freedom: The Canadian Experience. Center for Transportation Studies, University of British Columbia. Vancouver, Canada.
  • Nelson, J.C. (1981). British Deregulation and US Transport Policy. In Kenneth D. Boyer and William G. Sheherd (eds.) Economic Regulation: Essays in Honor of James R. Nelson. Michigan State University. East Lansing, Michigan.
  • Nelson, J.C. (1981). British Deregulation and US Transport Policy. In Kenneth D. Boyer and William G. Sheherd (eds.) Economic Regulation: Essays in Honor of James R. Nelson. Michigan State University. East Lansing, Michigan.
  • Marin, P.L. (1995). “Productivity differences in the airline industury: Partial deregulation versus short-run protection”, JEL Discussion Paper, No.EI/11, JEL Nos.:D24,L59,L23,L93.
  • Porembski, M., Breitenstein, K. and Alpar, P. (2005). “Visualising Efficiency and Reference Relations in Data Envelopment Analysis with an Application to the Branches of a German Bank”, Journal of Productivity Analysis, 23 (2), 203-21.
  • Ray, S.C. and Mukherje, K. (1996), “Decomposition of the Fisher ideal index of productivity: A non-parametric dual analysis of US Airlines Data, The Economic Journal, vol.106, no.439, 1659-1678.
  • Reichmann, G. and Sommersguter-Reichmann, M. (2006). “University Library Benchmarking: An International Comparison Using DEA”, International Journal of Production Economics, 100 (2), 131-147.
  • Richmond, J. (1974). “Estimating the efficiency of production”, International Economic Rewiev, 15, 515-521.
  • Scheraga, C.A. (2004). “Operational Efficiency Versus Financial Mobility in the Global Airline Industry: A Data Envelopment and Tobit Analysis”, Transportation Research Part, 38(5), 383-404.
  • Schmidt, P. (1976). “On the Statistical Estimation of Parametric Frontier Production Functions”, The Rewiev of Economics and Statistics, vol.58, issue 2, 238-239.
  • Schmidt, P. and Sickles R.C. (1984). “Production Frontiers and Panel Data”, Journal of Business & Economic Statistics, vol. 2, No. 4, 367-374.
  • Serrano-Cinca, C., Fuertes-Callen and Mar-Molinero, C. (2005). “Measuring DEA Efficiency in Internet Companies”, Decission Support System, 38 (4): 557-573.
  • Sena, V. (1999). “Stochastic Frontier Estimation: A Review of the Software Options”, Journal Of Applied Econometrics, 14 (3): 579-586.
  • Sickles, R.C. (1985). “A nonlinear multivariate error components analysis of technology and specific factor productivity growth with an application to the U.S. airlines”, Journal of Econometrics, 27, 61-78.
  • Sickles, R.C., Good, D. and Johnson, R.L. (1986). “Allocative distortions and the regulatory transition of the U.S. airline industry”, Journal of Econometrics, 33, 143-163.
  • Sickles, R.C., Good, D. and Geatchaw, L. (2002). “Specification of Distance Function Using Semi- and Non-parametric Methods with and Application to the Dynamic Performance of Eastern ans Western European Air Carriers”, Journal of Productivitiy Analysis, 17(1.2), 133-155.
  • Smith, P.C. and Street, A. (2005). “Measuring the efficiency of public services: the limits of analysis”. Journal of Royal Statistical Society. 168, 401-417.
  • Street, A. (2003). “How much condence should we place in efficiency estimates?” Health Economics, 12 (11), 895-907.
  • Takamura, Y. and Tone, K. (2003). “A Comparative Site Evaluation Study for Relocating Japanese Government Agencies Out of Tokyo”. Socio-economic Planning Science. 37(2), 85-102.
  • Thiam, A. et al. (2001). “Technical efficiency in developing country agriculture: a meta- analysis”. Agricultural Economics. 25, 235-243.
  • Timmer, C. (1971). “Using a Probabilistic Frontier Production Function to Measure Technical Efficiency”, Journal Of Political Economy, 79: 776-794.
  • Tsionas, E.and Christopoulos, D. (2001). “Efficiency measurement with nonstationary variables: an application of panel cointegration techniques”, Economic Bulletin, Vol.3, No.14, 1-7.
  • Tulkens, H. (1993). “On FDH Efficiency Analysis: Some Methodological Issues and Applications to Retail Banking, Courts and Urban Transit”, Journal of productivity Analysis, 4 (1/2), 183-210.
  • Weinstein, M.A. (1964). “The sum of values from a normal and truncated normal distrubution”, Technometrics, 6, 104-105 and 469-470.
  • Whitnah, D.R. (1998). US Department of Transportation. Greenwood Press, Westport CT, USA.
  • Zaim, O. (2004). “Measuring Environmental Performance of Government Manufacturing Through Changes in Pollution Intensities: DEA Framework”, Ecological Economics, 48 (1), 37-47.

Türk Havayolu Ulaştırmasının Açılım Dönemine Yönelik Teknik Etkinlik Analizi: Bir Stokastik Sınır Yöntemi Uygulaması

Year 2014, Volume: 18 Issue: 2, 49 - 73, 01.12.2014

Abstract

Etkinlik genel anlamda ideal seviyeleye yaklaşma oranı olarak tanımlanabilir. Teknik etkinliğin fonksiyonlar üzerinden tanımlanması, onun performans ölçümlerinde sıkça kullanılmasına neden olmaktadır. Stokastik sınır yöntemi de, etkinlik ölçümlerinin ekonometrik yöntemlerle tahminini sağladığından oldukça ilgi görmüştür. Çalışmamızda, stokastik sınır yöntemi kullanılarak, Türk hava ulaştırmasına yönelik bir etkinlik analizi ele alınmaktadır. Ele alınan dönem, Türk hava ulaştırması için önem taşımaktadır. Geçen yüzyılın ikinci yarısında sektörün dünyadaki çarpıcı başarısının aynı dönemde Türkiye’de görülemediği, buna karşın yeni yüzyılın başında gecikmeli olarak açılım hamlelerinin uygulamaya konulduğu bu dönemin incelemesinin daha sonraki süreçte elde edilen ilerlemenin değerlendirilmesinde oldukça önemli olacağı düşünülmektedir. Tahminler sonunda % 57 seviyelerindeki teknik etkinlik değerlerinin, çalışmamızda tespit edilen kurumsal ve istatistiksel yetersizlikler dolayısıyla kardinal bir değerlendirmeye çok uygun olmamasına karşın, ordinal düzeyde etkinlik açısından oldukça yol alınabileceğini gösterdiğini, bu anlamda söz konusu döneme ilişkin ilk saptamayı desteklediğini söylemek mümkündür.

References

  • Afriat, S.N. (1972). “Efficiency estimation of production functions”, International Economic Review,13, 568-598
  • Aigner, D.J. and Chu S. (1968). ‘On Estimating the Industry Production Function’, American Economic Review, 58: 826-835.
  • Aigner, D.J., Lovell, C.A.K. and Schmidt, P. (1977). “Formulation and Estimation of Stochastic Frontier Production Function Models”, Journal of Econometrics, 6, 21- 37.
  • Battese, G.E. and Broca, S.S. (1997). “Functional Forms of Stochastic Frontier Production Functions and Models for Technical inefficiency Effects: A Comparative Study for Wheat Farmers in Pakistan”, Journal of Productivity Analysis, 8, 395-414.
  • Battese, G.E. and Coelli, T.J. (1988). “Prediction of Firm-Level Technical Efficiencies With a Generalised Frontier Production Function and Panel Data”, Journal of Econometrics, 38, 387-399.
  • Battese, G.E. and Coelli, T.J. (1991). “Frontier Production Functions, Technical Efficiency And Panel Data: With Application To Paddy Farmers In Indiaa”. Working Papers in Econometrics and Applied Statistics. No.56, Department of Econometrics, University of New England, Armidale.
  • 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, 153-169.
  • 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, 325-332.
  • Battese, G.E. and Corra, G.S. (1977). “Estimation of a Production Frontier Model: With Application to the Pastoral Zone of Eastern Australia”, Australian Journal of Agricultural Economics, 21, 169-179.
  • Berg, S.A., Forsund, F.R., Hjalmarsson, L. and Suominen, M. (1993). “Banking Efficiency in the Nordic Countries”. Journal of Banking & Finance. (17) 2-3, 371–388.
  • Coelli, T.J. 1996. "A Guide to Frontier Version 4.1. A Computer Program for Stochastic Frontier Production and Cost Function Estimation." Working Paper 7/96, CEPA- Centre for Efficiency and Productivity Analysis. University of New England.
  • Coelli, T.J., Grifell-Tatje, E. and Perelman, S. (2002). “Capacity Utilisation and Profitability: A Decomposition of Short-Run Profit Efficiency”, International Journal of Production Economics, 79(3), 261-78.
  • Coelli, T.J., Perelman, S. and Romano, E. (1999). “Accounting for environmental influences in stochastic frontier models: With application to international airlines”, Journal of Productivity Analysis, 11, 251-273.
  • Cornwell, C., Schmidt, P. and Sickles, R.C. (1990). “Production Frontiers with Cross- Sectional and Time-Series Variation in Efficiency Levels”, Journal of Econometrics, vol. 46, 185-200.
  • Cullinane, K., Song, D.W. and Wang, T. (2005). “The Application of Mathematical Programming Approaches to Estimating Container Port Production Efficiency”, Journal of Productivity Analysis, 24(1), 73-92.
  • Das, A., A. Nag and S.C. Ray (2009). “Labor-use Efficiency in Indian Banking: A Branch-level Analysis”. Omega, 37 (2009) 411-425.
  • Dodson, M.E. and Garrett, T.A. (2004). “Inefficient Education Spending in Public School Districts: A Case for Consolidation”. Contemporary Economic Policy, 22(2), 270-280.
  • Dolton, P., Marcenaro, O.D. and Navarro, L. (2003). “The Effective Use of Student Time: A Stochastic Frontier Production Function Case Study”. Economics of Education Review, 22(6), 547-560.
  • Duke, J. and Torres, V. (2005). “Multifactor Productivity Change in the Air Transportion Industry”. Monthly Labor Review, 25(8), 32-45.
  • EC, (2001). White Paper: Time to Decide, European Comission, Brussels.
  • Farrel, M. (1957). ‘The Measurement of Productive Efficiency’, Journal of the Royal Statistical Society, A120: 253-81.
  • Fried, H.O., Lovell, C.A.K. and Schmidt, P.(eds.) (2008). The Measurement of Productive Efficiency and Productivity Growth, Oxford University Press, New York
  • Foroughi, A.A., Jones, D.F. and Tamiz, M. (2005). “A Selection Method for a Preferential Election”. Applied Mathematics and Computation, 163(1), 107- 116.
  • Fuiji, A. (2001). “Determinants and probability distribution of inefficiency in the stochastic cost frontier in Japanese hospitals”. Applied Economics Letters, 8, 807-812.
  • Fuller, J.W. (1983). Regulation and Competition in Transportation. Center for Transportation Studies, University of British Columbia. Vancouver, Canada.
  • Geddes, R.R. (2010). The Road to Renewal: Private investment in US Transportation Infrastructure. American Enterprise Institute, Washington, DC.
  • Good, D.H., Nadiri, M.I. and Sickles, R.C. (1991). “The structure of production, technical change and efficiency in a mutinational industry: An application to U.S. airlines”, National Bureau of Economic Research, NBER Workin Paper No:3939.
  • Greene, W.H. (2008). “The Econometric Approach to Efficiency Analysis” in H.O Fried, C.A.K Lovell and S.S Schmidt (eds) The Measurement of Productive Efficiency and Productivity Growth, 92-251, Oxford University Press, New York.
  • ICAO, (2004). The World of Civil Aviation, 2001-2004, Circular 291-AT/123 (11/02 E/P1/1400), ICAO HQ, Montreal
  • Jondrow, J., Lovell, C.A.K., Materov, I.S. and Schmidt, P. (1982). “On estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model”, Journal of Econometrics, 19, 233-238.
  • Kneip A., Sickles R. C. and Song W. (2011). “A new panel data Treatment for heterogeneity in time: Forthcoming in Econometric Theory”. Working Paper. Rice University, Houston .
  • Kodde, D.A. and Palm, F.C. (1986). “Wald criteria for jointly testing equality and inequality restrictions”, Econometrica, 54, 1243-1248.
  • Kumbhakar, S.C. (1987a). “The specification of technical and allocative inefficiency in stochastic production and profit frontiers”, Journal of Econometricsl, 34, 335- 348.
  • Kumbhakar, S.C. (1987b). “Production Frontiers, Panel Data: An Application of U.S. Class 1 Railroad”, Journal of Business and Economic Statistics, 5 (2): 249-255.
  • Kumbhakar, S.C. (1990). “Production frontiers, panel data and time-varying technical inefficiency”, Journal of Econometricsl, 46:1/2 (October /November), 201-12.
  • Kumbhakar, S.C. and Lovel,C.A.K. (2000). Stochastic Frontier Analysis, Cambrige University Press, New York.
  • Lee, R.D. (2012). “Economic Efficiency”. FEE-Foundation for Economical Education. http://www.fee.org/the_freeman/detail/economic- efficiency/#axzz2F1VAFZw1. Erişim tarhi: 13/08/2012.
  • Mairesse, F. and Vanden-Eeckaut, P. (2002). “Museum Assesment and FDH Technology: Towards a Global Approach”. Journal of Cultural Economics, 26 (4), 261-286.
  • Nelson, J.C. (1942). New Concepts in Transportation Regulation. In Transportation and National Policy (197-237). US Government Printing Office. Washington, DC.
  • Nelson, J.C. (1947). Some Problems of Postwar Air Transportation. American Economic Review. 2 (37), 492-97.
  • Nelson, J.C. (1962a). The Pricing of Highway, Waterways and airways Facilities. American Economic Review. 2 (52), 15-22; 426-33.
  • Nelson, J.C. (1962b). Government’s Role Toward Transportation. Transportation Journal. 4 (1), 15-22.
  • Nelson, J.C. (1973). A Critic of Governmental Intervention in Transport. In Joseph S. De Salvo (ed.) Perspectives on Regional Transportation Planning. Lexington Books, Lexington. Massachussets.
  • Nelson, J.C. ve Heaver, T.D. (1977). Railway Pricing Under Commercial Freedom: The Canadian Experience. Center for Transportation Studies, University of British Columbia. Vancouver, Canada.
  • Nelson, J.C. (1981). British Deregulation and US Transport Policy. In Kenneth D. Boyer and William G. Sheherd (eds.) Economic Regulation: Essays in Honor of James R. Nelson. Michigan State University. East Lansing, Michigan.
  • Nelson, J.C. (1981). British Deregulation and US Transport Policy. In Kenneth D. Boyer and William G. Sheherd (eds.) Economic Regulation: Essays in Honor of James R. Nelson. Michigan State University. East Lansing, Michigan.
  • Marin, P.L. (1995). “Productivity differences in the airline industury: Partial deregulation versus short-run protection”, JEL Discussion Paper, No.EI/11, JEL Nos.:D24,L59,L23,L93.
  • Porembski, M., Breitenstein, K. and Alpar, P. (2005). “Visualising Efficiency and Reference Relations in Data Envelopment Analysis with an Application to the Branches of a German Bank”, Journal of Productivity Analysis, 23 (2), 203-21.
  • Ray, S.C. and Mukherje, K. (1996), “Decomposition of the Fisher ideal index of productivity: A non-parametric dual analysis of US Airlines Data, The Economic Journal, vol.106, no.439, 1659-1678.
  • Reichmann, G. and Sommersguter-Reichmann, M. (2006). “University Library Benchmarking: An International Comparison Using DEA”, International Journal of Production Economics, 100 (2), 131-147.
  • Richmond, J. (1974). “Estimating the efficiency of production”, International Economic Rewiev, 15, 515-521.
  • Scheraga, C.A. (2004). “Operational Efficiency Versus Financial Mobility in the Global Airline Industry: A Data Envelopment and Tobit Analysis”, Transportation Research Part, 38(5), 383-404.
  • Schmidt, P. (1976). “On the Statistical Estimation of Parametric Frontier Production Functions”, The Rewiev of Economics and Statistics, vol.58, issue 2, 238-239.
  • Schmidt, P. and Sickles R.C. (1984). “Production Frontiers and Panel Data”, Journal of Business & Economic Statistics, vol. 2, No. 4, 367-374.
  • Serrano-Cinca, C., Fuertes-Callen and Mar-Molinero, C. (2005). “Measuring DEA Efficiency in Internet Companies”, Decission Support System, 38 (4): 557-573.
  • Sena, V. (1999). “Stochastic Frontier Estimation: A Review of the Software Options”, Journal Of Applied Econometrics, 14 (3): 579-586.
  • Sickles, R.C. (1985). “A nonlinear multivariate error components analysis of technology and specific factor productivity growth with an application to the U.S. airlines”, Journal of Econometrics, 27, 61-78.
  • Sickles, R.C., Good, D. and Johnson, R.L. (1986). “Allocative distortions and the regulatory transition of the U.S. airline industry”, Journal of Econometrics, 33, 143-163.
  • Sickles, R.C., Good, D. and Geatchaw, L. (2002). “Specification of Distance Function Using Semi- and Non-parametric Methods with and Application to the Dynamic Performance of Eastern ans Western European Air Carriers”, Journal of Productivitiy Analysis, 17(1.2), 133-155.
  • Smith, P.C. and Street, A. (2005). “Measuring the efficiency of public services: the limits of analysis”. Journal of Royal Statistical Society. 168, 401-417.
  • Street, A. (2003). “How much condence should we place in efficiency estimates?” Health Economics, 12 (11), 895-907.
  • Takamura, Y. and Tone, K. (2003). “A Comparative Site Evaluation Study for Relocating Japanese Government Agencies Out of Tokyo”. Socio-economic Planning Science. 37(2), 85-102.
  • Thiam, A. et al. (2001). “Technical efficiency in developing country agriculture: a meta- analysis”. Agricultural Economics. 25, 235-243.
  • Timmer, C. (1971). “Using a Probabilistic Frontier Production Function to Measure Technical Efficiency”, Journal Of Political Economy, 79: 776-794.
  • Tsionas, E.and Christopoulos, D. (2001). “Efficiency measurement with nonstationary variables: an application of panel cointegration techniques”, Economic Bulletin, Vol.3, No.14, 1-7.
  • Tulkens, H. (1993). “On FDH Efficiency Analysis: Some Methodological Issues and Applications to Retail Banking, Courts and Urban Transit”, Journal of productivity Analysis, 4 (1/2), 183-210.
  • Weinstein, M.A. (1964). “The sum of values from a normal and truncated normal distrubution”, Technometrics, 6, 104-105 and 469-470.
  • Whitnah, D.R. (1998). US Department of Transportation. Greenwood Press, Westport CT, USA.
  • Zaim, O. (2004). “Measuring Environmental Performance of Government Manufacturing Through Changes in Pollution Intensities: DEA Framework”, Ecological Economics, 48 (1), 37-47.
There are 69 citations in total.

Details

Primary Language Turkish
Journal Section Research Articles
Authors

Onur Tutulmaz This is me

Hasan Şahin This is me

Publication Date December 1, 2014
Submission Date August 11, 2015
Published in Issue Year 2014 Volume: 18 Issue: 2

Cite

APA Tutulmaz, O., & Şahin, H. (2014). Türk Havayolu Ulaştırmasının Açılım Dönemine Yönelik Teknik Etkinlik Analizi: Bir Stokastik Sınır Yöntemi Uygulaması. Çukurova Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 18(2), 49-73.