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Türkiye Doğal Gaz Dağıtım Firmalarının Etkinliğinin Stokastik Sınır Analiziyle Ölçülmesi

Year 2021, Volume 29, Issue 49, 131 - 150, 30.07.2021
https://doi.org/10.17233/sosyoekonomi.2021.03.07

Abstract

Gelir esnekliği düşük, firmalar için ara mal, hane halkları için nihai mal durumundaki doğal gazın ülke içinde dağıtımının ve kullanımının optimal gerçekleştirilmesi gerekmektedir. Bu gereklilikten hareketle, ilgili ekonomik birimlere doğal gazın ulaştırılmasında sorumluluğu üstlenen dağıtım firmalarının ne kadar etkin (ya da etkinsiz) çalıştığını ölçmek, bu çalışmanın amacını oluşturmaktadır. Bu amaç çerçevesinde, 2013-2018 yıllarını içeren dönemde Türkiye içinde faaliyet gösteren 63 doğal gaz dağıtım firmasının etkinliği Stokastik Sınır Analizi (SFA) yöntemiyle ölçülmektedir. Analiz sonuçlarına göre; hiçbir firmanın tam etkinlikte çalışamadığı, Bursa Şehir İçi Doğal Gaz Dağıtım firmasının en yüksek etkinliğe, Aksa Çanakkale Doğal Gaz Dağıtım firmasının ise en düşük etkinliğe sahip olduğu sonucuna ulaşılmaktadır. Bulgular; etkinsizliğin, ölçüm hatalarından çok, teknik etkinsizlikten kaynaklandığını ve firmaların ölçeğe göre artan getiride çalıştıklarını göstermektedir.

References

  • Aigner, D. & C.A.K. Lovell & P. Schmidt (1977), “Formulation and Estimation of Stochastic Frontier Production Function Models”, Journal of Econometrics, 6 /North-Holland Publishing Firm: 20-37.
  • Akalın, H. & S.U. Seçkiner & Y. Eroğlu (2017), “Stokastik Sınır Analizi Kullanarak Rüzgar Türbinleri İçin Etkinlik Değerlendirmesi”, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 32(4), 1311-1326.
  • Amirteimoori, A.R. & K. Shahroodi & S.F. Mahmoodkiani (2015), “Network Data Envelopment Analysis: Application to Gas Companies in Iran”, International Journal of Applied Operational Research, 5(1), 1-16.
  • Avcı, T. & A. Çağlar (2016), “Stokastik Sınır Analizi: İstanbul Sanayi Odası’na Kayıtlı Firmalara Yönelik Bir Uygulama”, Siyaset, Ekonomi ve Yönetim Araştırmaları Dergisi, 4(2), 17-57.
  • Battese, G. & G. Corra (1977), “Estimation of A Production Frontier Model with The Application of The Pastoral Zone of Easter Australia”, Australian Journal of Agricultural Economics, 21(3), 167-179.
  • Battese, G. & T.J. Coelli (1995), “A Model For Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data”, Empirical Economics, 20(2), 325-32.
  • Belotti, F. & S. Daidone & G. Ilardi & V. Atella (2013), “Stochastic Frontier Analysis Using Stata”, Stata Journal, 13(4), 718-758.
  • Carrington, R. & T.J. Coelli & E. Groom (2002), “International Benchmarking for Monopoly Price Regulation: The Case of Australian Gas Distribution”, Journal of Regulatory Economics, 21(2), 191-216.
  • Coelli, T.J. & J.O. Christopher & D.S.P. Rao & G.E. Battese (1998), An Introduction to Efficiency and Productivity Analysis, Kluwer Publication, Boston.
  • Coelli, T.J. (1995), “Recent Developments in Frontier Modelling and Efficiency Measurement”, Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, 39(3), 1-27.
  • Demir, M.A. & M. Bilik (2018), “Türkiye’nin Ticaret Etkinliği: Stokastik Sınır Çekim Modeli Yaklaşımı”, Academic Review of Economics & Administrative Sciences, 11(1), 29-48.
  • EPDK (2018), “Turkish Natural Gas Market”, Report, <https://www.epdk.org.tr/Detay/Icerik/3-0-94/dogal-gazyillik-sektor-raporu>, 10.02.2020.
  • EPDK (N/A), <https://www.epdk.org.tr/Detay/Icerik/3-0-94/dogal-gazyillik-sektor-raporu>, 10.02.2020.
  • Erbetta, F. & L. Rappuoli (2003), “Estimating Optimal Scale and Technical Efficiency in The Italian Gas Distribution Industry”, Higher Education and Research on Mobility Regulation and The Economics of Local Services Working Paper, 6, 2-19.
  • Ertürk, M. & S. Türüt-Aşık (2011), “Efficiency Analysis Of Turkish Natural Gas Distribution Companies By Using Data Envelopment Analysis Method”, Energy Policy, 39(3), 1426-1438.
  • Farsi, M. & M. Filippini & M. Kuenzle (2007), “Cost Efficiency in the Swiss Gas Distribution Sector”, Energy Economics, 29(1), 64-78.
  • Filippini, M. & L. Orea (2014), “Applications of The Stochastic Frontier Approach in Energy Economics”, Economics and Business Letters, 3(1), 35-42.
  • Haney, A. & P. Michael (2009), “Efficiency analysis of energy networks: An international survey of regulators”, Energy Policy, 37(12), 5814-5830.
  • Hawdon, D. (2003), “Efficiency, performance and regulation of the international gas industry - a bootstrap DEA approach”, Energy Policy, 31(11), 1167-1178.
  • Hünerli, Ö.C. & Ü. Aydın (2019), “Türkiye’de Faaliyet Gösteren Doğal Gaz Dağıtım Firmalarının Veri Zarflama Analizi Yöntemiyle Etkinliğinin Araştırılması”, Journal of Yasar University, 14(Special Issue), 133-146.
  • Jamasb. T. & M. Pollitt (2003), “International Benchmarking and Regulation: An Application to European Electricity Distribution Utilities”, Energy Policy, 31(15), 1609-1622.
  • Kim, T.Y. & J.D. Lee & Y.H. Park & B. Kim (1999), “International Comparisons of Productivity and its Determinants in the Natural Gas Industry”, Energy Economics, 21, 273-293.
  • Kodde, D.A. & F.C. Palm (1986), “Wald Criteria for Jointly Testing Equality and Inequality Restrictions”, Econometrica, 54, 1243-1248.
  • Kök, R. & E. Deliktaş (2003), Endüstri İktisadında Verimlilik Ölçme ve Strateji Geliştirme Teknikleri, Dokuz Eylül Üniversitesi İİBF Yayını, 19, 1. Baskı, İzmir.
  • Kumbhakar, S.C. & H-J. Wang & A.P. Horncastle (2015), A Practitioner’s Guide to Stochastic Frontier Analysis Using Stata, Cambridge University Press, N.Y.
  • Levin, H. (1974), “Measuring Efficiency in Educational Production”, Public Finance Quarterly, 2(1), 3-24.
  • Marques, V. et al. (2011), “What Drives Efficiency on the Portuguese Gas Distribution?”, Conference Paper, May 2012, DOI: 10.1109/EEM.2012.625474417-25.
  • Martin-Gamboa, M. & D. Iribarren & J. Dufour (2017), “Environmental Impact Efficiency of Natural Gas Combined Cycle Power Plants: A Combined Life Cycle Assessment and Dynamic Data Envelopment Analysis Approach”, The Science of the Total Environment, 615, 29-37.
  • Meeusen, W. & J. van den Broeck (1977), “Efficiency Estimation from Cobb-Douglas Production Functions With Composed Error”, International Economic Review, 18, 435-444.
  • Ojaraida. L. & O. Iledare & A. Idowu (2019), “Data Envelopment Analysis DEA of Natural Gas Utilization in Nigeria”, SPE Nigeria Annual International Conference and Exhibition, 5-7, August, Lagos, Nigeria.
  • Oliveira, L.S.M. & T.C.V.D. Correira & J.C.C.B.S. de Mello (2014), “Data Envelopment Analysis Applied to Evaluate the Usage of Oil and Natural Gas: South America Case”, Proceedings of the International Conference on Operational Research on Development ICORD VI, Fortelenza, Brazil, 487-495.
  • Öztürk, Z. & M.S. Yıldız (2016), “Hastane Etkinliklerinin Tahmininde Stokastik Sınır Analizi: Tarihi ve Ampirik Uygulamaları”, Uluslararası Sağlık Yönetimi ve Stratejileri Araştırma Dergisi, 1(3), 1-12.
  • Richmond, J. (1974), “Estimating the Efficiency of Production”, International Economic Review, 15(2), 515-21.
  • Storto, C. lo. (2014), “Gas Distribution in Italy: A Non-Parametric Analysis of Companies Operational Efficiency”, Advanced Material Research, Vol. 838-841, Trans Tech. Publication Switzerland: 1972-1978.
  • TPAO (N/A), <http://www.tpao.gov.tr/?mod=sektore-dair>, 10.02.2020.
  • Vikas & Bansal R. (2019) “Efficiency Evaluation of Indian Oil and Gas Sector: Data Envelopment Analysis”, International Journal of Emerging Markets, 14(2), 362-378.
  • Winsten, C. (1957), “Discussion of Mr. Farrell’s Paper”, Journal of the Statistical Society, Series A, General, 120, 282-284.
  • Yanes, L. (2013), “Stochastic Frontier Estimation for Gas Transmission Pipelines (Australia and United States Data)”, Acil Allen Consulting Dampier to Bunbury Pipeline. 19 September: 14.
  • Zorić, J. & N. Hrovatin & G.C. Scarsi (2009), “Gas Distribution Benchmarking of Utilities from Slovenia, The Netherlands and The United Kingdom: An Application of Data Envelopment Analysis”, South East European Journal of Economics and Business, 4(1), 113-124.

Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis

Year 2021, Volume 29, Issue 49, 131 - 150, 30.07.2021
https://doi.org/10.17233/sosyoekonomi.2021.03.07

Abstract

Natural gas should be distributed and consumed optimally in a given country since it is an important intermediate good for producers and a necessary final good for households with a low-income elasticity. Thus, this study aims to measure the efficiency of natural gas distribution companies responsible for delivering natural gas to economic units. The efficiency of 63 natural gas distribution companies operating in Turkey is estimated by the Stochastic Frontier Analysis method for 2013-2018. According to the findings, it is found that no firm operates within full efficiency. It is also concluded that while Bursa Natural Gas Distribution firm has the highest efficiency, Aksa Çanakkale Natural Gas Distribution firm has the lowest efficiency for the period studied. The findings show that inefficiency mainly stems from technical inefficiency rather than measurement errors and that natural gas distribution firms experience increasing returns to scale.

References

  • Aigner, D. & C.A.K. Lovell & P. Schmidt (1977), “Formulation and Estimation of Stochastic Frontier Production Function Models”, Journal of Econometrics, 6 /North-Holland Publishing Firm: 20-37.
  • Akalın, H. & S.U. Seçkiner & Y. Eroğlu (2017), “Stokastik Sınır Analizi Kullanarak Rüzgar Türbinleri İçin Etkinlik Değerlendirmesi”, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 32(4), 1311-1326.
  • Amirteimoori, A.R. & K. Shahroodi & S.F. Mahmoodkiani (2015), “Network Data Envelopment Analysis: Application to Gas Companies in Iran”, International Journal of Applied Operational Research, 5(1), 1-16.
  • Avcı, T. & A. Çağlar (2016), “Stokastik Sınır Analizi: İstanbul Sanayi Odası’na Kayıtlı Firmalara Yönelik Bir Uygulama”, Siyaset, Ekonomi ve Yönetim Araştırmaları Dergisi, 4(2), 17-57.
  • Battese, G. & G. Corra (1977), “Estimation of A Production Frontier Model with The Application of The Pastoral Zone of Easter Australia”, Australian Journal of Agricultural Economics, 21(3), 167-179.
  • Battese, G. & T.J. Coelli (1995), “A Model For Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data”, Empirical Economics, 20(2), 325-32.
  • Belotti, F. & S. Daidone & G. Ilardi & V. Atella (2013), “Stochastic Frontier Analysis Using Stata”, Stata Journal, 13(4), 718-758.
  • Carrington, R. & T.J. Coelli & E. Groom (2002), “International Benchmarking for Monopoly Price Regulation: The Case of Australian Gas Distribution”, Journal of Regulatory Economics, 21(2), 191-216.
  • Coelli, T.J. & J.O. Christopher & D.S.P. Rao & G.E. Battese (1998), An Introduction to Efficiency and Productivity Analysis, Kluwer Publication, Boston.
  • Coelli, T.J. (1995), “Recent Developments in Frontier Modelling and Efficiency Measurement”, Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, 39(3), 1-27.
  • Demir, M.A. & M. Bilik (2018), “Türkiye’nin Ticaret Etkinliği: Stokastik Sınır Çekim Modeli Yaklaşımı”, Academic Review of Economics & Administrative Sciences, 11(1), 29-48.
  • EPDK (2018), “Turkish Natural Gas Market”, Report, <https://www.epdk.org.tr/Detay/Icerik/3-0-94/dogal-gazyillik-sektor-raporu>, 10.02.2020.
  • EPDK (N/A), <https://www.epdk.org.tr/Detay/Icerik/3-0-94/dogal-gazyillik-sektor-raporu>, 10.02.2020.
  • Erbetta, F. & L. Rappuoli (2003), “Estimating Optimal Scale and Technical Efficiency in The Italian Gas Distribution Industry”, Higher Education and Research on Mobility Regulation and The Economics of Local Services Working Paper, 6, 2-19.
  • Ertürk, M. & S. Türüt-Aşık (2011), “Efficiency Analysis Of Turkish Natural Gas Distribution Companies By Using Data Envelopment Analysis Method”, Energy Policy, 39(3), 1426-1438.
  • Farsi, M. & M. Filippini & M. Kuenzle (2007), “Cost Efficiency in the Swiss Gas Distribution Sector”, Energy Economics, 29(1), 64-78.
  • Filippini, M. & L. Orea (2014), “Applications of The Stochastic Frontier Approach in Energy Economics”, Economics and Business Letters, 3(1), 35-42.
  • Haney, A. & P. Michael (2009), “Efficiency analysis of energy networks: An international survey of regulators”, Energy Policy, 37(12), 5814-5830.
  • Hawdon, D. (2003), “Efficiency, performance and regulation of the international gas industry - a bootstrap DEA approach”, Energy Policy, 31(11), 1167-1178.
  • Hünerli, Ö.C. & Ü. Aydın (2019), “Türkiye’de Faaliyet Gösteren Doğal Gaz Dağıtım Firmalarının Veri Zarflama Analizi Yöntemiyle Etkinliğinin Araştırılması”, Journal of Yasar University, 14(Special Issue), 133-146.
  • Jamasb. T. & M. Pollitt (2003), “International Benchmarking and Regulation: An Application to European Electricity Distribution Utilities”, Energy Policy, 31(15), 1609-1622.
  • Kim, T.Y. & J.D. Lee & Y.H. Park & B. Kim (1999), “International Comparisons of Productivity and its Determinants in the Natural Gas Industry”, Energy Economics, 21, 273-293.
  • Kodde, D.A. & F.C. Palm (1986), “Wald Criteria for Jointly Testing Equality and Inequality Restrictions”, Econometrica, 54, 1243-1248.
  • Kök, R. & E. Deliktaş (2003), Endüstri İktisadında Verimlilik Ölçme ve Strateji Geliştirme Teknikleri, Dokuz Eylül Üniversitesi İİBF Yayını, 19, 1. Baskı, İzmir.
  • Kumbhakar, S.C. & H-J. Wang & A.P. Horncastle (2015), A Practitioner’s Guide to Stochastic Frontier Analysis Using Stata, Cambridge University Press, N.Y.
  • Levin, H. (1974), “Measuring Efficiency in Educational Production”, Public Finance Quarterly, 2(1), 3-24.
  • Marques, V. et al. (2011), “What Drives Efficiency on the Portuguese Gas Distribution?”, Conference Paper, May 2012, DOI: 10.1109/EEM.2012.625474417-25.
  • Martin-Gamboa, M. & D. Iribarren & J. Dufour (2017), “Environmental Impact Efficiency of Natural Gas Combined Cycle Power Plants: A Combined Life Cycle Assessment and Dynamic Data Envelopment Analysis Approach”, The Science of the Total Environment, 615, 29-37.
  • Meeusen, W. & J. van den Broeck (1977), “Efficiency Estimation from Cobb-Douglas Production Functions With Composed Error”, International Economic Review, 18, 435-444.
  • Ojaraida. L. & O. Iledare & A. Idowu (2019), “Data Envelopment Analysis DEA of Natural Gas Utilization in Nigeria”, SPE Nigeria Annual International Conference and Exhibition, 5-7, August, Lagos, Nigeria.
  • Oliveira, L.S.M. & T.C.V.D. Correira & J.C.C.B.S. de Mello (2014), “Data Envelopment Analysis Applied to Evaluate the Usage of Oil and Natural Gas: South America Case”, Proceedings of the International Conference on Operational Research on Development ICORD VI, Fortelenza, Brazil, 487-495.
  • Öztürk, Z. & M.S. Yıldız (2016), “Hastane Etkinliklerinin Tahmininde Stokastik Sınır Analizi: Tarihi ve Ampirik Uygulamaları”, Uluslararası Sağlık Yönetimi ve Stratejileri Araştırma Dergisi, 1(3), 1-12.
  • Richmond, J. (1974), “Estimating the Efficiency of Production”, International Economic Review, 15(2), 515-21.
  • Storto, C. lo. (2014), “Gas Distribution in Italy: A Non-Parametric Analysis of Companies Operational Efficiency”, Advanced Material Research, Vol. 838-841, Trans Tech. Publication Switzerland: 1972-1978.
  • TPAO (N/A), <http://www.tpao.gov.tr/?mod=sektore-dair>, 10.02.2020.
  • Vikas & Bansal R. (2019) “Efficiency Evaluation of Indian Oil and Gas Sector: Data Envelopment Analysis”, International Journal of Emerging Markets, 14(2), 362-378.
  • Winsten, C. (1957), “Discussion of Mr. Farrell’s Paper”, Journal of the Statistical Society, Series A, General, 120, 282-284.
  • Yanes, L. (2013), “Stochastic Frontier Estimation for Gas Transmission Pipelines (Australia and United States Data)”, Acil Allen Consulting Dampier to Bunbury Pipeline. 19 September: 14.
  • Zorić, J. & N. Hrovatin & G.C. Scarsi (2009), “Gas Distribution Benchmarking of Utilities from Slovenia, The Netherlands and The United Kingdom: An Application of Data Envelopment Analysis”, South East European Journal of Economics and Business, 4(1), 113-124.

Details

Primary Language English
Subjects Social
Journal Section Articles
Authors

Üzeyir AYDIN (Primary Author)
Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi
0000-0003-2777-6450
Türkiye


Ömür Cem HÜNERLİ This is me
Halk Bankası
0000-0002-4713-1900
Türkiye

Publication Date July 30, 2021
Published in Issue Year 2021, Volume 29, Issue 49

Cite

Bibtex @research article { sosyoekonomi713223, journal = {Sosyoekonomi}, issn = {1305-5577}, address = {}, publisher = {Sosyoekonomi Society}, year = {2021}, volume = {29}, pages = {131 - 150}, doi = {10.17233/sosyoekonomi.2021.03.07}, title = {Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis}, key = {cite}, author = {Aydın, Üzeyir and Hünerli, Ömür Cem} }
APA Aydın, Ü. & Hünerli, Ö. C. (2021). Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis . Sosyoekonomi , 29 (49) , 131-150 . DOI: 10.17233/sosyoekonomi.2021.03.07
MLA Aydın, Ü. , Hünerli, Ö. C. "Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis" . Sosyoekonomi 29 (2021 ): 131-150 <https://dergipark.org.tr/en/pub/sosyoekonomi/issue/64335/713223>
Chicago Aydın, Ü. , Hünerli, Ö. C. "Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis". Sosyoekonomi 29 (2021 ): 131-150
RIS TY - JOUR T1 - Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis AU - Üzeyir Aydın , Ömür Cem Hünerli Y1 - 2021 PY - 2021 N1 - doi: 10.17233/sosyoekonomi.2021.03.07 DO - 10.17233/sosyoekonomi.2021.03.07 T2 - Sosyoekonomi JF - Journal JO - JOR SP - 131 EP - 150 VL - 29 IS - 49 SN - 1305-5577- M3 - doi: 10.17233/sosyoekonomi.2021.03.07 UR - https://doi.org/10.17233/sosyoekonomi.2021.03.07 Y2 - 2021 ER -
EndNote %0 Sosyoekonomi Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis %A Üzeyir Aydın , Ömür Cem Hünerli %T Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis %D 2021 %J Sosyoekonomi %P 1305-5577- %V 29 %N 49 %R doi: 10.17233/sosyoekonomi.2021.03.07 %U 10.17233/sosyoekonomi.2021.03.07
ISNAD Aydın, Üzeyir , Hünerli, Ömür Cem . "Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis". Sosyoekonomi 29 / 49 (July 2021): 131-150 . https://doi.org/10.17233/sosyoekonomi.2021.03.07
AMA Aydın Ü. , Hünerli Ö. C. Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis. Sosyoekonomi. 2021; 29(49): 131-150.
Vancouver Aydın Ü. , Hünerli Ö. C. Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis. Sosyoekonomi. 2021; 29(49): 131-150.
IEEE Ü. Aydın and Ö. C. Hünerli , "Measuring the Efficiency of Turkish Natural Gas Distribution Companies Using Stochastic Frontier Analysis", Sosyoekonomi, vol. 29, no. 49, pp. 131-150, Jul. 2021, doi:10.17233/sosyoekonomi.2021.03.07