IDEAS home Printed from https://ideas.repec.org/p/hwc/wpaper/004.html

Energy Efficiency in Transition Economies: A Stochastic Frontier Approach

Author

Listed:
  • Antonio Carvalho

    (Centre for Energy Economics Research and Policy, Heriot-Watt University)

Abstract

The paper outlines and estimates a measure of underlying efficiency in electricity consumption for an unbalanced panel of 28 transition economies and 5 Western European OECD countries in the period 1994-2007, by estimating a Bayesian Generalized True Random Effects (GTRE) stochastic frontier model that estimates both persistent and transient inefficiency. The properties of alternative GTRE estimation methods in small samples are explored to guide the estimation strategy. The paper analyses the behaviour of underlying efficiency in electricity consumption in these economies after accounting for time-invariant technological differences. After outlining the specific characteristics of the transition economies and their heterogeneous structural economic changes, an aggregate electricity demand function is estimated to obtain efficiency scores that give new insights for transition economies than a simple analysis of energy intensity. There is some evidence of convergence between the CIS countries and a block of Eastern European and selected OECD countries, although other country groups do not follow this tendency, such as the Balkans.

Suggested Citation

  • Antonio Carvalho, 2016. "Energy Efficiency in Transition Economies: A Stochastic Frontier Approach," CEERP Working Paper Series 004, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    • Handle: RePEc:hwc:wpaper:004
    as

    Download full text from publisher

    File URL: http://ceerp.hw.ac.uk/RePEc/hwc/wpaper/004.pdf
    File Function: First version, 2016
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    2. Cooper, R.Caron & Schipper, Lee, 1992. "The efficiency of energy use in the USSR —an international perspective," Energy, Elsevier, vol. 17(1), pages 1-24.
    3. Massimo Filippini & William Greene, 2016. "Persistent and transient productive inefficiency: a maximum simulated likelihood approach," Journal of Productivity Analysis, Springer, vol. 45(2), pages 187-196, April.
    4. Richard E. Ericson, 1991. "The Classical Soviet-Type Economy: Nature of the System and Implications for Reform," Journal of Economic Perspectives, American Economic Association, vol. 5(4), pages 11-27, Fall.
    5. repec:aen:journl:2002v23-01-a02 is not listed on IDEAS
    6. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    7. W. R. Gilks & P. Wild, 1992. "Adaptive Rejection Sampling for Gibbs Sampling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(2), pages 337-348, June.
    8. repec:aen:journl:2011v32-02-a03 is not listed on IDEAS
    9. Mr. Aleh Tsyvinski & Mr. Martin Petri & Mr. Günther Taube, 2002. "Energy Sector Quasi-Fiscal Activities in the Countries of the Former Soviet Union," IMF Working Papers 2002/060, International Monetary Fund.
    10. Badunenko, Oleg & Kumbhakar, Subal C., 2016. "When, where and how to estimate persistent and transient efficiency in stochastic frontier panel data models," European Journal of Operational Research, Elsevier, vol. 255(1), pages 272-287.
    11. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2014. "Measuring energy efficiency and rebound effects using a stochastic demand frontier approach: the US residential energy demand," Efficiency Series Papers 2014/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    12. Griffiths, William E. & Hajargasht, Gholamreza, 2016. "Some models for stochastic frontiers with endogeneity," Journal of Econometrics, Elsevier, vol. 190(2), pages 341-348.
    13. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2005. "Unobserved heterogeneity in stochastic cost frontier models: an application to Swiss nursing homes," Applied Economics, Taylor & Francis Journals, vol. 37(18), pages 2127-2141.
    14. Cornillie, Jan & Fankhauser, Samuel, 2004. "The energy intensity of transition countries," Energy Economics, Elsevier, vol. 26(3), pages 283-295, May.
    15. Schneider, Friedrich, 2002. "The Size and Development of the Shadow Economies of 22 Transition and 21 OECD Countries," IZA Discussion Papers 514, IZA Network @ LISER.
    16. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    17. Massimo Filippini & William Greene & Giuliano Masiero, 2016. "Persistent and transient productive inefficiency in a regulated industry: electricity distribution in New Zealand," IdEP Economic Papers 1603, USI Università della Svizzera italiana.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lina Sineviciene & Iryna Sotnyk & Oleksandr Kubatko, 2017. "Determinants of energy efficiency and energy consumption of Eastern Europe post-communist economies," Energy & Environment, , vol. 28(8), pages 870-884, December.
    2. Twerefou, Daniel Kwabena & Abeney, Jacob Opantu, 2020. "Efficiency of household electricity consumption in Ghana," Energy Policy, Elsevier, vol. 144(C).
    3. Twerefou, Daniel Kwabena & Abeney, Jacob Opantu & Toman, Michael & Turkson, Festus Ebo & Baffour, Priscilla Twumasi, 2023. "Household Electricity Consumption Inefficiency and Poverty: Evidence from Ghana," EfD Discussion Paper 23-11, Environment for Development, University of Gothenburg.
    4. Dilawar Khan & Muhammad Nouman & József Popp & Muhammad Asif Khan & Faheem Ur Rehman & Judit Oláh, 2021. "Link between Technically Derived Energy Efficiency and Ecological Footprint: Empirical Evidence from the ASEAN Region," Energies, MDPI, vol. 14(13), pages 1-16, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. António Carvalho, 2018. "Energy efficiency in transition economies : A stochastic frontier approach," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 26(3), pages 553-578, July.
    2. Raushan Bokusheva & Lukáš Čechura & Subal C. Kumbhakar, 2023. "Estimating persistent and transient technical efficiency and their determinants in the presence of heterogeneity and endogeneity," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 450-472, June.
    3. Badunenko, Oleg & D’Inverno, Giovanna & De Witte, Kristof, 2023. "On distinguishing the direct causal effect of an intervention from its efficiency-enhancing effects," European Journal of Operational Research, Elsevier, vol. 310(1), pages 432-447.
    4. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    5. Sabrina Auci & Laura Castellucci & Manuela Coromaldi, 2021. "How does public spending affect technical efficiency? Some evidence from 15 European countries," Bulletin of Economic Research, Wiley Blackwell, vol. 73(1), pages 108-130, January.
    6. Magambo, Isaiah & Dikgang, Johane & Gelo, Dambala & Tregenna, Fiona, 2021. "Environmental and Technical Efficiency in Large Gold Mines in Developing Countries," MPRA Paper 108068, University Library of Munich, Germany.
    7. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    8. Boris E. Bravo‐Ureta & Víctor H. Moreira & Javier L. Troncoso & Alan Wall, 2020. "Plot‐level technical efficiency accounting for farm‐level effects: Evidence from Chilean wine grape producers," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 811-824, November.
    9. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    10. Massimo Filippini & Elisa Tosetti, 2014. "Stochastic Frontier Models for Long Panel Data Sets: Measurement of the Underlying Energy Efficiency for the OECD Countries," CER-ETH Economics working paper series 14/198, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    11. Llorca, Manuel & Baños, José & Somoza, José & Arbués, Pelayo, 2014. "A latent class approach for estimating energy demands and efficiency in transport: An application to Latin America and the Caribbean," Efficiency Series Papers 2014/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    12. Bravo-Ureta, Boris E. & Njuki, Eric & Palacios, Ana Claudia & Salazar, Lina, 2022. "Agricultural Productivity in El Salvador: A Preliminary Analysis," IDB Publications (Working Papers) 11984, Inter-American Development Bank.
    13. Blasch, Julia & Boogen, Nina & Filippini, Massimo & Kumar, Nilkanth, 2017. "Explaining electricity demand and the role of energy and investment literacy on end-use efficiency of Swiss households," Energy Economics, Elsevier, vol. 68(S1), pages 89-102.
    14. Marin, Giovanni & Palma, Alessandro, 2017. "Technology invention and adoption in residential energy consumption," Energy Economics, Elsevier, vol. 66(C), pages 85-98.
    15. Pengfei Sheng & Yuechi Zhang, 2019. "The effect of pollution on the inequality in health care expenditure: Evidence from China," Energy & Environment, , vol. 30(8), pages 1380-1395, December.
    16. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    17. Lukáš Čechura & Zdeňka Žáková Kroupová, 2021. "Technical Efficiency in the European Dairy Industry: Can We Observe Systematic Failures in the Efficiency of Input Use?," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    18. Rawat, Pankaj S. & Sharma, Seema, 2021. "TFP growth, technical efficiency and catch-up dynamics: Evidence from Indian manufacturing," Economic Modelling, Elsevier, vol. 103(C).
    19. Liu, Xiao-Yan & Pollitt, Michael G. & Xie, Bai-Chen & Liu, Li-Qiu, 2019. "Does environmental heterogeneity affect the productive efficiency of grid utilities in China?," Energy Economics, Elsevier, vol. 83(C), pages 333-344.
    20. Bernstein, David H., 2020. "An updated assessment of technical efficiency and returns to scale for U.S. electric power plants," Energy Policy, Elsevier, vol. 147(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other
    • P20 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hwc:wpaper:004. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Antonio Carvalho The email address of this maintainer does not seem to be valid anymore. Please ask Antonio Carvalho to update the entry or send us the correct address (email available below). General contact details of provider: http://ceerp.hw.ac.uk/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.