IDEAS home Printed from https://ideas.repec.org/p/oeg/wpaper/2014-04.html

A latent class approach for estimating energy demands and efficiency in transport: An application to Latin America and the Caribbean

Author

Listed:
  • Llorca, Manuel
  • Baños, José
  • Somoza, José
  • Arbués, Pelayo

Abstract

In this paper, we use a stochastic frontier analysis approach to estimate demand functions for energy in the transport sector. The estimation of frontier functions allows us to obtain energy efficiency measures that are a robust alternative to the energy intensity indicators that are commonly used for international comparisons. Due to the likely unobserved heterogeneity among countries, we propose the use of a latent class model that allows to test for the existence of groups of countries with clearly differentiated demands that are associated with distinct price and income elasticities. This study is the first to use a latent class stochastic frontier approach in the estimation of energy demand functions. The proposed procedure is applied to Latin America and the Caribbean, where the transport sector represents a large share of the total energy consumption. These energy demand functions call for the inclusion of energy price in their estimation. As the transport of both goods and passengers implies the consumption of different types of energy, an index that aggregates various energy prices is thus required for the analysis. However, international agencies do not provide specific indicators of aggregate energy prices in transport for the majority of the countries analysed. For this reason, in this paper we propose the construction of a transitive multilateral index which, in contrast to those frequently presented by the aforementioned agencies, facilitates international comparisons over time.

Suggested Citation

  • 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).
  • Handle: RePEc:oeg:wpaper:2014/04
    as

    Download full text from publisher

    File URL: https://www.unioviedo.es/oeg/ESP/esp_2014_04.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980, October.
    2. Ceylan, Huseyin & Ceylan, Halim & Haldenbilen, Soner & Baskan, Ozgur, 2008. "Transport energy modeling with meta-heuristic harmony search algorithm, an application to Turkey," Energy Policy, Elsevier, vol. 36(7), pages 2527-2535, July.
    3. repec:aen:journl:2011v32-02-a03 is not listed on IDEAS
    4. Hymel, Kent M. & Small, Kenneth A. & Dender, Kurt Van, 2010. "Induced demand and rebound effects in road transport," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1220-1241, December.
    5. 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.
    6. Zhang, Ming & Mu, Hailin & Li, Gang & Ning, Yadong, 2009. "Forecasting the transport energy demand based on PLSR method in China," Energy, Elsevier, vol. 34(9), pages 1396-1400.
    7. Lu, I.J. & Lewis, Charles & Lin, Sue J., 2009. "The forecast of motor vehicle, energy demand and CO2 emission from Taiwan's road transportation sector," Energy Policy, Elsevier, vol. 37(8), pages 2952-2961, August.
    8. repec:aen:journl:2007v28-01-a02 is not listed on IDEAS
    9. Galindo, Luis Miguel, 2005. "Short- and long-run demand for energy in Mexico: a cointegration approach," Energy Policy, Elsevier, vol. 33(9), pages 1179-1185, June.
    10. Daniel J. Graham & Stephen Glaister, 2002. "The Demand for Automobile Fuel: A Survey of Elasticities," Journal of Transport Economics and Policy, University of Bath, vol. 36(1), pages 1-25, January.
    11. repec:aen:journl:1999v20-03-a01 is not listed on IDEAS
    12. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    13. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    14. Barros, Carlos Pestana & Prieto-Rodriguez, Juan, 2008. "A revenue-neutral tax reform to increase demand for public transport services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(4), pages 659-672, May.
    15. Bauer, Mariano & Mar, Elizabeth & Elizalde, Alberto, 2003. "Transport and energy demand in Mexico: the personal income shock," Energy Policy, Elsevier, vol. 31(14), pages 1475-1480, November.
    16. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    17. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    18. 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.
    19. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    20. Haldenbilen, Soner & Ceylan, Halim, 2005. "Genetic algorithm approach to estimate transport energy demand in Turkey," Energy Policy, Elsevier, vol. 33(1), pages 89-98, January.
    21. Reifschneider, David & Stevenson, Rodney, 1991. "Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 715-723, August.
    22. Lu, I.J. & Lin, Sue J. & Lewis, Charles, 2008. "Grey relation analysis of motor vehicular energy consumption in Taiwan," Energy Policy, Elsevier, vol. 36(7), pages 2556-2561, July.
    23. Murat, Yetis Sazi & Ceylan, Halim, 2006. "Use of artificial neural networks for transport energy demand modeling," Energy Policy, Elsevier, vol. 34(17), pages 3165-3172, November.
    24. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    25. Limanond, Thirayoot & Jomnonkwao, Sajjakaj & Srikaew, Artit, 2011. "Projection of future transport energy demand of Thailand," Energy Policy, Elsevier, vol. 39(5), pages 2754-2763, May.
    26. Pradhan, Shreekar & Ale, Bhakta Bahadur & Amatya, Vishwa Bhusan, 2006. "Mitigation potential of greenhouse gas emission and implications on fuel consumption due to clean energy vehicles as public passenger transport in Kathmandu Valley of Nepal: A case study of trolley buses in Ring Road," Energy, Elsevier, vol. 31(12), pages 1748-1760.
    27. Wohlgemuth, Norbert, 1997. "World transport energy demand modelling : Methodology and elasticities," Energy Policy, Elsevier, vol. 25(14-15), pages 1109-1119, December.
    28. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    29. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    30. Chavez-Baeza, Carlos & Sheinbaum-Pardo, Claudia, 2014. "Sustainable passenger road transport scenarios to reduce fuel consumption, air pollutants and GHG (greenhouse gas) emissions in the Mexico City Metropolitan Area," Energy, Elsevier, vol. 66(C), pages 624-634.
    31. Hao, Han & Wang, Hewu & Yi, Ran, 2011. "Hybrid modeling of China’s vehicle ownership and projection through 2050," Energy, Elsevier, vol. 36(2), pages 1351-1361.
    32. 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.
    33. 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.
    34. -, 2010. "Sustainable Development in Latin America and the Caribbean: Trends, Progress, and Challenges in Sustainable Consumption and Production, Mining, Transport, Chemicals and Waste Management," Libros y Documentos Institucionales, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), number 3160 edited by Eclac.
    35. Ang, B.W., 2006. "Monitoring changes in economy-wide energy efficiency: From energy-GDP ratio to composite efficiency index," Energy Policy, Elsevier, vol. 34(5), pages 574-582, March.
    36. Al-Ghandoor, Ahmed & Samhouri, Murad & Al-Hinti, Ismael & Jaber, Jamal & Al-Rawashdeh, Mohammad, 2012. "Projection of future transport energy demand of Jordan using adaptive neuro-fuzzy technique," Energy, Elsevier, vol. 38(1), pages 128-135.
    37. Dreher, M & Wietschel, M & Göbelt, M & Rentz, O, 1999. "Energy price elasticities of energy-service demand for passenger traffic in the Federal Republic of Germany," Energy, Elsevier, vol. 24(2), pages 133-140.
    38. -, 2005. "The millennium development goals: a Latin American and Caribbean perspective," Libros y Documentos Institucionales, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), number 2798 edited by Eclac.
    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. Llorca, Manuel & Jamasb, Tooraj, 2017. "Energy efficiency and rebound effect in European road freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 98-110.

    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. repec:aen:journl:ej38-5-llorca is not listed on IDEAS
    2. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    3. Massimo Filippini & Lester C. Hunt, 2013. "'Underlying Energy Efficiency' in the US," CER-ETH Economics working paper series 13/181, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    4. Llorca, Manuel & Jamasb, Tooraj, 2017. "Energy efficiency and rebound effect in European road freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 98-110.
    5. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    6. 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.
    7. 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.
    8. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    9. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    10. Concetta Castiglione & Davide Infante & Marta Zieba, 2018. "Technical efficiency in the Italian performing arts companies," Small Business Economics, Springer, vol. 51(3), pages 609-638, October.
    11. 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.
    12. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    13. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    14. Castiglione, Concetta & Infante, Davide & Zieba, Marta, 2023. "Public support for performing arts. Efficiency and productivity gains in eleven European countries," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    15. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    16. Tran, Kien C. & Tsionas, Mike G., 2016. "Zero-inefficiency stochastic frontier models with varying mixing proportion: A semiparametric approach," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1113-1123.
    17. Idaira Cabrera‐Suárez & Jorge V. Pérez‐Rodríguez, 2021. "Bank branch performance and cost efficiency: A stochastic frontier panel data approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5850-5863, October.
    18. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, vol. 28(1), pages 69-90, July.
    19. K Hervé Dakpo & Laure Latruffe & Yann Desjeux & Philippe Jeanneaux, 2022. "Modeling heterogeneous technologies in the presence of sample selection: The case of dairy farms and the adoption of agri‐environmental schemes in France," Agricultural Economics, International Association of Agricultural Economists, vol. 53(3), pages 422-438, May.
    20. Marin, Giovanni & Palma, Alessandro, "undated". "Technology Invention and Diffusion in Residential Energy Consumption. A Stochastic Frontier Approach," Energy: Resources and Markets 230687, Fondazione Eni Enrico Mattei (FEEM).
    21. Farsi, Mehdi & Filippini, Massimo & Kuenzle, Michael, 2007. "Cost efficiency in the Swiss gas distribution sector," Energy Economics, Elsevier, vol. 29(1), pages 64-78, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:oeg:wpaper:2014/04. 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: Luis Orea or David Roibas (email available below). General contact details of provider: https://edirc.repec.org/data/geovies.html .

    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.