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A Stochastic Frontier Analysis Approach for Estimating Energy Demand and Efficiency in the Transport Sector of Latin America and the Caribbean

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  • Manuel Llorca
  • Jose Banos
  • Somoza Jose
  • Pelayo Arbues

Abstract

In this paper, a stochastic frontier analysis approach is applied to estimate energy demand functions in the transport sector. This approach allows us to obtain energy efficiency measures at country level that are a robust alternative to the energy intensity indicators commonly used for international comparisons. A transitive multilateral price index is constructed for aggregating the diverse energy components employed in the sector. Due to the likely unobserved heterogeneity among countries, the use of a random parameters model is proposed to accommodate these differences and to obtain different income and price elasticities per country. The estimated model is compared with alternative approaches of addressing this issue such as latent class, true fixed effects or true random effects models. This study is the first to use a random parameters 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 total energy consumption.

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  • Manuel Llorca & Jose Banos & Somoza Jose & Pelayo Arbues, 2017. "A Stochastic Frontier Analysis Approach for Estimating Energy Demand and Efficiency in the Transport Sector of Latin America and the Caribbean," The Energy Journal, , vol. 38(5), pages 153-174, September.
  • Handle: RePEc:sae:enejou:v:38:y:2017:i:5:p:153-174
    DOI: 10.5547/01956574.38.5.mllo
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    as
    1. Fouquet, Roger, 2012. "Trends in income and price elasticities of transport demand (1850–2010)," Energy Policy, Elsevier, vol. 50(C), pages 62-71.
    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. 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.
    4. 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.
    5. 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.
    6. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    7. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    8. Massimo Filippini & Lester C. Hunt, 2011. "Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 59-80.
    9. 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.
    10. Gabriel Di Bella & Mr. Lawrence Norton & Mr. Joseph Ntamatungiro & Ms. Sumiko Ogawa & Issouf Samaké & Marika Santoro, 2015. "Energy Subsidies in Latin America and the Caribbean: Stocktaking and Policy Challenges," IMF Working Papers 2015/030, International Monetary Fund.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Jorge Rogat, 2007. "The Politics of Fuel Pricing in Latin America and Their Implications for the Environment," Energy & Environment, , vol. 18(1), pages 1-12, January.
    16. 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.
    17. 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.
    18. Huntington, Hillard G., 1994. "Been top down so long it looks like bottom up to me," Energy Policy, Elsevier, vol. 22(10), pages 833-839, October.
    19. -, 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.
    20. 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.
    21. 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.
    22. 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.
    23. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    24. Massimo Filippini & Luis Orea, 2014. "Applications of the stochastic frontier approach in Energy Economics," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 35-42.
    25. 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.
    26. Roger Fouquet (ed.), 2013. "Handbook on Energy and Climate Change," Books, Edward Elgar Publishing, number 14429.
    27. Islas, Jorge & Manzini, Fabio & Masera, Omar, 2007. "A prospective study of bioenergy use in Mexico," Energy, Elsevier, vol. 32(12), pages 2306-2320.
    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. Wohlgemuth, Norbert, 1997. "World transport energy demand modelling : Methodology and elasticities," Energy Policy, Elsevier, vol. 25(14-15), pages 1109-1119, December.
    30. Stead, D., 2001. "Transport intensity in Europe -- indicators and trends," Transport Policy, Elsevier, vol. 8(1), pages 29-46, January.
    31. David Bonilla & Timothy Foxon, 2009. "Demand for New Car Fuel Economy in the UK, 1970-2005," Journal of Transport Economics and Policy, University of Bath, vol. 43(1), pages 55-83, January.
    32. 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.
    33. -, 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.
    34. 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.
    35. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    36. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2015. "A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand," Energy Economics, Elsevier, vol. 49(C), pages 599-609.
    37. 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.
    38. Filippini, Massimo & Hunt, Lester C. & Zorić, Jelena, 2014. "Impact of energy policy instruments on the estimated level of underlying energy efficiency in the EU residential sector," Energy Policy, Elsevier, vol. 69(C), pages 73-81.
    39. Joanne Evans & Massimo Filippini & Lester C. Hunt, 2013. "The contribution of energy efficiency towards meeting CO2 targets," Chapters, in: Roger Fouquet (ed.), Handbook on Energy and Climate Change, chapter 8, pages 175-223, Edward Elgar Publishing.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. 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 bu," Energy, Elsevier, vol. 31(12), pages 1748-1760.
    45. 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.
    46. 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.
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