IDEAS home Printed from https://ideas.repec.org/p/ags/ucbecw/121931.html
   My bibliography  Save this paper

Demand and price volatility: rational habits in international gasoline demand

Author

Listed:
  • Scott, K. Rebecca

Abstract

The combination of habits and a forward outlook suggests that consumers will be sensitive not just to prices but to price dynamics. In particular, rational habits models suggest 1. that price volatility and uncertainty will reduce demand for a habit-forming good and 2. that such volatility will dampen demands responsiveness to price. These two implications can be tested by augmenting a traditional partial-adjustment or error-correction model of demand. I apply this augmented model to data on gasoline consumption, as rational habits provide a succinct representation for the investmentand behavioral decisions that determine gasoline usage. The trade-o¤s among 2SLS, system GMM, and pooled mean group (PMG) estimators are considered, and my preferred PMG estimator provides evidence for the two implications of rational habits in a panel of 29 countries for the years 1990-2009.The sensitivity of certain results to the choice of estimator o¤ers a cautionary illustration of the cost of assumptions such as coe¢ cient heterogeneity. Given the evidence uncovered in favor of rational gasoline habits, such habits may help to explain some of the cross-country variation in "total" price elasticity. These habits also imply that the e¤ect of price volatility must be taken into account when projecting the impacts of potential policies on gasoline consumption.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Scott, K. Rebecca, 2011. "Demand and price volatility: rational habits in international gasoline demand," CUDARE Working Papers 121931, University of California, Berkeley, Department of Agricultural and Resource Economics.
  • Handle: RePEc:ags:ucbecw:121931
    DOI: 10.22004/ag.econ.121931
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/121931/files/CUDARE%201122%20Scott%20.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.121931?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ruth A. Judson & Richard Schmalensee & Thomas M. Stoker, 1999. "Economic Development and the Structure of the Demand for Commercial Energy," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 29-57.
    2. Robert V. Breunig & Carol Gisz, 2009. "An Exploration of Australian Petrol Demand: Unobservable Habits, Irreversibility and Some Updated Estimates," The Economic Record, The Economic Society of Australia, vol. 85(268), pages 73-91, March.
    3. Espey, Molly, 1998. "Gasoline demand revisited: an international meta-analysis of elasticities," Energy Economics, Elsevier, vol. 20(3), pages 273-295, June.
    4. Joakim Westerlund, 2007. "Testing for Error Correction in Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(6), pages 709-748, December.
    5. Krichene, Noureddine, 2002. "World crude oil and natural gas: a demand and supply model," Energy Economics, Elsevier, vol. 24(6), pages 557-576, November.
    6. Bhaskara Rao, B. & Rao, Gyaneshwar, 2009. "Cointegration and the demand for gasoline," Energy Policy, Elsevier, vol. 37(10), pages 3978-3983, October.
    7. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    8. Mark Coppejans & Donna Gilleskie & Holger Sieg & Koleman Strumpf, 2007. "Consumer Demand under Price Uncertainty: Empirical Evidence from the Market for Cigarettes," The Review of Economics and Statistics, MIT Press, vol. 89(3), pages 510-521, August.
    9. De Vita, G. & Endresen, K. & Hunt, L.C., 2006. "An empirical analysis of energy demand in Namibia," Energy Policy, Elsevier, vol. 34(18), pages 3447-3463, December.
    10. Narayan, Paresh Kumar & Smyth, Russell, 2007. "A panel cointegration analysis of the demand for oil in the Middle East," Energy Policy, Elsevier, vol. 35(12), pages 6258-6265, December.
    11. Polemis, Michael L., 2006. "Empirical assessment of the determinants of road energy demand in Greece," Energy Economics, Elsevier, vol. 28(3), pages 385-403, May.
    12. Dahl, Carol & Sterner, Thomas, 1991. "Analysing gasoline demand elasticities: a survey," Energy Economics, Elsevier, vol. 13(3), pages 203-210, July.
    13. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    14. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    15. Jonathan E. Hughes & Christopher R. Knittel & Daniel Sperling, 2008. "Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand," The Energy Journal, International Association for Energy Economics, vol. 29(1), pages 113-134.
    16. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(3), pages 597-625, June.
    17. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    18. Storchmann, Karl, 2005. "Long-Run Gasoline demand for passenger cars: the role of income distribution," Energy Economics, Elsevier, vol. 27(1), pages 25-58, January.
    19. Bentzen, Jan & Engsted, Tom, 2001. "A revival of the autoregressive distributed lag model in estimating energy demand relationships," Energy, Elsevier, vol. 26(1), pages 45-55.
    20. Jonathan E. Hughes & Christopher R. Knittel & Daniel Sperling, 2008. "Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand," The Energy Journal, International Association for Energy Economics, vol. 29(1), pages 113-134.
    21. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    22. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    23. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    24. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    25. Zia Wadud & Daniel Graham & Robert Noland, 2009. "A cointegration analysis of gasoline demand in the United States," Applied Economics, Taylor & Francis Journals, vol. 41(26), pages 3327-3336.
    26. Eltony, M. N. & Al-Mutairi, N. H., 1995. "Demand for gasoline in Kuwait : An empirical analysis using cointegration techniques," Energy Economics, Elsevier, vol. 17(3), pages 249-253, July.
    27. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    28. David Roodman, 2006. "How to Do xtabond2," North American Stata Users' Group Meetings 2006 8, Stata Users Group.
    29. Alves, Denisard C. O. & De Losso da Silveira Bueno, Rodrigo, 2003. "Short-run, long-run and cross elasticities of gasoline demand in Brazil," Energy Economics, Elsevier, vol. 25(2), pages 191-199, March.
    30. Samimi, Rodney, 1995. "Road transport energy demand in Australia: A cointegration approach," Energy Economics, Elsevier, vol. 17(4), pages 329-339, October.
    31. Edward F. Blackburne III & Mark W. Frank, 2007. "Estimation of nonstationary heterogeneous panels," Stata Journal, StataCorp LP, vol. 7(2), pages 197-208, June.
    32. Bentzen, Jan, 1994. "An empirical analysis of gasoline demand in Denmark using cointegration techniques," Energy Economics, Elsevier, vol. 16(2), pages 139-143, April.
    33. Angelier, Jean Pierre & Sterner, Thomas, 1990. "Tax harmonization for petroleum products in the EC," Energy Policy, Elsevier, vol. 18(6), pages 500-505.
    34. Brons, Martijn & Nijkamp, Peter & Pels, Eric & Rietveld, Piet, 2008. "A meta-analysis of the price elasticity of gasoline demand. A SUR approach," Energy Economics, Elsevier, vol. 30(5), pages 2105-2122, September.
    35. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    36. Baltagi, Badi H. & Griffin, James M., 1983. "Gasoline demand in the OECD : An application of pooling and testing procedures," European Economic Review, Elsevier, vol. 22(2), pages 117-137, July.
    37. Lutz Kilian, 2010. "Explaining Fluctuations in Gasoline Prices: A Joint Model of the Global Crude Oil Market and the U.S. Retail Gasoline Market," The Energy Journal, , vol. 31(2), pages 87-112, April.
    38. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    39. Edward F. Blackburne III & Mark W. Frank, 2007. "XTPMG: Stata module for estimation of nonstationary heterogeneous panels," Statistical Software Components S456868, Boston College Department of Economics.
    40. World Bank, 2009. "World Development Indicators 2009," World Bank Publications - Books, The World Bank Group, number 4367.
    41. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    42. Richard Blundell & Stephen Bond & Frank Windmeijer, 2000. "Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator," IFS Working Papers W00/12, Institute for Fiscal Studies.
    43. Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
    44. Nguyen-Van, Phu, 2010. "Energy consumption and income: A semiparametric panel data analysis," Energy Economics, Elsevier, vol. 32(3), pages 557-563, May.
    45. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    46. Damiaan Persyn & Joakim Westerlund, 2008. "Error-correction–based cointegration tests for panel data," Stata Journal, StataCorp LP, vol. 8(2), pages 232-241, June.
    47. Chi‐Young Choi & Nelson C. Mark & Donggyu Sul, 2010. "Bias Reduction in Dynamic Panel Data Models by Common Recursive Mean Adjustment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(5), pages 567-599, October.
    48. Storchmann, Karl, 2005. "Erratum to "Long-run gasoline demand for passenger cars: The role of income distribution" [Energy Economics, 27 (1), 25-58]," Energy Economics, Elsevier, vol. 27(4), pages 687-687, July.
    49. Harris, R. & Tzavalis, E., 1996. "Inference for Unit Roots in Dynamic Panels," Discussion Papers 9604, University of Exeter, Department of Economics.
    50. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    51. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    52. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    53. Stephen R. Bond, 2002. "Dynamic panel data models: a guide to micro data methods and practice," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 141-162, August.
    54. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    55. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    56. Akinboade, Oludele A. & Ziramba, Emmanuel & Kumo, Wolassa L., 2008. "The demand for gasoline in South Africa: An empirical analysis using co-integration techniques," Energy Economics, Elsevier, vol. 30(6), pages 3222-3229, November.
    57. Gang Liu, 2004. "Estimating Energy Demand Elasticities for OECD Countries. A Dynamic Panel Data Approach," Discussion Papers 373, Statistics Norway, Research Department.
    58. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    59. Ramanathan, R., 1999. "Short- and long-run elasticities of gasoline demand in India: An empirical analysis using cointegration techniques," Energy Economics, Elsevier, vol. 21(4), pages 321-330, August.
    60. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    61. Kui-Yin Cheung & Elspeth Thomson, 2004. "The Demand for Gasoline in China: A Cointegration Analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(5), pages 533-544.
    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. Shaw, Charles, 2020. "Econometric Analysis of Demand for Petrol in India, 1966-2019," MPRA Paper 104797, University Library of Munich, Germany.

    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. Scott, K. Rebecca, 2015. "Demand and price uncertainty: Rational habits in international gasoline demand," Energy, Elsevier, vol. 79(C), pages 40-49.
    2. Bakhat, Mohcine & Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2017. "Elasticities of transport fuels at times of economic crisis: An empirical analysis for Spain," Energy Economics, Elsevier, vol. 68(S1), pages 66-80.
    3. Mohcine Bakhat & José M. Labeaga & Xavier Labandeira & Xiral Lñpez, 2013. "Economic Crisis and Elasticities of Car Fuels: Evidence for Spain," Working Papers fa15-2013, Economics for Energy.
    4. Peñasco, Cristina & del Río, Pablo & Romero-Jordán, Desiderio, 2017. "Gas and electricity demand in Spanish manufacturing industries: An analysis using homogeneous and heterogeneous estimators," Utilities Policy, Elsevier, vol. 45(C), pages 45-60.
    5. Rosa M. González-Marrero & Rosa M. Lorenzo-Alegría & Gustavo A. Marrero, 2011. "Gasoline and Diesel Consumption for Road Transport in Spain: a Dynamic Panel Data Approach," Economic Reports 04-2011, FEDEA.
    6. Gharehgozli, Orkideh, 2021. "An empirical comparison between a regression framework and the Synthetic Control Method," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 70-81.
    7. Santos, Gervásio F., 2013. "Fuel demand in Brazil in a dynamic panel data approach," Energy Economics, Elsevier, vol. 36(C), pages 229-240.
    8. Jimy Ferrer Carbonell & Roberto Escalante Semerena, 2014. "Demanda de gasolina en la zona metropolitana del Valle de México: análisis empírico de la reducción del subsidio," Revista de Economía del Rosario, Universidad del Rosario, June.
    9. Yongfu Huang, 2011. "Private investment and financial development in a globalized world," Empirical Economics, Springer, vol. 41(1), pages 43-56, August.
    10. Havranek, Tomas & Irsova, Zuzana & Janda, Karel, 2012. "Demand for gasoline is more price-inelastic than commonly thought," Energy Economics, Elsevier, vol. 34(1), pages 201-207.
    11. Eshagh Mansourkiaee, 2023. "Estimating energy demand elasticities for gas exporting countries: a dynamic panel data approach," SN Business & Economics, Springer, vol. 3(1), pages 1-28, January.
    12. Vogel, Johanna, 2013. "Regional Convergence in Europe: A Dynamic Heterogeneous Panel Approach," MPRA Paper 51794, University Library of Munich, Germany.
    13. Rodriguez-Palenzuela, Diego & Dées, Stéphane & Andersson, Malin & Bijsterbosch, Martin & Forster, Katrin & Zorell, Nico & Audoly, Richard & Buelens, Christian & Compeyron, Guillaume & Ferrando, Annali, 2016. "Savings and investment behaviour in the euro area," Occasional Paper Series 167, European Central Bank.
    14. Eberhardt, Markus & Teal, Francis, 2008. "Modeling technology and technological change in manufacturing: how do countries differ?," MPRA Paper 10690, University Library of Munich, Germany.
    15. Chen, Ping-Yu & Chen, Sheng-Tung & Hsu, Chia-Sheng & Chen, Chi-Chung, 2016. "Modeling the global relationships among economic growth, energy consumption and CO2 emissions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 420-431.
    16. Scott, K. Rebecca, 2012. "Rational habits in gasoline demand," Energy Economics, Elsevier, vol. 34(5), pages 1713-1723.
    17. Jaunky, Vishal Chandr, 2011. "The CO2 emissions-income nexus: Evidence from rich countries," Energy Policy, Elsevier, vol. 39(3), pages 1228-1240, March.
    18. Samargandi, Nahla & Fidrmuc, Jan & Ghosh, Sugata, 2015. "Is the Relationship Between Financial Development and Economic Growth Monotonic? Evidence from a Sample of Middle-Income Countries," World Development, Elsevier, vol. 68(C), pages 66-81.
    19. Lee, Chien-Chiang & Chiu, Yi-Bin, 2011. "Oil prices, nuclear energy consumption, and economic growth: New evidence using a heterogeneous panel analysis," Energy Policy, Elsevier, vol. 39(4), pages 2111-2120, April.
    20. Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005. "Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration," Econometric Theory, Cambridge University Press, vol. 21(4), pages 795-837, August.

    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:ags:ucbecw:121931. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/dabrkus.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.