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Demand and Price Volatility: Rational Habits in International Gasoline Demand

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  • 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.

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  • Scott, K. Rebecca, 2011. "Demand and Price Volatility: Rational Habits in International Gasoline Demand," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2q87432b, Department of Agricultural & Resource Economics, UC Berkeley.
  • Handle: RePEc:cdl:agrebk:qt2q87432b
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    1. 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.
    2. Espey, Molly, 1998. "Gasoline demand revisited: an international meta-analysis of elasticities," Energy Economics, Elsevier, vol. 20(3), pages 273-295, June.
    3. Krichene, Noureddine, 2002. "World crude oil and natural gas: a demand and supply model," Energy Economics, Elsevier, vol. 24(6), pages 557-576, November.
    4. 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.
    5. 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.
    6. 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.
    7. Bhaskara Rao, B. & Rao, Gyaneshwar, 2009. "Cointegration and the demand for gasoline," Energy Policy, Elsevier, vol. 37(10), pages 3978-3983, October.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    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. 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.
    18. Edward F. Blackburne III & Mark W. Frank, 2007. "Estimation of nonstationary heterogeneous panels," Stata Journal, StataCorp LP, vol. 7(2), pages 197-208, June.
    19. Bentzen, Jan, 1994. "An empirical analysis of gasoline demand in Denmark using cointegration techniques," Energy Economics, Elsevier, vol. 16(2), pages 139-143, April.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. Nguyen-Van, Phu, 2010. "Energy consumption and income: A semiparametric panel data analysis," Energy Economics, Elsevier, vol. 32(3), pages 557-563, May.
    27. 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.
    28. Damiaan Persyn & Joakim Westerlund, 2008. "Error-correction–based cointegration tests for panel data," Stata Journal, StataCorp LP, vol. 8(2), pages 232-241, June.
    29. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    30. 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.
    31. Gang Liu, 2004. "Estimating Energy Demand Elasticities for OECD Countries. A Dynamic Panel Data Approach," Discussion Papers 373, Statistics Norway, Research Department.
    32. 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.
    33. 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.
    34. 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.
    35. Dahl, Carol & Sterner, Thomas, 1991. "Analysing gasoline demand elasticities: a survey," Energy Economics, Elsevier, vol. 13(3), pages 203-210, July.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. David Roodman, 2006. "How to Do xtabond2," North American Stata Users' Group Meetings 2006 8, Stata Users Group.
    41. 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.
    42. Samimi, Rodney, 1995. "Road transport energy demand in Australia: A cointegration approach," Energy Economics, Elsevier, vol. 17(4), pages 329-339, October.
    43. Angelier, Jean Pierre & Sterner, Thomas, 1990. "Tax harmonization for petroleum products in the EC," Energy Policy, Elsevier, vol. 18(6), pages 500-505.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. World Bank, 2009. "World Development Indicators 2009," World Bank Publications - Books, The World Bank Group, number 4367.
    49. 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.
    50. 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.
    51. 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.
    52. Harris, R. & Tzavalis, E., 1996. "Inference for Unit Roots in Dynamic Panels," Discussion Papers 9604, University of Exeter, Department of Economics.
    53. 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.
    54. 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.
    55. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    56. 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.
    57. 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.
    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.
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    1. Shaw, Charles, 2020. "Econometric Analysis of Demand for Petrol in India, 1966-2019," MPRA Paper 104797, University Library of Munich, Germany.

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