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Demand Systems with Nonstationary Prices

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  • Arthur Lewbel

    (Boston College)

  • Serena Ng

    (University of Michigan)

Abstract

Relative prices are nonstationary and standard root-T inference is invalid for demand systems. But demand systems are nonlinear functions of relative prices, and standard methods for dealing with nonstationarity in linear models cannot be used. Demand system residuals are also frequently found to be highly persistent, further complicating estimation and inference. We propose a variant of the translog demand system, the NTLOG, and an associated estimator that can be applied in the presence of nonstationary prices with possibly nonstationary errors. The errors in the NTLOG can be interpreted as random utility parameters. The estimates have classical root-T limiting distributions. We also propose an explanation for the observed nonstationarity of aggregate demand errors, based on aggregation of consumers with heterogeneous preferences in a slowly changing population. Estimates using U.S. data are provided. 2005 President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Arthur Lewbel & Serena Ng, 2005. "Demand Systems with Nonstationary Prices," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 479-494, August.
  • Handle: RePEc:tpr:restat:v:87:y:2005:i:3:p:479-494
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    References listed on IDEAS

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    1. Ng, Serena, 1995. "Testing for Homogeneity in Demand Systems When the Regressors Are Nonstationary," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 147-163, April-Jun.
    2. Pierre Perron & Serena Ng, 1996. "Useful Modifications to some Unit Root Tests with Dependent Errors and their Local Asymptotic Properties," Review of Economic Studies, Oxford University Press, vol. 63(3), pages 435-463.
    3. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    4. Lewbel, Arthur, 1996. "Aggregation without Separability: A Generalized Composite Commodity Theorem," American Economic Review, American Economic Association, vol. 86(3), pages 524-543, June.
    5. James Banks & Richard Blundell & Arthur Lewbel, 1997. "Quadratic Engel Curves And Consumer Demand," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 527-539, November.
    6. Barten, A. P., 1969. "Maximum likelihood estimation of a complete system of demand equations," European Economic Review, Elsevier, vol. 1(1), pages 7-73.
    7. Lewbel, Arthur, 1987. "Fractional demand systems," Journal of Econometrics, Elsevier, vol. 36(3), pages 311-337, November.
    8. Arthur Lewbel & Serena Ng, 2005. "Demand Systems with Nonstationary Prices," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 479-494, August.
    9. Pollak, Robert A & Wales, Terence J, 1980. "Comparison of the Quadratic Expenditure System and Translog Demand Systems with Alternative Specifications of Demographic Effects," Econometrica, Econometric Society, vol. 48(3), pages 595-612, April.
    10. Blundell, Richard & Pashardes, Panos & Weber, Guglielmo, 1993. "What Do We Learn About Consumer Demand Patterns from Micro Data?," American Economic Review, American Economic Association, vol. 83(3), pages 570-597, June.
    11. Diewert, Walter E & Wales, Terence J, 1987. "Flexible Functional Forms and Global Curvature Conditions," Econometrica, Econometric Society, vol. 55(1), pages 43-68, January.
    12. Moschini, Giancarlo, 1999. "Imposing Local Curvature Conditions in Flexible Demand Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 487-490, October.
    13. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    14. Lewbel, Arthur, 1991. "The Rank of Demand Systems: Theory and Nonparametric Estimation," Econometrica, Econometric Society, vol. 59(3), pages 711-730, May.
    15. Brown, Bryan W & Walker, Mary Beth, 1989. "The Random Utility Hypothesis and Inference in Demand Systems," Econometrica, Econometric Society, vol. 57(4), pages 815-829, July.
    16. McElroy, Marjorie B, 1987. "Additive General Error Models for Production, Cost, and Derived Demand or Share Systems," Journal of Political Economy, University of Chicago Press, vol. 95(4), pages 737-757, August.
    17. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
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    Cited by:

    1. L. Pieroni & D. Lanari & L. Salmasi, 2013. "Food prices and overweight patterns in Italy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(1), pages 133-151, February.
    2. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    3. Asai, Manabu & Caporin, Massimiliano & McAleer, Michael, 2015. "Forecasting Value-at-Risk using block structure multivariate stochastic volatility models," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 40-50.
    4. Apostolos Serletis & Maksim Isakin, 2017. "Stochastic volatility demand systems," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1111-1122, November.
    5. Chia-Lin Chang & Thanchanok Khamkaew & Michael McAleer, 2010. "Estimating Price Effects in an Almost Ideal Demand Model of Outbound Thai Tourism to East Asia," CIRJE F-Series CIRJE-F-735, CIRJE, Faculty of Economics, University of Tokyo.
    6. D. Aristei & Luca Pieroni, 2008. "Cointegration Rank Test and Long Run Specification: A Note on the Robustness of Structural Demand Systems," Working Papers 0809, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    7. Ogura, Manami, 2011. "Testing for structural break in Japanese demand system after the bubble era," Structural Change and Economic Dynamics, Elsevier, vol. 22(3), pages 277-286, September.
    8. Barnett, William A. & Serletis, Apostolos, 2008. "The Differential Approach to Demand Analysis and the Rotterdam Model," MPRA Paper 12319, University Library of Munich, Germany.
    9. Andrea Saayman & Isabel Cortés-Jiménez, 2013. "Modelling Intercontinental Tourism Consumption in South Africa: A Systems-of-Equations Approach," South African Journal of Economics, Economic Society of South Africa, vol. 81(4), pages 538-560, December.
    10. Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014. "Bounding quantile demand functions using revealed preference inequalities," Journal of Econometrics, Elsevier, vol. 179(2), pages 112-127.
    11. David Aristei & Luca Pieroni, 2005. "Estimating the Role of Government Expenditure in Long-run Consumption," Quaderni del Dipartimento di Economia, Finanza e Statistica 13/2005, Università di Perugia, Dipartimento Economia.
    12. Zheng, Xiaoyong & Zhen, Chen, 2008. "Healthy food, unhealthy food and obesity," Economics Letters, Elsevier, vol. 100(2), pages 300-303, August.
    13. Khiabani, Nasser & Hasani, Karim, 2010. "Technical and allocative inefficiencies and factor elasticities of substitution: An analysis of energy waste in Iran's manufacturing," Energy Economics, Elsevier, vol. 32(5), pages 1182-1190, September.
    14. Holt, Matthew T. & Goodwin, Barry K., 2009. "The Almost Ideal and Translog Demand Systems," MPRA Paper 15092, University Library of Munich, Germany.
    15. Andres Silva & Senarath Dharmasena, 2016. "Considering seasonal unit root in a demand system: an empirical approach," Empirical Economics, Springer, vol. 51(4), pages 1443-1463, December.
    16. Resende Filho, M A & Bressan, V G F & Braga, M J & Bressan, A A, 2011. "Sobre a Demanda Agregada por Carnes no Mercado Brasileiro
      [On the Demand for Meat in Brazil]
      ," MPRA Paper 31818, University Library of Munich, Germany.
    17. Acharya, Rajesh H. & Sadath, Anver C., 2017. "Implications of energy subsidy reform in India," Energy Policy, Elsevier, vol. 102(C), pages 453-462.
    18. Pieroni, Luca, 2009. "Does defence expenditure affect private consumption? Evidence from the United States," Economic Modelling, Elsevier, vol. 26(6), pages 1300-1309, November.
    19. Choi, Chi-Young & Hu, Ling & Ogaki, Masao, 2008. "Robust estimation for structural spurious regressions and a Hausman-type cointegration test," Journal of Econometrics, Elsevier, vol. 142(1), pages 327-351, January.
    20. Arthur Lewbel & Serena Ng, 2005. "Demand Systems with Nonstationary Prices," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 479-494, August.
    21. Chi-Young Choi & Ling Hu & Masao Ogaki, 2005. "Structural Spurious Regressions and A Hausman-type Cointegration Test," RCER Working Papers 517, University of Rochester - Center for Economic Research (RCER).

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • D1 - Microeconomics - - Household Behavior

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