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The rank and model specification of demand systems: an empirical analysis using United States microdata

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  • Christopher J. Nicol

Abstract

A rank-three demand system is estimated with United States Consumer Expenditure Survey microdata. A unique price data set is also used, which permits the analysis of effects of systematic errors in price variables. It is found that errors in price variables bias test results for the rank-three hypothesis, in particular towards rejection. Other test results are affected to a lesser extent. Estimating smaller systems of demand equations, even when conditioning on excluded goods, yields significantly different results. Another important conclusion is that model specification is statistically significantly different for households of varying family sizes and housing tenure statuses.

Suggested Citation

  • Christopher J. Nicol, 2001. "The rank and model specification of demand systems: an empirical analysis using United States microdata," Canadian Journal of Economics, Canadian Economics Association, vol. 34(1), pages 259-289, February.
    • Handle: RePEc:cje:issued:v:34:y:2001:i:1:p:259-289
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    Citations

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    Cited by:

    1. Panayiota Lyssiotou, 2003. "On estimating the cost of characteristics indices from consumer demand analysis," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 36(2), pages 326-349, May.
    2. Slesnick, Daniel T., 2005. "Prices and demand: New evidence from micro data," Economics Letters, Elsevier, vol. 89(3), pages 269-274, December.
    3. Tiezzi, Silvia & Verde, Stefano F., 2016. "Differential demand response to gasoline taxes and gasoline prices in the U.S," Resource and Energy Economics, Elsevier, vol. 44(C), pages 71-91.
    4. Fortuna, Natercia, 2008. "Local rank tests in a multivariate nonparametric relationship," Journal of Econometrics, Elsevier, vol. 142(1), pages 162-182, January.
    5. Xavier Labandeira & José M. Labeaga & Miguel Rodríguez, 2006. "A Residential Energy Demand System for Spain," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 87-112.
    6. Boonsaeng, Tullaya & Carpio, Carlos E., 2017. "Budget Allocation Patterns of American Household across Income Level in the 21 Century," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258245, Agricultural and Applied Economics Association.
    7. Tri Wahyu Cahyono & Hiromi Tokuda, 2024. "New Capital Relocation of Indonesia: Estimating Food Demand in East Kalimantan and Jakarta," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 15(9), pages 1-26, April.
    8. Desiderio Romero-Jordán & José Félix Sanz-Sanz, 2009. "Energy Taxes and Household Compliance with the Kyoto Protocol," Public Finance Review, , vol. 37(2), pages 142-169, March.
    9. Abiodun Elijah Obayelu & V.O. Okoruwa & O.I.Y. Ajani, 2009. "Cross‐sectional analysis of food demand in the North Central, Nigeria," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 1(2), pages 173-193, January.
    10. Nicol, C. J., 2003. "Elasticities of demand for gasoline in Canada and the United States," Energy Economics, Elsevier, vol. 25(2), pages 201-214, March.
    11. Donald, Stephen G. & Fortuna, Natércia & Pipiras, Vladas, 2011. "Local and Global Rank Tests for Multivariate Varying-Coefficient Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(2), pages 295-306.
    12. W D A Bryant, 2009. "General Equilibrium:Theory and Evidence," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6875, August.
    13. Lyssiotou, Panayiota, 2012. "Demographics and demand: Evaluation of alternative functional forms," Economics Letters, Elsevier, vol. 117(3), pages 627-631.
    14. Takashi Unayama, 2006. "The Engel curve for alcohol and the rank of demand systems," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1019-1038.
    15. Paul Oslington, 2012. "General Equilibrium: Theory and Evidence," The Economic Record, The Economic Society of Australia, vol. 88(282), pages 446-448, September.

    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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