IDEAS home Printed from https://ideas.repec.org/a/cje/issued/v37y2004i3p613-628.html
   My bibliography  Save this article

Aggregation effects on price and expenditure elasticities in a quadratic almost ideal demand system

Author

Listed:
  • Frank Denton
  • Dean Mountain

Abstract

While it is well known that demand elasticities calculated at the macro level will in general differ from those calculated at the micro level because of aggregation effects, there remain the questions of how large the effects are and how they vary with the degree of inequality in the income distribution. We explore these questions with models based on a quadratic version of the Almost Ideal Demand System. We investigate the elasticity differences theoretically and then calibrate the models and generate numerical results, using income data for seven countries with widely different distributions. The aggregation effects are found generally to be rather small, even with highly unequal income distributions.

Suggested Citation

  • Frank Denton & Dean Mountain, 2004. "Aggregation effects on price and expenditure elasticities in a quadratic almost ideal demand system," Canadian Journal of Economics, Canadian Economics Association, vol. 37(3), pages 613-628, August.
    • Handle: RePEc:cje:issued:v:37:y:2004:i:3:p:613-628
    as

    Download full text from publisher

    File URL: https://www.jstor.org/stable/3696008
    Download Restriction: only available to JSTOR subscribers
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lewbel, Arthur, 1990. "Income distribution movements and aggregate money illusion," Journal of Econometrics, Elsevier, vol. 43(1-2), pages 35-42.
    2. O'Higgins, Michael & Schmaus, Guenther & Stephenson, Geoffrey, 1989. "Income Distribution and Redistribution: A Microdata Analysis for Seven Countries," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 35(2), pages 107-131, June.
    3. Denton, Frank T. & Mountain, Dean C., 2001. "Income distribution and aggregation/disaggregation biases in the measurement of consumer demand elasticities," Economics Letters, Elsevier, vol. 73(1), pages 21-28, October.
    4. Stoker, Thomas M, 1986. "Simple Tests of Distributional Effects on Macroeconomic Equations," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 763-795, August.
    5. Stoker, Thomas M, 1984. "Completeness, Distribution Restrictions, and the Form of Aggregate Functions," Econometrica, Econometric Society, vol. 52(4), pages 887-907, July.
    6. Stoker, Thomas M, 1993. "Empirical Approaches to the Problem of Aggregation Over Individuals," Journal of Economic Literature, American Economic Association, vol. 31(4), pages 1827-1874, December.
    7. 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.
    8. 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.
    9. Arthur Lewbel, 1992. "Aggregation with Log-Linear Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 59(3), pages 635-642.
    10. Lewbel, Arthur, 1991. "The Rank of Demand Systems: Theory and Nonparametric Estimation," Econometrica, Econometric Society, vol. 59(3), pages 711-730, May.
    11. Denton, Frank T & Mountain, Dean C & Spencer, Byron G, 1999. "Age, Trend, and Cohort Effects in a Macro Model of Canadian Expenditure Patterns," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 430-443, October.
    12. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    13. Mchel O'Higgins & Guenther Schmaus & Geofrey Stephenson, 1989. "Income Distribution And Redistribution: A Microdata Analysis For Seven Countries," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 35(2), pages 107-131, June.
    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. Frank T. Denton & Dean C. Mountain, 2007. "Exploring the Effects of Aggregation Error in the Estimation of Consumer Demand Elasticities," Social and Economic Dimensions of an Aging Population Research Papers 226, McMaster University.
    2. Frank T. Denton & Dean C. Mountain & Byron G Spencer, 2006. "Errors of aggregation and errors of specification in a consumer demand model: a theoretical note," Canadian Journal of Economics, Canadian Economics Association, vol. 39(4), pages 1398-1407, November.
    3. Frank T. Denton & Dean C. Mountain, 2016. "Biases in consumer elasticities based on micro and aggregate data: an integrated framework and empirical evaluation," Empirical Economics, Springer, vol. 50(2), pages 531-560, March.
    4. Ingvild Almas, 2012. "International Income Inequality: Measuring PPP Bias by Estimating Engel Curves for Food," American Economic Review, American Economic Association, vol. 102(2), pages 1093-1117, April.
    5. Frank Denton & Dean Mountain, 2014. "The implications of mean scaling for the calculation of aggregate consumer elasticities," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(3), pages 297-314, September.
    6. Frank Denton & Dean Mountain & Byron Spencer, 2006. "Age, Retirement, and Expenditure Patterns: An Econometric Study of Older Households," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 34(4), pages 421-434, December.
    7. Frank T. Denton & Dean C. Mountain, 2011. "Aggregation and Other Biases in the Calculation of Consumer Elasticities for Models of Arbitrary Rank," Quantitative Studies in Economics and Population Research Reports 447, McMaster University.
    8. Bente Halvorsen & Bodil M. Larsen, 2006. "Aggregation with price variation and heterogeneity across consumers," Discussion Papers 489, Statistics Norway, Research Department.
    9. Tite Ehuitché Beke, 2017. "Analysis of Substitute Products in the Demand for Food Products in Côte d'Ivoire," Working Papers 330, African Economic Research Consortium, Research Department.
    10. Bente Halvorsen & Bodil M. Larsen, 2013. "How serious is the aggregation problem? An empirical illustration," Applied Economics, Taylor & Francis Journals, vol. 45(26), pages 3786-3794, September.
    11. Baek, Ji Won, 2016. "The effects of the Internet and mobile services on urban household expenditures: The case of South Korea," Telecommunications Policy, Elsevier, vol. 40(1), pages 22-38.
    12. Bente Halvorsen & Bodil M. Larsen, 2008. "The Role of Heterogeneous Demand for Temporal and Structural Aggregation Bias," Discussion Papers 537, Statistics Norway, Research Department.
    13. Zhang, Aihua & Lv, Jia & Kong, Ying, 2017. "The Effects of the Internet and Mobile Services on Urban Household Expenditures," 14th ITS Asia-Pacific Regional Conference, Kyoto 2017: Mapping ICT into Transformation for the Next Information Society 168554, International Telecommunications Society (ITS).
    14. Denton, Frank T. & Mountain, Dean C., 2011. "Exploring the effects of aggregation error in the estimation of consumer demand elasticities," Economic Modelling, Elsevier, vol. 28(4), pages 1747-1755, July.
    15. Bente Halvorsen, 2006. "When can micro properties be used to predict aggregate demand?," Discussion Papers 452, Statistics Norway, Research Department.

    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. Frank T. Denton & Dean C. Mountain, 2004. "Aggregation effects on price and expenditure elasticities in a quadratic almost ideal demand system," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 37(3), pages 613-628, August.
    2. Denton, Frank T. & Mountain, Dean C., 2011. "Exploring the effects of aggregation error in the estimation of consumer demand elasticities," Economic Modelling, Elsevier, vol. 28(4), pages 1747-1755, July.
    3. Frank T. Denton & Dean C. Mountain, 2007. "Exploring the Effects of Aggregation Error in the Estimation of Consumer Demand Elasticities," Social and Economic Dimensions of an Aging Population Research Papers 226, McMaster University.
    4. Frank T. Denton & Dean C. Mountain, 2016. "Biases in consumer elasticities based on micro and aggregate data: an integrated framework and empirical evaluation," Empirical Economics, Springer, vol. 50(2), pages 531-560, March.
    5. Denton, Frank T. & Mountain, Dean C., 2001. "Income distribution and aggregation/disaggregation biases in the measurement of consumer demand elasticities," Economics Letters, Elsevier, vol. 73(1), pages 21-28, October.
    6. Frank Denton & Dean Mountain, 2014. "The implications of mean scaling for the calculation of aggregate consumer elasticities," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(3), pages 297-314, September.
    7. Frank T. Denton & Dean C. Mountain, 2011. "Aggregation and Other Biases in the Calculation of Consumer Elasticities for Models of Arbitrary Rank," Quantitative Studies in Economics and Population Research Reports 447, McMaster University.
    8. Frank T. Denton & Dean C. Mountain & Byron G Spencer, 2006. "Errors of aggregation and errors of specification in a consumer demand model: a theoretical note," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 39(4), pages 1398-1407, November.
    9. LaFrance, Jeffrey T., 2008. "The structure of US food demand," Journal of Econometrics, Elsevier, vol. 147(2), pages 336-349, December.
    10. Giorgio Fagiolo, 2001. "Engel Curves Specification in an Artificial Model of Consumption Dynamics with Socially Evolving Preferences," LEM Papers Series 2001/16, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    11. Bente Halvorsen & Bodil M. Larsen, 2008. "The Role of Heterogeneous Demand for Temporal and Structural Aggregation Bias," Discussion Papers 537, Statistics Norway, Research Department.
    12. Hildenbrand, Werner & Kneip, Alois, 2005. "Aggregate behavior and microdata," Games and Economic Behavior, Elsevier, vol. 50(1), pages 3-27, January.
    13. Toshinobu Matsuda, 2006. "A trigonometric flexible consumer demand system," Canadian Journal of Economics, Canadian Economics Association, vol. 39(1), pages 145-162, February.
    14. Douglas Fisher & Adrian R. Fleissig & Apostolos Serletis, 2006. "An Empirical Comparison of Flexible Demand System Functional Forms," World Scientific Book Chapters, in: Money And The Economy, chapter 13, pages 247-277, World Scientific Publishing Co. Pte. Ltd..
    15. Lyssiotou, Panayiota & Pashardes, Panos & Stengos, Thanasis, 2002. "Nesting quadratic logarithmic demand systems," Economics Letters, Elsevier, vol. 76(3), pages 369-374, August.
    16. Matteo Barigozzi & Alessio Moneta, 2016. "Identifying the Independent Sources of Consumption Variation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 420-449, March.
    17. Gallet, Craig A., 2010. "The income elasticity of meat: a meta-analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), pages 1-14.
    18. Zapata, Hector O. & Sulgham, Anil K., 2006. "A Semiparametric Approach to Estimate Engel curves using the US Micro Data," 2006 Annual meeting, July 23-26, Long Beach, CA 21092, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Gong, X. & van Soest, A.H.O. & Zhang, P., 2000. "Sexual Bias and Household Consumption : A Semiparametic Analysis of Engel curves in Rural China," Other publications TiSEM 896cf4d1-37e5-490b-9e05-4, Tilburg University, School of Economics and Management.
    20. Pedro H. Albuquerque, 2003. "A practical log-linear aggregation method with examples: heterogeneous income growth in the USA," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 665-678.

    More about this item

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • D10 - Microeconomics - - Household Behavior - - - General

    Statistics

    Access and download statistics

    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:cje:issued:v:37:y:2004:i:3:p:613-628. 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: Prof. Werner Antweiler (email available below). General contact details of provider: https://edirc.repec.org/data/ceaaaea.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.