IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Heterogeneity in consumer demands and the income effect: evidence from panel data

  • Mette Lunde Christensen


    (Institute of Economics, University of Copenhagen)

All micro studies of demand are based on using time series cross sectional data. Because in such data each household is only observed once, it is only under strong identifying restrictions that one can interpret the coefficients on consumer behavior. For example, if tastes are correlated with income, the usual estimates of income elasticities from cross sectional data are biased. In contrast, panel data allows identification of the coefficients on consumer behavior in the presence of unobservable correlated heterogeneity. In this paper we make use of a unique Spanish panel data set on household expenditures to test whether unobservable heterogeneity in household demands (taste) is correlated with total expenditures (income). We find that tastes are indeed correlated with income for half of the goods considered.

(This abstract was borrowed from another version of this item.)

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: no

Paper provided by International Conferences on Panel Data in its series 10th International Conference on Panel Data, Berlin, July 5-6, 2002 with number C4-1.

in new window

Date of creation: Mar 2002
Date of revision:
Handle: RePEc:cpd:pd2002:c4-1
Contact details of provider:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Richard Blundell & Alan Duncan & Costas Meghir, 1998. "Estimating Labor Supply Responses Using Tax Reforms," Econometrica, Econometric Society, vol. 66(4), pages 827-862, July.
  2. Browning, Martin & Meghir, Costas, 1991. "The Effects of Male and Female Labor Supply on Commodity Demands," Econometrica, Econometric Society, vol. 59(4), pages 925-51, July.
  3. Martin Browning & M. Dolores Collado, 2004. "Habits and Heterogeneity in Demands: a Panel Data Analysis," CAM Working Papers 2004-18, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
  4. Grandmont, Jean-Michel, 1987. "Distributions of Preferences and the 'Law of Demand.'," Econometrica, Econometric Society, vol. 55(1), pages 155-61, January.
  5. Rosa L. Matzkin, 2003. "Nonparametric Estimation of Nonadditive Random Functions," Econometrica, Econometric Society, vol. 71(5), pages 1339-1375, 09.
  6. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
  7. Martin Browning & M. Dolores Collado, 2001. "The Response of Expenditures to Anticipated Income Changes: Panel Data Estimates," American Economic Review, American Economic Association, vol. 91(3), pages 681-692, June.
  8. Aasness, Jorgen & Biorn, Erik & Skjerpen, Terje, 1993. "Engel Functions, Panel Data, and Latent Variables," Econometrica, Econometric Society, vol. 61(6), pages 1395-1422, November.
  9. Raquel Carrasco & José M. Labeaga & J. David López-Salido, 2005. "Consumption and Habits: Evidence from Panel Data," Economic Journal, Royal Economic Society, vol. 115(500), pages 144-165, 01.
  10. Walter Beckert, 2007. "Specification and Identification of Stochastic Demand Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(6), pages 669-683.
  11. Manuel Arellano & Lars P. Hansen & Enrique Sentana, 2000. "Underidentification?," Econometric Society World Congress 2000 Contributed Papers 1824, Econometric Society.
  12. Grandmont Jean-michel, 1991. "Transformation of the commodity space, behavioral heterogeneity and the aggregation problem," CEPREMAP Working Papers (Couverture Orange) 9114, CEPREMAP.
  13. Walter Beckert & Richard Blundell, 2004. "Invertibility of Nonparametric Stochastic Demand Functions," Birkbeck Working Papers in Economics and Finance 0406, Birkbeck, Department of Economics, Mathematics & Statistics.
  14. Richard Blundell & Martin Browning & Ian Crawford, 1998. "Nonparametric Engel Curves and Revealed Preference," Discussion Papers 99-07, University of Copenhagen. Department of Economics.
  15. 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 570-97, June.
  16. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762, November.
  17. 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.
  18. Donald J. Brown & Rosa L. Matzkin, 1998. "Estimation of Nonparametric Functions in Simultaneous Equations Models, with an Application to Consumer Demand," Cowles Foundation Discussion Papers 1175, Cowles Foundation for Research in Economics, Yale University.
  19. Brown, Bryan W & Walker, Mary Beth, 1989. "The Random Utility Hypothesis and Inference in Demand Systems," Econometrica, Econometric Society, vol. 57(4), pages 815-29, July.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:cpd:pd2002:c4-1. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sune Karlsson)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.