IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Heterogeneity in Consumer Demands and the Income Effect: Evidence from Panel Data

  • Mette Christensen

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: http://www.socialsciences.manchester.ac.uk/medialibrary/economics/discussionpapers/EDP-0714.pdf
Download Restriction: no

Paper provided by Economics, The University of Manchester in its series The School of Economics Discussion Paper Series with number 0714.

as
in new window

Length:
Date of creation: 2007
Date of revision:
Handle: RePEc:man:sespap:0714
Contact details of provider: Postal: Manchester M13 9PL
Phone: (0)161 275 4868
Fax: (0)161 275 4812
Web page: http://www.socialsciences.manchester.ac.uk/subjects/economics/

More information through EDIRC

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. Arellano, Manuel & Hansen, Lars Peter & Sentana, Enrique, 2012. "Underidentification?," Journal of Econometrics, Elsevier, vol. 170(2), pages 256-280.
  2. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
  3. Aasness, Jorgen & Biorn, Erik & Skjerpen, Terje, 1993. "Engel Functions, Panel Data, and Latent Variables," Econometrica, Econometric Society, vol. 61(6), pages 1395-1422, November.
  4. 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.
  5. 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.
  6. Rosa L. Matzkin, 2003. "Nonparametric Estimation of Nonadditive Random Functions," Econometrica, Econometric Society, vol. 71(5), pages 1339-1375, 09.
  7. Grandmont Jean-michel, 1985. "Distributions of preferences and the "law of demand"," CEPREMAP Working Papers (Couverture Orange) 8513, CEPREMAP.
  8. Richard Blundell & Alan Duncan & Costas Meghir, 1998. "Estimating Labor Supply Responses Using Tax Reforms," Econometrica, Econometric Society, vol. 66(4), pages 827-862, July.
  9. Carrasco, Raquel & Labeaga Azcona, J Maria & López-Salido, J David, 2002. "Consumption and Habits: Evidence from Panel Data," CEPR Discussion Papers 3520, C.E.P.R. Discussion Papers.
  10. Richard Blundell & Martin Browning & Ian Crawford, 1997. "Non-parametric Engel curves and revealed preferences," IFS Working Papers W97/14, Institute for Fiscal Studies.
  11. 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.
  12. Walter Beckert, 2007. "Specification and Identification of Stochastic Demand Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(6), pages 669-683.
  13. 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.
  14. 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.
  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. 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.
  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.
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:man:sespap:0714. 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: (Marianne Sensier)

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.