Advanced Search
MyIDEAS: Login

Modelling Income Processes with lots of heterogeneity

Contents:

Author Info

  • Javier Alvarez

    (Alicante University, Spain)

  • Martin Browning

    (Institute of Economics, University of Copenhagen)

  • Mette Ejrnæs

    (Institute of Economics, University of Copenhagen)

Abstract

All empirical models of earnings processes in the literature assume a good deal of homogeneity. For example, all authors assume either that everyone has a unit root process or that everyone has a stationary process. In contrast to this we model earnings processes allowing for lots of heterogeneity between agents. To do this we have to formulate a series of increasingly complex processes which make maximum likelihood or GMM procedures very onerous. To avoid this we use a simulated minimum distance (SMD) estimation procedure. this is the first time that such an estimator has been applied to dynamic panel data models. We fit our models to a variety of statistics including most of those considered by previous investigators (for example, trends in the cross-section variance and transition probabilities from low income states). The principal sample we use is of a group of Danish male workers followed for 16 years. The sample we draw is very homogeneous in terms of observables such as education, age, experience, marital status and all have full year, full time employment during the period considered. Despite this observable homogeneity we find much greater latent heterogeneity than previous investigators. Applying our methods to a more heterogenous sample drawn from the PSID we find a completely different but still very heterogenous process is needed. This suggests that not only do processes vary a lot within groups they also vary between different samples so that detailed modelling is required in each instance. We show that allowance for heterogeneity makes substantial differences to inferences of interest. For example, we find that workers appear to trade off mean for variance in their choice of earnings process. Such a conclusion would be ruled out by a model that did not allow for correlated heterogeneity.

Download Info

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.econ.ku.dk/cam/wp0910/wp0203/2002-01.pdf/
Download Restriction: no

Bibliographic Info

Paper provided by University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics in its series CAM Working Papers with number 2002-01.

as in new window
Length: 42 pages
Date of creation: Nov 2001
Date of revision:
Handle: RePEc:kud:kuieca:2002_01

Contact details of provider:
Postal: Øster Farimagsgade 5, Building 26, DK-1353 Copenhagen K., Denmark
Phone: (45) 35 32 30 74
Fax: +45 35 32 30 00
Email:
Web page: http://www.econ.ku.dk/CAM/
More information through EDIRC

Related research

Keywords:

Other versions of this item:

Find related papers by JEL classification:

References

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. Martin Browning & Annamaria Lusardi, 1995. "Household Saving: Micro Theories and Micro Facts," Department of Economics Working Papers 1995-02, McMaster University.
  2. Moshe Buchinsky & Jennifer Hunt, 1999. "Wage Mobility In The United States," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 351-368, August.
  3. George Hall & John Rust, 2002. "Econometric Methods for Endogenously Sampled Time Series: The Case of Commodity Price Speculation in the Steel Market," Cowles Foundation Discussion Papers 1376, Cowles Foundation for Research in Economics, Yale University.
  4. Costas Meghir & Luigi Pistaferri, 2001. "Income variance dynamics and heterogenity," IFS Working Papers W01/07, Institute for Fiscal Studies.
  5. Mark Yuying An & Ming Liu, 1996. "Using Indirect Inference to Solve the Initial Conditions Problem," Econometrics 9611004, EconWPA.
  6. Javier Alvarez & Martin Browning & Mette Ejrnæs, 2001. "Modelling Income Processes with lots of heterogeneity," CAM Working Papers 2002-01, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
  7. Smith, A A, Jr, 1993. "Estimating Nonlinear Time-Series Models Using Simulated Vector Autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S63-84, Suppl. De.
  8. Lee, Bong-Soo & Ingram, Beth Fisher, 1991. "Simulation estimation of time-series models," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 197-205, February.
  9. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-52, July.
  10. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S85-118, Suppl. De.
  11. Lillard, Lee A & Willis, Robert J, 1978. "Dynamic Aspects of Earning Mobility," Econometrica, Econometric Society, vol. 46(5), pages 985-1012, September.
  12. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54.
  13. Jan F. Kiviet & Garry D.A. Phillips, 1998. "Degrees of freedom adjustment for disturbance variance estimators in dynamic regression models," Econometrics Journal, Royal Economic Society, vol. 1(RegularPa), pages 44-70.
  14. repec:cup:etheor:v:12:y:1996:i:4:p:657-81 is not listed on IDEAS
  15. Peter Gottschalk, 1997. "Inequality, Income Growth, and Mobility: The Basic Facts," Journal of Economic Perspectives, American Economic Association, vol. 11(2), pages 21-40, Spring.
  16. Jeff Dominitz & Charles F. Manski, 1994. "Using Expectations Data to Study Subjective Income Expectations," NBER Working Papers 4937, National Bureau of Economic Research, Inc.
  17. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
  18. Bourguignon, F. & Morrisson, C. & Atkinson, A.B., 1991. "Empirical Studies of Earnings Mobility," DELTA Working Papers 91-14, DELTA (Ecole normale supérieure).
  19. Kiviet, Jan F & Kramer, Walter, 1992. "Bias of SDE 2 in the Linear Regression Model with Correlated Errors," The Review of Economics and Statistics, MIT Press, vol. 74(2), pages 362-65, May.
  20. Gallant, A. Ronald & Tauchen, George, 1996. "Which Moments to Match?," Econometric Theory, Cambridge University Press, vol. 12(04), pages 657-681, October.
  21. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
  22. Francis X. Diebold & Til Schuermann, 1996. "Exact Maximum Likelihood Estimation of Observation-Driven Econometric Models," NBER Technical Working Papers 0194, National Bureau of Economic Research, Inc.
  23. Ulrich K. M¸ller & Graham Elliott, 2003. "Tests for Unit Roots and the Initial Condition," Econometrica, Econometric Society, vol. 71(4), pages 1269-1286, 07.
  24. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January.
  25. Carrasco, Raquel & Arellano, Manuel, 2003. "Binary choice panel data models with predetermined variables," Open Access publications from Universidad Carlos III de Madrid info:hdl:10016/4685, Universidad Carlos III de Madrid.
  26. John M. Abowd & David Card, 1986. "On the Covariance Structure of Earnings and Hours Changes," NBER Working Papers 1832, National Bureau of Economic Research, Inc.
  27. John C. Hause, 1977. "The Covariance Structure of Earnings and the On-The-Job Training Hypothesis," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 6, number 4, pages 335-365 National Bureau of Economic Research, Inc.
  28. Peter Gottschalk & Robert Moffitt, 1994. "The Growth of Earnings Instability in the U.S. Labor Market," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 25(2), pages 217-272.
  29. Christopher D. Carroll & Andrew A. Samwick, 1995. "The Nature of Precautionary Wealth," NBER Working Papers 5193, National Bureau of Economic Research, Inc.
  30. Baker, Michael, 1997. "Growth-Rate Heterogeneity and the Covariance Structure of Life-Cycle Earnings," Journal of Labor Economics, University of Chicago Press, vol. 15(2), pages 338-75, April.
  31. Chamberlain, Gary, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 225-38, January.
  32. Neal, Derek & Rosen, Sherwin, 2000. "Theories of the distribution of earnings," Handbook of Income Distribution, in: A.B. Atkinson & F. Bourguignon (ed.), Handbook of Income Distribution, edition 1, volume 1, chapter 7, pages 379-427 Elsevier.
  33. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
  34. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
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 in new window

Cited by:
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.

Lists

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

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:kud:kuieca:2002_01

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

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.