IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Comparing Standard Regression Modeling to Ensemble Modeling: How Data Mining Software Can Improve Economists' Predictions

Listed author(s):
  • Joyce P. Jacobsen

    ()

    (Department of Economics, Wesleyan University)

  • Laurence M. Levin

    (VISA)

  • Zachary Tausanovitch

    (Network for Teaching Entrepreneurship)

Economists’ wariness of data mining may be misplaced, even in cases where economic theory provides a well-specified model for estimation. We discuss how new data mining/ensemble modeling software, for example the program TreeNet, can be used to create predictive models. We then show how for a standard labor economics problem, the estimation of wage equations, TreeNet outperforms standard OLS regression in terms of lower prediction error. Ensemble modeling also resists the tendency to overfit data. We conclude by considering additional types of economic problems that are well-suited to use of data mining techniques.

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://repec.wesleyan.edu/pdf/jjacobsen/2014003_jacobsen.pdf
Download Restriction: no

Paper provided by Wesleyan University, Department of Economics in its series Wesleyan Economics Working Papers with number 2014-003.

as
in new window

Length: 25 pages
Date of creation: Dec 2014
Handle: RePEc:wes:weswpa:2014-003
Contact details of provider: Postal:
PAC 123, 238 Church Street, Middletown, CT 06459-0007

Phone: (860)685-2340
Fax: (860)685-2781
Web page: http://www.wesleyan.edu/econ/

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. James H. Stock, 2010. "The Other Transformation in Econometric Practice: Robust Tools for Inference," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 83-94, Spring.
  2. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
  3. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
  4. Matthias Schonlau, 2005. "Boosted regression (boosting): An introductory tutorial and a Stata plugin," Stata Journal, StataCorp LP, vol. 5(3), pages 330-354, September.
  5. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
  6. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
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:wes:weswpa:2014-003. 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: (Manolis Kaparakis)

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.