Hostname: page-component-848d4c4894-nr4z6 Total loading time: 0 Render date: 2024-05-15T11:59:04.671Z Has data issue: false hasContentIssue false
  • English
  • Français

The Deletion of Variables From Regression Models Based on Tests of Significance: A Statistical and Moral Issue*

Published online by Cambridge University Press:  28 April 2015

David L. Debertin  and
R. J. Freund
David L. Debertin
Affiliation:
Department of Agricultural Economics, University of Kentucky
R. J. Freund
Affiliation:
Institute of Statistics atTexas A&M University
Get access

Extract

The purpose of this paper is to illustrate some of the dangers inherent in use of statistical tests as a criterion for deleting variables from regression models. The deletion of variables from regression models based on t or F tests of regression coefficients has been a procedure widely followed by applied economists and other researchers. When economic theory does not provide an adequate conceptual basis for rigorous a priori specification of the regression model, one approach to model specification has been to include in the regression equation all variables thought to be “somehow” related to the dependent variable of interest. Subsets of variables with statistically significant coefficients are identified, with the aid of a stepwise regression routine. Truncated models consisting of only those variables with statistically significant regression coefficients are sometimes presented in the published research without reference to the initial data dredging that took place.

Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 7 , Issue 1 , July 1975 , pp. 211 - 216
Copyright
Copyright © Southern Agricultural Economics Association 1975

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

The authors are indebted for the assistance provided by E. W. Kehrberg, T. K. White, J. Havlicek, G. L. Bradford, Alan J. Randall, Eldon D. Smith and L. D. Jones. Any errors remain the responsibility of the authors.

References

[1] Draper, Norman and Smith, H.. Applied Regression Analysis, John Wiley and Sons, New York, 1966.Google Scholar
[2] Egbert, Alvin C. “An Aggregate Model of Agriculture — Empirical Estimates and Some Policy Implications,” Journal of Farm Economics. 51: 71–86, February 1969.Google Scholar
[3] Gustman, Alan L., and Pidot, George B. Jr. “Interactions Between Educational Spending and Student Enrollment,” Journal of Human Resources. 8: 3–23, Winter, 1973.CrossRefGoogle Scholar
[4] Ladd, George W. “Federal Milk Marketing Order Provisions, Effects on Producer Prices and Intermarket Price Relationships,” Journal of Farm Economics. 51: 625–642, August 1969.Google Scholar
[5] Sahota, Gian S. “Efficiency of Resource Allocation in Indian Agriculture,” Journal of Farm Economics. 50: 584–605, August 1968.Google Scholar
[6] Schutzer, W. A., and Hallberg, M. C.. “Impact of Water Recreational Development on Rural Property Values,” Journal of Farm Economics. 50: 584–605, August 1968.Google Scholar
[7] Scott, John T., and Heady, Earl O.. “Regional Demand for Farm Buildings in the United States,” Journal of Farm Economics. 49: 184–198, February 1967.CrossRefGoogle Scholar
[8] Selvin, Hanan C., and Alan, Stuart. “Data Dredging Procedures in Survey Analysis,” The American Statistician 20: 20–23, June 1966.Google Scholar
[9] Wallace, T. D. and Ashar, V. G.. “Sequential Methods in Model Construction,” Review of Economics and Statistics. 54: 172–178, May 1972.CrossRefGoogle Scholar