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Implementing restricted least squares in linear models

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  • J. Haisken-DeNew

    (RWI Essen)

Abstract

The presentation illustrates the user-written program hds97, which implements the restricted least squares procedure as described by Haisken-DeNew and Schmidt (1997). Log wages are regressed on a group of k-1 industry/region/job/etc. dummies. The kth dummy is the omitted reference dummy. Using RLS, all k dummy coefficients and standard errors are reported. The coefficients are interpreted as percent-point deviations from the industry weighted average. An overall measure of dispersion is also reported. This ado-file corrects problems with the Krueger and Summers (1988) Econometrica methodology of overstated differential standard errors and understated overall dispersion. General comments: The coefficients of continuous variables are not affected by hds97. Also, all results calculated in hds97 are independent of the choice of the reference category. By the way, for all dummy variable sets having only two outcomes, i.e., male/female, the t-values of the hds97 adjusted coefficients are always equal in magnitude but opposite in sign.

Suggested Citation

  • J. Haisken-DeNew, 2006. "Implementing restricted least squares in linear models," German Stata Users' Group Meetings 2006 06, Stata Users Group.
  • Handle: RePEc:boc:dsug06:06
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    File URL: http://fmwww.bc.edu/repec/dsug2006/RLS_Haisken_DeNew.ppt
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