Regression specifications in applied econometrics frequently employ regressors that are defined as the product of two other regressors to form an interaction. Unfortunately, the interpretation of the results of these models is not as straight forward as in the linear case. In this paper, we present a method for drawing inferences for interaction models by defining the partial influence function. We present an example that demonstrates how one may draw new inferences by constructing the confidence intervals for the partial influence functions based on the traditional published findings for regressions with interaction terms.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. 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.
Length: 13 pages Date of creation: 2007 Date of revision: Handle: RePEc:mlb:wpaper:1015
Contact details of provider: Postal: Department of Economics, The University of Melbourne, 5th Floor, Economics and Commerce Building, Victoria, 3010, Australia Phone: +61 3 8344 5289 Fax: +61 3 8344 6899 Email: Web page: http://www.economics.unimelb.edu.au More information through EDIRC
For technical questions regarding this item, or to correct its listing, contact: (Colemann Leong).
Find related papers by JEL classification: C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
This paper has been announced in the following NEP Reports:
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.: