Interaction Effects and Difference-in-Difference Estimation in Loglinear Models / John Mullahy.

By:

Mullahy, John

Contributor(s):

National Bureau of Economic Research

Material type: Text

TextSeries: Technical Working Paper Series (National Bureau of Economic Research) ; no. t0245.Publication details: Cambridge, Mass. National Bureau of Economic Research 1999.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: In applied econometric work, analysts are concerned often with estimation of and inferences about interaction effects, e.g. 'Does the magnitude of the effect of z1 on y depend on z2? ' This paper develops tests for and proper interpretation of various forms of interaction effects in one prominent class of regression models loglinear models for which the nature of estimated interaction effects has not always been given due attention. The results obtained here have a direct bearing on the interpretation of so-called difference-in-difference estimates when these are obtained using loglinear models. An empirical example of the impacts of health insurance and chronic illness on prescription drug utilization underscores the importance of these issues in practical settings.

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November 1999.

In applied econometric work, analysts are concerned often with estimation of and inferences about interaction effects, e.g. 'Does the magnitude of the effect of z1 on y depend on z2? ' This paper develops tests for and proper interpretation of various forms of interaction effects in one prominent class of regression models loglinear models for which the nature of estimated interaction effects has not always been given due attention. The results obtained here have a direct bearing on the interpretation of so-called difference-in-difference estimates when these are obtained using loglinear models. An empirical example of the impacts of health insurance and chronic illness on prescription drug utilization underscores the importance of these issues in practical settings.