Estimating the Neighborhood Influence on Decision Makers: Theory and an Application on the Analysis of Innovation Decisions
AbstractWhen making decisions, agents tend to make use of decisions others have made in similar situations. Ignoring this behavior in empirical models can be interpreted as a problem of omitted variables and may seriously bias parameter estimates and harm inference. We suggest a possibility of integrating such outside in uences into models of discrete choice decisions by defining an abstract space in which agents with similar characteristics are neighbors who possibly in uence each other. In order to correct for correlations between the characteristics, the design of this space allows for nonorthogonality of its dimensions. Several Monte Carlo simulations show the small sample properties of spatial models with binary choice. When applying the estimator to innovation decisions data of German firms, we find evidence for the existence of neighborhood effects.
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Bibliographic InfoPaper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 01-04.
Length: 23 Pages
Date of creation: Jun 2001
Date of revision:
Other versions of this item:
- Hautsch, Nikolaus & Klotz, Stefan, 2003. "Estimating the neighborhood influence on decision makers: theory and an application on the analysis of innovation decisions," Journal of Economic Behavior & Organization, Elsevier, vol. 52(1), pages 97-113, September.
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