Publikation:

Estimating the neighborhood influence on decision makers : theory and an application on the analysis of innovation decisions

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dp01_04.pdf
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2001

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Hautsch, Nikolaus
Klotz, Stefan

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Zusammenfassung

When making decisions, agents tend to make use of decisions oth- ers 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 ofintegrat- ing 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 ofits dimensions. Several Monte Carlo simulations show the small sample properties of spatial models with binary choice. When applying the estimator to inno- vation decisions data of German firms, we find evidence for the existence of neighborhood effects.

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Fachgebiet (DDC)
330 Wirtschaft

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decision models, discrete choice, neighborhood in uence, spatial econometrics, social space, Euclidean measure

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ISO 690HAUTSCH, Nikolaus, Stefan KLOTZ, 2001. Estimating the neighborhood influence on decision makers : theory and an application on the analysis of innovation decisions
BibTex
@techreport{Hautsch2001Estim-11757,
  year={2001},
  series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie},
  title={Estimating the neighborhood influence on decision makers : theory and an application on the analysis of innovation decisions},
  number={2001/04},
  author={Hautsch, Nikolaus and Klotz, Stefan}
}
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