Econometric analysis of the sequential probit model with an application to innovation surveys
We study the role of information sources on innovation in a two stage sequential probit model that can be used to analyze survey data in which questions are asked sequentially. Firms can fall into three catagories: (i) they do not innovation; (ii) they introduce a radical innovation on their market; (iii) they imitate an existing innovation. We estimate parameters of this model in a classical framework in which multiple intergrals that arise in the likelihood function are estimated by simulation and in a Bayesian framework in which we use the latent variable structure of the model to implement an operational Gibbs sampler. We show that information sources globally influence the way by which a firm innovates, and we associate a specific information network to each mode of innovation.
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|Date of creation:||01 Apr 2001|
|Contact details of provider:|| Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html|
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