Count-data regression models of the time to adopt new technologies

Bruce Mcwilliams, Yacov Tsur, Eithan Hochman and David Zilberman

Applied Economics Letters, 1998, vol. 5, issue 6, 369-373

Abstract: This paper presents a framework for interpreting and using the count-data model for estimating the time of technology adoption. The Bernoulli trials of the negative binomial model are interpreted as the stages involved in a potential adopter learning and updating information relevant to a new technology. Empirically, the paper estimates the Poisson, the generalized negative binomial, and the geometric models in order to identify the determinants of computer adoption on farms in California.

Date: 1998
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Persistent link: https://EconPapers.repec.org/RePEc:taf:apeclt:v:5:y:1998:i:6:p:369-373

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DOI: 10.1080/135048598354744

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