Innovation and market creation

Cross bred cow adoption is an important and potent policy variable precipitating subsistence household entry into emerging bulk markets. This paper focuses on the design of policies that create and sustain milk-market expansion among a sample of households in the Ethiopian highlands. In this context it is desirable to measure a household's `proximity' to market in terms of the level of deficiency of an essential input. This problem is compounded by four factors. One is the existence of cross bred cow numbers (count data) as an important, endogenous decision by the household; second is the lack of a multivariate generalization of the Poisson regression model; third is the censored nature of the milk sales data (sales from non participating households are, essentially, censored at zero); and fourth is an important simultaneity that exists between the decision to adopt a cross bred cow, the decision about how much nulls to produce, the decision about how much milk to consume and the decision to market that milk which is produced but not consumed internally by the household. Routine application of Gibbs sampling and data augmentation overcome these problems in a relatively straightforward manner. The authors model the count data from two sites close to Addis Ababa in a latent, categorical variable setting with known bin boundaries. The single equation model is then extended to a simultaneous equations setting that accommodates the important covariance between crossbred cow adoption, milk output, and milk sales equations. Section two presents a brief background to the problems motivating statistical analysis. Section three presents traditional Poisson regression and section four presents the latent variable model. Section five presents the multivariate model, section six computes distance estimates and section seven concludes.