Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We describe an econometric procedure to model transitions in Markov chains whose state space is finite and classification stems from observed continuous variables. We show how stationary and non-stationary transition probabilities as well as the marginal effects of continuous and dichotomous variables determining transition can be estimated. The model resembles the ordered probit approach used in Epstein et al. (2006) but allows for the differences in the nature of the dependent variable and suggests some very important extensions pertaining to more meaningful representation of parameter estimates and the simultaneous construction of transition matrices.