Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The innovation adoption literature has focused primarily on a producer's decision of whether and how much to adopt. An equally pertinent question is when to adopt, because in the case of new technologies it often 'pays to wait' for more information. We propose a double-limit hurdle model to analyse adoption intensity and inertia in the context of a divisible technology. The proposed framework incorporates probit or Tobit models as testable special cases. A maximum likelihood estimation framework is set out and generalized to account for heteroscedastic errors. The empirical analysis, which uses household-level data from India's semi-arid tropics, provides new insights into the factors influencing adoption inertia and intensity.