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Estimating Input Complementarities with Unobserved Heterogeneity: Evidence from Ethiopia
Author(s) -
Abay Kibrom A.,
Berhane Guush,
Taffesse Alemayehu Seyoum,
Abay Kibrewossen,
Koru Bethelhem
Publication year - 2018
Publication title -
journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.157
H-Index - 61
eISSN - 1477-9552
pISSN - 0021-857X
DOI - 10.1111/1477-9552.12244
Subject(s) - complementarity (molecular biology) , econometrics , economics , multivariate probit model , probit model , probit , multivariate statistics , random effects model , meta analysis , statistics , mathematics , medicine , genetics , biology
The level of technology adoption is often characterised as low in Africa. Recent evidence, however, points to the coexistence of substantial heterogeneity across farm households and the lack of a suitable mix of inputs for farmers to take advantage of input complementarities. We use a random coefficients multivariate probit model to quantify the complementarities between agricultural inputs and alternative forms of unobserved heterogeneity effects in modeling farmers' technology adoption decisions. The empirical analysis reveals that, conditional on various types of unobserved heterogeneity effects, farmers' technology adoption decisions exhibit strong complementarity for some inputs. The analysis also reveals substantial unobserved heterogeneity effects. We show that ignoring these behavioural features (unobserved heterogeneity and input complementarity) has important implications in quantifying the effect of some policy interventions that are meant to facilitate technology adoption. In particular, ignoring these features leads to significant overestimation of the effectiveness of extension services.