TY - JOUR

T1 - Estimating Input Complementarities with Unobserved Heterogeneity

T2 - Evidence from Ethiopia

AU - Abay, Kibrom Araya

AU - Berhane, Guush

AU - Taffesse, Alemayehu Seyoum

AU - Abay, Kibrewossen

AU - Koru, Bethelhem

PY - 2017/9/21

Y1 - 2017/9/21

N2 - 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.

AB - 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.

KW - Input complementarity

KW - maximum simulated likelihood approaches

KW - random coefficients multivariate probit

KW - technology adoption

KW - unobserved heterogeneity

U2 - 10.1111/1477-9552.12244

DO - 10.1111/1477-9552.12244

M3 - Journal article

AN - SCOPUS:85030322892

VL - 69

SP - 495

EP - 517

JO - Journal of Agricultural Economics

JF - Journal of Agricultural Economics

SN - 0021-857X

IS - 2

ER -