Farm households' participation in rural non-farm employment in post-war Rwanda: Drivers and policy implications

Abstract

Despite the post-war government's unprecedented efforts to stimulate growth of the rural non-farm (RNF) sector in Rwanda, evidence suggests that participation in this sector remains low compared with other developing and transition economies. This study investigates the micro and meso-level factors defining farm household's capacity and incentives to participate in RNF employment in the post-war Rwanda. Based on the household's time allocation theory, this study employs household survey data collected in Gisagara District in a double-hurdle regression. The results reveal that female-headedness, labour availability, education, social networks, access to finance and rural towns increase the probability of participating in RNF activities, whereas for participating households, the time allocated to RNF activities tends to decrease with age, land productivity, distance to market and dispersed settlements. The article concludes with key implications for rural development policies such as basic education and umudugudu settlements.

Keywords:

• household model
• rural non-farm employment
• double-hurdle model
• Rwanda

Acknowledgement

The authors are grateful to the African Economic Research Consortium (AERC) for the award of the scholarship grant which made this study possible.

Notes

⁴Definitions: C, consumption goods; D, leisure; X_M, quantity of market goods; X_C, quantity of home-grown goods; T, total time available; H_F, on-farm work hours; H_N, non-farm work hours; L, leisure; E, exogenous preferences structures; H, human capital; G, household's locational characteristics; W_F, farm wage; W_N, non-farm wage; V, unearned income; P_Q, the anticipated price of farm outputs; P_Z, price of non-labour variable inputs; P_M, price of marketed goods; Z, quantity of non-labour variable inputs; W_F, on-farm wage rate; L, hired labour hours; L_D, labour demand; Q, farm output; K, farm specific characteristics.

⁵ and .

⁶ L_D = H_F + L.

⁷Assuming competitiveness in inputs and output markets, and were simplified into P.

⁸The diagonality of the covariance matrix shows that the two error terms are assumed to be independently distributed; is the binary choice variable in Equation (8); Z is a vector of capacity factors explaining the decision to participate in RNF employment, whereas α represents their respective influences; the second forumla of Equation (9) explains the factors affecting the extent of participation ( is the latent variable that reflects farmer's time allocation in RNF employment), X, and β being the vector of factor explaining the intensity of participation and their influences respectively; and the observed variable, Y_i, is determined as .