Oil palm and structural transformation of agriculture in Indonesia

Abstract

Structural transformation of agriculture typically involves a gradual increase of mean farm sizes and a reallocation of labor from agriculture to other sectors. Such structural transformation is often fostered through innovations in agriculture and newly emerging opportunities in manufacturing and services. Here, we use panel data from farm households in Indonesia to test and support the hypothesis that the recent oil palm boom contributes to structural transformation. Oil palm is capital‐intensive but requires much less labor per hectare than traditional crops. Farmers who adopted oil palm increase their cropping area, meaning that some of the labor saved per hectare is used for expanding the farm. Average farm sizes increased in recent years. In addition, we observe a positive association between oil palm adoption and off‐farm income, suggesting that some of the labor saved per hectare is also reallocated to non‐agricultural activities. Oil palm adoption significantly increases the likelihood of households pursuing own non‐farm businesses. However, oil palm adoption does not increase the likelihood of being employed in manufacturing or services, which is probably due to the limited non‐farm labor demand in the local setting. Equitable and sustainable agricultural transformation requires new lucrative non‐agricultural employment opportunities in rural areas.

Technical efficiency and farmland expansion: Evidence from oil palm smallholders in Indonesia

“…Notably, the model reveals a considerable effect of land size, although the elasticity of agrochemical use is quite low, confirming the experimental findings of Darras et al (2019). The effect of labor is also comparably small yet reasonable as both direction and magnitude find support in the relevant literature on the low labor intensity of oil palm cultivation (Chrisendo et al, 2021;. Palm age and density exhibit first-order nonsignificant and second-order significant negative coefficients and thereby only partly confirm the quadratic relationship with output of both variables that is often found in the plant growth literature (e.g., Corley et al, 2003).…”

Adoption patterns and productivity impacts of agricultural mechanization services

“…In this study, we allow for correlations across the AMS choices of all four tasks by utilizing a multivariate probit model. The multivariate probit model is generalized from the bivariate probit model and has been applied to many settings (e.g., Atamanov & Van den Berg, 2012;Bontemps & Nauges, 2016;Chrisendo et al, 2021;Ma et al, 2018;Magrini et al, 2017). For a recent review of multivariate probit/logit model see Bel et al (2018).…”

Smallholders in agro-industrial production: Lessons for rural development from a comparative analysis of Ghana’s and Indonesia’s oil palm sectors

“…Benefits arise through higher selling prices and profits compared to more traditional crops such as rubber and rice (Feintrenie and Levang, 2009). Moreover, oil palm cultivation requires less labor than the previously cultivated rubber, enabling households to expand their farms and participate in off-farm employment, thus generating additional income (Chrisendo et al, 2021;Euler et al, 2017). Nonfarm households benefit through employment in the sector, which has been found to improve their living conditions (Bou Dib et al, 2018;Rist et al, 2010).…”