Social safety nets and productivity outcomes: Evidence and implications for Bangladeshi rice growers

Abstract

Using national representative cross-sectional data from 8846 rice growing plots in Bangladesh, we analyze the impact of social safety net programs (SSNPs) on rice farmers' productivity and efficiency. This study applied the propensity score matching (PSM) approach to correct the possible self-selection biases arising from observed and unobserved factors affecting a household's SSNP participation decisions. The stochastic frontier production function is estimated separately for participants and non-participants to compare yield and technical efficiency. Our results show that the output elasticities of all inputs except land and fertilizer are significantly higher for non-participants than participants. The SSNP participants are estimated to have 1.95% higher technical efficiency than the non-participants, while their frontier yield is 11.75% higher. The average treatment effect on treated (ATET) also confirms the yield and efficiency-enhancing role of SSNPs, particularly in climate-stressed areas. The study argues for widening the SSNP coverage to increase the marginal farmers' efficiency in climate-vulnerable areas. Other policy interventions include policies to increase farmers' access to land through the proper functioning land market, education, providing literacy training, and different production inputs.