This was created in partnership with Environment for Development .
Despite the recent popularity of conditional cash transfers (CCT) and payments for environmental services (PES) programs, what determines their success is not well understood. We developed a conceptual framework to give insight into some of the main determinants of CCT and PES program efficiency that hope to increase investments in human and environmental capital. We used a simple agent-based model and validated the results with empirical data from existing programs. We show that 1) the share of participants who meet the program’s conditions at baseline is a powerful predictor of program efficiency, (2) and selection bias erodes program efficiency to a large extent. (Selection bias stems from agents who already meet program criteria and who self-select into programs at higher rates than those who do not meet the conditions.) Based on these results, we discuss possibilities for improving efficiency—mainly by targeting applicants or increasing payments—and criteria for evaluating and choosing CCT, PES, or other policy instruments.