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Fight fire with finance: a randomized field experiment to curtail land-clearing fire in Indonesia
Initial registration date
August 07, 2018
August 09, 2018 7:59 AM EDT
Other Primary Investigator(s)
TNP2K & the SMERU Research Institute
Additional Trial Information
Payments for ecosystems services (PES) and conditional cash transfers (CCTs) are popular and often effective policy approaches to spur behavior change: paying people to undertake behaviors they otherwise would not. Behaviors being “incentivized” usually benefit society, for example reducing deforestation with PES and increasing vaccination and school attendance with CCTs. However, there remains limited evidence on the effectiveness of PES-type interventions in settings of high deforestation and limited institutional capacity, and no studies have focused on fire—an increasingly prominent way to clear land. Our project is based in West Kalimantan, one of the main provinces where Indonesia’s catastrophic 2015—16 fires were concentrated. The goal of the study is to estimate the effects of cash transfers to village governments reduce fire—offered as a PES contract to the village governments, with payment made after the fire season—by randomly assigning 75 villages to the program and 200 to a comparison group.
Edwards, Ryan et al. 2018. "Fight fire with finance: a randomized field experiment to curtail land-clearing fire in Indonesia ." AEA RCT Registry. August 09.
75 treatment villages receive instruction on fire prevention, plus Rp 10 million (~$750) at start of the experiment to help with fire prevention, and a conditional payment of Rp 150 million (~$11,500) at the end of the fire season (December 31, 2018) if successful in eliminating fires. In order to receive their ex-post payment, villages are required to not set any fire (with some exceptions built into the contract) and promptly extinguish any natural fires. Hence, payment is conditional on performance, which we monitor using a satellite data and field verification. Similar to Indonesia’s National Program for Empowerment (PNPM), village facilitation and fire prevention training takes place in treatment villages before agreements are signed. Our intention is to scale up this pilot program to three provinces with additional treatment arms (i.e., different payment levels and information-only treatments) the following year if the first-year results are promising.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
Fire incidence and extent.
Primary Outcomes (explanation)
Thermal hotspots are measured as counts per village using NASA’s MODIS and VIIRS Active Fire Products and official administrative boundaries. Burned area is a MODIS product.
Secondary Outcomes (end points)
Forest loss, village financial behavior, villager environmental beliefs and values, and economic and social wellbeing.
Secondary Outcomes (explanation)
Tree cover loss will be constructed from satellite imagery, and other outcomes will be measured in administrative data and additional household surveys.
75 out of 275 study villages across the West Kalimantan districts of Kubu Raya, Sanggau, Sintang, and Ketapang are randomly assigned to the treatment group. The remaining 200 form the comparison group. These four districts are selected based on historical fire record, remaining forest cover, and the relative prevalence of smallholder farmers in the local palm oil sector. To ease facilitation logistics and ensure our program reaches the most high-risk areas, we restrict the four-district sample to villages (a) in the eight most fire-prone sub-districts in each district, and (b) that had fire in at least two of the last three years. Pre-intervention fire outcomes are measured using satellite data and initial village characteristics are observed in the 2014 Potensi Desa (a triennial census of village heads), the 2013 Agricultural Census, the SMERU Poverty Map, and a village head survey. End line data collection will take place after the initial village contracts expire on December 31, 2018. Daily satellite data cover the whole study period and an extended pre-period, with the blind control group reducing the scope for John Henry and Hawthorne effects. Additional outcomes will be examined using other satellite and administrative data, and potentially an additional end line survey.
Experimental Design Details
By computer, stratified by district (i.e., Stata code)
Village (i.e., desa)
Was the treatment clustered?
Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
75 treatment and 200 control villages
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
INSTITUTIONAL REVIEW BOARDS (IRBs)