<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Robin Burgess | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/robin-burgess/</link><description>Robin Burgess</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><atom:link href="https://macropaperwarehouse.com/authors/robin-burgess/index.xml" rel="self" type="application/rss+xml"/><item><title>The Origins and Control of Forest Fires in the Tropics</title><link>https://macropaperwarehouse.com/papers/the-origins-and-control-of-forest-fires-in-the-tropics/</link><guid>https://macropaperwarehouse.com/papers/the-origins-and-control-of-forest-fires-in-the-tropics/</guid><description>&lt;p&gt;This paper studies the economics of illegal tropical forest fires in Indonesia, framed as a modern counterpart to Pigou&amp;rsquo;s canonical externality example of sparks from railway engines. The central research question is whether private firms adjust their fire-setting behavior depending on the degree to which the costs of fire spread fall on themselves versus others, and what enforcement architecture shapes that adjustment.&lt;/p&gt;
&lt;p&gt;The empirical setting is Indonesia&amp;rsquo;s national forest estate, where palm oil and wood fiber concession holders use fire as a cheap land-clearance method — burning primary forest costs 44–70% less than mechanical clearance — despite the practice being illegal. The paper assembles a novel dataset of 107,334 fires across Indonesia&amp;rsquo;s major forested islands from October 2000 to January 2016, constructed from NASA MODIS daily satellite hotspot data (1 km resolution, four flyovers per day). Fire ignitions and spread paths are traced by linking contiguous pixels burning on adjacent days. This fire data is merged with geocoded concession boundaries (logging, palm oil, wood fiber), land-use classifications (protected forest, unleased productive forest, areas outside the forest estate), annual deforestation data from Hansen et al. (2013) at 30 m resolution, daily wind speed data from NOAA NCEP-DOE Reanalysis 2 interpolated to each 1 km pixel, and data on firms investigated by the Indonesian government following the 2015 fires. The main analytical sample focuses on the 39,077 fires started inside wood fiber and palm oil concessions.&lt;/p&gt;</description></item></channel></rss>