LT Week 5 Flashcards
The consequences of pollution
Motivation
Burgess, Hansen, Olken, Potapov & Sieber (2012). “The Political Economy of Deforestation in the Tropics”
Understanding how political institutions and local officials’ incentives affect deforestation.
Theory
Burgess, Hansen, Olken, Potapov & Sieber (2012). “The Political Economy of Deforestation in the Tropics”
“To guide empirical analysis, paper presents a model in which firms decide where to log, but their activities are contingent on obtaining permits (legal or otherwise) from the local district governments that enforce forest policy. Assume that there are a large number of logging firms that can choose where to log, but must obtain a permit from the district government to do so. Districts choose the number of permits to sell to firms taking the number of permits issued by other districts as given.
In determining number of permits to issue, districts are engaged in Cournot competition with one another within a provincial wood market. As number of districts in a wood market increases, the Cournot framework suggests that the amount of wood extracted should rise and the price of wood should fall.
Decentralisation event means we move closer to perfect competition than monopoly on the spectrum, so quantity would increase in this model and prices of wood would fall (this means we would see more deforestation). If deforestation were controlled centrally, you would have an essential monopoly which would mean that the highest possible prices and the lowest possible quantity (lower deforestation).
If the government centrally allocates all permits it will act as a monopolist – which standard theory suggests would result in higher prices and lower quantities of permits”
Special settings
Burgess, Hansen, Olken, Potapov & Sieber (2012). “The Political Economy of Deforestation in the Tropics”
“Both Week 5 papers explore the role of policy in deforestation trends. Deforestation accounts for almost one fifth of annual emissions of greenhouse gases. Rainforests are disproportionately located in low income and developing countries.
Vast majority of tropical rainforests are owned and managed by national governments, which in turn rely on bureaucrats and politicians to enforce logging rules. It is thus important for political actors to govern deforestation effectively.
Political decentralization creates the backdrop for this paper. In Post-Suharto Indonesia, amid fears that multi-ethnic country would break apart, substantial administrative and fiscal authority devolved to approximately 300 district governments. District forest departments became part of local district governments. Between 2000 and 22008 the number of districts in the main forest islands of Indonesia almost doubled from 189 in 2000 to 312 in 2008. This paper exploits the differential timing of these district splits to understand how decentralization affected the deforestation rate. Estimates show that illegal logging makes up as much as 60%-80% of total logging in Indonesia. Much of it can be condoned by local officials.”
Empirical design
Burgess, Hansen, Olken, Potapov & Sieber (2012). “The Political Economy of Deforestation in the Tropics”
“Examine several empirical predictions of the Cournot theory.
Use a panel dataset to test whether the number of districts in the province affects the quantities and prices of wood felled in the province. For quantities, dependent variable is count data (no. of pixels) where count can be 0 so use a Poisson QML count specification rather than log dependent variable with OLS.
Data
Burgess, Hansen, Olken, Potapov & Sieber (2012). “The Political Economy of Deforestation in the Tropics”
“MODIS satelite imagery: For each annual interval, a total of 438 image inputs is used (146 metrics per year plus their calculated differences) (Hansen et al. 2005). This amount of information, in effect 438 dimensions for each 250 meter by 250 meter pixel, is used to estimate forest cover loss per year for that pixel.
This cell-level data is then summed by district and forest zone (i.e., the four forest categories in the Forest Estate: the Production, Conversion, Protection, and Conservation Forest). This yields our final left-hand-side variable deforestdzt, which counts the number of cells likely to have been deforested in district d in forest zone z and year t.
For province level data, we calculate the total number of districts and municipalities in province p on island i in year t, NumDistrictsInProvpit.
To examine the impact of other sources of rents available to district governments, we examine oil and gas revenues per capita at the district level, PCOilandGasdt.”
Key findings
Burgess, Hansen, Olken, Potapov & Sieber (2012). “The Political Economy of Deforestation in the Tropics”
- more districts = more deforestation and illegal logging
- Result #2: more districts = lower wood prices
- Result #3: other sources of rents are substitutes, but only in the short-term
“Table IV:
- Column 1 looks at entire Forest Estate together. Results show that annual rate of deforestation increases by 3.85% if an additional district is formed within a province
- In the Conservation zones we see a statistically significant increase in illegal deforestation of 9.57%.
- Panel B reports medium run impact by including lags. Focu on the sum of the immediate effect and the first three lags, which is the net impact of adding an additional province three years later. Why? Results could be driven not by increased competition but because it takes time for an enforcement institution to be built up, which can be exploited. If this were the case, we would not see a a progressivley larger effect over time, whereas in a competition story we would. Hence in all cases effects are larger than intitial specification.
- Therefore, Result 1: More Districts = More Deforestation and Illegal Logging
Table V:
- Increase in quantity and a decrease in price no matter what period of time you look at. Lag effect even stronger as above, corroborating competition story.
- Main results in column 1 and 2 of Panel A show that adding one additional district in a province decreases prices by 1.7% and increases the quantity of logs felled by 8.4%. Impact on price only signifcant in lagged specification at 3.4% reduction in price.
Table VI:
- Examines how logging responds to changes in another source of local rents for district governemnts: oil and gas revenues
- Share of oil and gas revenues rebated back to districts, half going to producing districts and other half being shared equally between districts in same province
- Less exploitation of oil and gas when deforestation increases in the short run (immediate effect panel a). Each USD $1 of per-capita oil and gas rents received by the district reduces logging by 0.3%. With lags, however, coefficients become positive (no more substituion effect). Why? Change in political equilibrium (whatever this means - seems tenuous) after redistricting which favoured oil and gas extractors”
Interpretation / policy implications
Burgess, Hansen, Olken, Potapov & Sieber (2012). “The Political Economy of Deforestation in the Tropics”
Monitoring of local bureaucrats and politicians who de facto control forest extraction. Command-and-control systems for forests in tropical countries reuire stronger governance.
Special settings
Burgess (2023): National Borders anbd the Conservation of Nature
“As Figure 1 establishes these different areas of tropical rainforest have experienced radically different patterns of deforestation. Brazil - which contains 65% of the Amazon rainforest, moves from having the highest rate of deforestation in 2001 to having the lowest rate in 2013, before converging back to the average of DR Congo and Indonesia
In the mid-2000s, Brazil launched a new conservation agenda with the 2004 Action Plan for the Prevention and Control of Deforestation in the Legal Amazon (PPCDAm) which strengthened the legal penalties associated with illegal deforestation, particularly on unclaimed and private land outside protected areas . This reduction was temporary, and starting in 2014, deforestation rates in Brazil (relative to countries just across the border) climb again.
This second reversal coincides with a period of economic crisis and growing lobbying from the agricultural sector, which is consistent with the hypothesis that environmental protection was undermined by political pressure.
Burgess (2023): National Borders anbd the Conservation of Nature
Motivation
Burgess (2023): National Borders anbd the Conservation of Nature
Tropical forests play a central role in slowing climate change and their conservation has become an international priority. In weak institutional settings where these tropical rainforests are, it is critical to assess how well conservation efforts are working.
Burgess (2023): National Borders anbd the Conservation of Nature
Empirical design
Burgess (2023): National Borders anbd the Conservation of Nature
“Propose a method that combines impartial monitoring via satellites with the use of national borders
To assess the effectiveness of conservation policies in Brazil they apply a regression discontinuity design to 30x30 meter resolution Landsat 7 data set in 27km bands on either side of Brazil’s 12,800km border with seven other nations in the Amazon from 2000 to 2020
Estimate a spatial regression discontinuity design using as the main outcome variable the share of forest cover lost in each year between 2001 and 2020 at the 120-meter pixel resolution level. Running variable is distance to the Brazilian international border: DistBorderi. Positive distances represent pixels in the Brazilian Amazon, while negative distances represent pixels in the Amazon outside Brazil.
Coeficient of interest is gamma (on the dummy variable equal to 1 if the pixel i is in Brazil) which measures the difference in the share of a pixel that is forested in 2000 or deforested in a year after 2000 on the Brazilian side of the border compared to the other side.
Remember key assumptions: we assume individuals are as good as randomly assigned around the threshold. identifying assumption would be violated if the precise location of the border was set according to local geographic or agronomic characteristics. Paper checks for this and finds that that certain factors around the border are smoothly distributed
”
Regression dicontinuity
Burgess (2023): National Borders anbd the Conservation of Nature
Data
Burgess (2023): National Borders anbd the Conservation of Nature
“Annual deforestation measures from 2001 to 2020, at a spatial resolution of 30 meters across the whole Latin America.
Annual forest loss is defined as the share of 30m Landsat pixels within our 120m pixels deforested within one year. Forest cover in 2000 is the average tree cover canopy of the Landsat pixels “
Burgess (2023): National Borders anbd the Conservation of Nature
Key findings
Burgess (2023): National Borders anbd the Conservation of Nature
Panel (a) shows the abruptly smaller forest cover in 2000 at the Brazilian border. We can see that the discontinuous higher annual deforestation rates on the Brazilian side of the border between 2001 and 2005 – Panel (b) – level out between 2006 and 2013 – Panel (c). Panel (d) shows that deforestation rates on the Brazilian side of the border returns being discontinuously higher between 2014 and 2020.
Burgess (2023): National Borders anbd the Conservation of Nature
Interpretation / policy implications
Burgess (2023): National Borders anbd the Conservation of Nature
“Climate change pays no regard to national borders and yet the policies that constrain or exacerbate it fall within national jurisdictions. It has made conservation of natural resources a more salient issue with the spotlight focused most brightly on tropical forests.
This paper oberves sharp discontinuities in forest loss at the border - this shows that the state does have the power to exercise control over global ecosystems
“
Burgess (2023): National Borders anbd the Conservation of Nature
Why do the authors look at the evolution of deforestation in other countries to assess the role of policies implemented by the Brazilian government? What does the paper conclude about the relationship between the political landscape and national conservation efforts?
