The Effect of Malaria on Settlement and Land Use: Empirical Evidence from the Brazilian Amazon

1
The Effect of Malaria on Settlement and Land Use
Empirical Evidence from the Brazilian Amazon

• Shufang Zhang, Marcia Caldas de Castro, and David
  Canning
• Harvard School of Public Health
• May, 2010

2
Malaria and Development

• Malaria burden
• Potentially large effects on income levels
• Mechanisms
• Health care costs, prevention and treatment
• Labor productivity
• Childhood exposure and cognitive development
• Educational Attainment and adult productivity
• Population pressure
• Avoidance

3
Effect of Malaria on Land Use

• Land use
• Avoidance can reduce the burden of malaria but
  had costs
• Settlement, choice of crop
• Evidence of Effect of Malaria on Crop Choice
• Paraguay, Conly (1975)
• Kenya, Wang'ombe and Mwabu (1993)
• Vietnam, Laxminarayan (2004)

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Machadinho Resettlement Project

• Resettlement project in Brazil in the 1980s
• Land plots allocated to settlers
• Our Questions
• What is the impact of malaria on settlement?
• What is the impact of malaria on land use?

5
Machadinho Resettlement Project
Site Photo (source M. Castro)
6
Machadinho Resettlement Area
Data Source Center for Regional Development and
Planning Federal Univeristy of Minas Gerais,
Brazil
7
Settlement Infrastructure

• Infrastructure constructed between 1982 and 1984,
  1200 km2 total area.
• Plots were laid out based on topographic
  featuressteam at the back, with front access to
  a road.
• Urban and sub urban areas designated
• Roads and laid out in advance (3 classes). Placed
  to avoid flooding in rainy season.
• Forest reserves maintained - right of use to
  indigenous rubber tappers.

8
Allocation of plots

• Designated for landless small farmers
• 1740 plots, each about 45 hectares Settlement
  oversubscribed.
• Settlers randomly allocated to plots July/ August
  1984.
• Settler gets right to use plot lapses if plot
  not farmed.
• In theory no trade in plots allowed in practice
  some swaps and trades carried out.

9
House built in 1985, all made of palm thatch.
House built in 1985. The roof is made of plastic,
and the sealing of the whole house is precarious.
10
House built in 1985. There is no door closing the
house.
11
Settlers in Machadinho in 1985
Source M. Castro
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Main urban area of Machadinho in 1985
Main urban area of Machadinho in 2001
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Farming

• Slash and Burn
• Cut down vegetation, wait to dry, and burn
• Typically poor soil quality
• Burn fertilizes soil
• Soil quality declines with use
• Main crops
• rubber, coffee, cocoa

14
Malaria Ecology

• Malaria
• Both Plasmodium falciparum and Plasmodium vivax
• River is preferred mosquito habitat
• Anopheles Darlingi
• Forest fringe for sun/shade
• Stagnant water when river falls
• Mosquito range up to 7km

15
Malaria and People

• New settlers lacked natural immunity and
  knowledge and were very susceptible to malaria
• Indigenous rubber trappers were asymptomatic but
  were a natural reservoir for malaria parasites
• Frontier pattern of malaria
• Clearing forest increases malaria initially
  more fringe - full clearance removes fringe.
• Malaria rate peaked in 1986, de Castro et al
  (2006)

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Machadinho Land Use Literature mainly case
studies

• Malaria can lead to settlers abandoning a plot,
  Martine (1990).
• Many settlers live in town to avoid malaria and
  for job opportunities, Sawyer (1993).
• High levels of malaria and poor soil quality led
  to many failures among farmer-settlers in the
  long run and the emergence of large cattle
  ranges. de Castro and Singer (2005).

17
Data

• Household Surveys
• For plots occupied and lived on
• Malaria, self reported symptoms, episodes per
  month/person
• Demographic and socioeconomic indicators
• Data for 1986 and 1987 are used in the study
• Map of Settlement Area
• Plot geography, distances
• Satellite images
• Area of plot cleared, crop cover, water cover.

18
Satellite Images

• Remote sensing data on land use
• Acreage and percentage of plot deforested
• Acreage and percentage of plot cropped
• Data available for year 1985 and 1986
• Remote Sensing Data

Satellite images M. Castro (PNAS, 2006)
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Variables

• Measured variables with ArcGIS
• Distance to river, Distance to nearest urban or
  suburban center, Distance to south entry,
  Distance to nearest stream, Nearest road type,
  Adjacent to river or forest reserve, Plot area
• Survey data
• Malaria rate, Household characteristics
  education, age structure, number of people live
  on the plot, number of planters, number of
  chainsaws.
• Satellite images
• Water cover, area cleared, area cropped

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Summary Statistics Plots
Table 1 Summary Statistics Table 1 Summary Statistics Table 1 Summary Statistics Table 1 Summary Statistics Table 1 Summary Statistics Table 1 Summary Statistics
Plot Characteristics Obs Mean Std. Dev. Min Max
Distance to the Machadinho river (7km if over 7km) 1734 4.75 2.36 0.2 7
Plot within 200 meters of the Machadinho river 1734 0.08 0.27 0 1
Plot within 200 meters of the forest reserve 1734 0.25 0.44 0 1
Distance to the nearest urban or suburban centers (km) 1734 4.38 2.04 0.3 11.6
Nearest road is major road (1yes 0no) 1734 0.13 0.34 0 1
Nearest road is sub-major road (1yes 0no) 1734 0.35 0.48 0 1
Distance to the nearest stream (km) 1734 0.46 0.26 0 1.58
Soil quality index 1670 0.16 0.03 0.07 0.44
Plot area (hectare) 1734 45.41 10.36 16.1 124.1
Distance to the south entry (km) 1734 15.20 7.80 0.44 29.48
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Summary Statistics households
Table 1 Summary Statistics Table 1 Summary Statistics Table 1 Summary Statistics Table 1 Summary Statistics Table 1 Summary Statistics Table 1 Summary Statistics
Household Characteristics by Plot, 1986 and 1987 Obs Mean St.dev. Min Max
Plot is occupied (1yes 0no) 3468 0.37 0.48 0 1
Self-reported malaria rate 1286 0.28 0.26 0 1
Household head's education 1281 1.66 1.91 0 7
Household head wife's education 1083 1.59 1.79 0 7
Proportion of people on the plot younger than 5 1279 0.13 0.17 0 1
Proportion of people on the plot between 5 and 15 1279 0.26 0.23 0 1
Proportion of people on the plot over 65 on a plot 1279 0.01 0.09 0 1
Total number of people living on the plot 1299 5.17 3.01 1 18
Number of chainsaws 1299 0.53 0.55 0 3
Number of planters 1299 0.50 0.54 0 2
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Summary Statistics Land Use
Land Use by Plot, 1985 and 1986 obs mean St. dev. min max
Water area (fixed) 1734 0.05 0.05 0 0.33
Proportion of land deforested 3468 0.10 0.09 0 0.69
Proportion of land cropped 3468 0.01 0.02 0 0.27
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Malaria Prevalence 1986
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Malaria Prevalence 1987
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Clearance and Cropping 1985
Percentage deforested in 1985
Percentage cropped in 1985
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Clearance and Cropping 1986
Percentage deforested in 1986
Percentage cropped in 1986
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The Impact of Malaria on Land Occupancy
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Simultaneous EquationStructural Model
Plot Occupied if
m malaria rate ylatent variable for
occupancy x plot variables r is distance to
river
hhousehold variables s distance to south
entry d time dummies i plot/household
Identification
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Removing Household Characteristics

• Household characteristics go into the error term
  valid because of randomization of plot
  allocation

Note that error also includes difference in
conditional expectation of malaria with and
without household characteristics but this
is uncorrelated with plot characteristics
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Correlation Matrix Between Plot Fixed
Characteristics and Household Characteristics
Distance to river Adjacency to river Adjacency to forest reserve Distance to nearest urban/suburban center Nearest road is major road Nearest road is sub major road Distance to the nearest stream Soil quality index Plot area Plot water area percentage Distance to south entry
Household head's education 0.0086 0.0371 0.0113 0.0632 0.007 -0.0142 -0.0311 0.0124 0.0523 -0.0468 -0.0335
Household head wife's education 0.0281 0.0245 -0.0209 0.0474 -0.0156 -0.0232 -0.0347 -0.0108 0.0475 -0.044 0.0006
Proportion of people on the plot younger than 5 0.0999 -0.0449 0.0283 0.0108 0.0025 0.0424 -0.011 -0.0385 0.0287 0.0183 0.0137
Proportion of people on the plot between 5 and 15 0.0093 0.0269 0.0066 -0.0108 -0.0224 0.0375 0.0605 -0.0513 -0.0315 0.0017 -0.0088
Proportion of people on the plot over 65 on a plot -0.0858 0.1100 0.0195 -0.0141 -0.0176 -0.0176 -0.0197 -0.0331 0.0074 0.0402 0.0462
Total number of people living on the plot 0.0306 0.0302 0.0178 -0.0741 -0.0429 0.1184 0.0988 -0.0498 -0.0269 -0.0331 -0.0277
Number of chainsaws a plot has 0.0225 0.015 -0.0263 -0.0185 0.0033 0.0597 0.0296 -0.0033 0.0419 -0.0268 0.0323
Number of planters a plot has -0.0435 0.0382 -0.0028 -0.0432 0.0442 0.0278 0.0625 0.026 -0.0439 -0.0925 -0.0086
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Reduced Form

• Substituting for expected malaria

Plot Occupied

• Standard Heckman selection model

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Identification

• We need an instrument for malaria in the
  settlement equation. Identifying assumption is
  that distance to river (up to 7 km) is
  correlated with malaria exposure but does not
  directly affect settlement. We correct for being
  adjacent to the river.
• We need an instrument that affects settlement
  but not malaria. We use distance to the south
  entry and connection with the outside world.

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Machadinho Resettlement Area
Data Source Center for Regional Development and
Planning Federal Univeristy of Minas Gerais,
Brazil
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Distance to River as IV for malaria
35
South Entry
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Heckman Selection Model
Dependent variable Plot Occupancy Malaria Rate
Independent variables (2) (1)
Distance to river 0.0156 (0.00501) -0.0431 (0.00429)
Nearest road is collector (best) road 0.157 (0.0337) -0.0973 (0.0211)
Distance to the south entry (km) -0.00462 (0.00128)
Year 87 0.114 (0.0134) -0.0598 (0.0133)

rho -0.105 (0.064) -0.105 (0.064)
Wald test of independent equations 2.71 2.71
No of observations 3333 3333
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Malaria Rate Reported vs Predicted
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Malaria reported vs predicted
Obs. mean S.D Min Max
Self-reported malaria rate for occupied plots 1286 0.282 0.261 0 1
Predicted malaria conditional on occupancy for occupied plots 1246 0.281 0.099 0.082 0.517
Predicted malaria unconditional on occupancy for all plots 3340 0.326 0.107 0.096 0.582
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Self-reported vs. Predicted Malaria Rate 1986
Self-reported malaria rate in 1986
Predicted malaria rate in 1986
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Self-reported vs. Predicted Malaria Rate 1987
Self-reported malaria rate in 1987
Predicted malaria rate in 1987
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Result The Impact of Malaria on Land Occupancy

• Point estimates of the effect of malaria on
  occupancy (t stat 2.98)
• Effect on probability of land occupancy of going
  from no malaria to 0.326 malaria rate (area
  average) is 0.12
• No malaria would have raised settlement fraction
  of plots from 0.37 to 0.49

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Malaria and Land Use

• Similar structural model
• Simpler because land use observed for each plot
  still problem of finding expected malaria
• Tobit Model
• Many plots have zero clearance/cropping
• Left censored data

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Table 4 The Impact of Malaria on Land Use Tobit
Model
Dependent variable Percentage Deforested Percentage Cropped
Independent variables (3) (4)
Distance to Machadinho river -0.00140 (0.000716) -0.000517 (0.000166)
Adjacent to river -0.0129 (0.00567) -0.00316 (0.00121)
Adjacent to forest reserve -0.0114 (0.00361) -0.00283 (0.000725)
Nearest road is collector (best) road 0.0524 (0.00583) 0.00687 (0.00118)
Nearest road is access (2nd best) road 0.00892 (0.00341) 0.00129 (0.000711)
Distance to nearest stream (km) 0.0143 (0.00665) 0.00345 (0.00133)
plot area (hectare) -0.000645 (0.000143) -0.0000899 (0.0000303)
Distance to the south entry (km) -0.000696 (0.000200) -0.000313 (0.0000404)
Year 86 0.0659 (0.00153) 0.0187 (0.000554)
No of observations 3340 3340
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The Impact of Malariaon Land Use

• No effect of the river on clearance
• Land close to the river is more likely to be
  cropped
• Plot occupancy uncorrelated with clearance
• Occupied plots less likely to be cropped
• Plots adjacent to major road more likely to be
  cleared and cropped

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Land Use by Occupancy 1986
Obs. mean S.D Min Max
Proportion plot cleared Plot occupied 825 0.135 0.093 0 0.620
Proportion plot cleared Plot not occupied 1190 0.124 0.092 0.001 0.092
Proportion plot cropped Plot occupied 825 0.017 0.023 0 0.235
Proportion plot cropped Plot not occupied 1190 0.025 0.029 0 0.269
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Malaria and Land Use

• Malaria deters settlement and living on a plot
• However, people may live in town and clear a plot
  in the same way as an occupied plot
• Cropping is more prevalent in high malaria /
  non-occupied plots
• Less malaria among farmers
• More access to work in town
• More money for capital and seeds

47
Conclusions

• Malaria deters settlers from living on plots
• Land use, clearance and cropping, is not deterred
  commuting to work on the plot is possible
• Pattern may be particular to this settlement
  area in Brazil
• good roads and transport
• Occupancy different from land use