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(joint with Juan Pablo Rud, Royal Holloway)

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1 (joint with Juan Pablo Rud, Royal Holloway)
Modern Industries, Pollution and Agricultural Productivity: Evidence from Mining in Ghana Fernando Aragon (SFU) (joint with Juan Pablo Rud, Royal Holloway) CEA Conference May 2013

2 Main issue Negative spillovers of modern industries
What is the effect of modern industries on agricultural production? In this paper: Case of gold mining in Ghana Modern, capital-intensive industry Severe concerns of pollution Near fertile rural area (cacao) This paper explores empirically the effect of modern mining on agricultural productivity.

3 Why is this relevant? Effect of pollution on agriculture not explored
Literature focuses on effects on human health Biological evidence that pollution affects crops Spillovers of modern industries Thought in terms of input competition Other non-input negative spillovers (e.g. pollution) neglected Economic policy Private and social costs Compensation and mitigation And through that channle may affect livelihoods as well….

4 What do we do? Main idea: pollution may affect crop yields
Non-input channels  residual productivity

5 What do we do? Estimate an agricultural production function
Effect of mine activities on total factor productivity Empirical strategy Repeated cross sections of HH surveys D-i-D: expansion of mining x exposure to mines (distance) Endog. inputs: IV and imperfect IV (partial identification)

6 Main findings Reduction of agricultural productivity
40 % decrease between , near mines But, no change in input use nor prices. Results consistent with pollution channel Satellite imagery: increase in air pollutants (NO2) Increase in rural poverty

7 Unsolved issues Cannot measure pollution directly (not available)
Effect on residual productivity  does pollution affect quality of inputs (land, water) or crops’ health? Large scale and artisanal mines overlap cannot separate source

8 Outline Background Methods Results

9 Background – Gold mining in Ghana
Important industry in Ghana 97% of mineral revenue, 45% of total exports, 12% of fiscal revenue. Modern, large scale, capital intensive 96% large scale, rest artisanal/galamsey Mostly foreign owned, exports all production as raw material.

10 Background – Gold mining in Ghana
Located in fertile agricultural land Ashanti gold belt: Western, Ashanti and Central regions. Cocoa producing regions Negative spillovers Population displacement Environmental pollution: anecdotal and scientific evidence Significant increase in late 1990s We exploit this source of variation.


12 Why would mining affect agriculture?
Input competition channel Demand-Supply  Increase in price of local inputs

13 Why would mining affect agriculture?
Input competition channel Demand-Supply  Increase in price of local inputs Mining has potential to pollute: air, water and soil Industry-specific pollutants  cyanide, acid drainages, heavy metals Similar to small city or power plant  emissions from heavy machinery (air pollutants) Biological evidence Exposure to air pollutants from burning fossil fuels  reduction in yields 30-60%, more susceptible to diseases. Heavy metals in water and soil  vegetation stunted or dwarfed (Environment Canada 2009)

14 Analytical framework Production function: F(A, Labor, Land)
Consumer-producer household choose inputs to maximize HH utility. We will discuss validity later…

15 Analytical framework With perfect input markets:
input demand is function of: prices and A  endogeneity of inputs problem If farmers cannot buy/sell inputs Input demand constrained by HH endowments Extreme case: Input demand = input endowment Use endowments as instruments for input use. We will discuss validity later…

16 Analytical framework Two possible channels for mining to affect agricultural output (and HH income) Change on input prices  change in input use Pollution  change on A We can isolate effect on A, by estimating the production function i.e. conditioning output on input use

17 Methods – empirical implementation
Assume Cobb – Douglas, y, m, l : log of agricultural output, land and labor A is function of: Svt = measure of exposure to mine activity Farmer characteristics Zi: age and literacy, land ownership, place of birth District, year fixed effects , dummy prox. each mine

18 Methods - Data Household data
Ghana Living Standard Surveys (GLSS): GLSS 4 ( ) and GLSS5 ( ), repeated cross sections Input and output (farming households) Real output calculated using local agric prices. Poverty (all HHs) Geographical coordinates of Enumeration Areas Distance to mining areas (GIS)

19 Methods – empirical implementation
Two issues: Endogeneity of mining activity: mining areas may be systematically different. Endogeneity of input choice

20 Methods - solutions Difference in difference:
Treated and control group defined by proximity to mine “mining” area = within 20 km of an active mine Treatment (continuous) : cumulative gold production Svt = cumulative gold production within 20 km



23 Results – Mining and Agricultural Productivity
Go to: Crop yields Go to: First Stage

24 Methods - solution Use of instrumental variables:
Endowments as instruments of input use (with imperfect input markets) But input endowments may be correlated to error term Use an imperfect IV strategy (Nevo and Rosen, 2012) If correlation between instrument and error is weaker than for the instrumented variable and The sign of that correlation is the same  Bounds of parameter values, i.e., partial identification

25 Results – Mining and Agricultural Productivity
Go to: Crop yields Go to: First Stage

26 Results – Mining and Agricultural Productivity
Go to: Crop yields Go to: First Stage

27 Increase of one S.D in gold production  reduction of 30% in residual productivity
Between 1998/99 and 2005  40% decrease. Too large? Consistent with biological evidence: 30-60% decrease in yields of crops exposed to polluted urban air.

28 Role of distance

29 Robustness checks No evidence of compositional change
Farmer’s observables Agricultural practices Robust to alternative specifications Parsimonious vs saturated Similar for locals and immigrants Placebo test (future mines) CES production fct

30 Is this pollution? No ground measures of pollution  satellite imagery (cross section only, 2005) Detect NO2  air pollutant linked to fuel combustion , toxic & precursor of tropospheric ozone

31 Is this pollution?

32 Columns 1,2 and 5 include input use

33 Competition for inputs?
Mine demanding more labor / reducing supply of land  Increase in input prices, reduction in demand for inputs.


35 Lack of effect of mining on input demand?, but productivity declined…
Consistent with imperfect input markets (inflexible inputs)

36 Measures of living standards - poverty

37 Increase in rural poverty (both farmers and non-farmers)
But nothing on urban poverty

38 Final remarks Expansion of mining associated to
Significant reduction in agricultural productivity Deterioration of living standards for rural population Seems to be driven by pollution instead of competition for inputs Important crowding out effect of modern industries Significant spillovers and re-distributive effects Local farmers lose, rest of country may gain Disregard for these spillovers over-estimate net benefits of sector


40 Results – Mining and Crop Yields
Column 2 uses glss 2 and 4 only… Back

41 First stage

42 Robustness – compositional changes

43 Robustness – alternative specifications

44 CES prod function

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