Presentation is loading. Please wait.

Presentation is loading. Please wait.

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

Similar presentations


Presentation on theme: "Modern Industries, Pollution and Agricultural Productivity: Evidence from Mining in Ghana Fernando Aragon (SFU) (joint with Juan Pablo Rud, Royal Holloway)"— Presentation transcript:

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

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) 2

3 Why is this relevant? 1.Effect of pollution on agriculture not explored – Literature focuses on effects on human health – Biological evidence that pollution affects crops 2.Spillovers of modern industries – Thought in terms of input competition – Other non-input negative spillovers (e.g. pollution) neglected 3.Economic policy – Private and social costs – Compensation and mitigation 3

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

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) 5

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 (NO 2 ) Increase in rural poverty 6

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 7

8 Outline Background Methods Results 8

9 Background – Gold mining in Ghana 1.Important industry in Ghana – 97% of mineral revenue, 45% of total exports, 12% of fiscal revenue. 2.Modern, large scale, capital intensive – 96% large scale, rest artisanal/galamsey 3.Mostly foreign owned, exports all production as raw material. 9

10 Background – Gold mining in Ghana 4.Located in fertile agricultural land – Ashanti gold belt: Western, Ashanti and Central regions. – Cocoa producing regions 5.Negative spillovers – Population displacement – Environmental pollution: anecdotal and scientific evidence 6.Significant increase in late 1990s – We exploit this source of variation. 10

11 11

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

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) 13

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

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. 15

16 Analytical framework Two possible channels for mining to affect agricultural output (and HH income) 1.Change on input prices change in input use 2.Pollution change on A We can isolate effect on A, by estimating the production function i.e. conditioning output on input use 16

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

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) 18

19 Methods – empirical implementation Two issues: 1.Endogeneity of mining activity: mining areas may be systematically different. 2.Endogeneity of input choice 19

20 Methods - solutions 1.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 – S vt = cumulative gold production within 20 km 20

21 21

22 22

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

24 Methods - solution 2.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 24

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

26 Results – Mining and Agricultural Productivity 26 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 % decrease. Too large? Consistent with biological evidence: 30-60% decrease in yields of crops exposed to polluted urban air. 27

28 Role of distance 28

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

30 Is this pollution? No ground measures of pollution satellite imagery (cross section only, 2005) Detect NO 2 air pollutant linked to fuel combustion, toxic & precursor of tropospheric ozone 30

31 Is this pollution? 31

32 32

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

34 34

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

36 Measures of living standards - poverty 36

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

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 38

39 39

40 Results – Mining and Crop Yields 40 Back

41 First stage 41

42 Robustness – compositional changes 42

43 Robustness – alternative specifications 43

44 CES prod function 44


Download ppt "Modern Industries, Pollution and Agricultural Productivity: Evidence from Mining in Ghana Fernando Aragon (SFU) (joint with Juan Pablo Rud, Royal Holloway)"

Similar presentations


Ads by Google