Impact of reducing the pre harvest burning of sugar-cane area on. Brazil

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1 Impact of reducing the pre harvest burning of sugar-cane area on respiratory health in Brazil Alexandre Nicolella Department of Economics University of São Paulo, Ribeirão Preto MGG n.7 University of Kent 2010

2 Biofuel: Brazil and World Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production Renewable sources: sugar-cane, corn, cellulose and woody crops etc Projections 5% of the liquid fuels by 2025 Brazil: 34% of the world ethanol production in 2009 Brazil consumption: Ethanol 22, m 3 Gasoline 19, m 3 (2009) Sugar-cane products: 18.1% of the Brazilian energy matrix

3 Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production Reasons for Ethanol Demand in Brazil 30 years of investment in R&D for industrial and agricultural ethanol sector Productivity: from 34t.ha 1 in 1960 to 69t.ha 1 in 2006 Ethanol cost: from US$ 980m 3 in 1975 to US$ m 3 in 2004 Rise of oil prices and the decline of ethanol prices Producer price: ethanol US$ 301m 3 and gasoline US$ 502m 3 (2009) Flex fuel technology Flex-fuel light-cars sold: from 39% in 2005 to 87% in 2009

4 Two System of Production Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production Sugar-cane area: from 4.9 (2000) to 8.2 million ha (2008) = g.r. 6.7% a year Sugar-cane is a semi perennial culture Mechanical harvest of the raw sugar-cane Manual harvest with previous burning of sugar-cane State of São Paulo: 56% of the sugar-cane area was harvested raw (2009)

5 Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production Consequences of Sugar Cane Production Labor market Water pollution Green house gases emission Soil degradation Health

6 Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production Health Consequences of Sugar-Cane Production Sugar-cane on air pollution: Andrade et al. (2010); Lara et al (2005) and Allen et al (2004) Fine particulate matter (PM 2.5 ) Coarse particulate matter (CPM) Black Carbon concentration (BC) Nitrite, sulfite, oxide of carbon

7 Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production Health Consequences of Sugar-Cane Production Sugar-cane and health Arbex et al (2000) and Arbex et al (2007) City of Araraquara (SP) using data from 1995 and 2003 (respectively) found a positive impact of sugar cane on inhalation and asthma admission Cançado (2006) City of Piracicaba (SP) using data from 1997/98 found a positive impact of sugar cane burning and child and elderly admission due to respiratory diseases Uriarte et al (2009) State of São Paulo using data from 2003 found a positive impact of fire occurrence on child and elderly admission due to respiratory diseases

8 and contribution Measure the impact of the increasing of raw sugar-cane harvesting area on inpatient and outpatient visits due to respiratory diseases on the state of São Paulo Contribution Raw sugar-cane harvested area Other sources of pollution as car and industries Incorporating socio-economics variables Health system supply Control for health private sector

9 Human Capital Model - Grossman (1972) and Cropper (1981) For a municipality the average health capital variation will be: H t+1 = H t+1 H t = I t δ t Ht (1) The average rate of decay or depreciation of health capital in a municipality: δ t = f (S t, Ψ t ) (2) The municipality per capita investment in health capital: I t = f (t h t, M t, E t, Υ) (3) The mean marginal cost to invest in health: π t = f (W t, P M t ) (4)

10 Human Capital Model - Model results Individuals in polluted area will choose to keep a lower level of health capital and will present more incidences of illness Model results Individual in long term polluted areas can undertaken some behaviors to minor the effect of this externality. Pollution can be endogenously determined.

11 Region: São Paulo State Study Region Data Base Econometric Specification State of São Paulo: 60% of total Brazilian sugar-cane production in 2007/2008 More detailed socio-economic data base for municipalities State Law N of gradually diminish the sugar cane burning 2007 Protocol that anticipate the abolishment of pre harvest burning of sugar-cane (2014/17)

12 Data Base Motivation Study Region Data Base Econometric Specification H t : S t Ψ o t Inpatient visits per 1000 habitants and local of residence due to respiratory diseases; Outpatient visits due to inhalation procedure per 1000 habitants; Length of stay per local of residence due to respiratory diseases. population density; percentage of population above 60 years; weather considered time invariant variable. total fleet 1000 units (2002) total industrial energy consumption 1000 MWh (2001)

13 Data Base Motivation Study Region Data Base Econometric Specification Ψ c t Raw sugar cane area in 1000 hectare. t h t and Υ Considered time invariant variable. M t and P M t Health professionals and nurses per 1000 habitants registered in the regional council for the municipalities; Percentage of population that is beneficiaries of private health plans E t and W t Average of real salary for formal workers.

14 Panel Model Motivation Study Region Data Base Econometric Specification The impact of increase raw sugar-cane harvested area on population respiratory health can be estimated as follow: h it = β 1 Ψ c it + β 2Ψ o it + β 3S it + β 4 M it + β 5 W it + ε it ε it = u it + θ i u it N(0, 1) (5) This model can control for the endogeneity caused by the individual (behavior) and municipality (weather) heterogeneity.

15 Stability Inpatient visits Outpatient Visits and Length of Stay Stability and sensibility of the model Inpatient visits per 1000 habitants due to respiratory diseases Independent Variables S t S t, Ψ S t, Ψ, M t S t, Ψ, M t, S t, Ψ, M t, E t, W t E t, W t FE model FE model FE model FE model FE model -SP Population density ( ) ( ) ( ) ( ) ( ) Population > *** *** ** ** ** (21.37) (23.69) (31.93) (31.72) (31.91) Raw sugar-cane *** *** *** *** (0.0379) (0.0355) (0.0355) (0.0355) Total fleet *** *** *** ( ) ( ) ( ) (0.0154) Industry Energy *** *** *** *** ( ) ( ) ( ) ( ) Health professionals ** ** ** (0.194) (0.191) (0.192) Private beneficiaries ** * * (1.928) (1.904) (1.918) Salary ** ** ( ) ( ) Constant 27.27*** 25.07*** 22.12*** 24.29*** 24.32*** (2.300) (2.514) (2.864) (2.933) (2.933) R-squared Municipalities Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

16 Stability Inpatient visits Outpatient Visits and Length of Stay Hospital admission per 1000hab - resp. diseases Inpatient visits due to respiratory diseases -FE Model Variable Inpatient Inpatient priv. Inpatient < 15 Inpatient > 60 Population Density ( ) ( ) ( ) ( ) Population > ** ** (31.72) (33.88) Raw sugar-cane *** ** ** *** (0.0355) (0.0678) (0.0772) (0.103) Total fleet *** *** ( ) ( ) ( ) ( ) Industry energy *** *** ** *** ( ) ( ) ( ) ( ) Health professionals ** *** *** *** (0.191) (0.221) (0.241) (0.429) Private beneficiaries * (1.904) Private beneficiaries < (2.560) Private beneficiaries > (8.136) Salary ** * ** ( ) ( ) ( ) ( ) Constant 24.29*** 25.87*** 25.24*** 49.06*** (2.933) (3.236) (2.341) (4.641) Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1

17 Inhalation and LS - resp. diseases Stability Inpatient visits Outpatient Visits and Length of Stay Outpatient visits for inhalation per 1000hab and Length of Stay Variable Inhalation - FE inhalation - RE Length of stay - FE Population density (0.0523) ( ) ( ) Population <15 2,043*** 1,633*** (627.5) (298.7) Population > * (5.470) Raw sugar-cane (2.707) (2.327) ( ) Total fleet (0.0882) (0.0418) ( ) industry energy ** (0.0483) (0.0411) ( ) Nurses *** (9.986) (4.106) Health professionals (0.0402) Private beneficiaries ** (153.0) (109.0) (0.518) Salary * (0.0781) (0.0471) ( ) Constant *** (222.4) (86.04) (0.554) Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1

18 Motivation Pollution Raw sugar-cane harvested area decrease the number of inpatient visits Total fleet and industrial energy consumption increases the number of inpatient visits Higher effect for young and elderly No effect on inhalation and length of stay Environmental factors Population over 60 decreases the number of inpatient visits Population under 15 years increases of inhalation per 1000 habitants

19 Motivation Health goods Health professionals decrease the number of inpatient visits and inhalation Large effect for young and elderly Private health plans beneficiaries decrease the number of inpatient visits Salary Salary decrease the number of inpatient visits and inhalation Especially for elderly

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