Evaluating the Economic Impacts of Climate Change on the Brazilian Agriculture

1. Evaluating the Economic Impacts of Climate Change on the Brazilian Agriculture Juliana Speranza Manaus, November, 2008. José Feres, Juliana Speranza, Eustáquio Reis Manaus, November, 2008

2. Motivation • Benchmark global warming is projected to increase global mean surface temperature by 1.1 – 6.4ºC over the period 1990 to 2100(IPCC 2007). Many questions remain regarding how the costs and benefits of warming are likely to be distributed across the globe and how a change in climate will affect various greenhouse effect mitigation projects, such as avoided deforestation and carbon-trading, over their lifetime.

3. Motivation • One of the most significant ways that global climate change is predicted to affect economic activity is through its effects in agriculture.

4. Motivation • The damages are particularly critical in tropical countries, like Brazil. Indeed, Brazilian agricultural and forestry sectors are particularly vulnerable to global warming since considerable production is currently undertaken under high-temperature conditions.

5. Motivation • Among the several consequences, falling farming incomes may have an expressive negative impact on economic development, may increase poverty and reduce the ability of households to invest in a better future.

6. Brazilian particularity • The Amazon rainforest Since deforestation is the 2ndlargest global source of carbon dioxide emissions, global warming will depend in part on future land use in the Amazon and the ability of the area’s vegetation to sequester carbon, thus creating a feedback within the climate change mechanism.

7. Policy concerns • Adaptative and mitigation policies (global warming) • Population socioeconomic reproduction (poverty) • Deforestation and agricultural borderexpansion • Migratory flows • Agricultural versus non-agricultural activities

8. Objective What are the impacts of climate change in terms of agricultural profitability/productivity, land values and area used in agro-pastoral activities in the distinct Brazilian regions?

9. Agricultural model • Basic aim: measuring the impact of climate change on the agricultural • Cross-Sectional Panel Model with Census Data • Input to GCM (3th AR data from IPCC 2001) • Georeferenced database • Methodology: • Ricardian approach • Fixed-effects approach Climate  profits  land conversion

10. Literature review • Production function approach: assumptions • Takes an underlying production function and varies the relevant environmental input variables to estimate the impact of these inputs on production. • Agroeconomic approach (specific crops). • Caveat: estimates do not account for the full range of compensatory responses to changes in weather made by profit-maximizing farmers (biased downward – “dumb-farmer”).

11. Literature review • Ricardian approach: assumptions • Land prices reflect the present discounted value of land rents into the infinite future. • Land prices are able to capture the impact of climate variables. • Captures all of the ways that farmers have adapted their climate, so long as the land is still classified as farmland (crop switching included). • Caveat: ommited variable bias.

12. Literature review: Ricardian Model Reproduced from Mendelsohn et al. (1994).

13. Literature review • Fixed effects approach: assumptions • Exploit the year-to-year random variation in temperature and precipitation to estimate whether agricultural profits/yields vary with climate. • Advantage: analternative to Ricardian model. • Caveat: adoptedtemporaryshocks.

14. Agricultural model • Two-stage method • First: econometric estimation • Equation specification • Yit:land price (Ricardian approach); land profitability (fixed-effects model) • Xit: observable variables • Wit: climate variables • estimated θ: response to climate changes

15. Agricultural model • Second stage: simulation • Climate change scenarios • GCM-projected climate (A1B and A2 scenario) • timeslices:2010-2039; 2040-2069; 2070-2099

16. Agricultural model:Census Data • Agricultural Census: 1970, 75, 80, 85, 95 • Municipality level data - approx. 3,200 obs by year • Land acreage, crop prices and quantities

17. Agricultural model:climate data • Base climatology: • Climate Research Unit (CRU) • 10 minute (~20km) interpolated grids intersected with AMC boundaries • 30-year averages (1961-1990) • temperature (Celsius) • precipitation (mm/month) • Seasonal specification • December, January, February • March, April, May • June, July, August • September, October, November

18. Agricultural model:climate change data • General Circulation Model (GCM) projections • Wagner Soares, INPE/CPTEC • Projected timeslices • 1961-1990 • 2020s • 2050s • 2080s • Intersected grids with MCAs Projected climate change = observed (CRU) base + intra-modeled anomaly

19. Agricultural model:Geographic data (soil) 1:5,000,000 digital maps of Brazilian soils (Embrapa) • Erosionpotential • PERO1 = 7.5 - 15% inclination • PERO2 = 30 - 45% inclination • Proportion of município in each of 12 categories of soil type • Proportion in 5 categories of soil quality

20. Soil type – 1:5,000,000

21. Results: variation in agricultural profitability

22. Results: variation in agricultural profitability – B2 scenario

23. Results: variation in agricultural profitability – A2 scenario

24. Results: variation of Temperature and Precipitation

31. Results: variation in converted land* and land value * Converted land: total area used in agro-pastoral activities including six land use categories (temporary and perennial crops, planted and natural pasture, planted forest and short fallow).

40. Agricultural model:Preliminary Conclusions • Overall impact of climate change will be quite modest in the medium term, but effects are significantly more severe in the long term • Consequences of climate change will vary across Brazilian regions • North and Center-West may be significantly harmed • South may benefit mildly