Macro-economic modeling in the Food-Energy-Water-Nexus
- 1. Macro-economic modeling in the Food-Energy-Water-Nexus The 2010 Social Accounting Matrix for Malawi & a Yield-Water module Franziska Schuenemann, M.Sc., M.A. University of Hohenheim Institute of Agricultural Economics and Social Sciences in the Tropics and Subtropics
- 2. Overview 1. What is the FEW Nexus 2. Policy: Expansion of biofuel (ethanol) production from sugarcane 3. Computable General Equlibrium Models (CGE) - Circular flow of income - Malawi 2010 macro SAM - Malawi 2010 disaggregated micro SAM - Findings 4. Yield-Water module - Methodology - Findings 5. Next steps and question for discussion 2
- 3. What is the Food-Energy-Water-Nexus? • Three nexus sectors intrinsically tied together and dependent on each other Production and consumption linkages Competition for the same resources • Policy targeting one sector invariably affects the other two Need policy approach to minimize trade-offs in resource use and to build synergies Need for economy-wide integrated framework to determine impact of different policy scenarios ex ante Water Supply security Available resources Energy security Food Security Urbanization Population Growth Climate Change Global Trends 3 After Hoff, 2011
- 4. Policy: Expansion of biofuel (ethanol) production from sugarcane Policy Background • Ethanol-gasoline blend in National Energy Policy • Sugarcane cluster in National Export Strategy Potential Effects • Energy security: • Positive if ethanol is blended into gasoline or if ethanol exports can be used to buy petrol • Negative regarding hydropower if water levels decrease due to extensive irrigation • Food security: • Negative if land is taken away from food crop production: lower food availability • Positive if poorer farmers can take part in sugarcane production (Herrmann et al., 2013): higher income and improved access to food • Water security: • Negative due to large amounts of irrigation water Development of simulation models to assess these complex effects 4
- 5. Computable General Equlibrium Models (CGE) • Capture all links between markets and agents in an economy • Combine economic theory with real world data to simulate different policy scenarios ex ante • Consists of two parts: • Theoretical model: explains the behavior of household, producers, etc. through mathematical equations • The social accounting matrix (SAM): economy-wide representation of a country’s economic structure 5
- 6. Factor market Producers Households Product market Factor cost Wages & rents Private cons. Intermediate dem. Save/invest Household savings Income taxes Government Government expenditure Gov. savings Investment demand Domestic demand for final goods (C + I + G) Rest of the world Import payments (M) Export receipts (X) Foreign savings Sales revenue 6 Circular flow of income
- 7. The 2010 Malawi Social Accounting Matrix (SAM) • Base-year equilibrium state for the CGE model from which simulations can be conducted • Captures all income and expenditure flows among households, producers, the government, and the rest of the world during the year 2010 in “accounts” • Main data sources of 2010 Malawi SAM: National accounts (with help from NSO workshop) Annual Economic Survey Balance of payments Input–output tables (supply–use tables) Malawi Integrated Household Survey (IHS) 2010/2011 7
- 8. The 2010 Malawi “macro” SAM 8 Activities Commodities Factors Enterprises Households Government Investment Rest of the World Total Activities 1,705,532 1,705,532 Commodities 733,923 147,937 918,696 162,955 169,863 183,696 2,317,071 Factors 971,609 68 971,677 Enterprises 240,808 28,515 35,792 305,114 Households 705,762 241,952 27,894 2,519 978,127 Government 87,338 56,767 47,750 48,368 240,223 Savings 6,102 9,437 18,109 136,215 169,863 Rest of the World 376,264 25,107 293 2,244 2,750 406,657 Total 1,705,532 2,317,071 971,677 305,114 978,127 240,223 169,863 406,657 2010 Macro SAM for Malawi (Millions of Kwacha)
- 9. The disaggregated micro SAM • 59 Sectors: • 19 in agriculture, 20 in industry & 11 in services • Factors of production • Labor (6) by skill/education and rural/urban • Land and livestock (7) by farm type (small-, medium-, large-scale and estate) • Capital (4) by sector (agriculture or non-agriculture) and farm size • 30 types of households: • Rural/urban • Farm/nonfarm • Farm size • Income quintiles • Next step: Regional disaggregation 9
- 10. Micro SAM findings Income quintile Government transfers as percentage of HH income 1 0.01 2 0.06 3 0.15 4 0.47 5 4.77 10 Household Type Non-agricultural capital as percentage of HH income Rural/small 10.24 Rural/medium 10.97 Rural/large 13.65 Rural/nonfarm 28.91 Urban/farm 11.84 Urban/nonfarm 37.20
- 11. Yield water module Calculates water needs for 14 different crops in Malawi including maize and sugarcane 11 Methodology • Following FAO linear yield response to water (Doorenbos & Kassam, 1979) 1 − 푌푎 푌푚 = 퐾푦 1 − 퐸푇푎 퐸푇푚 1. Calculation of reference evapotranspiration ET0 of grass with the FAO Penman- Monteith equation based on historic climatological data for 20 weather stations in Malawi for the years 1983-2005 (Allen et al., 1998) 퐸푇0 = 0.408Δ 푅푛 − 퐺 + 훾 900 푇 + 273 푢2(푒푠 − 푒푎) Δ + 훾(1 + 0.34 푢2) 2. Calculation of ETm for each crop by multiplying ET0 with the respective crop coefficient: 퐸푇푚 = 푘푐 퐸푇0 3. Calculation of ETa through a daily soil-water-balance
- 12. Yield water module findings 12 350 300 250 200 150 100 50 0 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 ET in mm Actual and potential evapotranspiration for maize in Southern Malawi ETa ETm
- 13. Yield water module findings 13 1000 900 800 700 600 500 400 300 200 100 0 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 ET in mm Actual evapotranspiration for maize and sugarcane in Southern Malawi Maize Sugarcane
- 14. Next steps and questions for discussion Next research steps: • Combination of yield-water module with CGE model and SAM • Extension of the SAM with sugarcane produced for biofuel as well as ethanol processing sectors • Link to microsimulation module for poverty and nutrition analysis based on Integrated Household Survey (IHS) 2010/2011 Questions: • Is there new data for the ethanol supply chain in Malawi? • What is the role of water security in Malawian policy making and will analyses such as ours raise more awareness? 14
- 15. 15 References Allen, R.G., Pereira, L.S., Raes, D. & Smith, M. 1998. Crop evapotranspiration. Guidelines for computing crop water requirements. In: FAO Irrigation and Drainage Paper No. 56. Rome, FAO. Hermann, R., Grote, U. & Brüntrup, M., 2013. Household Welfare Outcomes of large-scale agricultural Investments: Insights from Sugarcane Outgrower Schemes and Estate Employment in Malawi. Paper prepared for presentation at the “Annual World Bank Conference on Land and Poverty”, Washington DC, April 8-11, 2013. Hoff, H. (2011). Understanding the Nexus. Background Paper for the Bonn2011 Conference: The Water, Energy and Food Security Nexus. Stockholm Environment Institute, Stockholm.