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

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

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

3After Hoff, 2011

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

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

Factor

market

Product

market

Producers Households

Factor cost

Wages &

rents

Private

cons.

Intermediate

dem.Save/invest

Household savings

Government

Income taxes

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

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

The 2010 Malawi “macro” SAM

8

Activities Commodities Factors Enterprises Households Government InvestmentRest of the

WorldTotal

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)

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

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

Yield water module

11

Calculates water needs for 14 different crops in Malawi including maize and sugarcane

Methodology

• Following FAO linear yield response to water (Doorenbos & Kassam, 1979)

1 −𝑌𝑎𝑌𝑚

= 𝐾𝑦 1 −𝐸𝑇𝑎𝐸𝑇𝑚

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)

𝐸𝑇0 =0.408∆ 𝑅𝑛 − 𝐺 + 𝛾

900𝑇 + 273

𝑢2(𝑒𝑠 − 𝑒𝑎)

∆ + 𝛾(1 + 0.34 𝑢2)

2. Calculation of ETm for each crop by multiplying ET0 with the respective crop coefficient: 𝐸𝑇𝑚 = 𝑘𝑐 𝐸𝑇0

3. Calculation of ETa through a daily soil-water-balance

Yield water module findings

12

0

50

100

150

200

250

300

350

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

ET

in m

m

Actual and potential evapotranspiration for maize in Southern Malawi

ETa

ETm

Yield water module findings

13

0

100

200

300

400

500

600

700

800

900

1000

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

ET

in m

m

Actual evapotranspiration for maize and sugarcane in Southern Malawi

Maize

Sugarcane

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

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.