Joint Research Centre (JRC) – IPTSAGRILIFE Unit

E. Ferrari, S. Acs, J. Delincé

The link between Agricultural and Rural Statistic and Agricultural Economic Modelling

13-15 October 2010ICAS-V Kampala

http://ipts.jrc.ec.europa.eu

http://agrilife.jrc.ec.europa.eu/s_home.html

What AGRILIFE does in modeling?

GTAP 2010 Award

Strategy versus Economic Models Data Needs?

• The economic dimension covers agricultural production, • The economic dimension covers agricultural production,

markets, and farm / nonfarm income.

• Core data should provide inputs to the national accounts and

global balances of supply and demand for food and other

agricultural products.

•Core data items that are crops should account for a major

proportion of land use, contribute significantly to farm and rural

house- hold well-being, and have an effect on the environment

and climate.

Core Data as in the Strategy 1/2

Core Data as in the Strategy 2/2

Two Case Studies

We will analyse two agriculture policy questions:

• Malawi: Impact of the 2008 agro-food commodities and oil

price boom on the economy and the relevance of maize

input subsidies input subsidies

• Sierra Leone: Sustainable Farm income generation

through:

- support to rice production (self-sufficiency)

- support to coffee and cocoa production (export)

Case study: Malawi

Model used :

Computable General Equilibrium (CGE), i.e.

Single-country static CGE models (IFPRI standard)

based on SAM (Social Accounting Matrix) data provided by

IFPRI (Thurlow et al. 2008).

MACRO Policy Question :

- Following the adoption of an input subsidy programme,

together with import tariff and sale domestic tax reductions

; as well as an increase in export tax;

- What was the impact on maize production, domestic

price, imports and smallholder farmers welfare ?

CGE Modeling

Macro Modelling – Social Accounting Matrix

Malawi: some results

Source: Piero Conforti, Emanuele Ferrari and Alexander Sarris 2009

Malawi: fit to the needs

Case study: Sierra Leone

In the frame of 8th EDF STABEX funds (2005):

• Support to rice production, as basic staple food for self-

sufficiency. This will help towards improving food security

and reducing dependency on volatile world market prices.

• Support to coffee and cocoa production as main cash

crops for export. It aims to create and increase farm crops for export. It aims to create and increase farm

household income.

AIM: impact analysis of these policies on household

income, labor use and production structure; using FSSIM

model adapted to small farm households in Sierra Leone.

Micro Modelling

DATA BASE ON FARM RESOURCES

Land Water LabourMachinery

...

INPUT/OUTPUT COEFFICIENTS

SURVEY

FSSIM-MP

Database onsoil,

wheather...

Data on agricultural policiesand socio-economic

environment

Database on crops,animals, agro-amenagement...

- Farm income- Externalities - Nitrate leaching - Soil erosion - Energy consumption - Nitrate Use - Water Use - ...- Agricultural activity levels - Land use - Animal number..

FSSIM-MP

COMMONMODULE

LIVESTOCKMODULE

CROPSMODULE

INVESTMENTMODULE

RISKMODULE

POLICYMODULE

PERENNIALMODULE

PMPMODULE

PREMIUMMODULE

Maximize: Utility functionSubject to: Agronomic, technical,economic, institutional, feeding ...constraints

FSSIM-Outputs

Case study: Sierra Leone

Micro model data requirement vs. Global Strategy suggestion

Variable Value Quantity Constraints

(per year) (per farm)

Input costs and quantities

Water value/m3 m3/crop/ha max. availability in m3/year,month

Fertiliser value/kg kg/crop/ha max. availability in kg/year

Pesticide value/l,kg l,kg/crop/ha max. availability in l,kg/year

Seeds value/kg kg/crop/ha max. availability in kg/year

Feed value/kg kg/livestock max. availability in kg/year

Household consumption value/product quantity/product min. requirement/yearHousehold consumption value/product quantity/product min. requirement/year

Resource requirement

Land value/ha land/crop, livestock total available in ha/land type

Machinery value/unit machinery/crop, livestock total available in number/machinery type

Buildings value/unit buildings/crop, livestock total available in number/building type

Livestock value/head head/crop, livestock total availability in head/year

Household labour - hours/crop,livestock total available in hours/year,period

Hired labour wage/hour hours/crop,livestock total available in hours/year,period

Output prices and quantities

Crops value/kg kg/ha max. marketable/year

Livestock value/head kg/head max. marketable/year

Data collection requirement

Frequency yearly 5-10 years 5-10 years

* In grey: not or partially collected by Global Strategy

Case study: Sierra Leone

Micro model data requirement vs. Global Strategy suggestion

-Information beyond the core crops (rice, maize, sorghum) is needed, on

-cash crops (coffee, cocoa)

-subsistence crops (cassava, sweet potatoes, millets, ground nuts, oil palm, fruits, vegetables)

-Disaggregated level (farm level, hectare/livestock level)-Disaggregated level (farm level, hectare/livestock level)

-Frequency

-Yearly: input/output prices

- Every 5-10 years:

-Farm structure data:

-type of crops/livestock produced on farm

-constraints at farm level

-Production technology data:

-input/output quantities per ha or head

Conclusions

Macro level:

- Links with national accounts, trade accounts are welcome.

- Lack of Input-Output tables among activity sectors challenges

the use of CGE (but AGRI stats are only one out of many)

- Level of disaggregation good enough to build adequate SAM

- Frequency required in line with CGE needs- Frequency required in line with CGE needs

Micro level:

-Additional specific data collection will be needed

-Global Strategy is insufficient, however, a good start point as

it gives useful information on the basic crops/livestock

production activities.

Thanks for your attention