10 kuhlgatz micro_data_cge_livestock

DatumSeite 1 Dr. Christian H. Kuhlgatz

Linking household data to agricultural models: Livestock in Africa

Linking household data to agricultural models with a focus on livestock in AfricaChristian H. Kuhlgatz, Aída González Mellado , Petra SalamonThünen Institute of Market Analysis

Accra6 November 2013



Development of Data and Tools for Livestock Policy: How can the TI contribute?

• Department of Farm Economics

• Department of Market Analysis• What we do: Policy support and research on development of

agricultural markets & trade policy• Prominent tools: CGE and partial equilibrium models

GTAP, MAGNET, AGMEMOD,…• Analyzed policy effects on EU - e.g.: Trade liberalization, ban on

EU soybean imports, …

Application of these models to African countries?



AGMEMOD goes Africa

•Capacity building training and AGMEMOD country model implementation in Braunschweig, June 2013 for

• Three African researchers interested in food trend analysis• supported by Regional Strategic Analysis and Knowledge Support

System (ReSAKSS)

•Reduced set of 5 crop markets for the start• Ethiopia with wheat, corn, sorghum, teff, and haricot beans• Kenya with wheat, corn, sorghum, haricot beans, sweet potatoes• Uganda with corn, sorghum, cassava, haricot beans, and sweet

potatoes

• Baseline finished, working on scenarios



Modeling livestock: specific issues

• Livestock is a long term investment• Dynamic modeling approach needed

• Animals are used for multiple purposes• Animal products for income and own consumption• complex crop-livestock interactions

(feed as input, manure and draft power as output)• Savings, transport services,…

To avoid capturing net effects: Relevant economic linkages and effects have to be incorporated into the model

• Capture heterogeneous effects on different households (spatially, income differences, rural-urban, …)



CGE or PE models

• CGE models provide a consistent and comprehensive representation of the economy and world trade

• Partial equilibrium: more detailed markets, flexible in capturing sector policies

• Objective: measure the effect of livestock activities for the economy

• Computable general equilibrium (CGE) models• allow feedback between livestock sector and other parts of the economy

• CGE models use ex ante simulations, and are calibrated by employing a Social Account Matrix (SAM)

• SAM: a snapshot of the country’s economy at a specific year



SAM data requirement for the country considered…



Approaches to integrate micro-level data into CGE

• Top down approach: Macro-Micro-Simulation• Simulations with parameters for representative household-

categories derived from HH-level• After Simulation: Changes in consumption and prices are passed

down to corresponding HHs in the survey.• Per capita expenditure and poverty measures are recalculated• No feedback from households to macro level

• Bottom up approach• Include all households into the CGE model• Time-consuming procedure: harmonize data of micro and macro

level



Sources for livestock data in Africa

• Livestock-specific micro-level data needed• Agricultural and livestock census data• Sample surveys with specific scope• Routinely collected data on prices• LSMS multi-purpose surveys• LSMS-ISA & Livestock Survey Module

• Information from different datasets can be combined, allowing to impute mean projections of livestock activities (e.g. Behnke 2010)



LSMS-ISA: Once source for all?

• Living Standard Measurement Study (World Bank)• Nationally representative household survey• Early versions: little information on livestock, e.g. insufficient

information on animal products, their main buyer and costs• Since 2009/10: LSMS-ISA

(Integrated Survey on Agriculture)• Panel data approach

• Ethiopia, Tanzania, Malawi, Niger, Nigeria, Uganda. Mali will follow…



LSMS-ISA: Data availability and disaggregation

• Household income categories can be considered

• Very good coverage: Livestock production, own consumption and savings

• Factors • Labor separable: Agricultural &Non-Agricultural Labor• Capital: in some surveys, livestock can be attributed to purpose• Input costs often not available for livestock products

• Taxes• Mostly not collected for household sales

• Inter household transfers• Lacking data on agricultural products transferred

• Final market demand• Disaggregation by buyer sometimes possible but not amount/value



Possible improvements for databases from CGE view

• Questionnaire design:• Do not provide the option to choose vague units that cannot be

converted into the metric system, provide conversion factors• Questions on main buyer of animal products should not allow

answers that indicate the location of the selling point

• Questions on production structure, input sources and buyers of livestock output• Input costs particularly for animal products incomplete and not

separated by input provider• Some surveys ask for main buyer, but best would be to indicate the

amount and value of sales to each buyer

• Collect data on taxes and livestock-related subsidies



Outlook and Africa specific challenges

• CGE can measure the effect of livestock on whole economy• E.g. analyses on poverty or labor migration• 2nd step: Partial equilibrium models can provide detailed results for

livestock market

• Recent LSMS-ISA studies include much usable data for CGE• In many countries not much changes needed to become a crucial data

source for macro-modeling

• Panel data collection of LSMS-ISA• Data of same household from several time periods allow modeling

effect of (positive and negative) savings on livestock productivity and welfare

• Challenge: significance of informal trade flows



Thank you

[email protected]ünen Institute of Market Analysis

www.ti.bund.de

10 kuhlgatz micro_data_cge_livestock

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