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10 kuhlgatz micro_data_cge_livestock
1. Linking household data to agricultural models
with a focus on livestock in Africa
Christian H. Kuhlgatz, Aída González Mellado , Petra Salamon
Thünen Institute of Market Analysis
Accra
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Dr. Christian H. Kuhlgatz
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Linking household data to agricultural models: Livestock in Africa
6 November 2013
2. 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?
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Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
3. 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
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Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
4. 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, …)
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Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
5. 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
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Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
6. SAM data requirement for the country considered…
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Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
7. Approaches to integrate micro-level data into CGE
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Top down approach: Macro-Micro-Simulation
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Simulations with parameters for representative householdcategories 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
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Include all households into the CGE model
Time-consuming procedure: harmonize data of micro and macro
level
Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
8. Sources for livestock data in Africa
• Livestock-specific micro-level data needed
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Agricultural and livestock census data
Sample surveys with specific scope
Routinely collected data on prices
LSMS multi-purpose surveys
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LSMS-ISA & Livestock Survey Module
• Information from different datasets can be
combined, allowing to impute mean projections of
livestock activities (e.g. Behnke 2010)
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Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
9. LSMS-ISA: Once source for all?
• Living Standard Measurement Study (World Bank)
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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)
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Panel data approach
Ethiopia, Tanzania, Malawi, Niger, Nigeria,
Uganda. Mali will follow…
Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
10. LSMS-ISA: Data availability and disaggregation
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Household income categories can be considered
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Very good coverage: Livestock production, own consumption and
savings
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Factors
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Taxes
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Mostly not collected for household sales
Inter household transfers
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Labor separable: Agricultural &Non-Agricultural Labor
Capital: in some surveys, livestock can be attributed to purpose
Input costs often not available for livestock products
Lacking data on agricultural products transferred
Final market demand
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Disaggregation by buyer sometimes possible but not amount/value
Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
11. Possible improvements for databases from CGE view
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Questionnaire design:
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Questions on production structure, input sources and
buyers of livestock output
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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
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
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Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
12. Outlook and Africa specific challenges
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CGE can measure the effect of livestock on whole economy
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Recent LSMS-ISA studies include much usable data for CGE
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In many countries not much changes needed to become a crucial data
source for macro-modeling
Panel data collection of LSMS-ISA
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E.g. analyses on poverty or labor migration
2nd step: Partial equilibrium models can provide detailed results for
livestock market
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
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Dr. Christian H. Kuhlgatz
Linking household data to agricultural models: Livestock in Africa
