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Policy Impact Analysis of Policies Using Partial Equilibrium Analysis (PEA)
Multi-Market Models (MMM)The Case of Paraguay and Other Examples
About the FAO Policy Learning Programme
This programme aims at equipping high level officials from developingcountries with cutting-edge knowledge and strengthening their capacity tobase their decisions on sound consideration and analysis of policies andstrategies both at home and in the context of strategic internationaldevelopments.
Related resources
• See all material prepared for the FAO Policy Learning Programme
• See the FAO Policy Learning Website: http://www.fao.org/tc/policy-learning/en/
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By
of the
FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS
Policy Impact Analysis of Policies Using Partial Equilibrium Analysis (PEA) Multi-Market Models (MMM)
The Case of Paraguay and Other Examples
Lorenzo Giovanni Bellù, Agricultural Policy Support OfficerAgricultural Policy Support Service, Policy Assistance and Resource Mobilization Division, FAO, Rome, Italy
and
Rosaria Vega Pansini, ConsultantBocconi University, Milan, Italy
About EASYPol
The EASYPol home page is available at: www.fao.org/easypol
This presentation belongs to a set of modules which are part of the EASYPol Resource package: FAO Policy Learning Programme : The Policy Framework: Policy Impact Analysis Using PEA and MMM
EASYPol is a multilingual repository of freely downloadable resources for policy making in agriculture, rural development and food security. The resources are the results of research and field work by policy experts at FAO. The site is maintained by FAO’s Policy Assistance Support Service, Policy and Programme Development Support Division, FAO.
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Purpose and objectives
PurposeTo illustrate PEA/MMM as one of the approaches
used in assessing policy impacts and compare it with selected other approaches.
Learning Objectives
Describe the balancing mechanism on which a partial multi market model is based.
Identify channels through which a policy measure impacts on costs, revenues, welfare of producers and consumers.
List advantages and disadvantages of PEA/MMM compared to other approaches for impact policy analysis.
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Topics covered:
1. General aspects of the PEA approach
2. Simple exercise on Partial equilibrium Analysis
3. Description of a country case: Agricultural policy in Paraguay
Identifying selected policy issues and policy measures for Paraguay;
4. Review the main features of the Multi-Market Model for policy impact analysis
5. Construction of a base scenario for policy analysis
6. Simulation results
7. Use of policy impact results to formulate policy advice
8. Study of other analytical tools for policy impact analysis
Contents
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Exercise on Partial Equilibrium Analysis (PEA)
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Partial Equilibrium Analysis exercise
At the end of this exercise the participants will be able to:
Explain the process through which supply and demand of a specific good match under some assumptions
Define the concept of elasticity of demand and supply
Explain how the simple PEA framework can be extended to a multi-market model (MMM)
Exercise based on the case of
the formal firewood chain
in Burkina Faso, Ouagadougou area
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The demand of a good/service is the quantity of thegood/service required by a consumer to satisfy itsneeds.It is determined by (is a function of) a set of elementssuch as prices and income. Example:
) , ,,( cookers gas firewood Demanded
firewood IncomePPPQQ D=
( - ) ( + ) ( - ) ( + )
Concept of demand function
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The functional form of the demand is the specificrelationship between the quantity demanded and theelements determining it. It is “assumed” by theanalyst. Simple example: Linear functional form:
gas firewood Demanded
firewood PPQ gf ββα ++=
Q firewood, P firewood and P gas are the “variables” of which Q firewood (b) P firewood (b) and P gas (b) are observed values of the variables “at the benchmark” ;
Alpha and the betas are the “parameters” of the demand function. Betas are usually estimated or worked out from “elasticities”. Alpha is usually “calibrated”.
Functional form of the demand
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Some definitions
OWN PRICE ELASTICITY: The “Elasticity” of the quantitydemanded of a given good with respect to its own price is thepercentage change of the quantity demanded when its own pricechanges of 1%, other things equal
CROSS PRICE ELASTICITY: The “Elasticity” of the quantitydemanded of a given good with respect to the price of any othergood is the percentage change of the quantity demanded whenthe price of the other good changes of 1%, other things equal.
CALIBRATION: Calculation of one or more parameters of thedemand function on the basis of the observed values of thevariables in the baseline situation.
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Example: Firewood in Burkina Faso baseline values and parameters
BaselineItem unit valuesFirewood quantity Qd b ,000 tons 1,100 Own price elasticity (guesstimate) 0.90- Cross price (Gas) elast.(guesstimate) 0.40
P firewood b US$/ton 68.00 Pgas b US$/ton 580.00
Baseline values and elasticities
Parameters of the demand function
Beta firewood -14.56Beta gas 0.76alpha 1650.00
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Demand side of the market
gas firewood Demanded
firewood 0.76 56.14 650,1 PPQ +−=
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Supply side of the market
Supply can be a function of prices as well, becauseproducers may willing to produce more for higher prices andvice-versa.
However, for a given price, supply can also be infinite if thatprice is high enough to cover (constant) production costs. Inthat case, the supply function is:
prod firewood C =P
68 firewood =P
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Numerical example
Show how a policy scenario changing the price of a substitute (the gas) changes the quantity of firewood
demanded by consumers
Spreadsheet exercise
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A recent FAO application of PEA – MMM was run in Paraguay, in the context of the ROA project, a six year programme aimed at:
Identifying and measuring the contributions generated by the agricultural sector in developing countries to poverty alleviation, social stability, environmental sustainability cultural identity.
An application of PEA – MMM to Paraguay
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Socio-economic situation of the
country:
Stagnating economy;Worsening of socio-economic conditions of the population;Increasing incidence of poverty: from 30.3% in 1994 to 39.2% in 2005;Increasing trend of both rural and urban poverty although the latter increased much more than the former.
The Paraguay case
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Agricultural sector: Diagnosis
Substantial concentration of land ownership
Increasingly capital intensive agricultural production
labour intensive crops (relevant to small farmers) shares to total crop production have been falling while the share of crops produced on farms intensive in the use of commercial inputs has increased.
These structural changes have reduced pro-poor bias of agricultural growth contributing to an increase in poverty;
Decreasing public expenditure in agriculture.
The Paraguay case [cont’d]
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Policy objectives:
Decrease the incidence of extreme poverty
Improve food security through:
Pro-poor agricultural growth
Improved distribution of land
Increased small farm productivity
Expansion of food supply
Increase the level and improved quality of public expenditure
The Paraguay case [cont’d]
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2. Possible policy options:
Alternative policies to improve farm competitiveness (change in tariffs; introduce export subsidies; full implementation of free trade agreements; exchange rate managements policies)
Improve technical assistance to small farmers in order to raise their productivity (improved seeds, provide funds to purchase higher quality seeds, information services);
Modernizing processing industry linked to agriculture
Increase net income of smallholders: lowering transaction costs and trade margins (through improved transport infrastructures, increase credit availability to deal with capital constraints; improve the quality of drinking water, of sanitation and health facilities, etc.)
The Paraguay case [cont’d]
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3. Selected Policy Related Questions
Is the identified policy measure contributing to poverty alleviation?
How much should the government invest to obtain tangible results ?
Is the identified policy measure environmentally sustainable?
What would be the most efficient policy mix to complement/enhance socio-economic impacts of the identified policy measure?
The Paraguay case [cont’d]
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To answer the previous questions, a socio-economic impact assessment of policy measures is needed.
Base scenario (Without policy): Socio-economic Situation in 2004
Socio-economic indicators chosen: Net income of different social groups and related with-without policy percentage change
Poverty incidence
Food security indicators
The Paraguay case [cont’d]
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Income and expenditure effects: By means of technological and trade margin changes, variations in income and expenditure by social group are simulated.
Poverty reduction aspects: combining the results of the MMM model in terms of income generation with household survey data to model income and expenditure effects.
Food security aspects: combining the simulation results of the MMM in terms of expenditure by social group with household survey data to generate information on calories and nutrient intake at the household level.
It is important in this context to capture income generating processes and expenditure paths, linked to technological
changes. That is why a Multi-Market Model (MMM)associated to household level data was chosen.
The Paraguay case [cont’d]
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Focuses on quantity-price equilibrium in inter-dependent markets. Consumer demand and Producer supply behavior explicitly modeled.
It allows to analyze the generation of net revenue and its allocation, by group of agents.
Most policies related to markets and chains. input-output price policies and policies on technology and factor use No macro-economic closure.
System of simultaneous equations and constraints, usually modeled in GAMS (rarely on MS Excel)
Knowledge of economic modeling and availability of elasticities for the different agents and different markets.
Relevance for poverty/FS
Coverage of policy measures
Resource needs
Technical structure
General characteristics
Multi Market Model features
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7 commoditiesCotton, maize, cassava, soybeans, wheat, sugar and livestock
4 Household groups:Small farmers, other farmers, non-farm urban, non-farm rural
6 blocks of equations:• Supply• Input demand• Final demand (consumption)• Income generation • Prices• Equilibrium conditions
Base year: 2004Calibration: based on three sets of data:
• Observed levels of quantities (levels and shares)• Observed Prices• Behavioral Parameters (own, cross price and other elasticities)
The Paraguay case: Specific features of the model
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Comparative analysis of the impact
Base indicators
Indicators with
policy 6) Scenario with policySimulations results
4) Base scenario
2) Policy measureIncreasing technical
assistance to small farmers3) ? Impact of measure ?
5) Impact Model
Policy Analysis Tool: Multi-Market Model
1) Policy issuesRural development and
poverty alleviation
The Paraguay case: Summary analytical framework
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Simulation exercises based on multi-market model: impact
Change in HH income percent
SCENARIOS Small farm
Other farm
Non farm rural
Non farm urban
total
0) Baseline=no simulation - - - - -
1) Plus 20% yields all crops Small Farm (SF) 10.8 0.0 0.4 0.9 1.4
2) Plus 20% yield all crops SF and minus 20% trade margins
12.4 1.0 0.4 0.3 1.7
3) Plus 30% maize yields to SF 6.8 0.0 0.0 0.1 0.7
4) Plus 30% manioc yield to SF 4.6 -0.5 0.3 0.8 0.6
5) Plus 10% yields all crops and all farmers 5.4 6.7 0.3 0.6 2.1
The Paraguay case: Simulation results
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Simulation exercise based on multi-market models: impact on
Poverty Incidence
SCENARIOSSmall farm
Other farm
Non farm rural
Non farm urban
total
0) Baseline=no simulation - - - - -
1) Plus 20% yields all crops SF -4.1 0.0 -0.1 -0.2 -1.7
2) Plus 20% yield all crops SF and minus 20% margin
-4.5 -0.1 -0.1 -0.2 -1.8
3) Plus 30% maize yields to SF -2.7 0.0 0.0 0.0 -1.1
4) Plus 30% manioc yields to SF -2.0 0.0 -0.1 -0.2 -0.9
5) Plus 10% yields all crops and all farmers -2.2 -2.7 0.0 -0.2 -1.0
Policy Impact Analysis: simulation results
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CommentsSmall Farmers sensitive to manioc/maize (measures 3 and 4);
The maize sector does not seem integrated downstream (almost no changes in other incomes). High self-consumption?
Measure 2 gives the maximum outcome to the “small farmers”
Measure 2 compared to measure 1, shifts part of the income from non-farm urban to small farm, as captured by poverty incidence ind.
Measure 5 provides the maximum total income increase (+2.1%)
RemarksAssumption: policy measures are exogenously funded. No macro-economic consistency imposed (deficit constraints, tax recovery etc).
The relative costs of the different policies is not considered (e.g. if policy 1 is much cheaper than policy 2, could possibly be justified on cost-effectiveness grounds)
The Paraguay case: Comments and remarks
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StrengthsIndicates the channels through which a given policy changes produce its effects.
Allows to model specific agricultural products.
Allows production decisions to be influenced by changes by output and input relative prices.
WeaknessesOnly direct and indirect effects in a small number of related markets.
Average income of different household groups are modelled assuming within groups distributional neutrality.
Does not allow analysis of investments.
Is a static model.
There is no macro-economic consistency
MMM strengths and weaknesses
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Other applications of PEA-MMM: Soybean markets and CO.SI.MO. model
The MMM approach has been recently applied at FAO by EST-TCA in the context of a soybean market study in Latin America
The study used the CO.SI.MO. Model
(COmmodity SImulation MOdel), a joint FAO-
OECD partial-equilibrium world agricultural
model for forward looking analysis of the
agricultural sector and related markets, policies and
emerging issues.
Goal of the study: Investigate trends of soybean demand under different international scenarios, such as: 1) reduction of demand from China; 2) worsening of yields; and 3) increased production costs.
Findings: the possible reduction of imports of Chile would affect Brazil and Argentina
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Other applications of PEA-MMM: Soybean markets
Results:1. Reduction of China imports would have a slight and almost even impact on
the quantities produced the countries of the region;2. Possible reduction in yields would however enable Brazil to increase its
volumes, due to less limiting factors than other countries;3. Increased production costs would leave Brazil unaffected but would
significantly reduce production of Argentina.
Quantity Reduction of China imp. Reduction of yields Increased prod.costsBaseline tons var % tons var % tons var %
Argentina 50,079 48,328 96.5% 46,562 93.0% 38,979 77.8%Brasil 79,362 75,616 95.3% 84,204 106.1% 78,927 99.5%Paraguay 6,043 5,897 97.6% 5,143 85.1% 5,753 95.2%Total 135,484 129,841 95.8% 135,909 100.3% 123,659 91.3%
This scenario analysis would enable countries to react with suitable policy measures whenever the mentioned events should occur.
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Other approaches for impact analysis: Micro accounting approach
Use of detailed household data to generate policy scenarios, by directly introducing changes in the data base, after selection of households affected.
Linked the quantity/quality of available data. Good for poverty (expenditures, consumption….)
Take only the direct effects. Not adapt for structural policies with strong indirect effects.
Accounting frame without explicit modelling of behaviour feedback.
Limited in most cases when household surveys have been carried out.
Relevance for poverty/FS
Coverage of policy measures
Resource needs
Technical structure
General characteristics
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Other approaches: Computable General Equilibrium Models
The models allow us to work in a coherent macro context and flexible prices, taking into consideration the behaviour aspects of economic agents.
The models allow us to analyse the establishment of revenue by group of agents and their expenditures.
Most of the policies concerned with markets, products and revenues. Weak in investments.
Simultaneous constraints and equation system.
We need strong knowledge of economic modelling, micro and macro data, time and resources.
Relevance for poverty/FS
Coverage of policy measures
Resource needs
Technical structure
General characteristics
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Other approaches: Sectoral and macro-economic accounting frameworks
Chain analysis and the Social Accounting Matrices (SAM) allow us to analyse the structural inter-dependencies.
The chain anlaysis allows us to analyse the production/ consumption systems. With SAM, we can analyse the macro-intersectoral links.
Only policies with impacts that do not deviate too far from the base situation.
Accounting frameworks with no explicit modelling of behaviour. For SAM, fixed prices.
Possible with some knowledge of accounting rules at company and macro levels. Much macro and micro data needed.
Relevance for poverty/FS
Coverage of policy measures
Resource needs
Technical structure
General characteristics
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Other Approaches: Integrated macro-micro approaches
These allow us to work in a macro coherent and flexible price context, by integrating the level of detail of micro-accounting approaches.
The approaches allow us to analyse the establish-ment of revenue and food expenditures by household.
Most policies concerned with markets, products and revenues. Weak for invetstments.
Different approach combinations are possible.
Strong knowledge of economic modelling. Needs: micro-macro data, time and resources.
Relevance for poverty/FS
Coverage of policy measures
Resource needs
Technical structure
General characteristics
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Pro-Poor Livestock Policy in Vietnam
Launched in 2001 to facilitate and support the formulation and implementation of livestock-related policies and institutional changes that have a positive impact on the world’s poor.
Example of integrated macro-micro approaches
To evaluate policy options for Livestock sector, different techniques have been applied and brought together in the IPALP
Integrated Poverty Assessment of Livestock Promotion (IPALP)
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Integrated Poverty Assessment of Livestock Promotion (IPALP)
The case of Vietnam
Promoting a general understanding of the role of livestock in poverty alleviation
Policy experiments to assess the impact of economy-wide policy of trade liberalization on poverty alleviation with and without concomitant livestock promotion.
Four components:Analysis of initial macro economic conditions
Micro-economic analysis of initial conditions
Dynamic simulation of policies and external economic conditions
Micro-economic assessment of PPLI and related polices
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Integrated Poverty Assessment of Livestock Promotion (IPALP)
The case of Vietnam
Policy Impact Assessment Tool chosen:• Dynamic integrated MICRO-MACRO simulation model
Micro component: econometric estimation of :• Household income generating model• Occupational choice models
Macro component: • CGE model calibrated to production and consumption side
using Social Accounting Matrix
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Integrated Poverty Assessment of Livestock Promotion (IPALP)
The case of Vietnam
Period: 2004-2010
Scenarios:
1. Baseline: no change in the status quo
2. Vietnam accession to the WTO= abolition of all tariffs and export subsidies over the period 2005-2007
3. Vietnam accession to the WTO with a livestock policy implementation that increases productivity in the livestock sector by 25% over five years.
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Integrated Poverty Assessment of Livestock Promotion (IPALP) [cont’d]
The case of Vietnam
Simulation results:
compared to the baseline scenario, the WTO shows most of its benefits for poverty reduction, especially for urban population.
When the WTO scenario is associated with the promotion of the livestock sector, poverty reduction is less in urban areas but very significant for the rural population.
Rising rural population participation in the WTO-induced economic expansion trough livestock promotion makes the third scenario more pro-poor.
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Potential:
The most completed models, encompassing an analysis of demand and supply at the same time;
Analysis at both macro and micro level;
Analysis of direct and indirect effects.
Limit:
Very complex models;
Requirements of different sources of data;
They do not take into account feedback effects generated at the micro level into the macro system.
Integrated Micro-Macro simulation models: Remarks
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Quantitative socio-economic policy analysis provides a support to policy making. Analytical efforts need to be well calibrated, taking into consideration many elements, such as:
policy measures analised
answers to be provided
donors
time
availability of resources
In many practical situations, an effective quantitative socio-economic impact analysis depends on:
the time frame of the exercise
the existing human capacity
the selection of the most appropriate approcach to analyse policy implications
Conclusions