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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