Regional Seminar on Compilation and Application of

Supply-Use Tables (SUTs) in Africa

5-8 February 2018 | UNECA, Addis Ababa, Ethiopia

www.agrodep.org

Use of SAMs in

Policy Analysis:

Examples from

AGRODEP

Betina V. DimarananAGRODEP Project Manager

Senior Research Coordinator

IFPRI-MTID

GOAL AND KEY ROLES

OF AGRODEPGoal of AGRODEP To position African experts to take a leading role in both:

the study of strategic development questions facing African countries as a group and

the broader agricultural growth and policy debate, which traditionally has been dominated by external actors and concerns.

Key Roles

Promoting access to and use of state-of-the-art economic modeling tools

Facilitating access to existing data sources for research and policy analysis

Building a network of state-of-the-art researchers:

Supporting collaboration among leading African scientists and their peers outside Africa

Building a dynamic research community that can respond to the emerging and long-term needs of CAADP growth and poverty reduction agenda. 2 w

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BRIEF BACKGROUND

Project launched in October 2010

Facilitated by IFPRI

Partners/Governance include: ASARECA, CORAF-

WECARD, FANRPAN, UNECA, AUC, AfDB, GTAP

Team based in IFPRI-Washington, DC and IFPRI-Dakar

Three major components:

Policy Analysis and Advisory Services – with mentorship

Technical Resources – models, toolboxes, and datasets

Capacity-Strengthening – training, grants, publications,

network

Membership-based

currently 181 regular members from 27 countries ++

30+ affiliate members (in intl. orgns; outside Africa) 3 www.agrodep.org

Product Activity FactorsInstitutiona

l SectorsCapital Total

ProductIntermediate

Consumption

Final

Consumptio

n

& Exports

GFCF &

Changes

in

Inventories

Total

Supply at

Purchasing

Price

ActivityLocal Supply

at Basic Price

Local

Supply at

Basic Price

FactorsFactor

Payments

Total

Factor

Payments

Institu-

tional

Sectors

Imports at

Basic Price

Margin,

Taxes,

&Subsidies

Taxes &

Subsidies

Total

Factor

Payments

TransfersTotal

Income

Capital SavingTotal

Saving

Total

Total Supply

at

Purchasing

Price

Local

Supply at

Basic Price

Total

Factor

Payments

Total

Expenses

Total

Investis-

sement

SAMs: based on SUTs

Supply of

Products

Value

Added

(Supply)

Uses of

Products

Income

Distributio

n

DEVELOPMENT OF SAMS

IN IFPRI

International Food Policy Research Institute (IFPRI) – well

established reputation in the development of SAMs for use in

economy-wide simulations for policy analysis (CGE models),

Examples:

mid-1990s: Macroeconomic Reforms and Regional Integrations

in Southern Africa (MERRISA) project

2016: “Strategies and Priorities for African Countries:

Economywide Perspectives from Country Studies” book

NEXUS project – IFPRI consortium with FAO, IFAD, JRC-IPTS

work directly with national statistical agencies

build consistent SAMs across countries

same benchmark year, standardized economic structure,

single classification and accounting system

transitioning IFPRI SAMs to the NEXUS framework ++

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EXAMPLES OF SAM-

BASED STUDIES FROM

AGRODEP• AGRODEP catalogs SAMs (and other datasets) for African

countries in data library

• We also produce SAMs that AGRODEP members have worked on: Togo, Senegal, The Gambia, Liberia, Mauritania, Sierra Leone, Kenya, Guine-Bissau, Cote d’Ivoire, Burkina Faso

• SAMS are documented in the AGRODEP Data Reports series

• AGRODEP Examples of studies based on SAMs

(1) SAM Multiplier Analysis – Kenya

(2) Single-country CGE Model – Nigeria and Tanzania

(3) Global CGE Model – EU-West Africa EPA

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(1) SAM MULTIPLIERS

Simple type of analysis that can be done with SAMs

The SAM is transformed to an economic model with exogenous and endogenous variables (accounts) and shocks on exogenous variables are transmitted to the endogenous ones through a “multiplier process” (Thorbecke, 2000; Round, 2003)

Exogenous accounts are, in general, government, capital or ROW

Main (strong) assumptions

All relations are linear

Prices are fixed

Excess capacity and underemployed labor exist

Model is demand driven

(1) SAM MULTIPLIERS:

KENYA EXAMPLE

“Poverty, Growth and Income Distribution in Kenya: A SAM Perspective” by R. Gakuru and N. Mathenge. AGRODEP Working Paper #1, June 2012.

2003 Kenya SAM - used to develop a multiplier simulation model which tracks the linkages among demand-driven shocks and economic growth, income generation, and income distribution for different economic groups

Use Pyatt and Round (2006) multiplicative decomposition method to do analysis at the household level

Decompose each multiplier into 3 components: transfer multipliers (within group effects), open-loop multiplier (cross and spill over effects) and closed loop multiplier (effects due to the circular flow of accounts)

Apply this to household income following exogenous injections in the agricultural and manufacturing sectors

Results:

Effects on household income are higher for exogenous injections in agriculture/manufacturing

Effects from agriculture on rural households are higher than on urban households

Urban households have more positive effects than rural ones from manufacturing, with higher deciles getting most of the benefits (inequality)

Kenya should focus not reducing poverty AND on reducing inequality

(2) SINGLE-COUNTRY CGE

ANALYSIS

Computable general equilibrium (CGE) models now widely used tool for policy analysis

Many single-country CGE models developed or adapted/extended from existing models (e.g. IFPRI standard model, PEP 1-1 model)

Initially for trade, but now used in a wide range of policies: agricultural policies, tax policy, environmental policies, demography (see Dixon and Jorgenson, 2012; Devarajan and Robinson, 2012)

Need a consistent framework to calibrate the model

SUT and then SAMs are key to get a starting solution

Should be up to date to reflect current technologies (I-O coefficients), important for simulations and also reflect data for an “average” year (not an outlier)

Importance of cross checking/validation because:

Simple balancing methods could yield oddities

Automatic splitting/aggregation could also yield non-realistic outcomes

(2) SINGLE-COUNTRY CGE

ANALYSIS – TANZANIA

“Sensitivity of CGE Models to Macroeconomic Closure Rules: Evidence from

the IFPRi Standard Model” – by D. Laborde and F. Traore

Toolbox (model code, data - 2006 SAM for Nigeria; 2003 SAM for Tanzania);

Documented in AGRODEP Technical Note #15, October 2017

(Macro)closure is important and drives results (Taylor and Lysy, 1979; Ratso,

1982; Dewatripont and Michel, 1983; Decaluwé, Martens, and Monette,

1988)

Study illustrates the sensitivity of CGE model results to macro-closure rules

(Savings-Investment balance, current account balance, and government

balance) with an example in Tanzania with trade liberalization

Main lessons

Overestimation of welfare effects with flexible current account balance

and government balance

Underestimation of negative impact of reduced investment on future

growth with flexible investment closures (important for static models)

Macroeconomic closure can be more important than changing

parameters value

(3) GLOBAL CGE

ANALYSIS

Multi-country multi-sector CGE models e.g. MIRAGE, MIRAGRODEP, GTAP

In addition to bilateral data problems (mainly trade related), the main issue here is having good SUTs and then SAMs with the same sectoral disaggregation for all countries involved in the analysis

We often need to do some retreatments of the data

To introduce a particular sector/product and proceed to a reconciliation

To reflect some of the characteristics of the economy (ies) under study (for instance loss of tariff revenues due to inefficient tax collection systems in some developing countries)

To correct some biases introduced by the aggregation (tariffs for instance)

(3) GLOBAL CGE

ANALYSIS: EU-WA EPA

“The European Union – West Africa Economic Partnership Agreement: Small Impact and New Questions” – by A. Bouet, D. Laborde, and F. Traore. IFPRI Discussion Paper #1612, February 2017.

Based on GTAP 9 database (base year 2011) with 8 WA countries treated separately.

Model used: MIRAGRODEP-DD, version of MIRAGRODEP with

dual dual modeling a la Stiffel Thorbecke (2003): double dichotomy between urban and rural areas and formal and informal sectors.

Inefficient tax collection systems -> low rate of effective tax collection

Various closure rules for public sector (constant public balance/GDP or public expenses per capita compensated by a lump-sum tax, a consumption tax or an income tax)

A consistent tariff aggregator (Laborde, Martin, and van der Mensbrugghe, 2011) used in an independent module at the tariff line to compute the aggregates

o Conclusion:

the benefits of the EPA between the EU and WA countries appear small, if not negative, for WA countries

IMPROVED SUTS AND

SAMS ARE ESSENTIAL

o Sound, updated, data helps inform better policy analysis

o Transparent, consistent, documented methods should be used in constructing SUTs and SAMs

o Researchers rely on data and modeling on generate evidence-based policy analysis to inform policy-makers

o AGRODEP, with its growing network of African researchers, will be better able to deliver policy advise in Africa based on good data.

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Thank you!