Policy impact assessment in developing countries using Social Accounting Matrices: The Kenya SAM 2014

• Author: Emanuele Ferrari,Pierre Boulanger,Hasan Dudu,Alfredo José Mainar‐Causapé
• Published date: 01 August 2020
• DOI: http://doi.org/10.1111/rode.12667
• Date: 01 August 2020

1128

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Rev Dev Econ. 2020;24:1128–1149.

wileyonlinelibrary.com/journal/rode

Received: 30 November 2018

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Revised: 19 February 2020

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Accepted: 22 March 2020

DOI: 10.1111/rode.12667

REGULAR ARTICLE

Policy impact assessment in developing countries

using Social Accounting Matrices: The Kenya SAM

2014

Alfredo JoséMainar-Causapé

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PierreBoulanger

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HasanDudu

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EmanueleFerrari

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction

in any medium, provided the original work is properly cited.

© 2020 The Authors. Review of Development Economics published by John Wiley & Sons Ltd

European Commission, Joint Research

Centre, Directorate for Sustainable

Resources, Economics of Agriculture Unit,

Seville, Spain

Correspondence

Alfredo José Mainar-Causapé, European

Commission, Joint Research Centre,

Directorate for Sustainable Resources,

Economics of Agriculture Unit, Expo, C/

Inca Garcilaso 3, 41092 Seville, Spain.

Email: amainar@us.es

Funding information

Directorate-General for International

Cooperation and Development; Joint

Research Centre

Abstract

This paper describes the structure and estimation of a Social

Accounting Matrix (SAM) of Kenya for the year 2014.

Among its specificities, this SAM includes a very high

disaggregation of the agri-food sector and accounts for the

double role of households as producers and consumers.

Accounting for these characteristics is crucial to provide

robust socioeconomic analysis in the context of developing

countries. Indeed, this type of database is valuable to per-

form ex-ante evaluations of economic policies with various

economic models and techniques. In this paper, we present

an application with a linear multiplier analysis (backward

linkages and value chain decomposition). The results show

the capacity of the primary sector in Kenya to generate

value added and employment, with this growth distributed

more intensely in rural households whose main livelihood is

semi-subsistence agriculture.

KEYWORDS

home production for home consumption, Kenyan economy, linear

multisectoral models, Social Accounting Matrices

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INTRODUCTION

Agriculture is the principal sector of the Kenyan economy, contributing approximately 33% of the

GDP in 2016 (Kenya National Bureau of Statistics, 2017) and employing around 80% of the national

workforce. About 75% of Kenya's population lives in rural areas (World Bank, 2018) and derives its

livelihood directly or indirectly from agriculture. As a majority of vulnerable groups, such as subsis-

tence farmers (agricultural, livestock, or mixed), depend on agriculture as their main source of liveli-

hood, the development of the agricultural sector is fundamental to any growth and poverty-reduction

strategy.

In African countries (Kenya among them), peasants are producers and factor suppliers of econo-

mies, and therefore a large portion of the workforce (sometimes all of it) is dedicated to the production

of self-consumed commodities. This results in substantial home production for home consumption

(HPHC) that should be accounted for in any economic analysis. These economies include two types

of "productive agents": households as producers of commodities partly for own consumption and

partly for sale on the market and households that produce exclusively market-oriented commodities

(Aragie, 2014). In addition, Kenya comprises households that produce cash crops (e.g., coffee and tea)

exclusively for the market. As a result, a Social Accounting Matrix (SAM) for Kenya should include

all three types of productive agricultural agents.

In Kenya, the self-consumption of commodities covers a significant proportion of food con-

sumed, especially in rural areas and by households with lower chances of finding off-farm jobs.

HPHC and the double role of households as producers and consumers must be properly considered.

Failure to consider these characteristics and the difference in price formation between self-con-

sumed commodities and marketed products lead to incorrect interpretations of the results of eco-

nomic models aimed at assessing policy impacts, particularly in rural areas (Taylor & Adelman,

2003; Tiberti, 2011).

In June 2008, the Kenyan government launched Kenya Vision 2030 (Government of Kenya,

2008) as the new long-term strategic document for Kenya’s economic and social development, iden-

tifying agriculture as one of the key sectors to deliver a 10% annual economic growth rate. In this

framework, several agricultural policies have been formulated to increase agricultural productivity

and income.1

The development of these policies requires an exhaustive knowledge of the inter-sec-

toral links and transmission mechanisms of the possible shocks generated by economic policies

on output, value added, and employment. This information must also be structured to reflect the

specificities of the country. Thus, a database that enables this multisectoral analysis, based on an ex-

haustive description of the economic flows and allowing the application of informative models and

tools, becomes a very relevant tool. This paper presents a 2014 Social Accounting Matrix (SAM) for

Kenya, with a novel specific structure that includes HPHC with a high disaggregation of the agri-

cultural sector and a regional disaggregation of agricultural sectors based on agro-ecological zones

(AEZs). The SAM provides a detailed description of the Kenyan economic structure and serves as

a database for linear multisectoral models and analysis tools. The estimation of linear multipliers

and value chain analyses for output, value added, and employment for the disaggregated primary

sector, distinguishing households as producers (for own consumption and market-oriented) from

normal activities, provides significant information, defining the basic outline of potential results of

the proposed policies.2

The rest of the paper is structured as follows. Section 2 introduces the concept of SAMs and de-

velops the HPHC issue. Section 3 illustrates the estimation process of the Kenya SAM, and Section 4

shows the multiplier and value chain analyses. Section 5 concludes.