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Ghana Social Science Journal, Volume 8, Numbers 1&2, 2011 GHANA SOCIAL SCIENCE JOURNAL Volume 8, Numbers 1&2, 2011 Faculty of Social Science University of Ghana, Legon, Accra INTE S GRI PROCEDAMU Ghana Social Science Journal, Volume 8, Numbers 1 & 2, 2011 Editors Dzodzi Tsikata Clara Fayorsey Editorial Committee Samuel Agyei-Mensah - Chairman Abena D. Oduro - Member Samuel Nii Ardey Codjoe - Member Dzodzi Tsikata - Member Clara Fayorsey - Member International Advisory Board Joseph Ayee, University of Kwa-Zulu Natal, South Africa Emmanuel Akyeampong, Harvard University, USA Jean Allman, Washington University in St. Louis, USA. Timothy Insoll, University of Manchester, UK Michael Lofchie, University of California, Los Angeles, USA Maureen Mackintosh, The Open University, UK Amina Mama, University of California, Davis, USA Adebayo Olukoshi, UN African Institute for Economic Development and Planning (IDEP), Senegal. Barry Riddell, Queens University, Canada. Mohammed Salih, Erasmus University of Rotterdam, Netherlands. Rotimi Suberu, Bennington College, USA © Faculty of Social Sciences, University of Ghana, Legon, Ghana, 2011 ISSN: 0855-4730 All rights reserved; no part of this journal may be reproduced, stored in a retrieval system, or transmitted in any means, electronic, mechanical, photo-copying, recording or otherwise, without the prior permission o f the publishers. Any person who does any unauthorized act in relation to this journal will be liable to criminal prosecution and claims for damages. Published by the Faculty of Social Sciences, University of Ghana P.O. Box 72, Legon, Ghana Tel. No. (233-21) 500179 E-mail: [email protected] Printed by Yamens Press Limited P.O. Box AN 6045 Tel No. (233-302) 223222/235036 E-mail: [email protected] CONTENTS Volume 8 Numbers 1 & 2 2011 Tariff Reforms, Food Prices, and Consumer Welfare in Ghana during the 1990s Charles Ackah 1-21 An Assessment of Feedback Effects in the Inflation-Economic Growth Nexus: Evidence from Nigeria S.I. Oladeji and A.A. Adegboye 22-39 Strengthening Lifelong Education for Development in Ghana D. Oduro-Mensah 40-49 Maternal and Newborn Health in Ghana, 2006 E.O. Tawiah 50-73 Ghanaian Females' Decision-making Autonomy and their Weight Status Naa Dodua Dodoo 74-91 Estimating Gender Earnings Gap in the Informal Sector Kayayei Labour Market: Micro-Level Empirical Evidence from Kumasi, Ghana Isaac Addai 92-105 'Me Sumsum Ni Ha'-The Dislocation and Non-Belonging of Child Domestic Workers in Accra Peace Mamle Tetteh 106-127 The Coping Strategies of Single Female Parents in Accra Albert Kpoor 128-149 Information Management: The Nemesis of Ghanaian Governments Margaret Ivy Amoakohene 150-173 The Brakwa Earthworks – Preliminary Report of Fieldwork Fritz Biveridge 173-190 Ghana Social Science Journal, Volume 8, Numbers 1&2, 2011, pp. 1-21 TARIFF REFORMS, FOOD PRICES, AND CONSUMER WELFARE IN GHANA DURING THE 1990S 1 CHARLES ACKAH ABSTRACT In this paper, we analyse the effect of food price changes on household consumption in Ghana during the 1990s and assess the extent to which changes can be explained by trade and agricultural policy reforms. The measurement of the total household welfare effect, one that jointly considers first order effects as well as consumption responses, is the object of this study. Food consumption behaviour in Ghana is analyzed by estimating a complete food demand system using the linear approximate version of the AIDS model with household survey data for 1991/92 and 1998/99. The estimated price elasticities are then utilized to evaluate the distributional impacts of the relative food price changes in terms of compensating variation. The results indicate that the distributional burden of higher food prices fell mainly on the urban poor. Keywords: Food prices, demand analysis, consumer welfare, Ghana INTRODUCTION ypically, there are a number of factors that determine the extent to which households Tare impacted by food price shocks including the magnitude of the relative price changes, the relative importance of different food commodities in the consumption basket of different households as well as the degree to which households are compensated for the price shocks by changes in income. This paper aims to fill some of the gaps in the literature by analyzing the food consumption behaviour of Ghanaian households using the Almost Ideal Demand System (AIDS) model developed by Deaton and Muellbauer (1980b) to obtain price and income elasticity estimates for six major food categories, which together comprise the basic subsistence staples for most poor households. The estimated price elasticities are then utilized to evaluate the welfare implications of the relative food price changes in terms of compensating variation. 1 Senior Research Fellow, Institute of Statistical, Social and Economic Research, University of Ghana. E-mail: [email protected] 2 Ghana Social Science Journal, Volume 8, Numbers 1&2, 2011, pp. 1-21 We then assess the extent to which welfare changes can be explained by agricultural trade policy reforms using counterfactual simulation analysis. The paper concentrates on the partial equilibrium welfare effects of food price changes, given the food consumption choices of households in Ghana. In essence, we focus on changes in consumer welfare resulting from the variations in food price changes, assuming income effects away. Whilst it would be appropriate to estimate the overall welfare changes (i.e. including producer welfare or allowing for income responses), we do not pursue this line of enquiry in this paper due to data limitations including adequate producer price data. Our analysis therefore does not account for supply responses through production and labour adjustments and the results must be interpreted with these caveats in mind. However, the data constraints notwithstanding, our simple partial equilibrium analysis provides useful insights into household food consumption behaviour and the distributional implications of the variation in food price changes for household welfare in Ghana during the 1990s – a decade of remarkable food price inflation reminiscent of the economic crisis that precipitated the Structural Adjustment Programmes (SAPs) in the early 1980s. The remainder of this paper is organized as follows: Section 2 provides a review of the literature on demand system analysis and household welfare. Section 3 presents the econometric model and describes the methodology used to measure welfare changes facing Ghanaian households during the 1990s. Section 4 discusses the dataset and sources and Section 5 reports the elasticity estimates and the welfare analysis due to the price changes in the 1990s. This section also assesses the impact of simulated trade policy reform. Section 6 concludes the paper with some policy implications of the findings. LITERATURE REVIEW Methodologically, most empirical papers estimating demand functions have used time series data, which were, until recently, only readily available in developed countries. As consumption data sets are not usually available in African countries, the estimation of demand elasticities is rare (Kedir, 2005). In the absence of appropriate time-series data, most studies adopt a methodology developed by Deaton (1987, 1988 and 1990) and Deaton and Grimard (1992), which introduces a technique based on the variation of prices across space to identify behavioural responses. However, despite being important, price data are relatively scarce for many developing countries (Gibson and Rozelle, 2002). In the absence of reliable market price data, many researchers have had to rely on imperfect proxy measures such as unit values (defined as the ratio of household expenditure on a particular good to the quantity consumed). The simplest unit rank demand system that could be considered is the linear demand system proposed by Stone (1954). One model that has proven flexible and adaptable to cross-sectional data without counterintuitive assumptions is the 3 Tariff Reforms, Food Prices, and Consumer Welfare in Ghana During the 1990s Almost Ideal Demand System (AIDS) introduced by Deaton and Muellbauer (1980b). This model proposed by Deaton and Muellbauer is of a flexible functional form which derives the budget share equation starting from the specification of a cost function belonging to the PIGLOG family.2 In a number of studies, Deaton (1988, 1990 and 1997) proposes a unique methodology to estimate demand elasticities using only a single cross- section of household budget survey data. His approach is based on the notion that prices for comparable goods can vary greatly across space in developing countries due to the fact that survey data is often collected in clusters of households in the same village. Deaton's two-stage estimation procedure first purges the unit value data of quality effects and then uses the cross-spatial variation in the 'corrected' unit values to identify own-price or cross- price elasticities. The main advantage of using unit values in demand analysis derives from the substantial cross-sectional variability, but it may give biased results (Deaton, 1990, 1997). Many commentators have argued that unit values, unlike market prices, are error-ridden and subject to sample selection problems as they are unavailable for non- purchasing households. The problem with unit value is that it is a function of expenditure and quantity, both of which are potentially measured with error in most household surveys (see Gibson and Rozelle, 2002); Kedir (2001, 2005); and Niimi (2005)). The most standard application of Deaton's approach follows the estimation of budget share and unit value equations such that for each household h in cluster c, the M-i good system of equations is given as: M whc =a1 +b1 ln xhc +d1zhc +ågj ln p jc +fc +u1hc (1) j =1 M ln vhc =a2 +b2 ln xhc +d2zhc +åqj ln p jc +u2hc (2) j =1 where w hc is the budget share devoted to the good in question (good i), xhc is total household expenditure, vhc is unit value, zhc is a vector of household characteristics, p jc is the (unobserved cluster) price, f c is the cluster fixed- effect, and the error terms of the two equations are u1hc and u2hc respectively.
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