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Seasonality in calorie consumption: Evidence from Mozambique

Channing Arndt, Mikkel Barslund, and Josť Sulemane1

SARPN acknowledges the African Economic Research Consortium (AERC) as the source of this document: www.aercafrica.org
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Introduction

Food security is at the core of many development policies, and seasonal fluctuations in the amount and quality of food consumption is a key component of food security. Accordingly, concerns about seasonal fluctuations in food intake go well back in time (see, for example, Miracle (1961)). Nevertheless, despite longstanding recognition of the importance of the issue, empirical evidence on seasonality of food consumption remains relatively thin, particularly in African contexts. Data demands form part of the reason for the relative paucity of studies. Analysing seasonality in calorie intake requires that the survey cover at least a full agricultural season. Further, the survey instrument needs to contain a careful recording of food consumption for each household in the sample for a sufficient period of time to provide a reasonable measure of average daily calorie intake. The concentration of interviews of households in certain periods of the year precludes analysis of seasonality in many household data sets.

This paper documents the extent of seasonality in calorie consumption at the household level in Mozambique using a recent nationwide household consumption survey covering 8,700 households in rural and urban areas. We focus on the nearly 5,000 rural households sampled since concern about seasonal fluctuations in consumption are most acute for rural households. The survey sample design explicitly considered seasonality. As such, the survey was implemented throughout a full calendar year with the first interviews beginning shortly after harvest. In addition, detailed records of household consumption were kept for a period of a week. As a result, the data set appears to be particularly well suited to consider the issue of seasonality in the context of a poor African economy.

While the data set is relatively well suited to the task of analysing seasonality, it is not perfect. For instance, due to data limitations, we do not consider intra-household allocation issues. These are clearly important as pointed out in a growing body of literature (see for example Chiappori (1988, 1992), Chiappori & Bourguignon (1992), Browning et.al. (1994)). Lacking data on intra-household allocations, the results presented here can be interpreted as a lower bound on the fluctuations the worst off individual member of a given household might face. For example, if bargaining power differs across members, some members might be able to maintain food intake despite declines in aggregate availability; however, aggregate availability limits would then dictate that remaining members must curtail consumption more than the average.

This article is structured as follows. Section 2 contains a review of literature focussing on attempts to measure seasonality in calorie consumption in sub-Saharan African contexts.2 The data set and data collection procedures are described in greater detail in section 3. Section 4 provides summary descriptive statistics. Section 5 presents the methodology employed for analysing seasonal consumption, while section 6 presents results. Section 7 concludes and advances suggestions for future research.

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Footnotes:
  1. Channing Arndt is advisor to the Ministry of Planning and Development in Mozambique and Associate Professor in the Department of Agricultural Economics at Purdue University; Mikkel Barslund is with the Development Economics Research Group (DERG), University at Copenhagen; Josť Sulemane is National Director of Studies and Policy Analysis Division within the Ministry of Planning and Development in Mozambique. The authors gratefully acknowledge support from the AERC.
  2. Examples of studies of seasonal fluctuations in household food intake in Asian countries using nationally representative data sets include Pinstrup-Andersen & Jaramillo (1989) and Behrman & Deolalikar (1989).


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