Rural Poverty, Risk and Development
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Rural Poverty, Risk and Development

Marcel Fafchamps

This book investigates the relationships between rural poverty, risk, and development. Building upon the author’s work in the area, it summarises the contributions of recent theoretical and empirical work to our understanding of how risk affects rural poverty levels in developing countries. In particular the book examines what we do and do not know about risk coping strategies among today’s poor rural societies. Ways in which these strategies may be re-examined and improved by governments and international organisations are proposed.
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Chapter 2: Risk and Poverty

Marcel Fafchamps


LIFE AND RISK Life is subject to all kinds of fluctuations. Some of these fluctuations are predictable: the absence of rain in the dry season, the utter helplessness of the newborn, the declining strength of the old. Others occur in a haphazard fashion that cannot be predicted, at least not precisely. These fluctuations constitute the rhythm of life. They must be dealt with, in one way or another, otherwise life can become highly unpleasant. Taking care of these fluctuations constitutes risk coping strategies. The main concern is with the strategies people use to minimize the impact of these fluctuations on their welfare. Thus, the definition of risk factors encompasses both predictable and unpredictable variations in income and health. In a recent review of informal insurance mechanisms, Morduch (1999) proposes three conceptual distinctions that are useful to characterize risk factors in general: high and low frequency risks; autocorrelated and non-autocorrelated risks; and covariate and idiosyncratic risks (see also Morduch (1995) and Fafchamps (2003a)). High and low frequency risk: Risk is, by definition, a process that unfolds over time. Certain risk factors such as minor illnesses occur frequently; others such as locust attacks are fortunately quite rare. As a first approximation, individual risk factors can be thought of as being realizations of a Poisson process in which the number of occurrences Zj(t) of a particular shock j over a time interval t follow: Pr[Zj(t)ϭz]ϭ e␯jt␯ztz j z! (2.1) where parameter ␯j denotes the mean...

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