The targeted public distribution system, intended to provide subsidised food to poor households, is the largest welfare programme in India, with a budget corresponding to about 1% of the net national product. Several studies have found the system to be inefficient and costly in assisting the poor. This paper analyses the case for, and against, replacing a reformed version of this system with a targeted and differentiated cash transfer scheme. Such a scheme could cover about two-thirds of households, and make far larger transfers to the poorest compared to the actual subsidy embedded in the current system, eliminating the risk of large exclusion errors. Further, the overall budget can be held at the present outlay level. It is argued that most of the objections to such a transfer scheme can be circumvented at the design stage.

Malnutrition is a serious problem in many developing countries. It is one of the main causes of child morbidity and contributes significantly to premature mortality. This chapter discusses the design and use of an alternative indicator of malnutrition – the composite index of anthropometric failure (CIAF). It argues the three most commonly used anthropometric indicators of stunting, wasting and underweight, while providing valuable information about distinct biological processes, are individually unable to provide a comprehensive picture of the overall burden of malnutrition among young children in a population. They are frequently used to predict health and mortality risk, but provide quite limited information on the relationship between malnutrition and disease. The CIAF, however, can also be used to predict morbidity risk, and in its disaggregated form provides a more useful picture of the relationship between ill health and malnutrition. It can also be used to examine the relationship between different forms of malnutrition and poverty. Using the new World Health Organization (WHO) reference population norms and recent anthropometric data on 45,377 Indian children aged under 5 years, the prevalence of stunting, wasting and underweight are calculated and compared to prevalence estimates by the CIAF. Age adjusted logistic regression is used to see how well different indicators predict morbidity risk. Analysis of variance is used to see the relationship between groups of anthropometric failure and poverty. This chapter also provides information on how reliable, nationally representative anthropometric data from household surveys can be freely accessed by researchers to pursue their own study.

The present article reviews the strengths and weaknesses of the three main methods for estimating the prevalence of malnutrition in populations: self-reported hunger, estimates based on food supplies, and anthropometrics. Although far from flawless, anthropometrics is found to be the most reliable method and also the most useful for directing policy. The main form of malnutrition among adults is overweight, not only in developed countries, but also in almost all developing countries. Only in a few developing countries is adult underweight more prevalent. By the conventional anthropometric indicators, about one-quarter of all children below the age of 5 in the developing countries are stunted or underweight, and about 10% are wasted. The total burden of malnutrition among young children, as measured by the Composite Index of Anthropometric Failure, is considerably higher, about 60% in India, the country with the largest child population in the world.

In his recent article on measuring the long-term trends in the real prices of primary commodities, Cuddington (2010) extends in several important respects our earlier efforts (Svedberg and Tilton, 2006) to correct real commodity price trends for biases in the Consumer Price Index and other deflators. First, he argues for a log-linear relationship between prices and time. Second, he proposes a simple and quick method for obtaining corrected price trends from the published but uncorrected estimates. Finally, he illustrates, for the case of copper and presumably for many other commodities as well, the difficulties of obtaining real price trends significantly different from zero when the log values of the price data contain a unit root, requiring the use of difference stationary models. We welcome these insights, which should improve and make easier efforts to estimate correctly real commodity price trends over the long run. We would stress, however, that it is still important to correct for the biases in inflation indices, notwithstanding the failure of difference stationary models to obtain long-run real price trends (both corrected and uncorrected) significantly different from zero.