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This paper discusses the application of the equilibrium displacement model (EDM) to estimate ex-ante the welfare effects of biological productivity growth for semi-subsistence crop and its impact on poverty reduction. The conventionally used EDM is compared with an alternative EDM that reflects more realistic assumptions for African semi-subsistence crops, such as the shape and shift of supply curve, significant margins due to high transportation costs between farmgate and consumption market, as well as between different consumption markets, and the degree of precisions of estimated structural parameters. The application to the dataset for Benin cassava farmers provides an example that the conventional EDM may significantly overestimate the total welfare gains, and may also lead to very different interpretation of how pro-poor the technology is.
This study demonstrates a method of providing ex-ante estimates of the distributional welfare effects of yield-increasing technology. We apply this approach to estimate the impact of a 10% increase in cassava yields in Nigeria. Using data from the 2012-13 Nigeria General Household Survey, we simulate the effect of the technology on each household in the sample (micro-simulation), taking into account both the yield increase and the resulting price reduction. The results suggest that the higher cassava yield would increase average household income by 0.2 percent, generate aggregate benefits of US$ 219 million per year, and reduce poverty by 0.2 percentage points, lifting 385 thousand people from poverty. Cassava growers who have net sales (11 percent of Nigerian households) would experience a reduction in income and an uptick in poverty due to the lower price. However, net-buying growers (10 percent) and consumers (47 percent) would benefit both in terms of income and poverty reduction. Smaller farms gain since many are net buyers who benefit from the lower price. Larger farms lose because many of them are net sellers who are adversely affected by the lower price. As most of the benefits of technology change are transferred to consumers (including many rural consumers), the cassava consumption patterns are at least as important as grower characteristics in determining the distributional impact of the technology. Applying this approach to all major crops in a country would help policy makers prioritize agricultural research across commodities to increase the poverty-reducing impact.
Some agricultural investments are commodity-specific, meaning that they increase the productivity of production, processing, or marketing of a single agricultural commodity or a set of closely-related commodities. Examples include investment in cassava breeding, expanding cotton ginning capacity, irrigation for rice production, expansion of cold storage capacity for horticultural exports, or road investment to a region whose main product is maize. Traditional cost-benefit analysis estimates the effect of in-vestments on net income assuming that the investment is not large enough to influence market prices. However, a different approach is needed when the investment affects market prices and/or there is an interest in other outcomes such as poverty reduction. This report describes an approach to estimating the impact of commodity-specific agricultural investments on income, poverty, and other measures of welfare. This approach can be extended to identify the optimal allocation of an investment budget across commodities subject to a given objective function. For example, it could be used to allocate agricultural research funds across commodities to maximize income, poverty reduction, or a weighted average of the two.
From 2006 to mid-2008 the international prices of agricultural commodities increased considerably, by a factor larger than two. This upward trend in agricultural prices captured the world's attention as a new food crisis was emerging. Several explanations for these movements in prices, ranging from demand-driven forces to supply shocks, have been provided by analysts, researchers, and development institutions. This paper is an attempt to empirically validate these explanations using time series econometrics and data at monthly frequency. We focus on the international price of corn, wheat, rice, and soybeans. First, we identify variables associated with the factors mentioned as causing the increase in these agricultural commodities prices. Second, we use time series analysis to try to quantitatively validate those explanations. The empirical work presented here includes first difference models and rolling Granger causality tests. Overall, our empirical analysis mainly provides evidence that financial activity in futures markets and proxies for speculation can help explain the observed change in food prices; any other explanation is not well supported by our time series analysis.
The substantial differences in agricultural productivity between Asia and Africa can be largely explained by differences in use of modern inputs. The evidence suggests that better access to infrastructure (such as roads and irrigation) and agricultural services has given Asian farmers significantly better access to modern inputs, while Sub-Saharan African farmers without such an access are not able to fully exploit the benefits of modern agricultural inputs. This brief discusses the relationship between agricultural service provision and modern input use by farmers in Nigeria, with a focus on the differences among states and local government areas (LGA).
This book documents frontier knowledge on the drivers of agriculture productivity to derive pragmatic policy advice for governments and development partners on reducing poverty and boosting shared prosperity. The analysis describes global trends and long-term sources of total factor productivity growth, along with broad trends in partial factor productivity for land and labor, revisiting the question of scale economies in farming. Technology is central to growth in agricultural productivity, yet across many parts of the developing world, readily available technology is never taken up. We investigate demand-side constraints of the technology equation to analyze factors that might influence producers, particularly poor producers, to adopt modern technology. Agriculture and food systems are rapidly transforming, characterized by shifting food preferences, the rise and growing sophistication of value chains, the increasing globalization of agriculture, and the expanding role of the public and private sectors in bringing about efficient and more rapid productivity growth. In light of this transformation, the analysis focuses on the supply side of the technology equation, exploring how the enabling environment and regulations related to trade and intellectual property rights stimulate Research and Development to raise productivity. The book also discusses emerging developments in modern value chains that contribute to rising productivity. This book is the fourth volume of the World Bank Productivity Project, which seeks to bring frontier thinking on the measurement and determinants of productivity to global policy makers.
A joint FAO and World Bank study which shows how the farming systems approach can be used to identify priorities for the reduction of hunger and poverty in the main farming systems of the six major developing regions of the world.