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An in-depth quantitative analysis is undertaken in this paper to assist the Southern African Development Community (SADC) Secretariat, member countries, and development partners in setting future regional investment priorities for agricultural research and development in the SADC region. A primary goal of this work was to identify a range of agricultural research priorities for achieving sector productivity and overall economic growth in southern Africa, at both the country and regional levels. This is accomplished by adopting an integrated modeling framework that combines a disaggregated spatial analytical model with an economywide multimarket model developed specifically for the region.
Agricultural Productivity in Africa: Trends, Patterns, and Determinants presents updated and new analyses of land, labor, and total productivity trends in African agriculture. It brings together analyses of a unique mix of data sources and evaluations of public policies and development projects to recommend ways to increase agricultural productivity in Africa. This book is timely in light of the recent and ongoing growth recovery across the continent. The good news is that agricultural productivity in Africa increased at a moderate rate between 1961 and 2012, although there are variations in the rate of growth in land, labor, and total factor productivities depending on country and region. Differences in input use and capital intensities in agricultural production in the various farming systems and agricultural productivity zones also affect advancements in technology. One conclusion based on the book’s research findings derives from the substantial spatial variation in agricultural productivity. For areas with similar agricultural productivity growth trends and factors, what works well in one area can be used as the basis for formulating best-fit, location-specific agricultural policies, investments, and interventions in similar areas. This finding along with others will be of particular interest to policy- and decisionmakers.
Despite the importance of location-specific adaptive crop breeding research, past reforms of breeding systems in Nigeria have focused more on centralizing the breeding activities into fewer locations. This has been based partly on the premise that such research systems can still effectively meet the need for a diverse set of varietal technologies that are suitable for different agroecological conditions through the use of numerous outstations and multilocational trials, regardless of the locations of the headquarters or the outstations where breeders are located. However, little empirical evidence exists to support this premise. Using panel data for agricultural households in northern Nigeria, as well as spatial data on agroecological factors, this study fills this knowledge gap. Specifically, it empirically shows that agricultural productivity and technical efficiency at farm household level is significantly and positively affected by similarity between the agroecological conditions of the locations of these households and where major crop breeding institutes are headquartered in Nigeria, namely Maiduguri, Kano, Zaria, Badeggi, Ibadan, and Umudike, after controlling for the agroecological conditions and various relevant household characteristics of these households. These findings suggest that where improved varieties are developed or evaluated affects agricultural productivity and technical efficiency in different locations. Overall agricultural productivity in Nigeria can be significantly increased not simply by increasing support for public sector varietal development, but by doing so in a manner that increases the similarity in agroecological conditions between areas where crop breeding is conducted and the areas where farm households produce those crops.
This paper studies the effect of local off-farm employment and migration on rural households’ technical efficiency of crop production using a five-year panel dataset from more than 2,000 households in five Chinese provinces. While there is not much debate about the positive contribution of migration and local off-farm employment to China’s economy, there is an increasing concern about the potential negative effects of moving labor away from agriculture on China’s future food security. This is a critical issue as maintaining self-sufficiency in grain production will be critical for China to feed its huge population in the future. Several papers have studied the impact of migration on production and yield with mixed results. But the impact of migration on technical efficiency is rarely studied. Methodologically, we incorporate the correlated random-effects approach into the standard stochastic production frontier model to control for unobservable that are correlated with migration and off-farm employment decisions and technical efficiency. The most consistent result that emerged from our econometric analysis is that neither migration nor local off-farm employment has a negative effect on the technical efficiency of grain production, which does not support the widespread notion that vast-scale labor migration could negatively affect China’s future food security.
This paper addresses the challenge of increasing the rate of varietal turnover to prevent depreciation of improved cultivars over time. It examines the supply of and demand for improved cultivars of wheat in India to illustrate this challenge in a unique manner, combining national-level data on breeder seed production with primary data on cultivar adoption. The analyses show that the rate of varietal turnover for wheat has slowed in India from an average of 9-10 years a decade ago to 13-14 years in 2010. By focusing on a sample of farmers and villages in Haryana, where seed and information networks are relatively well developed, the study finds that wheat farmers still prefer cultivars that were released 9-10 years ago.
Since the publication of the World Development Report 2008, two related strands of research have emerged-one on the validity of smallholder-led development strategy and the other on agricultural intensification under population pressure. The former casts doubt about the role of agriculture in economic development in smallholders dominated countries and the later provides evidence that are contrary to earlier findings on induced innovation theory. Using a unique panel dataset, we examine whether these arguments are valid for Bangladesh--a densely populated country that has experienced significant growth in recent decades. The results suggest that (1) agriculture as a source of income declined significantly over the past two decades; (2) the operated farm size stopped declining in the late 1980s; and (3) that population density relates positively with a host of agricultural intensifications indicators with no evidence of threshold.
This study was undertaken to assess farmers’ preferences and willingness to pay (WTP) for various climate-smart interventions in the Indo-Gangetic Plain. The research outputs will be helpful in integrating farmers’ choices with government programs in the selected regions. The Indo-Gangetic Plain (IGP) was selected because it is highly vulnerable to climate change, which may adversely affect the sustainability of the rice-wheat production system and the food security of the region. Climate-smart agriculture (CSA) can mitigate the negative impacts of climate change and improve the efficiency of the rice-wheat-based production system. CSA requires a complete package of practices to achieve the desired objectives, but adoption is largely dependent on farmers’ preferences and their capacity and WTP. To assess farmers’ choices and their WTP for the potential climate-smart technologies and other interventions, we used scoring and bidding protocols implemented through focus group meetings in two distinct regions of Eastern and Western IGP. We find that laser land leveling (LLL), crop insurance, and weather advisory services were the preferred interventions in Eastern IGP. Farmers preferred LLL, direct seeding, zero tillage, irrigation scheduling, and crop insurance in Western IGP. Through the bidding approach, farmers implicitly express their WTP for new technologies that could transform current agricultural practices into relatively low-carbon and more productive farming methods. But actual large-scale adoption of the preferred climate-smart technologies and other interventions would require access to funding as well as capacity building among technology promoters and users.
Use of mechanization in African agriculture has returned strongly to the development agenda, particularly following the recent high food prices crisis. Many developing country governments—including Ghana, the case study of this paper—have resumed support for agricultural mechanization, typically in the form of providing subsidies for tractor purchase and establishment of private-sector-run agricultural mechanization service centers (AMSECs). The aim of this paper is to assess the impact of Ghana’s AMSEC program on various outcomes, using data from household surveys that were conducted with 270 farmers, some of them located in areas with the AMSEC program (treatment) and others located in areas without the program (control).
This study aims to explore and quantify systematic similarities and differences between four major global cropping systems products: the dataset of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000), the spatial production allocation model (SPAM), the global agroecological zone (GAEZ) dataset, and the M3 dataset developed by Monfreda, Ramankutty, and Foley. The analysis explores not only the final cropping systems maps but also the interdependencies of each product, methodological differences, and modeling assumptions, which will provide users with information vital for discerning between datasets in selecting a product appropriate for each intended application.