Natural Resource Endowments, Subsistence Agriculture, and Poverty in the Chhotanagpur Plateau

The Chhotanagpur Plateau in Eastern India lies on the so-called Tribal belt and is one of the poorest regions of India. Beginning in 1998, the Indian Statistical Institute in Kolkata and the International Rice Research Institute began research to examine the biophysical and socioeconomic factors constraining agricultural activity and household income in the region. This report provides an initial descriptive and quantitative analysis of the integrated biophysical and socioeconomic database constructed from this research. The report begins with brief overview of the geography and history of the study area, followed by descriptions of the main biophysical characteristics of the study area, such as climate, topography, soil, water availability, and the typology of land types in the area. The main cropping systems associated with each land type are identified. This research highlighted the importance of low scale variations in topography in explaining cropping systems. Part Two of the report reviews socioeconomic characteristics of the villages and of surveyed households. Key characteristics noted include the high incidence of poverty, the diversity of economic activities, and the small share of imputed household income derived from rice cultivation. The report concludes with a brief discussion of policy implications and avenues for future research in the study.Natural Resource Management; Rural Poverty; Rice Production; Subsistence Farming; Eastern India

Economic Growth in the Philippines: A Spatial Econometrics Analysis at the Provincial Level, 1991 – 2000.

Investigating the determinants of economic growth remains a long research tradition in the economic growth literature. Most studies in this literature have tried to link economic growth and different economic factors using either neoclassical growth theories or endogenous growth approaches. These studies apply these growth theories to identify the factors responsible for the observed differences/disparities between regions or countries. While early studies focused on cross-country analyses, the recent most studies consider regions or sub-national entities as unit of analysis. This has raised the question of whether theories developed for cross-country analysis could be automatically applied for regional or sub-national analysis. Given the profound difference between nations and regions in terms of degree of openness, theories developed in cross-country analysis may not be automatically applied in regional analysis (see Mangrini, 2004). However, properly accounting for the spatial interaction effects may provide a way to use these theories in regional analysis. Regional analysis of economic growth has therefore spurned the development of specialized quantitative methods designed to account for the spatial dimensions of higher resolution, spatially referenced data. The goal of this research is to investigate the process of regional economic growth in the Philippines focusing on provincial data. Previous studies on regional growth within the Philippines have analyzed the regional growth process following neoclassical growth models or endogenous growth models without explicitly modeling spatial dependence between regions and the role of spillover effects. Traditional growth regressions with ordinary least squares may yield biased or inconsistent estimates if spatial autocorrelation is present but have been accounted for. This paper uses spatial econometrics techniques to estimate three theoretical growth models: the unconditional growth model, the Solow model and the Mankiw Romer and Weil model. Investment and human capital were found to be the main drivers of economic growth.Community/Rural/Urban Development, Research and Development/Tech Change/Emerging Technologies, Research Methods/ Statistical Methods,

Natural Resource Endowments, Subsistence Agriculture, and Poverty in the Chhotanagpur Plateau

The Chhotanagpur Plateau in Eastern India lies on the so-called Tribal belt and is one of the poorest regions of India. Beginning in 1998, the Indian Statistical Institute in Kolkata and the International Rice Research Institute began research to examine the biophysical and socioeconomic factors constraining agricultural activity and household income in the region. This report provides an initial descriptive and quantitative analysis of the integrated biophysical and socioeconomic database constructed from this research. The report begins with brief overview of the geography and history of the study area, followed by descriptions of the main biophysical characteristics of the study area, such as climate, topography, soil, water availability, and the typology of land types in the area. The main cropping systems associated with each land type are identified. This research highlighted the importance of low scale variations in topography in explaining cropping systems. Part Two of the report reviews socioeconomic characteristics of the villages and of surveyed households. Key characteristics noted include the high incidence of poverty, the diversity of economic activities, and the small share of imputed household income derived from rice cultivation. The report concludes with a brief discussion of policy implications and avenues for future research in the study

Natural Resource Endowments, Subsistence Agriculture, and Poverty in the Chhotanagpur Plateau

The Chhotanagpur Plateau in Eastern India lies on the so-called Tribal belt and is one of the poorest regions of India. Beginning in 1998, the Indian Statistical Institute in Kolkata and the International Rice Research Institute began research to examine the biophysical and socioeconomic factors constraining agricultural activity and household income in the region. This report provides an initial descriptive and quantitative analysis of the integrated biophysical and socioeconomic database constructed from this research. The report begins with brief overview of the geography and history of the study area, followed by descriptions of the main biophysical characteristics of the study area, such as climate, topography, soil, water availability, and the typology of land types in the area. The main cropping systems associated with each land type are identified. This research highlighted the importance of low scale variations in topography in explaining cropping systems. Part Two of the report reviews socioeconomic characteristics of the villages and of surveyed households. Key characteristics noted include the high incidence of poverty, the diversity of economic activities, and the small share of imputed household income derived from rice cultivation. The report concludes with a brief discussion of policy implications and avenues for future research in the study

Global Rice Atlas: Disaggregated seasonal crop calendar and production

Purpose: Rice is an important staple crop cultivated in more than 163 million ha globally. Although information on the distribution of global rice production is available by country and, at times, at subnational level, information on its distribution within a year is often lacking in different rice growing regions. Knowing when and where rice is planted and harvested and the associated production is crucial to policy and decision making on food security. To examine seasonal and geographic variations in food supply, we developed a detailed rice crop calendar and linked it with disaggregated production data. Approach and methods used: We compiled from various sources detailed data on rice production, and planting and harvesting dates by growing season. To standardize the production data to the same period, we adjusted the production values so that the totals for each country will be the same as those of FAO for 2010-2012. We then linked data on rice production with the corresponding crop calendar information to estimate production at harvest time by month then we calculated totals for each country and region. Key results: The bulk of global annual harvests of rice is from September to November, corresponding with the harvest of the wet season rice in Asia and Africa. Total rough rice production during those peak months exceed 381 million tons, which account for about half of annual global rice output. Production is lowest in January with only 11 million tons in total. Regional production is lowest in Asia in January, Americas in December, Africa in July and rest of the world in May. Synthesis and Applications: A globally complete and spatially detailed rice crop calendar is important to crop growth simulation modelling and assessment of vulnerability of rice areas to biotic and abiotic stresses. Linked to production estimates, it can be used in analyzing spatial and seasonal production trends to better assess and predict price fluctuations , and to mitigate potential significant shortfalls in food production at certain times of the year

Mapping the suitability of selected crops in the Ganges Delta

Assessing the suitability of different crops in specific geographic locations is crucial for optimizing crop productivity, promoting climate resilience, and guiding land use decisions. This study assessed the biophysical suitability of rice, watermelon and maize in the Ganges Delta, one of the most densely populated deltas in the world and also extremely vulnerable to climate change. This delta is expected to increasingly experience more frequent and intense extreme weather events, sea level rise and food insecurity. The suitability maps could be used in targeting alternative cropping systems, adjusting crop calendar and recommending crop management practices to increase productivity and improve the resilience of the Ganges Delta

Mapping the suitability of rice and other crops in the Mekong Mega Delta

The Mekong Delta is an important food production zone supplying rice for domestic and export markets. It is, however, highly vulnerable to the impacts of climate change. More frequent and more intense floods, salinization, water shortages and climate extremes are expected to affect the livelihood of farmers in the region. As part of the CGIAR’s Asian Mega-Deltas Research Initiative, we are exploring promising options with farmers to accelerate the adoption of diversified production systems that are better adapted to the effects of climate change. Suitability maps developed for each crop can be used to assess where and when crops would be most suitable for production and to identify and target adaptation recommendations for sustainable, resilient and productive agri-food systems in the Delta

Economic Growth in the Philippines: A Spatial Econometrics Analysis at the Provincial Level, 1991 – 2000.

Investigating the determinants of economic growth remains a long research tradition in the economic growth literature. Most studies in this literature have tried to link economic growth and different economic factors using either neoclassical growth theories or endogenous growth approaches. These studies apply these growth theories to identify the factors responsible for the observed differences/disparities between regions or countries. While early studies focused on cross-country analyses, the recent most studies consider regions or sub-national entities as unit of analysis. This has raised the question of whether theories developed for cross-country analysis could be automatically applied for regional or sub-national analysis. Given the profound difference between nations and regions in terms of degree of openness, theories developed in cross-country analysis may not be automatically applied in regional analysis (see Mangrini, 2004). However, properly accounting for the spatial interaction effects may provide a way to use these theories in regional analysis. Regional analysis of economic growth has therefore spurned the development of specialized quantitative methods designed to account for the spatial dimensions of higher resolution, spatially referenced data. The goal of this research is to investigate the process of regional economic growth in the Philippines focusing on provincial data. Previous studies on regional growth within the Philippines have analyzed the regional growth process following neoclassical growth models or endogenous growth models without explicitly modeling spatial dependence between regions and the role of spillover effects. Traditional growth regressions with ordinary least squares may yield biased or inconsistent estimates if spatial autocorrelation is present but have been accounted for. This paper uses spatial econometrics techniques to estimate three theoretical growth models: the unconditional growth model, the Solow model and the Mankiw Romer and Weil model. Investment and human capital were found to be the main drivers of economic growth