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Additional file 1. Additional figures and tables.

Additional file 1: Table S1. Demographics of patients with and without lung nodules stratified by the AI and expert as well as expert CAC scores. Table S2. Comparison of risk factors and clinical attributes between patients with expert determined nodules, comparison of risk factors and clinical attributes between patients with AI determined nodules, and comparison of risk factors and clinical attributes between patients with CAC > 0 and CAC = 0. Table S3. Demographics and risk factors associated with pulmonary outcomes. Table S4. Demographics and risk factors associated with cardiac outcomes. Table S5. Simple logistic regression for parallel analysis of AI-volume and expert-volume for prediction of cardiac outcomes. Table S6. AUC and McFadden R2 for outcomes with and without AI components included in the model. Table S7. Summary statistics of Patients with False Positive Nodules. Figure S1. ROC curves for comparison of CAC AI-Volume and Expert-Volume for prediction of MACE. Expert and AI-Volume both excellently predict MACE. Figure S2. ROC Curves for comparison of CAC AI-Volume and Expert Volume for prediction of ACS/MI hospitalization in our study timeframe. Figure S3. ROC Curves for comparison of CAC AI-Volume and Expert Volume for prediction of percutaneous coronary intervention (coronary catheterization or stent placement) or coronary artery bypass graft operation. Figure S4. Root cause analysis of false-positive nodules. A. Logistic regression of having one false positive nodule as predicted by age. B. Logistic regression probability curve of false positive nodules as a function of age. C. True anatomic identities and relative frequencies of false positive nodule etiologies.

We present an easily calibrated spatial modeling framework for estimating location-specific fertilizer responses, using smallholder maize farming in Tanzania as a case study. By incorporating spatially varying input and output prices, we predict the expected profitability for a location-specific smallholder farmer. A stochastic rainfall component of the model allows us to quantify the uncertainty around expected economic returns. The resulting mapped estimates of expected profitability and uncertainty are good predictors of actual smallholder fertilizer usage in nationally representative household survey data. The integration of agronomic and economic information in our framework makes it a powerful tool for spatially explicit targeting of agricultural technologies and complementary investments, as well as estimating returns to investments at multiple scales.

Rural land titling has stronger impacts on farm investments for female title-holders than for male title-holders. This effect is particularly pronounced for investments which are less capital-intensive. The gendered impacts of smallholder ownership of land titles may have to do with systematic differences in tenure security under traditional systems. Policies and programmes aimed at encouraging female access to land titles can improve the economic impact of agricultural land titling through increases in productivity and land productivity enhancing investments.

This essay investigates the relationship between rural household income growth and access to electricity, extension services and roads. Following Dercon et al (2009), I outline a household income growth model that includes access to these public goods as growth conditioners. I estimate the model using panel data on Kenyan smallholders covering the period 2000-2010. I find that the expansion of electricity, feeder roads and agricultural extension services are all important conditioners. Access to agricultural extension services has a particularly strong impact on growth. As an extension of the growth model, I investigate whether spatial spillovers in public goods exist and to what extent these spillovers contribute to household growth. I find strong evidence of spatial dependence in the growth process. Specification tests support a spatial Durbin model which allows for both endogenous spatial dependence in outcomes and exogenous spatial dependence through access conditions in neighboring areas. Direct and indirect spatial spillover effects have the greatest impact through feeder roads, suggesting that conventional (non-spatial) estimates of partial effects may be particularly prone to downward bias. Results from this study also indicate the importance of rural services and electricity to household growth outcomes, suggesting that studies of rural infrastructure which focus exclusively on road networks will miss important dimensions of rural accessibility and economic remoteness.

Improving farmers’ access to markets is widely recognized as a major development challenge. A review of the literature suggests that indicators of market access may bear little relationship to the specific processes of interest and hence provide misguided evidence of the impacts of improved market access. This paper attempts to “unpack” the dimensions of market access and, in the process, uses farm survey data from Kenya to investigate changes in multiple indicators during the post-liberalization period. Findings show that market access conditions experienced by rural Kenyans exhibit considerable variation across time, space, and indicator type. We suggest ways in which structured hypothesizing and sensitivity analysis may strengthen empirical treatments of market access issues in applied research.

The authors identify a set of development priorities for agriculture that cut across West Africa at both the country and regional levels to achieve economywide growth goals in the region. To do this we adopt a modeling and analytical framework that involves the integration of spatial analysis to identify yield gaps determining the growth potential of different agricultural activities for areas with similar conditions and an economywide multimarket model to simulate ex ante the economic effects of closing these yield gaps. Results indicate that the greatest agriculture-led growth opportunities in West Africa reside in staple crops (cereals and roots and tubers) and livestock production. Contributing the most to agricultural growth in the Sahel are livestock, rice, coarse grains, and oilseeds (groundnuts); in Coastal countries, staple crops such as cassava, yams, and cereal seems to be relatively more important than other subsectors; and in Central Africa livestock and root crops are the sources of growth with highest potential. Results also point toward an essential range of policies and investments that are needed to stimulate the productivity growth of prioritized activities. These include developing opportunities for regional cooperation on technology adaptation and diffusion, strengthening regional agricultural markets, exploiting opportunities for greater regional cooperation and harmonization, diversifying traditional markets, and enhancing linkages between agricultural and nonagricultural sectors.

The opportunities and constraints facing Ethiopian agriculture are strongly influenced by conditions which vary across geographical space. These conditions include basic agricultural production potentials, access to input and output markets, and local population densities which represent both labor availability and local demand for food. Understanding the geographical expression of these factors is an important way of making sense of Ethiopia’s agricultural and rural development options and for guiding the definition of supporting policies.

This report uses panel data on 1,267 smallholder households to monitor changes in their access to markets and services. We find that Kenyan smallholders’ proximity to infrastructure, markets, and services has improved markedly over the last decade. These improvements, however, have not been uniformly distributed over either time or space. Farmers in high-potential areas of the country continue to enjoy closer proximity to most kinds of markets and services compared to low-potential areas, but the greatest relative improvements over the 1997-2007 period have been in areas of medium and low potential. We also distinguish between public and private investments in examining changes in smallholders’ access to markets. Changes deriving from public investments have tended to be most geographically equitable; private investments appear to have been relatively concentrated in the less productive farming areas of the country, possibly because earlier investments focused on high-potential areas, leaving unexploited investment opportunities in the less productive areas. These changes in smallholders’ access to markets may offer important insights about the private sector’s response to market liberalization in recent Kenyan history.

Rural non-farm development plays a key role in generating employment in many developing countries. Clustering is an important industrial organization in the rural non-farm sector. Based on primary surveys of both urban and rural handloom weaver clusters in Ethiopia which took place in May/June 2008, one of the most important rural nonfarm sectors, this paper examines the mechanism and performance of clustering. The clustering way of handloom production is observed even in remote rural areas, illustrating its vitality and flexibility in adapting to restricted environments. Despite its resilience in surviving in harsh environments, improvements in infrastructure can significantly increase labor productivity in a cluster. In towns with electricity access, producers work longer hours than those in towns without electricity and more entrepreneurs with limited access to capital are able to participate in handloom production because of finer division of labor.

"We identify a set of development priorities for agriculture that cut across West Africa, at both the country and the regional level, to achieve economy-wide growth goals in the region. To do this, we adopt a modeling and analytical framework that involves the integration of spatial analysis to identify yield gaps determining growth potential of different agricultural activities for areas with similar conditions and an economy-wide multimarket model to simulate ex ante the economic effects of closing these yield gaps. Results indicate that the greatest agriculture-led growth opportunities in West Africa reside in staple crops (cereals as well as roots and tubers) and livestock production. Rice is the commodity with the highest potential for growth and the one that could generate the greatest benefits for many countries. Activities contributing the most to agricultural growth in the Sahel are livestock, rice, coarse grains, and groundnuts; in coastal countries, staple crops like cassava, yams, and cereals seem to be relatively more important than the contributions of other subsectors; and livestock and root crops are the sources of growth with highest potential in Central Africa. Our results also point toward an essential range of policies and investments that are needed to stimulate productivity growth of prioritized activities. These include the following: development of opportunities for regional cooperation on technology adaptation and diffusion, strengthening of regional agricultural markets exploiting opportunities for greater regional cooperation and harmonization, diversification of traditional markets, and enhancement of linkages between agricultural and nonagricultural sectors." from authors' abstract

"Strategies for boosting the agricultural economies of developing countries usually focus on small farms, attempting, for example, to link smallholders with markets through production chain development. However, such strategies often fail to differentiate between different types of small farmers or to investigate the distribution of assets within the group—efforts that are important because unequal distributions of assets can restrict pro-poor growth. Further, strategies to develop production chains favor some small farmers over others (i.e., those already participating in targeted chains and those with relatively more productive assets). Using landholding size as an organizational filter, we performed a basic descriptive analysis of smallholder traits in Ghana, using data from the 2005–2006 Ghana Living Standards Survey (GLSS5). We found strong inequalities in landholding distributions within Ghana's small-farm sector in all regions of the country. Using a classification of smallholders we derived based on landholding size, we examined a variety of small-farm traits and found that many of the broadly perceived defining characteristics of smallholder agriculture—such as low input use and low market engagement—are negatively correlated with landholding size. The crowding of farms at the smaller end of the small-farm spectrum in Ghana suggests that rural development strategies based on expanding existing market chains will face challenges in connecting with the bulk of small producers, who are less well endowed than average statistics indicate." from authors' abstract

"This paper considers vulnerability reduction in Sub-Saharan Africa (SSA) from a more aggregated macro viewpoint. We focus on risk related to agriculture, since vulnerability and agriculture are intimately linked in SSA due to the location of the poor, their dependence on agriculture and the inherent risks of an agricultural livelihood. We argue that agricultural growth is one of the most effective means for improving permanent incomes and reducing vulnerability. However, agriculture is not homogeneous, and the inherent risks vary across countries and regions. Therefore, we also discuss appropriate investment strategies and policy instruments for different sets of risks." from Authors' Abstract

""Smallholders in Ghana, as elsewhere, are widely considered to be the largest as well as the most vulnerable component of the rural sector. Ghana professes national development objectives of reducing rural poverty through the increased productivity and commercialization of smallholder agriculture.... This work uses household survey data, district-level production data and a variety of mapped infrastructural and biophysical data to characterize the production environments and characteristics of smallholder agriculture. This paper explores the relevance of geographically-differentiated characteristics. Several key issues are highlighted: the less prevalent use of inputs, lower commercialization, and lower welfare rates of producers with smaller landholdings.

"The choices that smallholder farmers are able to make are strongly conditioned by the geographic conditions in which they live. The importance of this fact for rural development strategy is not lost on policy makers. For example, the government of Ethiopia frequently frames policy discussions by broadly different geographical conditions of moisture availability, recognizing moisture reliable, drought prone and pastoralist areas. These conditions are seen as important criteria for determining the nature, extent and priority of development interventions for different parts of the country. There is considerable evidence, however, that other geographical factors also have important implications for rural development options. This paper uses agroecology, access to markets, and population density to define development domains: geographical locations sharing broadly similar rural development constraints and opportunities. Unlike similar efforts conducted elsewhere, this work is unique in that it seeks to move away from a subjective mapping of factors of theorized importance to a more rigorous definition of development domains on the basis of quantitative data on smallholder livelihood strategies. After selecting variables for mapping, we calibrate our definition for domains in such a way that their explanatory power is maximized across a range of livelihood strategies that figure in the current Ethiopian rural development discourse (market engagement, dependence upon agriculture, etc.)." Authors' Abstract

"We examine the spatial determinants of the prevalence of poverty for small spatially defined populations in rural Malawi. Poverty prevalence was estimated using a small-area poverty estimation technique. A theoretical approach based on the risk chain conceptualization of household economic vulnerability guided our selection of a set of potential risk and coping strategies — the determinants of our model — that could be represented spatially. These were used in two analyses to develop global and local models, respectively. In our global model—a spatial error model — only eight of the more than two dozen determinants selected for analysis proved significant. In contrast, all of the determinants considered were significant in at least some of the local models of poverty prevalence. The local models were developed using geographically weighted regression. Moreover, these models provided strong evidence of the spatial nonstationarity of the relationship between poverty and its determinants. That is, in determining the level of poverty in rural communities, where one is located in Malawi matters. This result for poverty reduction efforts in rural Malawi implies that such efforts should be designed for and targeted at the district and subdistrict levels. A national, relatively inflexible approach to poverty reduction is unlikely to enjoy broad success." Authors' Abstract

"Because the conditions for agricultural development vary considerably across space, we need to develop methods that allow us to take such variability into account when evaluating development strategies for particular crops or farming systems. This paper addresses spatially varying characteristics in an evaluation of the potential economic benefits of three cotton development strategies for Uganda: area expansion, productivity improvement, and domestic consumption increase. We begin with a historical review of cotton production in Uganda. We then described the major challenges and opportunities for Ugandan cotton production, including farm-level production constraints. Household-level production data from the 2000 Uganda National Household Survey (UNHS) are used to estimate the current spatial distribution of cotton production (called the cotton production area, or CPA), based on the association of household cotton production with ranges in mapped variables (altitude, length of growing period, and population density), district cotton production statistics and expert knowledge of local production patterns. Cotton development domains (CDDs) are then defined by agroclimatic suitability, market/ginnery access, and inclusion in the CPA. We use the UNHS data to evaluate the importance of cotton as a livelihood enterprise and its role in rural livelihood strategies. Key ecosystems and protected areas are considered in conjunction with the CDDs in defining feasible areas for expansion of production. Finally, the Dynamic Research Evaluation for Management (DREAM) model is used to estimate benefits that accrue from the three development strategies considered." Authors' Abstract

This is a draft paper, submitted in advance of presentation at the 2014 Annual Meeting of the Agricultural & Applied Economics Association.