Given that women in rural communities in developing countries are responsible for the nutrition and health-related decisions affecting children in their care, their empowerment may influence the health status of their children. The association between women’s empowerment, measured by using a recently developed Women’s Empowerment in Agriculture Index, and children’s health status is examined for a sample of households in Northern Ghana applying a Multiple Indicators Multiple Causes (MIMIC) model. The MIMIC approach is used to link multiple indicator variables with multiple independent variables through a “single underlying” latent variable. Height-for-age and weight-for-height z-scores are used as indicators of the underlying children’s health status and women’s empowerment in agriculture and control variables are used as the multiple independent variables. Our results show that neither the composite empowerment score used to capture women’s empowerment in agriculture nor its decomposed components are statistically significant in their association with the latent children’s health status. However, the associations between children’s health status and control variables such as mother’s education, child’s age, household’s hunger scale and residence locale are statistically significant. Results also confirm the existence of the ‘single underlying’ common latent variable. Of the two health status indicators, height-for-age scores and weight-for- height scores, the former exhibited a relatively stronger association with the latent health status. While promoting women’s empowerment to enhance their ability to make strategic life choices, it is important to carefully consider how the achievement of these objectives will impact the women’s well-being and the well-being of the children in their care.

Abstract. Precision agriculture (PA) has been commercially available for decades, however only specific technologies have been readily adopted. The overall goal of this study was to provide information of the historical changes (from 2000 to 2016), current status of PA utilization, and sales expectations in the next time period. Within this overarching objective, specific goals included 1) determining the specific technologies that farmers adopt and 2) estimating the probability of transitioning from one bundle of PA technologies to another. The three information-intensive technologies included: 1) yield monitor (YM) with or without GNSS 2) variable rate (VR) application of inputs, and 3) precision soil sampling (PSS). Combinations of these three technologies in addition to a possible “no technology adopted” response resulted in eight categories of PA technology bundles. Each year, farms were classified as having one of these eight possible bundles of PA technology. Adoption of PA technologies has increased over time, with the use of only YMs and the bundle of all three PA technologies (YM, PSS, and VR) as the two primary bundles being adopted. When only VR was adopted, there was a 47% probability that the farm would add a YM by next year. When a farm used YM, VR, and PSS, there was a 99% probability that a farm would continue using the bundle in the following year. The results are useful for farmers, extension professionals, and policymakers to understand prior adoption paths for bundles of PA technology. Future steps can connect this database on adoption of PA technology with farm meta-descriptors such as acreage, type of crop, rotation, other relevant management practices, and financial variables so to better understand how farmers are integrating technologies into their farming operations. Keywords: Adoption, Information-intensive, Markov chain, Precision agriculture, Sequential, Site specific, Soil sampling, Transition probability, Variable rate, Yield monitor.

During the recession, the decline in home value and home ownership reduced the demand for ornamental plants, lawn and garden products, and related services, which resulted in significantly negative effect on the green industry revenues.Postrecession consolidation in the United States green industry has forced smaller firms to re-evaluate their marketing strategies. New-media marketing has gained attention as a relatively low-cost and high-exposure marketing strategy. This paper utilizes binary logit and interval censored regression to examine the use and the impact of social-media marketing in the green industry. The analysis was based on primary data from a survey of US nurseries and garden centers. The findings reveal that the daily use of social-media marketing is largely driven by the network effect and the managers' attitudes. They also indicate that the small-sized firms receive higher returns from social media use in terms of increased sales compared with larger firms. K E Y W O R D S green industry, horticulture, social-media marketing, technology adoption J E L M31, O33, Q13 Agribusiness. 2019;35:281-297.wileyonlinelibrary.com/journal/agr

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This case study describes Brazilian ethanol industry and strategic issues faced by sugarcane farmers and processors as a result of recent industry expansion into the states of Goias and Mato Grosso do Sul. It provides detailed description of the ethanol supply chain in Brazil from field to market and discusses market drivers influencing the industry. Shaped by government regulations, market liberalization, globalization, and technological change, the Brazilian ethanol industry provides a rich context for learning and applying strategic analysis tools. The case is designed to be used in a graduate or undergraduate agribusiness management or strategic management course. The specific teaching objective for this case is to refine and reinforce students’ understanding of industry analysis and the effect of market drivers on competitive forces in an industry. Students will be expected to conduct an industry analysis and provide strategy recommendations to managers of ethanol plants and farmers. The case study incorporates all of the essential information for students to understand the underlying economics of the ethanol value chain and how the external forces shape strategic growth opportunities.

The recent rise in food prices in China triggered by global commodity price spikes led to growing welfare concerns among economists and policymakers. While evidence suggests the Chinese government was successful in preventing major upswings in food prices, the true impact on consumer welfare remains unknown. This study examines consumer welfare consequences of food price increases in China based on the Fixed-Effects Exact Affine Stone Index (FE-EASI) demand model that accounts for unobserved consumer and provincial heterogeneity estimated on nationally representative provincial-level panel data. The effects of actual price changes as well as two policy initiatives are evaluated. The major findings indicate that urban wages outpaced food prices, and consumer welfare loss has been moderate as a fraction of food expenditures. The results of policy analysis indicate that government subsidies overcompensated the negative effects of price increases for the relatively less affluent households. Finally, a counterfactual analysis is utilized to illustrate the empirical superiority of the EASI over the QUAIDS system commonly used in previous welfare analyses.

We investigate food preference changes in Russia that may have resulted from political, economic, and other changes. Our empirical framework utilizes advances in consumer theory and exploits provincial-level panel data on food consumption and supply shifters to identify price and income effects. Our findings indicate that consumers underwent a structural preference change that began in 2007 and continued into 2014. To illustrate the magnitude of this change, we contrast economic effects for select food commodities across regions. The new insights will be useful in designing timely and effective food and trade policies, as well as informing strategy decisions of agribusiness industry players.

Dedicated annual sorghum crops, such as sweet sorghum or energy sorghum, may provide an option for farmers to supply cellulosic feedstocks for biofuel production and help the industry meet government mandates. Kansas farmers are poised to be major producers of sweet sorghum for biofuels due to favorable agro-ecological conditions. The purpose of this paper is to assess Kansas farmers' willingness to grow sweet sorghum under contract as a feedstock for biofuel production. The paper examines farmers' willingness-to-pay for contract attributes and the impact of socio-economic factors on their willingness-to-pay for these attributes. A stated choice survey was administered to Kansas farmers to assess their willingness to grow sweet sorghum for biofuels under various contracting scenarios. Results show that farmers may be willing to grow biomass for bioenergy under contract, but may have varying preferences for the importance of contract attributes such as net returns, contract length, insurance availability, government incentives, and potential for biorefinery harvest options based on socio-economic characteristics of growers.