This study examines the factors influencing women farmers’ choice of adaptation strategies to reduce the negative impacts of climate change and the effects of these strategies on household income and food insecurity. A field survey was conducted among 426 women farmers in the Center-North region, which covers 7% of Burkina Faso territory. Descriptive statistics, a multinomial logit model, and a propensity score matching model were used to analyze the data collected. The results of the econometric analysis show that high domestic tasks, type of climate shocks experienced, membership in women’s group, and financial constraints are important determinants of adaptation decisions. Adaptation strategies are also found to have a positive impact on income and a negative impact on household food insecurity. These different findings highlight the need to prioritize flexible adaptation options to improve women farmers’ resilience to climate change, rather than generic solutions.

A typical characteristic of the wine supply chain in the Old World is the significant share of cooperatives in wine-making that coexists with investor-owned firms and on-farm wine-makers. This paper analyzes the determinants of whether grape growers deliver their grapes to a cooperative winery of which they are members, sell their grapes to outside wineries, or make their own wine on their farm. Our analysis is based on data from a typical wine-producing area in Northern Italy. The explanatory variables comprise the potential prices linked to the different grape allocations and various farmer and farm characteristics. The high share of farmers delivering their grapes to cooperatives can, to a large extent, be explained by their higher price relative to one of the spot markets. On-farm wine-making is favored by larger farms and more educated farmers.

Multinomial logit (MNL) differs from many other econometric methods because it estimates the effects of variables upon nominal, not ordered outcomes. One consequence of this is that the estimated coefficients vary depending upon a researcher’s decision about the choice of a reference, or “baseline,” outcome. Most researchers realize this in principle, but many focus upon the statistical significance of MNL coefficients for inference in the same way that they use the coefficients from models with ordered dependent variables. In some instances, this leads researchers to report statistics that do not reflect the correct quantities of interest and reach flawed conclusions. In this note, I argue that researchers need to orient their approach to analyzing both the substantive and statistical significance of predicted probabilities of interest that match their research questions.

Rural broadband infrastructure and service has received a significant amount of funding through the American Recovery and Reinvestment Act of 2009. These funds should increase broadband availability, but will broadband be used in rural areas and in particular by farmers? This paper uses Agricultural Resource Management Survey data to investigate why the majority of U.S. farmers choose not to use the Internet in their farm business. Although frequently cited by policymakers, concerns about inadequate Internet service or security actually account for a small percentage of responses. This research identifies targeted educational programs that focus on alleviating perceived barriers to Internet use.

Typically, marketers define market segments by their demographic characteristics, assuming that these segments represent consumers with relatively homogeneous buying patterns. A more managerially useful definition, however, groups consumers of similar behavior directly and then seeks to find demographic commonalities among them. This study uses a latent class analysis technique to segment consumers based on their responsiveness to a set of marketing variables, finding that a multiple-segment model provides a better fit to the data, and that these segments differ significantly in their responsiveness. By targeting marketing activities to their most responsive segments, the efficiency of commodity promotion can be dramatically improved.

A survey of Kansas, Texas, and Iowa agricultural producers was taken to examine the factors affecting their grain marketing practices. Sales indices models and models of qualitative choice are used to determine whether marketers' choices of cash market, forward contract, or futures and options oriented marketing practices are significantly affected by their personal and farm business characteristics. Results indicate that geographic location, farm size, grain enterprise specialization, farming experience, use of grain storage, and use of crop insurance have significant effects upon the respondents' choice of grain marketing practices.

Farm Service Agency (FSA) direct loans are intended to provide transitory credit to creditworthy borrowers unable to obtain conventional credit at reasonable terms. Farm loan program (FLP) effectiveness is measured in part by how readily direct loan borrowers graduate to conventional credit. A survey of FSA borrowers originating direct loans during fiscal years 1994-1996 is used to estimate graduation rates. A majority of 1994-1996 loan originators did exit the direct FLP by November 2004. A multinomial logit model indicates financial strength at origination resulted in greater likelihood of farming without direct loans approximately 9 years after loan origination.

A multinomial logit model was estimated and used to analyze the impact of various producer characteristics on the adoption of flow-through and recirculating technology in soft-shelled crab production. Because of the industry's geographic isolation and high turnover rate, data was collected by personal interviews in 1991. The results suggest that increased adoption might be fostered by targeting education programs towards full time, family operated businesses in non-traditional production regions. However, development of effective education programs may be hindered by the lack of a significant relationship between producer adoption decisions and the information provided by university or extension personnel.

A visitor's decision to use a particular recreational site is influenced by the individual's taste as well as the characteristics of the site. For this reason, improved knowledge of the visitors' interests and factors influencing their choices are vital for both planning and policy formulations in coastal development. This study examines visitor characteristics and desired site-specific characteristics in order to determine the factors affecting use of the Louisiana coast for specific recreational purposes. We use a multinomial logit model and internet survey data to evaluate the factors affecting individuals' decisions to visit coastal Louisiana for a specific use. Results suggest that the major variables affecting the choice of coastal recreational activities include environmental quality of the site, income, and travel time.