This paper investigates what factors and characteristics of organic consumers affect annual organic food expenditure by using Nielsen’s consumer panel dataset from 2010 to 2014. To be specific, this paper explores new marketing opportunities by investigating organic consumer heterogeneity in different household income levels by utilizing the multilevel model. Findings in this study will contribute to the previous and existing literature in three-folds. First, we find that the organic consumers are more heterogeneous in the high-level of income groups (approximately above $60,000), as well as the low-income households between $35,000 and $45,000. This finding demonstrates that the income levels above $60,000 and around $40,000 have potential market segmentation. Second, we find that that annual organic expenditure is positively associated with consumers who consecutively repurchase organic food products compared to irregular organic consumers, supporting a different level of satisfaction. Third, we find that USDA organic labeling has a positive effect on annual organic expenditure compared to the organic labeling certified by private companies, implying the importance of credibility for the organic labeling.

This study aims to identify critical consumer-demographic characteristics associated with the consumption of products containing hemp and investigate their effect on total expenditure in the USA. To estimate the likelihood of market participation and consumption level, the Heckman selection model is employed utilizing Nielsen consumer panel data from 2008 to 2015. Using a Heckman selection model, this study finds that socio-demographic characteristics, especially income, age, and education, play an important role in explaining purchases of and demand for different categories of hemp products. Noteworthy is the finding that the role of the age of the household head is mixed with respect to consumption decisions and consumption level across the products. In most cases, higher education and income households are more likely to buy hemp products, and those are associated with significantly higher consumption levels. The hemp products used in this study are made of hemp seeds, and our findings show that the hemp seed market could be segmented based on the forms. Results provide a basic understanding of a consumer profile and overall hemp market that has had double-digit growth over the last six years. As the industry continues to move forward, policymakers will need a deeper understanding of the factors driving the industry to create regulations supporting the development of the hemp industry.

Background: The reintroduction of Cannabis sativa L. in the form of hemp (< 0.3% THC by dry weight) into the US agricultural sector has been complex and remains confounded by its association with cannabis (> 0.3% THC by dry weight). This has been further exacerbated by inconsistent hemp regulations in the US since the 2014 Farm Bill’s reintroduction. Methods: A content analysis was performed to analyze the terms and definitions presented by state and tribal hemp production plans, the USDA Hemp producer license, and the 2014 state pilot plans. A total of 69 hemp production plans were analyzed. Results: Results suggest significant discrepancies between hemp production plans, which have been exacerbated by extending the 2014 Farm Bill language into the 2018 Farm Bill timeframe. Conclusions: Findings from this study point to areas in need of uniformity and consistency as the regulatory framework is modified and provides a starting point for change for federal policymakers. The results may also be useful to companies attempting to market products across state boundaries. Suggestions for how to mitigate these inconsistencies are provided based on the content analysis findings.

This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as well informing the likelihood of adverse water quality events from nutrient run-off.

Two simulated farm case studies provide a means for teaching financial and risk management strategies to western Kentucky grain farmers. Aggregate financial data for 227 grain farms define the case studies, which illustrate how cost and debt affect cash flow and working capital over a 5-year period. Responding to the case studies, farmers were able to discuss these financial concepts in a group setting among competitor neighbors without revealing personal business information. The use of composite financial data engaged the farmers and allowed for improved discussion on risk management products and the potential to protect working capital over multiple years. Extension professionals can apply the methods described.