Retail Markups and Discount-Store Entry

Hard discountersare retail formats that set retail food prices even lower than ex- isting discount formats, such as Walmart and Target. O¤ering limited assortments and focusing on store-brands, these formats promise to change the competitive landscape of food retailing. In this paper, we study the e¤ect of entry of one hard-discount format on markups earned by existing retail stores, focusing on several important grocery mar- kets across the Eastern U.S. Focusing on establishment-level protability, we estimate store-level markups using the production-side approach of De Loecker and Warzynski (2012). We nd that hard-discounter entry had the expected e¤ect of reducing margins from similar stores, but did not a¤ect markups earned by stores in the same market that are likely to appeal to a di¤erent market segment. In general, hard-discounter entry reduced markups for incumbment retailers by 7:3% relative to markups in non-entry markets. These results indicate that the net e¤ect of hard-discounter entry reduces the overall level of store protability, regardless of higher sales realized by incumbent retailers

Using a Sensory Learning Framework to Design Effective Curricula: Evidence from Indigenous Nutrition Education Programs

As health disparities among Native Americans persist, promoting better health outcomes is of paramount concern among Indigenous populations. A variety of programs exist that try to alleviate problems resulting in higher rates of diet-related chronic diseases and premature death. For this study, we collaborated with an Indigenous-led nonprofit that implemented a series of nutrition education courses designed to empower community members to make healthier food choices. The theoretically based curriculum, which provided learners with information in the form of sensory-based modules, e.g., food preparation, food handling, cultural awareness, and practical cooking skills, was introduced in various communities in the Great Plains and Southwest. The nutrition education programs were modeled after a canonical educational learning model, Bloom’s Taxonomy, designed to provide participants with information and resources necessary to make healthier food choices across three cognitive domains (i.e., tiers). We used a mixed-methods approach, coupling Principal Components Analysis with a qualitative SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, to assess each program’s capacity to enhance learning retention, i.e., to assess the salience of information provided and the extent to which each program was more or less successful in participants’ learning. We found that course content and instruction are strongly correlated with program satisfaction. In addition, from the qualitative analysis, we found that as each successive module of the program challenged higher cognitive domains, participants were more likely to indicate satisfaction in the course material as well as state a desired change in their behavior, which we attribute to participants’ ability to synthesize and evaluate information. Aspects of this programming framework have the potential to be adapted to and integrated into other Native communities striving for the successful adoption of healthier diets

Store Choice and Consumer Behavior in Food Deserts: An Empirical Application of the Distance Metric Method

While food access is an increasingly studied component of research related to diet and health, consumer behavior and store choice have been relatively overlooked in understanding the dietary health-food access relationship. Especially in areas with high poverty rates, where the proportion of low-access and low-income population persists over time, consumers are faced with shopping at non-traditional stores, which may augment the negative welfare impacts of residing in these areas. Using IRI's Consumer Network Panel, IRI's InfoScan, and Nielsen's TDLinx store characteristics data, this paper develops a structural model of store choice that frames Pinkse, Slade, and Brett's (2002) distance metric (DM) method inside a demand system to model what behaviors drive consumers' store choice decisions, highlighting underserved communities. While the DM method has been used previously to model brand choice, this paper is the first to use it to investigate store choice. Because the store-choice model is based on demand for store attributes (such as relative prices, product assortment measures, store services, and distance between stores), it reveals consumer preferences for store types and provides insight into policy prescriptions that attempt to improve food access

COVID-19 Impact on Fruit and Vegetable Markets: One Year Later

More than one year after the outbreak of COVID-19, fruit and vegetable markets continue to adjust to the evolving landscape. In this article, we focus on three key measures of input and output market performance that serve as indicators of the stability of fruit and vegetable markets in the medium-term, and offer some insight for how these markets will continue to adjust in the longer run. Specifically, we use data to highlight the most recent trends in (i) the production and aggregate movement for major fruit and vegetable crops in the United States and Canada, (ii) labour supply and immigration visa patterns, and (iii) U.S.-Canada trade patterns for fruits and vegetables. We provide evidence that the fresh produce supply chain has remained relatively robust in the months following the outbreak of COVID-19.Acknowledgments: The project was supported, in part, through USDA Hatch project NYC-121864. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the United States Department of Agriculture (USDA)

Store Choice and Consumer Behavior in Food Deserts: An Empirical Application of the Distance Metric Method

Shopping and store-choice decisions are intertwined with firms’ decisions to enter or exit a market, as well as with heterogeneous consumer demographics. The importance of food access becomes apparent in determining where households choose to purchase food, as consumers residing in underserved areas are faced with shopping at non-traditional stores that may result in negative welfare outcomes. Research regarding consumer purchasing behavior has traditionally looked at store choice as a nested discrete choice decision; however, we propose an alternative approach that models consumer store choice preferences for store attribute bundles, including product assortment, store services, and price via the Distance Metric (DM) method of Pinkse, Slade, and Brett (2002). Methodologically, the use of the DM method offers a straightforward way to measure substitution patterns between stores with similar attributes. In addition, the importance of product assortment, store services, and price can be described to create a more flexible model of store selection within different markets across the U.S