@inbook{muth_okrent_zhen_karns_2020, place={London}, title={Conducting cost-benefit analyses using scanner and label data}, ISBN={9780128145074}, DOI={10.1016/B978-0-12-814507-4.00008-0}, abstractNote={Scanner and label data have numerous applications for estimating the costs and benefits of policies and regulations affecting food and beverage products. When estimating costs, the number of barcodes, formulas, servings, manufacturers, or other units of analysis can be calculated using scanner data. When estimating benefits, the volume of sales can be used as a proxy for consumption in modeling the potential improvements in health associated with food choices. In this chapter, we describe the different ways that store scanner data and household scanner data, with or without linking to label data, can be used as the basis for cost-benefit analyses. We then provide an overview of a labeling cost model and a reformulation cost model that were constructed using 2012 Nielsen Scantrack store scanner data.}, booktitle={Using Scanner Data for Food Policy Research}, publisher={Academic Press}, author={Muth, Mary K. and Okrent, Abigail M. and Zhen, Chen and Karns, Shawn A.}, year={2020}, pages={203–229} }
 @inbook{muth_okrent_zhen_karns_2020, place={London}, title={Estimating food demand systems using scanner data}, ISBN={9780128145074}, DOI={10.1016/B978-0-12-814507-4.00006-7}, abstractNote={Demand system estimates are useful tools to examine the effects of policy-induced changes in prices (i.e., taxes and subsidies), income, changes in food labels, and advertising on food purchasing patterns. This chapter illustrates techniques, opportunities, and challenges of estimating a food demand system using a combination of retail and household scanner data. It includes a general overview of estimating demand systems and an application of estimating a demand system for salty snacks using household purchase and retail sales information recorded in the IRI Academic Datasets.}, booktitle={Using Scanner Data for Food Policy Research}, publisher={Academic Press}, author={Muth, Mary K. and Okrent, Abigail M. and Zhen, Chen and Karns, Shawn A.}, year={2020}, pages={141–175} }
 @inbook{muth_okrent_zhen_karns_2020, place={London}, title={Insights from past food research using scanner data}, ISBN={9780128145074}, DOI={10.1016/B978-0-12-814507-4.00005-5}, abstractNote={Numerous studies have used store and household scanner data to investigate food policy issues. Some studies have focused on assessing the statistical properties of scanner data to provide a better understanding of the data. Topics of focus related to food policy include food pricing, food access, food assistance, market competition, health and nutrition claims, nutritional content, diet quality, and food safety. This chapter provides an overview of novel and interesting ways scanner data have been used to address food policy issues in the literature.}, booktitle={Using Scanner Data for Food Policy Research}, publisher={Academic Press}, author={Muth, Mary K. and Okrent, Abigail M. and Zhen, Chen and Karns, Shawn A.}, year={2020}, pages={59–140} }
 @inbook{muth_okrent_zhen_karns_2020, place={London}, title={Label and nutrition data at the barcode level}, ISBN={9780128145074}, DOI={10.1016/B978-0-12-814507-4.00003-1}, abstractNote={For many types of food research and policy studies, access to information from product labels, particularly nutrient content and product claims, enables or substantially enhances analyses. Some scanner data companies provide label information linked to purchase or sales data at the barcode level. Other data vendors specialize only in providing label data, and researchers must acquire purchase or sales data from a separate source. Data vendors obtain label data directly from manufacturers or through some means of coding data from product labels in the marketplace. We provide a list of suggested considerations when researchers seek to acquire label data for conducting food policy research.}, booktitle={Using Scanner Data for Food Policy Research}, publisher={Academic Press}, author={Muth, Mary K. and Okrent, Abigail M. and Zhen, Chen and Karns, Shawn A.}, year={2020}, pages={31–39} }
 @inbook{muth_okrent_zhen_karns_2020, place={London}, title={Measuring the food environment using scanner data}, ISBN={9780128145074}, DOI={10.1016/B978-0-12-814507-4.00007-9}, abstractNote={Household scanner data can be used to calculate measures of the healthfulness of the food environment. These measures can then be used to model the effects of the food environment on the nutritional quality of household food purchases. In this chapter, we demonstrate an approach to measuring the healthfulness of the food environment using scanner and dietary recall data. Using scanner data purchases and the estimated parameters from regression models with dietary recall data, we calculate household-level and retail chain-level approximate healthy eating indexes (aHEI). We then use these measures in reduced-form models of the nutritional quality of household food purchases while accounting for the endogeneity associated with household and store location choice.}, booktitle={Using Scanner Data for Food Policy Research}, publisher={Academic Press}, author={Muth, Mary K. and Okrent, Abigail M. and Zhen, Chen and Karns, Shawn A.}, year={2020}, pages={177–202} }
 @inbook{muth_okrent_zhen_karns_2020, place={London}, title={Methodological approaches for using scanner data}, ISBN={9780128145074}, DOI={10.1016/B978-0-12-814507-4.00004-3}, abstractNote={Methodological issues that arise when working with scanner data vary depending on whether researchers are using data reported at the store level or household level or are using product-level data aggregated to geographic areas, marketing channels, or demographic categories. Complications arise particularly with underreporting at the store or household level, unreported types of products, and types of variables provided in analysis datasets. To account for common limitations or to prepare data in an appropriate form to address a research question, researchers may need to create their own aggregated data, adjust quantities or prices to make the data more representative or complete, construct appropriate time-series price indices, and determine whether to weight the data.}, booktitle={Using Scanner Data for Food Policy Research}, publisher={Academic Press}, author={Muth, Mary K. and Okrent, Abigail M. and Zhen, Chen and Karns, Shawn A.}, year={2020}, pages={41–57} }
 @inbook{muth_okrent_zhen_karns_2020, place={London}, title={Sources of scanner data across the globe}, ISBN={9780128145074}, DOI={10.1016/B978-0-12-814507-4.00002-X}, abstractNote={IRI, Kantar, and Nielsen are the main suppliers of commercially available household and store scanner data across the globe. In some cases, scanner data companies partner with each other to collect and sell data, but each offers different coverage of countries and types of datasets. In some cases, researchers have obtained direct access to scanner data from stores for use in conducting analyses and for running experiments within stores. IRI and Nielsen also provide a limited amount of data to academic researchers at a reduced cost. We provide a list of suggested considerations when researchers seek to purchase or otherwise acquire scanner data for use in conducting food policy research.}, booktitle={Using Scanner Data for Food Policy Research}, publisher={Academic Press}, author={Muth, Mary K. and Okrent, Abigail M. and Zhen, Chen and Karns, Shawn A.}, year={2020}, pages={13–30} }
 @inbook{muth_okrent_zhen_karns_2020, place={London}, title={What is scanner data and why is it useful for food policy research?}, ISBN={9780128145074}, DOI={10.1016/B978-0-12-814507-4.00001-8}, abstractNote={Scanner data obtained from stores or household panels allow for much more detailed analyses of food purchase behavior than previously possible using aggregated data. The data are recorded at the scannable barcode level and can be linked to detailed information on characteristics of products, purchasers, and stores. The main commercial suppliers of store and household scanner data across the globe are Kantar, IRI, and Nielsen, but sometimes researchers obtain data directly from stores. The data are increasingly being used for a broad range of food policy research applications. When using the data, researchers should have an understanding of the data collection procedures used by the data vendors; the extent of coverage across geographies, stores, households, and products; and potential barriers or other practical considerations.}, booktitle={Using Scanner Data for Food Policy Research}, publisher={Academic Press}, author={Muth, Mary K. and Okrent, Abigail M. and Zhen, Chen and Karns, Shawn A.}, year={2020}, pages={1–12} }
 @article{muth_wohlgenant_karns_2007, title={Did the pathogen reduction and hazard analysis and critical control points regulation cause slaughter plants to exit?}, volume={29}, ISSN={["1058-7195"]}, DOI={10.1111/j.1467-9353.2007.00374.x}, abstractNote={Our multiperiod analysis tested whether the 1996 Pathogen Reduction and Hazard Analysis and Critical Control Points food safety regulation affected the probability of slaughter plant exit. We estimated probit models using pooled plant-level datasets for the preimplementation, implementation, and postimplementation periods. Results suggest that very small and small meat slaughter plants were more likely to exit during implementation than during preimplementation but less likely after implementation. In contrast, the results suggest the regulation had little effect on the probability of very small and small poultry slaughter plant exit during implementation but may have affected the probability of exit postimplementation. Copyright 2007, Oxford University Press.}, number={3}, journal={REVIEW OF AGRICULTURAL ECONOMICS}, author={Muth, Mary K. and Wohlgenant, Michael K. and Karns, Shawn A.}, year={2007}, pages={596–611} }
 @article{muth_rucker_thurman_chuang_2003, title={The fable of the bees revisited: Causes and consequences of the US honey program}, volume={46}, ISSN={["0022-2186"]}, DOI={10.1086/377290}, abstractNote={In his 1973 paper, Steven Cheung discredited the “fable of the bees” by demonstrating that markets for beekeeping services exist and function well. Although economists heeded Cheung’s lessons, policy makers did not. The honey program has operated for over 50 years, supporting the price of honey through a variety of mechanisms. Its effects were minor before the 1980s but then became important, with annual government expenditures near $100 million for several years. Reforms of the program in the late 1980s reduced its market effects and budget costs, returning it to its original role as a minor commodity program. Although the 1996 Farm Bill formally eliminated the honey program, it was reinstated in the 2002 Farm Bill. We measure the historical welfare effects of the program during its various incarnations, examine its frequently stated public interest rationale—the encouragement of honeybee pollination—and interpret its history in light of economic theories of regulation.}, number={2}, journal={JOURNAL OF LAW & ECONOMICS}, author={Muth, MK and Rucker, RR and Thurman, WN and Chuang, CT}, year={2003}, month={Oct}, pages={479–516} }
 @article{muth_karns_wohlgenant_anderson_2002, title={Exit of meat slaughter plants during implementation of the PR/HACCP regulations}, volume={27}, number={1}, journal={Journal of Agricultural and Resource Economics}, author={Muth, M. K. and Karns, S. A. and Wohlgenant, M. K. and Anderson, D. W.}, year={2002}, pages={187–203} }
 @article{muth_wohlgenant_1999, title={A test for market power using marginal input and output prices with application to the US beef processing industry}, volume={81}, ISSN={["1467-8276"]}, DOI={10.2307/1244027}, abstractNote={for a number of years, it has only been applied in rather limited ways. In this paper we show how this method can be used to develop a general test for oligopoly and oligopsony behavior. The test exploits the fact that, under price-taking behavior, there is a known, fixed relationship between changes in input prices on output supply and changes in output price on input demands. The model and test developed are shown to be quite general and not dependent on empirical estimates of output demand and input supply. We apply this test to the U.S. beef processing industry. Because of the high level of market concentration in this industry, there is concern that beef packing firms are exercising market power in the purchase of finished cattle by keeping cattle prices below competitive levels and in the sale of packed beef by keeping prices above competitive levels. Most previous studies of the beef packing industry have found evidence that firms, at least part of the time, are exercising market power in the purchase of finished cattle (Schroeter; Azzam and Pagoulatos; Schroeter and Azzam; Azzam; Azzam and Park; Koontz, Garcia, and Hudson) or are exercising market power in the sale of packed beef (Schroeter, Schroeter and Azzam). However, all of these studies are fairly restrictive in their assumptions regarding fixed proportions, the relationship between market power in the input and output markets, and the specification of input supply and output demand. Previous studies by Muth and by Muth and Wohlgenant (1999), which allow for variable proportions and do not impose restrictions on the relationship of market power in each market, did not find evidence of market power in the output and input markets for the beef packing industry; however, the results of each of these studies do depend on the specification of input supply and output demand.}, number={3}, journal={AMERICAN JOURNAL OF AGRICULTURAL ECONOMICS}, author={Muth, MK and Wohlgenant, MK}, year={1999}, month={Aug}, pages={638–643} }
 @article{muth_wohlgenant_1999, title={Measuring the degree of oligopsony power in the beef packing industry in the absence of marketing input quantity data}, volume={24}, number={2}, journal={Journal of Agricultural and Resource Economics}, author={Muth, M. K. and Wohlgenant, M. K.}, year={1999}, pages={299–312} }
 @article{muth_thurman_1995, title={Why support the price of honey?}, number={2}, journal={Choices (Ames, Iowa)}, author={Muth, M. K. and Thurman, W. N.}, year={1995}, pages={19} }