Using Scanner Data for Food Policy Research PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Using Scanner Data for Food Policy Research PDF full book. Access full book title Using Scanner Data for Food Policy Research by Mary K. Muth. Download full books in PDF and EPUB format.
Author: Mary K. Muth
Publisher: Academic Press
ISBN: 0128145471
Category : Business & Economics
Languages : en
Pages : 252
Get Book Here
Book Description
Using Scanner Data for Food Policy Research is a practitioners' guide to using and interpreting scanner data obtained from stores and households in policy research. It provides practical advice for using the data and interpreting their results. It helps the reader address key methodological issues such as aggregation, constructing price indices, and matching the data to nutrient values. It demonstrates some of the key econometric and statistical applications of the data, including estimating demand systems for policy simulation, analyzing effects of food access on food choices, and conducting cost-benefit analysis of food policies. This guide is intended for early-career researchers, particularly those working with scanner data in agricultural and food economics, nutrition, and public health contexts. - Describe different types of scanner data, the types of information available in the data, and the vendors that offer these data - Describe food-label data that can be appended to scanner data - Identify key questions that researchers should consider when acquiring scanner and label data for food policy research - Demonstrate how to use scanner data using tools from econometric and statistical analyses, including the limitations in interpreting results using the data - Describe and resolve key methodological issues related to using the data to facilitate more rapid analyses - Provide an overview of published literature as background for designing new studies - Demonstrate key applications of the data for food policy research
Author: Mary K. Muth
Publisher: Academic Press
ISBN: 0128145471
Category : Business & Economics
Languages : en
Pages : 252
Get Book Here
Book Description
Using Scanner Data for Food Policy Research is a practitioners' guide to using and interpreting scanner data obtained from stores and households in policy research. It provides practical advice for using the data and interpreting their results. It helps the reader address key methodological issues such as aggregation, constructing price indices, and matching the data to nutrient values. It demonstrates some of the key econometric and statistical applications of the data, including estimating demand systems for policy simulation, analyzing effects of food access on food choices, and conducting cost-benefit analysis of food policies. This guide is intended for early-career researchers, particularly those working with scanner data in agricultural and food economics, nutrition, and public health contexts. - Describe different types of scanner data, the types of information available in the data, and the vendors that offer these data - Describe food-label data that can be appended to scanner data - Identify key questions that researchers should consider when acquiring scanner and label data for food policy research - Demonstrate how to use scanner data using tools from econometric and statistical analyses, including the limitations in interpreting results using the data - Describe and resolve key methodological issues related to using the data to facilitate more rapid analyses - Provide an overview of published literature as background for designing new studies - Demonstrate key applications of the data for food policy research
Author: Katharine G. Abraham
Publisher: University of Chicago Press
ISBN: 022680125X
Category : Business & Economics
Languages : en
Pages : 502
Get Book Here
Book Description
Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.
Author: Robert C. Feenstra
Publisher: University of Chicago Press
ISBN: 0226239667
Category : Business & Economics
Languages : en
Pages : 404
Get Book Here
Book Description
Every time you buy a can of tuna or a new television, its bar code is scanned to record its price and other information. These "scanner data" offer a number of attractive features for economists and statisticians, because they are collected continuously, are available quickly, and record prices for all items sold, not just a statistical sample. But scanner data also present a number of difficulties for current statistical systems. Scanner Data and Price Indexes assesses both the promise and the challenges of using scanner data to produce economic statistics. Three papers present the results of work in progress at statistical agencies in the U.S., United Kingdom, and Canada, including a project at the U.S. Bureau of Labor Statistics to investigate the feasibility of incorporating scanner data into the monthly Consumer Price Index. Other papers demonstrate the enormous potential of using scanner data to test economic theories and estimate the parameters of economic models, and provide solutions for some of the problems that arise when using scanner data, such as dealing with missing data.
Author: International Labour Office
Publisher: International Labour Organization
ISBN: 9789221136996
Category : Business & Economics
Languages : en
Pages : 578
Get Book Here
Book Description
The consumer price index (CPI) measures the rate at which prices of consumer goods and services change over time. It is used as a key indicator of economic performance, as well as in the setting of monetary and socio-economic policy such as indexation of wages and social security benefits, purchasing power parities and inflation measures. This manual contains methodological guidelines for statistical offices and other agencies responsible for constructing and calculating CPIs, and also examines underlying economic and statistical concepts involved. Topics covered include: expenditure weights, sampling, price collection, quality adjustment, sampling, price indices calculations, errors and bias, organisation and management, dissemination, index number theory, durables and user costs.
Author: Christopher D. Carroll
Publisher: University of Chicago Press
ISBN: 022612665X
Category : Business & Economics
Languages : en
Pages : 517
Get Book Here
Book Description
Robust and reliable measures of consumer expenditures are essential for analyzing aggregate economic activity and for measuring differences in household circumstances. Many countries, including the United States, are embarking on ambitious projects to redesign surveys of consumer expenditures, with the goal of better capturing economic heterogeneity. This is an appropriate time to examine the way consumer expenditures are currently measured, and the challenges and opportunities that alternative approaches might present. Improving the Measurement of Consumer Expenditures begins with a comprehensive review of current methodologies for collecting consumer expenditure data. Subsequent chapters highlight the range of different objectives that expenditure surveys may satisfy, compare the data available from consumer expenditure surveys with that available from other sources, and describe how the United States’s current survey practices compare with those in other nations.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309100054
Category : Medical
Languages : en
Pages : 146
Get Book Here
Book Description
Several changes in the United States over the past two decades have implications for diet, nutrition, and food safety, including patterns of food consumption that have produced an increase in overweight and obese Americans and threats to food safety from pathogens and bioterrorism. The changes raise a number of critical policy and research questions: How do differences in food prices and availability or in households' time resources for shopping and food preparation affect what people consume and where they eat? How do factors outside of the household, such as the availability of stores and restaurants, food preparation technology, and food marketing and labeling policies, affect what people are consuming? What effects have food assistance programs had on the nutritional quality of diets and the health of those served by the programs? Where do people buy and consume food and how does food preparation affect food safety? To address these and related questions, the Economic Research Service (ERS) of the U.S. Department of Agriculture (USDA) asked the Committee on National Statistics to convene a panel of experts to provide advice for improving the data infrastructure on food consumption and nutrition. The panel was charged to review data needs to support research and decision making for food and nutrition policies and programs in USDA and to assess the adequacy of the current data infrastructure and recommend enhancements to improve it. The primary basis for the panel's deliberations, given limited resources, was a workshop on Enhancing the Data Infrastructure in Support of Food and Nutrition Programs, Research, and Decision Making, which the panel convened on May 27-28, 2004. This report is based on the discussions at the workshop and the deliberations of the panel. The report outlines key data that are needed to better address questions related to food consumption, diet, and health; discusses the available data and some limitations of those data; and offers recommendations for improvements in those data. The panel was charged to consider USDA data needs for policy making and the focus of the report is on those needs.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 030945428X
Category : Social Science
Languages : en
Pages : 151
Get Book Here
Book Description
Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.
Author: Emek Basker
Publisher: Edward Elgar Publishing
ISBN: 1783477385
Category : Business & Economics
Languages : en
Pages : 513
Get Book Here
Book Description
This Handbook explores and critically examines current research in economics and marketing science on key issues in retailing and distribution. Providing a rich perspective for the discussion of public policy, contributions from several disciplines and continents range from the history of chains and the impact of multinational retailers on international trade patterns to US merger policy in the retail context, the rise of the Internet, and consumer-to-consumer sales. The chapters address methodological issues such as the structural estimation of entry games between retailers, productivity measurement when both inputs and output are not fully observable, and demand estimation with variable assortment. Policy issues explored include mergers, zoning, and the regulation of buyer power, while other chapters address some of the recent exciting developments in technology, retail formats, and data availability. The book goes on to study the changes in online retailing and ‘big data’, and to examine competition in specific retail sectors including gasoline stations, automobile dealerships, supermarkets, and ‘big box’ retail. This state-of-the-art Handbook is an essential reference for students and academics of economics and marketing science, and offers an outsider’s perspective to specialists in operations research, data analytics, geography, and sociology.
Author: Frank Pasquale
Publisher: Harvard University Press
ISBN: 0674967100
Category : Law
Languages : en
Pages : 320
Get Book Here
Book Description
Every day, corporations are connecting the dots about our personal behavior—silently scrutinizing clues left behind by our work habits and Internet use. The data compiled and portraits created are incredibly detailed, to the point of being invasive. But who connects the dots about what firms are doing with this information? The Black Box Society argues that we all need to be able to do so—and to set limits on how big data affects our lives. Hidden algorithms can make (or ruin) reputations, decide the destiny of entrepreneurs, or even devastate an entire economy. Shrouded in secrecy and complexity, decisions at major Silicon Valley and Wall Street firms were long assumed to be neutral and technical. But leaks, whistleblowers, and legal disputes have shed new light on automated judgment. Self-serving and reckless behavior is surprisingly common, and easy to hide in code protected by legal and real secrecy. Even after billions of dollars of fines have been levied, underfunded regulators may have only scratched the surface of this troubling behavior. Frank Pasquale exposes how powerful interests abuse secrecy for profit and explains ways to rein them in. Demanding transparency is only the first step. An intelligible society would assure that key decisions of its most important firms are fair, nondiscriminatory, and open to criticism. Silicon Valley and Wall Street need to accept as much accountability as they impose on others.
Author: Sergio Consoli
Publisher: Springer Nature
ISBN: 3030668916
Category : Application software
Languages : en
Pages : 357
Get Book Here
Book Description
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
