{"product_id":"advances-in-business-statistics-methods-and-data-collection-isbn-9781119672302","title":"Advances in Business Statistics, Methods and Data Collection","description":"\u003cb\u003eADVANCES IN BUSINESS STATISTICS, METHODS AND DATA COLLECTION\u003c\/b\u003e \u003cp\u003e\u003ci\u003eAdvances in Business Statistics, Methods and Data Collection\u003c\/i\u003e delivers insights into the latest state of play in producing establishment statistics, obtained from businesses, farms and institutions. Presenting materials and reflecting discussions from the 6th International Conference on Establishment Statistics (ICES-VI), this edited volume provides a broad overview of methodology underlying current establishment statistics from every aspect of the production life cycle while spotlighting innovative and impactful advancements in the development, conduct, and evaluation of modern establishment statistics programs. Highlights include:\u003c\/p\u003e \u003cul\u003e \u003cli\u003ePractical discussions on agile, timely, and accurate measurement of rapidly evolving economic phenomena such as globalization, new computer technologies, and the informal sector.\u003c\/li\u003e \u003cli\u003eComprehensive explorations of administrative and new data sources and technologies, covering big (organic) data sources and methods for data integration, linking, machine learning and visualization.\u003c\/li\u003e \u003cli\u003eDetailed compilations of statistical programs’ responses to wide-ranging data collection and production challenges, among others caused by the Covid-19 pandemic.\u003c\/li\u003e \u003cli\u003eIn-depth examinations of business survey questionnaire design, computerization, pretesting methods, experimentation, and paradata.\u003c\/li\u003e \u003cli\u003eMethodical presentations of conventional and emerging procedures in survey statistics techniques for establishment statistics, encompassing probability sampling designs and sample coordination, non-probability sampling, missing data treatments, small area estimation and Bayesian methods.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eProviding a broad overview of most up-to-date science, this book challenges the status quo and prepares researchers for current and future challenges in establishment statistics and methods. Perfect for survey researchers, government statisticians, National Bank employees, economists, and undergraduate and graduate students in survey research and economics, \u003ci\u003eAdvances in Business Statistics, Methods and Data Collection \u003c\/i\u003ewill also earn a place in the toolkit of researchers working –with data– in industries across a variety of fields.\u003c\/p\u003e \u003cp\u003eList of Contributors xxix\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 1 Introduction to New Measures\/Indicators for the Economy 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1 Advances in Business Statistics, Methods and Data Collection: Introduction 3\u003cbr\u003e\u003ci\u003eGer Snijkers, Mojca Bavdaž, Stefan Bender, Jacqui Jones, Steve MacFeely, Joseph W. Sakshaug, Katherine J. Thompson, and Arnout van Delden\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2 GDP and the SNA: Past and Present 23\u003cbr\u003e\u003ci\u003eSteve MacFeely and Peter van de Ven\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3 GDP and the SNA: Future Challenges 43\u003cbr\u003e\u003ci\u003eSteve MacFeely and Peter van de Ven\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4 Bridging the Gap Between Business and Macroeconomic Statistics: Methodological Considerations and Practical Solutions 63\u003cbr\u003e\u003ci\u003eTimo Koskimäki and Kristian Taskinen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5 Measuring Investment in Intangible Assets 79\u003cbr\u003e\u003ci\u003eMojca Bavdaž, Ahmed Bounfour, Josh Martin, Alberto Nonnis, Giulio Perani, and Tjaša Redek\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6 Measuring the US Digital Economy 105\u003cbr\u003e\u003ci\u003eJessica R. Nicholson, Thomas F. Howells III, and David B. Wasshausen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7 Establishment Based Informal Sector Statistics: An Endeavor of Measurement from Economic Census 2018 of Nepal 125\u003cbr\u003e\u003ci\u003eMahesh C. Pradhan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 2 Topics in the Production of Official Establishment Statistics and Organizational Frameworks 145\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8 Statistical Producers Challenges and Help 147\u003cbr\u003e\u003ci\u003eJacqui Jones and Holly O’Byrne\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9 The Development and Maintenance of Statistical Business Registers as Statistical Infrastructure in Statistics Indonesia and the Australian Bureau of Statistics 175\u003cbr\u003e\u003ci\u003eImam Machdi, Ratih Putri Pertiwi, Rr. Nefriana, and Willem Erasmus\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10 Managing Response Burden for Official Statistics Business Surveys – Experiences and Recent Developments at Statistics Netherlands, Statistics Portugal, and Statistics Sweden 193\u003cbr\u003e\u003ci\u003eJohan Erikson, Deirdre Giesen, Leanne Houben, and Paulo Saraiva\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11 Producing Official Statistics During the COVID-19 Pandemic 225\u003cbr\u003e\u003ci\u003eJacqui Jones, Luisa Ryan, A.J. Lanyon, Marie Apostolou, Tanya Price, Corinna König, Marieke Volkert, Joseph W. Sakshaug, Dane Mead, Helen Baird, Duncan Elliott, and Craig H. McLaren\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 3 Topics in the Use of Administrative Data 265\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12 Methodology for the Use of Administrative Data in Business Statistics 267\u003cbr\u003e\u003ci\u003eArnout van Delden and Danni Lewis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13 Developing Statistical Frameworks for Administrative Data and Integrating It into Business Statistics. Experiences from the UK and New Zealand 291\u003cbr\u003e\u003ci\u003eNicholas Cox, Craig H. McLaren, Claire Shenton, Tom Tarling, and Ella W. Davies\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14 The Evolution of Integrating Administrative Data in Business Statistics in Ireland 315\u003cbr\u003e\u003ci\u003eColin Hanley and Sorcha O’Callaghan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 4 Topics in Business Survey Data Collection 335\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15 What Computerized Business Questionnaires and Questionnaire Management Tools Can Offer 337\u003cbr\u003e\u003ci\u003eGustav Haraldsen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16 Tailoring the Design of a New Combined Business Survey: Process, Methods, and Lessons Learned 357\u003cbr\u003e\u003ci\u003eGer Snijkers, Leanne Houben, and Fred Demollin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17 Advances in Question(naire) Development, Pretesting, and Evaluation 387\u003cbr\u003e\u003ci\u003eDiane K. Willimack, Heather Ridolfo, Amy Anderson Riemer, Melissa Cidade, and Kathy Ott\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18 Using Paradata in Electronic Business Survey Questionnaires 413\u003cbr\u003e\u003ci\u003eGer Snijkers, Susan Demedash, and Jessica Andrews\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19 Recent Findings from Experiments in Establishment Surveys 437\u003cbr\u003e\u003ci\u003eJosh Langeland, Heather Ridolfo, Jaki McCarthy, Kathy Ott, Doug Kilburg, Karen CyBulski, Melissa Krakowiecki, Larry Vittoriano, Matt Potts, Benjamin Küfner, Joseph W. Sakshaug, and Stefan Zins\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20 Web Portals for Business Data Collection 469\u003cbr\u003e\u003ci\u003eBente Hole and Leanne Houben\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21 A Creative Approach to Promoting Survey Response 501\u003cbr\u003e\u003ci\u003eCharles F. Brady, Jr. and Kari L. Klinedinst\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 5 Topics in the Use of New Data Sources and New Technologies 519\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e22 Statistical Data Production in a Digitized Age: The Need to Establish Successful Workflows for Micro Data Access 521\u003cbr\u003e\u003ci\u003eStefan Bender, Jannick Blaschke, and Christian Hirsch\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23 Machine Learning in German Official Statistics 537\u003cbr\u003e\u003ci\u003eFlorian Dumpert\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e24 Six Years of Machine Learning in the Bureau of Labor Statistics 561\u003cbr\u003e\u003ci\u003eAlexander Measure\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e25 Using Machine Learning to Classify Products for the Commodity Flow Survey 573\u003cbr\u003e\u003ci\u003eChristian Moscardi and Benjamin Schultz\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e26 Alternative Data Sources in the Census Bureau’s Monthly State Retail Sales Data Product 593\u003cbr\u003e\u003ci\u003eRebecca Hutchinson, Scott Scheleur, and Deanna Weidenhamer\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 6 Topics in Sampling and Estimation 613\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e27 Introduction to Sampling and Estimation for Business Surveys 615\u003cbr\u003e\u003ci\u003ePaul A. Smith and Wesley Yung\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e28 Sample Coordination Methods and Systems for Establishment Surveys 637\u003cbr\u003e\u003ci\u003eAlina Matei and Paul A. Smith\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e29 Variance Estimation for Probability and Nonprobability Establishment Surveys: An Overview 659\u003cbr\u003e\u003ci\u003eJill A. Dever and Dan Liao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e30 Bayesian Methods Applied to Small Area Estimation for Establishment Statistics 685\u003cbr\u003e\u003ci\u003ePaul A. Parker, Ryan Janicki, and Scott H. Holan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e31 Variance Estimation Under Nearest Neighbor Ratio Hot Deck Imputation for Multinomial Data: Two Approaches Applied to the Service Annual Survey (sas) 705\u003cbr\u003e\u003ci\u003eRebecca Andridge, Jae Kwang Kim, and Katherine J. Thompson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e32 Minimizing Revisions for a Monthly Economic Indicator 727\u003cbr\u003e\u003ci\u003eNicole Czaplicki, Stephen Kaputa, and Laura Bechtel\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 7 Topics in Data Integration, Linking and Matching 755\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e33 Record Linkage for Establishments: Background, Challenges, and an Example 757\u003cbr\u003e\u003ci\u003eMichael D.Larsen and Alan Herning\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e34 Methods for Estimating the Quality of Multisource Statistics 781\u003cbr\u003e\u003ci\u003eArnout van Delden, Sander Scholtus, Ton de Waal, and Irene Csorba\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e35 Adopting Previously Reported Data into the 2022 Census of Agriculture: Lessons Learned from the 2020 September Agricultural Survey 805\u003cbr\u003e\u003ci\u003eLinda J. Young, Joseph B. Rodhouse, Zachary Terner, and Gavin Corral\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e36 Integrating Alternative and Administrative Data into the Monthly Business Statistics: Some Applications from Statistics Canada 821\u003cbr\u003e\u003ci\u003eMarie-Claude Duval, Richard Laroche, and Sébastien Landry\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eAcknowledgments 837\u003c\/p\u003e \u003cp\u003eReferences 838\u003c\/p\u003e \u003cp\u003eIndex 839\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eGer Snijkers, PhD, \u003c\/b\u003eis Senior Methodologist at Statistics Netherlands and former Professor of data collection methodology in business research at Utrecht University in the Netherlands. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eMojca Bavda\u003c\/b\u003ež\u003cb\u003e, PhD,\u003c\/b\u003e is Associate Professor at the School of Economics and Business, University of Ljubljana, Slovenia. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eStefan Bender,\u003c\/b\u003e is Head of the Data Service Center of the Deutsche Bundesbank and Honorary Professor at the School of Social Sciences, University Mannheim, Germany. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eJacqui Jones\u003c\/b\u003e is the General Manager of Macroeconomic Statistics at the Australian Bureau of Statistics. She formerly worked at the UK Office for National Statistics.  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eSteve MacFeely, PhD, \u003c\/b\u003eis Director of Data and Analytics at the World Health Organization (WHO) and co-chair of the Committee of Chief Statisticians of the UN System. Formerly he was Chief Statistician of the United Nations Conference on Trade and Development (UNCTAD) and the Deputy Director of the Central Statistics Office, Ireland.  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eJoseph W. Sakshaug, PhD,\u003c\/b\u003e is Professor at the Institute for Employment Research and Department of Statistics at the Ludwig Maximilian University of Munich, Germany. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eKatherine J. Thompson\u003c\/b\u003e is the Senior Mathematical Statistician in the Associate Directorate for Economic Programs at the U.S. Census Bureau. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eArnout van Delden, PhD,\u003c\/b\u003e is Senior Methodologist in the use of administrative data and multisource statistics at Statistics Netherlands.  \u003c\/p\u003e\u003cp\u003e\u003ci\u003eAdvances in Business Statistics, Methods and Data Collection\u003c\/i\u003e delivers insights into the latest state of play in producing establishment statistics, obtained from businesses, farms and institutions. Presenting materials and reflecting discussions from the 6th International Conference on Establishment Statistics (ICES-VI), this edited volume provides a broad overview of methodology underlying current establishment statistics from every aspect of the production life cycle while spotlighting innovative and impactful advancements in the development, conduct, and evaluation of modern establishment statistics programs. Highlights include:\u003c\/p\u003e \u003cul\u003e \u003cli\u003ePractical discussions on agile, timely, and accurate measurement of rapidly evolving economic phenomena such as globalization, new computer technologies, and the informal sector.\u003c\/li\u003e \u003cli\u003eComprehensive explorations of administrative and new data sources and technologies, covering big (organic) data sources and methods for data integration, linking, machine learning and visualization.\u003c\/li\u003e \u003cli\u003eDetailed compilations of statistical programs’ responses to wide-ranging data collection and production challenges, among others caused by the Covid-19 pandemic.\u003c\/li\u003e \u003cli\u003eIn-depth examinations of business survey questionnaire design, computerization, pretesting methods, experimentation, and paradata.\u003c\/li\u003e \u003cli\u003eMethodical presentations of conventional and emerging procedures in survey statistics techniques for establishment statistics, encompassing probability sampling designs and sample coordination, non-probability sampling, missing data treatments, small area estimation and Bayesian methods.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eProviding a broad overview of most up-to-date science, this book challenges the status quo and prepares researchers for current and future challenges in establishment statistics and methods. Perfect for survey researchers, government statisticians, National Bank employees, economists, and undergraduate and graduate students in survey research and economics, \u003ci\u003eAdvances in Business Statistics, Methods and Data Collection \u003c\/i\u003ewill also earn a place in the toolkit of researchers working –with data– in industries across a variety of fields.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988673020133,"sku":"NP9781119672302","price":130.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119672302.jpg?v=1761781210","url":"https:\/\/k12savings.com\/products\/advances-in-business-statistics-methods-and-data-collection-isbn-9781119672302","provider":"K12savings","version":"1.0","type":"link"}