000			04712cam a2200517Mu 4500
001			on1290485460
003			OCoLC
005			20230817090252.0
006			m d
007			cr cnu---unuuu
008			220101s2022 ilu o ||| 0 eng d
040			_aEBLCP _beng _cEBLCP _dOCLCO _dDEGRU _dOCLCO _dN$T
019			_a1290021510
020			_a022680139X
020			_a9780226801391 _q(electronic bk.)
035			_a3104441 _b(N$T)
035			_a(OCoLC)1290485460 _z(OCoLC)1290021510
050		4	_aHB143
082	0	4	_a330.072/7
049			_aMAIN
100	1		_aAbraham, Katharine G.
245	1	0	_aBig Data for Twenty-First-Century Economic Statistics _h[electronic resource].
260			_aChicago : _bUniversity of Chicago Press, _c2022.
300			_a1 online resource (502 p.).
490	1		_aNational Bureau of Economic Research Studies in Income and Wealth ; _vv.79
500			_aDescription based upon print version of record.
505	0	0	_tFrontmatter -- _tContents -- _tPrefatory Note -- _tIntroduction: Big Data for Twenty- First- Century Economic Statistics: The Future Is Now -- _tI. Toward Comprehensive Use of Big Data in Economic Statistics -- _t1. Reengineering Key National Economic Indicators -- _t2. Big Data in the US Consumer Price Index -- _t3. Improving Retail Trade Data Products Using Alternative Data Sources -- _t4. From Transaction Data to Economic Statistics -- _t5. Improving the Accuracy of Economic Measurement with Multiple Data Sources -- _tII. Uses of Big Data for Classification -- _t6. Transforming Naturally Occurring Text Data into Economic Statistics -- _t7. Automating Response Evaluation for Franchising Questions on the 2017 Economic Census -- _t8. Using Public Data to Generate Industrial Classification Codes -- _tIII. Uses of Big Data for Sectoral Measurement -- _t9. Nowcasting the Local Economy -- _t10. Unit Values for Import and Export Price Indexes -- _t11. Quantifying Productivity Growth in the Delivery of Important Episodes of Care within the Medicare Program Using Insurance Claims and Administrative Data -- _t12. Valuing Housing Services in the Era of Big Data -- _tIV. Methodological Challenges and Advances -- _t13. Off to the Races -- _t14. A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data -- _t15. Estimating the Benefits of New Products -- _tContributors -- _tAuthor Index -- _tSubject Index
520			_aThe papers in this volume analyze the deployment of Big Data to solve both existing and novel challenges in economic measurement. The existing infrastructure for the production of key economic statistics relies heavily on data collected through sample surveys and periodic censuses, together with administrative records generated in connection with tax administration. The increasing difficulty of obtaining survey and census responses threatens the viability of existing data collection approaches. The growing availability of new sources of Big Data--such as scanner data on purchases, credit card transaction records, payroll information, and prices of various goods scraped from the websites of online sellers--has changed the data landscape. These new sources of data hold the promise of allowing the statistical agencies to produce more accurate, more disaggregated, and more timely economic data to meet the needs of policymakers and other data users. This volume documents progress made toward that goal and the challenges to be overcome to realize the full potential of Big Data in the production of economic statistics. It describes the deployment of Big Data to solve both existing and novel challenges in economic measurement, and it will be of interest to statistical agency staff, academic researchers, and serious users of economic statistics.
590			_aAdded to collection customer.56279.3
650		0	_aBig data.
650		0	_aEconomics _xStatistical methods _xData processing.
650		6	_aDonn�ees volumineuses.
650		6	_a�Economie politique _xM�ethodes statistiques _xInformatique.
650		7	_aBUSINESS & ECONOMICS / General. _2bisacsh
655		4	_aElectronic books.
700	1		_aJarmin, Ron S.
700	1		_aMoyer, Brian C.
700	1		_aShapiro, Matthew D.
776	0	8	_iPrint version: _aAbraham, Katharine G. _tBig Data for Twenty-First-Century Economic Statistics _dChicago : University of Chicago Press,c2022 _z9780226801254
830		0	_aStudies in income and wealth.
856	4	0	_3EBSCOhost _uhttps://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3104441
938			_aDe Gruyter _bDEGR _n9780226801391
938			_aProQuest Ebook Central _bEBLB _nEBL6827947
938			_aEBSCOhost _bEBSC _n3104441
994			_a92 _bN$T
999			_c256437 _d256437