Matthew D. Shapiro – författare
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4 produkter
4 produkter
Inbunden, Engelska, 2002
827 kr
Skickas inom 5-8 vardagar
The data from bar-code scanners offers 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 sample. But scanner data also presents a number of difficulties for current statistical systems. This book 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 US, UK and Canada, including a project to incorporate scanner data into the monthly Consumer Price Index. Other papers demonstrate the potential of using scanner data to test economic theories.
E-bok
PDF, Engelska, 20071 875 kr
Läs direkt efter köp
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.
Inbunden, Engelska, 2022
1 201 kr
Skickas inom 5-8 vardagar
The 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.
E-bok
Engelska, 20222 652 kr
Läs direkt efter köp
The 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.