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This work on index-number construction focuses on production indexes, including output and input deflators that can be used for constructing real output and real input. The authors treat separately the different production units: the firm, the industry, and the economy, as well as the different forms of industrial organization: monopoly, monopsony, and competition. Only in the simplest cases is the appropriate theory isomorphic to that of the cost-of-living index because of the interlinkages among the various production units. A firm cannot always assume that the behaviour of its competitors, suppliers, and customers will be unaffected by price changes and only in special cases can an industry take supply and demand conditions as given.
Although inflation is much feared for its negative effects on the economy, how to measure it is a matter of considerable debate that has important implications for interest rates, monetary supply, and investment and spending decisions. Underlying many of these issues is the concept of the Cost-of-Living Index (COLI) and its controversial role as the methodological foundation for the Consumer Price Index (CPI). Price Index Concepts and Measurements brings together leading experts to address the many questions involved in conceptualizing and measuring inflation. They evaluate the accuracy of COLI, a Cost-of-Goods Index, and a variety of other methodological frameworks as the bases for consumer price construction.
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.
With the United States and other developed nations spending as much as 14 percent of their GDP on medical care, economists and policy analysts are asking what these countries are getting in return. Yet it remains frustrating and difficult to measure the productivity of the medical care service industries. This volume takes aim at that problem, while taking stock of where we are in our attempts to solve it.
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.
It has become trite to observe that increases in health care costs have become unsustainable. How best for policy to address these increases, however, depends in part on the degree to which they represent increases in the real quantity of medical services as opposed to increased unit prices of existing services. And an even more fundamental question is the degree to which the increased spending actually has purchased improved health. Accounting for Health and Health Care addresses both these issues. The government agencies responsible for measuring unit prices for medical services have taken steps in recent years that have greatly improved the accuracy of those measures. Nonetheless, this book has several recommendations aimed at further improving the price indices.
Controlling inflation is among the most important objectives of economic policy. By maintaining price stability, policy makers are able to reduce uncertainty, improve price-monitoring mechanisms, and facilitate more efficient planning and allocation of resources, thereby raising productivity. This volume focuses on understanding the causes of the Great Inflation of the 1970s and ’80s, which saw rising inflation in many nations, and which propelled interest rates across the developing world into the double digits. In the decades since, the immediate cause of the period’s rise in inflation has been the subject of considerable debate. Among the areas of contention are the role of monetary policy in driving inflation and the implications this had both for policy design and for evaluating the performance of those who set the policy. Here, contributors map monetary policy from the 1960s to the present, shedding light on the ways in which the lessons of the Great Inflation were absorbed and applied to today’s global and increasingly complex economic environment.
Existing economic indicators and indexes assess economic activity but no single indicator measures the general macro-economic performance of a nation, state, or region in a methodologically simple and intuitive way. This paper proposes a simple, yet informative metric called the Economic Performance Index (EPI). The EPI represents a step toward clarity, by combining data on inflation, unemployment, government deficit, and GDP growth into a single indicator. In contrast to other indexes, the EPI does not use complicated mathematical procedures but was designed for simplicity, making it easier for professionals and laypeople alike to understand and apply to the economy. To maximize ease of understanding, we adopt a descriptive grading system. In addition to a Raw EPI that gives equal weights to its components, we construct a Weighted EPI and show that both indexes perform similarly for U.S. data. To demonstrate the validity of the EPI, we conduct a review of U.S. history from 1790 to 2012. We show that the EPI reflects the major events in U.S. history, including wars, periods of economic prosperity and booms, along with economic depressions, recessions, and even panics. Furthermore, the EPI not only captures official recessions over the past century but also allows for measuring and comparing their relative severity. Even though the EPI is simple by its construction, we show that its dynamics are similar to those of the Chicago Fed National Activity Index (CFNAI) and The Conference Board Coincident Economic Index® (CEI).
Basic notions of cost-benefit analysis; Derivation of shadow prices; Estimation of shadow prices; Technical derivation of shadow prices.