This textbook integrates mathematical index theory and its application in official price statistics. It tries to bridge theory and practice, due to the apparent divergence between mathematicians with ever more sophisticated and complex models and practitioners with problems that are more and more difficult to understand without broad knowledge and some experience. The text offers an introduction into axiomatic, microeconomic and stochastic reasoning as regards index numbers, with moderately difficult mathematics. It also summarizes many ongoing discussions concerning methodological merits and demerits of specific indices, such as consumer price-, producer price-, unit value- and chain indices, in official price statistics. The book is comprehensive and presents a readable overview of a great number of topics in modern price index theory and their application in inflation measurement, deflation of aggregates in National Accounts, sampling and quality adjustment in price collection and other important though controversial issues.
This book is the first comprehensive text on index number theory since Irving Fisher's 1922 The Making of Index Numbers. The book covers intertemporal and interspatial comparisons; ratio- and difference-type measures; discrete and continuous time environments; and upper- and lower-level indices. Guided by economic insights, this book develops the instrumental or axiomatic approach.
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.
A joint production by six international organizations, this manual explores the conceptual and theoretical issues that national statistical offices should consider in the daily compilation of export and import price indices. Intended for use by both ...
'An authoritative survey with exciting new insights of special interest to economists and econometricians who analyse intertemporal and interspatial price relationships.' - Professor Angus Maddison, Groningen University This book presents a comprehensive review of recent developments in the theory and construction of index numbers using the stochastic approach, demonstrating the versatility of this approach in handling various index number problems within a single conceptual framework. It also contains a brief, but complete, review of the existing approaches to index numbers with illustrative numerical examples. The stochastic approach considers the index number problem as a signal extraction problem. The strength and reliability of the signal extracted from price and quantity changes for different commodities depends upon the messages received and the information content of the messages. The most important applications of the new approach are to be found in the context of measuring rate of inflation; fixed and chain base index numbers for temporal comparisons and for spatial intercountry comparisons; the latter generally require special index number formulae that result in transitive and base invariant comparisons.
This book answers the question of how exactly property price indexes should be constructed. The formation and collapse of property bubbles has had a profound impact on the economic administration of many nations. The property price bubble that began around the mid-1980s in Japan has been called the 20th century's biggest bubble. In its aftermath, the country faced a period of long-term economic stagnation dubbed the "lost decade." Sweden and the United States have also faced collapses of property bubbles in the 20th and early 21st centuries, respectively. It has been pointed out that the "information gap" that existed between policy-making authorities and the property (including housing) and financial markets was a problem. In 2009, the IMF proposed the creation of a housing price index to the G20 in order to fill this information gap, and the proposal was adopted. Furthermore, in 2011, it was suggested that the next economic crisis would be caused by a bubble in commercial property prices, and it was decided to create a commercial property index as well. This book provides practical examples of how the theory of property price indexes can be applied to the issues of property as a non-homogenous good and a technological and environmental change.
There is no book currently available that gives a comprehensive treatment of the design, construction, and use of index numbers. However, there is a pressing need for one in view of the increasing and more sophisticated employment of index numbers in the whole range of applied economics and specifically in discussions of macroeconomic policy. In this book, R. G. D. Allen meets this need in simple and consistent terms and with comprehensive coverage. The text begins with an elementary survey of the index-number problem before turning to more detailed treatments of the theory and practice of index numbers. The binary case in which one time period is compared with another is first developed and illustrated with numerous examples. This is to prepare the ground for the central part of the text on runs of index numbers. Particular attention is paid both to fixed-weighted and to chain forms as used in a wide range of published index numbers taken mainly from British official sources. This work deals with some further problems in the construction of index numbers, problems which are both troublesome and largely unresolved. These include the use of sampling techniques in index-number design and the theoretical and practical treatment of quality changes. It is also devoted to a number of detailed and specific applications of index-number techniques to problems ranging from national-income accounting, through the measurement of inequality of incomes and international comparisons of real incomes, to the use of index numbers of stock-market prices. Aimed primarily at students of economics, whatever their age and range of interests, this work will also be of use to those who handle index numbers professionally.
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.
