· 2011
A leading economist contends that the recent financial crisis was caused not by the failure of mainstream economics but by corrupted monetary data constructed without reference to economics. Blame for the recent financial crisis and subsequent recession has commonly been assigned to everyone from Wall Street firms to individual homeowners. It has been widely argued that the crisis and recession were caused by “greed” and the failure of mainstream economics. In Getting It Wrong, leading economist William Barnett argues instead that there was too little use of the relevant economics, especially from the literature on economic measurement. Barnett contends that as financial instruments became more complex, the simple-sum monetary aggregation formulas used by central banks, including the U.S. Federal Reserve, became obsolete. Instead, a major increase in public availability of best-practice data was needed. Households, firms, and governments, lacking the requisite information, incorrectly assessed systemic risk and significantly increased their leverage and risk-taking activities. Better financial data, Barnett argues, could have signaled the misperceptions and prevented the erroneous systemic-risk assessments. When extensive, best-practice information is not available from the central bank, increased regulation can constrain the adverse consequences of ill-informed decisions. Instead, there was deregulation. The result, Barnett argues, was a worst-case toxic mix: increasing complexity of financial instruments, inadequate and poor-quality data, and declining regulation. Following his accessible narrative of the deep causes of the crisis and the long history of private and public errors, Barnett provides technical appendixes, containing the mathematical analysis supporting his arguments.
The book surveys modern literature on financial aggregation and index number theory, with special emphasis on the contributions of the book's two coauthors. In addition to an introduction and a systematic survey chapter unifying the rest of the book, this publication contains reprints of six published articles central to the survey chapter. Financial Aggregation and Index Number Theory provides a reference work for financial data researchers and users of central bank data, placing emphasis on possible improvements in such data from use of the microeconomic index number and aggregation theory.
In response to the recent financial crisis, many countries have initiated monetary stimulus packages. Maintaining proper measures of monetary aggregates is of particular importance for such economic policies. However, many central banks worldwide use the simple-sum monetary indexes, which ignore the liquidity characteristics of financial assets. Using the simple-sum indexes can produce misleading information, especially for broad monetary aggregates within which financial assets are not likely to be perfect substitutes. This book focuses on alternative economic stability indicators, and outlines the methods for constructing proper monetary and financial indicators – known as Divisia indexes. The Divisia monetary indexes are designed to measure accurately the liquidity in the economy by assigning different weights to different financial assets according to their usefulness in transactions. This book is highly relevant to economists interested in monetary policy and the construction of core inflation indicators and proper monetary indexes, in accordance with aggregation and index number theory. This book is the first to publish Divisia-based money supply indexes and core inflation indicators for the Gulf Cooperation Council (GCC) countries and for the Gulf Monetary Union. Researchers who use the financial data published by GCC central banks can use our indexes and findings to examine the interactions among the relevant macro-economic variables.
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· 2009
The position taken by William Barnett in this panel discussion is that federal government agencies, including the Bureau of Labor Statistics, view researchers as being among those who comprise the audience for produced data, but not necessarily the most important members of that audience.Recently, political pressures from Congress have been at center stage. Barnett takes the position that more focus on the data needs of economic researchers and econometricians would result in substantial gains in data quality and sample size available to economists. As an example to illustrate his point, he displays the results possible by linking Commerce Department data with the early NBER data of Simon Kuznets to produce a data base covering a much longer period of time than is included in the official Commerce Department data alone. The panel discussion that follows Barnett's taped comments emphasizes the concerns of the Commission that recently announced its recommendations regarding revision of the CPI.
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