Building New Monetary Services Indexes: Concepts, Data and Methods

This is the second of two articles that describe the monetary services index (MSI) project of the Federal Reserve Bank of St. Louis. The project’s MSI database, which contains the monetary services index (MSI), its dual user cost index, and other related indexes and data, is available on the Bank’s World Wide Web server.1 To facilitate comparison with the monetary aggregates published by the Board of Governors of the Federal Reserve System, all of the indexes in the MSI database are provided for the same groupings of monetary assets as the Board’s M1, M2, M3, and L aggregates.2 Indexes are provided at monthly, quarterly, and annual frequencies. The St. Louis MSI database also contains all non-confidential data and computer programs used to construct the indexes. Unlike the Board of Governor’s monetary aggregates, the monetary services indexes and their dual user cost indexes are statistical index numbers, based on economic aggregation and statistical index number theory. The previous article in this Review, “Monetary Aggregation Theory and Statistical Index Numbers,” surveys the literature on monetary aggregation theory and the use of statistical index number theory in monetary economics. Here, we discuss the construction of the monetary services index and related indexes. In the first section, we define notation and introduce some key concepts that are used throughout the article. We emphasize the distinction between real and nominal monetary asset stocks and their user costs, and we review the concepts of the real monetary services index and its nominal dual user cost index. In the second section, we define each of the indexes in the monetary services indexes database, including the following: total expenditure on monetary assets; the nominal monetary services index; the real dual user cost index; the currency equivalent index; the simple sum index; and a set of indexes based on Theil’s (1967) stochastic approach to index number theory. We emphasize that it is important to distinguish between real and nominal monetary index numbers: The aggregation theory underlying the monetary services indexes and related indexes is developed in terms of the real stocks of monetary assets, but actual monetary asset stock data are collected in nominal terms. We conclude that it is appropriate to construct a nominal monetary services index and thereafter to produce an approximation to the real monetary services index by deflating the nominal index. In the third section, we describe the monetary asset stock data. We discuss the issue of weak separability, and we define the groupings of monetary assets for which we construct indexes. These groupings correspond to the assets contained in M1, M2, M3, and L, as well as the assets contained in M1A and MZM.3 Because the aggregates are nested—each broader aggregate contains all the components of the previous, narrower aggregate—we refer to the groupings as levels of aggregation. M1A is the narrowest level of aggregation and L the broadest. In the fourth section, we discuss the own rate of return data used in the Richard G. Anderson is an assistant vice president at the Federal Reserve Bank of St. Louis. Barry E. Jones and Travis D. Nesmith are Ph.D. candidates at Washington University in St. Louis and visiting scholars at the Federal Reserve Bank of St. Louis. Mary C. Lohmann, Kelly M. Morris, and Cindy A. Gleit provided research assistance.