Are preliminary announcements of the money stock rational forecasts

This paper focuses on the role of sweep programs in properly measuring money. We propose new monetary aggregates that adjust the conventional measures to account for the medium of exchange capability of funds in sweep programs. Using data on swept funds in retail and commercial demand deposit (DD) sweep programs, we provide time series of monthly data on the sweep-adjusted money measures. By the twenty-first century, DD sweeps have led to distortion in reported MZM of approximately 3 percent, 5 percent for M2, and 6 percent for M2M. Underreporting of M1 due to retail and DD sweep programs is almost 70 percent.

/pdf/redefining-the-monetary-aggregates-a-clean-sweep-1k6a2n5n7k.pdf

Redefining the monetary aggregates: a clean sweep

DIFFICULTIES IN MEETING its monetary targets led the Federal Reserve in October 1979 to adopt a new operating procedure to achieve firmer control over monetary aggregates. Yet the inflationary environment has fostered financial developments that affect the behavior of the traditional monetary aggregates and that raise questions whether different aggregates may not be better. This paper compares the various monetary aggregates for their usefulness as guides for monetary policy in the light of recent financial developments. The criterion of usefulness is the ability to influence and predict GNP growth. This ability is tested in two ways, first by the stability of the velocities of the monetary aggregates, and second by the advance information they provide of GNP growth. It is presumed that the aggregates with the most stable velocities make the best targets for monetray policy, and that those containing the most advance information make the best guides for policy. The paper has three main sections. The first discusses the criteria for using monetary aggregates as targets and guides. The second two sections describe and report tests of the various monetary aggregates as targets and guides. A summary of findings is presented as a final section.

The Choice Among Monetary Aggregates as Targets and Guides for Monetary Policy

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation.

/pdf/does-money-matter-in-inflation-forecasting-24lzlnq0bd.pdf

Does money matter in inflation forecasting

In the early 1990s, M2 growth has been weaker than estimated while bond mutual funds have grown rapidly. This study assesses whether adding bond funds to M2 would yield a monetary aggregate that is more explainable using a standard error correction model of money with and without modifications for bond interest rate and thrift resolution effects. Results indicate that it is important to net out institutional and IRA/Keogh assets from bond funds (as is done for M2) and that adding such a bond fund series to M2 results in an aggregate that is somewhat more explainable than M2.

Should bond funds be added to M2

The redefined monetary aggregates

Developments in the U.S. financial system since the mid-1970s

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The redefined monetary aggregates

Developments in the U.S. financial system since the mid-1970s