Optimal Control of the Money Supply

Using optimal control theory and a vector autoregressive representation of the relationship between money and interest rates, one can derive a feedback control procedure which defines the best possible tradeoff between interest rate volatility and money supply fluctuations and which could be used to reduce both from their current levels.

Money, Real Interest Rates, and Output: A Reinterpretation of Postwar U.S. Data

This paper reexamines both monthly and quarterly U.S. postwar data to investigate if the observed comovements between money, real interestrates, prices and output are compatible with the money-real interest-output link suggested by existing monetary theories of output, which include both Keynesian and equilibrium models.The major empirical findings are these;1) In both monthly and quarterly data, we cannot reject the hypothesis that the ex ante real rate is exogenous, or Granger-causally prior in the context of a four-variable system which contains money, prices, nominal interest rates and industrial production.2) In quarterly data, there is significantly more information con-tained in either the levels of expected inflation or the innovationof this variable for predicting future output, given current and lagged output, than in any other variable examined (money, actualinflation, nominal interest rates, or ex ante real rates). The effect of an inflation innovation on future output is unambiguously negative. The first result casts strong doubt on the empirical importance of existing monetary theories of output, which imply that money should have a causal role on the ex ante real rates. The second result would appear incompatible with most demand driven models of output.In light of these results, we propose an alternative structural model which can account for the major dynamic interactions among the variables.This model has two central features: i) output is unaffected by money supply;and ii) the money supply process is motivated by short-run price stability.

Building a coherent risk measurement and capital optimisation model for financial firms

This paper was presented at the conference "Financial services at the crossroads: capital regulation in the twenty-first century" as part of session 5, "International capital allocation at financial institutions." The conference, held at the Federal Reserve Bank of New York on February 26-27, 1998, was designed to encourage a consensus between the public and private sectors on an agenda for capital regulation in the new century.Risk ; Econometric models ; Bank capital ; Financial institutions

Forecasting and Conditional Projection Using Realistic Prior Distributions

This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. The procedure is applied to ten macroeconomic variables and is shown to improve out-of-sample forecasts relative to univariate equations. Although cross-variables responses are damped by the prior, considerable interaction among the variables is shown to be captured by the estimates.We provide unconditional forecasts as of 1982:12 and 1983:3.We also describe how a model such as this can be used to make conditional projections and to analyze policy alternatives. As an example, we analyze a Congressional Budget Office forecast made in 1982:12.While no automatic causal interpretations arise from models like ours, they provide a detailed characterization of the dynamic statistical interdependence of a set of economic variables, which may help inevaluating causal hypotheses, without containing any such hypotheses themselves.