Academic journal article Federal Reserve Bank of St. Louis Review

A Measure of Price Pressures

Academic journal article Federal Reserve Bank of St. Louis Review

A Measure of Price Pressures

Article excerpt

The Federal Reserve, like most central banks, devotes considerable economic resources to monitoring and analyzing large volumes of economic data. This effort, often termed "current analysis" by insiders, feeds directly into another, crucial aspect of central banking: forecasting key economic series such as real gross domestic product (GDP) growth, inflation, and employment. Forecasting the paths of key economic variables is an effort that flows directly from the Fed's congressionally mandated responsibility to (i) provide sufficient liquidity to achieve and maintain low inflation rates and (ii) promote maximum sustainable economic growth. This responsibility, which stems from the Federal Reserve Act and subsequent amendments, is often termed the Fed's dual mandate. Since the passage of the DoddFrank Wall Street Reform and Consumer Protection Act, the Fed has been handed a third monetary policy responsibility: financial stability.

In this analysis, we focus on the Fed's price stability mandate--specifically, in the context of forecasting inflation. Given its importance, Federal Reserve officials have historically been reluctant to attach an explicit definition of price stability--a rather ambiguous term that can mean different things to different people. That reluctance changed in January 2012, when the Federal Reserve defined price stability as a numerical inflation target--2 percent--over the medium term (Board of Governors of the Federal Reserve System, 2013):

   The Federal Open Market Committee (FOMC) judges that inflation at
   the rate of 2 percent (as measured by the annual change in the
   price index for personal consumption expenditures, or PCE) is most
   consistent over the longer run with the Federal Reserve's mandate
   for price stability and maximum employment. Over time, a higher
   inflation rate would reduce the public's ability to make accurate
   longer-term economic and financial decisions. On the other hand, a
   lower inflation rate would be associated with an elevated
   probability of falling into deflation, which means prices and
   perhaps wages, on average, are falling-a phenomenon associated with
   very weak economic conditions. Having at least a small level of
   inflation makes it less likely that the economy will experience
   harmful deflation if economic conditions weaken. The FOMC
   implements monetary policy to help maintain an inflation rate of 2
   percent over the medium term.

The Fed's inflation-targeting regime, which is similar to those of many other major central banks, thus requires the FOMC to forecast future inflation ("inflation over the medium term"). But in a large structural model such as the Board of Governors FRB/US model, the inflation process is modeled largely on the New Keynesian Phillips curve (NKPC) framework. In the NKPC model, current inflation depends on both current economic conditions--typically measured as the deviation between actual output and potential output or, equivalently, between the current unemployment rate and the natural rate of unemployment--and agents' expectations of future inflation. (1) Previous shocks matter only to the extent that they influence current conditions or expectations of future inflation. The NKPC model thus marries the Keynesian view that there is a short-run trade-off between real output (or unemployment) and inflation (by means of some "sticky price" mechanism) and the neoclassical view that, in the long run, excess money growth only leads to higher inflation (money neutrality).

We take a different approach in our analysis. First, our framework uses a pure time-series model to forecast inflation. Simple time-series models have been shown to be as accurate as larger, more complex structural models--and the resource demands on the forecaster are significantly smaller. (2) Our model is a Bayesian vector autoregressive (VAR) model augmented with a set of factors that summarize disaggregated price, employment, and interest rate data. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.