Financial Market Variables do not Predict Real Activity: Further Evidence

CHRISTIAN E. WEBER (*) Previous studies argue that financial variables do not help forecast U.S. output growth. F statistics for excluding financial variables from output growth equations depend on the sample period and the inclusion of 1974:12 in the sample. Also, an autoregressive model of output growth often provides better forecasts than models with lagged financial variables included. I decompose output into permanent and cyclical components and ask whether financial variables help forecast either component in isolation. The paper-bill spread does improve in-sample forecasts of cyclical output, but no financial variable helps forecast either cyclical output or permanent output growth out of sample. (JEL E52, C22, C53) I. INTRODUCTION The last decade has witnessed a dramatic increase in efforts to determine the link between monetary aggregates and interest rate variables and real economic activity. Although Friedman and Schwartz (1963) and Sims (1972) argued that movements in monetary aggregates have historically been followed by movements in output in the same direction, it was only in the mid-1980s that empirical research on the link between financial variables and real economic activity accelerated. Beginning with Sims (1980), one of the key stylized facts that emerged from this research is that although monetary aggregates appear not to help forecast output, various interest rate variables do. Hafer and Kutan (1997) and Thoma and Gray (1998) summarize recent work in this area. Recently, however, Thoma and Gray (1998) (henceforth T-G) have questioned this stylized fact. Using rolling regressions, they show that F statistics for excluding lags of M2 or the paper-bill spread or the federal funds rate from an autoregressive (AR) model of growth in industrial production are frequently insignificant for sample periods truncated prior to the mid-1970s. Also, excluding December 1974 from longer samples generally renders lags of these financial variables jointly insignificant and eliminates the apparent superiority of the spread as a forecaster of output growth. Finally, for most sample periods, a simple AR model of growth in industrial production outperforms vector autoregressive (VAR) models, which include M2 growth, the spread, or the Fed funds rate in the sense that the AR model generally yields lower root mean squared forecast errors than the VAR models. As T-G note, their findings imply that financial variables do not help forecast output growth. Either monetary policy is neutral or e conomists have yet to identify the variable(s) whose fluctuations represent changes in monetary policy. Like most other researchers, T-G specify their empirical models in first differences of all integrated (unit root) series. While this approach is standard, I have argued in Weber (1999) that separate empirical models for the stationary component of output in levels and the first difference of the permanent component of output provide more and better information than a single model of observed output growth. First, tests for excluding financial variables from output growth equations are in fact tests for excluding these variables from models for growth in the permanent component of output. They have nothing to do with the cyclical influence of financial variables. Second, due to two sets of possibly invalid restrictions that they place on the separate processes for permanent and temporary output, tests for excluding financial variables from traditional money-output autoregressions are based on potentially biased estimators. The appendix provides a formal statement and proof of these assertions based on a propo sition in Weber (1999). Thus, recent evidence that money growth does not help forecast output growth may reflect biased estimates of the distributed lag coefficients rather than an actual failure of money growth to help forecast output growth. These observations argue strongly for causality tests based directly on separate autoregressive-distributed lag (ARDL) models for permanent output growth and the cyclical component of output. …