Temporal instability of the unemployment-inflation relationship

Econometric modeling of the relationship between inflation and unemployment has been a central topic in macroeconomics since the investigation of Phillips (1958), who documented a negative correlation between these variables in a half-century of U.K. data. Since the simultaneous occurrence of high inflation and high unemployment in the United States and other countries during the 1970s, there has been general agreement that this econometric relationship is unstable. Indeed, the instability has been so great that Lucas and Sargent characterized it as "econometric failure on a grand scale. "(1) This article summarizes some results from our recent work that documents various dimensions of this instability. (2) We display econometric instability in three alternative and complementary ways. First we look at the simple correlation coefficient linking the unemployment rate and inflation, which initially attracted the attention of Phillips (1958) in U.K. data and Samuelson and Solow (1960) in U.S. data. We show that this correlation has changed in an important way since World War II, so that over the entire 1954-94 period the correlation is essentially zero. However, we also show that this largely reflects the changing trend behavior of the two series: When we eliminate trends and high-frequency components of inflation and unemployment so as to focus on the business cycle behavior of the two series, we find that there has been a remarkably stable negative correlation. This combined pattern of stability and instability suggests the value of investigating the stability and performance of inflation and unemployment forecasting rules over various sample periods and horizons. Accordingly, our second approach is to investigate instability in the parameters of a reduced-form bivariate forecasting model--a vector autoregression (VAR)--for the two series. We document instability in the parameters of the forecasting model, particularly for the coefficients in the inflation equation. However, a closer examination suggests that this statistically significant time variation in parameters has a relatively small effect on the accuracy of forecasts. (3) The inflation-unemployment relationship in major macroeconometric models is governed in large part by the econometrics of the "price equation" or "wage-price block," which specifies that the inflation rate is a negative function of the level of unemployment. Typically, these specifications imply that there is a rate of unemployment at which inflation is stable--a nonaccelerating inflation rate of unemployment (NAIRU), or "natural" rate of unemployment. (4) One potential source of instability in the observed unemployment-inflation relationship in major econometric models is time variation in the NAIRU; our third approach is to study the extent of this form of instability in a conventional price equation. We find that while there may be time variation in the NAIRU, it is very hard to estimate precisely the extent of this time variation and the level of the NAIRU at any point in time. For example, in the econometric model with the most precise NAIRU estimate, the 95 percent confidence interval for the current value of the NAIRU ranges from 4.9 to 7.6 percentage points. (5) Instability in the correlation between the unemployment rate and inflation Figure 1 plots the unemployment and inflation data used in this paper over the 1954-94 period. (6) The characteristics of the data evident in the figure suggest that a single correlation coefficient will do a poor job summarizing the relation between the two series. For example, both inflation and the unemployment rate are lower in the first half of the sample than in the second half. This suggests a positive correlation between the series. On the other hand, during business cycle recessions (shown as shaded areas in the figure), inflation tends to fall and unemployment increases; the opposite occurs during business cycle expansions. …