Gordon (1997) The Time-Varying NAIRU and Its Implications for Economic Policy

nairuphillips-curveinflationsupply-shocksmonetary-policystate-spacekalman-filtertime-varying-parametermacroeconomics

Summary

Gordon (1997) estimates a time-varying Non-Accelerating Inflation Rate of Unemployment (TV-NAIRU) within the "triangle model" of inflation using state-space maximum likelihood via the Kalman filter. The key innovation is a smoothness prior: ση=0.2\sigma_\eta = 0.2 is chosen to keep the NAIRU from zig-zagging implausibly quarter-to-quarter, on the economic ground that the no-supply-shock NAIRU reflects slowly-moving microeconomic market structure. Estimated U.S. NAIRU (GDP deflator): 6.0% (mid-1950s) → 5.3% (1962) → 6.2% plateau (1967–72) → 6.5% hump (1978–82) → 5.6% (mid-1996). The inflation-acceleration cost of a sustained 1-percentage-point unemployment gap is only 0.32% per year.

Key Claims

Concepts Introduced or Extended

Entities Mentioned

Quotes

"Staiger, Stock and Watson (1996, p. 2) have cast doubt on the enterprise of estimating the NAIRU, concluding that 'a typical 95% confidence interval for the NAIRU in 1990 is 5.1 percent to 7.7 percent. . . . This imprecision suggests caution in using the NAIRU to guide monetary policy.' . . . The recent suggestion . . . that the NAIRU for the year 1990 could range from 5.1 to 7.7 percent makes no economic sense." (pp. 21, 29)

"I propose using a 'smoothness' prior: the NAIRU can move around as much as it likes, subject to the qualification that sharp quarter-to-quarter zig-zags are ruled out." (p. 22)

My Take

The key methodological contribution is the smoothness-prior argument: when multiple NAIRU series are statistically indistinguishable, use an economic criterion (slow-moving market structure) to select among them. This is a principled alternative to SSW's statistical criterion (report a wide confidence interval) and predates later Bayesian approaches to the same problem. The Gordon-SSW debate is partly a debate about what the NAIRU concept is for: SSW treat it as a statistical object with well-characterised uncertainty; Gordon treats it as an economic concept with an implied smoothness that the data cannot separately identify. Both are legitimate. The triangle model's extraordinary out-of-sample performance (RMSE 0.7% over 9 years out-of-sample, smaller than in-sample SEE) is genuinely impressive and provides strong validation. The main caveat is that Gordon conditions on one "proper model" and ignores parameter uncertainty, which is precisely what SSW are measuring. The 1997 paper is the lean, policy-oriented companion to the more detailed Gordon (2005) structural decomposition.