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Mehra, Yash P.. "Predicting the recent behavior of inflation using output gap-based Phillips curves.(productivity growth influences inflation)." Economic Quarterly. Federal Reserve Bank of Richmond. 2004. HighBeam Research. 22 Apr. 2018 <https://www.highbeam.com>.
Mehra, Yash P.. "Predicting the recent behavior of inflation using output gap-based Phillips curves.(productivity growth influences inflation)." Economic Quarterly. 2004. HighBeam Research. (April 22, 2018). https://www.highbeam.com/doc/1G1-122662437.html
Mehra, Yash P.. "Predicting the recent behavior of inflation using output gap-based Phillips curves.(productivity growth influences inflation)." Economic Quarterly. Federal Reserve Bank of Richmond. 2004. Retrieved April 22, 2018 from HighBeam Research: https://www.highbeam.com/doc/1G1-122662437.html
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Many analysts believe that strong productivity growth has played an important role in the favorable inflation performance of the U.S. economy since the mid-1990s. Inflation, as measured by the behavior of the GDP deflator, hovered mostly near a low of 2 percent in the second half of the 1990s and has decelerated further during the past three years. Some policymakers think that, as a result of the continuing strong productivity and weak labor market, inflation may remain low throughout 2004, despite the continued strong pickup in economic activity. (1)
The traditional output gap-based Phillips curve relates current inflation to lagged inflation, supply shocks, and a measure of excess demand such as the level of the output gap. This Phillips curve is likely to overestimate inflation in the second half of the 1990s unless one revises upward estimates of real potential output made possible by the ongoing acceleration of productivity growth. However, in recent speeches, a few policymakers have highlighted two other potential anti-inflationary consequences of the recent surge in productivity. One is that the recent surge in productivity accompanied by weak labor markets has reduced unit labor costs, leading to possible downward pressures on inflation. (2) The other potential consequence stems from the ensuing behavior of aggregate demand. The strong productivity growth and the resulting surge of real potential output imply aggregate demand must grow fast enough to absorb higher potential output. Otherwise, disinflationary pressures may develop. (3)
In order to investigate the above-noted potential anti-inflationary consequences of acceleration of productivity, this article augments the traditional output gap-based Phillips curve to include two additional variables: the cyclical component of a markup variable defined as the markup of prices over unit labor costs and the change in the output gap. The markup allows for the short-term influence of a productivity-induced decline in unit labor costs on inflation, whereas the "rate of change" specification implies inflation depends also on how fast aggregate demand is growing relative to potential (called here the "demand growth gap"). I estimate the modified Phillips curve and examine whether it predicts the recent deceleration of inflation. (4) I also examine the robustness of the results of using wage share, rather than the markup, to capture the short-term influence of productivity-induced decline in unit labor costs on inflation. (5)
Some analysts have argued that Phillips curves are not useful for predicting inflation. In particular, Atkeson and Ohanian (2001) present evidence indicating that one-year-ahead inflation forecasts from several NAIRU (nonaccelerating-inflation rate of unemployment) Phillips curves are no more accurate than those from a naive model that predicts inflation next year will be the same as it had been over the past year. Sims (2002) points out that the results in Atkeson and Ohanian arise entirely from having the forecast evaluation period restricted to 1984-1999, a period when inflation was very stable. I examine the robustness of the results in Atkeson and Ohanian along another dimension. Their forecasting exercise predicts the one-year-ahead inflation rate conditional on just past values of a real activity variable and the inflation rate, thereby ignoring the potential contribution of the future values of real activity over the forecast horizon. (6) Their exercise may be a reasonable way to construct the forecast because, in real time, forecasters usually do not have information about the future values of the indicator variable. However, it is plausible that a forecast including this extra information may be more accurate than the one ignoring it. As a robustness check, I take the other extreme and generate one-year-ahead predictions of the inflation rate under the counter-factual assumption that the forecaster knows actual values of the indicator variable over the forecast horizon. I then investigate whether the Phillips curve still generates less accurate predictions of the inflation rate than does the naive model.
The empirical work presented here estimates the modified Phillips curve over two sample periods, 1961Q1 to 1995Q4 and 1961Q1 to 2003Q4, using the chain-weighted GDP deflator as the measure of inflation. (7) It suggests the following conclusions. First, the estimated coefficients that appear on the output gap and its rate of change are significant and correctly signed, suggesting there is a "rate of change effect." Inflation is predicted to rise when the output gap is positive and when aggregate demand increases faster than real potential output. Second, the markup, which is usually defined as the excess of the price level over unit labor costs, has a slow-moving trend and is not statistically significant when included in the estimated Phillips curve. However, the cyclical component of the markup when included in the Phillips curve is significant and appears with a negatively signed estimated coefficient, meaning inflation is predicted to fall if the cyclical markup is high. If the Phillips curve includes the wage share instead of the markup, the estimated coefficient on the wage share is positive, suggesting inflation is predicted to fall if the wage share declines.
Third, the predictions of the one-year-ahead inflation rate conditional on actual values of the explanatory variables suggested by traditional and modified Phillips curves track actual inflation well, outperforming those based on the naive model that predicts inflation using only its past values. (8) This result holds over 1980-2003 as well as over 1984-1999, a period when inflation was stable. The results also indicate demand growth and output gap variables help most in generating accurate predictions of the inflation rate. The markup (or the wage share) does not improve the predictive accuracy if it is included in the modified Phillips curve. Together these results suggest that Phillips curves are useful for predicting inflation.
Regarding sources of the recent deceleration of inflation, the correlations summarized in the estimated modified Phillips curve suggest one plausible explanation of the recent behavior of inflation. As noted at the outset, inflation, after hovering near a low of 2 percent in the second half of the 1990s, decelerated further during the past three years. In the second half of the 1990s, the demand growth gap stayed close to the 2 percent range, as aggregate demand grew just fast enough to absorb the productivity-induced increase in potential. However, during the period 2000-2002, aggregate demand did not grow fast enough to absorb higher potential output, creating a declining demand growth gap and negative output gap. The recent deceleration is well predicted by the behavior of a Phillips curve that includes these two gap variables. However, the contribution of the markup (or wage share) in improving the prediction of the inflation rate since the mid-1990s remains negligible, suggesting the markup is not providing information beyond that contained in the gap variables. These results suggest that the weak demand growth gap together with the resulting negative output gap trump the cyclical markup (or wage share) as the major source of the recent deceleration of inflation.
The plan of this article is as follows. Section 1 discusses two modifications to the conventional expectations-augmented Phillips curve. It also provides an overview of the data including graphs of key variables that enter the Phillips curve, the estimation procedure, and the empirical specifications estimated here. Section 2 presents the new empirical work, and Section 3 contains concluding observations.
1. MODEL AND THE METHOD
Traditional and Modified Phillips Curves
The traditional reduced-form Phillips curve relates current inflation to lagged inflation, supply shocks, and a measure of excess demand such as the level of output or unemployment gap. Following Gordon (1985, 1988) and Stockton and Glassman (1987), the traditional output gap-based Philips curve can be derived from the following reduced-form price and wage equations.
[DELTA][p.sub.t] = [h.sub.0] + [h.sub.1] [DELTA] (w - q)[.sub.t] + [h.sub.2][x.sub.t] + [h.sub.3]s[p.sub.t], (1.1)
[DELTA] (w - q)[.sub.t] = [k.sub.0] + [k.sub.1] [DELTA][p.sub.t.sup.e] + [k.sub.2][x.sub.t] + [k.sub.3]s[w.sub.t], and (1.2)
[DELTA][p.sub.t.sup.e] = g(L)[DELTA][p.sub.t], (1.3)
where all variables are in natural logarithms and where p is the price level; w is the nominal wage; q is labor productivity; x is a demand pressure variable; [p.sup.e] is the expected price level; sp represents supply shocks affecting the price equation; sw represents supply shocks affecting the wage equation; g(L) is a lag operator; and [DELTA] is the first difference operator. Equation (1.1) describes the price markup behavior: prices are marked over productivity-adjusted wage costs and are influenced by cyclical demand and the exogenous supply shocks. …
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