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Inflation dynamics are often described by some form of the Phillips curve. Named after A. W. Phillips, the British economist whose study of U.K. wage and unemployment data laid the groundwork, the Phillips curve denotes an inverse relationship between inflation and some measure of economic slack. A much-discussed issue in the literature is how forward-looking this relationship is. In this post, we address this question using a flexible version of the New KeynesianPhillips curve (NKPC) to illustrate the key role that expectations play in inflation dynamics.
Joseph Tracy, Robert Rich, Samuel Kapon, and Ellen Fu
Indicators of labor market slack enable economists to judge pressures on wages and prices. Direct measures of slack, however, are not available and must be constructed. Here, we build on our previous work using the employment-to-population (E/P) ratio and develop an updated measure of labor market slack based on the behavior of labor compensation. Our measure indicates that roughly 90 percent of the labor gap that opened up following the recession has been closed.
inflation as dependent on inflation expectations and the level of economic slack, with changes in expectations or slack leading to changes in the inflation rate. The global slowdown and the subsequent sovereign debt crisis caused the greatest divergence in unemployment rates among euro area member countries since the monetary union was founded in 1999. The pronounced differences in economic performances of euro area countries since 2008 should have led to significant differences in price behavior. That turned out to be the case, with a strong correlation evident between disinflation and labor market deterioration in euro area countries.
M. Henry Linder, Richard Peach, and Robert W. Rich
Among the measures of core inflation used to monitor the inflation outlook, the series excluding food and energy prices is probably the best known and most closely followed by policymakers and the public. While the conventional “ex food and energy” measure is a composite of the price changes of a large number of different products and services, almost all models developed to explain and forecast its behavior do not distinguish between the goods and services categories. Is the distinction important? Here, we highlight the different behavior and determinants of goods inflation and services inflation and suggest, based on preliminary analysis, that we can improve the forecast accuracy of this conventional core inflation measure by combining separate inflation forecasts of the two categories.
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