More on the Phillips curve

An Inverted-L Phillips curve

Why did policymakers assume that the 2020 surge in inflation was temporary? Because they assumed that the Phillips curve was flat, argue Benigno and Eggertsson. This was an erroneous assumption as policymakers failed to appreciate the impact of the unprecedented labor shortage caused by COVID-19, the type of shortage historically occurring only during wartime.
In this paper, Benigno and Eggertsson develop a New Keynesian model with search and matching frictions, complemented by a form of wage rigidity that generates strong nonlinearities. In this model, economic slack is measured as firms’ job vacancies over the number of unemployed workers. In the last 63 years, situations of labor shortage have emerged on two occasions: during the Vietnam War in the late 1960s a period also marked by a substantial demand stimulus, and the period around the COVID-19 epidemic (see figure below). They find that, labor shortages are associated with surges in inflation. As a result, the nonlinearities arise due to an imperfect labor market. The proposed New Keynesian Phillips curve is an Inverted L-curve that can explain the sharp, unexpected rise in inflation in the U.S. in the early 2020s following the COVID-19 pandemic. This new nonlinear Phillips curve implies:

• Demand shocks played a greater role than supply shocks in explaining the surge.
• Appropriate monetary policy can engineer a “soft landing” because inflation can be brought down quickly through a relatively small sacrifice in output.

It’s Baaack: The Surge in Inflation in the 2020s and the Return of the Non-Linear Phillips Curve
Authors: Pierpaolo Benigno, Gauti B. Eggertsson
From: University of Bern, Brown University

Breaks in the Phillips curve

In this paper, Smith et al. apply Bayesian panel methods with breakpoints to disaggregate data in order to study Phillips curve inflation dynamics. There are two reasons for which they look at disaggregate data, whether by industry, by region, or by country: a) there may be some cross-sectional heterogeneity which might shed light on the causes of changing Phillips curves; and b) since different regions and sectors experience different business cycles, there is extra information in disaggregate data that enables the identification of slope coefficients and regime changes more precisely than using aggregate data alone. The authors use U.S. industry data covering the sample 1959Q1-2022Q3.
For the U.S. they find a kink in the Phillips curve at a threshold of unemployment rates of 5 and 4.2 percent. Using these thresholds, they find that the Phillips curve is steeper in a tight labor market  and that “ignoring breaks has the effect of leading to underestimation of the additional steepness in tight labor markets in the most recent period.”
Breaks in the Phillips Curve: Evidence from Panel Data
Authors: Simon C. Smith, Allan Timmermann, Jonathan Wright
From: Federal Reserve Board