Measuring the Level and Uncertainty of Trend Inflation

Abstract

Firmly-anchored inflation expectations are widely viewed as playing a central role in the successful conduct of monetary policy. This paper presents estimates of trend inflation, based on information contained in survey expectations, the term structure of interest rates, and realized inflation rates. My application combines a variety of data sources at the monthly frequency and it can flexibly handle missing data arising from infrequent observations and limited data availability. In order to assess whether inflation expectations are anchored, uncertainty surrounding future changes in trend inflation -measured by a time-varying volatility of trend shocks -is estimated as well.Not surprisingly, the estimates suggest that trend inflation in the U.S. rose and fell again over the 1970s and 1980s, accompanied by increases in uncertainty. Considering the recent crisis, full-sample estimates of trend inflation fell quite a bit, but not too dramatically. In contrast, real-time estimates recorded sizeable increases of trend uncertainty during the crisis of 2007/2008, which have abated since then.JEL Classification: C53, E37, E47, E58

Measuring Price-Level Uncertainty and Instability in the U.S., 1850-2012

“…For instance, Cogley, et al (2010) investigate autocorrelation in the inflation gap, π t − µ t , and Cecchetti, et al (2007) model log-volatility innovations as a two-state Markov process, thus allowing jumps in r t and q t . Kozicki and Tinsley (2012) and Mertens (2011) introduce survey data on inflation forecasts to aid identification, 16 Mertens (2011) and Stella and Stock (2012) develop multivariate forecasting models by incorporating data on other macroeconomic outcomes such as unemployment and the term structure of interest rates, 17 and Chan, et al (2013) introduce a priori bounds on the random walk component µ t .…”

A Bayesian Evaluation of Alternative Models of Trend Inflation

“…Inflation less trend follows an autoregressive process in some of these studies (e.g., Cogley, Primiceri, and Sargent 2010) but not in others (Stock and Watson 2007). In addition, some research using random walk trends (Stock and Watson 2007, Mertens 2011, and Cogley, Primiceri, and Sargent 2010 has found that the variability of the trend component in inflation has varied over time.…”

“…2 A number of studies and still-used forecasting models measure inflation expectations, or in effect, trend inflation, with past inflation (e.g., Brayton, Roberts, and Williams 1999, Gordon 1998, and Macroeconomic Advisers 1997. 3 Another array of studies has modeled trend inflation as following a random walk (e.g., Cogley, Primiceri, and Sargent 2010, Cogley and Sbordone 2008, Ireland 2007, Kiley 2008, Kozicki and Tinsley 2006, Mertens 2011, Piger and Rasche 2008, and Stock and Watson 2007. Inflation less trend follows an autoregressive process in some of these studies (e.g., Cogley, Primiceri, and Sargent 2010) but not in others (Stock and Watson 2007).…”

Non-Linear Phillips Curves with Inflation Regime-Switching

“…2 Modern time series models of the inflation process now routinely embed time-varying volatility and persistence; examples include Stock and Watson (2007), Cogley, Primiceri and Sargent (2010), Mertens (2011), and Clark and Doh (2014). The Markov-switching approach of Nalewaik (2015) does as well, and results here show one advantage of that approach is that a rich set of control variables-labor-market slack, a non-linear function of labor-market slack, the real dollar exchange rate, and bank lending-can be included into the model easily without the imposition of strong prior assumptions.…”