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Working Paper
Which Output Gap Estimates Are Stable in Real Time and Why?
Output gaps that are estimated in real time can differ substantially from those estimated after the fact. We aim to understand the real-time instability of output gap estimates by comparing a suite of reduced-form models. We propose a new statistical decomposition and find that including a Okun’s law relationship improves real-time stability by alleviating the end-point problem. Models that include the unemployment rate also produce output gaps with relevant economic content. However, we find that no model of the output gap is clearly superior to the others along each metric we consider.
Working Paper
GDP Trend-cycle Decompositions Using State-level Data
This paper develops a method for decomposing GDP into trend and cycle exploiting the cross-sectional variation of state-level real GDP and unemployment rate data. The model assumes that there are common output and unemployment rate trend and cycle components, and that each state?s output and unemployment rate are subject to idiosyncratic trend and cycle perturbations. The model is estimated with Bayesian methods using quarterly data from 2005:Q1 to 2016:Q1 for the 50 states and the District of Columbia. Results show that the U.S. output gap reached about -8% during the Great Recession and is ...
Working Paper
When Can Trend-Cycle Decompositions Be Trusted?
In this paper, we examine the results of GDP trend-cycle decompositions from the estimation of bivariate unobserved components models that allow for correlated trend and cycle innovations. Three competing variables are considered in the bivariate setup along with GDP: the unemployment rate, the inflation rate, and gross domestic income. We find that the unemployment rate is the best variable to accompany GDP in the bivariate setup to obtain accurate estimates of its trend-cycle correlation coefficient and the cycle. We show that the key feature of unemployment that allows for precise ...
Working Paper
An Output Gap Measure for the Euro Area : Exploiting Country-Level and Cross-Sectional Data Heterogeneity
This paper proposes a methodology to estimate the euro-area output gap by taking advantage of two types of data heterogeneity. On the one hand, the method uses information on real GDP, inflation, and the unemployment rate for each member state; on the other hand, it jointly considers this information for all the euro-area countries to extract an area-wide output gap measure. The setup is an unobserved components model that theorizes a common cycle across euro-area economies in addition to country-specific cyclical components. I estimate the model with Bayesian methods using data for the 19 ...
Working Paper
The roles of inflation expectations, core inflation, and slack in real-time inflation forecasting
Using state-space modeling, we extract information from surveys of long-term inflation expectations and multiple quarterly inflation series to undertake a real-time decomposition of quarterly headline PCE and GDP-deflator inflation rates into a common long-term trend, common cyclical component, and high-frequency noise components. We then explore alternative approaches to real-time forecasting of headline PCE inflation. We find that performance is enhanced if forecasting equations are estimated using inflation data that have been stripped of high-frequency noise. Performance can be further ...