Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices

TL;DR

This paper introduces two real-time mixed-frequency models for assessing US economic indicators, enabling timely monitoring of output potential, gaps, and relationships like the Phillips curve and Okun's law.

Contribution

It develops and compares two semi-structural models for real-time economic monitoring, with one incorporating official output gap measures for improved trend estimation.

Findings

The baseline model provides a trend-cycle decomposition with minimal restrictions.

Adding the CBO's output gap yields smoother trend estimates but worse long-term forecasts.

Models facilitate real-time assessment of economic trends and gaps.

Abstract

We propose two specifications of a real-time mixed-frequency semi-structural time series model for evaluating the output potential, output gap, Phillips curve, and Okun's law for the US. The baseline model uses minimal theory-based multivariate identification restrictions to inform trend-cycle decomposition, while the alternative model adds the CBO's output gap measure as an observed variable. The latter model results in a smoother output potential and lower cyclical correlation between inflation and real variables but performs worse in forecasting beyond the short term. This methodology allows for the assessment and real-time monitoring of official trend and gap estimates.