Real-time macroeconomic monitoring: real activity, inflation, and interactions

The authors sketch a framework for monitoring macroeconomic activity in real-time and push it in new directions. In particular, they focus not only on real activity, which has received most attention to date, but also on inflation and its interaction with real activity. As for the recent recession, the authors find that (1) it likely ended around July 2009; (2) its most extreme aspects concern a real activity decline that was unusually long but less unusually deep, and an inflation decline that was unusually deep but brief; and (3) its real activity and inflation interactions were strongly positive, consistent with an adverse demand shock.Financial crises ; Real-time data ; Macroeconomics

Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions

We sketch a framework for monitoring macroeconomic activity in real-time and push it in new directions. In particular, we focus not only on real activity, which has received most attention to date, but also on inflation and its interaction with real activity. As for the recent recession, we find that (1) it likely ended around July 2009; (2) its most extreme aspects concern a real activity decline that was unusually long but less unusually deep, and an inflation decline that was unusually deep but brief; and (3) its real activity and inflation interactions were strongly positive, consistent with an adverse demand shock.Nowcasting, Prices, Wages, Business cycle, Expansion, Contraction, Recession, Turning point, State-space model, Dynamic factor model

The macroeconomy and the yield curve: a nonstructural analysis

We estimate a model with latent factors that summarize the yield curve (namely, level, slope, and curvature) as well as observable macroeconomic variables (real activity, inflation, and the stance of monetary policy). Our goal is to provide a characterization of the dynamic interactions between the macroeconomy and the yield curve. We find strong evidence of the effects of macro variables on future movements in the yield curve and much weaker evidence for a reverse influence. We also relate our results to a traditional macroeconomic approach based on the expectations hypothesis

Real-Time Measurement of Business Conditions

We construct a framework for measuring economic activity in real time (e.g., minute-by-minute), using a variety of stock and flow data observed at mixed frequencies. Specifically, we propose a dynamic factor model that permits exact filtering, and we explore the efficacy of our methods both in a simulation study and in a detailed empirical example.Business cycle, Expansion, Recession, State space model, Macroeconomic forecasting, Dynamic factor model

Real-Time Measurement of Business Conditions, Second Version

We construct a framework for measuring economic activity at high frequency, potentially in real time. We use a variety of stock and flow data observed at mixed frequencies (including very high frequencies), and we use a dynamic factor model that permits exact filtering. We illustrate the framework in a prototype empirical example and a simulation study calibrated to the example.Business cycle, Expansion, Recession, State space model, Macroeconomic forecasting, Dynamic factor model, Contraction, Turning point

Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange

We provide a framework for evaluating and improving multivariate density forecasts. Among other things, the multivariate framework lets us evaluate the adequacy of density forecasts involving cross-variable interactions, such as time-varying conditional correlations. We also provide conditions under which a technique of density forecast "calibration" can be used to improve deficient density forecasts. Finally, motivated by recent advances in financial risk management, we provide a detailed application to multivariate high-frequency exchange rate density forecasts. Copyright © 1998 F.X. Diebold, J. Hahn, and A.S. Tay. This paper is also available at

Evaluating Density Forecasts

We propose methods for evaluating density forecasts. We focus primarily on methods that are applicable regardless of the particular user's loss function. We illustrate the methods with a detailed simulation example, and then we present an application to density forecasting of daily stock market returns. We discuss extensions for improving suboptimal density forecasts, multi-step-ahead density forecast evaluation, multivariate density forecast evaluation, monitoring for structural change and its relationship to density forecasting, and density forecast evaluation with known loss function.

The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach

We estimate a model that summarizes the yield curve using latent factors (specifically, level, slope, and curvature) and also includes observable macroeconomic variables (specifically, real activity, inflation, and the monetary policy instrument). Our goal is to provide a characterization of the dynamic interactions between the macroeconomy and the yield curve. We find strong evidence of the effects of macro variables on future movements in the yield curve and evidence for a reverse influence as well. We also relate our results to the expectations hypothesis.

Evaluating density forecasts

The authors propose methods for evaluating and improving density forecasts. They focus primarily on methods that are applicable regardless of the particular user's loss function, though they take explicit account of the relationships between density forecasts, action choices, and the corresponding expected loss throughout. They illustrate the methods with a detailed series of examples, and they discuss extensions to improving and combining suboptimal density forecasts, multistep-ahead density forecast evaluation, multivariate density forecast evaluation, monitoring for structural change and its relationship to density forecasting, and density forecast evaluation with known loss function.Forecasting

The Macroeconomy and the Yield Curve: A Nonstructural Analysis

We estimate a model with latent factors that summarize the yield curve (namely, level, slope, and curvature) as well as observable macroeconomic variables (real activity, inflation, and the stance of monetary policy). Our goal is to provide a characterization of the dynamic interactions between the macroeconomy and the yield curve. We find strong evidence of the effects of macro variables on future movements in the yield curve and much weaker evidence for a reverse influence. We also relate our results to a traditional macroeconomic approach based on the expectations hypothesis.Yield curve, term structure, interest rates, macroeconomic fundamentals, factor model, statespace model