E43 Determination of Interest Rates; Term Structure of Interest Rates

GDP Growth Predictions through the Yield Spread. Time-Variation and Structural Breaks

JEL code(s)	C22 Single Equation Models; Single Variables: Time-Series Models C32 Multiple or Simultaneous Equation Models: Time-Series Models C53 Forecasting and Other Model Applications E37 Prices, Business Fluctuations, and Cycles: Forecasting and Simulation E43 Determination of Interest Rates; Term Structure of Interest Rates E47 Money and Interest Rates: Forecasting and Simulation
Keywords	real-time data, structural breaks, Term Spread, TVP Models
Authors:	Pierangelo De Pace
Date published:	February 1, 2011
Abstract:	We use TVP models and real-time data to describe the evolution of the leading properties of the yield spread for output growth in five European economies and in the US over the last decades and until the third quarter of 2010. We evaluate the predictive performance of benchmark term-structure models and identify structural breaks in the marginal processes of term spreads and government bond yields to shed light on the dynamic characteristics of the yield curve. Econometric analysis shows that: (i) the predictive content of the term spread is not always significant over time and across countries; (ii) the spread significantly contributes to the forecast performance of simple growth regressions in Europe, but not in the US in recent years; (iii) the variance of the random shocks to the term spreads tends to fall in all countries. This decline is accompanied by vanishing leading properties from the mid-1990s. Such properties reappear after 2008.
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What does a financial system say about future economic growth?

JEL code(s)	E43 Determination of Interest Rates; Term Structure of Interest Rates E44 Financial Markets and the Macroeconomy G12 Asset Pricing; Trading volume; Bond Interest Rates
Keywords	financial markets, CCAPM, Economic Growth, expectations, forecasting, term spreads
Authors:	Szymon Grabowski
Date published:	January 1, 2009
Abstract:	In many research studies it is argued that it is possible to extract useful information about future economic growth from the performance of financial markets. However, this study goes further and shows that it is not only possible to use expectations derived from financial markets to forecast future economic growth, but that data about the financial system can be used for this purpose as well. The research is conducted for the Polish emerging economy on the basis of monthly data. The results suggest that, based purely on the data from the financial system, it is possible to construct reasonable measures that can, even for an emerging economy, effectively forecast future real economic activity. The outcomes are proved by two different econometric methods, namely, by a time series analysis and by a probit model. All presented models are tested in-sample and out-of-sample.
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