Macroeconomic and Business Cycle Measurement, Modeling and Forecasting

Diebold, F.X. and Yilmaz, K. (in press 2008), "Macroeconomic Volatility and Stock Market Volatility, Worldwide," in T. Bollerslev, J. Russell and M. Watson (eds.), Volatility and Time Series Econometrics: Essays in Honor of Robert F. Engle. Oxford: Oxford University Press.

We study a broad international cross section of stock markets, and we find a clear link between macroeconomic fundamentals and stock market volatilities, with volatile fundamentals translating into volatile stock markets.

Aruoba, S.B., Diebold, F.X. and Scotti, C. (2007, revised 2008), "Real-Time Measurement of Business Conditions," Journal of Business and Economic Statistics, in press.

We construct a framework for measuring high-frequency economic activity 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 effcacy of our methods both in an empirical example and in a simulation study.

Campbell, S.D. and Diebold, F.X. (Forthcoming), "Stock Returns and Expected Business Conditions: Half a Century of Direct Evidence," Journal of Business and Economic Statistics.

Using half a century of Livingston expected business conditions data, we characterize directly the impact of expected business conditions on expected excess stock returns. Expected business conditions consistently affect expected excess returns in a statistically and economically significant counter-cyclical fashion: depressed expected business conditions are associated with high expected excess returns. Moreover, inclusion of expected business conditions in otherwise-standard predictive return regressions substantially reduces the explanatory power of the conventional financial predictors, including the dividend yield, default premium, and term premium, while simultaneously increasing R squared. Interestingly, one important and recently introduced non-financial predictor, the generalized consumption/wealth ratio ("CAY"), retains its predictive power even when controlling for expected business conditions, which accords with the view that the consumption/wealth ratio plays a role in asset pricing different from and complementary to that of expected business conditions. We argue that time-varying expected business conditions likely captures time-varying risk, while time-varying consumption/wealth captures time-varying risk aversion.

Andersen, T., Bollerslev, T., Diebold, F.X. and Vega, C. (2007), "Real-Time Price Discovery in Stock, Bond and Foreign Exchange Markets," Journal of International Economics, 73, 251-277.

We progress relative to Andersen, Bollerslev, Diebold and Vega (2003, AER) by using a unique dataset to characterize news responses across several markets and countries. Among other things, we show that equity markets react differently to the same news depending on the state of the economy. In particular, good news has negative effects in expansions, and the traditionally-expected positive effects in recessions, which we explain by temporal variation in the competing "cash flow" and "discount rate" effects in equity valuation. We believe that our results, in conjunction with recent work by Boyd, Jagannathan and Hu, make a powerful advance toward answering Barsky's (1989, AER) key question, "Why Don't the Prices of Stocks and Bonds Move Together?": they do move together insofar as the correlation between stock and bond returns is sizeable and important, but it switches sign in expansions vs. recessions, and it therefore appears spuriously small when averaged over the business cycle.

Diebold, F.X., Piazzesi, M. and Rudebusch, G.D. (2005), "Modeling Bond Yields in Finance and Macroeconomics," American Economic Review, 95, 415-420.

New aspects of the macro/finance interface as embodied in yield curve modeling. The tension between current finance approaches that have the theoretically appealing property of freedom from arbitrage but forecast poorly, and traditional macroeconomic approaches that admit arbitrage but forecast well. A step toward resolving the tension: making Nelson-Siegel arbitrage-free.

Diebold, F.X. (2005), “On Robust Monetary Policy with Structural Uncertainty,” in J. Faust, A. Orphanides and D. Reifschneider (eds.), Models and Monetary Policy: Research in the Tradition of Dale Henderson, Richard Porter, and Peter Tinsley. Washington, DC: Board of Governors of the Federal Reserve System, 82-86.

Pitfalls and opportunities associated with the new robust control. Local vs. global robustness, and the dangers of complacency.

Andersen, T., Bollerslev, T., Diebold, F.X. and Vega, C. (2003), "Micro Effects of Macro Announcements: Real- Time Price Discovery in Foreign Exchange," American Economic Review, 93, 38-62.

Diebold, F.X. (2003), "'Big Data' Dynamic Factor Models for Macroeconomic Measurement and Forecasting" (Discussion of Reichlin and Watson papers), in M. Dewatripont, L.P. Hansen and S. Turnovsky (Eds.), Advances in Economics and Econometrics, Eighth World Congress of the Econometric Society. Cambridge: Cambridge University Press, 115-122.

Diebold, F.X. and Li, C. (2006), “Forecasting the Term Structure of Government Bond Yields,” Journal of Econometrics, 130, 37-64.

The classic Nelson-Siegel curve, suitably dynamized and reinterpreted as a modern three-factor model of level, slope and curvature, forecasts bond yields surprisingly well, particularly at horizons between two and four quarters ahead.

Diebold, F.X., Rudebusch, G.D. and Aruoba, B. (2006), “The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach,” Journal of Econometrics, 131, 309-338.

Do macroeconomic fundamentals help predict the yield curve? Does the yield curve help predict macroeconomic fundamentals? The answers are yes and yes, although the stronger direction of predictive causality seems to be from the macroeconomy to yields.

Bangia, A. Diebold, F.X., Kronimus, A., Schagen, C., and Schuermann, T. (2002), "Ratings Migration and the Business Cycle, with Application to Credit Portfolio Stress Testing," Journal of Banking and Finance, 26, 445- 474.

Diebold, F.X. and Kilian, L. (2001), "Measuring Predictability: Theory and Macroeconomic Applications," Journal of Applied Econometrics, 16, 657-669.

Diebold, F.X. (1998), "The Past, Present and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, 12, 175-192.

Diebold, F.X., Ohanian, L. and Berkowitz, J. (1998), "Dynamic Equilibrium Economies: A Framework for Comparing Models and Data," Review of Economic Studies, 65, 433-452.

Diebold, F.X. and Rudebusch, G. (1996), "Measuring Business Cycles: A Modern Perspective," Review of Economics and Statistics, 78, 67-77.