On May 10th and 11th the Weidenbaum Center and the Research Department of the Federal Reserve Bank of St. Louis co-sponsored a workshop for leading researchers in applied time series analysis, with James Hamilton as the invited lecturer. Topics of presentations included recent changes in monetary policy implementation, the interaction between monetary policy and financial markets, and the dynamics of business cycle recoveries. For more information, contact James Morley or Jeremy Piger.

Click on a presenter below to go to their home page, or a paper title to access a PDF version of the paper.
 
 

• New Directions in Business Cycle Research - Power Point presentation made at the conference.

• Zero-Information-Limit Models and Spurious Inference: The Case of ARMA with Near Cancellation by Charles Nelson and Richard Startz - In this paper we introduce the idea of Zero-Information-Limit (ZIL) models and show how that property accounts for spurious inference in the ARMA model when there is near cancellation between AR and MA factors. 

• Evaluating the Role of Human Capital in Economic Development: A Factor Analysis Approach

• Measuring the Reaction of Monetary Policy to the Stock Market by Robert Rigobon and Brian Sack - Movements in the stock market can have a significant impact on the macroeconomy and are therefore likely to be an important factor in the determination of monetary policy. However, little is known about the magnitude of the Federal Reserve's reaction to the stock market. One reason is that it is difficult to estimate the policy reaction because of the simultaneous response of equity prices to interest rate changes. This paper uses an identification technique based on the heteroskedasticity of stock market returns to identify the reaction of monetary policy to the stock market. The results indicate that monetary policy reacts significantly to stock market movements, with a 5% rise (fall) in the S&P 500 index increasing the likelihood of a 25 basis point tightening (easing) by about half. This reaction is roughly of the magnitude that would be expected from estimates of the impact of stock market movements on aggregate demand. Thus, it appears that the Federal Reserve systematically responds to stock price movements only to the extent warranted by their impact on the macroeconomy.

• Why Were Changes in the Federal Funds Rate Smaller in the 1990s? by Arabinda Basistha and Richard Startz - In this paper, we identify two major changes in the dynamics of the federal funds rate in the 1990s. We model the desired rate in a two-regime setting, on when the Fed makes no change and the other when the Fed is moving the desired rate to a new level. We find that the 1990s saw longer duration in the no-change regime as well as smaller changes in the other regime. We show the smaller changes were neither due to a less aggressive Fed nor due to lower volatility of the fundamentals. In fact, the Fed responded more aggressively to changes in fundamentals in the 1990s. The results also suggest that the Fed became more forward-looking in the last decade.

• The Term Structure of Real Rates and Expected Inflation

• Empirical Assessment of an Intertemporal Option Pricing Model with Latent Variables by Rene Garcia, Richard Luger and Eric Renault - This paper assesses the empirical performance of an intertemporal option pricing model with latent variables which generalizes the Black-Scholes and the stochastic volatility formulas. We derive a closed-form formula for an equilibrium model with recursive preference where the fundamentals follow a Markov switching process. In a simulation experiment based on the model, we show that option prices are more informative about preference parameters than stock returns. When we estimate the preference parameters implicit in S&P 500 call option prices given our model, we find quite reasonable values for the coefficient of relative risk aversion and the intertemporal elasticity of substitution. Finally, when we calibrate the model to minimize out-of-sample pricing errors, we obtain a performance which is in line with a practitioners' Black and Scholes approach based on implied volatility.

• Strategic Asset Allocation Under Regime Switching by Massimo Guidolin and Allan Timmermann - This paper studies optimal asset allocation to stocks, long-term bonds and T-bills in the presence of regime switching in returns. We find strong evidence that four separate regimes - characterized as crash, slow growth, bull and bull burst states - are required to capture the joint distribution of stock and bond returns. Optimal asset allocations vary considerably over these states - both across bonds and stocks and among large and small stocks - and consequently also change over time as investors update their perceptions of the current state probabilities. Furthermore, while in the crash state investors always allocate more of their portfolio to stocks the longer their investment horizon, the optimal allocation to stocks actually declines as a function of the investment horizon in bull markets.

• Bayesian Analysis of Hidden-Markov, Change-Point, and Stochastic Volatility Models: A Summary

• Non-Markovian Regime Switching with Endogenous States

• A Nonlinear Model of the Business Cycle by Edward E. Leamer and Simon M. Potter - The usual index of leading indicators has constant weights on its components and is therefore implicitly premised on the assumption that the dynamical properties of the economy remain the same over time and across phases of the business cycle. We explore the possibility that the business cycle has phases, for example, recessions, recoveries and normal growth, each with its unique dynamics. Based on this possibility we develop a nonlinear model of the business cycle that combines a number of previous approaches. We model the state of the economy as a latent variable with a threshold autoregression structure. In addition to dependence on its own lags the latent variable is also determined by observed economic and financial variables. In turn these variables are modeled as following a nonlinear vector autoregression with regimes defined by the latent business cycle variable. A Markov Chain Monte Carlo algorithm is developed to estimate the model. Special attention is paid to specification of prior distributions given the large dimension of the model. We also investigate using the business cycle chronology of the NBER to aid in the classification of the latent variable. The two main empirical objectives of the model are to provide more accurate predictions of economic variables particularly at turning points and to describe how the dynamics differ across business cycle phases.

• Time-Varying Parameter Models with Endogenous Explanatory Variables

• A Markov-Switching Model of Business Cycle Dynamics with a Post-Recession 'Bouce-Back' Effect by Chang-Jin Kim, James Morley, and Jeremy Piger - This paper presents a nonlinear model of U.S. GDP growth dynamics that allows for post-recession "bounce-back" effect in the level of GDP. While a number of studies have attempted to capture such an effect using ad hoc recession-based dummy variable methods, we endogenously estimate this business cycle asymmetry using an extended version of Hamilton's (1989) Markov-switching model. Like Hamilton, we find model regimes that correspond closely to NBER-dated recession and expansions. We also find a large "bounce-back" effect that, according to our Monte Carlo analysis, is statistically significant and implies a relatively small permanent effect of recessions.

• Smooth but not Random: The Behavior of Aggregate Consumption According to Cointegration Analysis with Correlated Unobserved Components by James Morley - This paper investigates the relationship between aggregate consumption and income. It applies a new approach to cointigration analysis that builds on Stock and Watson's (1988a) common stochastic trends representation. The permanent and transitory components of the cointegrated time series are estimated directly using the Kalman filter and are allowed to be correlated. This approach avoids any implicit restriction that permanent income be as smooth as consumption. Instead, permanent income appears to be reasonably volatile, with consumption adjusting toward it slowly over time.