Michael J Dueker
Biographic Data
| ID | 5766530 |
|---|---|
| NAME | Michael J Dueker |
| GIVEN NAMES | Michael J |
| FAMILY NAME | Dueker |
| SIGNATURE | DUEKER M J |
| AFFILIATIONS | Federal Reserve Bank of St. Louis |
| VERIFIED | No |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1997 |
| LATEST PUBLICATION YEAR | 2005 |
| H-INDEX | 1 |
Dynamic Forecasts of Qualitative Variables: A Qual VAR Model of U.S. Recessions
This article presents a new Qual VAR model for incorporating information from qualitative and/or discrete variables in vector autoregressions. With a Qual VAR, it is possible to create dynamic forecasts of the qualitative variable using standard VAR projections. Previous forecasting methods for qualitative variables, in contrast, produce only static forecasts. I apply the Qual VAR to forecasting the 2001 business recession out of sample and to an…
Non-Markovian Regime Switching with Endogenous States and Time-Varying State Strengths
Aggregate price shocks and financial stability: The United Kingdom 1796–1999
Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate
Previous time series applications of qualitative response models have ignored features of the data, such as conditional heteroscedasticity, that are routinely addressed in time series econometrics of financial data. This article addresses this issue by adding Markov-switching heteroscedasticity to a dynamic ordered probit model of discrete changes in the bank prime lending rate and estimating via the Gibbs sampler. The dynamic ordered probit mode…
Maximum-Likelihood Estimation of Fractional Cointegration with an Application to U.S. and Canadian Bond Rates
We estimate a multivariate ARFIMA model to illustrate a cointegration testing methodology based on joint estimates of the fractional orders of integration of a cointegrating vector and its parent series. Previous cointegration tests relied on a two-step testing procedure and maintained the assumption in the second step that the parent series were known to have a unit root. In our empirical example of fractional cointegration, we illustrate how un…
Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility
This article introduces four models of conditional heteroscedasticity that contain Markov-switching parameters to examine their multiperiod stock-market volatility forecasts as predictions of options-implied volatilities. The volatility model that best predicts the behavior of the options-implied volatilities allows the Student-t degrees-of-freedom parameter to switch such that the conditional variance and kurtosis are subject to discrete shifts.…
Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility
This article introduces four models of conditional heteroscedasticity that contain Markov-switching parameters to examine their multiperiod stock-market volatility forecasts as predictions of options-implied volatilities. The volatility model that best predicts the behavior of the options-implied volatilities allows the Student-t degrees-of-freedom parameter to switch such that the conditional variance and kurtosis are subject to discrete shifts.…
Maximum-Likelihood Estimation of Fractional Cointegration with an Application to U.S. and Canadian Bond Rates
We estimate a multivariate ARFIMA model to illustrate a cointegration testing methodology based on joint estimates of the fractional orders of integration of a cointegrating vector and its parent series. Previous cointegration tests relied on a two-step testing procedure and maintained the assumption in the second step that the parent series were known to have a unit root. In our empirical example of fractional cointegration, we illustrate how un…
Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate
Previous time series applications of qualitative response models have ignored features of the data, such as conditional heteroscedasticity, that are routinely addressed in time series econometrics of financial data. This article addresses this issue by adding Markov-switching heteroscedasticity to a dynamic ordered probit model of discrete changes in the bank prime lending rate and estimating via the Gibbs sampler. The dynamic ordered probit mode…
Aggregate price shocks and financial stability: The United Kingdom 1796–1999
Non-Markovian Regime Switching with Endogenous States and Time-Varying State Strengths
Dynamic Forecasts of Qualitative Variables: A Qual VAR Model of U.S. Recessions
This article presents a new Qual VAR model for incorporating information from qualitative and/or discrete variables in vector autoregressions. With a Qual VAR, it is possible to create dynamic forecasts of the qualitative variable using standard VAR projections. Previous forecasting methods for qualitative variables, in contrast, produce only static forecasts. I apply the Qual VAR to forecasting the 2001 business recession out of sample and to an…
Economics (6 works) · Econometrics (5 works) · Mathematics (5 works) · Statistics (5 works) · Monetary Policy and Economic Impact (4 works) · Complex Systems and Time Series Analysis (3 works) · Financial Risk and Volatility Modeling (3 works) · Market Dynamics and Volatility (3 works) · Finance (2 works) · Finance (2 works)