Eric Zivot
Biographic Data
| ID | 8879203 |
|---|---|
| NAME | Eric Zivot |
| GIVEN NAMES | Eric |
| FAMILY NAME | Zivot |
| SIGNATURE | ZIVOT E |
| AFFILIATIONS | University of Washington |
| ORCID | 0009-0006-7455-9503 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1992 |
| LATEST PUBLICATION YEAR | 2003 |
| H-INDEX | 0 |
Why Are the Beveridge-Nelson and Unobserved-Components Decompositions of GDP So Different
This paper reconciles two widely used decompositions of GDP into trend and cycle that yield starkly different results. The Beveridge-Nelson (BN) decomposition implies that a stochastic trend accounts for most of the variation in output, whereas the unobserved-components (UC) implies cyclical variation is dominant. Which is correct has broad implications for the relative importance of real versus nominal shocks. We show the difference arises from …
Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis
Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes iss…
Markov Regime Switching and Unit-Root Tests
We investigate the power and size performance of unit-root tests when the data undergo Markov regime switching. All tests, including those robust to a single break in trend growth rate, have low power against a process with a Markov-switching trend. Under the null hypothesis, we find that previously documented size distortions in Dickey–Fuller-type tests caused by a single break in trend growth rate or variance do not generalize to most parameter…
A Bayesian Time Series Model of Multiple Structural Changes in Level, Trend, and Variance
We consider a deterministically trending dynamic time series model in which multiple structural changes in level, trend, and error variance are modeled explicitly and the number, but not the timing, of the changes is known. Estimation of the model is made possible by the use of the Gibbs sampler. The determination of the number of structural breaks and the form of structural change is considered as a problem of model selection, and we compare the…
Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis
Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes iss…
No prominent works on this page.
Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis
Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes iss…
A Bayesian Time Series Model of Multiple Structural Changes in Level, Trend, and Variance
We consider a deterministically trending dynamic time series model in which multiple structural changes in level, trend, and error variance are modeled explicitly and the number, but not the timing, of the changes is known. Estimation of the model is made possible by the use of the Gibbs sampler. The determination of the number of structural breaks and the form of structural change is considered as a problem of model selection, and we compare the…
Markov Regime Switching and Unit-Root Tests
We investigate the power and size performance of unit-root tests when the data undergo Markov regime switching. All tests, including those robust to a single break in trend growth rate, have low power against a process with a Markov-switching trend. Under the null hypothesis, we find that previously documented size distortions in Dickey–Fuller-type tests caused by a single break in trend growth rate or variance do not generalize to most parameter…
Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis
Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes iss…
Why Are the Beveridge-Nelson and Unobserved-Components Decompositions of GDP So Different
This paper reconciles two widely used decompositions of GDP into trend and cycle that yield starkly different results. The Beveridge-Nelson (BN) decomposition implies that a stochastic trend accounts for most of the variation in output, whereas the unobserved-components (UC) implies cyclical variation is dominant. Which is correct has broad implications for the relative importance of real versus nominal shocks. We show the difference arises from …
Econometrics (5 works) · Mathematics (5 works) · Monetary Policy and Economic Impact (5 works) · Statistics (5 works) · Economics (4 works) · Cointegration (3 works) · Computer Science (3 works) · Market Dynamics and Volatility (3 works) · Structural break (3 works) · Unit root (3 works)