Bayesian estimation of the long-run trend of the US economy
Year of publication: |
2022
|
---|---|
Authors: | Kim, Jaeho ; Chon, Sora |
Published in: |
Empirical economics : a quarterly journal of the Institute for Advanced Studies. - Berlin : Springer, ISSN 1435-8921, ZDB-ID 1462176-9. - Vol. 62.2022, 2, p. 461-485
|
Subject: | Structural break | Long-run trend | Unobserved components model | Bounded stochastic volatility | Zeitreihenanalyse | Time series analysis | USA | United States | Strukturbruch | Volatilität | Volatility | Bayes-Statistik | Bayesian inference | Stochastischer Prozess | Stochastic process | Schätzung | Estimation | Schätztheorie | Estimation theory | Zustandsraummodell | State space model | Wirtschaftswachstum | Economic growth |
-
Is it one break or ongoing permanent shocks that explains US real GDP?
Luo, Sui, (2014)
-
Why are Bayesian trend-cycle decompositions of US real GDP so different?
Kim, Jaeho, (2020)
-
Large mixed-frequency VARs with a parsimonious time-varying parameter structure
Götz, Thomas B., (2021)
- More ...
-
Does the financial leverage effect depend on volatility regimes?
Chon, Sora, (2021)
-
Why Are Bayesian Trend-Cycle Decompositions of U.S. Real GDP So Different?
Kim, Jaeho, (2018)
-
Why are Bayesian trend-cycle decompositions of US real GDP so different?
Kim, Jaeho, (2020)
- More ...