structural vector autoregressionstructural vector moving averageWhittle likelihoodI propose to estimate structural impulse responses from macroeconomic time series by doing Bayesian inference on the Structural Vector Moving Average representation of the data. This approach has two advantages over Structural ...
Structural VARVector AutoregressionVector autoregressive models have widely been applied in macroeconomics and macroeconometrics to estimate economic relationships and to empirically assess theoretical hypothesis. To achieve the latter, we propose a Bayesian inference approach to analyze the dynamic interactions ...
Much of it has been with different variants of the (Bayesian) structural vector autoregression (SVAR) model. For instance, Alessandri and Mumtaz (2021) use a panel VAR model with stochastic volatility in mean (SVM) to study the impact of climate volatility on economic growth on 133 countries ...
A large Bayesian vector autoregression model for Russia We apply an econometric approach developed specifically to address the 'curse of dimensionality' in Russian data and estimate a Bayesian vector autoregress... E Deryugina,AA Ponomarenko - 《Social Science Electronic Publishing》 被引量: 5发表:...
Time Varying Structural Vector Autoregressions and Monetary Policy Monetary policy and the private sector behaviour of the U.S. economy are modelled as a time varying structural vector autoregression, where the sources of ... GE Primiceri - 《Review of Economic Studies》 被引量: 3202发表: 2005年...
F. (2012). Structural Vector Autoregression, Mimeo. • Litterman, R. B. (1986). Forecasting with Bayesian vector autoregressions five years of experience. Journal of Business and Economic Statistics, (4):25-38. • Rubio-Ramirez, J.F., D. F. Waggoner, and T. Zha (2010), Structural...
We estimate a Bayesian vector autoregression for the U.K. with drifting coefficients and stochastic volatilities. We use it to characterize posterior densities for several objects that are useful for designing and evaluating monetary policy, including local approximations to the mean, persistence, and ...
We estimate a Bayesian vector autoregression for the U.K. with drifting coefficients and stochastic volatilities. We use it to characterize posterior densities for several objects that are useful for designing and evaluating monetary policy, including local approximations to the mean, persistence, and ...
To address the shortcomings of conventional monitoring models, such as difficulty in selecting influencing factors and poor ability to resist the interference of outliers, this paper develops a structural safety monitoring model that can realize adaptive identification of various types of outliers in dam...
Traditional approaches to structural vector autoregressions (VARs) can be viewed as special cases of Bayesian inference arising from very strong prior beli... C Baumeister,JD Hamilton - 《American Economic Review》 被引量: 0发表: 2019年 加载更多研究...