scholarly journals The impact of US uncertainty on the Euro area in good and bad times: evidence from a quantile structural vector autoregressive model

Empirica ◽  
2018 ◽  
Vol 46 (2) ◽  
pp. 353-368 ◽  
Author(s):  
Rangan Gupta ◽  
Chi Keung Marco Lau ◽  
Mark E. Wohar
Keyword(s):  
Euro Area ◽  
Autoregressive Model ◽  
Vector Autoregressive Model ◽  
Vector Autoregressive ◽  
Structural Vector Autoregressive Model ◽  
The Impact ◽  
Structural Vector

scholarly journals Analysis of the Monetary Policy Dynamics in Romania Using a Structural Vector Autoregressive Model

2019 ◽  
pp. 146-161
Keyword(s):  
Monetary Policy ◽  
Autoregressive Model ◽  
Vector Autoregressive Model ◽  
Vector Autoregressive ◽  
Monetary Aggregates ◽  
Policy Dynamics ◽  
Structural Vector Autoregressive Model ◽  
The Impact ◽  
Structural Vector ◽  
Empirical Framework

This chapter aims to provide an elaborate empirical analysis of the monetary policy dynamics in Romania using a structural vector autoregressive model. This chapter contributes to literature based on an empirical framework regarding the implications of exchange rate channel within the monetary policy, and the impact of the monetary aggregates channels in order to explain the evolution of the prices level in Romania.

scholarly journals A Spatial Panel Structural Vector Autoregressive Model with Interactive Effects and Its Simulation

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 883
Author(s):  
Yaqing Liu ◽  
Hongbing Ouyang ◽  
Xiaolu Wei
Keyword(s):  
Autoregressive Model ◽  
Common Factors ◽  
Interactive Effects ◽  
Vector Autoregressive Model ◽  
Finite Sample ◽  
Vector Autoregressive ◽  
Spatial Panel ◽  
The Common ◽  
Structural Vector Autoregressive Model ◽  
Structural Vector

The existing spatial panel structural vector auto-regressive model can effectively capture the time and spatial dynamic dependence of endogenous variables. However, the hypothesis that the common factors have the same effect for all spatial units is unreasonable. Therefore, incorporating time effects, spatial effects, and time-individual effects, this paper develops a more general spatial panel structural vector autoregressive model with interactive effects (ISpSVAR) that can reflect the different effects of common factors on different spatial units. Additionally, based on whether or not the common factors can be observed, this paper proposes procedures to estimate ISpSVAR separately and studies the finite sample properties of estimators by Monte Carlo simulation. The simulation results show the effectiveness of the proposed ISpSVAR model and its estimation procedures.

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