2026-04-18T00:14:00Zhttps://recercat.cat/oai/requestoai:recercat.cat:10230/574792025-12-13T21:20:31Zcom_2072_6col_2072_452952
RECERCAT
author
Mumtaz, Haroon
author
Petrova, Katerina
2023-07-06T06:54:53Z2023-07-06T06:54:53Z2023
In this paper, we extend the Bayesian Proxy vector autoregression (VAR) model to incorporate time variation in the parameters. A novel Metropolis-within-Gibbs sampling algorithm is provided to approximate the posterior distributions of the model's parameters. Using the proposed algorithm, we estimate the time-varying effects of taxation shocks in the United States and the United Kingdom and find evidence for a decline in the impact of these shocks on output growth.Katerina Petrova acknowledges support by the Alan Turing Institute under the EPSRC grant EP/N510129/1, the General Directorate for Research in the Government of Catalonia through the Beatriu de Pinós grant 2019/BP/00239, and the Spanish Ministry of Science and Innovation, through the Severo Ochoa Programme for Centres of Excellence in R&D (CEX2019-000915-S).
© 2022 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess
time-varying parameters
stochastic volatility
proxy VAR
tax shocks
Changing impact of shocks: a time-varying proxy SVAR approach
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion