RT Journal Article
T1 Non-Gaussian score-driven conditionally heteroskedastic models with a macroeconomic application
A1 Blazsek, Szabolcs
A1 Escribano, Álvaro
A1 Licht, Adrián
AB We contribute to the literature on empirical macroeconomic models with time-varying conditional moments, by introducing a heteroskedastic score-driven model with Student's t-distributed innovations, named the heteroskedastic score-driven -QVAR (quasi-vector autoregressive) model. The -QVAR model is a robust nonlinear extension of the VARMA (VAR moving average) model. As an illustration, we apply the heteroskedastic -QVAR model to a dynamic stochastic general equilibrium model, for which we estimate Gaussian-ABCD and -ABCD representations. We use data on economic output, inflation, interest rate, government spending, aggregate productivity, and consumption of the USA for the period of 1954 Q3 to 2022 Q1. Due to the robustness of the heteroskedastic -QVAR model, even including the period of the coronavirus disease of 2019 (COVID-19) pandemic and the start of the Russian invasion of Ukraine, we find a superior statistical performance, lower policy-relevant dynamic effects, and a higher estimation precision of the impulse response function for US gross domestic product growth and US inflation rate, for the heteroskedastic score-driven -ABCD representation rather than for the homoskedastic Gaussian-ABCD representation.
PB Cambridge University Press.
SN 1365-1005
YR 2023
FD 2023-03-09
LK https://hdl.handle.net/10016/39117
UL https://hdl.handle.net/10016/39117
LA eng
NO Szabolcs Blazsek and Adrián Licht acknowledge funding from Universidad Francisco Marroquín. Álvaro Escribano acknowledges funding from the Ministry of Economics of Spain (ECO2016-00105-001, MDM 2014-0431), the Community of Madrid (MadEco-CM S2015/HUM-3444), and Agencia Estatal de Investigación (2019/00419/001).
DS e-Archivo
RD 17 jul. 2024