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Item type:Publication, Time-Varying Effects of External Shocks on Macroeconomic Fluctuations in Peru: An Empirical Application Using TVP-VAR-SV Models(Springer Science+Business Media, 2023-11-24)This study uses a family of VAR models with time-varying parameters and stochastic volatility (TVP-VAR-SV) to analyze the impact of external shocks on output growth and inflation in Peru in 1992Q1-2017Q1. The statistical relevance of the models is assess... - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Approximate Bayesian Estimation of Stochastic Volatility in Mean Models Using Hidden Markov Models: Empirical Evidence from Emerging and Developed Markets(Springer Science+Business Media, 2023-11-03)The stochastic volatility in mean (SVM) model proposed by Koopman and Uspensky (J Appl Econ 17:667–689, 2002) is revisited. This paper has two goals. The first is to offer a methodology that requires less computational time in simulations and estimates compared with others proposed in the literature as in Abanto-Valle et al. (Q Rev Econ Financ 80:272–286, 2021) and others. To achieve the first goal, we propose to approximate the likelihood function of the model applying Hidden Markov Models machinery to make possible Bayesian inference in real-time. We sample from the posterior distribution of parameters with a multivariate Normal distribution with mean and variance given by the posterior mode and the inverse of the Hessian matrix evaluated at this posterior mode using importance sampling. Further, the frequentist properties of estimators are analyzed conducting a simulation study. The second goal is to provide empirical evidence estimating the SVM model using daily data for five Latin American stock markets, USA, England, Japan and China. The results indicate that volatility negatively impacts returns, suggesting that the volatility feedback effect is stronger than the effect related to the expected volatility. This result is similar to the findings of Koopman and Uspensky (J Appl Econ 17:667–689, 2002), where the respective coefficient is negative but non statistically significant. However, in our case, all countries (except Peru and China) presents negative and statistically significant effects. Our results are similar to those found using Hamiltonian Monte Carlo (HMC) and Riemannian HMC methods based on Abanto-Valle et al. (Q Rev Econ Financ 80:272–286, 2021). - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Impacts and evolution of monetary policy shocks on macroeconomic fluctuations in Peru using regime-switching VAR models(Elsevier BV, 2026-08-01)This paper applies regime-switching VAR models with time-varying parameters and variances to analyze the impact and evolution of monetary policy shocks and their contribution to GDP growth, inflation, and the interest rate in Peru over 1994Q3–2019Q4. The approach offers an alternative and complementary perspective to Pérez Rojo and Rodrıguez (2024). The main findings are: (i) the best-fitting models incorporate regime-switching volatility; (ii) two distinct regimes emerge, coinciding with the adoption of inflation targeting (IT); (iii) the volatility of GDP growth and inflation began to decline in the early 1990s, while interest rate volatility fell sharply after IT implementation; and (iv) prior to IT, monetary policy shocks explained 15%, 30%, and 90% of the long-term forecast error variance decomposition of inflation, GDP growth, and the interest rate, respectively, but their contribution became negligible thereafter. Overall, the results are robust across alternative specifications, underscoring the stabilizing role of IT in Peru’s monetary policy framework.