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Item type:Publication, Evolution of Monetary Policy in Peru: An Empirical Application using a Mixture Innovation TVP-VAR-SV Model(Pontificia Universidad Católica del Perú. Departamento de Economía, 2020-02)This paper discusses the evolution of monetary policy (MP) in Peru in 1996Q1-2016Q4 using a mixture innovation time-varying parameter vector autoregressive model with stochastic volatility (TVP-VAR-SV) as proposed by Koop et al. (2009). The main empirical results are: (i) the VAR coefficients and volatilities change more gradually than the covariance errors over time; (ii) the volatility of MP shocks was higher under the pre-Inflation Targeting (IT) regime; (iii) a surprise increase in the interest rate produces GDP growth falls and reduces ináation in the long run; (iv) the interest rate reacts more quickly to aggregate supply (AS) shocks than to aggregate demand (AD) shocks; (v) MP shocks explain a high percentage of domestic variable behavior under the pre-IT regime but their contribution decreases under the IT regime. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Modeling the Volatility of Returns on Commodities: An Application and Empirical Comparison of GARCH and SV Models(Pontificia Universidad Católica del Perú. Departamento de Economía, 2020-02)Seven GARCH and stochastic volatility (SV) models are used to model and compare empirically the volatility of returns on four commodities: gold, copper, oil, and natural gas. The results show evidence of fat tails and random jumps created by supply/demand imbalances, international instability episodes, geopolitical tensions, and market speculation, among other factors. We also find evidence of a leverage effect in oil and copper, resulting from their dependence on world economic activity; and of an inverse leverage effect in gold and natural gas, consistent with the formerís role as safe asset and with uncertainty about the latterís future supply. Additionally, in most cases there is no evidence of an impact of volatility on the mean. Finally, we find that the best-performing return volatility models are GARCH-t for gold, SV-t for copper and oil, and SV with leverage effects (SV-L) for natural gas.
