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    Regime-Switching, stochastic volatilty and impacts of monetary policy shocks on macroeconomic fluctuations in Peru
    (Pontificia Universidad Católica del Perú. Departamento de Economía, 2024-08)
    This paper utilizes regime-switching VAR models with stochastic volatility (RS-VAR-SV) to analyze the impact and evolution of monetary policy shocks and their contribution to the dynamics of GDP growth, inflation, and the interest rate in Peru for the period from 1994Q3 to 2019Q4. The main findings are: (i) the best-fifting models incorporate only SV; (ii) there are two distinct regimes coinciding with the implementation of the inflation targeting (IT) scheme; (iii) the volatility of GDP growth and inflation began to decrease in the early 1990s, while interest rate volatility declined following IT implementation; and (iv) pre-IT, monetary policy shocks accounted for 15%, 30%, and 90% of the forecast error variance decomposition for in ation, GDP growth, and the interest rate in the long term, respectively. Following IT adoption, monetary policy ceased to be a source of uncertainty for the economy. These results are robust to changes in priors, domestic and external variables, the number of regimes, and the ordering and number of variables of the model.
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    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.