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Item type:Publication, Time evolution of external shocks on macroeconomic fluctuations in Pacific Alliance countries: empirical application using TVP-VAR-SV models(Pontificia Universidad Católica del Perú, 2022-03)This article provides empirical evidence on the evolution of the impact of external shocks on the macroeconomic dynamics of the Pacific Alliance (PA) countries. For this purpose, we estimate a family of VAR models that allows time variation (or constancy) of parameters, including the variance matrix (TVP-VAR-SV). The results suggest that: (i) fluctuations from China create the most significant and persistent responses: a 1% increase in China’s growth raises growth by 0.3%-0.4% during the first year in Chile, Colombia, and Mexico; and by 0.8% in Peru; (ii) responses to export price shocks evolve considerably over time; e.g., the impact on growth in Chile and Peru tripled in 1994-2009 and then moderated until 2019; and (iii) unexpected Fed rate increases result in significant increases in AP countries’ monetary policy rates, an effect that escalates during crisis periods and further deepens the negative impact on domestic output growth. Additionally, variance decomposition shows that external factors explained over 50% of deviations in the domestic variables considered in this work. In particular, the results show that external shock absorption over the sample is higher in Mexico and Peru. In contrast, the change in domestic dynamics in absence of external disturbances would have been milder in Chile and Colombia. Finally, we perform four robustness exercises, which imply the following modifications to the baseline model: (i) changing priors; (ii) modifying two external variables; (iii) using lowdimensional models (4, 5, and 6 variables); and (iv) expanding the model by adding a fiscal policy variable. The results do not change significantly relative to those found using the baseline model. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Regime-Switching, Stochastic Volatility, Fiscal Policy Shocks and Macroeconomic Fluctuations in Peru(Pontificia Universidad Católica del Perú. Departamento de Economía, 2024-10)Following Chan and Eisenstat (2018a), we use a family of regime-switching models with time-varying parameters and stochastic volatility (RS-VAR-SV) to analyze the evolution of fiscal shocks impacts on Peru's economic growth from 1995Q1 to 2019Q4. Key findings include: (i) identification of two distinct economic regimes with different macroeconomic fundamentals tied to improvements in fiscal and monetary policy; (ii) enhanced model fi with the inclusion of stochastic volatility; (iii) a positive trend in the size of spending multipliers, though they remain below unity; (iv) during the 2008 Global Financial Crisis, capital expenditure shocks mitigated the decline in economic growth by 2 percentage points, highlighting their counter-cyclical potential. These findings are corroborated by robustness checks, which include changes in priors, variable reordering, adjustments in external and demand variables, and extending the sample to 2022Q4 to encompass the COVID-19 crisis. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Impact of Monetary Policy Shocks in the Peruvian Economy Over Time(Pontificia Universidad Católica del Perú. Departamento de Economía, 2023-08)We investigate the evolution of the impact of monetary policy (MP) shocks in Peru in 1996Q1-2018Q2 using a set of time-varying parameter vector autoregressive models with stochastic volatility (TVP-VAR- SV), as proposed by Chan and Eisenstat (2018). The main results are: (i) the volatilities, intercepts, and contemporaneous coe cients change more gradually than VAR coe cients over time; (ii) the volatility of MP shocks falls from 4% to 0.3% on average during the In ation Targeting (IT) regime; (iii) in the long run, a contractionary MP shock decreases both gross domestic product (GDP) growth and in ation by 0.28% and 0.1%, respectively; (iv) the interest rate reacts faster to aggregate supply shocks than to both aggregate demand shocks and exchange rate shocks; (v) under the pre-IT regime, MP shocks explain almost 20%, 10%, and 85% of the uncertainty in GDP growth, in ation, and the interest rate, respectively; and under the IT regime, all these percentages shrink to 1-2%. The sensitivity analysis con rms the robustness of the main results across various prior speci cations, measures of external and domestic variables, and recursive identi cations. In general, the results show that MP has contributed to diminishing macroeconomic volatility in Peru. - 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Time-Varying Effects of Financial Uncertainty Shocks on Macroeconomic Fluctuations in Peru(Pontificia Universidad Católica del Perú. Departamento de Economía, 2024-01)This article employs a family of VAR models with time-varying parameters and stochastic volatility (TVP-VAR-SV) to estimate the impact of external financial uncertainty shocks on a set of macroeconomic variables in Peru for the period from 1996Q1 to 2022Q4. The main findings can be summarized as follows: (i) a simple VAR model with stochastic volatility is sufficient to capture uncertainty dynamics compared to TVP-VAR alternatives; (ii) uncertainty shocks have a negative and significant impact on private investment growth in the medium and long term; (iii) the impact on private investment growth is three times greater than that on GDP growth; (iv) uncertainty shocks behave like aggregate supply shocks, leading to an increase in the inflation rate; and (v) uncertainty shocks have stronger effects in scenarios characterized by unfavorable financial conditions. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 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.