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Item type:Publication, Presidential approval in Peru: an empirical analysis using a fractionally cointegrated VAR(Springer, 2022-08-01)Presidential approval in Peru depends on economic outcomes. However, voters are unable to distinguish between outcomes resulting from economic policies and those caused by exogenous external factors. Estimation results from seven Fractional Cointegrated VAR (FCVAR) models suggest that presidential approval increases with the monetary policy interest rate, the terms of trade, and manufacturing employment; and decreases with the nominal PEN/USD exchange rate and inflation volatility. Additionally, a Principal Components Analysis (PCA) conducted over a large set of macroeconomic indicators points to a greater influence of external over domestic factors in explaining presidential approval; i.e., economic outcomes that determine the dynamics of presidential approval are not under presidential control in Peru. It can be argued that these findings identify a significant source of political instability and a considerable challenge to democratic governance. To the authors’ best knowledge, this is the first application of fractional cointegration analysis to political economy in Latin America. - 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.