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Evolution of the effects of mineral commodity prices on fiscal fluctuations: empirical evidence from TVP-VAR-SV models for Peru

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Abstract

This paper studies the evolution of the effects of fluctuations in mineral commodity prices on fiscal variables, especially those associated with fiscal revenues, in Peru by means of VAR models with time-varying parameters and stochastic volatility (TVP-VAR-SV). We compare different alternative specifications using the marginal likelihood and the deviance information criterion, which show that it is essential to consider stochastic volatility. It is found that an increase of 1% in the growth of mineral commodity prices generates increases of around 1.5 and 2.5% in the growth of taxes from mining and mining canon, respectively, thus reflecting a remarkable sensitivity of these variables to external shocks. In turn, these responses are increasingly more pronounced until reaching a peak around 2009 and then decrease, which is in line with the dynamics of the commodities boom. In the variance decomposition, the importance of shocks in mineral commodity prices in explaining fluctuations in taxes from mining and mining canon increases in line with the increasing tendency of mineral prices until the Great Recession, where shocks in mineral commodity prices explain between 40 and 50% of fluctuations in taxes from mining and mining canon, and then it is reduced. This shows the importance of allowing time-varying parameters and stochastic volatility in contrast with a standard VAR.

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Notes

  1. In addition, we consider regime-switching models like those in Sims and Zha (2006). Thus, let \(S_{t}\in \{1,\ldots ,r\}\) denote the regime indicator at time t, such that r is the number of regimes, the regime-switching model (RS-VAR) is given by: \(B_{0,S_{t}}y_{t}= \mu _{S_{t}}+\sum _{j=1}^{p}B_{j,S_{t}}y_{t-j}+\epsilon _{t},\) where \(\epsilon _{t}\sim N(0,\Sigma _{S_{t}})\) and each parameter is estimated within an specific regime. We also consider two restricted versions of this model, namely, RS-VAR-R1, which assumes that VAR coefficients are the same across regimes, and RS-VAR-R2, which assumes that the covariance matrices are the same across regimes.

  2. This index is calculated by assigning differentiated weights for various metals and minerals according to World Bank’s estimation of the respective export values.

  3. The results of the log marginal likelihood for the regime-switching models are available upon request. The DIC is not calculated for them since the posterior distributions under these models typically have multiple modes, making the calculation of the DIC difficult (besides the fact that regime-switching models tend to exhibit bad performance).

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Authors and Affiliations

  1. Department of Economics, Universidad de Lima, Lima, Peru

    Dante A. Urbina

  2. Department of Economics, Pontificia Universidad Católica del Perú, 1801 Universitaria Avenue, Lima 32, Lima, Peru

    Dante A. Urbina & Gabriel Rodríguez

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  1. Dante A. Urbina
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Correspondence to Gabriel Rodríguez.

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This paper is drawn from the second Chapter of the PhD Thesis of Dante A. Urbina, Graduate School of the Pontificia Universidad Católica del Perú (PUCP). The authors thank the useful comments provided by Patricia Tovar, Jorge Rojas, Alejandro Lugón, Luis García, José Távara, Waldo Mendoza, Bienvenido Ortega Aguaza, and Yuri Landa Arroyo. We also appreciate the advice of the Editors Laura Alfaro and Katheryn (Kadee) Russ. Any remaining errors are our responsibility.

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Urbina, D.A., Rodríguez, G. Evolution of the effects of mineral commodity prices on fiscal fluctuations: empirical evidence from TVP-VAR-SV models for Peru. Rev World Econ 159, 153–184 (2023). https://doi.org/10.1007/s10290-022-00460-7

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