Factores macroeconómicos y climáticos que inciden sobre la volatilidad de precios de los commodities peruanos, periodo 2008-2019

Descripción del Articulo

This research analyzed the determinants of price volatility in commodities traded in Peru during the 2008-2019 period, focusing on three potential factors: worldwide commodity production, Peruvian exports, and global temperature. Through the application of GARCH(1,1) models for volatility estimation...

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Detalles Bibliográficos
Autor: López Rojas, Mario Andre
Formato: tesis doctoral
Fecha de Publicación:2025
Institución:Universidad Nacional De La Amazonía Peruana
Repositorio:UNAPIquitos-Institucional
Lenguaje:español
OAI Identifier:oai:repositorio.unapiquitos.edu.pe:20.500.12737/11579
Enlace del recurso:https://hdl.handle.net/20.500.12737/11579
Nivel de acceso:acceso abierto
Materia:Fluctuaciones económicas
Precios
Materias primas
Mercado internacional
Indicadores macroeconómicos
Factores climáticos
https://purl.org/pe-repo/ocde/ford#5.02.01
Descripción
Sumario:This research analyzed the determinants of price volatility in commodities traded in Peru during the 2008-2019 period, focusing on three potential factors: worldwide commodity production, Peruvian exports, and global temperature. Through the application of GARCH(1,1) models for volatility estimation and subsequent multiple regressions, it was found that, contrary to the hypotheses proposed, worldwide production shows a negative and significant relationship with price volatility (coefficient -0.01788, p-value=0.0354), suggesting a market stabilizing effect. Peruvian exports showed a negative but non-significant coefficient (-0.000005958, p-value=0.1273), while global temperature did not evidence a statistically detectable relationship with volatility (coefficient 0.00321, p-value=0.6524). The most robust finding was the high persistence of volatility, with a highly significant autoregressive component (coefficient 0.7817, p-value=0.1273), while global temperature did not evidence a statistically detectable relationship with volatility (coefficient 0.00321, p-value=0.6524). The most robust finding was the high persistence of volatility, with a highly significant autoregressive component (coefficient 0.7817, p-value<2e-16), explaining approximately 78% of current volatility.
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