Palabras clave
Inferencia bayesiana
Monte Carlo Hamiltoniano
Inflación y crecimiento del producto
Bivariate GARCH-M models
Bayesian inference
Hamiltonian Monte Carlo
Inflation and output growth
Cómo citar
Resumen
El modelo GARCH (modelo autorregresivo condicional heterocedástico generalizado) es un modelo estadístico para series de tiempo usado para describir la varianza del error como una función de los errores al cuadrado pasados y de las varianzas. Estos modelos GARCH son usados para modelar la volatilidad variando en el tiempo y los clusters de volatilidad. Si además el efecto de la varianza es incluido en las observaciones para predecir la media, se tiene un GARCH-M (GARCH en media). En este artículo, se analizan estos modelos en un contexto bayesiano para series de tiempo bivariadas, donde las observaciones son asumidas de comportarse como un modelo VAR-GARCH-M. Una aplicación del modelo bivariado es ajustado para medir el efecto de la variabilidad de la inflación y crecimiento del producto en la media de la inflación y crecimiento del producto.
Citas
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