Term structure and real-time learning
Authors
Issue Date
31-Jan-2018
Physical description
53 p. : fórmulas, gráficos, tablas
Abstract
Este artículo incorpora la estructura temporal de tipos de interés en un modelo EGED de media escala. La extensión resulta en un modelo de predicción multiperiódico que se estima bajo dos supuestos alternativos: aprendizaje adaptativo y expectativas racionales. La información de la estructura temporal de los tipos de interés permite caracterizar las expectativas de los agentes utilizando únicamente información disponible en el momento en que los agentes forman sus expectativas en tiempo real, hecho normalmente ignorado en la literatura de aprendizaje. El modelo estimado bajo aprendizaje mejora el ajuste de los datos respecto al modelo racional. Este ajuste incluye no solo datos macroeconómicos, sino también la curva de tipos y las expectativas de las tasas de crecimiento del consumo e inflación disponibles en la Encuesta de Expertos en Previsión Económica. Los resultados de estimación muestran que la mayoría de las fuentes endógenas de persistencia agregada se reducen de forma significativa con la incorporación de la estructura temporal en el modelo de predicción multiperiódico con aprendizaje
This paper introduces the term structure of interest rates into a medium-scale DSGE model. This extension results in a multi-period forecasting model that is estimated under both adaptive learning and rational expectations. Term structure information enables us to characterize agents’ expectations in real time, which addresses an imperfect information issue mostly neglected in the adaptive learning literature. Relative to the rational expectations version, our estimated DSGE model under adaptive learning largely improves the model fit to the data, which include not just macroeconomic data but also the yield curve and the consumption growth and inflation forecasts reported in the Survey of Professional Forecasters. Moreover, the estimation results show that most endogenous sources of aggregate persistence are dramatically undercut when adaptive learning based on multi-period forecasting is incorporated through the term structure of interest rates
This paper introduces the term structure of interest rates into a medium-scale DSGE model. This extension results in a multi-period forecasting model that is estimated under both adaptive learning and rational expectations. Term structure information enables us to characterize agents’ expectations in real time, which addresses an imperfect information issue mostly neglected in the adaptive learning literature. Relative to the rational expectations version, our estimated DSGE model under adaptive learning largely improves the model fit to the data, which include not just macroeconomic data but also the yield curve and the consumption growth and inflation forecasts reported in the Survey of Professional Forecasters. Moreover, the estimation results show that most endogenous sources of aggregate persistence are dramatically undercut when adaptive learning based on multi-period forecasting is incorporated through the term structure of interest rates
Publish on
Documentos de Trabajo / Banco de España, 1803
Subjects
Aprendizaje con datos en tiempo real; Diferenciales de tipos; Predicción multiperiódica; Agentes de corto-largo horizonte; Encuesta de Expertos en Previsión Económica; Modelo de EGED de media escala; Real-time adaptive learning; Term spread; Multi-period forecasting; Short-versus long-sighted agents; SPF forecasts; Medium-scale DSGE model; Fluctuaciones y ciclos económicos; Mercados financieros; Información e incertidumbre; Modelización econométrica
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