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Bayesian Econometrics



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Autore: Bernardi Mauro Visualizza persona
Titolo: Bayesian Econometrics Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica: 1 electronic resource (146 p.)
Soggetto topico: Technology: general issues
Soggetto non controllato: unconventional monetary policy
transmission channel
Bayesian TVP-SV-VAR
Bayesian econometrics
portfolio choice
sentiments
stock market predictability
cryptocurrency
Bitcoin
forecasting
point forecast
density forecast
dynamic model averaging
dynamic model selection
forgetting factors
military and civilian spending
DSGE model
fiscal policy
monetary policy
Bayesian estimation
Bayesian VAR
density forecasting
time-varying volatility
ES
CES function
Bayesian nonlinear mixed-effects regression
MCMC methods
macroeconomic and financial applications
Persona (resp. second.): GrassiStefano
RavazzoloFrancesco
BernardiMauro
Sommario/riassunto: Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data, models, parameters and parameter restriction uncertainties, in a unified and coherent framework. This book contributes to this literature by collecting a set of carefully evaluated contributions that are grouped amongst two topics in financial economics. The first three papers refer to macro-finance issues for real economy, including the elasticity of factor substitution (ES) in the Cobb–Douglas production function, the effects of government public spending components, and quantitative easing, monetary policy and economics. The last three contributions focus on cryptocurrency and stock market predictability. All arguments are central ingredients in the current economic discussion and their importance has only been further emphasized by the COVID-19 crisis.
Titolo autorizzato: Bayesian Econometrics  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910557102303321
Lo trovi qui: Univ. Federico II
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