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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 online resource (146 p.)
Soggetto topico: Technology: general issues
Soggetto non controllato: Bayesian econometrics
Bayesian estimation
Bayesian nonlinear mixed-effects regression
Bayesian TVP-SV-VAR
Bayesian VAR
Bitcoin
CES function
cryptocurrency
density forecast
density forecasting
DSGE model
dynamic model averaging
dynamic model selection
ES
fiscal policy
forecasting
forgetting factors
macroeconomic and financial applications
MCMC methods
military and civilian spending
monetary policy
point forecast
portfolio choice
sentiments
stock market predictability
time-varying volatility
transmission channel
unconventional monetary policy
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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