Bayesian Econometrics
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, mode...
Zapisane w:
| Format: | Online |
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| Język: | angielski |
| Wydane: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Hasła przedmiotowe: | |
| Dostęp online: | ONIX_20210501_9783039437856_1192 |
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| _version_ | 1869521207181705216 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-69446 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-694462024-04-09T23:16:41Z Bayesian Econometrics Bernardi, Mauro Grassi, Stefano Ravazzolo, Francesco 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 thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues 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. 2021-05-01T15:49:50Z 2021-05-01T15:49:50Z 2020 book ONIX_20210501_9783039437856_1192 9783039437856 9783039437863 https://directory.doabooks.org/handle/20.500.12854/69446 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/3250 https://mdpi.com/books/pdfview/book/3250 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03943-786-3 10.3390/books978-3-03943-786-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039437856 9783039437863 146 Basel, Switzerland open access |
| spellingShingle | 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 thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues Bayesian Econometrics |
| title | Bayesian Econometrics |
| title_full | Bayesian Econometrics |
| title_fullStr | Bayesian Econometrics |
| title_full_unstemmed | Bayesian Econometrics |
| title_short | Bayesian Econometrics |
| title_sort | bayesian econometrics |
| topic | 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 thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues |
| topic_facet | 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 thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues |
| url | ONIX_20210501_9783039437856_1192 |