| 000 | 03429naaaa2200673uu 4500 | ||
|---|---|---|---|
| 001 | https://directory.doabooks.org/handle/20.500.12854/69446 | ||
| 005 | 20220714181301.0 | ||
| 020 | _abooks978-3-03943-786-3 | ||
| 020 | _a9783039437856 | ||
| 020 | _a9783039437863 | ||
| 024 | 7 |
_a10.3390/books978-3-03943-786-3 _cdoi |
|
| 041 | 0 | _aEnglish | |
| 042 | _adc | ||
| 072 | 7 |
_aTB _2bicssc |
|
| 100 | 1 |
_aBernardi, Mauro _4edt _91598580 |
|
| 700 | 1 |
_aGrassi, Stefano _4edt _91598581 |
|
| 700 | 1 |
_aRavazzolo, Francesco _4edt _91598582 |
|
| 700 | 1 |
_aBernardi, Mauro _4oth _91598580 |
|
| 700 | 1 |
_aGrassi, Stefano _4oth _91598581 |
|
| 700 | 1 |
_aRavazzolo, Francesco _4oth _91598582 |
|
| 245 | 1 | 0 | _aBayesian Econometrics |
| 260 |
_aBasel, Switzerland _bMDPI - Multidisciplinary Digital Publishing Institute _c2020 |
||
| 300 | _a1 electronic resource (146 p.) | ||
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
| 520 | _aSince 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. | ||
| 540 |
_aCreative Commons _fhttps://creativecommons.org/licenses/by/4.0/ _2cc _4https://creativecommons.org/licenses/by/4.0/ |
||
| 546 | _aEnglish | ||
| 650 | 7 |
_aTechnology: general issues _2bicssc _9928609 |
|
| 653 | _aunconventional monetary policy | ||
| 653 | _atransmission channel | ||
| 653 | _aBayesian TVP-SV-VAR | ||
| 653 | _aBayesian econometrics | ||
| 653 | _aportfolio choice | ||
| 653 | _asentiments | ||
| 653 | _astock market predictability | ||
| 653 | _acryptocurrency | ||
| 653 | _aBitcoin | ||
| 653 | _aforecasting | ||
| 653 | _apoint forecast | ||
| 653 | _adensity forecast | ||
| 653 | _adynamic model averaging | ||
| 653 | _adynamic model selection | ||
| 653 | _aforgetting factors | ||
| 653 | _amilitary and civilian spending | ||
| 653 | _aDSGE model | ||
| 653 | _afiscal policy | ||
| 653 | _amonetary policy | ||
| 653 | _aBayesian estimation | ||
| 653 | _aBayesian VAR | ||
| 653 | _adensity forecasting | ||
| 653 | _atime-varying volatility | ||
| 653 | _aES | ||
| 653 | _aCES function | ||
| 653 | _aBayesian nonlinear mixed-effects regression | ||
| 653 | _aMCMC methods | ||
| 653 | _amacroeconomic and financial applications | ||
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://mdpi.com/books/pdfview/book/3250 _70 _zDOAB: download the publication |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/69446 _70 _zDOAB: description of the publication |
| 999 |
_c3001394 _d3001394 |
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