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Forecasting economy with Bayesian autoregressive distributed lag model: choosing optimal prior in economic downturn
Bušs, Ginters - 2009
Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag (ADL) model is chosen. The results show that a...
Persistent link: https://www.econbiz.de/10015218160
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Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations in R
Ardia, David - 2009
time-consuming and difficult task of tuning a sampling algorithm. The usage of the package is shown in an empirical …
Persistent link: https://www.econbiz.de/10015218251
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Efficient Bayesian estimation and combination of GARCH-type models
Ardia, David; Hoogerheide, Lennart F. - 2010
used in importance sampling for model estimation, model selection and model combination. The procedure is fully automatic …
Persistent link: https://www.econbiz.de/10015221773
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Bayesian estimation of the GARCH(1,1) model with Student-t innovations
Ardia, David; Hoogerheide, Lennart F. - 2009
time-consuming and difficult task of tuning a sampling algorithm. The usage of the package is shown in an empirical …
Persistent link: https://www.econbiz.de/10015225073
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Efficient Bayesian estimation and combination of GARCH-type models
Ardia, David; Hoogerheide, Lennart F. - 2010
used in importance sampling for model estimation, model selection and model combination. The procedure is fully automatic …
Persistent link: https://www.econbiz.de/10015225074
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Bayesian estimation of the GARCH(1,1) model with Student-t innovations
Ardia, David; Hoogerheide, Lennart F. - 2009
time-consuming and difficult task of tuning a sampling algorithm. The usage of the package is shown in an empirical …
Persistent link: https://www.econbiz.de/10015226469
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Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean
Legrand, Romain - 2018
no sophisticated Kalman filtering methods and reduces to a standard Gibbs sampling algorithm. iii) as an extension, it …
Persistent link: https://www.econbiz.de/10015261554
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Bayesian dynamic variable selection in high dimensions
Korobilis, Dimitris; Koop, Gary - 2020
This paper proposes a variational Bayes algorithm for computationally efficient posterior and predictive inference in … time periods which predictors are relevant (or not) for forecasting the dependent variable. The new algorithm is evaluated …
Persistent link: https://www.econbiz.de/10015212021
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On bootstrap validity for specification tests with weak instruments
Doko Tchatoka, Firmin - 2013
This paper investigates the asymptotic validity of the bootstrap for Durbin-Wu-Hausman (DWH) specification tests when instrumental variables (IVs) may be arbitrary weak. It is shown that under strong identification, the bootstrap offers a better approximation than the usual asymptotic chi-square...
Persistent link: https://www.econbiz.de/10015237364
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On bootstrap validity for specification tests with weak instruments
Doko Tchatoka, Firmin - 2013
This paper investigates the asymptotic validity of the bootstrap for Durbin-Wu-Hausman (DWH) specification tests when instrumental variables (IVs) may be arbitrary weak. It is shown that under strong identification, the bootstrap offers a better approximation than the usual asymptotic chi-square...
Persistent link: https://www.econbiz.de/10015237400