| 1. |
- Ankargren, Sebastian, et al.
(författare)
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A mixed-frequency Bayesian vector autoregression with a steady-state prior
- 2018
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We consider a Bayesian vector autoregressive (VAR) model allowing for an explicit priorspecication for the included variables' `steady states' (unconditional means) for data measuredat dierent frequencies. We propose a Gibbs sampler to sample from the posteriordistribution derived from a normal prior for the steady state and a normal-inverse-Wishart prior for the dynamics and error covariance. Moreover, we suggest a numerical algorithmfor computing the marginal data density that is useful for nding appropriate values for thenecessary hyperparameters. We evaluate the proposed model by applying it to a real-timedata set where we forecast Swedish GDP growth. The results indicate that the inclusionof high-frequency data improves the accuracy of low-frequency forecasts, in particular forshorter time horizons. The proposed model thus facilitates a simple and helpful way ofincorporating information about the long run through the steady-state prior as well asabout the near future through its ability to cope with mixed frequencies of the data.
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| 2. |
- Ankargren, Sebastian, et al.
(författare)
-
Estimating a VECM for a small open economy
- 2018
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- One of the most popular ways to model macro economic variables is bythe vector error correction model (VECM). Besides forecasting and testing ofhypotheses, the VECM is often used for calculating impulse responses, whichdescribe how shocks today aect the variables in the future. In economic theory,a small open economy denotes the economy of a country which is toosmall to inuence the surrounding world. The surrounding world can, for thisreason, be seen as exogenous relative to the economy of this small open economy.The main contribution of this paper is the proposal of how to estimatea VECM with exogeneity restrictions on both the short-run dynamics andthe short-run adjustment parameters between small open economies and thesurrounding world. A Monte Carlo simulation of impulse responses showsthat the proposed model is considerably more ecient compared to modelsfully or partially ignoring exogeneity. It is also shown that the empirical sizewhen testing for the number of long-run relations is closer to the nominalsize. Using two Swedish macroeconomic data sets the proposed method isapplied to estimate the models under weak exogeneity and Granger noncausality,respectively. We nd for some variables large deviances in impulseresponses between our proposed model incorporating both types of restrictionsand models using none or only one type of restriction, thus illustratingthe need for imposing the full set of restrictions instead of settling for just one.
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| 3. |
- Ankargren, Sebastian, et al.
(författare)
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On the least-squares model averaging interval estimator
- 2018
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Ingår i: Communications in Statistics - Theory and Methods. - : Informa UK Limited. - 0361-0926 .- 1532-415X. ; 47:1, s. 118-132
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Tidskriftsartikel (refereegranskat)abstract
- In many applications of linear regression models, randomness due to model selection is commonly ignored in post-model selection inference. In order to account for the model selection uncertainty, least-squares frequentist model averaging has been proposed recently. We show that the confidence interval from model averaging is asymptotically equivalent to the confidence interval from the full model. The finite-sample confidence intervals based on approximations to the asymptotic distributions are also equivalent if the parameter of interest is a linear function of the regression coefficients. Furthermore, we demonstrate that this equivalence also holds for prediction intervals constructed in the same fashion.
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