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Wyszukujesz frazę "Bayesian shrinkage" wg kryterium: Temat

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    Wyświetlanie 1-3 z 3
    Tytuł:
    Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality
    Autorzy:
    Stelmasiak, Damian
    Szafrański, Grzegorz
    Powiązania:
    https://bibliotekanauki.pl/articles/2076506.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Bayesian shrinkage
    VAR models
    seasonality
    forecasting inflation
    density-based scores
    Opis:
    Bayesian VAR (BVAR) models offer a practical solution to the parameter proliferation concerns as they allow to introduce a priori information on seasonality and persistence of inflation in a multivariate framework. We investigate alternative prior specifications in the case of time series with a clear seasonal pattern. In the empirical part we forecast the monthly headline inflation in the Polish economy over the period 2011-2014 employing two popular BVAR frameworks: a steady-state reduced-form BVAR and just-identified structural BVAR model. To evaluate the forecast performance we use the pseudo realtime vintages of timely information from consumer and financial markets. We compare different models in terms of both point and density forecasts. Using formal testing procedure for density-based scores we provide the empirical evidence of superiority of the steady-state BVAR specifications with tight seasonal priors.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2016, 1; 21-42
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bayesian combined forecasts and Monte Carlo simulations to improve inflation rate predictions in Romania
    Autorzy:
    Simionescu, Mihaela
    Powiązania:
    https://bibliotekanauki.pl/articles/692557.pdf
    Data publikacji:
    2020
    Wydawca:
    Uniwersytet Ekonomiczny w Poznaniu
    Tematy:
    forecasts accuracy
    Bayesian forecasts combination
    shrinkage parameter
    econometric model
    Opis:
    In this paper we applied the regression approach and Bayesian inference to obtain more accurate forecasts of the inflation rate in the case of the Romanian economy. The necessity of using the most accurate forecasts for the inflation rate is required by the realisation of economic criteria for the accession to the eurozone and by the inflation targeting strategy of the National Bank of Romania. Considering the assumption that simple econometric models provide better forecasts than complex models, in this paper we combined various forecasts from individual models using as prior information the expectations of experts. The empirical findings for Romanian inflation rate forecasts over the horizon of 2016-2018 indicated that a fixed effects model performed better than other simple models (autoregressive moving average model, dynamic model, simple and multiple linear model, VAR, Bayesian VAR, simultaneous equations model). The Bayesian combined forecasts that used experts’ predictions as priors, with a shrinkage parameter tending to infinity, improved the accuracy of all predictions using individual models, outperforming also naïve forecasts and zero and equal weights forecasts. However, predictions based on Monte Carlo simulation outperformed all the scenarios in terms of the mean error and mean absolute error.  
    Źródło:
    Research Papers in Economics and Finance; 2020, 4, 1; 7-20
    2543-6430
    Pojawia się w:
    Research Papers in Economics and Finance
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bayesian combined forecasts and Monte Carlo simulations to improve inflation rate predictions in Romania
    Autorzy:
    Simionescu, Mihaela
    Powiązania:
    https://bibliotekanauki.pl/articles/692571.pdf
    Data publikacji:
    2020
    Wydawca:
    Uniwersytet Ekonomiczny w Poznaniu
    Tematy:
    forecasts accuracy
    Bayesian forecasts combination
    shrinkage parameter
    econometric model
    Opis:
    In this paper we applied the regression approach and Bayesian inference to obtain more accurate forecasts of the inflation rate in the case of the Romanian economy. The necessity of using the most accurate forecasts for the inflation rate is required by the realisation of economic criteria for the accession to the eurozone and by the inflation targeting strategy of the National Bank of Romania. Considering the assumption that simple econometric models provide better forecasts than complex models, in this paper we combined various forecasts from individual models using as prior information the expectations of experts. The empirical findings for Romanian inflation rate forecasts over the horizon of 2016-2018 indicated that a fixed effects model performed better than other simple models (autoregressive moving average model, dynamic model, simple and multiple linear model, VAR, Bayesian VAR, simultaneous equations model). The Bayesian combined forecasts that used experts’ predictions as priors, with a shrinkage parameter tending to infinity, improved the accuracy of all predictions using individual models, outperforming also naïve forecasts and zero and equal weights forecasts. However, predictions based on Monte Carlo simulation outperformed all the scenarios in terms of the mean error and mean absolute error.  
    Źródło:
    Research Papers in Economics and Finance; 2020, 4, 1; 7-20
    2543-6430
    Pojawia się w:
    Research Papers in Economics and Finance
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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