Temat: Bayesian analysis - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Bayesian Analysis of Weak Form Reduced Rank Structure in VEC Models
Autorzy:: Wróblewska, Justyna
Tematy:: cointegration
Bayesian analysis
common cyclical features; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/483347.pdf Link otwiera się w nowym oknie
Opis:: The concept of cointegration that enables the proper statistical analysis of long-run comovements between unit root processes has been of great interest to numerous economic investigators since it was introduced. However, investigation of short-run comovement between economic time series seems equally important, especially for economic decision-makers. The concept of common features and based on it the idea of two additional reduced rank structure forms in a VEC model (the strong and the weak one) may be of some help. The strong form reduced rank structure (SF) takes place when at least one linear combination of the first differences of the variables exists, which is white noise. However, when this assumption seems too strong, the weaker case can be considered. The weak form appears when the linear combination of first differences adjusted for long-run efects exists, which is white noise. The main focus of this paper is a Bayesian analysis of the VEC models involving the weak form of reduced rank restrictions. After the introduction and discussion of the said Bayesian model, the presented methods will be illustrated by an empirical investigation of the price - wage spiral in the Polish economy.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: AIC, BIC, Bayesian evidence against the interacting dark energy model
Autorzy:: Krawiec, Adam
Kurek, Aleksandra
Kamionka, Michał
Szydłowski, Marek
Opis:: Recent astronomical observations have indicated that the Universe is in a phase of accelerated expansion. While there are many cosmological models which try to explain this phenomenon, we focus on the interacting $\Lambda$ CDM model where an interaction between the dark energy and dark matter sectors takes place. This model is compared to its simpler alternative—the $\Lambda$ CDM model. To choose between these models the likelihood ratio test was applied as well as the model comparison methods (employing Occam’s principle): the Akaike information criterion (AIC), the Bayesian information criterion (BIC) and the Bayesian evidence. Using the current astronomical data: type Ia supernova (Union2.1), h(z)h(z), baryon acoustic oscillation, the Alcock–Paczynski test, and the cosmic microwave background data, we evaluated both models. The analyses based on the AIC indicated that there is less support for the interacting $\Lambda$ CDM model when compared to the $\Lambda$ CDM model, while those based on the BIC indicated that there is strong evidence against it in favor of the $\Lambda$ CDM model. Given the weak or almost non-existing support for the interacting $\Lambda$ CDM model and bearing in mind Occam’s razor we are inclined to reject this model.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

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Skocz do pozycji: 3.

Tytuł:: One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models
Autorzy:: Wróblewska, Justyna
Pajor, Anna
Opis:: The paper aims at comparing forecast ability of VAR/VEC models witha non-changing covariance matrix and two classes of Bayesian Vector ErrorCorrection – Stochastic Volatility (VEC-SV) models, which combine the VECrepresentation of a VAR structure with stochastic volatility, represented by theMultiplicative Stochastic Factor (MSF) process, the SBEKK form or the MSF-SBEKK specification.Based on macro-data coming from the Polish economy (time series ofunemployment, inflation and interest rates) we evaluate predictive densityfunctions employing of such measures as log predictive density score, continuousrank probability score, energy score, probability integral transform. Eachof them takes account of different feature of the obtained predictive densityfunctions.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

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Skocz do pozycji: 4.

Tytuł:: One-Period Joint Forecasts of Polish Inflation, Unemployment and Interest Rate Using Bayesian VEC-MSF Models
Autorzy:: Wróblewska, Justyna
Pajor, Anna
Tematy:: cointegration
stochastic volatility
Bayesian analysis
forecast verification; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czasopisma i Monografie PAN
Powiązania:: https://bibliotekanauki.pl/articles/55789970.pdf Link otwiera się w nowym oknie
Opis:: The paper aims at comparing forecast ability of VAR/VEC models with a non-changing covariance matrix and two classes of Bayesian Vector Error Correction – Stochastic Volatility (VEC-SV) models, which combine the VEC representation of a VAR structure with stochastic volatility, represented by the Multiplicative Stochastic Factor (MSF) process, the SBEKK form or the MSF-SBEKK specification. Based on macro-data coming from the Polish economy (time series of unemployment, inflation and interest rates) we evaluate predictive density functions employing of such measures as log predictive density score, continuous rank probability score, energy score, probability integral transform. Each of them takes account of different feature of the obtained predictive density functions.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Bayesian Model Selection in the Analysis of Cointegration
Autorzy:: Wróblewska, Justyna
Tematy:: cointegration
Bayesian analysis
Grassmann manifold
Stiefel manifold
posterior probability; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/483357.pdf Link otwiera się w nowym oknie
Opis:: In this paper we present the Bayesian model selection procedure within the class of cointegrated processes. In order to make inference about the cointegration space we use the class of Matrix Angular Central Gaussian distributions. To carry out posterior simulations we use an alorithm based on the collapsed Gibbs sampler. The presented methods are applied to the analysis of the price - wage mechanism in the Polish economy.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Bayesian Inference for State Space Model with Panel Data
Autorzy:: Pandey, Ranjita
Chaturvedi, Anoop
Tematy:: Bayesian analysis
Gibbs sampler
conditional posterior densities
predictive distribution; Pokaż więcej
Wydawca:: Główny Urząd Statystyczny
Powiązania:: https://bibliotekanauki.pl/articles/466044.pdf Link otwiera się w nowym oknie
Opis:: The present work explores panel data set-up in a Bayesian state space model. The conditional posterior densities of parameters are utilized to determine the marginal posterior densities using the Gibbs sampler. An efficient one step ahead predictive density mechanism is developed to further the state of art in prediction-based decision making.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 7.

Tytuł:: Bayesian Estimation of Capital Stock and Depreciation in the Production Function Framework
Autorzy:: Boratyński, Jakub
Osiewalski, Jacek
Tematy:: productive capital stock
depreciation rate
aggregate production function
Bayesian analysis; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2075283.pdf Link otwiera się w nowym oknie
Opis:: We propose a Bayesian approach to estimating productive capital stocks and depreciation rates within the production function framework, using annual data on output, employment and investment only. Productive capital stock is a concept related to the input of capital services to production, in contrast to the more common net capital stock estimates, representing market value of fixed assets. We formulate a full Bayesian model and employ it in a series of illustrative empirical examples. We find that parameters of our model, from which the time-path of capital is derived, are weakly identified with the data at hand. Nevertheless, estimation is feasible with the use of prior information on the production function parameters and the characteristics of productivity growth. We show how precision of the estimates can be improved by augmenting the model with an equation for the rate of return
Dostawca treści:: Biblioteka Nauki

Artykuł

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Skocz do pozycji: 8.

Tytuł:: Bayesian Analysis of Weak Form Polynomial Reduced Rank Structures in VEC Models
Autorzy:: Wróblewska, Justyna
Tematy:: cointegration
Bayesian analysis
polynomial common cyclical features
permanent-transitory decompostion; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/483287.pdf Link otwiera się w nowym oknie
Opis:: The main goal of the paper is the Bayesian analysis of weak form polynomial serial correlation common features together with cointegration. In the VEC model the serial correlation common feature leads to an additional reduced rank restriction imposed on the model parameters. After the introduction and discussion of the model, the methods will be illustrated with an empirical investigation of the price-wage nexus in the Polish economy. Additionally, consequences of imposing such additional short-run restrictions for permanent-transitory decomposition will be discussed.
Dostawca treści:: Biblioteka Nauki

Artykuł

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Skocz do pozycji: 9.

Tytuł:: Przegląd Archeologiczny T. 67 (2019)
The chronology and periodization of the Bronze and the early Iron Age burial ground in Domasław, Wrocław district, based on radiocarbon dating
Chronologia i periodyzacja cmentarzyska z epoki brązu i wczesnej epoki żelaza w Domasławiu, pow. wrocławski, na podstawie datowania radiowęglowego
Autorzy:: Goslar, Tomasz
Wydawca:: Instytut Archeologii i Etnologii Polskiej Akademii Nauk
Ośrodek Badań nad Kulturą Późnego Antyku i Wczesnego Średniowiecza
Powiązania:: Przegląd Archeologiczny
Opis:: il. ; 29 cm
ill. ; 29 cm
The article presents the results of the radiocarbon dating and Bayesian analysis of 14C dates of bones from the burial ground in Domasław. The Bayesian analysis used the relative chronology obtained based on the characteristic features of grave goods and the assigning of individual burials to specific periods of the late Bronze Age (III EB – V EB ) or the early Iron Age (HC – LtA). A coherent chronological model of the burial ground was accepted after assuming that graves with transitional features, attributable to two subsequent periods, could have been contemporary of graves from one or the other period. The temporal frames of particular periods calculated by the model allow us to improve previously published chronological diagrams of the late Bronze Age and the early Iron Age in the region.
Dostawca treści:: RCIN - Repozytorium Cyfrowe Instytutów Naukowych

Książka

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Skocz do pozycji: 10.

Tytuł:: Bayesian Analysis of Stochastic Volatility Model and Portfolio Allocation
Bayesowska analiza modelu zmienności stochastycznej w optymalizacji portfela
Autorzy:: Pajor, Anna
Tematy:: multivariate stochastic volatility model
Bayesian analysis
portfolio allocation
Markov chain Monte Carlo; Pokaż więcej
Wydawca:: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Powiązania:: https://bibliotekanauki.pl/articles/907594.pdf Link otwiera się w nowym oknie
Opis:: In this paper we present the multivariate stochastic volatility model based on the Cholesky decomposition. This model and the Bayesian approach is used to model bivariate daily financial time series and construct an optimal portfolio. We consider the hypothetical portfolios consisted of two currencies that were most important for the Polish economy: the US dollar and the German mark. In the optimization process we used the predictive distributions of future returns and the predictive covariance matrix obtained from the MSV model.
W artykule przedstawiono model zmienności stochastycznej, oparty na dekompozycji Choleskiego. Następnie model SV oraz podejście Bayesowskie zostało wykorzystane do modelowania zmienności dwuwymiarowych finansowych szeregów czasowych oraz budowy optymalnego portfela walutowego. Rozważono hipotetyczny portfel, w skład którego wchodzą złotówkowe kursy dwóch walut: dolara amerykańskiego i marki niemieckiej. W procesie optymalizacji portfela wykorzystano predyktywny rozkład stóp zwrotu oraz predyktywny rozkład macierzy warunkowych kowariancji, uzyskany w rozważanym modelu MSV za pomocą metod Monte Carlo (MCMC).
Dostawca treści:: Biblioteka Nauki

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