Unobserved Component Model for Forecasting Polish Inflation

This paper aims to use the local level models with GARCH and SV errors to predict Polish inflation. The series to be forecast, measured monthly, is consumer price index (CPI) in Poland during 1992-2008. We selected three forecasting models i.e. LL-GARCH(1,1) with Normal or Student errors and LL-SV. A simple AR(2)-SV model is used as a benchmark to assess the accuracy of prediction. The presented results indicate, that there is no clear advantage of LL models in forecasting Polish inflation over standard AR(2)-SV model, although all the models give satisfactory results

Bayesian Model Averaging for Autoregressive Distributed Lag (BMA_ADL) in gretl

This paper presents a software package that implements Bayesian Model Averaging for Autoregressive Distributed Lag models BMA_ADL ver.~0.9 in gretl. Gretl (the GNU regression, econometrics and time-series library) is an increasingly popular free, open-source software for econometric analysis with an easy-to-use graphical user interface. Bayesian Model Averaging (BMA) incorporates model uncertainty into conclusions about the estimated parameters. It is an efficient tool for discovering the most likely models and variables by obtaining estimates of their posterior characteristics

Bayesian Model Averaging for Autoregressive Distributed Lag (BMA_ADL) in gretl

This paper presents a software package that implements Bayesian Model Averaging for Autoregressive Distributed Lag models BMA_ADL ver.~0.9 in gretl. Gretl (the GNU regression, econometrics and time-series library) is an increasingly popular free, open-source software for econometric analysis with an easy-to-use graphical user interface. Bayesian Model Averaging (BMA) incorporates model uncertainty into conclusions about the estimated parameters. It is an efficient tool for discovering the most likely models and variables by obtaining estimates of their posterior characteristics

Bayesian Model Averaging and Jointness Measures for gretl

This paper presents a software package that implements Bayesian model averaging for gretl, the GNU regression, econometrics and time-series library. Bayesian model averaging is a model-building strategy that takes account of model uncertainty in conclusions about estimated parameters. It is an efficient tool for discovering the most probable models and obtaining estimates of their posterior characteristics. In recent years we have observed an increasing number of software packages devoted to Bayesian model averaging for different statistical and econometric software. In this paper, we propose the BMA package for gretl, which is an increasingly popular free, open-source software for econometric analysis with an easy-to-use graphical user interface. We introduce the BMA package for linear regression models with jointness measures proposed by Ley and Steel (2007) and Doppelhofer and Weeks (2009)

Prognozowanie inflacji w Polsce przy użyciu modelu Stocka i Watsona

The paper presents various types of local level model, which are based on Stock and Watson’s model, recently proposed forU.S.inflation. The main purpose is to use many different local level model specifications, especially with Normal GARCH and Student-t GARCH disturbances, to predict Polish inflation. The paper is a full Bayesian analysis and concerns Consumer Price Index (CPI) inPolandduring 1992-2008. The presented results indicate, that standard AR(2)-SV is quite suitable for the prediction of Polish inflation.W artykule przeprowadzono badania dotyczące trafności prognoz otrzymanych za pomocą modelu Stocka i Watsona. Rozważono różne postacie tego modelu i zbadano, które z nich dają możliwość uzyskania najtrafniejszej prognozy. Badania empiryczne dotyczyły inflacji w Polsce w latach 1992–2008. Ostatni rok posłużył do oceny jakości prognoz. Badania przeprowadzono na podstawie wskaźnika cen konsumenta CPI. Uzyskane wyniki nie potwierdzają jednoznacznej przewagi modelu Stocka i Watsona, w prognozowaniu inflacji, nad standardowym modelem autoregresyjnym

Phylogeography of Swertia perennis in Europe based on cpDNA markers

Background. Swertia perennis (Gentianaceae) is a perennial diploid and clonal plant species that is discontinuously distributed in peat bogs in the mountains of Europe, Asia and North America as well as in the lowlands of Europe. The current geographical dispersion of S. perennis is probably the result of quaternary climatic changes that have played an important role in determining the distribution of Swertia and other plant and animal species. Methods. In this study we used molecular techniques and combined data from chloroplast DNA markers (trnLF region and trnH-psbA spacer) to elucidate the phylogeography of S. perennis in Europe. Plants were collected from 28 populations in different locations in the lowlands and mountainous areas of Europe (e.g., the Carpathians, Sudetes, Bohemian Forest and Alps). cDNA was analysed to detect the genetic relationship between specimens from different locations. Results. A total of 20 haplotypes were identified across the dataset. They were characterised by a high level of genetic variability but showed a lack of phylogeographical structure. This pattern may be the result of repeated recolonization and expansion from several areas. Such genetic differentiation may also be attributed to the relatively long-term isolation of S. perennis in Pleistocene refugia in Europe, which resulted in independent separation of different cpDNA phylogenetic lineages and variation in the nucleotide composition of cpDNA. Discussion. The lack of strong phylogeographical structure makes it impossible to indicate the centre of haplotype diversity; however, refugia located in the Carpathians, Sudetes or Alps are the most probable sites where S. perennis existed in Europe. This lack of structure may also indicate a high level of gene flow in times when the landscape and fen systems were not fragmented in numerous geographically-isolated populations. This makes it difficult to speculate about the relationships between Asiatic and European plant populations and the origin and distribution of this species in Europe. Today, it seems to be restricted due to the occurrence of plants which clearly reflects the genetic variability from the ancient period

Model Stocka i Watsona oraz jego modyfikacje — Analiza inflacji w Polsce

The paper presents general local level model with stochastic volatility, recently proposed for U.S. inflation by Stock and Watson. The main purpose is to present and compare other local level model specifications, especially with Normal GARCH and Student-t GARCH disturbances. The paper is a full Bayesian analysis and concerns inflation in Poland during 1992-2007. The model selection and posterior estimates provide strong evidence in favor of a model with heavy-tailed disturbances in the core component, and the transitory component. Also, after the system transformations in the early 90's, the volatility of the disturbances driving both components have been substantially decreasing over time