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    Wyświetlanie 1-7 z 7
    Tytuł:
    Wykorzystanie Google Trends do modelowania stopy bezrobocia rejestrowanego w Polsce
    Use of Google Trends in modelling registered unemployment rate in Poland
    Autorzy:
    Malinowski, Mariusz
    Powiązania:
    https://bibliotekanauki.pl/articles/971502.pdf
    Data publikacji:
    2021-03-31
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    nowcasting
    bezrobocie
    dane makroekonomiczne
    Google Trends
    unemployment
    macroeconomic dat
    Opis:
    W artykule podjęto problematykę monitorowania stopy bezrobocia w Polsce. Celem przedstawionego badania jest sprawdzenie, czy dołączenie wybranych indeksów Google Trends do autoregresyjnego modelu stopy bezrobocia rejestrowanego poprawia trafność generowanych przez niego prognoz. Zastosowana metoda badania opiera się na technikach nowcastingu służących do oceny bieżącego stanu gospodarki. Dane za lata 2004–2019 zostały zaczerpnięte z publikacji GUS oraz serwisu Google Trends, który pozwala na śledzenie popularności terminów wyszukiwanych przez internautów. Porównano jakość dopasowania modelu do danych oraz błędy prognoz modelu podstawowego i modeli rozszerzonych o zmienne egzogeniczne. Artykuł przedstawia zarówno potencjał, jak i ograniczenia wykorzystywania nowego źródła danych w analizach makroekonomicznych dotyczących Polski. Na podstawie przeprowadzonej analizy można uznać, że indeksy Google, powszechnie wykorzystywane w literaturze anglojęzycznej, nie poprawiają trafności predykcji modelu autoregresyjnego. Zadowalające rezultaty uzyskiwane są tylko dla indeksów związanych z międzynarodową mobilnością siły roboczej.
    The paper deals with the problem of monitoring the unemployment rate in Poland. The main aim of the article is to check whether the addition of selected Google Trends indices improves the accuracy of forecasts generated by the autoregressive model of registered un-employment rate. The research method is based on nowcasting techniques which are used to assess the current state of an economy. Data for the years 2004–2019 were retrieved from publication by Statistics Poland (GUS) and Google Trends, the latter of which allows tracking the popularity of terms searched by Internet users. The study compares the goodness of fit and forecast errors of the basic model with these of models extended with exogenous variables. Both the potential and the limitations of the utilisation of a new source of data in macro-economic analyses concerning Poland are presented in the paper. The analysis yields a conclu-sion that Google indexes (commonly used in the literature written in English) do not improve the accuracy of predictions of the autoregressive model. Satisfactory results are only obtained for indices related to the international mobility of the workforce.
    Źródło:
    Wiadomości Statystyczne. The Polish Statistician; 2021, 66, 3; 45-61
    0043-518X
    Pojawia się w:
    Wiadomości Statystyczne. The Polish Statistician
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Precipitation estimation and nowcasting at IMGW-PIB (SEiNO system)
    Autorzy:
    Szturc, J.
    Jurczyk, A.
    Ośródka, K.
    Wyszogrodzki, A.
    Giszterowicz, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/108484.pdf
    Data publikacji:
    2018
    Wydawca:
    Instytut Meteorologii i Gospodarki Wodnej - Państwowy Instytut Badawczy
    Tematy:
    opad atmosferyczny
    prognoza probabilistyczna
    szacowanie
    opad
    dane
    wysoka rozdzielczość
    precipitation
    nowcasting
    probabilistic forecast
    precipitation estimation
    high-resolution data
    Opis:
    A System for the Estimation and Nowcasting of Precipitation (SEiNO) is being developed at the Institute of Meteorology and Water Management – National Research Institute. Its aim is to provide the national meteorological and hydrological service with comprehensive operational tools for real-time high-resolution analyses and forecasts of precipitation fields. The system consists of numerical models for: (i) precipitation field analysis (estimation), (ii) precipitation nowcasting, i.e., extrapolation forecasting for short lead times, (iii) generation of probabilistic nowcasts. The precipitation estimation is performed by the conditional merging of information from telemetric rain gauges, the weather radar network, and the Meteosat satellite, employing quantitative quality information (quality index). Nowcasts are generated by three numerical models, employing various approaches to take account of different aspects of convective phenomena. Probabilistic forecasts are computed based on the investigation of deterministic forecast reliability determined in real time. Some elements of the SEiNO system are still under development and the system will be modernized continuously to reflect the progress in measurement techniques and advanced methods of meteorological data processing.
    Źródło:
    Meteorology Hydrology and Water Management. Research and Operational Applications; 2018, 6, 1; 1-12
    2299-3835
    2353-5652
    Pojawia się w:
    Meteorology Hydrology and Water Management. Research and Operational Applications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment
    Autorzy:
    Lenart, Łukasz
    Powiązania:
    https://bibliotekanauki.pl/articles/2076445.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    HICP
    seasonal volatility
    exponential smoothing
    nowcasting
    predictive distribution
    logscore
    Opis:
    The aim of this paper is to examine the problem of existing seasonal volatility in total and disaggregated HICP for Baltic Region countries (Denmark, Estonia, Latvia, Finland, Germany, Lithuania, Poland and Sweden). Using nonparametric tests, we found that in the case of m-o-m prices, including fruit, vegetables, and total HICP, the homogeneity of variance during seasons is rejected. Based on these findings, we propose an exponential smoothing model with periodic variance of error terms that capture the repetitive seasonal variation (in conditional or unconditional second moments). In a pseudo-real data experiment, the short-term forecasts (nowcasting) for the considered components of inflation were determined using different specifications of considered models. The forecasting performance of the models was measured using one of the scoring rules for probabilistic forecasts called logarithmic score. We found instead that while the periodic phenomenon in variance was statistically significant, the models with a periodic phenomenon in variance of error terms do not significantly improve forecasting performance in disaggregated cases and in the case of total HICP. The simpler models with constant variance of error term have comparative forecasting (nowcasting) performance over the alternative model
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2017, 1; 29-67
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    MeteoGIS: GIS-based system for monitoring of severe meteorological phenomena
    Autorzy:
    Jurczyk, A.
    Ośródka, K.
    Szturc, J.
    Giszterowicz, M.
    Przeniczny, P.
    Tkocz, G.
    Powiązania:
    https://bibliotekanauki.pl/articles/108449.pdf
    Data publikacji:
    2015
    Wydawca:
    Instytut Meteorologii i Gospodarki Wodnej - Państwowy Instytut Badawczy
    Tematy:
    meteorological data
    weather radar
    GIS
    monitoring
    nowcasting
    Opis:
    The MeteoGIS system developed at the Institute of Meteorology and Water Management – National Research Institute in Poland is a GIS-based system for real-time monitoring of weather and the generation of meteorological warnings. Apart from its monitoring features, it can also provide more advanced analysis, including SQL (Structured Query Language) queries and statistical analyses. Input data are provided mainly by the INCA-PL 2 nowcasting model which employs forecasts from the high-resolution AROME numerical weather prediction model and measurement data from the Polish weather radar network POLRAD and surface meteorological stations. As well as this, data from the PERUN lighting detection system are used. Ingestion of such data allows for the mitigation of risk from potentially hazardous weather phenomena such as extreme temperatures, strong wind, thunderstorms, heavy rain and subsequent impending floods. The following meteorological parameters at ground level are visualised in the MeteoGIS: (i) precipitation (accumulation and type), (ii) temperature, (iii) wind (speed and direction), (iv) lightning (locations and type). End users of the system are workers from civil protection services who are interested in shortterm warnings against severe weather events, especially area-oriented ones (related to districts, catchments, etc.). The reliability of visualised data is a very important issue, and from the MeteoGIS user’s point of view the improvement in data quality is a continuous process.
    Źródło:
    Meteorology Hydrology and Water Management. Research and Operational Applications; 2015, 3, 2; 49-61
    2299-3835
    2353-5652
    Pojawia się w:
    Meteorology Hydrology and Water Management. Research and Operational Applications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The forecasting of tornado events: the synoptic background of two different tornado case studies
    Autorzy:
    Wrona, B.
    Avotniece, Z.
    Powiązania:
    https://bibliotekanauki.pl/articles/108603.pdf
    Data publikacji:
    2015
    Wydawca:
    Instytut Meteorologii i Gospodarki Wodnej - Państwowy Instytut Badawczy
    Tematy:
    tornado
    synoptic background
    forecasting
    nowcasting
    Opis:
    The synoptic analyses of two different tornado cases, observed in Latvia and Poland in the summer of 2012, are examined in this paper. The first of them, the tornado in Latvia seemed to be a “textbook example” of tornado occurrence. Its development took place in the contact zone of the warm, tropical air, characterized by a very high CAPE (Convective Available Potential Energy), with cold and moist polar marine air mass behind the convergence line that determined very good conditions for convective updraft. Additionally, the moderate environmental wind shear favoured the sufficient condition for concentrating the atmosphere’s vorticity into well-organized strong rotating upward motions that produced the supercell structures and tornado. Thus, from the forecaster’s point of view, the occurrence of this severe convective event was not a surprise. This phenomenon was predicted correctly more than a dozen hours before the tornado occurred. The second event occurred in the north of Poland and was associated with a thunderstorm where a supercell was formed in conditions of low CAPE but favourable wind profile, both vertical and horizontal. Helical environments (characterized by large shear vectors that veered with height in the lowest three kilometres, especially the nearest one kilometre) were arguably the most important factor that determined the Polish tornado’s occurrence. In this case the analysis of the synoptic situation was not so clear and the superficial analysis, even post factum, regarding radar, satellite or detection maps might have suggested “quite a normal” summer thunderstorm. However, the detailed examination showed the reasons why tornado genesis took place. The potential conditions for the occurrence of this severe phenomenon were indicated by forecasters, although the forecasts were less exact with regard to the place of occurrence and the heaviness of the strike.
    Źródło:
    Meteorology Hydrology and Water Management. Research and Operational Applications; 2015, 3, 1; 51-58
    2299-3835
    2353-5652
    Pojawia się w:
    Meteorology Hydrology and Water Management. Research and Operational Applications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Nowcasting Quarterly GDP Dynamics in the Euro Area – The Role of Sentiment Indicators
    Autorzy:
    Gajewski, Paweł
    Powiązania:
    https://bibliotekanauki.pl/articles/632857.pdf
    Data publikacji:
    2014-06-01
    Wydawca:
    Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
    Tematy:
    nowcasting
    sentiment indicators
    kluczowe prognozowanie bieżące
    wskaźniki koniunktury
    Opis:
    The paper compares the most closely watched sentiment indicators with respect to their ability to nowcast quarterly GDP dynamics in the Euro Area and its biggest economies. We analyse cross-correlations and out-of-sample forecast errors generated from equations estimated by rolling regressions in fixed-length window. The results show that models employing PMI Composite perform best in the cases of the Euro Area, Germany, France and Italy, whilst Spanish GDP dynamics is best nowcasted using ESI-based models. PMI-based models generate the most accurate nowcasts at the beginning of the quarter, as well as during periods of high volatility of GDP growth rates
    W artykule porównane zostały zdolności najpilniej obserwowanych wskaźników obrazujących nastroje gospodarcze do bieżącego prognozowania kwartalnej dynamiki PKB w strefie euro i jej największych państwach członkowskich. Analizowane są korelacje krzyżowe oraz błędy prognoz poza próbę, wygenerowane z równań szacowanych w oparciu o regresję kroczącą w oknie stałej długości. Wyniki wskazują, że modele wykorzystujące wskaźnik PMI Composite dają na ogół najlepsze wyniki w strefie euro, Niemczech, Francji i Włoszech, podczas gdy bieżąca dynamika hiszpańskiego PKB jest najprecyzyjniej prognozowana przez modele oparte na wskaźniku ESI. Modele oparte na PMI generują relatywnie najlepsze prognozy na początku kwartału, a także w okresach wysokiej zmienności stóp wzrostu PKB.
    Źródło:
    Comparative Economic Research. Central and Eastern Europe; 2014, 17, 2; 5-23
    1508-2008
    2082-6737
    Pojawia się w:
    Comparative Economic Research. Central and Eastern Europe
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Radarowa detekcja superkomórek burzowych w Polsce
    Supercell storm radar detection in Poland
    Autorzy:
    Pilorz, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/132190.pdf
    Data publikacji:
    2014
    Wydawca:
    Polskie Towarzystwo Geograficzne
    Tematy:
    superkomórka burzowa
    radar meteorologiczny
    sygnatury radarowe
    nowcasting
    zagrożenia meteorologiczne
    supercell storm
    weather radar
    radar signatures
    meteorological threats
    Opis:
    “Supercell storms are capable of producing the most violent of hail, wind and tornado events (Moller et. al. 1994); thus they are the most important storm type to forecast and detect” (Moller 2001). Supercell storm is defined by “presence of a deep and persistent, rotating updraft called a mesocyclone” (Weisman and Klemp 1984). Mesocyclone presence leads to the specific vertical storm structure seen as a Bounded Weak Echo Region. Mesocyclone presence also leads to the changes in the horizontal shape of the storm, observed on the radar reflecivity in a low elevation as a hook echo. Large hail, associated with supercells, is a very important threat to detect. It can be easily recognized by the presence of the reflecivity more than 50 dBZ, above 8 km above ground level (Burgess and Lemon 1990). Nine cases of supercells in Poland between 2007 and 2013 were examined. Results show that all quoted features were present. Moreover, most of them appeared before the threat which they indicate. It means that threats associated with supercells can be predicted in a short time.
    Źródło:
    Teledetekcja Środowiska; 2014, 51; 93-105
    1644-6380
    Pojawia się w:
    Teledetekcja Środowiska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-7 z 7

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