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Inwestycje dywersyfikacyjne przedsiębiorstw w nieruchomości inwestycyjne oraz wartości niematerialne i prawne

100%
Nehrebecka N., Białek-Jaworska A.
Nauki o Finansach
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2015
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issue 2(23)
22-40
EN
The article identified determinants of the corporate investment diversification in Poland, ie. in investment property or intangible assets and their dependence on corporate savings. The analysis was conducted on unbalanced panel data of individual companies employing at least 10 workers contained in the annual reports of Central Statistical Office (F-02) from the years 1995-2012. The parameters used to estimate the system GMM [Generalised Methods of Moments]. Also included is a robust variance-covariance matrix. The obtained results allow to conclude that the increase in liquid reserves (savings) increases the investment diversification spending (in real estate and intangible assets). A positive correlation was obtained in diversified investments of the real effective exchange rate based on CPI and growth opportunities. This may be due to the anti-inflationary role of investment in real estate, as well as the improvement of the situation of exporters of services (investing in intangible assets), granting licenses to foreign companies on their own technology or software due to the appreciation of the exchange rate.
2
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The impact of R&D expenditure on productivity in the manufacturing industry in Poland

100%
Roszko-Wójtowicz E., Grzelak M. M., Laskowska I.
Econometrics. Ekonometria. Advances in Applied Data Analytics
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2019
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issue vol. 23 no. 4
112-138
EN
EU strategy documents, including the Europe 2020 Strategy, emphasise the priority role of industry in the growth of EU economies. The aim of the presented research is to measure and assess the impact of expenditure on research and development (R&D) activities on the competitiveness of manufacturing divisions in Poland. Labour productivity, expressed as (1) a quotient of gross value added and employment, and (2) a quotient of sold production and employment in the analysed manufacturing divisions, was adopted as the measure of competitiveness. The empirical part of the paper is based on data published by the Central Statistical Office. The analysis covers the period 2009-2017 and provides a contribution to determining the role and importance of research and development as well as innovative activities in shaping competitive advantages of manufacturing enterprises. The obtained results for panel models confirm that R&D expenditure is a secondary factor in changes occurring in the Polish manufacturing industry.
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Zastosowanie dynamicznych modeli panelowych w analizie determinant przestępczości w Polsce w latach 2005–2016

72%
Gadomski Ł., Malaczewski M.
Finanse i Prawo Finansowe
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2020
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vol. 1
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issue 25
29-47
EN
The purpose of this study is to verify an impact of both economic and social factors affecting crime in Poland. The data used in the study is characterized by an annual frequency and is presented as a breakdown by voivodships. The time interval of the analysis covers the years 2005–2016 due to limited data availability. As part of the analyzes, the significance of following variables is verified: feminization rate, inflation, urbanization rates and population density. In addition, in the study a synthetic indicator representing the quality of life in the region is included. The significance of selected variables is verified by econometric model. Due to the use of panel data and the authors' conviction that there is a relationship between past crime values and their current implementations, it is decided to use dynamic panel models (FDGMM method).
PL
Celem niniejszego badania jest weryfikacja wpływu czynników zarówno ekonomicznych, jak i społecznych, mających wpływ na kształtowanie się przestępczości w Polsce. Dane wykorzystane w badaniu charakteryzują się częstotliwością roczną i prezentowane są w ramach przekroju wojewódzkiego. Przedział czasowy analizy obejmuje lata 2005–2016 z uwagi na ograniczenie dostępności danych. W ramach przeprowadzonych analiz dokonano weryfikacji istotności zmiennych: współczynnik feminizacji, inflacja, współczynniki urbanizacji oraz gęstości zaludnienia. Dodatkowo zdecydowano o uwzględnieniu w badaniu wskaźnika syntetycznego reprezentującego poziom jakości życia w regionie. Weryfikacja istotności wybranych zmiennych została przeprowadzona poprzez budowę modelu ekonometrycznego. Z uwagi na wykorzystanie danych panelowych oraz przekonanie autorów o występowaniu związku pomiędzy przeszłymi wartościami przestępczości a ich obecnymi realizacjami, zdecydowano się na wykorzystanie dynamicznych modeli panelowych (metoda FDGMM).
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