The Natura 2000 Network and the State of Local Economy of Rural Areas of the Green Lungs of Poland Region – The Application of Models

Dacko, Mariusz

doi:doi:10.53098/wir.2010.1.146/13

- ris
- BibTeX
- EndNote
- Csv

The Natura 2000 Network and the State of Local Economy of Rural Areas of the Green Lungs of Poland Region – The Application of Models Dacko, Mariusz

Object structure

The Natura 2000 Network and the State of Local Economy of Rural Areas of the Green Lungs of Poland Region – The Application of Models

Dacko, Mariusz

Instytut Rozwoju Wsi i Rolnictwa Polskiej Akademii Nauk

Warszawa

2010

Journal/Article

Natura 2000 ; agriculture ; economic activity ; regression trees

In the paper models of regressive trees were used to illustrate the shaping of the agricultural sector’s condition and economic activity of the residents of rural areas in the Green Lungs of Poland region. These models were prepared in an effort to empirically check the pessimistic assessments of the state of the local economy of communes situated in the Green Lungs of Poland region, which are broadly covered by special protection of birds and habitats within the Natura 2000 network. The models’ results presented simple criteria for distinguishing communes with different levels of the development of economic activity and agriculture. They also made it possible to assess the validity of the used predictors that constituted the sub-components of sustainable development distinguished in the research project. The results of predictions of the models of regressive trees were shown on maps, which permitted to make an assessment of the spatial shaping of local economy in the areas of the Green Lungs of Poland region.

Bołtromiuk A., Kłodziński M., 2009: Konflikt sieci Natura 2000 z procesem rozwoju gminy. „Czas Morza” 3 (39).
Breiman L., Friedman J., Olshen R.A., Stone Ch. J., 1993: Classification and Regression Trees. Chapman and Hall, New York.
Dacko M., 2007: Badanie rynku mieszkań w Olsztynie z zastosowaniem metod statystycznych. Studia i materiały Towarzystwa Naukowego Nieruchomości. „Rynek nieruchomości – analizy, modelowanie, inwestowanie” 15, 3–4.
Łapczyński M., 2003: Drzewa klasyfikacyjne w badaniach satysfakcji i lojalności klientów (http://www.statsoft.pl/czytelnia/marketing/drzewa.pdf).
Łapczyński M., 2007: Wpływ aktywności mieszkańców na poziom życia w gminach woj. małopolskiego (http://www.statsoft.pl/czytelnia/8_2007/Lapczynski05.pdf).
Manasse P., Roubini N., 2009: „Rules of thumb” for sovereign debt crises. „Journal of International Economics” 78, 2: 192–205.
Sokołowski A., 2002: Metody stosowane w Data mining. Materiały seminaryjne „Data mining – metody i przykłady”. Statsoft, Kraków.
Sroka W., Dacko M., 2010: Ocena czynników rozwoju przodujących gospodarstw rolniczych z wykorzystaniem drzew regresyjnych typu C & RT. „Zagadnienia Ekonomiki Rolnej” 2.