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Dynamiczne wlasnosci miar ubostwa energetycznego

Author

Listed:
  • Maciej Lis
  • Agata Miazga
  • Michal Ramsza

Abstract

Celem niniejszej pracy jest zbadanie wplywu zmian w cenach, dochodach oraz strukturze gospodarstw domowych na zasieg ubostwa energetycznego w Polsce do roku 2030. W tym celu zbudowane zostaly scenariusze zmian w kazdym wyroznionym wymiarze (struktura demograficzna, poziom dochodow, struktura budynkow oraz ceny energii). Symulacyjnie wyznaczono, w jakim zakresie te scenariusze przeloza sie na zakres ubostwa energetycznego, mierzonego absolutnie, relatywnie oraz subiektywnie. Analize przeprowadzamy za pomoca statyczno-dynamicznego modelu mikrosymulacyjnego. Wyniki wskazuja, ze ze wzrost cen energii o 1% przelozy sie na wzrost wydatkow na energie jedynie o 0,1-0,2%. Wzrost dochodow wplynie na niewielki spadek wydatkow energetycznych w strukturze konsumpcji. Do roku 2030 nie przewidujemy znaczacych zmian w skali ubostwa energetycznego w Polsce. Wedlug miary relatywnej (LIHC) oraz miary subiektywnej skala zjawiska nieznacznie sie zmniejszy, a wedlug miary absolutnej '10% dochodow' nieznacznie sie powiekszy.

Suggested Citation

  • Maciej Lis & Agata Miazga & Michal Ramsza, 2016. "Dynamiczne wlasnosci miar ubostwa energetycznego," IBS Research Reports 01/2016, Instytut Badan Strukturalnych.
    • Handle: RePEc:ibt:report:rr012016
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    File URL: http://ibs.org.pl/app/uploads/2016/01/IBS_Research_Report_01_2016_pl.pdf
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    Citations

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    Cited by:

    1. Agnieszka Biernat-Jarka & Paulina Trębska & Sławomir Jarka, 2021. "The Role of Renewable Energy Sources in Alleviating Energy Poverty in Households in Poland," Energies, MDPI, vol. 14(10), pages 1-21, May.
    2. Marlena Piekut, 2020. "Patterns of Energy Consumption in Polish One-Person Households," Energies, MDPI, vol. 13(21), pages 1-31, October.

    More about this item

    Keywords

    modelowanie; ubostwo energetyczne; microsimulation modelling; energy poverty;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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