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Country characteristics and non-indigenous species

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  • GREN, ING-MARIE
  • THIERFELDER, TOMAS
  • BERGLUND, HELENA

Abstract

This paper presents an econometric test of two hypotheses underlying the occurrence of non-indigenous species (NIS) at the global scale: openness of recipient nations which allows for international trade to act as a vector of NIS, and habitat fragmentation in recipient nations which facilitates establishment of introduced NIS. Explorative econometric methods have been utilised that combine the analysis of dimensionality with subset variable selection and multiple linear regression. Both NIS hypotheses are thereby supported, although slightly different in the cases of the mainland and island nations. It is concluded that expressions of openness have a larger impact on the number of NIS per unit territorial area in the mainland nations, whereas biota variables play a more dominant role in the case of the island nations. It is also concluded that different expressions of NIS occurrence affect the result, where NIS per area unit facilitates excellent explanatory performance.

Suggested Citation

  • Gren, Ing-Marie & Thierfelder, Tomas & Berglund, Helena, 2011. "Country characteristics and non-indigenous species," Environment and Development Economics, Cambridge University Press, vol. 16(1), pages 51-70, February.
    • Handle: RePEc:cup:endeec:v:16:y:2011:i:01:p:51-70_00
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    Cited by:

    1. Gren, Ing-Marie & Campos, Monica & Gustafsson, Lena & Elofsson, Katarina, 2013. "Species Imperilment on the Global Scale: Empirical evidences of economic causes," Working Paper Series 2013:7, Swedish University of Agricultural Sciences, Department Economics.
    2. Perrings, Charles, 2014. "Environment and development economics 20 years on," Environment and Development Economics, Cambridge University Press, vol. 19(3), pages 333-366, June.
    3. Marbuah, George & Gren, Ing-Marie & Mckie, Brendan G. & Buisson, Laëtitia, 2021. "Economic activity and distribution of an invasive species: Evidence from night-time lights satellite imagery data," Ecological Economics, Elsevier, vol. 185(C).

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