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Accounting and Statistical Analyses for Sustainable Development

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If you make use of this material, you may credit the authors as follows:

Lemke Claudia, "Accounting and Statistical Analyses for Sustainable Development", Springer Nature, 2021, DOI: 10.1007/978-3-658-33246-4, License:

In this Open Access publication Claudia Lemke develops a comprehensive Multi-Level Sustainable Development Index (MLSDI) that is applicable to micro, meso, and macro objects by conducting methodological and empirical research. Multi-level comparability is crucial because the Sustainable Development Goals (SDGs) at macro level can only be achieved if micro and meso objects contribute. The author shows that a novel information-theoretic algorithm outperforms established multivariate statistical weighting methods such as the principal component analysis (PCA). Overcoming further methodological shortcomings of previous sustainable development indices, the MLSDI avoids misled managerial and political decision making.


Environmental Economics, Sustainability, Sustainable Development Goals (sdgs), Composite Indicators, Multilevel Perspective, Principal Component Analysis, Information Theory, Open Access

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