Abstract
The authors discuss the importance of composite indicators for capturing the complexity and multidimensionality of different phenomena and propose an analysis based on the penalty for bottleneck (PFB) method to show how plausible policy recommendations can be extracted from composite indicators. The basic problem of the policy application of composite indicators lies on their limited capacity to handle the ingredients of the studied phenomenon from the systemic perspective. The resulting PFB-based policy recommendation is clear: the bottleneck component should be improved first because it has a magnifying effect on the other system indicators. Unlike other methodologies, the PFB analysis allows to create a policy-portfolio mix that optimizes the use of additional resources. The authors explore a practical application of the PFB methodology to the Global Entrepreneurship Index data. The authors conclude that the PFB can be successfully applied to numerous fields in order to provide more accurate policy recommendations than other methodologies that do not take a system-based bottleneck approach.
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Notes
- 1.
Here we do not want to go into other issues like outlier and skewness handling.
- 2.
Weighting can also be applied, however, weighting changes the trade-offs between the variables.
- 3.
Obviously, there is a limit to how to improve the features, that is \( {\tilde{y}}_k\le 1 \); but we are not dealing with this case in the following.
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Acknowledgment
Gábor Rappai and László Szerb express their thanks for the financial support of this research, which has been provided by OTKA Research Foundation, theme number K 81527.
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Szerb, L., Ács, Z.J., Rappai, G., Kehl, D. (2023). Building Composite Indicators for Policy Optimization Purposes. In: Acs, Z.J., Lafuente, E., Szerb, L. (eds) The Entrepreneurial Ecosystem. Palgrave Studies in Entrepreneurship and Society. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-25931-9_2
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