IMF Working Papers

Measuring Soft Power: A New Global Index

By Serhan Cevik, Tales Padilha

October 4, 2024

Download PDF More Formats on IMF eLibrary Order a Print Copy

Preview Citation

Format: Chicago

Serhan Cevik, and Tales Padilha. "Measuring Soft Power: A New Global Index", IMF Working Papers 2024, 212 (2024), accessed December 22, 2024, https://doi.org/10.5089/9798400289576.001

Export Citation

  • ProCite
  • RefWorks
  • Reference Manager
  • BibTex
  • Zotero
  • EndNote

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

Soft power is difficult to measure directly, and existing indicators—mostly subjective and not always transparent—fail to take into account the multidimensional nature of soft power. In this paper, we introduce a new comprehensive Global Soft Power Index (GSPI) composed of six dimensions for a broad sample of countries over a long span of time. The proposed framework allows for comparisons not only at the “headline” level of the GSPI, but also at the level of the sub-indices, which in turn helps identify and study how countries differ at a granular level of soft power. In a final step of the analysis, we present a possible macro-financial application to investigate the relationship between soft power and exchange rates. The results indicate that some dimensions of the GSPI play an important role in explaining exchange rate volatility. Overall, the composite GSPI presented in this paper provides a systematic approach to measure soft power along its multiple dimensions. By capturing the matrix of soft power characteristics, the GSPI offers significant advantages in comparative analysis of soft power across countries and over time.

Subject: Education, Exchange rates, Foreign exchange, Real exchange rates

Keywords: Comparative analysis, Composite indicators, Exchange rate volatility, Exchange rates, Global, K-Means clustering, Principal component analysis, Real exchange rates, Soft power

Publication Details