60 likes | 77 Views
Some comments on WGI indicators. Jean-François Sattin IAE de Valenciennes. Internal consistency.
E N D
Some comments on WGI indicators Jean-François Sattin IAE de Valenciennes
Internal consistency • The identifying assumption in the unobserved components model is that any observed correlation between two measures of corruption, for example, is due to their common, but unobserved, signal of corruption. (Kaufman, Kraay, 2007) • How to cope with the sources of common errors in measurement ? • Halo effect • Contaminations between sources • Western bias • How to manage missing data ? • Two steps estimation • “Representative” database really representative ? • Risk-Western biased (e.g. Vries, 2007)
Contamination between sources: An exemple • Freedom House’s Index of Economic Freedom and Economist Intelligence Unit are two distinct sources in WGI. • But Freedom House assess property right protection by relying on the Economist Intelligence Unit reports. • What means a high correlation score?
Implications • Practical ground: For a country improving WGI ranking seems quite difficult • Multiple dimensions to be improved • Biases in the « representative » database (e.g. Vries, 2007) • Worldwide trends • Ethical ground: Allocating aid for LDCs • WGI as a new tool of imperialism ? • Still the Western bias • Margins of error management
Conclusion • Methodological ground: (Brousseau & al., 2007) • Need for new, independent datasets of governance assessment (Brousseau & al., 2007). • Need for triangulation • Practical ground: • All institutional indicator need to be used carefully. • Need for achievable targets for LDCs
References • Brousseau, Harnay & Sattin, 2007, Measuring Law and Institutions: A critical survey of current practices and some recommendations to build indicators, University of Paris X, Mimeo • Kaufman, Kraay, 2007, Governance Indicators: Where Are We, Where Should We Be Going?, World Bank Policy Research Working Paper • Vries, 2007, How Does Your Country Rank? The Discussion about International Data on Good Governance, Proceedings from the International Conference on Government Performance Management