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The Political Economy of IMF Surveillance

Authors: Domenico Lombardi; Ngaire Woods;

The Political Economy of IMF Surveillance

Abstract

This paper investigates the political economy foundations of international Monetary Fund (IMF) surveillance by developing a taxonomy that accounts for its differential impact across the membership and examine its rationale in light of how surveillance has historically affected members' economic policies. With powerful member countries now pressing for the IMF to strengthen surveillance, we identify the factors that would enable it to affect the policies of its member countries, exploring the impact that IMF's internal governance has on the effectiveness of both bilateral and multilateral surveillance and contrasting it with the experience of select international organizations.

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Average
Top 10%
Top 10%
Related to Research communities
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