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02348cas a2200313 a 4500 |
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AALejournalIMF021676 |
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230101c9999 xx r poo 0 0eng d |
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|c 5.00 USD
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|z 9781513574219
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|a 2075-8669
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| 040 |
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|a BD-DhAAL
|c BD-DhAAL
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|a International Monetary Fund.
|b Strategy, Policy, and Review Department.
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|a How to Assess Country Risk :
|b The Vulnerability Exercise Approach Using Machine Learning.
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|a Washington, D.C. :
|b International Monetary Fund,
|c 2021.
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| 300 |
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|a 1 online resource (66 pages)
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|a Technical Notes and Manuals
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| 500 |
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|a <strong>Off-Campus Access:</strong> No User ID or Password Required
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| 500 |
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|a <strong>On-Campus Access:</strong> No User ID or Password Required
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|a Electronic access restricted to authorized BRAC University faculty, staff and students
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|a The IMF's Vulnerability Exercise (VE) is a cross-country exercise that identifies country-specific near-term macroeconomic risks. As a key element of the Fund's broader risk architecture, the VE is a bottom-up, multi-sectoral approach to risk assessments for all IMF member countries. The VE modeling toolkit is regularly updated in response to global economic developments and the latest modeling innovations. The new generation of VE models presented here leverages machine-learning algorithms. The models can better capture interactions between different parts of the economy and non-linear relationships that are not well measured in 'normal times.' The performance of machine-learning-based models is evaluated against more conventional models in a horse-race format. The paper also presents direct, transparent methods for communicating model results.
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|a Mode of access: Internet
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|a ML Technique
|2 imf
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|a National Government Expenditures and Related Policies
|2 imf
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| 650 |
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|a Risk Assessment, Supervised Machine Learning and Prediction
|2 imf
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| 650 |
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|a Sudden Stop, Exchange Market Pressure and Fiscal Crisis
|2 imf
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| 650 |
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|a Tax Evasion and Avoidance
|2 imf
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| 650 |
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|a Ve Modeling Toolkit
|2 imf
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| 830 |
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|a Technical Notes and Manuals; Technical Notes and Manuals ;
|v No. 2021/003
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| 856 |
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|z Full text available on IMF
|u http://elibrary.imf.org/view/journals/005/2021/003/005.2021.issue-003-en.xml
|z IMF e-Library
|