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Europe > Ireland

You are looking at 1 - 3 of 3 items for :

  • Type: Journal Issue x
  • Technological Change: Choices and Consequences; Diffusion Processes x
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Cover Technical Notes and Manuals
How to Assess Country Risk: The Vulnerability Exercise Approach Using Machine Learning
International Monetary Fund. Strategy, Policy, & Review Department
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.
Keywords:
Risk Assessment; Supervised Machine Learning; Prediction; Sudden Stop; Exchange Market Pressure; Fiscal Crisis; Debt; Financial Crisis; Economic Crisis; Economic Growth; VE modeling toolkit; ML technique; Vulnerability Exercise approach using machine learning; IMF's Vulnerability Exercise; ML tool; crisis risk indices; Early warning systems; Global financial crisis of 2008-2009; Sudden stops; Banking crises; Global
Cover IMF Research Perspectives
IMF Research Perspectives: Spring-Summer 2020
IMF Research Perspectives Spring-Summer 2020
Keywords:
IRB; worker; view IMF research; MARTINEZ PERIA interview
Cover IMF Working Papers
The Structural Determinants of the Labor Share in Europe
Dilyana Dimova
The labor share in Europe has been on a downward trend. This paper finds that the decline is concentrated in manufacture and among low- to mid-skilled workers. The shifting nature of employment away from full-time jobs and a rollback of employment protection, unemployment benefits and unemployment benefits have been the main contributors. Technology and globalization hurt sectors where jobs are routinizable but helped others that require specialized skills. High-skilled professionals gained labor share driven by productivity aided by flexible work environments, while low- and mid-skilled workers lost labor share owing to globalization and the erosion of labor market safety nets.
Keywords:
WP; skilled worker; import penetration; employment share; further labor share erosion; labor market; labor share erosion; labor share shrinkage; labor share stagnation; share data; share decline; wage share; labor share; technology; employment policies; globalization; shift share analysis; labor share contraction; labor share growth; labor share shrink; labor share stem; self-employment share; labor share come; labor share tend; labor share fluctuation; Employment; Employment protection; Unemployment benefits; Global; Baltics; Europe