What Can We (Machine) Learn about Welfare Dynamics from Cross-Sectional Data?

What Can We (Machine) Learn about Welfare Dynamics from Cross-Sectional Data?

This paper implements a machine learning approach to estimate intra-generational economic mobility using cross-sectional data. A Least Absolute Shrinkage and Selection Operator (Lasso) procedure is applied to explore poverty dynamics and household-...

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Bibliographic Details
Main Author: Lucchetti, Leonardo
Format: Working Paper
Language:English
Published: World Bank, Washington, DC 2018
Subjects:
POVERTY
POVERTY TRANSITIONS
LASSO
MACHINE LEARNING
WELFARE DYNAMICS
SYNTHETIC PANELS
CLASS MOBILITY
Online Access:http://documents.worldbank.org/curated/en/949841533741579213/What-can-we-machine-learn-about-welfare-dynamics-from-cross-sectional-data
http://hdl.handle.net/10986/30235

Internet

http://documents.worldbank.org/curated/en/949841533741579213/What-can-we-machine-learn-about-welfare-dynamics-from-cross-sectional-data
http://hdl.handle.net/10986/30235

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