A Super-Learning Machine for Predicting Economic Outcomes

We present a Super-Learning Machine (SLM) to predict economic outcomes which improves prediction (i) by cross-validated optimal tuning, (ii) by comparing/combining results from different learners. Our application to a labor economics dataset shows that different learners may behave differently. However, combining learners into one singleton super-learner proves to preserve good predictive accuracy lowering the variance more than stand-alone approaches.

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Year of publication:	2020-03-10
Authors:	Cerulli, Giovanni

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Type of publication:	Book / Working Paper
Language:	English
Notes:	Cerulli, Giovanni (2020): A Super-Learning Machine for Predicting Economic Outcomes.
Classification:	C53 - Forecasting and Other Model Applications ; C61 - Optimization Techniques; Programming Models; Dynamic Analysis ; C63 - Computational Techniques
Source:	BASE

Persistent link: https://www.econbiz.de/10015266851