A Super-Learning Machine for Predicting Economic Outcomes

Cerulli, Giovanni (2020): A Super-Learning Machine for Predicting Economic Outcomes.

Abstract

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Machine learning; Ensemble methods; Optimal prediction
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling

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