The More the Merrier? A Machine Learning Algorithm for Optimal Pooling of Panel Data

The More the Merrier? A Machine Learning Algorithm for Optimal Pooling of Panel Data
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Volume/Issue: Volume 2020 Issue 044
Publication date: February 2020
ISBN: 9781513529974
$18.00
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Topics covered in this book

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Economics- Macroeconomics , WP , country , algorithm , Machine learning , GDP growth , forecasts , panel data , pooling , proximate country , machine learning method , example country , macroeconomic aggregate , bias-variance tradeoff , country of interest , Production growth , Eastern Europe

Summary

We leverage insights from machine learning to optimize the tradeoff between bias and variance when estimating economic models using pooled datasets. Specifically, we develop a simple algorithm that estimates the similarity of economic structures across countries and selects the optimal pool of countries to maximize out-of-sample prediction accuracy of a model. We apply the new alogrithm by nowcasting output growth with a panel of 102 countries and are able to significantly improve forecast accuracy relative to alternative pools. The algortihm improves nowcast performance for advanced economies, as well as emerging market and developing economies, suggesting that machine learning techniques using pooled data could be an important macro tool for many countries.