Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/177390 
Year of Publication: 
2018
Publisher: 
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft, Kiel und Hamburg
Abstract: 
With the advent of big data in economics machine learning algorithms become more and more appealing to economists. Despite some attempts of establishing artificial neural networks in in the early 1990s, only little is known about their ability of estimating causal effects in policy evaluation. We employ a simple forecasting neural network to analyze the effect of the construction of the Oresund bridge on the local economy. The outcome is compared to the causal effect estimated by the proven Synthetic Control Method. Our results suggest that – especially in so-called prediction policy problems – neural nets may outperform traditional approaches.
Subjects: 
Artificial Neural Nets
Machine Learning
Synthetic Control Method
Policy Evaluation
JEL: 
C45
O18
Document Type: 
Preprint

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