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Rethinking Policy Evaluation – Do Simple Neural Nets Bear Comparison with Synthetic Control Method?

Arne Steinkraus ()

EconStor Preprints from ZBW - Leibniz Information Centre for Economics

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.

Keywords: Artificial Neural Nets; Machine Learning; Synthetic Control Method; Policy Evaluation (search for similar items in EconPapers)
JEL-codes: C45 O18 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-big and nep-cmp
Date: 2018
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