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

19 Pages Posted: 30 Apr 2018

Date Written: April 13, 2018

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

JEL Classification: C45, O18

Suggested Citation

Steinkraus, Arne, Rethinking Policy Evaluation - Do Simple Neural Nets Bear Comparison with Synthetic Control Method? (April 13, 2018). Available at SSRN: https://ssrn.com/abstract=3161901 or http://dx.doi.org/10.2139/ssrn.3161901

Arne Steinkraus (Contact Author)

Institute of Economics ( email )

Abt-Jerusalem-Str. 7
Braunschweig, D-38106
Germany

HOME PAGE: http://https://www.tu-braunschweig.de/vwl

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