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Using Machine Learning for Causal Inference

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Machine Learning (ML) is still an underdog in the field of economics. However, it gets more and more recognition in the recent years. One reason for being an underdog is, that in economics and other social sciences one is not only interested in predicting but also in making causal inference. Thus many “off-the-shelf” ML algorithms are solving a fundamentally different problem. We here at STATWORX are also facing a variety of problems e.g. dynamic pricing optimization. “Prediction by itself is only occasionally sufficient. The post office is happy with any method that predicts correct addresses from hand-written scrawls…[But] most statistical surveys have the identification of causal factors as their ultimate goal.” – Bradley Efron Introduction However, the literature of combining ML and casual inferencing is growing by the day. One common problem of causal inference is the estimation of heterogeneous…
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