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Synthetic Data Generation for Economists

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arxiv 2011.01374 v2 pith:PC4FT3TB submitted 2020-11-02 econ.GN cs.LGq-fin.EC

Synthetic Data Generation for Economists

classification econ.GN cs.LGq-fin.EC
keywords datasyntheticanalyseseconomicgenerationgoogleinternalresults
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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As more tech companies engage in rigorous economic analyses, we are confronted with a data problem: in-house papers cannot be replicated due to use of sensitive, proprietary, or private data. Readers are left to assume that the obscured true data (e.g., internal Google information) indeed produced the results given, or they must seek out comparable public-facing data (e.g., Google Trends) that yield similar results. One way to ameliorate this reproducibility issue is to have researchers release synthetic datasets based on their true data; this allows external parties to replicate an internal researcher's methodology. In this brief overview, we explore synthetic data generation at a high level for economic analyses.

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