经济学家的综合数据生成
Synthetic Data Generation for Economists
摘要：
随着越来越多的科技公司从事严格的经济分析，我们面临着一个数据问题：由于使用敏感、专有或私人数据，内部文件无法复制。读者只能假设模糊的真实数据（例如，谷歌内部信息）确实产生了给定的结果，或者他们必须寻找可比较的面向公众的数据（例如，Google Trends）也会产生类似的结果。改善这种可重复性问题的一种方法是让研究人员根据他们的真实数据发布合成数据集;这允许外部各方复制内部研究人员的方法。在这篇简短的概述中，我们探讨了用于经济分析的高层次合成数据生成。
英文摘要：
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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