We use a dataset covering nearly the entire target population based on passively collected data from smartphones to measure the impact of the first COVID-19 wave on the gig economy in Poland. In particular, we focus on transportation (Uber, Bolt) and delivery (Wolt, Takeaway, Glover, DeliGoo) apps, which make it possible to distinguish between the demand and supply part of this market. Based on Bayesian structural time-series models, we estimate the causal impact of the first COVID-19 wave on the number of active drivers and couriers. We show a significant relative increase for Wolt and Glover (15% and 24%) and a slight relative decrease for Uber and Bolt (-3% and -7%) in comparison to a counterfactual control. The change for Uber and Bolt can be partially explained by the prospect of a new law (the so-called Uber Lex), which was already announced in 2019 and is intended to regulate the work of platform drivers.

翻译：我们使用一套基于从智能手机被动收集的数据的覆盖近全部目标人口的数据集来衡量第一次COVID-19波对波兰干工业经济的影响,特别是侧重于运输(Uber、Bolt)和交付(Wolt、Takeaway、Glover、DeliGooo)应用软件,从而有可能区分这一市场的供需部分。根据巴耶斯结构时间序列模型,我们估计了第一次COVID-19波对活跃驾驶员和送货员人数的因果关系。我们显示了沃尔特和格洛弗(15%和24%)的相对比重大幅上升,与反事实控制相比,Uber和Bolt(3%和-7%)的相对下降。Uber和Bolt的变动可以部分地由2019年已经宣布的新法律(所谓的Uber Lex)的前景来解释,其目的是规范平台司机的工作。