Unemployment in Russia during COVID-19: Teleworkability and Face-to-Face context
The aggregate data, scripts, and Supplementary Tables are an additional material to the paper Kotyrlo E. "The Impact of Anti-COVID-19 Restrictions and Transitory Unemployment Insurance Policies on Unemployment in Russia" Journal of Economic Studies, 2023, doi: 10.1108/JES-12-2022-0615. Aggregate data are composed on the base of 5 mln monthly administrative records, January 2019 – December 2020, on individuals registered as unemployed by the Russian Public Employment Service. Individual data are received through the Research Data Infrastructure (INID) (https://www.data-in.ru/). Aggregate data account for individuals with a period of less than 6 months between application for unemployment and their latest working month. They are aggregated by teleworkability (TW) and face-to-face (F2F) indices as proposed by Dingel and Neiman (2020) and Sostero et al. (2020) into monthly data. Data report 149 latest professional occupations that are categorized by the TW index and a F2F score. Data are aggregated by TW index, by 5 categories (0, 2, 4, 6, 8) of face-to-face intensity and, in addition, by gender and three levels of education (primary, secondary and higher). Stata do files provide a code for two-way fixed effects estimates and plots (TWFE.do) of TW (F2F) effects and Wald and change-in-change DID (fuzzy-did.do) effects proposed by de Chaisemartin and D’Haultfoeuille (2020). R script provides a code for doubly robust ATT estimates and plots of TW (F2F) effects as proposed by Callaway and Sant’Anna (2021).