begins after week 9 in 2020, corresponding to the first COVID-19 case, while, for separations, the exposure period is after week 12 when layoffs were restricted by the government.

We use a difference-in-differences (DiD) approach, with the identifying assumption being that control and treated weeks move on parallel trends before the exposure period. This is tested visually as well as by including leads of the treatment for a sufficient number of weeks before (Autor, 2003; Cookson and Laliotis, 2017). The model is the following: where m is the number of hires (or separations) in week t (t=1,...,21) for group i (i=0,1), Treat is a binary indicator equal to 1 if the week is observed in 2020 and 0 if observed before (average of weeks 2018-2019), Post is a dummy switched on during the exposure period for both groups (week 9 or 12) and e is an error term. In this quasiexperimental setup, the coefficient of interest is the one associated with the interaction of treatment and exposure period indicators, i.e., α3. As the lockdown was lifted on May 4, we restrict this analysis for weeks 1-21 so our DiD estimates are not affected by increased labor market activity due to relaxing restrictions. Under the pre-exposure parallel trends assumption, the estimated DiD coefficients will indicate the short-term labor market impacts of COVID-19. As in (1), the model is estimated using negative binomial regressions.

# **4.4. Online vacancies**

Daily data on the number of vacancies posted online are extracted from the two most popular job search portals in Greece. In order to achieve a wide coverage of the market, we use Alexa’s ranking, which is web traffic data-based metric.<sup>14</sup> An automated data acquisition mechanism was set up to scrape and store daily information on job postings from all selected portals. Extracted data were pre-processed (e.g., string cleaning, language detection, avoid multiple entries per job ad and harmonization of company name and sectoral affiliation) before being used for the analysis. Advanced machine learning techniques were employed for deduplication. After deduplication, a total of 17,812 job vacancies were collected. Most job vacancies cover occupations such as sales and purchasing agents and brokers, administrative and specialized secretaries, administration professionals, transport and storage laborers, and information and communications technology professionals. A combination of Natural Language Processing and Name Entity Extraction/Recognition methods was adopted to extract the core information from the job postings. Examples of job posting fields extracted through this process include job title, job description, job category, location, job type, contract type, experience, qualification, employer, employer type, firm location, firm size. The extracted data cover the period from January 2020 through June 2020.

> 14 The the two highest-ranked job portals according to Alexa (www.alexa.com) are kariera.gr and jobfind.gr. Alexa’s traffic data take into account websites’ unique visitors and page views. A recent assessment conducted by Cedefop also lists kariera.gr and jobfind.gr among the top private job portals in Greece based on different sources, including a study conducted by ELSTAT in 2017 and based on number of advertisements, number of monthly visitors and Alexa ranking (Cedefop, 2018).

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