Analyzing The Impact of COVID-19 on the Moroccan Job Market by Mining Job Ads

• Main Authors: Rahhal, Ibrahim, Khaouja, Imane, Carley, Kathleen M, Kassou, Ismail, Sbihi, Nada
• Format: Conference Proceeding
• Language: English
• Subjects: Companies; Covid impact; COVID-19; Economics; Industries; Job market analysis; pandemic; Pandemics; Time measurement; Uncertainty
• ISSN: 2159-5119
• DOI: 10.1109/ICTMOD55867.2022.10041826

The COVID-19 health crisis has drastically changed the lives of individuals around the world. The fear of infection, public guidelines, and a great deal of uncertainty resulted in a sharp decline in economic activity, disrupting global value chains and causing widespread job losses. Morocco, like the rest of the world, has experienced different changes in the job market. In this paper, we examine the effects of the pandemic on the Moroccan job market, focusing on which sectors and occupations were affected the most. Therefore, we analyze a 3-year-long collected dataset of job ads to understand the shifts that occurred in the job market. We use a variety of machine learning and text-mining techniques to process these ads. As part of our analysis, we classify those job ads according to the sector and the job title they mention. Our results show that the number of job ads has severely decreased during the lockdown period since the majority of businesses have stopped their activities. The demand declined in some sectors more than others during this period. However, despite the economic downturn, certain industries and sectors maintained most of their operations, and in some cases even experienced an increase in demand, such as the transport & logistic sector.