The intervention of local public authorities and the impact of the COVID-19 pandemic in Romania: a subnational analysis.

The COVID-19 pandemic had a strong territorial dimension, with a highly asymmetric impact among Romanian counties, depending on pre-existing vulnerabilities, regions' economic structure, exposure to global value chains, specialization, and overall ability to shift a large share of employees to remote working. The aim of this paper is to assess the role of Romanian local authorities during this unprecedented global medical emergency by capturing the changes of public spending at the local level between 2010 and 2021 and amid the COVID-19 pandemic, and to identify clusters of Romanian counties that shared similar characteristics in this period, using a panel data quantitative model and hierarchical cluster analysis. Our empirical analysis shows that between 2010-2021, the impact of social assistance expenditures was higher than public investment (capital spending and EU funds) on the GDP per capita at county level. Additionally, based on various macroeconomic and structural indicators (health, labour market performance, economic development, entrepreneurship, and both local public revenues and several types of expenditures), we determined seven clusters of counties. The research contributes to the discussion regarding the increase of economic resilience but also to the evidence-based public policies implementation at local level.

Teleworking-An Economic and Social Impact during COVID-19 Pandemic: A Data Mining Analysis.

The health crisis generated by the COVID-19 pandemic has induced, among other things, an increase in the importance of remote work or teleworking (TL) in the current period. The objective of this research is to identify the economic and social impact of telework in changing the behavior of employees in Romania. The research was conducted approximately one year after the onset of the pandemic until the beginning of the vaccination period in Romania. The research proposed includes three main directions of analysis of the extracted data, which are related to telework efficiency, this being considered one of the most important indicators for a company. In order to obtain conclusive results, we used a mixed methodology, combining results obtained through a survey based on a self-administered electronic questionnaire, with a data mining analysis. Detailed analysis of the groups identified based on work efficiency allowed us to highlight the most common employee profiles. This analysis was doubled by a second classification experiment, which provided us a more detailed analysis of the groups identified based on job satisfaction and highlighted the most common employee profiles. The expansion of telework in various economic areas is a result of adaptation to the new economic and social conditions caused by the COVID-19 pandemic.