Statistical analysis of the impacts of COVID crisis on unemployment in post-soviet countries

Unemployment and its effects on the country’s economy have been important throughout the history of market economies. There are two approaches to unemployment: firstly, it is a large problem due to the withdrawal of labor resources from the economic cycle; secondly, it is an opportunity to redistrib...

Full description

Saved in:
Bibliographic Details
Main Authors: Tolmachev, M., Tsypin, A., Latkov, A., Barashov, N.
Format: Conference Proceeding
Language:English
Subjects:
Economic analysis
Economic models
Labor
Market economies
Statistical analysis
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Unemployment and its effects on the country’s economy have been important throughout the history of market economies. There are two approaches to unemployment: firstly, it is a large problem due to the withdrawal of labor resources from the economic cycle; secondly, it is an opportunity to redistribute labor resources to new economic sectors. We believe that there can be another approach: the unemployment level can be indicative of the state of the economy, especially during crises. Therefore, this research is highly relevant during the COVID crisis. The purpose of this research is to calculate the effects of the COVID crisis on the unemployment level in post-Soviet countries. To accomplish the purpose set, we used the historical method, comparisons, and mathematical statistics. The results of the research showed that despite the similarities between the causes of the crises, the existing economic models in the post-Soviet countries respond differently to shocks. This can be manifested in unemployment level variations in the republics in question depending on the remoteness of the market transformation. The effects of the economic situation on the unemployment level (Okun’s law) in the post-Soviet counties differed under various crises, which is confirmed by the differences in point distributions in 2008-2009 and 2020.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0167626