Abstract
In this paper, we want to examine how unemployment impacts social life, and, by using datasets from six European countries, we analyze the effect of unemployment on two of the main aspects of social life: social exclusion and life satisfaction. First, we predict unemployment rates using the Auto Regressive Integrated Moving Average (ARIMA) model and the results are further used in a linear regression model alongside social exclusion and life satisfaction data, thus obtaining the hybrid model. With the help of the point prediction method, we use the hybrid model to predict new values for the two aspects of social life for the upcoming three years and we analyze the results obtained in order to better understand their interconnection. The results suggest that unemployment has particularly adverse effects on the subjective perception of life satisfaction, furthermore increasing the social exclusion percentage.
Highlights
Unemployment is one of the most important and complex phenomena in the economic system and the unemployment rate is frequently used as an indicator for analyzing other indicators
On the other side we take a look at the social exclusion part of social life, so we considered the percentage of people at risk of poverty or social exclusion (PRPSE) from the same Eurostat survey [27], examining once again only the working-age population within the same time frame from 2005 to 2020
Starting from the desire to analyze the connection between unemployment on one hand and two of the most important parts of social life on the other hand, we studied the correlation between the unemployment rate (UR), the percentage of people at risk of poverty or social exclusion (PRPSE) and the self-perceived life satisfaction (SPLS), considering them two-by-two, pairwise
Summary
Unemployment is one of the most important and complex phenomena in the economic system and the unemployment rate is frequently used as an indicator for analyzing other indicators. Work done in [6] shows the use of online media content for unemployment prediction, while [7] studies the relationship between unemployment and psychological well-being by analyzing Twitter posts From another point of view, research shows that there are gender differences in the connection between unemployment and mental health, women tend to be less affected by unemployment than men in the labour market and in the family, mainly due to women’s roles in the family [8]. In [12], Ho and Xie used ARIMA to study the reliability forecasting of a mechanical system failure, concluding that this model produces satisfactory results concerning its performance in prediction. We take a look at two of the most important aspects of social life and observe that there is a positive slope between the unemployment rate and the percentage of people at risk of social exclusion and a negative slope between the unemployment rate and self-perceived life satisfaction
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