This comparative study focuses on the barriers to social and economic inclusion, as well as the integration and coping strategies of Arab and Moldovan migrants in Romania. We explored the integration barriers they face, the main individual and societal aspects that lead to their resilience, and their self-perception of vulnerability, by carrying out 35 psychosocial interviews and four focus groups with young migrants (aged 18 to 29), belonging to the two different subgroups (of Arab and Moldovan origins, respectively). The comparative analysis revealed that migrants from Arab countries face harsher integration barriers compared to Moldovan migrants, they have a more severe self-perceived vulnerability, and their integration may be a longer and more complex process. Results showed that mastery of the language and the network of acquaintances play an indispensable role in inclusion. Moldovans integrate more easily than Arabs, thanks to their fluency in Romanian, the native language shared with the majority local population, the geographical and cultural proximity to the country of destination, and the larger personal network. We highlight the need for improving integration policies for young migrants, tailoring them to the specific problems and barriers that migrants are facing.

This study examines the short-run and long-run relationships between happiness and two economic variables, namely income and unemployment. Drawing from a sample of eleven European countries over a time period of 36 years spanning 1985–2020, we find that both income and unemployment have a significant impact on happiness levels. In particular, the results show that higher income leads to higher happiness in the long-run, but the short-run impact is rather weak. Moreover, unemployment decreases people’s happiness levels both in the short and in the long-run, emphasizing the need for European policies directed to job creation.

This study focuses on the integration facilitators of young migrants in Romania, as resulting from the information gathered through a Photovoice participatory action research method. Young third country nationals were asked to take photos which they thought best summed up their migration experiences. Next to the photos, the migrants were also asked to submit short texts describing the captured images and the meanings that these had for them, thus adding richness and nuance to the data. The evidence gathered reveals that several factors, such as access to education, interacting with a new culture, and with new places and people, are perceived as opportunities and positive migration outcomes. Therefore, human and social capital, as well as the natural or urban environment in the host country, contribute to the enhancement of integration opportunities for young migrants. The paper sets out to analyze how such factors which can facilitate integration are captured in a PAR. Research results show that young migrants perceive their experiences in Romania as enhanced by some factors through which they advance in their integration paths.

COVID-19 pandemic has affected and still affects many countries in the world, reshaping many of the economic and social activities. Based on the results of an online survey, this paper highlights the perceptions of the way the pandemic has affected one of the most vulnerable categories in a society, migrants. We focus our research on the migrants and refugees from Middle East and North Africa (MENA) countries, living in Europe, as in the recent years and mostly after the migrant crisis in 2015, they are in large numbers in European countries. Using ANOVA models, our results show that unemployed migrants, students but also migrants who find it difficult on present income are most worried about the COVID-19 crisis and fell they will be greatly affected in terms of income and employment by this crisis. Also, women are more worried by COVID-19 than men with respect to the health aspect.

The purpose of this article is to determine the factors influencing the birth rate in Romania, by incorporating explicitly the spatial factor in the proposed models. The study is justified by the dramatic fall of the birth rate over the past three decades. With a negative natural population growth and an increasing number of emigrants, the population will become older and there will be a few million less in the next decades. To achieve the objective, various spatial modelling methods were used, such as Spatial AutoRegressive Model (SAR), Spatial Error Model (SEM), Geographically Weighted Regression (GWR) and a spatial panel data model. The data granularity is at the county level for the year 2020. Results show that GDP per capita and the amount of financial support received by families for raising a child have a significant effect on the birth rate. Using a spatial approach for modelling the birth rate, we reveal demographic problems that may exist in certain areas and identify the regions that would require a policy to stimulate birth rates.

Spatial data analysis approaches have grown in popularity in recent years as there has been an increased interest in studying migration at the regional level. We employed in our analysis the Nomenclature of Territorial Units for Statistics (NUTS) level, which offers a more thorough view of migratory patterns inside a nation as well as among EU countries.Using spatial data analytic tools, this research aims to investigate the key determinants of international migration at the NUTS2 level. Using data from the Eurostat database, we undertake an extensive analysis of migration movements in a sample of European Union countries. We apply spatial econometric models to examine the relationship between crude rate migration and other relevant variables as independent variables. Although the available data at the NUTS2 level of regional ranking are limited, we believe that we included the most comprehensive set of relevant variables in our analysis.Our study contributes to the existing literature on migration determinants by highlighting the importance of spatial analysis techniques in understanding migration factors at the NUTS2 level.