Impact of Housing Affordability and Other Socioeconomic Variables on Internal Migration in Lithuania

Abstract

The way housing affordability/wages/unemployment influenced internal migration of the population in Lithuania within the period of 2005−2019 is being analyzed in the article. Correlation-regression analysis is used to determine the relationships between the analyzed social phenomena. First, the correlation between housing affordability/wages/unemployment (their changes) and internal migration indicators is calculated, and the impact of data delays is assessed. Later simple and multiple regression equations are constructed. The conditions under which and how strongly housing affordability/wages/unemployment can influence population migration decisions have been identified in the analysis. Higher affordability of housing/wages is positively related to the number of people who moved to a certain Lithuanian city from other places in Lithuania per year. On the contrary, negative dependence of the number of people who moved to a certain city from other places in Lithuania on the unemployment rate in the city where those people moved in have been recorded. Both, affordability of housing and the unemployment rate explain actually 73−88 percent of variable dispersion of the internal migration in Vilnius, Kaunas and Klaipėda.

Life course decisions in Central and Eastern Europe: A gendered connection between family formation and moving intentions?

“…Spatial mobility also has a more important role in the life course of Central and Eastern Europeans than other Europeans. Aside from well-documented intra-European migration from east to west and from east to south (van Mol & de Valk, 2016), spatial mobility or internal migration within a country, has defined a considerable share of personal movement in CEE, largely from rural to urban areas (e.g., Kulu, 2006;Zhekova, 2006;Okólski, 2012;Rowe et al, 2019;Laurinavičius et al, 2021).…”

Macroeconomic Variables Influencing Housing Prices in Vilnius

“…In the same period, along with growing income housing prices (i.e., nominal house prices and housing rent prices) increased even more. Increase in prices was also very uneven, the same way as income growth (Laurinavičius et al, 2018(Laurinavičius et al, , 2021. Thus, the article analyzes if macroeconomic variables (such as unemployment/GDP per capita/inflation/wages/internal migration) have a statistically significant impact on housing prices.…”