Land use disadvantages in Germany: A matter of ethnic income inequalities?

Abstract

Environmental hazards affect people from different income groups and migration backgrounds on different levels. The research on environmental inequalities and environmental justice has proposed several theories to explain such inequities; still, it remains unclear which of these theories applies to the German societal context. This research investigates whether individual-level income differences between Germans and migrants account for objectively measured exposure to the environmental goods and bads of land use, specifically soil sealing and green spaces. Marginal effects and predictions based on georeferenced survey data from the German General Social Survey reveal that Germans with higher incomes live in areas with better neighbourhood quality. Germans with lower incomes are exposed to fewer disadvantages stemming from land use, and there is no marginal difference between nonurban and urban municipalities. Spatial assimilation in high-income groups occurs; however, the difference in low-income groups can be explained by place stratification and discrimination in the housing market. While this study uses more indirect and non-hazardous measures of environmental quality – in contrast to air pollution or noise – it provides evidence that such indicators also create distributional injustices in Germany.

Thematic Review of Motivational Factors, Types of Uncertainty, and Entrepreneurship Strategies of Transitional Entrepreneurship among Ethnic Minorities, Immigrants, and Women Entrepreneurs

“…Market disadvantages theory (MDT), otherwise called the iron cage perspective, is traced to the pioneering works of Weber (1930) and Light (1979), who both affirmed that racial discrimination in employment engenders employment disadvantages or exclusion from economic activities. The MDT explains the degree of immigrant integration into the labor market in the host countries when measured in terms of immigrant composition, the number of employees, and occupational status in the host countries (Jünger 2021). The MDT is beneficial for explaining transitional entrepreneurs, such as immigrants, ethnic groups, and minorities, who take up entrepreneurship as an economic survival strategy in foreign countries (Light 1979;Smith-Hunter and Boyd 2004;Chrysostome 2010).…”

“…Level 1 uncertainty presents a clear future with likelihoods, possibilities, and probabilities of success for ethnic, immigrant, and women entrepreneurs in their operating environment, usually in developed countries such as the UK, the US, Canada, and Australia, where there are new market opportunities and strong support for transitional entrepreneurship. Furthermore, Level 2 uncertainty presents several alternate paths and trajectories of ethnic, immigrant, and women entrepreneurs in Western European countries that are particularly successful in integrating ethnic minorities and immigrants (Jünger 2021). Some of the reported types of uncertainty facing transitional entrepreneurs in Britain, Scotland, and by extension other Western countries that largely influence the success or failure of transitional entrepreneurship include racial discrimination, drop-in paid employment, insufficient economic reward in self-employment, language difficulties, business venturing risk, restrictive immigration policy, low participation in postcompulsory education, the level of entrepreneurial ambitions, demographic change, lower returns in retail and small businesses, rising competition in business venturing, and globalization waves (Jones and Ram 2003;Blanchflower 2004;Deakins et al 2007;Siqueira 2007;Clark and Drinkwater 2010;Li et al 2003).…”

Spatial Data Analysis

“…Examples of spatial topics in the social sciences include labour market dynamics (Martén et al 2019, Nisic 2017, Zoch 2021, processes of residential segregation (Roberto 2018, Tóth et al 2021) and gentrification (Fransham 2020, Zapatka & Beck 2021, the spatial distribution of environmental goods or bads (Boillat et al 2022, Jünger 2022, Rüttenauer 2018, the consequences of extreme weather events (Ogunbode et al 2019, Hoffmann et al 2022, Rüttenauer 2023 or the access to infrastructural conditions (Moreno-Monroy et al 2018, Liao et al 2020, Wiedner et al 2022.…”

Environmental Inequality and Residential Sorting in Germany: A Spatial Time-Series Analysis of the Demographic Consequences of Industrial Sites

“…The expo sure level to envi ron men tal pol lu tion is not equally dis trib uted across households. Research has shown that eth nic and racial minor i ties in the United States as well as in Europe are dis pro por tion ately exposed to envi ron men tal harms (e.g., Ard 2015;Glatter-Götz et al 2019;Jünger 2021;Mohai and Saha 2015a;Pasetto et al 2019;Pastor et al 2005;Rüttenauer 2018Rüttenauer , 2019a. Similarly, eco nom i cally dis ad vantaged house holds tend to live in areas with higher lev els of envi ron men tal pol lu tion (e.g., Ash and Fetter 2004;Downey and Hawkins 2008;Raddatz and Mennis 2013;Wolverton 2009).…”