Rich Cities, Poor Countryside? Social Structure of the Poor and Poverty Risks in Urban and Rural Places in an Affluent Country. An Administrative Data based Analysis using Random Forest

Hümbelin, Oliver; Hobi, Lukas Christian; Fluder, Robert (10 November 2021). Rich Cities, Poor Countryside? Social Structure of the Poor and Poverty Risks in Urban and Rural Places in an Affluent Country. An Administrative Data based Analysis using Random Forest Bern: University of Bern Social Sciences Working Paper

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In many countries, it is difficult to study subnational poverty patterns, as official statistics often rely on surveys with limited ability to disaggregate regionally. This is a drawback because the social and economic structure varies within countries, which has a significant impact on poverty. To address poverty, it is therefore important to further understand urban/rural differences. In this context, administrative data-based approaches offer new opportunities. This paper contributes to the field of territorial poverty studies by using linked tax data to examine poverty in a large political district in Switzerland with 1 million inhabitants and rural and urban parts. We measure poverty using income and financial reserves (asset-based poverty) and examine poverty in urban and rural areas. By doing so we can compare the social structure of the poor in detail. We then use random forest based variable importance analysis to see whether the importance of poverty risks factors differs in urban and rural parts. We can show that poor people in rural areas are more likely to be of retirement age compared to the urban parts. Among the workforce, the share of poor is larger for those who work in agriculture compared to those working in industry or the service sector. In urban areas, the poor are more often freelancers and people of foreign origin. Despite on where they live, people with no or little education, single parents, and people working in gastronomy/tourism are disproportionately often poor. With respect to risk factors, we find that the general opportunity structure like density of workplaces or aggravated access in mountain areas seem to be of minor importance compared to risk factors that relate to the immediate social situation. Low attachment to the labor market is by far the most important characteristic predicting poverty on the household level. However, the sector of occupation is of big importance too. Since the possibilities to engage in a specific occupation are linked to the regional opportunity structure, this result fosters the argument that territorial opportunities matter.

Item Type:

Working Paper

Division/Institute:

School of Social Work > Social Security focus area
School of Social Work > Institute for Social Security and Social Policy

Name:

Hümbelin, Oliver;
Hobi, Lukas Christian and
Fluder, Robert

Subjects:

H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
H Social Sciences > HN Social history and conditions. Social problems. Social reform

Publisher:

University of Bern Social Sciences Working Paper

Funders:

[UNSPECIFIED] Schweizerischer Nationalfonds

Projects:

[UNSPECIFIED] Ungleichheit, Armutsrisiken und Wohlfahrtsstaat

Language:

English

Submitter:

Oliver Hümbelin

Date Deposited:

22 Dec 2021 14:30

Last Modified:

22 Dec 2021 14:30

Uncontrolled Keywords:

poverty, poverty risk factors, regional difference, admin-data, random forest

URI:

https://arbor.bfh.ch/id/eprint/16156

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