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Interpersonal lending network dataset of a Hungarian village in a disadvantaged region based on a quantitative survey
The dataset presented in this paper consists of a network of interpersonal lending relations from a single village of a deprivated area of Hungary. The data are originated from quantitative surveys from May 2014 to June 2014. The data collection was embedded in a Participatory Action Research (PAR)...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945707/ https://www.ncbi.nlm.nih.gov/pubmed/36845647 http://dx.doi.org/10.1016/j.dib.2023.108946 |
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author | Gosztonyi, Márton Havran, Dániel Pollák, Zoltán Berlinger, Edina |
author_facet | Gosztonyi, Márton Havran, Dániel Pollák, Zoltán Berlinger, Edina |
author_sort | Gosztonyi, Márton |
collection | PubMed |
description | The dataset presented in this paper consists of a network of interpersonal lending relations from a single village of a deprivated area of Hungary. The data are originated from quantitative surveys from May 2014 to June 2014. The data collection was embedded in a Participatory Action Research (PAR) which aimed to investigate the financial survival strategies of low-income households in a Hungarian village in a disadvantaged region. The directed graphs of lending and borrowing are a unique dataset that empirically captures a hidden and informal financial activity between households. The network contains 164 households and 281 credit connections among them. |
format | Online Article Text |
id | pubmed-9945707 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99457072023-02-23 Interpersonal lending network dataset of a Hungarian village in a disadvantaged region based on a quantitative survey Gosztonyi, Márton Havran, Dániel Pollák, Zoltán Berlinger, Edina Data Brief Data Article The dataset presented in this paper consists of a network of interpersonal lending relations from a single village of a deprivated area of Hungary. The data are originated from quantitative surveys from May 2014 to June 2014. The data collection was embedded in a Participatory Action Research (PAR) which aimed to investigate the financial survival strategies of low-income households in a Hungarian village in a disadvantaged region. The directed graphs of lending and borrowing are a unique dataset that empirically captures a hidden and informal financial activity between households. The network contains 164 households and 281 credit connections among them. Elsevier 2023-02-02 /pmc/articles/PMC9945707/ /pubmed/36845647 http://dx.doi.org/10.1016/j.dib.2023.108946 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Gosztonyi, Márton Havran, Dániel Pollák, Zoltán Berlinger, Edina Interpersonal lending network dataset of a Hungarian village in a disadvantaged region based on a quantitative survey |
title | Interpersonal lending network dataset of a Hungarian village in a disadvantaged region based on a quantitative survey |
title_full | Interpersonal lending network dataset of a Hungarian village in a disadvantaged region based on a quantitative survey |
title_fullStr | Interpersonal lending network dataset of a Hungarian village in a disadvantaged region based on a quantitative survey |
title_full_unstemmed | Interpersonal lending network dataset of a Hungarian village in a disadvantaged region based on a quantitative survey |
title_short | Interpersonal lending network dataset of a Hungarian village in a disadvantaged region based on a quantitative survey |
title_sort | interpersonal lending network dataset of a hungarian village in a disadvantaged region based on a quantitative survey |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945707/ https://www.ncbi.nlm.nih.gov/pubmed/36845647 http://dx.doi.org/10.1016/j.dib.2023.108946 |
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