Ricardo A. Pasquini
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September 9, 2020 by admin 0
Economics, Uncategorized

An indebtedness atlas for Argentina

The indebtedness atlas An indebtedness atlas for Argentina The level of indebtedness of the general population has recently been signaled by national authorities [as one of the most pressing problems in Argentina1. While the country ranks relatively low in terms of financial inclusion, for example, with less than 10% of adults borrowing from a traditional bank in 2017 (Demirguc-Kunt, et. al, 2018), there is also an active debate on the role of high-interest rates loans, such as payday loans2. While the literature has shown that neighborhoods matter for upward income mobility or in shaping children outcomes (Chetty et al. 2020), the relationship between neighborhoods and access to credit or indebtedness has remained relatively unexplored. Which neighborhoods in Argentina are the most problematic in terms of financial distress of their population? Which neighborhoods exhibit signals to be credit constrained? Does the physical proximity of credit suppliers play a role? Are there neighborhoods which tend to finance at higher costs, for example, due to a higher participation of payday borrowing? What has been the effects of national policies providing low cost to the population on their indebtedness and financial distress? In this project we are building fine-grain maps of the indebtedness of…

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Big Data Financial inclusion Households Finance Indebtedness

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Categories

  • Causal Inference (4)
  • Coding Notes (8)
  • Defi (1)
  • Economics (8)
  • Machine Learning (1)
  • Uncategorized (19)
  • Urban Economics (3)

Recent Posts

  • Note on the Impact of Liquidation on Health Factor in Overcollateralized Loans
  • Econometrics with simulations 📚
  • Explicando Inferencia por Aleatorización a un futbolero
  • Optimal calibration of a ML classifier based on business knowledge
  • Note on AMMs “picked-off” risk

Tag Cloud

AMM apps bienes publicos causal inference classification conda COVID-19 criptomonedas cryptocurrencies defi econometrics economía de mercados Ethereum Exportar resultados Export output Financial inclusion financiamiento cuadrático fraud geopandas Geospatial analysis Gitcoin h3 hexagons Households Finance Indebtedness Jupyter Loops machinelearning Mercado de Alquileres MongoDB negocios precision proyectos ingeniería public goods pymongo python quadratic funding recall Regression roc-curve scalability Stata Tablas Tables ubuntu
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Recent Posts

  • Note on the Impact of Liquidation on Health Factor in Overcollateralized Loans
  • Econometrics with simulations 📚
  • Explicando Inferencia por Aleatorización a un futbolero
  • Optimal calibration of a ML classifier based on business knowledge
  • Note on AMMs “picked-off” risk
  • Un atlas de deudas para Argentina
  • Bienes públicos, Gitcoin, y financiamiento cuadrático
  • An indebtedness atlas for Argentina

Tags

AMM apps bienes publicos causal inference classification conda COVID-19 criptomonedas cryptocurrencies defi econometrics economía de mercados Ethereum Exportar resultados Export output Financial inclusion financiamiento cuadrático fraud geopandas Geospatial analysis Gitcoin h3 hexagons Households Finance Indebtedness Jupyter Loops machinelearning Mercado de Alquileres MongoDB negocios precision proyectos ingeniería public goods pymongo python quadratic funding recall Regression roc-curve scalability Stata Tablas Tables ubuntu