In Argentina, households financial distress has recently been identified by national authorities as one of the most pressing problems in the country.1 Related discussions in the media have also taken place, for example, regarding the role of high interest rates credit lending.2 These discussions at the national level are paralleled by a growing interest of the financial literature in the topic. There is a growing interest in the effects of accelerated financial inclusion, a phenomenon driven by innovations in fintech and a search for democratization in finance.3 These are some of the issues behind our interest in studying questions related to access to finance and financial distress, with Argentina as a case study.
An additional factor is that a growing academic literature shows the importance of studying questions related to the economic circumstances of households at the local level, evidencing, for example, the relevance of a unit of analysis such as the neighborhood, to explain access to economic opportunities, differential conditions in terms of access to health, among other factors.4 Studying the geographical variation in terms of financial distress, could allow identifying particular areas that are experiencing debt distress and also help the formulation of locally targeted policies.
We are currently building a "Debt Distress Atlas", a series of maps and visualizations that are aimed to describe the geography of debt distress in the country, and which we expect will allow the study of specific research hypothesis.
We built these maps from anonymized data for a sample of more than 4 million people. The primary source of data is Central de Deudores del Banco Central (central bank's credit bureau). This is individual level data on the state and amount of debt contracted by them with banks and registered non-bank lenders.
The Atlas
A live site with the atlas (alpha version) is here .
As illustrated in the image reproduced below, the Atlas currently allows navigating maps on financial distress across the main urban agglomerates in Argentina. For instance, the map below shows the "average debt status" of households in the Great Buenos Aires region, an area where approximately 15 million people live.
The average debt status is based on an indicator of an individual debt defined by the Central Bank. The status indicator takes a value equal to 1 for those debts without arrears, and therefore considered in a "normal" stage. It takes a value equal to 2 for delays in payments between 31 and 90 days, called "low risk". A value equal to 3 for those delayed between 90 and 180 days, called "medium risk". A value equal to 4 for arrears of more than 180 days up to one year, called ‘high risk’. A value equal to 5 to arrears of more than one year, called "irrecoverable". The map shows the average of the debt status of individuals living in the respective areas.
The map shows that areas under stress are generally located in the margins of the urban agglomerate, suggesting a correlation with other economic vulnerability indicators such as poverty rates, and urban accesibility.
Comments are particularly welcome.