Generation of socio-economic public policies in Colombia through Data Science and Machine Learning tools.

Problem definition

The high level of inequality in Colombia is a fundamental constraint to economic growth and social progress. The country has one of the highest levels of income inequality in the world; the second highest among 18 countries in Latin America and the Caribbean (LAC), and the highest among all OECD countries (World Bank, 2021).

In this context, the Colombian state has generated targeting elements such as Socio-Economic Stratification and Sisbén in order to generate public policies conducive to mitigating poverty and generating social mobility for its most vulnerable population. Throughout this study, the aim is to analyze the relevance of various variables involved in public decision-making and the generation of programs whose main objective is to impact the neediest population.

Aims of the project

To analyze the relevance and correlation of targeting tools such as socio-economic stratification and the Sisbén with the public policies generated in the social and economic spheres by the Colombian state.

To create a base document that allows the application of emerging technologies in this case data science tools and ML that will serve as a guide in subsequent studies and projects involving public policies of the Colombian state.

Tools

Python, Pandas, Plotly, Dash, Tensorflow

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