How corruption affects the development of a nation: case study Mexico.

In this work we analyze the correlations between indexes that quantify corruption and indexes used to estimate the measure of wealth and well-being of a nation. Following the identification of the corruption-affected indexes, some strategies for lowering these indexes are put forth, and time estimates (six years in the future) are used to forecast the advantages of these strategies' execution on indexes that measure a country's wealth and well-being. Our statistical study demonstrates the detrimental effects that corruption has on peace, climate change performance and social progress of the Mexican nation. In this sense, the adverse impacts of corruption on a country's growth might be mitigated by policies that lower its rates; seeking to reduce its negative impacts on indexes related to the development of a nation. Machine learning projections show us scenarios where measures are implemented to reduce corruption and the benefits on the development indexes of a nation are visualized.