Food access of poor households in Mexico: a classification tree application
Poverty and lack of food access are critical problems in developing countries, affecting more than 20 % of the population in Mexico. This research aimed to analyze the factors influencing food access in Mexican households and to develop a predictive model. The machine learning technique, known as cl...
| Authors: | , , , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2024 |
| Country: | México |
| Institution: | UNIVERSIDAD AUTÓNOMA CHAPINGO |
| Repository: | Revista de Geografía Agrícola |
| Language: | Spanish |
| OAI Identifier: | oai:ojs2.revistas.chapingo.mx:article/606 |
| Online Access: | https://revistas.chapingo.mx/geografia/article/view/606 |
| Access Level: | Open access |
| Keyword: | Políticas sociales carencias monetarias líneas de bienestar canasta alimentaria hambre Social policies monetary deprivation monetary deprivation, hunger |
| Summary: | Poverty and lack of food access are critical problems in developing countries, affecting more than 20 % of the population in Mexico. This research aimed to analyze the factors influencing food access in Mexican households and to develop a predictive model. The machine learning technique, known as classification tree, was used and the results were compared with those of a logit model, frequently used in the literature. In terms of accuracy, the classification tree outperformed the logit model inidentifying households at risk of food insecurity (0.6039 vs. 0.5402) and provided a visual interpretation of the results. The findings suggest that households living in poverty, located in urban areas, with more than three members or without basic education, should be prioritized in social policies, since they are more likely to face food access problems in Mexico |
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