Critique of statistical inference models to analyze the determinants of accessibility inequalities
DOI:
https://doi.org/10.58922/transportes.v32i3.2972Keywords:
Accessibility inequalities. Statistical inference models. Causal analysis.Abstract
The strategic diagnosis of socio-spatial inequalities in accessibility commonly uses statistical modeling to analyze causality. However, the formulated linear regression models may not be adequate, generating bias in the estimates and errors in the interpretation of the causal effects. Therefore, the objective of this work is to criticize the statistical models that analyze the cause-effect relationships between land-use and transport subsystems’ restrictions with accessibility levels in the strategic urban planning. For this, data from Fortaleza were used to exemplify the problems that can occur when carrying out a diagnosis without establishing the possible indirect paths between accessibility and its restrictions, in addition to not considering the sources of endogeneity. It was possible to verify that the analysis of complex phenomena through linear regression can benefit from the use of causal diagrams, allowing a better understanding of the causal paths between the variables, with the adequate control of endogeneity.
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Copyright (c) 2024 Maria Cristina Cavalcante Belo, Davi Garcia Lopes Pinto, Carlos Felipe Grangeiro Loureiro
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