PANEL DATA AND SPATIAL ECONOMETRIC: ANALYSIS OF TRANSPORT-RELATED SOCIAL OUTCOMES - A COMPARATIVE STUDY OF ROAD TRAFFIC FATALITIES AND URBAN DEMOGRAPHICS

Authors

  • Pedro Silva

DOI:

https://doi.org/10.63330/sasciencesv6n2-041

Keywords:

Panel Data Models, Fixed Effects, Random Effects, Spatial Econometrics, Moran's I, LISA, Spatial Regression, Traffic Fatalities, Urban Demographics, Coimbra

Abstract

This paper presents a comprehensive econometric analysis employing two complementary methodological frameworks: panel data models and spatial regression techniques. The first case study examines the determinants of road traffic fatalities across 51 US states during the period 1990-1996, utilizing Ordinary Least Squares (OLS), Fixed Effects, and Random Effects specifications to identify significant socioeconomic and demographic predictors. The second case study investigates the spatial distribution of elderly population (aged 65 and over) in Coimbra, Portugal, based on 2021 Census data, employing Moran's I statistics, Local Indicators of Spatial Association (LISA), and spatial regression models including Spatial Lag and Spatial Error specifications. Our findings reveal that ethanol consumption per capita, income levels, and age structure significantly influence traffic fatalities, while spatial autocorrelation analysis confirms moderate but statistically significant clustering patterns in the distribution of elderly residents and accessible housing infrastructure. The Spatial Error Model emerges as the best-fitting specification for the Coimbra dataset, indicating that unobserved spatially correlated factors substantially influence the spatial distribution of aging population. These results contribute to the understanding of how econometric methods can inform transport policy and urban planning decisions.

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References

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Published

2026-06-26

How to Cite

Silva, P. . (2026). PANEL DATA AND SPATIAL ECONOMETRIC: ANALYSIS OF TRANSPORT-RELATED SOCIAL OUTCOMES - A COMPARATIVE STUDY OF ROAD TRAFFIC FATALITIES AND URBAN DEMOGRAPHICS. South American Sciences, 6(2), 1–28. https://doi.org/10.63330/sasciencesv6n2-041

Issue

Vol. 6 No. 2 (2026): South American Sciences

Section

Artigos

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