The Impact of Economic Performance and Human Development on Road Traffic Fatalities in Iran with the Approach of Autoregressive Distributed Lag Models

Document Type : Original Article

Authors

1 Assistant Professor, Economics Department, Islamic Azad University, Zanjan Branch, Zanjan, Iran.

2 Assistant Professor, Civil Engineering Department, Islamic Azad University, Zanjan Branch, Zanjan, Iran.

3 Assistant Professor, Statistics and Mathematics Department, Islamic Azad University, Zanjan Branch, Zanjan, Iran.

Abstract

The purpose of this research is to investigate the impact of economic performance and human development on road traffic fatalities (RTF) in Iran. The statistical data used in this research is from the Central Bank of the Islamic Republic of Iran and the World Bank for the years
1379-1400 and it is annual and Eviews 10 software is used to estimate the proposed model. The time series data of this study are not all stationary, and based on this, in order to estimate the desired pattern, the self-distribution approach with wide intervals is used. The ARDL (1,0,0,0) model was chosen based on the Schwartz-Bayesian criterion. The estimation results with such an approach in the short term show that RTF (-1) and unemployment rate have a significant positive effect on road fatalities. This effect has been obtained negative significant for the variables of GDP per capita and human development index in the short term. The estimated long-term coefficients in affecting road fatalities for the variables of GDP per capita and human development are negative and significant, and for the explanatory variable of unemployment rate is positive and significant. The results show that sustainable development is one of the dimensions of maintaining the safety of people's lives in the road transportation system, It is necessary to pass through the channel or path of investment in human development and this investment is the main pillar and core in reducing road traffic fatalities. The results of the analysis in the framework of the error correction model indicate the value of -0.174 for the coefficient of the error correction, which indicates a relatively low speed of adjustment.

Keywords


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