Investigating the Long Run Causality between CoronaVirus Prevalence and Selected Economic Variables in Iran Using Estimation Error Correction Term Coefficient

Document Type : Research Paper

Author

Lecturer and PhD student in Economics, Islamic Azad University, Isfahan Branch (Khorasgan), Isfahan, Iran.

10.22103/jdc.2022.18479.1171

Abstract

Objective: Ever since the World Health Organization formally identified the corona virus as a worldwide epidemic, various countries have entered new and, of course, unknown stages. The prevalence of the corona virus, in addition to posing serious health risks and problems, has had significant and sometimes irreversible effects on global trade and the economy. From there Iran is no exception to the prevalence of coronary disease in other countries and is facing a major crisis of this disease, the need to study and analyze the long-term causality between the prevalence and recurrence of persistent peaks of the disease and the country's economy is very important. Therefore, the purpose of this study is to analyze the long run causality between coronavirus prevalence as a dummy variable and selected economic variables (exports, transportation, unemployment and economic growth) in Iran.
 Methods: the Vector Error Correction Model (VECM) will be used and by estimating the coefficient of Error Correction Term (ECT) this issue will be investigated during the period 1978-2021.
 Results: Based on the statistical significance of the error correction term coefficient, it can be concluded that in the model, except for exports and unemployment, other variables (transportation, economic growth, prevalence of Covid-19) cannot try to adjust the short run error to the long run equilibrium and cause to long run equilibrium in the system. Because the error correction term coefficient only for exports and unemployment in this model is statistically negative and significant. Therefore, there is only causal relationship of other variables to exports and unemployment. According to the results of diagnostic tests, it was found that since the probability statistic in all tests is more than 0.05, therefore, the null hypotheses of the tests are not rejected.
 Conclusion: Relying on the concept that the significance of long run dynamic relationships in the model is based on the statistical significance of the coefficient of error correction term, it can be concluded that, except export and unemployment, other variables in the model (transportation, economic growth, prevalence of Covid-19) They cannot try to adjust the short run error to long run equilibrium and cause long run equilibrium in the system. Economic studies conducted so far during the epidemic show that the prevalence of coronavirus in economic sectors including tourism, foreign trade, capital markets, foreign exchange markets, housing markets, small businesses, public businesses, commodity prices, GDP will affect the interior. Due to the losses caused by the prevalence of coronavirus in the Iran's economy, if no immediate action is taken to compensate for the economic losses and a practical solution is not taken, the damage will increase exponentially and many economic activists will face many challenges which may even be removed from the economic cycle. Adapting countries to compliance with health protocols improves trade and exports. The government should put the safety of transport workers on the agenda to continue to provide essential services, and it is useful to apply the lessons learned from the experiences of areas that were affected by the disease early on.

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References

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Journal of Development and Capital
Volume 6, Issue 2 - Serial Number 11
December 2021
Pages 57-70

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  • Receive Date: 07 November 2021
  • Revise Date: 14 December 2021
  • Accept Date: 09 January 2022

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