The impact of COVID-19, vaccination, and non-pharmaceutical policies on Ethiopian trade: a structural gravity using semi-parametric machine learning

ABSTRACT

The COVID-19 outbreak in early 2020 had a significant impact on human health and the economy. To effectively manage this pandemic, we must balance economic losses and health benefits. We must use real-time data to accomplish this. The literature currently available for Ethiopia is based on simulations of pre-COVID macroeconomic data and economic indicators. Using a Poisson pseudo maximum likelihood estimator for a machine learning semi-mixed effect model (SMEM) of structural gravity, this study estimated the impact of COVID-19 cases and deaths, vaccinations, and non-pharmaceutical policies on Ethiopian trade. Cases, deaths, and the stringency index all have statistically significant negative effects on bilateral exports and imports. Vaccinations, on the other hand, have a statistically significant positive impact on both bilateral exports and imports. When compared to bilateral imports, Ethiopia's bilateral exports suffer greatly. Import substitution and increased vaccination coverage and rates are the policy implications.

KEYWORDS:

• Pandemic
• bilateral trade
• Poisson pseudo maximum likelihood
• semi-mixed effects model

Acknowledgments

First and foremost, I want to thank God, his mother, Saint Virgin Mary, his Angels, and his Saints. Next, my wife, Mihret Mamo, who sacrifices everything for the completion of this work, must be recognized. In addition, I would like to thank my advisors, Lemma Zemedu, Abule Mehare, and Ketema Bekele, for their free service in providing comments. Then Isabel Proença and Stefan Sperlich pitched in, sharing data and code for replication and identifying estimation issues. Finally, I'd like to express my gratitude to the Ethiopian Roads Authority's training and examination institute, as well as its employees, for their cooperation in accommodating me.

Author contribution statement

Mandefrot Amare: Constructed the dataset and analyzed the data.

Lemma Zemedu: Analyzed and interpreted the data.

Abule Mehare: Interpret the data and wrote the paper.

Ketema Bekele: Wrote and edit the paper.

Data availability statement

Data will be made available on request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by both Haramaya and Gambella University, Ethiopia [grant number: phd/rf/no.101/date/2021].