High unemployment rates in lower, mid income countries after Covid: Study

In contrast to higher-income nations like Canada, lower-to-middle-income countries still experience high unemployment rates in the wake of COVID-19 lockdowns and economic restrictions, according to a recent study conducted by York University in collaboration with the University of Witwatersrand in Johannesburg.

In contrast, during the global economic crisis of 2008-2009, higher-income nations suffered more from the recession than did lower-income nations.

The study compared macroeconomic variables including unemployment and inflation across Nigeria, South Africa, and Canada, representing lower-middle, upper-middle, and high-income countries, respectively. It did this by using Twitter sentiments.

They discovered that all three countries' unemployment rates rose during the start of the pandemic; however, Canada was able to reduce the rate after the first few months, in contrast to Nigeria and South Africa, which are still dealing with high levels of unemployment.

Jude Kong, an assistant professor at York University and the director of the Africa-Canada AI & Data Innovation Consortium, believes that the study "indicates how vulnerable lower-middle income countries are to lockdowns and economic limits, bearing a greater loss during the COVID-19 epidemic" (ACADIC).

Nigeria's unemployment rate was lower than South Africa's before COVID-19, lockdowns, and economic restrictions, while South Africa's inflation rate was lower than Nigeria's. But compared to Canada and South Africa, unemployment and inflation rates in Nigeria have risen faster throughout the pandemic.

Particularly in Canada and Nigeria, which have both had high unemployment and high prices throughout the pandemic, the inflation rate is rising in all three countries right now.

"All income country groups have been impacted by the COVID-19 disaster. However, lower economic classes bear a disproportionately greater burden. It will be challenging to recover from this complexity, particularly for middle-income countries, warns study co-author Professor Bruce Mellado, member of the Gauteng Premier COVID-19 Advisory Committee and co-president of ACADIC. Professor Mellado is responsible for modelling at the University of Witwatersrand and iThemba LABS in South Africa. Johannesburg and Pretoria are located in Gauteng, the province with the highest population in South Africa.

"The COVID-19 pandemic management educated us about the value of data to make evidence-based judgments. As a result, the way that decision-makers see data has significantly changed. According to Mduduzi Mbada, the interim director general of the Gauteng Province, "We are looking forward to the utilization of more data in dealing with societal challenges."

Even while South Africa's inflation rate is still close to pre-pandemic levels, any measures taken to address the country's high unemployment rate are likely to result in higher inflation. Although Canada's unemployment rate is still low, the country is currently experiencing its highest inflation rate in 15 years, which may have been a result of the government's decision to offer employment insurance and the Canada Emergency Response Benefit to workers who lost their jobs as a result of COVID-19.

This study is distinctive in part because the authors used various machine learning algorithms to calculate the monthly unemployment rates for South Africa and Nigeria utilizing non-traditional data including sentiment analysis from Twitter and Google Trends data. For all three nations, monthly inflation data were available, however, South Africa and Nigeria did not have monthly unemployment data.

Real-time information is abundant on social media and social networks like Facebook, Twitter, LinkedIn, Instagram, Snapchat, Pinterest, and Reddit. This data is electronically stored and frequently available.

According to Kong, "They are well-positioned to alter the way and the speed at which particularly hard to obtain infectious illness data is made public." "Classical surveillance systems, which often provide the data used to develop infectious disease models, have a number of drawbacks, including significant time lags and a lack of geographic resolution. They are also expensive.

Data from country-specific Twitter accounts can be utilized to better understand local macroeconomic concerns and opinions, potentially resulting in policies that are more focused and popular with the people.

According to Mellado, social media can supplement traditional vaccine and pharmacovigilance approaches, in which the tracking of vaccine- and drug-related adverse events primarily relies on passive reporting by physicians, by providing data on behaviors and outcomes related to vaccine or drug use, including drug-related adverse events.

Researchers can determine the most popular topics and gauge public opinion thanks to their abundance of text-based data in the form of posts and comments. This enables a better understanding of anxieties and concerns about macroeconomics at the local level and can benefit decision-makers and policymakers.