A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments

Abstract

The COVID-19 pandemic has had a devastating impact on the global economy. In this paper, we use the Phillips curve to compare and analyze the macroeconomics of three different countries with distinct income levels, namely, lower-middle (Nigeria), upper-middle (South Africa), and high (Canada) income. We aim to (1) find macroeconomic changes in the three countries during the pandemic compared to pre-pandemic time, (2) compare the countries in terms of response to the COVID-19 economic crisis, and (3) compare their expected economic reaction to the COVID-19 pandemic in the near future. An advantage to our work is that we analyze macroeconomics on a monthly basis to capture the shocks and rapid changes caused by on and off rounds of lockdowns. We use the volume and social sentiments of the Twitter data to approximate the macroeconomic statistics. We apply four different machine learning algorithms to estimate the unemployment rate of South Africa and Nigeria on monthly basis. The results show that at the beginning of the pandemic the unemployment rate increased for all the three countries. However, Canada was able to control and reduce the unemployment rate during the COVID-19 pandemic. Nonetheless, in line with the Phillips curve short-run, the inflation rate of Canada increased to a level that has never occurred in more than fifteen years. Nigeria and South Africa have not been able to control the unemployment rate and did not return to the pre-COVID-19 level. Yet, the inflation rate has increased in both countries. The inflation rate is still comparable to the pre-COVID-19 level in South Africa, but based on the Phillips curve short-run, it will increase further, if the unemployment rate decreases. Unfortunately, Nigeria is experiencing a horrible stagflation and a wild increase in both unemployment and inflation rates. This shows how vulnerable lower-middle-income countries could be to lockdowns and economic restrictions. In the near future, the main concern for all the countries is the high inflation rate. This work can potentially lead to more targeted and publicly acceptable policies based on social media content.

Technological Changes, Investments, and Unemployment Pre and Post Covid 19 in the United States A State-Level Analysis

“…If the points are mainly sloping upwards, it indicates a positive relationship, while a downward slope indicates a negative relationship which is our case. This finding is consistent with Nia et al's (2022) study in Canada, which revealed that although unemployment rates were controlled and reduced during the pandemic, inflation surged to unprecedented levels, a trend also observed in the United States.…”

Tweeting the economy: Analyzing social media sentiments and macroeconomic indicators

“…Conversely, sentiment from non-news accounts does not exhibit a significant relationship with GDP. This finding introduces a novel perspective and evidence compared to studies by Abbas et al (2022), Jabeen et al (2022), and Nia et al (2022, suggesting that a positive relationship between Twitter sentiment and GDP is more likely when sentiment from news accounts is predominant. These findings underscore the pivotal role of social media, particularly Twitter, as a platform for capturing public opinion that can be linked to macroeconomic indicators.…”

A fairness assessment of mobility-based COVID-19 case prediction models

“…To combat the COVID-19 pandemic, governments and private companies around the world were promoting the use of digital public health technologies for data collection and processing [54][55][56][57][58]. Through the use of GPS, cellular networks and Wi-Fi, smartphones can collect and aggregate location data in real-time to monitor population flows, identify transmission hotspots, determine the effectiveness of non-pharmacologic interventions [59], and predict future COVID-19 cases [7,20,25].…”