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2022 Monthly Lab. Rev. 1 (2022)

handle is hein.journals/month145 and id is 1 raw text is: Monthly ii BL Labormu pL January 2022 Predicting unemployment and recessions using overall sentiment of the economy Lisa N. Huynh Recessions and unemployment measures are difficult to predict. In The economics of walking about and predicting unemployment (National Bureau of Economic Research, Working Paper 29172, August 2021), authors David G. Blanchflower and Alex Bryson predict changes in the unemployment rate using business sentiment (industry fear of unemployment), and individuals' perceptions of the economy, including their financial situation and fear of unemployment. The authors explain that these social survey data could be predictive of economic downturns and should be used for forecasting. The term economics of walking about refers to forming opinions of economic trends by observing economic actors and collecting their expectations in qualitative social data. The authors argue that the economics of walking about can show that global recessions (for example, the Great Recession) are expected, nonrandom shocks to the economy and can be predicted well in advance. Historically, economists have had a tough time predicting recessions. However, in the months preceding economic downturns, researchers have noticed individual and business sentiment falling. Therefore, Blanchflower and Bryson assert that these sentiments can be used to predict economic downturns. To model the economic prospects and general well-being of countries, economists traditionally use unemployment and gross domestic product (GDP) growth. According to the authors, unemployment rates tend to be more accurate than GDP estimates and are subject to less frequent revisions. They also express that unemployment is also an indicator of labor market health and the well-being of individuals, especially during a recession. The coronavirus disease 2019 pandemic-induced recession, however, was an exception to the usual accuracy of the unemployment figures in the United States because unemployment figures drastically dropped and required a larger than usual revision. Yet, owing to specific government subsidies and supports in most European countries, these figures did not drop as much in other countries and so retained their accuracy. The study uses the reported fear of future unemployment to identify turning points in the unemployment rate within the next 12 months that would mark the start of a recession. Blanchflower and Bryson use the analysis to show how the expectations and attitudes of individuals in the labor market contain information that would help analysts forecast economic downturns up to 12 months in advance. They conclude that with these forecasting techniques, economic damages to employment can be mitigated by allowing firms and governments to react more quickly. This early detection of downturns is crucial to limit the economic uncertainty and financial strain that result from large recessions such as the Great Recession or the 2020 recession.

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