Data Quality Analysis For The Relationship Between Unemployment And Real GDP

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The driving forces behind the change in unemployment (rate) in developed economies represent a very important and actual problem for the modern economic theory. For example, there exists an opinion that the change in unemployment may manifest tangible structural changes in the labor market. The COVID-19 pandemic is a natural non-economic (exogenous forces) experiment to test and validate all economic theories of unemployment. One can expect major changes in the overall organization of all economies (developed, emerging, etc.) when significant parts of them are suppressed or just decimated due to non-economic reasons. In this blog, we addressed the problem of structural unemployment by modeling the rate of unemployment with Okun’s law, i.e. the relationship of unemployment and real GDP growth. 

The COVID-19 pandemic is a deciding/survival opportunity for any quantitative economic theory like Okun’s law. Obviously, all descriptive economic theories never take data seriously, and these religious sects have their own apologists and believers: “In the beginning was the Word”.  In a series of future posts, we are going to revisit and validate our previous results obtained for a specific version of Okun’s law developed in a series of papers. The last overview of our empirically estimated Okun-style models for selected developed countries (the United States, France, the United Kingdom, Australia, Canada, and Spain) was published in 2011. The quantitative results suggest the absence of structural unemployment in the studied developed countries. The persistence of high unemployment is completely related to a low rate of real economic growth. 

This overview used the data between 1950 and 2009 from two principal sources – the Total Economy Database of the Conference Board and the OECD. Currently, the data on real GDP per capita and unemployment are available for the years between 2010 and 2019. We use the same data sources (Maddison Project Database instead of the TED) and compare the selected time series with similar time series from the BEA and BLS

In our previous work, we had to introduce (virtual) structural breaks in Okun’s law in order to improve the agreement between the change in the unemployment rate and real GDP per capita. As we described in several posts in December 2020, such breaks likely manifest artificial changes in definitions of unemployment and real GDP rather than actual shifts in the economic behavior of the variables in Okun’s law. The crucial importance of data quality and consistency for quantitative analysis makes is mandatory to check all time series of unemployment, employment, labor force, and real GDP per capita for definitional breaks and also to compare similar time series from different sources. Any deviation between similar time series from different sources should be considered as an estimate of measurement accuracy and resolution.  

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