I wrote some handwritten comments on labor market capacity constraints and inflation, which I alluded to in my previous article. A tangent that appeared and does not fit into the manuscript is the behavior of the employment/population ratio. Although the argument that “overheating of the labor market is a major component of sustainable domestic inflation” is entirely plausible, the problem is how to define the term “overheating”. If we want to tell stories about history, we can choose the data however we want. But if we want to make quantitative forecasts – which is what you need for a falsifiable theory of inflation – you need certain variables to power your model.
The unemployment rate seems to correct these structural changes: it is the percentage of the population looking for work. People who are not looking for work – stay-at-home spouses, people on disability benefits, students, retirees, the wealthy – are not counted in the labor force. This explains why the unemployment rate is well below 100% minus the employment-to-population ratio.
The problem with the unemployment rate is that it is also affected by structural changes in the economy. (The number of UI claimants has been affected by the tightening of UI policies, but this should theoretically not affect the unemployment rate determined by the BLS survey.) The argument made in the 2010s (which I agreed with) was that the job market was stagnating and people were abandoning the official “job seeker” status. They either stopped looking (because they knew they had no chance of being hired), enrolled in education programs (of varying quality), or ended up accepting jobs offering fewer hours than they wanted. Thus, there has been increased interest in alternative labor reduction measures – other than those who were convinced that the economy was going to overheat “any minute” throughout the period 2012-2020. As jobs were created, people entered the labor force at about the same rate, so the number of unemployed did not fall to zero.
If we just look at the “prime working age” cohort (25-54) – which excludes college and early retirement ages – we get a better sense of the state of the market work. It is enough to compare with the levels after 1990, since the effects of “women’s liberation” had then largely spread to the most active age group. Using this measure, the ratio is close to the pre-pandemic level, but below the 2000 boom level.
Since I’m not offering an inflation forecast, I won’t comment further on the implications of what happens next (are we really running out of available workers?). Instead, I just want to point out that this measure made much more sense in explaining post-2000 dynamics than the unemployment rate, which misled a lot of people in the previous cycle. From the perspective of inflation theory, the decomposition of various capacity indicators in response to structural changes in the economy makes it difficult to verify quantitative models. An indicator may work in one cycle, but it may collapse one to two cycles later, which is not that surprising given that recent business cycles last about a decade.
Email Subscription: Go to https://bondactivities.substack.com/ (c) Brian Romanchuk 2023
I wrote some handwritten comments on labor market capacity constraints and inflation, which I alluded to in my previous article. A tangent that appeared and does not fit into the manuscript is the behavior of the employment/population ratio. Although the argument that “overheating of the labor market is a major component of sustainable domestic inflation” is entirely plausible, the problem is how to define the term “overheating”. If we want to tell stories about history, we can choose the data however we want. But if we want to make quantitative forecasts – which is what you need for a falsifiable theory of inflation – you need certain variables to power your model.
The unemployment rate seems to correct these structural changes: it is the percentage of the population looking for work. People who are not looking for work – stay-at-home spouses, people on disability benefits, students, retirees, the wealthy – are not counted in the labor force. This explains why the unemployment rate is well below 100% minus the employment-to-population ratio.
The problem with the unemployment rate is that it is also affected by structural changes in the economy. (The number of UI claimants has been affected by the tightening of UI policies, but this should theoretically not affect the unemployment rate determined by the BLS survey.) The argument made in the 2010s (which I agreed with) was that the job market was stagnating and people were abandoning the official “job seeker” status. They either stopped looking (because they knew they had no chance of being hired), enrolled in education programs (of varying quality), or ended up accepting jobs offering fewer hours than they wanted. Thus, there has been increased interest in alternative labor reduction measures – other than those who were convinced that the economy was going to overheat “any minute” throughout the period 2012-2020. As jobs were created, people entered the labor force at about the same rate, so the number of unemployed did not fall to zero.
If we just look at the “prime working age” cohort (25-54) – which excludes college and early retirement ages – we get a better sense of the state of the market work. It is enough to compare with the levels after 1990, since the effects of “women’s liberation” had then largely spread to the most active age group. Using this measure, the ratio is close to the pre-pandemic level, but below the 2000 boom level.
Since I’m not offering an inflation forecast, I won’t comment further on the implications of what happens next (are we really running out of available workers?). Instead, I just want to point out that this measure made much more sense in explaining post-2000 dynamics than the unemployment rate, which misled a lot of people in the previous cycle. From the perspective of inflation theory, the decomposition of various capacity indicators in response to structural changes in the economy makes it difficult to verify quantitative models. An indicator may work in one cycle, but it may collapse one to two cycles later, which is not that surprising given that recent business cycles last about a decade.
Email Subscription: Go to https://bondactivities.substack.com/ (c) Brian Romanchuk 2023