Hipple (2010) finds the absolute level of unincorporated self-employment largely stable if shifting toward wage-counted incorporated self-employment, but also reports the scale of this sector as comprising just under 11% of total national earnings from work.
The exclusion of all these types of earnings supports inquiry into the validity of data built on potential composition problems, the weighting for part and full time earnings. While the median is the proper measure of central tendency in cases of non-normal data; outliers etc., and it is meaningful to say that the distance between the top and the middle increased more than the distance between the bottom and the middle for different reasons, which is in a global sense the outcome of this research, the composition of earnings levels could change very drastically in ways policymakers may or may not want, while the median remains unchanged. As with mandatory performance of unpaid work at home, composition factors compromise the validity of describing a category of earnings the significance of which is falling in a changing workplace.
Other factors compound this compounding problem, particularly using age as a "proxy for experience" (17). Mosisa and Hipple point out that the labor force participation rate for individuals 55 and over, i.e. those between 55 and 64 in the sample this study analyzes, has been markedly increasing since 1995 (Mosisa 2006). If seniors switch from full-time work at the top of their earnings potential to lower-earning part-time work after 'retirement' (demonstrated in CBO 2008 for the 50-55 cohort), this completely undermines the point of using age as a proxy for experience, particularly when the largest cohort of the highest-earning but least-educated sector of the workforce (2011 p. 6) but yet that transition to part-time work is minimized in the weights against the remaining hourly wage earners. Likewise if a worker had two (or more!) part-time jobs, those earnings would not be represented as heavily as full-time earnings. My objective is not to solve this problem here but to point out that any conclusions drawn from this research deserve close critical scrutiny as far as the applicability of any assertions. Any claims supported by this research may very well have a falling, rather than increasing utility in a real policy application.
While these problems may not destroy the validity of the conclusions this report asserts, which is not my goal here, they force us to accept the possibility that there may be significant other factors at play. While the conclusions from this study may accurately describe wage hours, the earning patterns of the group who work the most hours at the highest pay rates, if that group is dwindling in importance relative to the society as a whole, describing them without a wider benchmark describes individual trees while leaving the wider forest unmapped. The increasing incidence of part-time work, self-employment, capital gains earnings (4) and gray/black market employment (CBO 2008) all combine to squeeze the utility of describing this class of earnings into an increasingly narrow channel. The other factors are growing in importance rather than shrinking, relative to this group of workers. This all leads to a broader possible criticism of the relevance of these conclusions even if the data are valid for the sector they describe.
To conclude this digression on the validity of the data, leaving discussion of relevance until after other meaningful areas for improvement have been mentioned, I will simply point out that the data in this report are not as useful as they could be because the complexity of all these adjustments restrict, rather than promote inquiry. The data this study presents are already weighted and sorted into percentiles, and while we can use them to check the validity of say claims about global trade effects they report (10; see Table 1, Appendix I) or their choice of business cycle peaks as indicating wage levels (13; see Table 2, Appendix I), reconstituting the raw data to compare them with the weighting adjustments will be so difficult that the noneconomist will very likely not be able to assess the conclusions thereby drawn and discussed. CBO could have done a better job assessing alternative interpretations, like they did in CBO 2008. There is more evidence in support but this is enough to raise valid questions.
Stepping outside of the data set to consider the relationship of these conclusions to their context, i.e. The relevance of the conclusions this report asserts (that the weighted median earnings have moved away from the lowest and highest percentiles they consider, for different reasons and in different ways), does not require us to search for factors outside CBO's own analysis. The factors they...
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