Rank The Different Components / Term Paper
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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
...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 compare these conclusions against include other earnings, treated at length within the data set above; market and institutional effects which each have several components; education; gender; technology and inflation effects that happen in the broader context in which the data they discuss are embedded. These discussions achieve varying levels of success, and some degree of obfuscation.
The separation of market and institutional affects into discrete categories and assigning affects from these forces into separate buckets is an unnecessary simplification that clouds rather than clarifies, and ends up simply inaccurate. The report spends extensive space exploring market-based factors like skill-biased technological employment demand changes over time; labor force participation rates and educational attainment for women relative to men; and effects on U.S. workforce demographics from immigration and global trade, to a degree of detail that stands to its credit. But claiming that these factors occur outside the institutions that define the parameters under which all market transactions occur, grievously misrepresents Congress' own role in limiting the factors they allege drive these natural equilibria. Firewalling minimum wage and unionization effects into a realm of pure institutional change ignores effects across the entire marketplace the paper elsewhere asserts are the results of these institutional forces (Note 31, p. 15). This direct self-contradiction is the result of asserting that trade, labor, educational and microeconomic decisions about wage choice and marginal substitution between acceptable / available employment options etc. occur in some abstract vacuum unaffected by policies enacted by the authors of the paper themselves, is the result of this reductio ad absurdum and unfortunately misrepresents important conclusions to a readership which may lack the sophistication to recognize this division fallacy, namely those setting the policies determining those market factors, i.e. Congress. We hear for example that "growth in the supply of college graduates" offset demand pressures following World War II (6), but the fact that much of that supply arose because of the G.I. Bill (a policy within which market forces became nested) is left ignored.
These simplifications run throughout and distort the results this paper describes. On the macroeconomic level, while CBO 2011 discusses effects of worker immigration and the effects of these workers' educational endowments (12), there is no mention whatsoever of effects from illegal immigration on the distribution and level of earnings in the data set. Discussion of this type of under-the-table 'gray market' employment is glaringly absent, particularly from a discussion of institutional and market drivers on employment and wages. CBO 2008 cites evidence the scale of this type of earned income may be up to 2% of total national earnings and concludes both administrative and survey data miss this type of income. The 2011 report finds the effects of these immigration and global trade trends on employment negligible, after creating an example where low-educated workers actually stimulate employment in other trades (12). Perhaps we can impute illegal immigration effects from this example, but whether these are marketplace or institutional effects remains muddled.
I discussed distortions introduced by choice of survey vs. administrative data within the data set above; those decisions also distort the relevance of that data to the context it takes place within. Choosing individual rather than household earnings also overlooks microeconomic decisions consumers make in the substitution both of work against leisure; different types of employment against each other; off- or on-balance sheet employment; and between substitutes not represented in chained inflation adjustment. The CBO mentions the context of these wage changes relative to productivity and non-wage earnings (2011, p. 4), but in a clinical, abstracted way that leaves room for improvement.
CBO 2008 describes at some length how discussing household income accounts for earnings outside the parameters of the 2011 focus on wage income. CBO 2011 dedicates a paragraph to discussing the relation of this data to overall productivity (4). I assert however along the lines of the 2008 study, that these broader, general yet microeconomic factors affect individual substitution between employment criteria. The 2011 paper discusses in Note 5 (2) how the recent recession forced many workers to take wage employment at lower rates than the jobs they lost against their preference. This type of choice affects the relative…
Sources Used in Documents:
Bureau of Economic Analysis: " Table 1.1.10. Percentage Shares of Gross Domestic Product." Last revised Feb. 25, 2011 (March 13, 2011): http://www.bea.gov/national/nipaweb/SelectTable.asp
Congressional Budget Office, "Recent Trends in the Variability of Individual Earnings and Household Income." Jan. 2008. United States Congress: Washington, D.C. (March 12, 1011) www.cbo.gov/doc.cfm?index=9507&type=1
Congressional Budget Office, "Changes in the Distribution of Workers' Hourly Wages Between 1979 and 2009." United States Congress: Washington, D.C. (Feb. 2011). March 10, 2011: www.cbo.gov/ftpdocs/120xx/doc12051/02-16-WageDispersion.pdf
Division of Labor Force Statistics. "Economic News Release Work at Home Summary" Table 7. Job-related work at home on primary job by reason for working at home, sex, class of worker, and pay status, May 2004 Washington, DC: U.S. Bureau of Labor Statistics. Last Modified: September 22, 2005 (March 12, 2011) www.bls.gov/news.release/homey.nr0.htm
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