In 1970 the median income in the United States was $56,000 per year, and in 2017 the median income was $68,000 per year (see Fig. 1, top curve). In 1970 the median cost of a three-bedroom family home was $23,400, and in 2017 the median cost of such a home was $325,000 (Norada Real Estate 2025; FedPrimeRate.com 2025). Thus in 1970 an individual would need to work 0.4 years to afford such a home (i.e., $23,400/$56,000 per year), and in 2017 an individual would need to work 4.8 years to afford such a home (i.e., $325,000/$68,000 per year), some 12 times longer. Moreover, this diminished relative income of the middle class is depicted by an increase in the Gini coefficient between 1970 and 2017 (Fig. 1, bottom curve).
The income distribution is not a normal function but rather a lognormal function, since it is limited by zero income (see Fig. 2). This means that when evaluating the income distribution, one cannot rely on the mean, given that the mean is biased toward the high-income earners. In fact, the median value of a lognormal distribution can be used to evaluate the income disparity of a population by noting the discrepancy between the median value (below which represents half the population) and the mean value (below which represents more than half the population). The ratio between the mean and the medium is another way of assessing income inequality (Schield 2018).
Note, both the income distribution and the Gini coefficient do not factor in acquired wealth through capital gains. Such information is proprietary and therefore it is not made available to the public by the Internal Revenue Service, which puts limits on the precision of estimates on income distribution (Schield 2018). This rule needs to be made conditional for the purpose of managing economic incentives, since all members of society (including the wealthy) benefit from the deployment of government funds toward infrastructure, science, and technology through agencies such as DOT, DOE, EPA, USDA, HUD, FEMA, DARPA, NSF, NIH, and so on.
Figure 1: Median income (top curve) and Gini coefficient values (bottom curve) are plotted from 1968 to 2017 for US households. Data from figure 8 of Schield (2018). (file: bible_009.jpg)
Figure 2: Frequency plot of number of households and household pre-tax income. Data from figure 1 of Schield (2018). For other details see Schield (2018). (file: bible_010.jpg)
Most labeled "ages" are periods much longer than one year. Most liberal American economists consider the period of roughly 1940s-1960s its "golden age" because there was both sustained growth (until the late '60s) & generally rising income, a growing middle class, thanks to the success of unions in imposing higher wages & provoking capitalist investment in productivity-raising tech to offset the higher costs. Among conservative economists, on the other hand, who were marginalized in that period, their "golden age" began with Carter/Reagan/Volcker & the imposition of neoliberal supply-side economics designed to reverse worker's gains & transfer income & wealth from workers to capitalists. They've been at it ever since. https://la.utexas.edu/users/hcleaver/304L/304Lsupplyside.html
Thanks: Changed ‘age’ to ‘time’. Any further suggestions appreciated.
Dear friends, Interesting discussion here!
I think the seminal work of Thomas Piketty "Capital in the Twenty-First Century" would provide a lot of data for these sort of questions. I do think that in the period (roughly) 1950s-1970s there was much less inequality in the US, which in my eyes would be a marker of a golden age. But that's just my personal opinion, of course :)
Best Wishes,
Haris
No — the “Golden Age” of capitalist growth usually refers to the post-World-II boom from roughly the late 1940s through the 1960s into the early 1970s (often dated c.1948–1973); by the 1970s the U.S. entered stagflation and slower growth, so 1970 itself is generally seen as the end of the golden era rather than its high-point.
Dear Chuck A Arize ,
Fair enough, I'm not an expert on the topic.
Best Wishes,
Haris
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