Big Ticket Items
Much of the money which people earn is put toward a few "big ticket" items, items which cost a large fraction of all of their pay. Two of these items would be new houses and new cars. Adjusted to the size of the civilian population (1), there has been a drop in the number of new houses sold (2) and also in the number of new cars sold (3).
Some of this drop in "per capita" sales of big ticket items has to do with an increase in the durability of the items. New houses and new cars today last longer than they used to. This could make people hold onto those items for longer, before buying something new again. But the drop from the historical peak (around 1977*), to a recent low (2016) is more than half--and it is doubtful that all buyers intended to hold onto items for more than twice the time that buyers of the past did.
If, say, the average buyer in 1977 held onto a new car until it had 100,000 miles on it, that would mean that average buyers in 2016 were putting 200,000 miles on their cars before buying anything new! Because it is unlikely people are intending to hold onto big ticket items for over twice as long as they used to, we have to try to explain the residual drop in sales.
One good explanation is that there is less productive efficiency, stemming from a prior loss of economic freedom.
In 1977, there were 159 million civilians and 819,000 new houses sold, which makes for about 5.2 new houses sold (that year) for every 1000 civilians. The average number of new cars sold per month was 920,500, which makes for about 5.8 new cars sold per month for every 1000 civilians. The numbers for 2016 are less than half of the numbers for 1977:
About 2.2 new houses sold (annual) and 2.2 new cars sold (monthly) for every 1000 civilians.
To return lost purchasing power to civilians--so that they can afford more new houses and more new cars--it is necessary to restore lost economic freedom (so that productive efficiency can rise). To restore economic freedom, it is necessary for the government to spend and to regulate less than before. Centralization of spending introduces artificial inefficiency in an economy, because less individuals are choosing where more of the resources go.
But when it comes to the allocation of scarce resources, it is better when more individuals are involved in the decision-making process, because knowledge about all of the local and recent circumstances is spread out among them. If it were possible to condense all of the knowledge which is spread out among millions of market participants into the heads of a few bureaucratic elites, then it might be possible to centralize much of the spending without losing productive- and distributive/allocative efficiency.
But it is not possible to condense this knowledge.
Because it is not possible to condense the knowledge, we need to de-centralize much of the spending and regulation. This will make human efforts pay off greater than before, resulting in a rise in the purchasing power of the average civilian.
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*New single-family house sales actually reached their highest level in 2005, but this peak was not from new and higher buying power, it was instead the result of artificial manipulation of the housing market. In other words, it was merely a government-facilitated asset bubble about to burst--driving "per capita" home sales all the way down to their lowest recorded level.
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Reference
(1) U.S. Bureau of Labor Statistics, Civilian Noninstitutional Population [CNP16OV], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CNP16OV, September 24, 2018.
(2) U.S. Bureau of the Census and U.S. Department of Housing and Urban Development, New One Family Houses Sold: United States [HSN1FA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HSN1FA, September 24, 2018.
(3) U.S. Bureau of Economic Analysis, Motor Vehicle Retail Sales: Domestic and Foreign Autos [LAUTONSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/LAUTONSA, September 24, 2018.
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