Factoid: US Manufacturing (Again)

Apparently, Oct 2 was Manufacturing Day in the US and Mark Perry took the opportunity to push his recurring theme of enduring US manufacturing strength. In his post, Perry updated his graph of US manufacturing output and employment (below). I have shared previous editions of this graph with my students, so here is the updated one.

In general, the story remains the same. US manufacturing output grew dramatically in the late 1990s and early 2000s while employment in the sector dropped just as dramatically. Of course, the Great Recession put a hurt on the sector but it has largely recovered (though it is not growing like it did in the beginning of the century).

As always, Perry makes the argument that having less people making more stuff is good and has a graph showing the rising worker productivity in the sector (below). The graph shows that worker productivity in the manufacturing sector more than doubled in the 13 years from 1997 to 2010. Note that the previous doubling took 42 years from 1955 to 1997. The point to be taken here is that US manufacturing workers have been improving their competitive edge on foreign workers through productivity increases which render simple comparisons of US and foreign wages meaningless.

However, the bigger story is in the graph on US spending on food, cars, clothing and household furnishings (i,e,, stuff we buy). Whereas US consumers spent over 40% of their disposable income on such stuff in 1950, today they spend just over 15% on it today. Perry sees two things going on here: "As US manufacturing has become more technologically advanced and efficient, the price of manufactured durable goods has fallen in relation to both: a) other consumer products and services, and b) Americans’ after-tax disposable personal income." Or, as I like to say, stuff is cheap nowadays.

Fair enough, but it is important to remember that price depends not just on the ability to supply stuff (i.e., the technology and efficiency of the manufacturing sector) but also on demand for stuff in general. While all of us consume more stuff than our parents did, we consume many things that aren't physical stuff at all. The price of all my TVs pales in comparison to my accumulated payments to Direct TV, as does the price of my smartphone to the cost of the service contract that came with it. And don't get me started with what I spend on healthcare.

Of course, Perry recognizes this when he includes the relative price of "other consumer products and services", but he is potentially missing growing demand for these things. Where innovation once meant building a better mousetrap (something that would be manufactured), it now more often means designing a better app (which is not manufactured in the traditional sense). Therefore. making physical stuff may not be the economic be-all and end-all it used to be.

Factoid: Percentage of Federal Income Tax Paid by the Top 1%

Mark Perry shares this graph of the percentage of Federal Income Taxes paid by the top 1% and bottom 95% of earners in the US.

This information comes from the Tax Foundation which provides the following histogram of the average tax rate paid by various income groups in the US:

It is interesting to note that the top 1/10 % pays a slightly lower tax rate than the top 1%. This may be due to capital gains (which are taxed at a lower rate than earned income) constituting a larger share of their income.

So, what's the point here? While I don't want to come off as too conservative, I think these graph do undercut the progressive argument that the rich are not paying their fair share, as far as Federal Income Tax goes. Of course, "fair" is a nebulous term (indeed, I sometimes call it the f-word), but when the top 1% are paying more in absolute terms and as a percentage of their income, it's hard to see what is unfair about this to anyone to the average middle-class American. I certainly can't see how one could justify raising taxes on the top 1% (or 5%) based on the current taxes being unfair.

However, this doesn't mean that we should not raise taxes on the top earners. If taxes need to be raised, the key question, to my mind, is where does it make the most fiscal and economic sense to raise them. Fiscally speaking, it used to be conventional wisdom that you had to raise tax rates on large numbers of people to realize significant revenue. But the top graph suggests that this is much less the case now than it was in the 1980s or early 1990s. If the top 1% and bottom 95% are paying about as much in taxes, adjusting the tax rates of either group by a given percentage will produce about as much revenue. Indeed, since then the top 5% are paying 59%, and adjusting their tax rates by any given percentage will produce more revenue than applying the same change to the bottom 95%.

As for the economic impact, the choice between raising tax rates on the rich versus raising them on the middle class is between discouraging investment or discouraging consumption. This is because the rich tend to save and invest more of their income than does the middle class. Given that interest rates and inflation are low, it appears that capital is relatively abundant in comparison to consumer demand, which suggests that raising taxes on the rich is the least bad option.

Furthermore, if you look at the second graph, there is kind of any obvious place to raise taxes since the top 1/10% are paying a lower tax rate than the top 1%. If this is because of the lower capital gains tax, then raising the capital gains tax seems like a logical place to start.

But hey wait! That's exactly what President Obama  suggested doing in his State of the Union speech, albeit based on an entirely different rationale. So while I reject the fairness based reasoning employed in the political rhetoric, I do support the specific policy (which is presumable rafted by less rhetorical economists).

Of course, this all begs the question of whether taxes need to be raised in the first place. The graph of federal expenditures below is why I lean towards saying that they do need to be raised. It shows that, for good or ill, the federal government has kept spending constant for the past few years. This suggests to me that we have gone about as far as we should go with cost cutting and so tax increases of some kind should be on the table. But, hey, that's just me (the blog is called thinking out loud).

PEW Research on the "Rising Cost of Not Going to College"

This week PEW Research published survey results showing the effect of a 4 year degree on earnings unemployment and poverty.  They found that the median income of respondents with a 4 year degree was $45,500 while the median income of respondents with only a high school degree was $28,000. Respondents with a 2 year degree did not fair much better with a median income of $30,000. So a Bachelors degree (or more) produces a 62.5% wage premium over a HS diploma and a 51.6% wage premium over an Associates degree or some college.

Comparing their current results to earlier PEW studies, they found that the gap between the earnings of college grads and non-grads has been growing since 1979. The results are best viewed in their graph of earnings from 1965 to 2013. The authors note that, even though the percentage of college graduates in their sample has been increasing (and the percentage of people with only a HS degree has been shrinking), median income in their surveys has remained flat since 1965.

Their report goes on to consider many more aspects of the situation and is definitely a must read. Of particular interest to college students and their parents is the section on regrets among college graduates. While one might expect that many would regret their choice of major, only 29% listed that as a major regret. The most commonly mentioned regret (50%) was not gaining more work related experience while in school.

While on the subject of income, the subject of assortative mating is getting some play due to an NBER paper by Greenwood, Gunar, Kocharkov, and Santos. Assortative mating refers to the tendency of people to marry other people with similar education/skill levels which results in people with high (low) earning potential forming households with someone with a high (low) earning potential. The prevalence of high-high and low-low pairings in comparison to low-high pairings exacerbates measures of income inequality where the unit of analysis is households, not individuals. Looking at 2005 data on incomes, the authors find that, if people were randomly paired with others, the gini coefficent of household income would decrease from .43 among actual households to .34 among randomly paired households (a 25% reduction).

So what do you do with this. Matthew Yglesias at Slate's Moneybox gives it a whirl.

Interest Tidbit: An iPhone would have cost $3.5m in 1991

Keeping with the theme of  increasing quality vs price of products, there is this article by Bret Swanson at TechPolicyDaily.com that calculates that the capabilities of an iPhone would have cost, $3.5 million in 1991.

Of course,all the hodgepodge of components wouldn't fit in your pocket and, therefore, the value of the miniaturization isn't included in the $3.5 million figure.

Also of note, the article mentions that a gigabyte of hard drive storage cost $10,000 in 1991 and today costs only 4 cents.

Some Info on Income Inequality

The President's State of the Union has kicked off the Democrat's income inequality offensive for this elections year. Here are some interesting arguments and research findings related to the subject.

Daniel Smith's Op-ed The Myth of Wage Stagnation Smith, a colleague at Troy University, lays out the argument that the oft-quoted data on earnings, which shows that average real wages only increased 5.58% since 1964, does not reflect increases in benefits and purchasing power. He points out that total compensation, which includes benefits, has increased 45% since 1964. He goes on to refer to Mark Perry's argument that purchasing power has increased when one considers the hours people need to work to earn enough money to buy consumer goods (see next link). Of course, not only do people have to work less hours to afford, say a TV, but the quality of the product purchased (which is not factored into inflation estimates) has increased dramatically in the past decades.

Fly in the ointment: While most of Smith's article is fact driven, he ends on an ideological note by arguing that the myth of wage stagnation is being used to do away with economic freedoms that increase incomes. While I have great sympathy for any argument in favor of economic freedom, it is more tenuous than the empirical case made in the first three quarters of the essay.

Mark Perry's Data on Hours Needed to Work to Purchase Goods  Speaking of Mark Perry, he often posts information on the increasing quality and decreasing real cost of consumer products. In this post, Perry has a table that shows the cost of 11 household appliances in 1959, 1973 and 2013. He also uses the average hourly manufacturing wage from each of those years to calculate the hours a factory worker would have to work to purchase them. Even though the price of these products increased from $1,851 in 1959 to $3,289 in 2013, the hours a worker need to work to purchase them dropped from 885.6 to 170.4.

Of course, Perry used the average manufacturing wage and much of the discussion has been about minimum wage workers who generally make much less. Perry did a comparison of what a college student could purchase with the earnings from a minimum wage summer job (40 hours/week for 12 weeks) in 1973 versus 2013. Someone working for minimum wage in 1973 would earn $768 ($1.60/hour x 480 hours) and someone working for minimum wage in 2013 would earn $3,480 ($7.25/ hour x 480 hours).

Now, if you use the CPI to adjust these wages for inflation, it would appear that the 2013 worker earned 14% less in real wages than the worker in 1973. However, if you look at what the two workers could buy with their earnings, you get a very different conclusion. The 1973 worker's $768 would purchase a typewriter, a calculator, a portable TV, a Radio-Tape player, and a compact refrigerator. The 2013 worker's $3,289 would buy a laptop and printer, an iPod, an iPad, an iPhone, a GPS, a digital camera, flatscreen TV, a blu-ray player, a home theater system, a Playstation, a Kindle Paperwhite, Sonicare toothbrush, a clock radio/iPod docking station, a TiVo, a satellite receiver for a car, an espresso machine. and a calculator.

The difference between these bundles of goods is even more remarkable when you consider that a billionaire could not have purchased many of the things at any price in 1973. This leads Perry to argue that today's kids are the luckiest generation (at least until the next one).

Fly in the Ointment: In both cases, Perry looked at manufactured consumer goods, which have seen both increases in quality and decreases (or relatively small increases) in price. In comparison many things like , houses, gasoline and beef, have not increased much in quality but have increased in price.  More importantly, healthcare, which has increased in quality, has gotten much more expensive. Of course, this is why the CPI, which looks at broad range of goods, says the $768 in 1973 is worth more than the $3,480 in 2013.

The Equality of Opportunity Project: Harvard's Equality of Opportunity project reports two interesting sets of findings regarding individual income mobility, i.e., the changes in income that individuals experience in their lifetimes. This is not income inequality, per se, but mobility relates directly to individual prospects in our economy.

First, they find that the prospect for upward mobility among children who grow up in below median income families varies a great deal across different geographic regions of the US. While you really need to look at the map they posted, the areas of lower upward mobility are heavily concentrated in the southeast while the areas of highest mobility run through the plains states.

Second, they report that income mobility was very stable from 1971 to 1992. They measure this mobility in terms of the difference in the average income percentile of children born to low income families versus children born in high income families. As they sum it up, "On average, children from the poorest families grow up to be 30 percentiles lower in the income distribution than children from the richest families, a gap that has been stable over time."

Fly in the Ointment: There really isn't one here, besides the difference between income inequality and mobility previously noted.