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we have much more in common with one another than we dare to realize.


Economist Mark Perry writes in his blog Carpe Diem, Evidence shows significant mobility in income and affluence – 73% of Americans will be in ‘top 20%’ for at least a year:


quoted from Mark Rank from the New York Times, From Rags to Riches:

It is clear that the image of a static 1 and 99 percent is largely incorrect. The majority of Americans will experience at least one year of affluence at some point during their working careers. (This is just as true at the bottom of the income distribution scale, where 54% of Americans will experience poverty or near poverty at least once between the ages of 25 and 60).

Ultimately, this information suggests that the United States is indeed a land of opportunity, that the American dream is still possible — but that it is also a land of widespread poverty. And rather than being a place of static, income-based social tiers, America is a place where a large majority of people will experience either wealth or poverty — or both — during their lifetimes.

Rather than talking about the 1 percent and the 99 percent as if they were forever fixed, it would make much more sense to talk about the fact that Americans are likely to be exposed to both prosperity and poverty during their lives, and to shape our policies accordingly. As such, we have much more in common with one another than we dare to realize.


Much of the data and information on social inequality is misleading and hard to measure.  Thomas Sowell has spoke of the need to recognize that individual journeys are also very different than a description of mere statistical categories.  This piece adds another dimension that even individuals rise and fall among categories during the course of a single life.

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Is too Much Information Antithetical to Knowledge?

From The Wall Street Journal Book Review: ‘The Power of Knowledge,’ by Jeremy Black

The review is by Roger Kimball


Although deeply grounded in history from the Middle Ages on down, this book also conjures with contemporary issues. Some are technical, like the vistas of information unraveled in the human genome project. Some are political. Until fairly recently, Mr. Black notes, central governments lacked the mechanisms to intervene consistently in everyday life. That, as anyone who can pronounce the acronym “NSA” knows, has changed dramatically. Mr. Black devotes an entire chapter to what he calls “the scrutinized society.” The effort to control public opinion and the flow of information has been most flagrant in totalitarian regimes, but he shows that in democracies, too, information is “filtered and deployed as part of the battle for public opinion.”

The growth and precision of information about society brings with it a pressure toward centralization and consolidation. But information doesn’t flow in one direction: There is also an antiphonal movement of dissent. In the 17th century, Mr. Black writes, “the habit of obedience towards authority was matched by a stubborn, and largely successful, determination to preserve local privileges, in part by rejecting demands for information that might be used to curtail these privileges.” Mr. Black concludes by observing that, though information serves people in power, it also gives “people more oversight and control over their rulers.” The jury may still be out on that.

Mr. Black has given us an eloquent paean to the transformative power of information. I hope it isn’t too impish to offer a countervailing observation or reminder about information itself. It comes from the current-day mathematician David Guaspari : “Comparing information and knowledge,” he wrote, “is like asking whether the fatness of a pig is more or less green than the designated hitter’s rule.”


The social networks are being mined by political campaigns. No one has yet done this more effectively than Obama.  Rand Paul and possibly others from the right are desperately trying to play catch up.

Government agencies have tools to follow the most minute activities and desires of its citizens and this can have totalitarian consequences in ways we are probably unable to imagine.  Yet citizens also have access to infinite data, information and opinions that can be used to hold their government accountable in ways that the old media could never attempt.

It seems that it is critical to be aware of any attempt of government agencies to control internet media sources.  Recent attempts to define what is a journalist, to monitor newsrooms, and to access sources without warrants should cause us all to pause.

Knowledge and Power by George Gilder takes a different approach.  Gilder contends that knowledge is spread wide and deep in the private sector and that wealth grows when knowledge and power converge.  This rarely happens in government.  It is why central economic planning fails. The use of social networks and other online data sources may provide a lot of data and information, but that falls far short of the knowledge that is needed to use the information wisely.  In fact too much information may at some point be antithetical to knowledge. Nassim Taleb suggested that too much data and information gives rise to relationships and conclusions that are not justified by facts and leads us to monstrous errors in judgment.

While we are aware of the use of technology in the private sector we are just becoming aware of its use as a tool of government power.

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Political Resistance to Innovation

“The problem of politics is that it does not know how to get less wrong. It is as a practical matter impossible to design a national health-care policy that can be tweaked and improved every quarter, or on-the-fly in real time as problems are discovered, as software is. It is nearly impossible to imagine political institutions creating something like a software-update feature for Social Security or the War on Drugs. Resistance to innovation is a part of the deep structure of politics. In that, it is like any other monopoly. It never goes out of business—despite flooding the market with defective and dangerous products, mistreating its customers, degrading the environment, cooking the books, and engaging in financial shenanigans that would have made Gordon Gekko pale to contemplate.”

Excerpt From: Kevin D. Williamson. “The End Is Near and It’s Going to Be Awesome.” HarperCollins, 2013-05-01. iBooks.

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The Rich and Poor Rise and Fall Together


Alan Reynolds writes The Truth About the One Percent in The National Review Online


The table shown here — which uses Piketty and Saez’s data — shows the top 1 percent’s average real income fell by 16.3 percent from 2007 to 2012, and ended up 6.4 percent lower than it was back in 2000:

Average Real Income of the Top 1 Percent (2012 dollars)
2000 $1,350,006
2001 1,063,706
2002 933,878
2003 964,989
2004 1,143,104
2005 1,323,935
2006 1,414,985
2007 1,510,932
2008 1,213,199
2009 961,785
2010 1,076,379
2011 1,056,640
2012 1,264,065

What about the “other 99 percent,” whose income supposedly rose by only 0.4 percent from 2009 to 2012? Piketty and Saez compare real incomes at different income levels without including Social Security, unemployment and disability benefits, food stamps, Medicaid, etc. Government transfers totaled $2.3 trillion in 2012, up 24.6 percent in real terms from 2007 and up 68 percent since 2000. Because Piketty and Saez estimate only pre-tax, pre-transfer income, they also ignore $149 billion in Treasury checks to lower-income families from refundable tax credits. They’ll also ignore huge Obamacare subsidies next year.

Once transfers and taxes are properly taken into account, my own research for the Cato Institute shows no clear trend toward greater inequality after 1989, aside from the tech-stock boom of 1998–2000. Instead of any predictable trend, data on income shares are dominated by cyclical variations in which rich and poor rise or fall together: When the top 1 percent’s share rises, the poverty rate falls, and when the top 1 percent’s share falls, the poverty rate rises.

There are numerous conceptual and measurement problems with attempting to judge the relative living standards of the rich, middle-class, and poor by relying on income reported on individual tax returns (ignoring, for a start, income that’s unreported or reported on corporate returns).

Saez himself has hinted that the seemingly strong surge in top-percentile incomes in 2012, for example, was largely a matter of strategic tax timing — reporting bonuses and capital gains in 2012 to avoid higher tax rates in 2013. The same thing happened in late 1992, when professionals and executives arranged to cash in bonuses and stock options in December rather than in January 1993, when income-tax rates went up. It also happened in 1986, when investors rushed to cash in capital gains before the capital-gains tax went up, briefly inflating reported real income of the top 1 percent by 34.6 percent in a single year.

Because reported capital gains and bonuses were similarly shifted forward from 2013 to 2012, we can expect a sizable drop in the top 1 percent’s reported income when the 2013 estimates come out a year from now. The befuddled media will doubtless figure out some way to depict that drop as an increase.


Alan Reynolds has done an extensive job challenging the income disparity data in his book Income and Wealth.  You can find excerpts in the search feature in this blog.  In short the data is manipulated depending on what is included in the wealth distribution data, what is measured (household income vs individual income), and what periods are selected.  For example much of the growth in income in the 1980′s had much to do with changes in the tax law that caused Subchapter C corps to convert to Subchapter S status.  Income data that used to show up on corporate returns now showed up on personal returns via K-1 reports. Similarly wealth that resided in tangible assets during the inflationary 1980′s returned to reportable financial statements in the 1980s as inflation was tamed.

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The Fair Value Fiasco

John Allison

“One of the basic requirements of the law of supply and demand is that there must be a willing buyer and a willing seller. During the chaos created by the random type of government policies just described, this basic condition did not exist. As a simple example, suppose my home is on the market for $600,000. With the huge uncertainty created by government decision makers during the financial crisis, the few buyers that are out there are looking for a fantastic deal and will pay only $300,000 for my house. I will not sell my home for $300,000. I do not owe anything on the home, and I can easily afford to wait until the market calms down. However, under fair-value accounting, my house would be valued at $300,000, and if I were a bank, I would take a $300,000 loss on the house through my income statement. This outcome is inconsistent with the law of supply and demand. Under this economic law, there must be a willing buyer and a willing seller for a market price to be established. “The fact that Tom Brown had to sell his house for $300,000 because he was in severe distress does not mean that I have to or will sell my house for this price.

One of the basic principles underlying accounting models is that “businesses will be valued as going concerns. In other words, the assumption is that the business will continue to operate. Fair-value accounting is inconsistent with this concept, because it effectively assumes that the business’s assets are being liquidated under stress.

Fair-value accounting was a major cause of the liquidity problems in capital markets. Public companies would not purchase economically valuable assets because of the accounting risk. I personally was involved in decisions where poor economic decisions were forced on us by accounting policy.”

Excerpt From: John A. Allison. “The Financial Crisis and the Free Market Cure:  Why Pure Capitalism is the World Economy’s Only Hope.” McGraw-Hill, 2013. iBooks.

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