Musings Report 2017-4 1-28-17 Statistics have Lost Their Mojo: Here's Why
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The last Musings of the month is a free-form exploration of the reaches of the fecund swamp that is the source of the blog, Musings and my books.
Statistics have Lost Their Mojo: Here's Why
One aspect of the "fake news" furor of the past few months has been largely overlooked: a growing sense that our official statistics no longer reflect reality very accurately.
Many of us discern a political agenda in this widening gap between highly touted statistics such as the unemployment rate and the economy the statistic is supposed to summarize: while an unemployment rate of 4.6% in the past meant the economy was growing briskly and almost everyone was participating in the prosperity, now growth is sluggish and prosperity is limited to the top 5%.
Something isn't right: a statistic that once reflected widespread prosperity and opportunity no longer reflects that kind of shared expansion. As noted on the blog, only the top 5% have gained income and wealth in the highly touted "recovery."
Is this the result of subtle political spin (i.e. the orders go down the political hierarchy to tweak the methodology to yield the desired end result) or are there even more fundamental problems in the way we calculate statistics?
A recent article in the UK's Guardian newspaper (to which I subscribe) explained why statistics as a field has become less reflective of the complex realities of modern economies and societies.
How statistics lost their power – and why we should fear what comes next. The ability of statistics to accurately represent the world is declining. In its wake, a new age of big data controlled by private companies is taking over – and putting democracy in peril.
"Here’s a problem, though. What if many of the defining questions of our age are not answerable in terms of the extent of people encompassed, but the intensity with which people are affected? Unemployment is one example. The fact that Britain got through the Great Recession of 2008-13 without unemployment rising substantially is generally viewed as a positive achievement. But the focus on 'unemployment' masked the rise of underemployment, that is, people not getting a sufficient amount of work or being employed at a level below that which they are qualified for.
This currently accounts for around 6% of the 'employed' labour force. Then there is the rise of the self-employed workforce, where the divide between “employed” and 'involuntarily unemployed' makes little sense."
The American Conservative magazine recently published an article which illuminates another problem with statistics: in a highly diverse and fragmented society, the statistical "answer" depends all too heavily on the construct of the population being sampled/measured.
The article explains how economists George Borjas and Giovanni Peri attempt to answer with data and statistical analysis this question: does uncontrolled immigration have a net positive or net negative effect on native-born workers?
Borjas' analysis concludes the net effect is negative, Peri's concludes it is net positive, as an expansion of immigrant labor means businesses are expanding and will hire more supervisors, who tend to be native-born.
Each argues for the validity of their data and analysis. Which is "correct"? It depends on the population being surveyed. Maybe one conclusion is "correct" for Miami and the other is "correct" in Orlando.
Given the complexity, diversity and fragmentation in the nation as a whole, can any over-arching statistic make any sense of the economy? It seems the answer is "not really." The accuracy and precision of one-big-basket statistics are both illusory.
Another possible factor in national statistics losing their value is the fragmentation of classes of workers and employment. When these statistical models were developed in the 1930s, broad categories such as "industrial workers" and "family farmers" were useful because these classes of workers shared key traits that made lumping them into one statistical basket common-sensical.
For example, industrial workers labored for 40+ hours in factories, and were largely interchangeable. Family farms were more or less productive but could usefully be lumped into one basket.
Now such broad categories cover a much smaller percentage of the workforce. We now have hybrid categories (workers with multiple part-time jobs, Uber drivers, etc.) that cannot be tossed into the old baskets if the resulting statistics are to have any validity or meaning.
Another problem is the intrinsic difficulty in measuring the "intensity" or nature of unemployment. As J.D. Vance, author of the book Hillbilly Elegy has observed in interviews, some of the long-term unemployed appear to have lost the culture of work--the drive and values required to work in a permanent job or be successfully self-employed.
How do we measure an erosion in the culture of work? What statistics can we gather that measure and illuminate this critical trend? How do we quantify qualities that don't lend themselves to easy measurement?
How can we tackle problems if we've mislabeled them and misunderstood them because statistics gave us a false confidence we understand the real problem?
Many people have noted that 95 million working-age adults have been classified as "out of the workforce." What does this mean? Does it mean they have found some other source of income (disability, etc.) so they don't need to bother with work, or they have lost the culture of work, or that they live in a desert of employment opportunities? If we can't identify the nature and intensity of their unemployment, how can we understand the drivers of this structural unemployment?
It's not just the diversification, complexity and fragmentation of the economy that has rendered one-big-basket statistics like unemployment worthless in terms of understanding problems and circumstances--it's also a fragmentation of our understanding of the social contract, and socially/economically productive roles.
From Left Field
Mark Blyth--Global Trumpism (1:26) (via Zeus Y.) -- if you haven't heard of Mark Blythe, give this a look...
Robots Over Roughnecks: Next Drilling Boom Might Not Add Many Jobs
Finding Balance of Public and Private in Community (via Lew G.)
Robert David Steele, Truth At Any Cost Lowers All Other Costs (1:01) (via Chad D.)
How America Could Collapse (via Lew G.)
Supply chain shocks have already led to shortages of videotape and auto parts. Could food or medicine be next?
FRONTLINE Interviews: Trump’s Road to the White House: Frank Luntz (via Lew G.)
The Power of Addiction and The Addiction of Power: Gabor Maté at TEDxRio (18:46)
The Dying Days of Liberalism (via Lew G.)
We are dealing with a series of institutions, an expert class, and a network of political and corporate alliances, that is being shaken beyond repair. We are in the earliest days of a historical transition...
How to Cut Infrastructure Costs in Half (Ellen Brown) -- cut the costs of borrowing...
The U.S. Empire Would Have Collapsed Decades Ago If It Didn’t Abandon The Gold Standard -- important to understand: you can't have a gold standard of money and run deficits, as your gold quickly goes to zero...
Hawaiians call Mark Zuckerberg 'the face of neocolonialism' over land lawsuits -- maybe Mark had good intentions, but suing native residents to clear up any land title claims is not very savvy PR...
Political Science’s “Theory of Everything” -- nice review of The Deep State
China’s Army of Global Homebuyers Is Suddenly Short on Cash (via Joel M.) -- this could be a big deal, as Chinese buyers are the marginal buyers willing to overpay for property everywhere on the globe. If they dry up, the global housing bubble pops in short order...
"Conquering the world on horseback is easy; it is dismounting and governing that is hard." Genghis Khan
Thanks for reading--
charles |
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