Doublethink means the power of holding two contradictory beliefs in one’s mind simultaneously, and accepting both of them.” – George Orwell, 19841

The parody of a presidential election playing out on the ubiquitous combination of traditional and social media reminds me of Orwell’s 1949 classic. There are any number of examples from the current election cycle that serve to validate Orwell’s prescient depiction of doublethink as a means of persons or organizations furthering their own or its own objectives at the expense of the best interests of public. The implications for the future suggested by what we are hearing and reading in the year 2016 are at best disconcerting.

Take for example the tracking by the Pulitzer Prize-winning site Politifact of the statements made by the leading candidates of the two major political parties. The site’s Truth-O-MeterTM rates Democratic front-runner Hillary Clinton’s statements as true or mostly true only 50% of the time. Including half-true rated statements raises the mark to 71%, leaving her statements 29% of the time rated as mostly false, false, or “pants on fire”. Donald Trump’s Truth-O-MeterTM record makes Clinton seem like a truth-seeker. Only 8% of the time are the billionaire’s statements rated true or mostly true. Including half-true ratings raises his “true” level to a whopping 24%. In other words, 76% of his statements prove mostly false, false, or pants on fire. Truthfulness must not be a priority (or even a criterion?) among primary election voters.

Perplexed as to what lies behind this observation, I entertain two hypotheses. One is the absence of alternatives; the belief that “all politicians are crooks, so what difference does it make?” I suppose there are many whose thinking goes along such lines. However, I sense there is something more sinister at work here; something Orwellian.

Consider one of the most controversial issues of the campaign: global climate change. Scientists established in 1859 (not a typo) that carbon dioxide (CO2) traps heat in the earth’s atmosphere; the so-called “greenhouse effect.” Since the late 1950s, we have known, thanks to a scientist named Keeling, CO2 concentrations in the atmosphere are seasonal, rising and falling each year depending on the growth and decline of seasonal plant life. While analyzing this seasonality, Keeling noticed that the lows each year after this seasonal swing in CO2 concentrations were creeping higher. The low in each year was not returning to the low in the preceding one.

For decades since Keeling’s discovery, the scientists at the Scripps Laboratory at the University of California at San Diego (and elsewhere) have been documenting atmospheric CO2 concentration trends. Anyone can see from the “Keeling Curve” charts, as they are known, at the Scripps site, that for most of the last 800,000 years (again, not a typo), CO2 concentration levels in the atmosphere have varied between about 170 parts per million (ppm, shown on the vertical axis) to about 300 ppm. The growth in CO2 concentrations picked up around the time of the industrial revolution, and began a noticeable acceleration in the 1950s. (One can view several different timeframes by clicking the buttons below the chart.) The Scripps site’s history of the Keeling curve describes carbon dioxide as a “greenhouse gas produced by natural processes and everyday human activities, especially the burning of fossil fuels.” Hence the trend’s correlation with the industrial revolution and the post-World War II economic boom.

Seen in the broad arc of 800,000 years of history, this post-WW II acceleration in heat-trapping gas in the atmosphere is so vertical so as to be confused with the right vertical axis. The most recent level of CO2 is above 400 ppm. According to the Bloomberg Carbon Clock the level scientists consider the “danger zone” for the planet is about 450.

Even if one believes the Scripps data on CO2 concentrations but disbelieves the connection between atmospheric CO2 levels and global warming, there is credible data available to all that validates this connection from the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information State of the Climate site. In their Global Analysis – Annual 2015, NOAA displays a table (go to the report’s link and scroll down) showing the sixteen warmest years on record (1880-2015). All such years have been since 1998.

In other words, the scientific evidence indicates that the planet is warming, the cause being the greenhouse effect induced by unprecedented concentrations of greenhouse gases such as CO2 in the atmosphere. Neither the Republican front-runner nor his chief opponent claim to believe in climate change. Senator Ted Cruz is reported (on Bloomberg, at the following link) to have called climate change “a “pseudoscientific theory” and contends the earth is actually in a cooling phase.” I believe Cruz means what he says, despite the scientific data, which he must have seen in order to have assessed that it represents “pseudoscience.” Hence the power of doublethink.

One might consider such instances of doublethink – the ability of millions of voters to rationalize voting for a habitual liar, or the ability of a presidential candidate to assert and convey a genuine belief in something that the scientific evidence covering eight centuries contradicts — as unique to politicians and their most active supporters.

The doublethink phenomenon, however, appears to be widespread. In a March 2016 Pew Research Center survey update, only 20% of republicans, 41% of independents and 68% of democrats are reported as viewing climate change as a “very serious problem.” The capacity to hear and read about troubling scientific data and at the same time discount the seriousness of that data would appear to be a tendency that crosses partisan lines. Set aside for a moment the climate change views of the survey’s republican and independent respondents. The 20% is confounding, and the 41% stat stirs me to wonder if doublethink is behind my “unaffiliated” voter registration status. Why would the democrat survey percentage not be something closer to 100%?

Take as another example the belief fundamental to the worldview propagated by Silicon Valley: that the digital revolution underlies a wave of productivity growth that promises to make the world a better place for all. As former Fed Vice Chairman Alan Blinder pointed out in the Q&A session following Federal Reserve Chairwoman Janet Yellen’s recent speech at the Economic Club of New York, labor productivity growth – a key determinant of long-term economic growth – has averaged about 0.5% the past five years. In fact, in a news release from March 3, 2016 on productivity and costs (Fourth Quarter and Annual Averages 2015, Revised), one can see from Table C, the nonfarm business sector labor productivity growth has been at about that rate (0.52%) over the years 2011 thru 2015. In contrast, the long-term rate from 1947 to 2015 was, according to the text in the release, 2.2%.

Considering the credence put in the belief that technological innovation is driving historic productivity growth, the recent decline in productivity growth rates is noteworthy. Moreover, the much-hyped acceleration in productivity may have long failed to live up to expectations. As MIT Professor emeritus and Economics Nobel winner Robert M. Solow lamented as far back as 1987, “You can see the computer age everywhere but in the productivity statistics.” (New York Times Book Review, July 12, 1987, p. 36)

As Blinder pointed out in the aforementioned Q&A session with Chair Yellen, the “tacit” (his word, not mine) labor productivity growth rate implicit in the current baseline Fed GDP forecast is 1.7%. Someone or some group of economists at the Fed must be comfortable looking past the deceleration in labor productivity growth seen, not just in the last five years, but since 2007.

At first blush, that trend reversal (the 2007-forward growth slowdown) would suggest the decline in productivity growth rates is at least in part a consequence of the Great Recession (which dates to late 2007). Northwestern University Macroeconomist Robert J. Gordon goes further (much) in his book, The Rise and Fall of American Growth: The U.S. Standard of Living Since the Civil War (Princeton University Press, 2016). Gordon summarizes the thesis of his book in a TED talk (The Death of Innovation, the End of Growth). Gordon’s research challenges the view that the technological advances for which the 21st century is so far known – Facebook, Twitter and Instagram being everyday examples – will drive labor productivity growth comparable to the growth derived from innovations like electricity, locomotives, jet planes and the automobile.

The strongest indication that doublethink may be lurking behind the Fed’s baseline GDP forecast productivity growth assumption was Chair Yellen’s reply to Blinder’s query: “It’s a source of huge concern,” she said. “We really don’t know.” Chair Yellen, a labor economist by specialty, has on a number of occasions characterized Fed policy decisions (e.g., Fed Funds Rates) as being “data-driven.” One can see why this issue is a source of concern by viewing the chart “U.S. Average Productivity Growth,” in (the pdf version of) Fed Vice Chair Fischer’s March 7, 2016 speech, “Reflections on Macroeconomcs Then and Now.” The U.S. average productivity growth rate for the period since the financial crisis (2008-2015) is 1.2%, compared with 2.1% for the period 1974 – 2007 or 3.0% for the period 1952 – 1973. This chart suggests long-term decline.

The post-crisis productivity growth slowdown may be due in large part to the Great Recession; the trend may be a cyclical one that corrects over time. However, Gordon presents a persuasive case that such a reversion to historical growth rates demands revolutionary innovations akin to those of the 20th century. So far the innovations we have seen this century have not revealed themselves in the productivity data to have been revolutionary. Quite the contrary.

Time will tell whether we are buying into a myth of technological-innovation-driven productivity growth. In the meantime, that this belief (despite the conflicting data) may be a key assumption behind the Fed GDP forecast overseen by a respected labor economist and Chair of a data-driven central bank may turn out to have been a remarkable example, along with the climate change debate and presidential election-year politics of the power of Orwell’s doublethink.

Let us hope the truth comes out in all three cases before it is too late.


1 Harcourt Brace and Company, 1949; referenced copy Plume, 1983, p. 176.


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