Thursday, December 8, 2016

America’s male employment crisis is both urban and rural Alan Berube

America's male employment crisis is both urban and rural

Alan Berube


In the wake of the 2016 presidential election, many analysts have interpreted Donald Trump's victory as the product of economic anxiety among the white working class—particularly in the smaller towns and rural areas that provided his electoral margin in closely contested states like North Carolina, Michigan, Pennsylvania, and Wisconsin.

Author

This piece does not purport to explain why people voted the way they did, or what role economic factors played in their decisions. Rather, it acknowledges that the state of the economy in small-town and rural America highlighted throughout the campaign and after the election surely deserves attention. Economists such as David Autor have chronicled how increasing Chinese imports over the past two decades produced long-term economic dislocation in many of these communities. Anne Case and Angus Deaton uncovered alarming evidence that mortality rates have risen among white Americans with lower levels of education, paralleling a rapid increase in drug overdoses largely concentrated in non-urban areas.

Central to these discussions is the availability of work in such communities, particularly for men who have borne the brunt of manufacturing job losses. Research from President Obama's Council of Economic Advisers highlighted the trends and factors underlying the decline in labor force participation among prime-aged men (ages 25–54). Earlier this year, I examined the metropolitan geography of non-working, prime-aged men, finding that smaller industrial centers in Michigan, Indiana, and Ohio exhibited low rates of male employment, as did mining centers in West Virginia and Louisiana, and agricultural centers in Arkansas, Texas, and inland California.

While the focus on metropolitan areas illustrates important regional patterns relating to economic function and migration, it may obscure important differences in employment within metro areas, while also overlooking the non-metropolitan communities on which economists have focused increasing attention. By examining the full range of U.S. community types, this analysis shows that cities and smaller communities ultimately have a shared interest in improving access to employment opportunities for prime-aged workers.

To illustrate conditions and trends in work across the urban-rural continuum, I examined U.S. Census data for cities and counties according to a novel Brookings Metro classification system[1]:

  • 139 primary cities anchor the nation's 100 largest metropolitan areas; they include the largest city in each of those metro areas, along with other cities in the metro name with populations of at least 100,000 (e.g., all three cities named in the Los Angeles-Long Beach-Anaheim metropolitan area).
  • 81 high-density suburban counties surround or abut many of these cities; at least 95 percent of residents in these counties live in a census-defined "urbanized area" that forms the dense core of the metropolitan area; these are often referred to as "older" or "first" suburbs (e.g., Alameda, CA; New Haven, CT; Fulton, GA).
  • 157 mature suburban counties represent the next era of metropolitan development, where today 75–95 percent of residents live in an urbanized area (e.g., Kendall, IL; Howard, MD; Collin, TX).
  • 344 emerging suburban and exurban counties lie at the fringe of major metro areas, where fewer than 75 percent of residents live in urbanized areas (e.g., Fauquier, VA; Aiken, SC; St. Croix, WI).
  • 567 small metropolitan counties comprise metropolitan areas outside the 100 largest (e.g., Muskegon, MI; St. Lucie, FL; Pueblo, CO).
  • 658 micropolitan counties are part of census-defined micropolitan areas centered on smaller cities and towns with populations between 10,000 and 50,000 people (e.g., Twin Falls, ID; Clinton, NY [Plattsburgh]; Dare, NC [Kill Devil Hills]).
  • 1,318 rural counties form the rest of the U.S. map, from Aroostook in northern Maine (population 72,000) to Golden Valley in central Montana (population 880).

Figure 1.

metro_20161205_work_by_county_type_fig1


Classifying the United States in this way reveals that primary cities, high-density and mature suburbs, and small metro area counties contain roughly similar numbers of residents (Figure 1). The less urbanized parts of the country contain smaller numbers of people, with rural areas accounting for the smallest share (just 6 percent of total U.S. population).

This view of the urban-rural continuum also points to three key findings regarding the geography of work (and non-work) among prime-aged men in the United States.

Rates of work among prime-aged men are below average in both cities and smaller, less urbanized communities. The latest available data, which reflect conditions between 2010 and 2014, indicate that slightly over 80 percent of all prime-aged men nationwide were working during that time.[2] Prevailing rates were lower, however, in both large cities and smaller, less urban communities (Figure 2). In big cities and smaller metro areas, 79 percent of prime-aged men were employed during those years. The shares dropped to 75 and 72 percent, respectively, in micropolitan and rural areas.


Figure 2.

metro_20161205_work_by_county_type_fig2


Even among these smaller places, rates of employment among prime-aged men varied across the United States. States beyond just the Rust Belt and Appalachia exhibited low rates of work in their micropolitan and rural areas. In fact, among states with at least 50,000 residents in these types of communities, rates were lowest in Florida, Arizona, and California (Figure 3). In non-metropolitan Louisiana, South Carolina, and Georgia, too, less than two-thirds of prime-aged men were employed in the 2010–2014 period. While Kentucky and West Virginia also exhibited employment rates below 70 percent in their smaller areas, these statistics indicate that even many states with racially and ethnically diverse rural areas suffer employment challenges in such communities.

Low rates of work among prime-aged men also affect many big cities with diverse populations. Among the 139 primary cities, 18 exhibited employment rates below 70 percent for these men from 2010–2014. Interestingly, Rust Belt cities—including three in Ohio and one each in Michigan and Pennsylvania—figure most prominently among those with very low prime-aged male employment rates. Other racially segregated cities in the Northeast (Hartford, Newark, Rochester, Springfield, and Syracuse) exhibit similarly low rates of work among these men.


Figure 3.

Many non-metro communities and cities share low rates of work

Micropolitan/rural areas in statePrime-aged male employment rate (2000 to 2010-14)Primary cityPrime-aged male employment rate (2000 to 2010-14)
Florida57.2Youngstown, Ohio47.6
Arizona58.1Detroit, Mich.51.1
California64.5Dayton, Ohio61.1
Louisiana65.5Cleveland, Ohio62.5
South Carolina65.8Hartford, Conn.62.6
Georgia66.5Harrisburg, Pa.65.6
Kentucky66.9Syracuse, N.Y..66.0
Mississippi69.2Newark, N.J.66.1
West Virginia69.3Springfield, Mass.66.5
Virginia69.9Rochester, N.Y.67.1
All micropolitan/rural areas73.8All primary cities79.3

Source: Brookings analysis of 2010-14 American Community Survey data
Note: States displayed had at least 50,000 micropolitan/rural residents in 2010-14


Employment rates among men fell dramatically in smaller communities, but rose in cities. Considerably lower rates of work among prime-aged men in micropolitan and rural areas reflect a long-term decline in their employment. From 2000 to 2010–2014, the share of males ages 25–54 who were employed dropped by 4.8 percentage points in micropolitan counties, and by 5.4 percentage points in rural counties (Figure 4). By contrast, employment among this group in cities rose by 2 percentage points during that time and fell only modestly in high-density suburbs. This suggests that a community's level of urbanization was closely related to its employment outcomes for prime-aged male workers.


Figure 4.

metro_20161205_work_by_county_type_fig4


While industrial Midwestern states did not have particularly low non-metro male employment rates in 2010–2014, many saw those rates fall significantly since 2000. Southern states—including South Carolina, Georgia, and Tennessee—suffered the most dramatic declines, but Michigan, Indiana, and Pennsylvania also registered drops of 6–8 percentage points in the share of their micropolitan and rural prime-aged males in work (Figure 5).

Many cities saw equivalent gains in employment rates among this group, including the largest (New York), second-largest (Los Angeles), and fourth-largest (Houston) cities in the country. Some of the changes in non-metro areas and cities may be attributable to changes in the strength of local economies and their demand for workers. At the same time, the changes may also reflect shifts in the underlying populations of those areas over time, as small communities lose more employable residents to out-migration and big cities gain them through in-migration. Notwithstanding those widespread gains, older industrial cities like Akron, Allentown, Augusta, Detroit, Syracuse, and Tacoma experienced declines in prime-aged male employment similar to those occurring in rural areas nationwide.


Figure 5.

Male employment fell dramatically in many states' non-metro areas, while it rose dramatically in several big cities

Micropolitan/rural areas in stateChange in prime-aged male employment rate (2000 to 2010-14)Primary cityChange in prime-aged male employment rate (2000 to 2010-14)
South Carolina-9.4Miami, Fla.12.5
Georgia-8.9Jersey City, N.J.10.0
Tennessee-8.1Newark, N.J.10.0
Michigan-7.7Los Angeles, Calif.8.2
Missouri-7.7McAllen, Texas7.8
Florida-7.6Houston, Texas7.1
North Carolina-7.2Ontario, Calif.7.0
Oregon-7.1Oakland, Calif.6.9
Indiana-6.5Oxnard, Calif.6.5
Pennsylvania-6.4New York, N.Y.6.3
All micropolitan/rural areas-5.1All primary cities2.0

Source: Brookings analysis of 2000 census and 2010-14 American Community Survey data
Note: States displayed had at least 50,000 micropolitan/rural residents in 2010-14


Big cities remain home to more out-of-work prime-aged men than other types of communities. As shown in Figure 2, prime-aged men in cities exhibited below-average employment rates in 2010–2014, as did those in small metro areas, micropolitan areas, and rural communities. This finding—combined with the fact that primary cities are the most populous of the seven community types analyzed here (see Figure 1)—shows that cities contain a larger number of out-of-work prime-aged men than any other community type (see Figure 6). An estimated 2.9 million non-working males ages 25–54 lived in big cities in 2010–2014. The next-largest group occupied small metro areas, followed by high-density and mature suburbs. If micropolitan and rural areas are considered together, they still contained fewer out-of-work prime-aged men than either primary cities or small metro areas.


Figure 6.

metro_20161205_work_by_county_type_fig6


This analysis points to two key takeaways.

First, for as much as the 2016 election pitted urban versus rural interests (reflected in maps of the presidential vote), these places share an important interest in improving the availability and quality of jobs. In the wake of the election, analysis has focused on the white working class and how to alleviate the economic distress facing the smaller communities in which many of those individuals live. But just a year and a half ago, the conversation focused on urban places like Baltimore and Ferguson, where tensions between communities of color and law enforcement exposed longstanding economic frustrations. Addressing the employment challenges faced by both types of communities will take serious, long-term commitment and public policy focus untethered from the news cycle.

Second, while jobs are certainly a shared priority for cities and rural areas, their divergent trend lines in employment opportunity merit reflection. The past 10–15 years have strengthened the economic hand of many cities, as coming-of-age generations seek a more urban lifestyle, and as an increasingly services-focused U.S. economy concentrates in places with greater access to highly skilled labor, innovative institutions, and strong global connectivity. These dynamics, in turn, have raised demand for workers in such places, even for those with lower levels of formal skills, drawing them into jobs at increased rates.

Those same dynamics have simultaneously disadvantaged many small towns and rural areas. If what economists call "agglomeration" is increasingly the route to employment opportunity, can small places succeed? As my colleague Mark Muro has argued convincingly, manufacturing jobs aren't coming back to those communities to a degree anywhere close to the number that have departed. Part of the answer may lie in strengthening connections between larger and smaller places through infrastructure investment and shared economic development strategies. Such efforts could unite economic leaders in cities and their surrounding rural areas in older industrial states, if state lawmakers choose not to pit those interests against one another. Yet if recent trends hold, efforts to bring jobs back to small-town America seem likely to face an uphill battle against market forces that have put jobs further out of reach for many of their residents.

FOOTNOTES

  1. 1My colleague Chad Shearer used a version of this classification system in a recent post-election analysis; this analysis updates and extends that system.
  2. 2Five-year estimates from the American Community Survey provide the only statistically reliable labor market data for the thousands of U.S. counties with populations under 20,000.

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John Case
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Piketty, Saez, Gabriel Zucman


Economic growth in the United States: A tale of two countries

Thomas Piketty and Emmanuel Saez, Gabriel Zucman



Overview

The rise of economic inequality is one of the most hotly debated issues today in the United States and indeed in the world. Yet economists and policymakers alike face important limitations when trying to measure and understand the rise of inequality.

One major problem is the disconnect between macroeconomics and the study of economic inequality. Macroeconomics relies on national accounts data to study the growth of national income while the study of inequality relies on individual or household income, survey and tax data. Ideally all three sets of data should be consistent, but they are not. The total flow of income reported by households in survey or tax data adds up to barely 60 percent of the national income recorded in the national accounts, with this gap increasing over the past several decades.1

This disconnect between the different data sets makes it hard to address important economic and policy questions, such as:

  • What fraction of economic growth accrues to those in the bottom 50 percent, the middle 40 percent, and the top 10 percent of the income distribution?
  • What part of the rise in inequality is due to to changes in the share of national income that goes to workers (labor income) and owners (capital income) versus changes in how these labor and capital incomes are distributed among individuals?

A second major issue is that economists and policymakers do not have a comprehensive view of how government programs designed to ameliorate the worst effects of economic inequality actually affect inequality. Americans share almost one-third of the fruits of economic output (via taxes that help pay for an array of social services) through their federal, state, and local governments. These taxes collectively add up to about 30 percent of national income, and are used to fund transfers and public goods that ultimately benefit all U.S. families. Yet we do not have a clear measure of how the distribution of pre-tax income differs from the distribution of income after taxes are levied and after government spending is taken into account. This makes it hard to assess the extent to which governments make income growth more equal.2

In a recent paper, the three authors of this issue brief attempt to create inequality statistics for the United States that overcome the limitations of existing data by creating distributional national accounts.3 We combine tax, survey, and national accounts data to build a new series on the distribution of national income. National income is the broadest measure of income published in the national accounts and is conceptually close to gross domestic product, the broadest measure of economic growth.4 Our distributional national accounts enable us to provide decompositions of growth by income groups consistent with macroeconomic growth.

In our paper, we calculate the distribution of both pre-tax and post-tax income. The post-tax series deducts all taxes and then adds back all transfers and public spending so that both pre-tax and post-tax incomes add up to national income. This allows us to provide the first comprehensive view of how government redistribution in the United States affects inequality. Our benchmark series use the adult individual as the unit of observation and split income equally among spouses in married couples. But we also produce series where each spouse is assigned their own labor income, allowing us to study gender inequality and its impact on overall income inequality. In this short summary, we would like to highlight three striking findings.

Our first finding—a surge in income inequality

First, our data show that the bottom half of the income distribution in the United States has been completely shut off from economic growth since the 1970s. From 1980 to 2014, average national income per adult grew by 61 percent in the United States, yet the average pre-tax income of the bottom 50 percent of individual income earners stagnated at about $16,000 per adult after adjusting for inflation.5 In contrast, income skyrocketed at the top of the income distribution, rising 121 percent for the top 10 percent, 205 percent for the top 1 percent, and 636 percent for the top 0.001 percent. (See Figures 1 and 2.)

Figure 1

Figure 2

It's a tale of two countries. For the 117 million U.S. adults in the bottom half of the income distribution, growth has been non-existent for a generation while at the top of the ladder it has been extraordinarily strong. And this stagnation of national income accruing at the bottom is not due to population aging. Quite the contrary: For the bottom half of the working-age population (adults below 65), income has actually fallen. In the bottom half of the distribution, only the income of the elderly is rising.6From 1980 to 2014, for example, none of the growth in per-adult national income went to the bottom 50 percent, while 32 percent went to the middle class (defined as adults between the median and the 90th percentile), 68 percent to the top 10 percent, and 36 percent to the top 1 percent. An economy that fails to deliver growth for half of its people for an entire generation is bound to generate discontent with the status quo and a rejection of establishment politics.

Because the pre-tax incomes of the bottom 50 percent stagnated while average national income per adult grew, the share of national income earned by the bottom 50 percent collapsed from 20 percent in 1980 to 12.5 percent in 2014. Over the same period, the share of incomes going to the top 1 percent surged from 10.7 percent in 1980 to 20.2 percent in 2014.7 As shown in Figure 2, these two income groups basically switched their income shares, with about 8 points of national income transferred from the bottom 50 percent to the top 1 percent. The gains made by the 1 percent would be large enough to fully compensate for the loss of the bottom 50 percent, a group 50 times larger.

To understand how unequal the United States is today, consider the following fact. In 1980, adults in the top 1 percent earned on average 27 times more than bottom 50 percent of adults. Today they earn 81 times more. This ratio of 1 to 81 is similar to the gap between the average income in the United States and the average income in the world's poorest countries, among them the war-torn Democratic Republic of Congo, Central African Republic, and Burundi. Another alarming trend evident in this data is that the increase in income concentration at the top in the United States over the past 15 years is due to a boom in capital income. It looks like the working rich who drove the upsurge in income concentration in the 1980s and 1990s are either retiring to live off their capital income or passing their fortunes onto heirs.

Our second finding—policies to ameliorate income inequality fall woefully short

Our second main finding is that government redistribution has offset only a small fraction of the increase in pre-tax inequality. As shown in Figure 1, the average post-tax income of the bottom 50 percent of adults increased by only 21 percent between 1980 and 2014, much less than average national income. This meager increase comes with two important limits.

First, there was almost no growth in real (inflation-adjusted) incomes after taxes and transfers for the bottom 50 percent of working-age adults over this period because even as government transfers increased overall, they went largely to the elderly and the middle class. Second, the small rise of the average post-tax income of the bottom 50 percent of income earners comes entirely from in-kind health transfers and public goods spending. The disposable post-tax income—including only cash transfers—of the bottom 50 percent stagnated at about $16,000. For the bottom 50 percent, post-tax disposable income and pre-tax income are similar—this group pays roughly as much in taxes as it receives in cash transfers.

Our third finding—comparing income inequality among countries is enlightening

Third, an advantage of our new series is that it allows us to directly compare income across countries. Our long-term goal is to create distributional national accounts for as many countries as possible; all the results will be made available online on the World Wealth and Income Database. One example of the value of these efforts is to compare the average bottom 50 percent pre-tax incomes in the United States and France.8 In sharp contrast with the United States, in France the bottom 50 percent of real (inflation-adjusted) pre-tax incomes grew by 32 percent from 1980 to 2014, at approximately the same rate as national income per adult. While the bottom 50 percent of  incomes were 11 percent lower in France than in the United States in 1980, they are now 16 percent higher. (See Figure 3.)

Figure 3

The bottom 50 percent of income earners makes more in France than in the United States even though average income per adult is still 35 percent lower in France than in the United States (partly due to differences in standard working hours in the two countries).9 Since the welfare state is more generous in France, the gap between the bottom 50 percent of income earners in France and the United States would be even greater after taxes and transfers.

The diverging trends in the distribution of pre-tax income across France and the United States—two advanced economies subject to the same forces of technological progress and globalization—show that working-class incomes are not bound to stagnate in Western countries. In the United States, the stagnation of bottom 50 percent of incomes and the upsurge in the top 1 percent coincided with drastically reduced progressive taxation, widespread deregulation of industries and services, particularly the financial services industry, weakened unions, and an eroding minimum wage.

Conclusion

Given the generation-long stagnation of the pre-tax incomes among the bottom 50 percent of wage earners in the United States, we feel that the policy discussion at the federal, state, and local levels should focus on how to equalize the distribution of human capital, financial capital, and bargaining power rather than merely the redistribution of national income after taxes. Policies that could raise the pre-tax incomes of the bottom 50 percent of income earners could include:

  • Improved education and access to skills, which may require major changes in the system of education finance and admission
  • Reforms of labor market institutions to boost workers' bargaining power and including a higher minimum wage
  • Corporate governance reforms and worker co-determination of the distribution of profits
  • Steeply progressive taxation that affects the determination of pay and salaries and the pre-tax distribution of income, particularly at the top end

The different levels of government in the United States today obviously have the power to make income distribution more unequal, but they also have the power to make economic growth in America more equitable again. Potentially pro-growth economic policies should always be discussed alongside their consequences for the distribution of national income and concrete ways to mitigate their unequalizing effects. We hope that the distributional national accounts we present today can prove to be useful for such policy evaluations.

We will post online our complete distributional national accounts micro-data. These micro-files make it possible for researchers, journalists, policymakers, and any interested user to compute a wide array of distributional statistics—income, wealth, taxes paid and transfers received by age, gender, marital status, and other measures—and to simulate the distributional consequences of tax and transfer reforms in the United States.

Thomas Piketty is a professor of economics at the Paris School of Economics. Emmanuel Saezis a professor of economics and director of the Center for Equitable Growth at the University of California-Berkeley. Gabriel Zucman is an assistant professor of economics at the University of California-Berkeley. They are co-directors of the World Wealth and Income Database, together with economists Facundo Alvaredo at the Paris School of Economics and Anthony Atkinson at Oxford University.

  1. Many important forms of income, such as fringe benefits of employees, retained profits and taxes paid by corporations, or imputed rent of homeowners, are part of U.S. national income but are not included in individual survey or tax data. ↩
  2. Official U.S. Census Bureau household income statistics are based on money income. Money income does not subtract individual taxes but adds back cash (but not in-kind) transfers. Hence, it is a mixed concept in between pre-tax and post-tax. It is conceptually sounder to focus separately on pre-tax and post-tax income. The U.S. Congressional Budget Office evaluates the federal tax burden by income groups but does not factor in state and local taxes (U.S. Congressional Budget Office, "The Distribution of Household Income and Federal Taxes, 2013", 2016, Washington DC: U.S. Congressional Budget Office) and does not try to assign the benefits of federal government spending back to individuals. ↩
  3. Thomas Piketty, Emmanuel Saez, and Gabriel Zucman, "Distributional National Accounts: Methods and Estimates for the United States", Cambridge MA: NBER Working Paper, December 2016, http://gabriel-zucman.eu/files/PSZ2016.pdf↩
  4. National income is gross domestic product minus capital depreciation plus net income received from abroad. Capital depreciation is not income and income from abroad is important, particularly among top earners. ↩
  5. All our data are expressed in constant 2014 dollars, using the national income deflator. ↩
  6. Our pre-tax income series are based on income after the operation of private and public pensions so that pension and social security income is included in pre-tax income (and the corresponding contributions are deducted). We also estimate series for factor income (before the operation of pension systems). Factor income series also display stagnation of bottom 50 percent of incomes since 1980. We prefer using pre-tax income series which give the elderly reasonable incomes so that aging has little impact on our inequality series. ↩
  7. This 9.5 points increase in the top 1 percent of the pre-tax U.S. national income share is similar in magnitude to the increase estimated in the Piketty-Saez series, where the top 1 percent income share (when including realized capital gains) increases by 11.4 points from 10 percent in 1980 to 21.4 percent in 2014. The Piketty-Saez series are based on a fiscal income concept, which captures only about two-thirds of total national income, and they use the family tax unit instead of the adult unit (see Thomas Piketty and Emmanuel Saez "Income Inequality in the United States, 1913-1998," Quarterly Journal of Economics, 118(1), 2003, 1-39.) ↩
  8. The results for France are presented in Bertrand Garbinti, Jonathan Goupille, and Thomas Piketty, "Inequality Dynamics in France, 1900-2014: Evidence from Distributional National Accounts (DINA)," 2016, Paris: Paris School of Economics working paper. ↩
  9. In these calculations, we apply the 2014 Purchasing Power Parity exchange rate of 0.819 Euros per US dollar estimated by the Organisation of Economic Cooperation and Development. ↩
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John Case
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Eastern Panhandle Independent Community (EPIC) Radio:Hound Dog, Abel EAkin, Acuff, JB do Local and Labor Dec 8

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Blog: Eastern Panhandle Independent Community (EPIC) Radio
Post: Hound Dog, Abel EAkin, Acuff, JB do Local and Labor Dec 8
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The populist paradox [feedly]

The populist paradox
http://stumblingandmumbling.typepad.com/stumbling_and_mumbling/2016/12/the-populist-paradox.html

THE POPULIST PARADOX

Danny Finkelstein in the Times is good on the need to resist attempts to bully the Supreme Court. He says:

Our institutions – parliament, government, the courts – must serve a plural society, they must balance interests and protect rights.

The case for doing so lies in large part in cognitive diversity – the idea that a plurality of viewpoints is wiser than an individual one. Edmund Burke famously wrote:

We are afraid to put men to live and trade each on his own private stock of reason; because we suspect that this stock in each man is small, and that the individuals would do better to avail themselves of the general bank and capital of nations and of ages (Par 145).

Herein lies a virtue of the rule of law: laws represent the capital of wisdom of ages, and so should act as a check upon our present and perhaps fleeting judgments. Similarly, as Danny says, parliament "allows diverse representation."

Which brings me to a paradox. Academic research in recent years – inspired by Daniel Kahneman – has taught us that Burke was right. Our judgments can be flawed in many ways. Our private stock of wisdom (and knowledge too) is indeed small. We'd therefore expect to see more support for institutions that embody diversity and which check our judgements. And yet the rise of populism represents the exact opposite of this – the urge that one's opinion must over-ride all constraints.

What explains this paradox?

You might object that parliament and the courts aren't as diverse as Danny says. The former is dominated by PPEist clones and the Supreme Court judges are old, posh and white. This, though, is an argument for ensuring more genuine diversity, not for allowing mob opinion to be unchecked.

Another answer is that academic research hasn't affected public opinion. Yes, the BBC does broadcast some good programmes about social science. But it is scrupulous in ensuring these are confined to a ghetto on Radio 4 whilst slots which get bigger audiences are filled by speak your branes drivel.

But there's something else. Increasing academic awareness of the limits of our judgment has been outweighed by the rise of narcissism. Everyone (not just young people) is a special snowflake whose opinion must be respected. It's this, saysAnjana Ahuja, that underpins the populist backlash against science:

Facts and the search for objective truth make up the essence of science; a disregard for the same is not only a hallmark of the new politics but a badge of honour…Why is science under siege? One possible explanation is that it favours objective evidence over subjective experience*.

We see the same thing in Arron Banks' efforts to teach Mary Beard about the fall of the Roman Empire and Douglas Carswell telling scientists about the causes of tides. As Burke said, "they have no respect for the wisdom of others; but they pay it off by a very full measure of confidence in their own." My readers don't need telling about the Dunning-Kruger effect or that Daniel Kahneman said that overconfidence is the most damaging and widespread of mistakes – but many people still do.

To be clear, my beef here is not so much with what you believe as how you believe it. There is a respectable case for Brexit, though it's weakening. What is unjustifiable is a fanaticism which wants to over-ride evidence, expertise and traditional institutions. This form of populism is not just a political problem but an intellectual and, dare I say it psychological, disorder.  

* She's writing about populist opposition to climate science. But we saw the same thing years ago when parents refused to give their children MMRvaccinations against the scientific evidence.


 -- via my feedly newsfeed