Posts tagged with facts

An astounding 26 percent of black males in the United States report seeing someone shot before turning 12.

Conditional on reported exposure to violence, black and white young males are equally likely to engage in violent behavior.
Aliprantis, Dionissi, 2014. “Human Capital in the Inner City,” Federal Reserve Bank of Cleveland, working paper no. 13-02R.

(Source: clevelandfed.org)




[Scientific theories can be accurate and even make novel predictions, whilst being ultimately wrong. Scientific theories can also be inaccurate, whilst being ultimately right.]



Consider specifically the state of ætherial theories in the 1830’s and 1840’s. The electrical fluid, a substance which was generally assumed to accumulate on the surface rather than permeate the interstices of bodies, had been utilized to explain inter alia the attraction of oppositely charged bodies, the behavior of the Leyden jar, the similarities between atmospheric and static electricity and many phenomena of current electricity.

Within chemistry and heat theory, the caloric æther … explain[ed] everything from the role of heat in chemical reactions to the conduction & radiation of heat and … standard problems of thermometry.

Within the theory of light, the optical æther functioned centrally in explanations of reflection, refraction, interference, double refraction, diffraction and polarization. (Of more than passing interest, optical æther theories had … made … startling[, true] predictions, e.g., Fresnel’s prediction of a bright spot at the center of the shadow of a circular disc: a surprising prediction which, when tested, proved correct. If that does not count as empirical success, nothing does!)

There were also gravitational (e.g., LeSage’s) and physiological (e.g., Hartley’s) æthers which enjoyed some measure of empirical success. It would be difficult to find a family of theories in this period which were as successful as æther theories. Compared to them, 19th century atomism … a genuinely referring theory … was a dismal failure. Indeed, on any account of empirical success which I can conceive of, non-referring 19th-century æther theories were more successful than contemporary, referring atomic theories.

[According to] J.C. Maxwell…the æther was better confirmed than any other theoretical entity in natural philosophy!

Larry Laudan’s A Confutation of Convergent Realism, Philosophy of Science, 48(1), 19-49

via David Corfield




Research focuses on real wages—wages that are adjusted for inflation. Getting data on wages is tricky. But accounting for inflation is even harder. (For example, workers often paid rent informally, meaning that there are few records around).

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And so it is unsurprising that researchers differ in their estimations of real wages. Some, such as Peter Lindert and Jeffrey Williamson, suggest that full-time earnings for British common labourers, adjusted for inflation, more than doubled in the seventy years after 1780. But Charles Feinstein argued that over the same period, British real wages only increased by around 30%. It’s a bit of a … mess.

Most people agree that after about 1840, real wages did better. Nicholas Crafts and Terence Mills shows that from 1840 to 1910, real wages more than doubled. Their findings are mirrored by other researchers ….

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in almost all British cities, mortality conditions in the 1860s were no better—and were often worse—than in the 1850s. In Liverpool in the 1860s, the life expectancy fell to an astonishing 25 years. It was not until the two subsequent decades that rises in life expectancy were found

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Advertising rises and falls with the economy, though how much is a matter of debate. Randall Rothenberg … points to the remarkable stability of advertising at about 2% of GDP since 1919, when the data began to be collected.

(Source: economist.com)





Since [2008], the [US] labor force participation rate (LFPR) has dropped from 66 percent to 63 percent. [Out of 314M people.] Many people have left the labor force because they are discouraged … (U.S. Bureau of Labor Statistics data indicate that a little under 1 million people fall into this category)….
…Knowing the reasons why people have left (or delayed entering) the labor force can help us [guess] how much of the ↓ might … ↑ if the economy ↑ and how much is permanent. (For more on this topic, see here, here, and here.)

The chart … shows the distribution of reasons in the fourth quarter of 2013…. Young people [usually say they] are not in the labor force … because they are in school. Individuals 25 to 50 years old who are not in the labor force mostly [say they] are taking care of their family or house. After age 50, disability or illness becomes the primary reason [given]—until around age 60, when retirement begins to dominate.
…
Of the 12.6 million increase in individuals not in the labor force, about 2.3 million come from people ages 16 to 24, and of that subset, about 1.9 million can be attributed to an increase in school attendance (see the chart below).

—Ellyn Terry

HT @conorsen
off-topic sidenote: the natural cohort —vs— year adjustments, like “the baby boom has shifted 7 years since 7 years ago” are an economic example of the covariant/contravariant distinction

Since [2008], the [US] labor force participation rate (LFPR) has dropped from 66 percent to 63 percent. [Out of 314M people.] Many people have left the labor force because they are discouraged … (U.S. Bureau of Labor Statistics data indicate that a little under 1 million people fall into this category)….

…Knowing the reasons why people have left (or delayed entering) the labor force can help us [guess] how much of the ↓ might … ↑ if the economy ↑ and how much is permanent. (For more on this topic, see herehere, and here.)

The chart … shows the distribution of reasons in the fourth quarter of 2013…. Young people [usually say they] are not in the labor force … because they are in school. Individuals 25 to 50 years old who are not in the labor force mostly [say they] are taking care of their family or house. After age 50, disability or illness becomes the primary reason [given]—until around age 60, when retirement begins to dominate.

Of the 12.6 million increase in individuals not in the labor force, about 2.3 million come from people ages 16 to 24, and of that subset, about 1.9 million can be attributed to an increase in school attendance (see the chart below).

Ellyn Terry

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HT @conorsen

off-topic sidenote: the natural cohort —vs— year adjustments, like “the baby boom has shifted 7 years since 7 years ago” are an economic example of the covariant/contravariant distinction


hi-res




U.S. homelessness dropped nearly 17% over the past eight yearsvia The State of Homelessness in the USA

hi-res




There are very few facts I think “everyone should know”. The huge income differences across countries are an exception.

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Everyone should know that income per person in Burundi is about 1% of in the U.S. (yes, even though there’s a recession on).

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And everybody should know a rough quantitative history of the world.

13 minutes by Tyler Cowen & Alex Tabarrok




A billion chronically hungry people in the world via The Economist
As you can see from the right-hand scale, during the 1990’s and 2000’s the “bottom billion” poorest people have been starving or close to it.
Even though the right-hand scale is more important, the lines get graphical emphasis.
Therefore the two pictures, though nearly equivalent in absolute terms, tell very different stories:about a spiking crisis and increasing failure to deal with poverty during rich-world recession
about marginal improvements that continue despite a rich-world financial debacle.

Both stories were told by the Food and Agriculture Organisation, of the United Nations.
Of course statistical bodies revise estimates all the time.
But still this juxtaposition warns us to question the facticity of numbers appearing in charts.
All data come from somewhere. Just because the numbers appear on a chart doesn’t make them correct.

A billion chronically hungry people in the world via The Economist

  • As you can see from the right-hand scale, during the 1990’s and 2000’s the “bottom billion” poorest people have been starving or close to it.
  • Even though the right-hand scale is more important, the lines get graphical emphasis.
  • Therefore the two pictures, though nearly equivalent in absolute terms, tell very different stories:
    1. about a spiking crisis and increasing failure to deal with poverty during rich-world recession
    2. about marginal improvements that continue despite a rich-world financial debacle.
  • Both stories were told by the Food and Agriculture Organisationof the United Nations.
  • Of course statistical bodies revise estimates all the time.
  • But still this juxtaposition warns us to question the facticity of numbers appearing in charts.
  • All data come from somewhere. Just because the numbers appear on a chart doesn’t make them correct.

hi-res




The Speenhamland allowance scale enacted in 1795 effectively set a floor on the income of labourers according to the price of bread.

When the gallon loaf cost 1s, the laborer was to have a weekly income of 3s for himself. … Weekly wages of 3s are equal to …3.72 pounds of bread per day for a single labourer. This is an important figure to remember as the Speenhamland allowance.

As a pound of bread provides about 1100 calories, the allowance gave the labourer a total of 4100 calories per day. An agricultural labourer doing 8-10 hours of vigorous work can easily require 3000 calories/day. It is evident that the Speenhamland allowance provided just above the bare means of subsistence.




What jobs do the 1% have? by Bajika, Cole, and Heim

BCH and the US government did all the work here. My only contribution was to highlight

  1. professions I didn’t expect to see like pilot, farmer, government, teacher
  2. some “standard narratives”:
    • the one about “lawyers and doctors”
    • (I don’t know why these two get grouped together, since one works in abstractions and the other works in gore…but whatever, that is a narrative)
    • the one about “study hard and you’ll get ahead” (scientists, professors, computer, maths)
    • and “real estate developers”
 

Obviously the top 1.5M earners aren’t important to the exclusion of the other 311M Estadounidenses, the 145M employed Estadounidenses, or everyone else.

Equally obvious is that

fraction of lawyers in the one percent is not the same as fraction of one percent who are lawyers

(some lawyerly deeds are more lucrative than others … same for doctors.)

Still, if you’re 

  • choosing a career
  • thinking about social justice
  • trying to understand how the world works

then you might want to find out about rich people. It might be better to do so with, you know, actual facts, rather than for example listening to a bunch of programmers b*tch about how much money lawyers and doctors make.

 

Back to Bajika Cole & Heim. Why is it that this basic information wasn’t known? BCH, Pikkety Saez, and a few others who have bothered to parse data to answer simple questions seem to get fairly good citations. Are economics researchers so bent on complicated research that they won’t “arb” citations by doing something a non-PhD could do?

It is well known that the share of US income going to the top percentiles has increased dramatically over 1986–2006.  Piketty and Saez found that the top ¹⁄1000’s share of pre-tax income (ex cap gains) in the United States that was received by the top ¹⁄1000 rose from 2.2% to 8.0%.

But we don’t know what these people typically do for a living. Kaplan and Rauh (2010) looked through publicly-available information on top executives of publicly-traded firms, financial professionals, law partners, and professional athletes and celebrities. Despite making various extrapolations beyond what is directly available in publicly-available data sources, they were only able to identify the occupations of 17% of the top ¹⁄1000 of income earners.

We tabulated individual income tax return data from the U.S.Treasury Department on what share of top income earners work in each type of occupation. Through this method we are able to account for the occupations of almost all top earners – for example, for over 99% of primary taxpayers in the top ¹⁄1000.

(I liberally edited without [] or ….)

They also looked at spouses of the well-paid, computed income shares, computed growth rates, and broke down the incomes into

  • 1% ex ½% (rank 1,500,000–750,000)
  • ½% ex 0.1% (rank 750,000–150,000)
  • 0.1% (rank 150,000–1)

. All of this is at the end of the PDF, after the bibliography.

Anyway let’s give BCH a hand for providing us with useful information.

"Theory is easy. Data are hard."

(Source: web.williams.edu)