Category: Data Source
Joel Mokyr on living standards during the Industrial Revolution
One of the notable arithmetical truths about the period of the Industrial Revolution is that it is quite possible (if not certain) that biological living standards in both urban and rural areas rose and yet average living standards declined. This can happen if urban living conditions are significantly worse than rural ones, and the proportion of people living in cities is rising because of migration from the countryside to the towns. It seems likely that the biological measures of living standards were especially sensitive to urbanization. While urban areas may have offered some positive amenities (such as entertainment and more choice in shopping), healthy living conditions were surely not among them.
That is from Mokyr's new and notable The Enlightened Economy: An Economic History of Britain 1700-1850. The obvious question of course is why so many people moved into cities. Did "new goods" make the urban living standard higher than some measures might suggest? Was it to avoid boredom? To avoid "rural idiocy" and invest in future IQ externalities for children?
Here is my previous post on the book.
What are the most borrowed books from UK libraries?
Circa 2009, three out of the top four are by James Patterson. Eventually Ian Rankin and Ruth Rendell make the list. Dan Brown I believe too many people have bought or already read. None of the Booker Final Six from the previous year make the list.
Catherine Cookson used to dominate these metrics but she has been swamped by American popular authors and is down to number ten for the decade. Number one for the noughties is in fact Jacqueline Wilson. That's an odd status to hold: "worth reading, just not worth buying."
A broader point is that non-fiction does very poorly on the "most borrowed" list. I'll offer up the hypothesis that low-brow fiction is what most people actually want to read, whereas many people will buy but not read non-fiction, for purposes of affiliation with the author or the concepts associated with the book.
Overall borrowers are more conservative than buyers, in the literal sense of wanting to borrow the same authors over and over again, yet in different titles.
Hat tip goes to the always-excellent Literary Saloon.
Henry Aaron writes to me
James Kwak's calculation of the value of tax exclusion is incomplete. He leaves out the exclusion from the payroll tax, worth 15.3 percent to the person in his example and to most people, and 2.9 percent (at the margin) for the rest who earn more than the OASDI taxable maximum. The correct math is that the gross wage is 1 + .0765 = 1.0765 to allow for the employer's payroll tax cost. The take home pay that could be used, after both payroll and income tax for someone in the 15 percent bracket is 1 – 0.0765 – 0.15 = 0.7735. That means that the tax wedge is equivalent to a subsidy of 1- [.7735/1.0765] =.7185. That is a 28.15 percent subsidy.
For filers in the 28 percent bracket, which is easy to reach for a couple each of whom earns, say, $75,000, the subsidy is a bit over 40 percent.
The fact I would like to know about the stimulus
I break the stimulus into three parts: the tax cuts and transfer increases, the aid to state and local governments, and the traditional spending programs. Here I'm talking about only the third part. (If you are wondering, I regard the first part as mostly ineffective and the second part as mostly effective.)
Of the workers employed by this third part of the Obama stimulus, what percentage of them already had jobs? What percentage moved from unemployed to employed? More hypothetically, what percentage had jobs but would have lost them, thus effectively counting as a move from "unemployed" to "employed" status?
I'm not talking about the maybe-hard-to-estimate effects from boosting aggregate demand, I'm talking about the "mere counting" aspect of the problem. "We hired him, he didn't have a job before. Now he has a job." What percentage of the hired people fall into that category?
I've read plenty on these studies, but they don't seem "net" to me.
Does anyone know where this information is available?
Census Miscounts
Wow, Justin Wolfers reports on a new NBER paper (ungated) by Trent Alexander, Michael Davern and Betsey Stevenson, that finds big errors in Census data, especially for citizens 65 years and older.
What’s the source of the problem? The Census Bureau purposely messes with the microdata a little, to protect the identity of each individual. For instance, if they recode a 37-year-old expat Aussie living in Philadelphia as a 36-year-old, then it’s harder for you to look me up in the microdata, which protects my privacy. In order to make sure the data still give accurate estimates, it is important that they also recode a 36-year-old with similar characteristics as being 37. This gives you the gist of some of their “disclosure avoidance procedures.” While it may all sound a bit odd, if these procedures are done properly, the data will yield accurate estimates, while also protecting my identity. So far, so good.
But the problem arose because of a programming error in how the Census Bureau ran these procedures. The right response is obvious: fix the programs, and publish corrected data. Unfortunately, the Census Bureau has refused to correct the data.
The problem also runs a bit deeper. If the mistake were just the one shown in the above graph, it would be easy to simply re-scale the estimates so that there are no longer too many, say, 85-year-old men – just weight them down a bit. But it turns out that the same coding error also messes up the correlation between age and employment, or age and marital status (and, the authors suspect, possibly other correlations as well). When you break several correlations like this, there’s no easy statistical fix.
Worse still, the researchers find that related problems afflict the microdata released for other major data sources. All told, they’ve found similar errors in:
- The 2000 Decennial Census.
- The American Community Survey, which is the annual “mini-census” (errors exist in 2003-2006, but not 2001-02, or 2007-08).
- The Current Population Survey, which generates our main labor force statistics (errors exist for 2004-2009).
These microdata have been used in literally thousands of studies and countless policy discussions.
The world’s 25 dirtiest cities
Here is the article, here is the top of the list:
1, Baku, Azerbaijan
2. Dhaka, Bangladesh
3. Antananarivo, Madagascar
4. Port-au-Prince (pre-quake? I believe they are now uncontested #1 or will be soon.)
5. Mexico City
Most of the rest are in Africa. If I did the ranking, Mexico City would do much better than number five, since air pollution isn't as bad as the lack of sanitation in cities such as Conakry (a mere #19). And why does Bangui (CAR) get such an idyllic photo? Nor does Google offer up any nasty photos of the place.
Hat tip goes to the essential Rachel Strohm, Twitter feed here.
Who are the friendliest people on earth?
Chug points me to this latest survey, and here is the list:
1. Bahrain
2. Canada
3. Australia
4. Thailand
5. Malaysia
6. South Africa
7. Hong Kong
8. Singapore
9. Spain
10. United States
That means friendly to expats, not friendly to each other. You’ll notice that English-speaking or English-fluent countries are overrepresented, plus Thailand (ahem).
Here is a critique of the survey and mostly I concur with the criticisms (sorry Omar). More generally, unless it is a woman seeking marriage, I view “friendliness to expats” as a social strategy, often intended for internal consumption, not necessarily insincere but not reflecting true temperament either. It’s not driven by actual friendliness. By the way, how did Spain ever make it to number nine?
Are the Japanese the most or the least friendly people on earth? “Helpful” isn’t the same as “friendly.” In what country are you most likely to make real friends? Marry a native? Aren’t those two variables inversely related?
“Friendly” is one of the words most likely to arouse my deconstructive suspicions.
Who are the biggest donors to Haiti?
Here is an interesting visual, which expresses pledged support to Haiti in per capita terms. #1 is Canada, by a large margin, followed by some of the Nordic countries.
Per capita the U.S. doesn't do so well (NB: I don't think remittances are counted), with less than half of what Guyana supplies. We're also behind Estonia, Switzerland, and United Arab Emirates, among other countries. The visual is measuring earthquake aid pledged, not all foreign aid.
In absolute terms here is another visual; U.S. is #1. I don't think this is using the same metric as above.
Here's another interesting visual. Relative to per capita gdp, Ghana is the single most significant pledger of aid to Haiti.
For the pointer I thank Rahul Nabar.
The incomes and professions of Haitian-Americans
The blog post is here. It's a proposal for "diaspora bonds" (I fear that excess corruption is a problem). I was more interested in this bit:
…nearly one-third of Haitian immigrants in the US belong to households that earned more than $60,000 in 2009. In comparison, less than 15% of the immigrants from Mexico, Dominican Republic and El Salvador in the US had that level of household income. A quarter of Haitian immigrants, especially women, are reportedly in the relatively higher paying health care and education sectors; only a small number of them are in the construction sector.
Hat tip goes to Whirled Citizen.
I was surprised this number was such a big one
Organized labor lost 10% of its members in the private sector last year, the largest decline in more than 25 years.
I meant to blog this the day I read it but somehow I forgot to; here is one source. I haven't seen it receive much discussion in the econ blogosphere. For one thing, it's a sign that the union wage premium isn't so stable.
Haiti fact of the day
In 2009, the cost of dealing with construction permits in Haiti was about 570% of income per capita.
Here is the source post, with further information. Had I mentioned that perhaps as much as eighty percent of the population of Port-au-Prince is homeless?
Haiti fact (?) of the day
Is it possible that now almost eight percent of Haiti's population consists of orphaned children? Reliable data are hard to come by but this one estimate suggests it might be true. (Current living population is maybe 9.5 million (?), with the number of orphans estimated at 750,000.) It is also the case that the Haitian government seems reluctant to let these children be adopted abroad, in part because it is difficult to tell which children are truly orphaned.
Addendum: Here is one estimate.
Speech Balloons
Here from Maya Sen are speech balloons illustrating the importance of various words from the majority and then dissenting/concurring opinions in Citizens United v. FEC (more frequently used words are larger). It's interesting to me that just looking at the balloons I can tell which side was more concerned with the Constitution and which side was more concerned with a particular view of the ideal polity.
See Bainbridge for a much more complete roundup of the issues.
Crayola’s Law
Predictably Amusing
Dan Ariely uses Google to look at the most common responses to "how can I get my boyfriend to" and "how can get my girlfriend to."