Interwar US inequality data are deeply flawed

For some years now, Phil Magness and myself have been working on improving the existing income inequality for the United States prior to World War II. One of the most important point we make concerns why we, as economists, ought to take data assumptions seriously. One of the most tenacious stylized facts (that we do not exactly dispute) is that income inequality in the United States has followed a U-curve trajectory over the 20th century. Income inequality was high in the early 1920s and descended gradually until the 1960s and then started to pick up again. That stylized fact comes from the work of Thomas Piketty and Emmanuel Saez with their data work (first image illustrated below). However, from the work of Auten and Splinter and Mechling et al. , we know that the increase post-1960 as measured by Piketty is somewhat overstated (see second image illustrated below).  While the criticism suggest a milder post-1960 increase, me and Phil Magness believe that the real action is on the left side of the U-curve (pre-1960).

Inequality

NOL1

Why? Here is our case made simple: the IRS data used to measure inequality up to at least 1943 are deeply flawed. In another paper recently submitted, I made the argument that some of the assumptions made by Piketty and Saez had flaws. This did not question the validity of the data itself. We decided to use state-level income tax data from the IRS to compute the state-level inequality and compare them with state-income tax data (e.g. the IRS in Wisconsin versus Wisconsin’s own personal income tax data). What we found is that the IRS data overstates the level of inequality by appreciable proportions.

Why is that? There are two reasons. The first is that the federal tax system had wide fluctuations in tax rates between 1917 and 1943 which means wide fluctuations in tax compliance. Previous scholars such as Gene Smiley pointed out that when tax rates fell, compliance went up so that measured inequality went up. But measured inequality is not true inequality because “off-the-books” income (which was unmeasured) divorced true inequality from measured inequality.  This is bound to generate false fluctuations in measurement as long as tax compliance was voluntary (which is true until 1943). State income taxes do not face that problem as their tax systems tended to be more stable throughout the period. The same is true with personal exemptions.

The second reason speaks to the manner the federal data is presented. The IRS created wide categories with the numbers of taxpayers according to net taxable income (rather than gross income) in each categories. For example, the categories go from 0$ to 1,000$ per filler and then increase by slice of 1,000$ until 10,000$ and then by slices of 5,000$ etc. This makes it hard to pinpoint where to start each the calculations for each of the fractiles of top earners. This is not true of all state income tax systems. For example, Delaware sliced the data by categories of 100$ and 500$ instead. Thus, we can more easily pinpoint the two. More importantly, most state-income tax systems reported the breakdown both for net taxable and gross income. This is crucial because Piketty and Saez need to adjust the pre-1943 IRS data – which are in net income – to that they can tie properly with the post-1943 IRS data – which are in adjusted gross income. Absent this correction, they would get an artificial increase in inequality in 1943. The problem is that the data for this adjustment is scant and their proposed solution has not been subjected to validation.

What do our data say? We compared them to the work of Mark Frank et al. who used the same methodology and Piketty Saez but at the state-level using the same sources. The image below pretty much sums it up! If the points are above the red line, the IRS data overestimates inequality. If below, the IRS underestimates. Overall, the bias tends towards overestimation. In fact, when we investigated all of the points separately, we found that those below the red line result merely from the way that Delaware’s (DE) was adjusted to convert net income into gross income. When we compared only net income-based measures of inequality, none are below the red line except Delaware from 1929 to 1931 (and by much smaller margins than shown in the figure below).

IRS.png

In our paper, we highlight how the state-level data is conceptually superior to the federal-level data. The problem that we face is that we cannot convert those measures into adjustments for the national level of inequality. All that our data do is suggest which way the bias cuts. While we find this unfortunate, we highlight that this would unavoidably alter the left side of the curve in the first graph of this blog post. The initial level of inequality would be less than it is now. Thus, combining this with the criticisms made for the post-1960 era, we may be in presence of a U-curve that looks more like a shallow tea saucer than the pronounced U-curve generally highlighted.  The U-curve form is not invalidated (i.e. is it a quadratic-looking function of time or not), but the shape of the curve’s tails is dramatically changed.

Nightcap

  1. Economics after neoliberalism (Hayek) Corey Robin, Boston Review
  2. Should some countries cease to exist? Branko Milanovic, globalinequality
  3. Consider reparations Robin Hanson, Overcoming Bias
  4. (Legal) immigration into the United States Jacques Delacroix, NOL

Asking questions about women in the academy

Doing the economist’s job well, Nobel Laureate Paul Romer once quipped, “means disagreeing openly when someone makes an assertion that seems wrong.”

Following this inspirational guideline of mine in the constrained, hostile, and fairly anti-intellectual environment that is Twitter sometimes goes astray. That the modern intellectual left is vicious we all know, even if it’s only through observing them from afar. Accidentally engaging with them over the last twenty-four hours provided some hands-on experience for which I’m not sure I’m grateful. Admittedly, most interactions on twitter loses all nuance and (un)intentionally inflammatory tweets spin off even more anger from the opposite tribe. However, this episode was still pretty interesting.

It started with Noah Smith’s shout-out for economic history. Instead of taking the win for our often neglected and ignored field, some twitterstorians objected to the small number of women scholars highlighted in Noah’s piece. Fair enough, Noah did neglect a number of top economic historians (many of them women) which any brief and incomprehensive overview of a field would do.

His omission raised a question I’ve been hooked on for a while: why are the authors of the most important publications in my subfields (financial history, banking history, central banking) almost exclusively male?

Maybe, I offered tongue-in-cheek in the exaggerated language of Twitter, because the contribution of women aren’t good enough…?

Being the twenty-first century – and Twitter – this obviously meant “women are inferior – he’s a heretic! GET HIM!”. And so it began: diversity is important in its own right; there are scholarly entry gates guarded by men; your judgment of what’s important is subjective, duped, and oppressive; what I happen to care about “is socially conditioned” and so cannot be trusted; indeed, there is no objectivity and all scholarly contribution are equally valuable.

Now, most of this is just standard postmodern relativism stuff that I couldn’t care less about (though, I am curious as to how it is that the acolytes of this religion came to their supreme knowledge of the world, given that all information and judgments are socially conditioned – the attentive reader recognises the revival of Historical Materialism here). But the “unequal” outcome is worthy of attention, and principally the issue of where to place the blame and to suggest remedies that might prove effective.

On a first-pass analysis we would ask about the sample. Is it really a reflection of gender oppression and sexist bias when the (top) outcome in a field does not conform to 50:50 gender ratios? Of course not. There are countless, perfectly reasonable explanations, from hangover from decades past (when that indeed was the case), the Greater Male Variability hypothesis, or that women – for whatever reason – have been disproportionately interested in some fields rather than others, leaving those others to be annoyingly male.

  • If we believe that revolutionising and top academic contributions have a long production line – meaning that today’s composition of academics is determined by the composition of bright students, say, 30-40 years ago – we should not be surprised that the top-5% (or 10% or whatever) of current academic output is predominantly male. Indeed, there have been many more of them, for longer periods of time: chances are they would have managed to produce the best work.
  • If we believe the Greater Male Variability hypothesis we can model even a perfectly unbiased and equal opportunity setting between men and women and still end up with the top contribution belonging to men. If higher-value research requires smarter people working harder, and both of those characteristics are distributed unequally between the sexes (as the Greater Male Variability hypothesis suggests), then it follows naturally that most top contributions would be men.
  • In an extension of the insight above, it may be the case that women – for entirely non-malevolent reasons – have interests that diverge from men’s (establishing precise reasons would be a task for psychology and evolutionary biology, for which I’m highly unqualified). Indeed, this is the entire foundation on which the value of diversity is argued: women (or other identity groups) have different enriching experiences, approach problems differently and can thus uncover research nobody thought to look at. If this is true, then why would we expect that superpower to be applied equally across all fields simultaneously? No, indeed, we’d expect to see some fields or some regions or some parts of society dominated by women before others, leaving other fields to be overwhelmingly male. Indeed, any society that values individual choice will unavoidably see differences in participation rates, academic outcomes and performance for precisely such individual-choice reasons.

Note that none of this excludes the possibility of spiteful sexist oppression, but it means judging academic participation on the basis of surveys responses or that only 2 out of 11 economic historians cited in an op-ed were women, may be premature judgments indeed.

In Defense of Not Having a Clue

Timely, both in our post-truth world and for my current thinking, Bobby Duffy of the British polling company IPSOS Mori recently released The Perils of Perception, stealing the subtitle I have (humbly enough) planned for years: Why We’re Wrong About Nearly Everything. Duffy and IPSOS’s Perils of Perception surveys are hardly unknown for an informed audience, but the book’s collection and succint summary of the psychological literature behind our astonishingly uninformed opinions, nevertheless provide much food for thought.

Producing reactions of chuckles, indignation, anger, and unseeming self-indulgent pride, Duffy takes me on a journey of the sometimes unbelievably large divergence between the state of the world and our polled beliefs about the world. And we’re not primarily talking about unobservable things like “values” here; we’re almost always talking about objective, uncontroversial measures of things we keep pretty good track of: wealth inequality, share of immigrants in society, medically defined obesity, number of Facebook accounts, murder and unemployment rates. On subject after subject, people guess the most outlandish things: almost 80% of Britons believed that the number of deaths from terrorist attacks between 2002 and 2016 were more or about the same as 1985-2000, when the actual number was a reduction of 81% (p. 131); Argentinians and Brazilians seem to believe that roughly a third and a quarter of their population, respectivelly, are foreign-born, when the actual numbers are low single-digits (p. 97); American and British men believe that American and British women aged 18-29 have had sex as many as 23 times in the last month, when the real (admittedly self-reported) number is something like 5 times (p. 57).

We can keep adding astonishing misperceptions all day: Americans believe that more than every third person aged 25-34 live with their parents (reality: 12%), but Britons are even worse, guessing almost half (43%) of this age bracket, when reality is something like 14%; Australians on average believe that 32% of their population has diabetes (reality more like 5%) and Germans (31% vs 7%), Italians (35% vs 5%), Indians (47% vs 9%) and Britons (27% vs 5%) are similarly mistaken.

The most fascinating cognitive misconception is Britain’s infected relationship with inequality. Admittedly a confusing topic, where even top-economists get their statistical analyses wrong, inequality makes more than just the British public go bananas. When asked how large a share of British household wealth is owned by the top-1% (p. 90), Britons on average answered 59% when the reality is 23% (with French and Australian respondents similarly deluded: 56% against 23% for France and 54% against 21% for Australia). The follow-up question is even more remarkable: asked what the distribution should be, the average response is in the low-20s, which, for most European countries, is where it actually is. In France, ironically enough given its current tax riots, the respondents’ reported ideal household wealth proportion owned by the top-1% is higher than it already is (27% vs 23%). Rather than favoring upward redistribution, Duffy draws the correct conclusion:

“we need to know what people think the current situation is before we ask them what they think it should be […] not knowing how wrong we are about realities can lead us to very wrong conclusions about what we should do.” (p. 93)

Another one of my favorite results is the guesses for how prevalent teen pregnancies are in various countries. All of the 37 listed countries (p. 60) report numbers around less than 3% (except South Africa and noticeable Latin American and South-East Asian outliers at 4-6%), but respondents on average quote absolutely insane numbers: Brazil (48%), South Africa (44%) Japan (27%), US (24%), UK (19%).

Note that there are many ways to trick people in surveys and report statistics unfaithfully and if you don’t believe my or Duffy’s account of the IPSOS data, go figure it out for yourself. Regardless, is the take-away lesson from the imagine presented really that people are monumentally stupid? Ignorant in the literal sense of the world (“uninstructed, untututored, untaught”), or even worse than ignorant, having systematically and unidirectionally mistaken ideas about the world?

Let me confess to one very ironic reaction while reading the book, before arguing that it’s really not the correct conclusion.

Throughout reading Duffy’s entertaining work, learning about one extraordinarily silly response after another, the purring of my self-indulgent pride and anger at others’ stupidity gradually increased. Glad that, if nothing else, that I’m not as stupid as these people (and I’m not: I consistently do fairly well on most questions – at least for the countries I have some insight into: Sweden, UK, USA, Australia) all I wanna do is slap them in the face with the truth, in a reaction not unlike the fact-checking initiatives and fact-providing journalists, editorial pages, magazines, and pundits after the Trump and Brexit votes. As intuitively seems the case when people neither grasp nor have access to basic information – objective, undeniable facts, if you wish – a solution might be to bash them in the head or shower them with avalanches of data. Mixed metaphors aside, couldn’t we simply provide what seems to be rather statistically challenged and uninformed people with some extra data, force them to read, watch, and learn – hoping that in the process they will update their beliefs?

Frustratingly enough, the very same research that indicate’s peoples inability to understand reality also suggests that attempts of presenting them with contrary evidence run into what psychologists have aptly named ‘The Backfire Effect’. Like all force-feeding, forcing facts down the throats of factually resistent ignoramuses makes them double down on their convictions. My desire to cure them of their systematic ignorance is more likely to see them enshrine their erroneous beliefs further.

Then I realize my mistake: this is my field. Or at least a core interest of the field that is my professional career. It would be strange if I didn’t have a fairly informed idea about what I spend most waking hours studying. But the people polled by IPSOS are not economists, statisticians or data-savvy political scientists – a tenth of them can’t even do elementary percent (p. 74) – they’re regular blokes and gals whose interest, knowledge and brainpower is focused on quite different things. If IPSOS had polled me on Premier League results, NBA records, chords or tunes in well-known music, chemical components of a regular pen or even how to effectively iron my shirt, my responses would be equally dumbfunded.

Now, here’s the difference and why it matters: the respondents of the above data are routinely required to have an opinion on things they evidently know less-than-nothing about. I’m not. They’re asked to vote for a government, assess its policies, form a political opinion based on what they (mis)perceive the world to be, make decisions on their pension plans or daily purchases. And, quite a lot of them are poorly equipped to do that.

Conversely, I’m poorly equipped to repair literally anything, work a machine, run a home or apply my clumsy hands to any kind of creative or artful endeavour. Luckily for me, the world rarely requires me to. Division of Labor works.

What’s so hard with accepting absence of knowledge? I literally know nothing about God’s plans, how my screen is lit up, my car propels me forward or where to get food at 2 a.m. in Shanghai. What’s so wrong with extending the respectable position of “I don’t have a clue” to areas where you’re habitually expected to have a clue (politics, philosophy, virtues of immigration, economics)?

Note that this is not a value judgment that the knowledge and understanding of some fields are more important than others, but a charge against the societal institutions that (unnaturally) forces us to. Why do I need a position on immigration? Why am I required (or “entitled”, if you believe it’s a useful duty) to select a government, passing laws and dealing with questions I’m thoroughly unequipped to answer? Why ought I have a halfway reasonable idea about what team is likely to win next year’s Superbowl, Eurovision, or Miss USA?

Books like Duffy’s (Or Rosling’s, or Norberg‘s or Pinkers) are important, educational and entertaining to-a-t for someone like me. But we should remember that the implicit premium they place on certain kinds of knowledge (statistics and numerical memory, economics, history) are useful in very selected areas of life – and rightly so. I have no knowledge of art, literature, construction, sports, chemistry or aptness to repair or make a single thing. Why should I have?

Similarly, there ought to be no reason for the Average Joe to know the extent of diabetes, immigration or wealth inequality in his country.

Nightcap

  1. African soldiers (excellent film review) Jeremy Harding, London Review of Books
  2. Not born in the USA Irfan Khawaja, Policy of Truth
  3. Iraq’s Kurds versus Turkey’s Kurds Mahmut Bozarslan, Al-Monitor
  4. Branko Milanovic’s confusion on inequality David Henderson, EconLog

Nightcap

  1. Why the left needs “bottom” Chris Dillow, Stumbling & Mumbling
  2. How Adam Smith proposed to have his cake and eat it too Branko Milanovic, globalinequality
  3. Can relationship anarchy create a world without heartbreak? Sophie Hemery, Aeon
  4. The Lies We Were Told Simon Wren-Lewis, Mainly Macro

Legal Immigration Into the United States (Part 8): Culture, Immigration, and Culture

Immigrants, Language and Income

The culture of their country of origin immigrants carry with them may have consequences for the speed of their integration and for their ability to assimilate. In turn, immigrants may cause a variety of changes in American culture. Language is central to both types of cultural effects.

Current immigrants frequently have inferior earning capabilities because they are less educated on the average than are the native born. This is not the only disability they bring with them. Often, usually, their command of the English language is limited. This linguistic deficiency has consequences beyond the economic sphere. The continued poverty language incompetence fosters also retards their assimilation.

Many on the right declare themselves concerned with immigrants’ eroding influence on wages. Most of us are interested in the speed with which immigrants assimilate. Both phenomena depend to a large extent on immigrants’ competence in the English language. Linguistic competence influences the ease and speed of immigrants’ assimilation in the long run. In the short and middle run, it’s a direct determinant of income. Immigrants vary widely on a continuum of this crucial variable, from a superior command English, to no English at all.

The English language is special. Much of the world has English as a first language or as normal language of instruction in schools. A second tier includes English as a second language in its schools or, more often, in some of its schools. English is the first second language in the world. Middle class people everywhere learn English. In many countries though most people have no systematic interaction with the English language. The disadvantages of not knowing the common language of the country where one lives are so great that it’s a sort of miracle that so many even try to ignore those by moving to the US equipped with no knowledge of English. It makes sense then mentally to divide immigrants into the US in two broad categories according to their mastery of English as they land.

Silicon Valley is teeming with prosperous Indians, many of whom are actual immigrants. (There is a kind of optical illusions at work here though: Many Indians are on temporary, H-1B and F-1 visas. Indian immigrants who are not successful just go home, soon to be replaced by others. They leave little trace.) The Indian real immigrants can themselves be subdivided in two economic classes. Some spread all over the US where they utilize family connections to manage hotels and retail businesses. The Indians in Silicon Valley belong largely to another breed. Almost all are graduates from two dozen elite Indian engineering and management schools of higher learning. They are solidly middle class by upbringing although many arrive poor because of the steep income gradient between India and the US. My Indian wife – who knows I know not how, but who does know – assures me that all, or nearly all of the latter, belong to the lofty Brahman caste. (This is a case where class and caste correspond, far from a universal given.) They are people who could aspire to a good job back home in India where, however, their economic futures and their horizons would remain limited because India keeps being India. They all seem to arrive, amazingly, with a strong work ethic and with excellent work habits.

I think I taught between 200 and 300 Indian immigrants in my MBA career. Not one contradicted this generalization. Of course, this is not a generalization about Indians, but about the self-selected subgroup of Indians that shows up in central and northern California after having been admitted to and survived gruelingly selective schools back home. A couple who self-designated to me, their MBA instructor, as “lazy” would have been considered veritable Heroes of Labor in the old Soviet Union.

All the Indians from this second group are educated in English from an early age. They are used, via reading, movies and the internet, to American English (and to American culture) before they land. Outwardly, their adaptation is seamless. Digression: Except possibly that they may suffer a high rate of failed marriages. They engage in arranged marriages in India, bring their brides to America. Here, the young brides, utterly deprived of the usual Indian female support network and also, I am guessing, with a lesser mastery of English, become terribly unhappy. For this reason alone, I am guessing that Indian immigrants are less well-adjusted overall than are Mexicans who tend to bring everyone who matters with them. This is just a plausible redundant impression I gathered over 25 years. I have no figures in support.

These educated Indians obtain good jobs and they work diligently and intelligently. They are able to progress at work in good part because they express themselves with a clarity seldom achieved by other kinds of immigrants. (This, in spite of some peculiarities of Indian English: “You will go there, is it?”) They are thrifty at first, helped by the shock of finding out that a pound of lentils costs three times more in San Jose than in Kolkatta (personal research – an email to my sister-in-law there). So, they achieve a modest level of prosperity in a relatively short few years. The quick emergence of Indians in other walks of American life unconnected to high technology or to business, including medicine, the law and even journalism, testifies anew to those widespread virtues but all of this success would hardly be possible absent initial fluency in English.

Immigrants of many other different origins also make their way to Silicon Valley in response to the constant demand for high-tech specialists. The Chinese among them are numerous and conspicuous. I had them in my MBA classes for twenty-five years, right alongside the Indians. They gave me the impression of being about as excellently trained as the Indians. My intuition suggests that they were more entrepreneurial, on the whole, or maybe just more individualistic, but they nearly all struggled with English. (“Nearly;” one young Chinese woman had the cheek to correct my mistakes of syntax in class on several occasions.) If your native language does not use verb forms to distinguish between present and past, you can learn to say, “I did it,” instead of “I do it yesterday,” but it must be like a herd of potholes on the road you are traveling.

I suspect that many of the young Chinese immigrants I knew, star students back home, lived lives of frustration in the US because of the language barrier. The frustration runs deeper than a relative inability to get things done. (Though the latter counts too. I can mention it  now because there is probably a statute of limitation: Forty-plus years ago, I wrote a Chinese student’s entire doctoral dissertation; it was very good both in content and in form. Also, the student cooked well.) If you express yourself at the level of a native-born ten-year-old, the unsophisticated foreign language virginal natives treat you like a fairly-gifted ten-year-old. This is pretty conjectural, of course. I would bet on it though! I have discussed this several times over steamed mussels with some favorite Chinese students with whom I had picked and prepared the shellfish; they had no reason to lie to me, not then, anyway.

It’s difficult to generalize about the few visually inconspicuous Europeans who also make it to Silicon Valley. Those who attended my classes were as competent in English as foreigners for whom it is a second language can be. I am guessing they were competent enough to be engineers. For some reason, Russians shone among them. Reminder: I am not indulging here in a devious comparative survey of different national educational systems. Immigration to America dips into different pools in different countries. Perhaps, smart Russians always go to America if they can while equally smart French engineers would rather stay home to continue their leisurely dégustation of blanquette de veau façon Normande.

It’s certain that mastery of English plays a big part in determining immigrants’ incomes as well as their economic contributions to American society. It’s also easy to miss the competence and the high character of those who don’t understand English well. And, as I have said, nothing sounds more like a ten-year-old than a bright foreigner whose English is struggling to reach the second grade level. With a low competence in English, even if it be only spoken English, the best jobs elude you although you would be capable of performing them, language notwithstanding. I believe that millions of immigrants are employed much below their maximum earning capacity solely because of their low linguistic competence. So, while the actual economic contribution of those immigrants is correctly assessed as low, their potential contribution is systematically underrated. This is a problem capable of solutions that are rarely discussed. A merit-based system would easily incorporate such solutions. So would a system of conditional admission linked to progress in English.

Anecdote: About twenty years ago, there was a tacit agreement among Anglo employers of casual Mexican labor that Mexicans were hard working and knew how to follow simple orders, but that was it. They were automatically treated as unskilled labor. Myself, with my good Spanish, I never had any trouble finding a tile layer, a carpenter, even an electrician among the day laborers gathering outside Home Depot every morning. The specialized workers I located were not slow to point out that the work I requested was skilled work and must be paid accordingly.

We must thus remember that linguistic disability must keep the wages of non-English speaking immigrants lower than they would otherwise be at a given level of occupational competence and personal ability. Language incompetence must thus also contribute to lower prices although at some cost to productivity.  (Yes, here is the paradox: Each produces little but there are many of them. In the end, we pay less than if they were not here.) The situation of Mexican immigrant entrepreneurs, specifically, tests this idea. Entrepreneurs need to possess at least a fair command of English, if nothing else, to round up customers. The language disability is thus removed or lessened in their case, allowing for a more straight comparison of income with Anglos. It seems to me that immigrant contractors do not bid especially low, or not much lower than their Anglo counterparts. At least, when you ask for bids on a previously described job, you couldn’t guess by bid amounts who is a Hispanic immigrant. It may also be thought that such immigrants  provide a better quality/cost ratio. I don’t know if this intuitive idea, based largely on my private experience, has been examined rigorously anywhere. It’s backed by the likelihood that the self-selected immigrant group possesses some traits of character superior to those found among natural groups, including among members of the host population. I develop this idea in “Why Immigrants are Superior” (referenced elsewhere).

[Editor’s note: in case you missed it, here is Part 7]

Nightcap

  1. Watching a country make a fool of itself (Brexit) Jan Fleischhauer, der Spiegel
  2. Disarticulation goes north Branko Milanovic, globalinequality
  3. The Bosnians who speak medieval Spanish Susanna Zaraysky, BBC
  4. A depressing take on inequality Vincent Geloso, NOL

Nightcap

  1. One of 2018’s best essays about Putin’s Russia Cathy Young, Reason
  2. How the Left abandoned the working class Simon Wren-Lewis, mainly macro
  3. A new (old) political theory about the American Civil War Allen Guelzo, Claremont Review of Books
  4. A Danish Tolstoy? Morten Høi Jensen, New York Review of Books

Nightcap

  1. Radical republicans and early modern democrats, Dutch style Dirk Alkemade, Age of Revolutions
  2. Did socialism keep capitalism equal? Branko Milanovic, globalinequality
  3. John McCain in 1974 Arnold Isaacs, War on the Rocks
  4. U.S.-Soviet hotline a symbol of Cold War cooperation Rick Brownell, Historiat

Eye Candy: travel advice for Dutch citizens

NOL Dutch travel advice
Click here to zoom

Interesting map, for a few reasons. The United States is in green, which means there are “no special safety risks” to worry about. What I take this to mean is that as long as you stay out of, say, North Sacramento, or East Austin, when the sun goes down you’ll be safe.

The “pay attention, safety risks” label makes quite a big jump in my conceptual understanding of this map. What this warning means is that if you are particularly stupid, you won’t end up getting mugged and losing your wallet (like you would in green areas), you will instead end up losing your life or being kidnapped for ransom (or slavery).

This is quite a big jump, but it makes perfect sense, especially if you think about the jump in terms of inequality and, more abstractly, freedom.

The minimum wage induced spur of technological innovation ought not be praised

In a recent article at Reason.comChristian Britschgi argues that “Government-mandated price hikes do a lot of things. Spurring technological innovation is not one of them”. This is in response to the self-serve kiosks in fast-food restaurants that seem to have appeared everywhere following increases in the minimum wage.

In essence, his argument is that minimum wages do not induce technological innovation. That is an empirical question. I am willing to consider that this is not the most significant of adjustment margins to large changes in the minimum wage. The work of Andrew Seltzer on the minimum wage during the Great Depression in the United States suggests that at the very least it ought not be discarded.  Britschgi does not provide such evidence, he merely cites anecdotal pieces of support. Not that anecdotes are bad, but those that are cited come from the kiosk industry – hardly a neutral source.

That being said, this is not what makes me contentious towards the article. It is the implicit presupposition contained within: that technological innovation is good.

No, technological innovation is not necessarily good. Firms can use two inputs (capital and labor) and, given prices and return rates, there is an optimal allocation of both. If you change the relative prices of each, you change the optimal allocation. However, absent the regulated price change, the production decisions are optimal. With the regulated price change, the production decisions are the best available under the constraint of working within a suboptimal framework. Thus, you are inducing a rate of technological innovation which is too fast relative to the optimal rate.

You may think that this is a little luddite of me to say, but it is not. It is a complement to the idea that there are “skill-biased” technological change (See notably this article of Daron Acemoglu and this one by Bekman et al.). If the regulated wage change affects a particular segment of the labor (say the unskilled portions – e.g. those working in fast food restaurants), it changes the optimal quantity of that labor to hire. Sure, it bumps up demand for certain types of workers (e.g. machine designers and repairmen) but it is still suboptimal. One should not presuppose that ipso facto, technological change is good. What matters is the “optimal” rate of change. In this case, one can argue that the minimum wage (if pushed up too high) induces a rate of technological change that is too fast and will act in disfavor of unskilled workers.

As such, yes, the artificial spurring of technological change should not be deemed desirable!

On “strawmanning” some people and inequality

For some years now, I have been interested in the topic of inequality. One of the angles that I have pursued is a purely empirical one in which I attempt to improvement measurements. This angle has yielded two papers (one of which is still in progress while the other is still in want of a home) that reconsider the shape of the U-curve of income inequality in the United States since circa 1900.

The other angle that I have pursued is more theoretical and is a spawn of the work of Gordon Tullock on income redistribution. That line of research makes a simple point: there are some inequalities that are, in normative terms, worrisome while others are not. The income inequality stemming from the career choices of a benedictine monk and a hedge fund banker are not worrisome. The income inequality stemming from being a prisoner of one’s birth or from rent-seekers shaping rules in their favor is worrisome.  Moreover, some interventions meant to remedy inequalities might actually make things worse in the long-run (some articles even find that taxing income for the sake of redistribution may increase inequality if certain conditions are present – see here).  I have two articles on this (one forthcoming, the other already published) and a paper still in progress (with Rosolino Candela), but they are merely an extension of the aforementioned Gordon Tullock and some other economists like Randall Holcombe, William Watson and Vito Tanzi. After all, the point that a “first, do no harm” policy to inequality might be more productive is not novel (all that it needs is a deep exploration and a robust exposition).

Notice that there is an implicit assumption in this line of research: inequality is a topic worth studying. This is why I am annoyed by statements like those that Gabriel Zucman made to ProMarket. When asked if he was getting pushback for his research on inequality (which is novel and very important), Zucman answers the following:

Of course, yes. I get pushback, let’s say not as much on the substance oftentimes as on the approach. Some people in economics feel that economics should be only about efficiency, and that talking about distributional issues and inequality is not what economists should be doing, that it’s something that politicians should be doing.

This is “strawmanning“. There is no economist who thinks inequality is not a worthwhile topic. Literally none. True, economists may have waned in their interest towards the topic for some years but it never became a secondary topic. Major articles were published in major journals throughout the 1990s (which is often identified as a low point in the literature) – most of them groundbreaking enough to propel the topic forward a mere decade later. This should not be surprising given the heavy ideological and normative ramifications of studying inequality. The topic is so important to all social sciences that no one disregards it. As such, who are these “some people” that Zucman alludes too?

I assume that “some people” are strawmen substitutes for those who, while agreeing that inequality is an important topic, disagree with the policy prescriptions and the normative implications that Zucman draws from his work. The group most “hostile” to the arguments of Zucman (and others such as Piketty, Saez, Atkinson and Stiglitz) is the one that stems from the public choice tradition. Yet, economists in the public-choice tradition probably give distributional issues a more central role in their research than Zucman does. They care about institutional arrangements and the rules of the game in determining outcomes. The very concept of rent-seeking, so essential to public choice theory, relates to how distributional coalitions can emerge to shape the rules of the game in a way that redistribute wealth from X to Y in ways that are socially counterproductive. As such, rent-seeking is essentially a concept that relates to distributional issues in a way that is intimately related to efficiency.

The argument by Zucman to bolster his own claim is one of the reason why I am cynical towards the times we live in. It denotes a certain tribalism that demonizes the “other side” in order to avoid engaging in them. That tribalism, I believe (but I may be wrong), is more prevalent than in the not-so-distant past. Strawmanning only makes the problem worse.

The great global trend for the equality of well-being since 1900

Some years ago, I read The Improving State of the World: Why We’re Living Longer, Healthier, More Comfortable Lives on a Cleaner Planet by Indur Goklany. It was my first exposition to the claim that, globally, there has been a long-trend in the equality of well-being. The observation made by Goklany which had a dramatic effect on me was that many countries who were, at the time of his writing, as rich (incomes per capita) as Britain in 1850 had life expectancy and infant mortality levels well superior to 1850 Britain. Ever since, I accumulated the statistics on that regard and I often tell my students that when comes the time to “dispell” myths regarding the improvement in living standards since circa 1800 (note: people are generally unable to properly grasp the actual improvement in living standards).

Some years after, I discovered the work of Leandro Prados de la Escosura who is a cliometrician who (I think I told him that when I met him) influenced me deeply in my work regarding the measurement of living standards and who wrote this paper which I will discuss here.  His paper, and his work in general, shows that globally the inequality in incomes has faltered since the 1970s.  That is largely the result of the economic rise of India and China (the world’s two largest antipoverty programs). Figure1Leandro

However, when extending his measurements to include life expectancy and schooling in order to capture “human development” (the idea that development is not only about incomes but the ability to exercise agency – i.e. the acquisition of positive liberty), the collapse in “human development” inequality (i.e. well-being) precedes by many decades the reduction in global income inequality. Indeed, the collapse started around 1900, not 1970!

Figure2LEandro.png

In reading Leandro’s paper, I remembered the work of Goklany which had sowed the seeds of this idea in my idea. Nearly a decade after reading Goklany’s work well after I fully accepted this fact as valid, I remain stunned by its implications. You should too.

Nightcap

  1. The new age of great power politics John Bew, New Statesman
  2. Before We Cure Others of Their False Beliefs, We Must First Cure Our Own Christopher Preble, Cato Unbound
  3. Libertarians (FDP) ruin coalition talks in Germany Christian Hacke, Deutsche Welle
  4. The Rich You Will Always Have With You Brandon Turner, Law & Liberty