Economics – Page 17 – Difficult Run

Consumption Inequality: 1960-2014

August 8, 2017 by Walker

Image result for consumption gif — Consumption

Economists Bruce D. Meyer and James X. Sullivan have a brand new NBER paper on inequality; specifically consumption inequality. From the abstract:

Official income inequality statistics indicate a sharp rise in inequality over the past five decades. These statistics do not accurately reflect inequality because income is poorly measured, particularly in the tails of the distribution, and current income differs from permanent income, failing to capture the consumption paid for through borrowing and dissaving and the consumption of durables such as houses and cars. We examine income inequality between 1963 and 2014 using the Current Population Survey and consumption inequality between 1960 and 2014 using the Consumer Expenditure Survey. We construct improved measures of consumption, focusing on its well-measured components that are reported at a high and stable rate relative to national accounts. While overall income inequality (as measured by the 90/10 ratio) rose over the past five decades, the rise in overall consumption inequality was small. The patterns for the two measures differ by decade, and they moved in opposite directions after 2006. Income inequality rose in both the top and bottom halves of the distribution, but increases in consumption inequality are only evident in the top half. The differences are also concentrated in single parent families and single individuals. Although changing demographics can account for some of the changes in consumption inequality, they account for little of the changes in income inequality. Consumption smoothing cannot explain the differences between income and consumption at the very bottom, but the declining quality of income data can. Asset price changes likely account for some of the differences between the measures in recent years for the top half of the distribution.

Meyer and Sullivan have been updating their data over the years. As the 2013 version (which measures inequality from 1960 to 2011) concludes,

Consumption inequality is less pronounced than income inequality and changes in consumption inequality differ considerably from changes in income inequality. While income inequality falls in the 1960s, consumption inequality rises slightly. Both consumption and income indicate rising inequality during the 1980s, but the rise is more noticeably for income. Since the mid-2000s, income inequality has risen while consumption inequality has fallen. Over the past three decades, both income and consumption inequality have risen, but the rise is much more noticeable for income (45 percent) than for consumption (19 percent). Differences between income and consumption are also evident for different parts of the distribution. Income inequality in the top half of the distribution rose steadily between 1980 and 2011, while consumption inequality for the top half of the distribution rose between 1980 and 2005, but then fell noticeably. Although changing demographics can account for some of the changes in consumption inequality, they do not account for changes in income inequality.

Comparisons of survey data to administrative records and national income accounts data indicate under-reporting of both income and consumption. There is evidence of considerable under-reporting of government transfers in income surveys, and the extent of under-reporting has grown overtime. Such under-reporting could lead to significant bias in the level and pattern of income inequality. There is also evidence of under-reporting of consumption data, although major components of consumption such as food at home and housing are reported at a high and stable rate relative to aggregate data. The differences between income and consumption inequality changes through 2005 are almost exclusively in the bottom half of the distribution, indicating that the under-reporting of consumption by the rich is not an explanation for the differences (pg. 21).

To quote Tyler Cowen, “This is one big reason why you can believe income inequality is high and/or rising, and not see it as the most significant normative issue.”

The Effects of Immigrants: Miami Edition

April 6, 2018August 2, 2017 by Walker

Economist Michael Clemens has an excellent article in Vox discussing some of his most recent research on immigration and in turn responds to Harvard’s George Borjas, the most prominent anti-immigration economist around:

Do immigrants from poor countries hurt native workers? It’s a perpetual question for policymakers and politicians. That the answer is a resounding “Yes!” was a central assertion of Donald Trump’s presidential campaign. When a study by an economist at Harvard University recently found that a famous influx of Cuban immigrants into Miami dramatically reduced the wages of native workers, immigration critics argued that the debate was settled.

…But there’s a problem. The study is controversial, and its finding — that the Cuban refugees caused a large, statistically unmistakable fall in Miami wages — may be simply spurious. This matters because what happened in Miami is the one historical event that has most shaped how economists view immigration.

In his article, Borjas claimed to debunk an earlier study by another eminent economist, David Card, of UC Berkeley, analyzing the arrival of the Cubans in Miami. The episode offers a textbook case of how different economists can reach sharply conflicting conclusions from exactly the same data.

Yet this is not an “on the one hand, on the other” story: My own analysis suggests that Borjas has not proved his case. Spend a few minutes digging into the data with me, and it will become apparent that the data simply does not allow us to conclude that those Cubans caused a fall in Miami wages, even for low-skill workers.

An influential 1990 study found “no difference in wage or employment trends between Miami — which had just been flooded with new low-skill workers — and other cities” following the arrival of 125,000 Cuban immigrants.

Two new studies reexamined the 1990 study. “Borjas, instead, focuses on workers who did not finish high school — and claimed that the Boatlift caused the wages of those workers, those truly at the bottom of the ladder, to collapse. The other new study (ungated here), by economists Giovanni Peri and Vasil Yasenov, of the UC Davis and UC Berkeley, reconfirms Card’s original result: It cannot detect an effect of the boatlift on Miami wages, even among workers who did not finish high school.” Clemens suggests looking at

certain subgroups that may have competed more directly with the newly-arrived Cubans. For example, the Mariel migrants were mostly men. They were Hispanic. Many of them were prime-age workers (age 25 to 59). So we should look separately at what happened to wages for each of those groups of low-skill workers who might compete with the immigrants more directly: men only, non-Cuban Hispanics only, prime-age workers only…Here again, if anything, wages rose for each of these groups of low-skill workers after 1980, relative to their previous trend. There isn’t any dip in wages to explain. And, again, the same is true if you compare wage trends in Miami to trends in other, similar cities. Peri and Yasenov showed that there is still no dip in wages even when you divide up low-skill workers by whether or not they finished high school. About half of the Mariel migrants had finished high school, and the other half hadn’t. So you might expect negative wage effects on both groups of workers in Miami. Here is what the wage trends look like for those two groups.

The wages of Miami workers with high school degrees (and no more than that) jump up right after the Mariel boatlift, relative to prior trends. The wages of those with less than a high school education appear to dip slightly, for a couple of years, although this is barely distinguishable amid the statistical noise. And these same inflation-adjusted wages were also falling in many other cities that didn’t receive a wave of immigrants, so it’s not possible to say with statistical confidence whether that brief dip on the right is real. It might have been — but economists can’t be sure. The rise on the left, in contrast, is certainly statistically significant, even relative to corresponding wage trends in other cities.

So how did Borjas come to different conclusions? He “starts with the full sample of workers of high school or less — then removes women, and Hispanics, and workers who aren’t prime age (that is, he tosses out those who are 19 to 24, and 60 to 65). And then he removes workers who have a high school degree. In all, that means throwing out the data for 91 percent of low-skill workers in Miami in the years where Borjas finds the largest wage effect. It leaves a tiny sample, just 17 workers per year.” Borjas’ conclusions involve a lot of statistical noise and, as Clemens notes, “if we’re willing to take low-skill workers in Miami and hand-pick small subsets of them, we can always find small groups of workers whose wages rose during a particular period, and other groups whose wages fell. But at some point we’re learning more about statistical artifacts than about real-world events.”

But there is another factor at work:

it turns out that the CPS sample includes vastly more black workers in the data used for the Borjas study after the boatlift than before it.

Because black men earned less than others, this change would necessarily have the effect of exaggerating the wage decline measured by Borjas. The change in the black fraction of the sample is too big and long-lasting to be explained by random error. (This is my own contribution to the debate. I explore this problem in a new research paper that I co-authored with Jennifer Hunt, a professor of economics at Rutgers University.)

Around 1980, the same time as the Boatlift, two things happened that would bring a lot more low-wage black men into the survey samples. First, there was a simultaneous arrival of large numbers of very low-income immigrants from Haiti without high school degrees: that is, non-Hispanic black men who earn much less than US black workers but cannot be distinguished from US black workers in the survey data. Nearly all hadn’t finished high school.

That meant not just that Miami suddenly had far more black men with less than high school after 1980, but also that those black men had much lower earnings. Second, the Census Bureau, which ran the CPS surveys, improved its survey methods around 1980 to cover more low-skill black men due to political pressure after research revealed that many low-income black men simply weren’t being counted.

You can see what happened in the graph below, which has a point for each year’s group of non-Hispanic men with less than high school, in the data used by Borjas (ages 25 to 59). The horizontal axis is the fraction of the men in the sample who are black. The vertical axis is the average wage in the sample. Because black men in Miami at this skill level earned much less than non-blacks, it’s no surprise that the more black men are covered by each year’s sample, the lower the average wage.

But here’s the critical problem: The fraction of black workers in this sample increased dramatically between the years just before the boatlift (in red) and the years just after the boatlift (in blue). That demographic shift would make the average wage in this group appear to fall right after the boatlift, even if no one’s wages actually changed in any subpopulation. What changed was who was included in the sample.

“When the statistical results in the Borjas study are adjusted to allow for changing black composition of the sample in each city,” Clemens continues, “the result becomes fragile. In the dataset Borjas focuses on, the result suddenly depends on which set of cities one chooses to compare Miami to. And in the other, larger CPS dataset that covers the same period, there is no longer a statistically significant dip in wages at all.” And once “you’ve discarded women, and Hispanics, and workers under 25, and workers over 59, and anyone who finished high school— and blacks, you’ve thrown away 98 percent of the data on low-skill workers in Miami. There are only four people left in each year’s survey, on average, during the years that the Borjas study finds the largest effect. With samples that small, the statistical confidence interval (represented by the dotted lines) is huge, meaning we can’t infer anything general from the results. We can’t distinguish large declines in wages from large rises in wages — at least until several years after the boatlift happened, and those can’t be plausibly attributed to the boatlift.”

In conclusion, “[t]here is no clear evidence that wages fell (or that unemployment rose) among the least-skilled workers in Miami, even after a sudden refugee wave sharply raised the size of that workforce. This does not by any means imply that large waves of low-skill immigration could not displace any native workers, especially in the short term, in other times and places. But politicians’ pronouncements that immigrants necessarily do harm native workers must grapple with the evidence from real-world experiences to the contrary.”

Persuasion in the Economy

September 28, 2017July 19, 2017 by Walker

Over 20 years ago, economists Deirdre (then Donald) McCloskey and Arjo Klamer argued that a quarter of GDP is due to “persuasion”: the sweet talk that is inherent in economic activity and transactions. A 2013 report by the Australian Treasury updates their findings and concludes that 30% of U.S. GDP is persuasion:

Chart 1 displays the steady rise of persuasion content in US employment. To focus on the biggest grouping — those having a persuasion content of three-quarters — in 1983, they accounted for 19.7 per cent of total employment and grew by two percentage points to 21.8 per cent by 1993. And again, from 22.1 per cent in 2003 the proportion of these workers increased to 22.3 per cent in 2009. Overall persuasion employment appears to have settled at around the 30 per cent mark.

How much of national output is attributable to persuasion? McCloskey and Klamer derive an estimate through the production measure of GDP: the ‘more obviously “talkie” parts of production are a large part of production for final consumption, and much of it is persuasion rather than information or command’. And since these ‘talkie’ parts, such as wholesale and retail trade, finance and general government, add up to 58 per cent of US GDP in 1991, they conjecture that ‘it would not be hard to see … a figure of about a quarter (of GDP) devoted to persuasion’ (p. 193).

An alternative guess could be made from the income side of the national accounts — GDP(I). Since the persuasion content of employment is 30 per cent and the proportion of national income accruing to labour is around 60 per cent in the US (Jacobson and Occhino (2012)), that gives the labour income component of persuasion in the national accounts of around 18 per cent. If a fifth to one-quarter of capital income represents persuasive activity, that accounts for another 8-10 per cent (that is 20-25 per cent x (1-0.6)) of persuasion in GDP(I).⁷ The digital economy’s rapid advance has meant that brand names, commercial trademarks and other intellectual property are playing a bigger role in economic transactions and by their nature may not be well reflected in the national accounts. Therefore it is quite possible that the persuasion content of GDP may now be closer to 30 per cent.

While it is likely that persuasion GDP has risen above one quarter, it also bears entertaining the possibility that some of that effort could be dissipated by economic contests and positioning à la Skaperdas and Vaidya (2009).

The report concludes,

Since the inspired guesstimate of McCloskey and Klamer, the economics profession launched itself into modelling many aspects of persuasion. Insights are to be had for sure, particularly in how regulators might mandate minimum product or service disclosure standards or how persuasion is deployed in economic contests. There might even be lessons as to how to communicate difficult economic reform proposals and how to navigate tricky political economy landscapes.

But as McCloskey (2011) suggests, some research effort may be falling back into the trap of treating persuasion as just another factor in formal optimisation exercises. In that sense, McCloskey and Klamer’s (1995) original hope remains unrealised. They had hoped that a renewed awareness of the importance of persuasion might encourage the modern economist to augment her technical tools of trade by taking seriously the potential of language in economic discourse and by utilising the power of interpretation in distinguishing between competing ‘hard results’. In this way, McCloskey’s agenda goes beyond evidence-based policy evaluations, useful and necessary as they are in policy discourse.

On a positive note, might it be time to update the McCloskey-Klamer catch phrase to ’30 per cent of GDP is persuasion’? Such renewed speculation would of course merely inform because the persuading was eloquently done by McCloskey and Klamer.

Humane Liberalism

July 18, 2017 by Walker

Related image As mentioned before, the newest issue of Dialogue was just released. The first article of the new issue is Robert Rees’ “Reimagining the Restoration: Why Liberalism is the Ultimate Flowering of Mormonism.” Rees attempts to redeem the word from its current negative connotations in American society, reviewing its meaning in the Middle Ages to the Enlightenment. He further connects to Joseph Smith’s statement that God “is more liberal in His views, and boundless in His mercies and blessings, than we are ready to believe or receive” (pg. 4). Rees goes on to emphasize liberal commitments to earth stewardship, gender equality, the poor, peace, education, etc.

The article reminded me of a recent essay by economic historian Deirdre McCloskey titled “Manifesto for a New American Liberalism, or How to Be a Humane Libertarian.” As McCloskey notes, “Outside the United States libertarianism is still called plain “liberalism,” as in the usage of the president of France, Emmanuel Macron, with no “neo-” about it” (pg. 1). “Liberals 1.0 don’t like violence,” she continues. “They are friends of the voluntary market order, as against the policy-heavy feudal order or bureaucratic order or military-industrial order. They are, as Hayek declared, “the party of life, the party that favors free growth and spontaneous evolution,” against the various parties of left and right which wish “to impose [by violence] upon the world a preconceived rational pattern.” In McCloskey’s view, “humane liberals are very far from being against poor people. Nor are they ungenerous, or lacking in pity. Nor are they strictly pacifist, willing to surrender in the face of an invasion. But they believe that in achieving such goods as charity and security the polity should not turn carelessly to violence, at home or abroad, whether for leftish or rightish purposes, whether to help the poor or to police the world. We should depend chiefly on voluntary agreements, such as exchange-tested betterment, or treaties, or civil conversation, or the gift of grace, or a majority voting constrained by civil rights for the minority” (pg. 2). She explains,

Such a humane liberalism has for two centuries worked on the whole astonishingly well. For one thing it produced increasingly free people, which (we moderns think) is a great good in itself. Slaves, women, colonial people, gays, handicapped, and above all the poor, from which almost all of us come, have been increasingly allowed since 1776 to pursue their own projects consistent with not using physical violence to interfere with other people’s projects. As someone put it: In the eighteenth century kings had rights and women had none. Now it’s the other way around. And—quite surprisingly—the new liberalism, by inspiriting for the first time in history a great mass of ordinary people, produced a massive explosion of betterments.

…The Enrichment was, I say again in case you missed it, three thousand percent per person, near enough, utterly unprecedented. The goods and services available to even the poorest rose by that astounding figure, in a world in which mere doublings, increases of merely 100 percent, had been rare and temporary, as in the glory of fifth-century Greece or the vigor of the Song Dynasty. In every earlier case, the little industrial revolutions had reverted eventually to a real income per head in today’s prices of about $3 a day, which was the human condition since the caves. Consider trying to live on $3 a day, as many people worldwide still do (though during the past forty years their number has fallen like a stone). After 1800 there was no reversion. On the contrary, in every one of the forty or so recessions since 1800 the real income per head after a recession exceeded what it had been at the previous peak. Up, up, up. Even including the $3- a-day people in Chad and Zimbabwe, world real income per head has increased during the past two centuries by a factor of ten, and by a factor of thirty as I said, in the countries that were lucky, and liberally wise. Hong Kong. South Korea. Botswana. The material and cultural enrichment bids fair to spread now to the world.

And the enrichment has been equalizing. Nowadays in places like Japan and the United States the poorest make more, corrected for inflation, than did the top quarter or so two centuries ago (pgs. 4-5).

The whole thing is worth reading. Check it out.

The Long-Term Effects of the African Slave Trade

July 17, 2017 by Walker

According to economist Nathan Nunn, the African slave trade (unsurprisingly) had numerous negative long-term effects, economically, socially and culturally. He writes,

An empirical literature has emerged that aims to supplement these historical accounts with quantitative estimates of the long-run impact of Africa’s slave trades. The first paper that attempted to provide such estimates was Nunn (2008). In the study, I undertook an empirical test, with the following logic. If the slave trades are partly responsible for Africa’s current underdevelopment, then, looking across different parts of Africa, one should observe that the areas that are the poorest today should also be the areas from which the largest number of slaves were taken in the past.

To undertake this study, I had to first construct estimates of the number of slaves taken from each country in Africa during the slave trades (i.e. between 1400 and 1900).

These estimates were constructed by combining data on the number of slaves shipped from each African port or region with data from historical documents that reported the ethnicity of over 106,000 slaves taken from Africa. Figure 1 provides an image showing a typical page from these historical documents. The documents shown are slave manumission records from Zanzibar. Each row reports information for one slave, including his/her name, ethnicity, age, and so on.

After constructing the estimates and connecting these with measures of modern day economic development, I found that, indeed, the countries from which the most slaves had been taken (taking into account differences in country size) were today the poorest in Africa. This can be seen in Figure 2, which is taken from Nunn (2008). It shows the relationship between the number of slaves taken between 1400 and 1900 and average real per capita GDP measured in 2000. As the figure clearly shows, the relationship is extremely strong. Furthermore, the relationship remains robust when many other key determinants of economic development are taken into account…According to the estimates from Nunn (2008), if the slave trades had not occurred, then 72% of the average income gap between Africa and the rest of the world would not exist today, and 99% of the income gap between Africa and other developing countries would not exist. In other words, had the slave trades not occurred, Africa would not be the most underdeveloped region of the world and it would have a similar level of development to Latin America or Asia.

“In a series of studies,” Nunn continues,

Whatley and Gillezeau (2011) and Whatley (2014) combine slave shipping records with ethnographic data and estimate the relationship between slave shipments and institutional quality and ethnic diversity in the locations close to the ports of shipment. Their analysis, consistent with Nunn (2008) and Green (2013), indicates that the slave trades did result in greater ethnic fractionalisation. In addition, their analysis also shows that the slave trades resulted in a deterioration of local ethnic institutions, measured in the late pre-colonial period.

Another subsequent study, undertaken by Nunn and Wantchekon (2011) asks whether the slave trades resulted in a deterioration of trust…In our study, Wantchekon and I extended the data construction efforts in Nunn (2008) and constructed estimates of the number of slaves taken from each ethnic group in Africa (rather than country). The ethnicity level estimates are displayed visually in Figure 3. The analysis combined the ethnicity-level slave export estimates with fine-grained household survey data, which reports individuals’ trust of those around them, whether neighbours, relatives, local governments, co-ethnics, or those from other ethnicities. The study documented a strong negative relationship between the intensity of the slave trade among one’s ethnic ancestors and an individual’s trust in others today.

The study then attempted to distinguish between the two most likely channels through which the slave trades could have adversely affected trust. One is that the slave trades made individuals and their descendants inherently less trusting. That is, it created a culture of distrust. In the insecure environment of the slave trade, where it was common to experience the betrayal of others, even friends and family, greater distrust may have developed, which could persist over generations even after the end of the slave trade.

Another possibility is that the slave trades may have resulted in a long-term deterioration of legal and political institutions, which are then less able to enforce good behaviour among citizens, and as a result people trust each other less today.

The study undertook a number of different statistical tests to identify the presence and strength of the two channels. They found that each of the tests generated the same answer: both channels are present. The slave trades negatively affected domestic institutions and governance, which results in less trust today. In addition, the slave trade also directly reduced the extent to which individuals were inherently trusting of others. We also found that, quantitatively, the second channel is twice as large as the first channel.

Guess what? The slave trade likely boosted the practice of polygyny in West Africa:

This is due to the fact that it was primarily males who were captured and shipped to the Americas, resulting in a shortage of men and skewed sex ratios within many parts of Africa. Interestingly, Dalton and Leung (2014) found that there is no evidence of such an impact for the Indian Ocean slave trade, where there was not a strong preference for male slaves. This has led the authors to conclude that Africa’s history of the slave trades is the primary explanation for why today polygyny is much more prevalent in West Africa than in East Africa.

Nunn concludes,

Although research understanding the long-term impacts of Africa’s slave trades is still in progress, the evidence accumulated up to this point suggests that this historic event played an important part in the shaping of the continent, in terms of not only economic outcomes, but cultural and social outcomes as well. The evidence suggests that it has affected a wide range of important outcomes, including economic prosperity, ethnic diversity, institutional quality, the prevalence of conflict, the prevalence of HIV, trust levels, female labour force participation rates, and the practice of polygyny. Thus, the slave trades appear to have played an important role in shaping the fabric of African society today.

GMO Yields

April 11, 2018July 14, 2017 by Walker

Image result for gmos

There’s a new paper out on genetically-engineered corn. Its results?:

This paper sought to identify whether, in fact, for corn “the nation-wide data . . . in the United States do not show a significant signature of genetic-engineering technology on the rate of yield increase,” as was indicated by NASEM (2016). Using corn yield panel data corresponding to roughly 28,000 U.S. county-years before and after adoption of GE corn, a simple model only including a time trend confirms NASEM’s assertion, as the effect of GE adoption appears, if anything, to have had a negative effect on yields. However, subsequent analysis reveals this simple model is biased. After controlling for weather and soil characteristics, and assuming a homogeneous effect of adoption, we find that adoption of GE corn has led to an approximate 17 percent increase in corn yields. We also find significant heterogeneity in the yield-effect that is not related to state-boundaries but rather to soil characteristics. On average, adoption of GE corn has led to an 18.5 bushel per acre increase in yield, but the effects range from 12.5 to 25.1 bushels per acre depending on soil characteristics. We conjecture that the variation across soil types may be related to differences in insect pressure.

While we found important soil-GE adoption interactions, there were no significant interactions related to weather. The findings suggest that the current GE traits have not led to more resilience to heat or water stresses. Moreover, while we find that the variance in corn yield has increased over time, adoption of GE corn has not lowered the variance. Nonetheless, if as our results show, adoption of GE corn increases yield without affecting variance, the coefficient of variation on yields has fallen as a result of GE corn adoption. This suggests GE corn is less risky as, for example, the actuarially fair price of insurance to indemnify a given yield falls as the coefficient of variation falls (pgs. 21-22).

So, once again, maybe we should calm down about GMOs.

American Revolution: Taxation and Representation?

July 12, 2017 by Walker

A week late, but what were some of the political economics behind the American Revolution? Here’s the abstract from a new working paper:

Why did the most prosperous colonies in the British Empire mount a rebellion? Even more puzzling, why didn’t the British agree to have American representation in Parliament and quickly settle the dispute peacefully? At first glance, it would appear that a deal could have been reached to share the costs of the global public goods provided by the Empire in exchange for political power and representation for the colonies. (At least, this was the view of men of the time such as Lord Chapman, Thomas Pownall and Adam Smith). We argue, however, that the incumbent government in Great Britain, controlled by the landed gentry, feared that allowing Americans to be represented in Parliament would undermine the position of the dominant coalition, strengthen the incipient democratic movement, and intensify social pressures for the reform of a political system based on land ownership. Since American elites could not credibly commit to refuse to form a coalition with the British opposition, the only realistic options were to maintain the original colonial status or fight a full-scale war of independence.

Happy belated July 4th!

Image result for fourth of july gif

Corporations, People, and Taxes

April 12, 2018July 8, 2017 by Walker

I was reviewing some old blog posts and such and came across the following. Remember this beautiful exchange?

Awww, yes. The “evil corporations” trope, i.e. the “confusion between abstract categories and flesh-and-blood human beings.”[ref]Thomas Sowell, Economic Facts and Fallacies, 2nd ed. (New York: Basic Books, 2011), 153.[/ref] Explaining the fallacious nature of this thinking, Thomas Sowell writes,

Abstract people can be aggregated into statistical categories such as households, families, and income brackets, without the slightest concern for whether those statistical categories contain similar people, or even the same number of people, or people who differ substantially in age, much less in such finer distinctions as whether or not they are working or whether they are the same people in the same categories over time. Abstract people have an immortality which flesh-and-blood people have yet to achieve.[ref]Thomas Sowell, Intellectuals and Society (New York: Basic Books, 2009), 112-113.[/ref]

What Romney’s hecklers (affiliates of Iowa Citizens for Community Improvement) and critics seem to have missed is the abstract nature of “greedy corporations.” The rhetoric invoked by these individuals often describes corporations as quasi-personal, transcendent entities that exist above and beyond flesh-and-blood people. As one writer notes, “Romney doesn’t mean that corporations are entitled to some of the legal rights of people in the Citizens United sense. He means it in the sense that the money made by corporations flows in and out of human hands—or pockets, in the language of the heckler who hoisted himself on his own metaphorical petard.” The abstractions of “corporations” and “the rich” are frequently linked, if not synonymous. Yet, empirical evidence suggests that corporate taxes negatively impact actual people. And not the rich ones you would hope for.[ref]See Matthew H. Jensen, Aparna Mathur, “Corporate Tax Burden on Labor: Theory and Evidence,” Tax Notes (June 6, 2011) for a nice rundown of the literature.[/ref]

A 2010 working paper explored international tax rates and manufacturing wages across 65 countries over 25 years. It suggests that a 1 percent increase in corporate tax rates decreases wage rates by 0.5-0.6 percent. “These results also hold for effective marginal and average tax rates” (pg. 22). A 2012 study[ref]Ungated working paper version here.[/ref] looked at over 55,000 companies in 9 European countries between 1996 and 2003. It found that every $1 increase in tax liability leads to a $0.49 decline in wages. This suggests that about 50% of the increased tax burden is passed on to the labor force over the long run. A 2007 Kansas City Fed working paper used cross-country data between 1979 and 2002 to find that a 1 percentage point increase in the average corporate tax rate led to a 0.7% decrease in annual gross wages; a decrease that was more than 4 times the amount of the corporate tax revenue collected. Furthermore, the “burden of the corporate tax on wages is shared equally across skill-level, suggesting that the corporate tax may not be as progressive as many politicians assume. Also, as the economy becomes more global, raising the corporate tax may result in lower than predicted corporate revenue increases due to the ability of firms to avoid taxes more effectively” (pg. 22). Another 2007 paper looked at a panel of U.S. multinationals across 50 countries over a 15-year period. The authors found that 45-75% of the corporate tax is shouldered by labor, with the rest falling on capital. Similarly, a 2013 study finds that a $1 increase in corporate tax liability leads to decreases in wages by about $0.60. The authors conclude,

Our findings suggest that labor shares a significant part of the burden of corporate income taxes. A direct calculation of the mean marginal effect of the corporate income tax from our estimates suggests that a 10 percent increase in the tax rate would decrease the average wage rate by 0.28–0.38 percent. Labor shares at least 42 percent of the burden of the corporate tax and possibly more. The average labor share of the corporate tax burden is around 60–80 percent (pg. 233).

A 2016 study[ref]Earlier, ungated version here.[/ref] of state corporate tax rates concluded that 25-30% fell on landowners and 30-35% fell on workers. A 2016 paper for the Federal Reserve looked at 131 tax increases and 140 tax cuts across 45 states going back to 1969. It found that “a one percentage-point increase in the top marginal corporate income tax rate reduces employment by between 0.3% and 0.5% and income by between 0.3% and 0.6%, measured relative to neighboring counties on the other side of the state border. These estimates are remarkably stable: they remain essentially unchanged regardless of local characteristics such as the flexibility of local labor markets, income levels, population density, or the prevalence of small businesses in a county. They are also stable across the business cycle and little changed when we control for localized industry-level shocks by comparing employment and income in bordering counties within the same industry” (pg. 3). A 2009 study by economist Robert Carroll found that across state lines “a one percent drop in the average tax rate leads to a 0.014 percent rise in real wages five years later.” In other words, wages rise $2.50 for every dollar reduction in the state-local corporate income taxes. The opposite also occurs: every dollar increase in tax rates leads to a $2.50 loss in wages. Drawing on recent research, Carroll suggests that “the least mobile factor of production is likely to bear the burden of a tax. In an increasingly global economy, labor is the least mobile because capital can flow freely across borders…When workers have more capital to work with, their labor productivity and wages will rise” (pg. 1). An abstraction is unable to pay its demanded “fair share” and instead places the economic burden on individuals. “After all, businesses are merely convenient ways of organizing economic activity,” writes Carroll, “so while businesses write checks to pay the corporate tax (and other taxes), the burden of those taxes falls ultimately on the individuals who depend on the corporations, in their roles as investors, workers, or consumers” (pg. 2). This is why Carroll finds numerous benefits to cutting corporate taxes, including higher long-term growth, higher wages and living standards, lowered tax burdens on low-income taxpayers and seniors, and boosted entrepreneurship, investment, and productivity.

The point of this review is to remind us that policy is complicated and often counterintuitive. We need to look at the empirical evidence. And if there isn’t much, perhaps we should wait until there is. The effects are real and they impact real people. The problem is that rarely will you achieve a utopian outcome. As I’m fond of saying, “There are no solutions; there are only trade-offs.”[ref]Sowell, The Vision of the Anointed: Self-Congratulation as a Basis for Social Policy(New York: Basic Books, 1995), 142.[/ref]

World Bank: Immigrants & Productivity

April 6, 2018July 7, 2017 by Walker

A new World Bank policy brief reviews the effects of immigrants on productivity:

For a sense of net effects –positive or negative, we looked at 22 primary studies. Explicit analysis on skilled versus unskilled immigrants is rare. So, most of the econometric results pertain to the effects of total immigrants. They remain instructive, given the overwhelming direction of migrant flows from less educated to more educated countries.

…In our RPB, broken down to the three components of labor productivity, positive effects from total immigrants are especially apparent through TFP. There is no statistically significant impact on physical capital per worker suggesting that capital accumulation need not be adversely affected. Human capital per worker is somewhat negatively affected, indicating that immigrants’ compositional effect on skills tends to outweigh the effect on natives’ skills upgrading. In the studies that analyze labor productivity alongside all its three components, positive immigrant effects on TFP more than offset the effects on physical capital and human capital per worker.

Outcomes vary across countries. Positive productivity effects from total immigrants are obvious for the U.S. – analysis using state-level data links task specialization of less-educated natives, induced by unskilled immigrant inflows, to TFP growth. Studies suggest that the complementarity and scale channels operate in Malaysia, but also that automation is somewhat hindered. Actual empirical evidence of net productivity effects seems mixed, and not representative enough of the economy as a whole, tending to focus on the manufacturing sector. In contrast, there is also the unique example of a large influx of skilled immigrants into Israel (fleeing the collapse of the Soviet Union) not having positive effects on productivity in the manufacturing sector.

More than anything, the cross-country evidence highlights that underlying the likelihood of positive net productivity effects is how immigrants link to specific gaps in the economy – regardless of skill level. And the response of agents, markets and institutions in host countries.

In fact, the report found that “on balance, total immigrant effects on labor productivity are statistically insignificant to positive” with “statistically significant positive effects” for total factor productivity (pg. 2). In short, “The economic case for an outright ban on unskilled immigrant workers is weak.”

And now I’ll leave you with the Hamilton Mixtape.

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