Tuesday, January 22, 2019

Some Economics of Foot-Binding

When I have thought of foot-binding in the past, which wasn't all that often, I've tended to view it as just one of those grim social practices, built on a mixture of social positioning and sexism, which disfigured the bodies of women. That's not wrong, but it's an oversimplification. Why did such a practice arise at one time, but not another time? Why did it end? Why did it differ across regions of China? Why feet? Xinyu Fan and Lingwei Wu give a fuller sense of context in "The Economic Motives for Foot-binding," a version of which was given at the meetings of the Allied Social Science Associations in Atlanta in early January. 

Here's a comment on how foot-binding was perceived in China (footnotes and citations omitted):
Originating from a female dancer in imperial palace during the Five Dynasties (907-960), foot-binding persisted for nearly a millennium in historical China. ... Foot-binding decisions by parents were made at girl’s early childhood (i.e. age 5 to 12), and marriage market matching took place in a later stage (i.e. 16-25). The bride’s family used the option to bind daughter’s feet to compete for better marriage opportunities and insure against downward mobility in the future. Regarding the value of foot-binding, men’s preference revealed it as a combination of appreciation of women’s beauty and virtue. For its aesthetic value, there exists a long-standing admiration of women’s small feet and elegant gait, traceable in Chinese poems and prose. In addition, foot-binding was also considered as carrying a “vector of status” , as a symbol of elegance, good breeding and a mark of status and virtue. Since foot-binding is a painful process for women to undertake, well-shaped and tiny bound feet also help to reveal their endurance, obedience and submissiveness. Taken together, as a package of beauty and women’s feminine virtue, foot-binding captured the key elements of men’s moral and aesthetic appreciation of women.
Fan and Wu point out that the foot-binding in China coincided with more widespread use of a national Civil Service Examination, which shook up the possibilities for social mobility in China. They write:
"Foot-binding is modeled as a premarital investment made by girls’ parents for marriage market competition. The heart of our theory is to relate such investment decisions with the dynamics of a gender-specific social mobility system – the Civil Examination System (in Chinese, the Keju, 607-1905). Briefly, the exam system triggered a transition from heredity aristocracy to meritocracy, under which system talented males could climb up the social ladder by passing exams while those who failed the exams would move downwards. As a consequence, the exams introduced greater social mobility, and resulted in a more heterogeneous composition of men compared to that of women on marital quality. This induced greater premarital investments by women for better marriage opportunities and against potential downward mobility. Foot-binding, as a package embodies both aesthetic and moral values of women, was adopted to differentiate themselves in the marriage market and served as a social ladder for women to climb up."
Foot-binding varied by region, and areas where physical mobility for women had greater economic value had less footbinding. 
Given that foot-binding deforms women’s feet, it sharply limits physical mobility thus precludes them from engaging in intensive non-sedentary activities, while having much less of an effect on sedentary activities such as household handicraft production. Therefore, among lower class women who played an active income-earning role, foot-binding prevalence exhibited regional variations driven by different agricultural regimes. In particular, foot-binding of lower class women was highly prevalent in regions where women specialized in sedentary labor (e.g. household handicraft), and less popular in regions requiring labor-intensive farmland work (e.g. rice cultivation). 
Footbinding ended early in the 20th century. Part of the reason was a government campaign against the practice. But economic forces were also at work. The national civil service examination ended in 1905, and educational and job opportunities for women were opening up.
Following the logic of the above model, we characterize the decline of foot-binding as the consequence of two forces: (1) the decreasing benefit of foot-binding in the marriage market, driven by equalization in gender-specific mobility; and (2) the increasing opportunity cost of foot-binding in the labor market. Regarding the first force, the exam system was abolished officially in 1905. During the Republican and following periods, girls had increasing educational, economic and social/public opportunities. The increasing equality of opportunities promoted gendersymmetric mobility, and women’s quality dispersion began to catch up with that of men. ... Another economic force driving women out of foot-binding was the modern industrialization process in textile. Combining data on local transportation, industrialization and economic development, Bossen and Gates (2017) demonstrated that the demise of foot-binding was closely related to the rise of textile industries that gradually replaced traditional household handicraft production, and some of them had to leave home to work in distant factories. Under these circumstances, foot-binding is no longer a desired tool to compete in the marriage market, as its benefits shrank while its opportunity cost increased. 

Monday, January 21, 2019

Some Economics for Martin Luther King Day

On November 2, 1983, President Ronald Reagan signed a law establishing a federal holiday for the birthday of Martin Luther King Jr., to be celebrated each year on the third Monday in January. As the legislation that passed Congress said: "such holiday should serve as a time for Americans to reflect on the principles of racial equality and nonviolent social change espoused by Martin Luther King, Jr.." Of course, the case for racial equality stands fundamentally upon principles of justice, not economics. But here are a few economics-related thoughts for the day clipped from 2018 posts at this blog, with more detail and commentary at the links:

1) "What Causes Inequality to Erupt Into Riots? Revisiting the Kerner Commission" (September 6, 2018)
"The Kerner report was the final report of a commission appointed by the U.S. President Lyndon B. Johnson on July 28, 1967, as a response to preceding and ongoing racial riots across many urban cities, including Los Angeles, Chicago, Detroit, and Newark. These riots largely took place in African American neighborhoods, then commonly called ghettos. On February 29, 1968, seven months after the commission was formed, it issued its final report. The report was an instant success, selling more than two million copies. ... The Kerner report documents 164 civil disorders that occurred in 128 cities across the forty-eight continental states and the District of Columbia in 1967 (1968, 65). Other reports indicate a total of 957 riots in 133 cities from 1963 until 1968, a particular explosion of violence following the assassination of King in April 1968 (Olzak 2015)."
The September 2018 issue of the Russell Sage Foundation Journal of the Social Sciences includes a 10-paper symposium from a range of social scientists concerning "The Fiftieth Anniversary of the Kerner Commission Report." The introductory essay by Susan T. Gooden and Samuel L. Myers Jr., "The Kerner Commission Report Fifty Years Later: Revisiting the American Dream" (pp. 1–17) does an excellent job of setting the historical context and contemporary reactions to the report, along with offering some comparisons that I at least had not seen before how hard it is to explain why some cities experienced riots and others did not.

The opening paragraph above is quoted from the Gooden/Myers paper. As they point out, perhaps the most commonly repeated comment from the report was that it baldly named white racism as an underlying cause. They quote the Kerner report: “What white Americans have never fully understood—but what the Negro can never forget—is that white society is deeply implicated in the ghetto. White institutions created it, white institutions maintain it, and white society condones it.” Although the Kerner report was widely disseminated, it was not popular. As Gooden and Myers report:
"President Johnson was enormously displeased with the report, which in his view grossly ignored his Great Society efforts. The report also received considerable backlash from many whites and conservatives for its identification of attitudes and racism of whites as a cause of the riots. `So Johnson ignored the report. He refused to formally receive the publication in front of reporters. He didn’t talk about the Kerner Commission report when asked by the media,' and he refused to sign thank-you letters for the commissioners (Zelizer 2016, xxxii–xxxiii)."
2) "Black-White Disparities: 50 Years After the Kerner Commission" (February 27, 2018)

Janelle Jones, John Schmitt, and Valerie Wilson offer a useful starting point in the short report, "50 years after the Kerner Commission: African Americans are better off in many ways but are still disadvantaged by racial inequality," from the Economic Policy Institute (February 26, 2018).

3) "Black/White Racial Inequality: A Place-Based Look" (October 5, 2018)

The black population is not equally distributed across the United States: not equally across regions of the country, nor within metropolitan areas. This unequal distribution is in substantial part a result of historical events and policy decisions, many of them rooted in racism. As a result, policies that affect certain regions of the country more than others, or certain parts of metropolitan areas more than others, will inevitably have disparate racial effects. Bradley L. Hardy, Trevon D. Logan, and John Parman lay out the evidence and arguments for these and related claims in "The Historical Role of Race and Policy for Regional Inequality," which appears as a chapter in Place-Based Policies for Shared Economic Growth, edited by Jay Shambaugh and Ryan Nunn (Hamilton Project at the Brookings Institution, September 2018). As one example:

"As of 1880, 90 percent of the black population still lived in the South and 87 percent of the black population lived in a rural area. In contrast, only 24 percent of the white population lived in the South, and 72 percent of the white population lived in rural areas. This meant that black individuals were disproportionately affected by constraints on economic opportunity in the rural South. Over the second half of the 19th century, incomes in the South and the North diverged significantly, with average income in the South only half of the national average by 1900 ,,, The destruction caused by the Civil War and the emergence of northern manufacturing while the southern economy remained predominantly agricultural contributed to these trends. The black population therefore found itself in a region with far less economic opportunity than the rest of the nation."
As the authors also note, the lack of opportunity for rural southern blacks was reinforced by racism by individuals, employers, social institutions and government, which affected education, labor markets, and political participation. This lack of opportunity stirred what is called the "Great Migration" of blacks from the American south to northern cities, a pattern that lasted into the 1960s and which helped to reduce black-white gaps in income and other areas. But when blacks arrived in northern cities, they faced patterns of rising segregation by race. In many ways, the geographic location patterns of the current black population was heavily shaped over the last century-and-a-half by those policies. Moreover, the geographic location patterns of the black population are closely linked to the continuing inequalities of outcomes experienced by the black population.

4) "Black-White Income and Wealth Gaps" (July 2, 2018)

William Darity Jr., Darrick Hamilton, Mark Paul, Alan Aja, Anne Price, Antonio Moore, and Caterina Chiopris discuss  "What We Get Wrong About Closing the Racial Wealth Gap" (April 2018, Samuel DuBois Cook Center on Social Equity at Duke University). The paper is written in the form of myths about the black-white wealth gap, then followed by evidence.
Myth 1: Greater educational attainment or more work effort on the part of blacks will close the racial wealth gap. ...
At every level of educational attainment, black families’ median wealth is substantially lower than their white counterparts. White households with a bachelor’s degree or post-graduate education (such as with a Ph.D., MD, and JD) are more than three times as wealthy as black households with the same degree attainment. Moreover, on average, a black household with a college-educated head has less wealth than a white family whose head did not even obtain a high school diploma. It takes a post-graduate education for a black family to have comparable levels of wealth to a white household with some college education or an associate degree ...
Myth 2: The racial homeownership gap is the “driver” of the racial wealth gap. ...
The data indicates that white households who are not home-owners hold 31-times more wealth than black households that do not. Among households that own a home, white households have nearly $140,000 more in net worth than comparable black households. ...
Myth 3: Buying and banking black will close the racial wealth gap. ...
Black-owned banks also are miniscule in the context of the general scale of American banking. The largest five black owned banks recently were estimated to have assets totaling $2.3 billion, while J.P. Morgan alone had an estimated $2 trillion in assets. 
Myth 4: Black people saving more will close the racial wealth gap. ...
[T]here is no evidence that black Americans have a lower savings rate than white Americans once household income is taken into account ...
Myth 5: Greater financial literacy will close the racial wealth gap...
Meager economic circumstances—not poor decision making or deficient knowledge—constrain choices and leave asset-poor borrowers with little to no other option but to use predatory and abusive alternative financial services. A negligible level of economic resources readily explains why blacks, specifically, use more predatory financial institutions. ...

Myth 6: Entrepreneurship will close the racial wealth gap. ....
Blacks are far less likely to own a business, and for blacks that do own a business they have far less equity. ... In reality the data paints a daunting picture for diversity in entrepreneurship. According to the U.S. Census Bureau’s Survey of Business Owners (SBO), which is conducted every five years, over 90 percent of Latino and black firms do not have even one employee other than the owner. ... No amount of tutorials or online courses from wealth experts can change the reality of the racialized advantages and disadvantages that undergird entrepreneurship in America. ...
Myth 7: Emulating successful minorities will close the racial wealth gap. ...
In short, so-called “successful” immigrant groups actually retrieve a comparable class position as the one they held in their country of origin. Their pre-migration capital, whether embodied in their education and training or their financial resources, is critical in determining their outcomes in the United States. ... To suggest that blacks and racialized Latino, and Native Americans should emulate other supposedly successful “minority” groups perpetuates the false narrative that their asset poverty is due to a lack of hard work, effort, or ambition. ...
Myth 8: Improved “soft skills” and “personal responsibility” will close the racial wealth gap.
Black men already are largely located in service sector jobs that require, or depend, on “soft-skills.” It is not “soft skills” requirements that distinguish black and white male sites of employment. It is relatively lower pay in the jobs held by the former and relatively higher pay in jobs held by the latter.
Myth 9: The growing numbers of black celebrities prove the racial wealth gap is closing. ...
Unfortunately, from “The Cosby Show” to Michael Jackson’s multi-platinum albums to Will Smith’s meteoric rise to the present day mega couple Jay-Z and Beyoncé, black celebrity has masked black poverty, rather than contributed to closing the racial wealth gap. ... Despite recently released 2016 Federal Reserve data showing that the median black family has a net worth of about $17,600, while the median white family has a net worth closer to $170,000 (Jan 2017), black life has come to be seen through the lens of radically exceptional cases, rather than typical ones.
Myth 10: Black family disorganization is a cause of the racial wealth gap. ...
However, marriage does little to help equalize wealth among white and black women with a college degree. For example, married white women without a bachelor’s degree are in households where they have more than two and a half times the wealth of married black women with a degree. Racial wealth disparities widen among married women with a bachelor’s degree; married white women are in households that have more than five times the amount of wealth as their black counterparts. White households with a single white parent have more than two times the net worth of two parent black households ...
Raj Chetty, Nathaniel Hendren, Maggie R. Jones, and Sonya R. Porter have written, "Race and Economic Opportunity in the United States:An Intergenerational Perspective" (March 2018, also available as NBER Working Paper #24441). The authors have written a nice readable summary of main findings for the VoxEU website (June 27, 2018). Here are the main findings:

Finding #1: Hispanic Americans are moving up in the income distribution across generations, while Black Americans and American Indians are not. ... In contrast, black and American Indian children have substantially lower rates of upward mobility than the other racial groups. For example, black children born to parents in the bottom household income quintile have a 2.5% chance of rising to the top quintile of household income, compared with 10.6% for whites.
Finding #2: The black–white income gap is entirely driven by differences in men’s, not women’s, outcomes. ...
Finding #3: Differences in family characteristics – parental marriage rates, education, wealth – and differences in ability explain very little of the black–white gap. ...
Finding #4: In 99% of neighbourhoods in the United States, black boys earn less in adulthood than white boys who grow up in families with comparable income.
Finding #5: Both black and white boys have better outcomes in low-poverty areas, but black-white gaps are bigger in such neighbourhoods. ...
Finding #6: Within low-poverty areas, black–white gaps are smallest in places with low levels of racial bias among whites and high rates of father presence among blacks. ...
Finding #7: The black–white gap is not immutable: black boys who move to better neighbourhoods as children have significantly better outcomes.
5) "Moral Licensing: When Doing Good Frees You to do Bad" (August 17, 2018)

"Moral licensing" is a term from the behavioral psychology literature. Daniel Effron of the London Business School, who has done some of the research in this area, describes it this way: "[T]he ability to point to evidence of past virtue can ironically make people more willing to act less-than-virtuously." Or as the title of one article puts it "being good frees us to be bad." Some of the examples in this literature describe how those who have participated in an action that seems virtuous then become more prone to display racist attitudes.

One study done back in 2008 asked whether a white person or a black person would be more qualified for a certain job. They were also asked about whether they favored Barack Obama for president--but some were asked before the question about job suitability and some were asked after. "[T]he opportunity to endorse Barack Obama made individuals subsequently more likely to favor Whites over Blacks." The results are in Effron, D.A., Cameron, J.S., Monin, B., Endorsing Obama Licenses Favoring Whites, Journal of Experimental Social Psychology (2009).

Sometimes just anticipating the prospect of doing good in the future can free you you up to do bad in the present. Jessica Cascio and E. Ashby Plant study "Prospective moral licensing: Does anticipating doing good later allow you to be bad now?" Journal of Experimental Social Psychology (2015, 56, pp. 110-116):
"Across four studies we explored whether anticipating engaging in a moral behavior in the future (e.g., taking part in a fundraiser or donating blood) leads people to make a racially biased decision (Studies 1 and 2) or espouse racially biased attitudes (Studies 3 and 4) in the present. Participants who anticipated performing a moral action in the future displayed more racial bias than control participants. ... These results demonstrate that anticipating a future moral act licenses people to behave immorally now and indicate that perceptions of morality encompass a wide variety of concepts, including past as well as anticipated future behavior."

Friday, January 18, 2019

Trump, Year Two: The Economic Record

When President Trump took office January 20, 2017, I asked "What if Trump Skeptics, Like Me, Turn Out to be Wrong? I wrote then:
If a Trump presidency turns out badly in various ways, then Trump skeptics like me will certainly say so. But if matters don't go wrong, then in fairness, then it seems to me that Trump skeptics should take a pledge to admit and acknowledge in a few years that at least some of our doubts and suspicions were incorrect--and indeed, we should be pleased that we were wrong. Here's my version of that pledge on a few economic issues.
  • If the US economy experiences a resurgence of manufacturing jobs, I will say so. 
  • If US economic growth surges to a 4% annual rate, I'll say so.
  • If the US economy does not actually retreat from foreign trade during four years of Trump presidency (which may well happen, given that globalization is driven by underlying economic forces, not just trade agreements), I will say so.
  • If US carbon emissions fall during a Trump presidency (which may happen with the resurgence of cleaner-burning natural gas and the larger installed base of noncarbon energy sources), I will say so.
  • If the budget deficit does not explode in size during a Trump administration, despite all the promises for tax cuts and a huge boost in infrastructure spending, I will say so. 
  • If the Federal Reserve has maintained its traditional independence after 3-4 years, I will say so. 
  • If the number of Americans without health insurance is about the same in 3-4 years, or even lower, I will say so. 
Well, President Trump has been in office two years.  What's the economic record? The US economy in 2018 continued the economic upswing that started in June 2009,  and by mid-2019, it will become the longest period without a recession in US economic history. However, The unemployment rate has been 4% or below for the last 10 months, and 5% or below for the last 37 months since December 2015. Inflation has stayed low. Despite its drop since late September, stock market values (like the S&P 500 index) are still up by abut 15% since January 20, 2017.

In short, it seems clear that the more dire predictions made back in 2017 about how the economy would immediately tank were based more in animus to Trump than in prescient analysis. Indeed, a lot of the economic patterns like growth and unemployment for the first two year of the Trump presidency look a lot like a continuation of patterns from the last few years of the Obama presidency. What about the specific questions I asked back in January 2017?

On the issue of manufacturing jobs,  total US manufacturing jobs bottomed out at 11.4 million in January 2010, had risen to 12.3 million by January 2017, and were up to 12.9 million by the end of 2018. A pattern set in the Obama administration has continued along with the continued growth of the US economy. .

On the rate of economic growth, the pattern looks much the same as it did in Obama's second term. Trump has had one quarter of growth at a rate faster than 4% (2018, Q2), but there is no particular sign of a jump in growth rates or productivity.

On trade issues, Trump just talked about protectionism in 2017, but actually started implementing it in 2018. However, one of the ironies here is that with the threat of greater protectionism about to kick in, it appears that a number of companies have accelerated their trade plans, boosting their imports ahead of future tariffs. Thus, the US trade deficit will probably grow in 2018 compared to 2017.  I'm not someone who thinks the bilateral US trade deficit with China should much of a focus, but for those who do, 2018 will mark the biggest such deficit ever. Thus, by one of President Trump's preferred measures, the size of the trade deficit, his policies are not a success in 2018. For those of us who worry about a disruption of global trade patterns, the bigger worries are coming in 2019.

On carbon emissions, US carbon emissions have been falling, not rising, while much of the rest of the world has been headed in the other direction. The lesson I would draw here is that too many people put too much faith in signing international agreements as the path to reducing carbon emissions. Focusing on government and industry actions, and how they shape prices, is considerably more important. For the US, I'd trade all the signatures on international climate change agreements for an actual carbon tax.

The ratio of federal debt held by the public to GDP doubled from 36% back in 2008 to about 72% by early 2013, This debt/GDP ratio edged up only a little more to 75% of GDP when Trump took office in early 2017, and had reached 76% by late 2018. But the Historical Tables released from Trump's Office of Management and Budget a year ago estimated that the budget deficit would rise from 3.5% of GDP in 2017 to 4.2% of GDP in 2018 and 4.7% of GDP in 2019 (Table 1.3). The real concern here is that in the middle run, starting about a decade from now, US spending is likely to rise substantially with the aging of the US population, and rather than address or postpone that issue, the $100 billion or so per year in tax cuts in the 2017  Tax Cuts and Jobs Act will make that middle-run debt crisis come a little sooner and be harder to address.

On the issue of the Federal Reserve, it seems fair to say that it has maintained its independence, but also to say that President Trump has challenged its independence in a way that hasn't been seen in the US since President Nixon pressured then-Fed chair Arthur Burns in the lead-up to the 1972 election--and Nixon's pressure was exerted mostly behind the scenes. The Fed has been systematically raising interest rates since December 2015, and if economic growth continues through 2019, I'd expect at least one more increase in 2019, too.

The number of Americans without health insurance hasn't budged much since President Trump took office. 

Looking ahead at 2019 and 2020, it seems to me that the US economy faces several meaningful sources of near-term risk.  Any of these would have a certain irony for the Trump presidency, because they would result in part from issues that President Trump has played a role in creating.

1) A recession could occur if the Federal Reserve raises interest rates too far, too fast. The Fed is fully aware of this danger, and has clearly signaled that it intends to look quite carefully at the evolution of the economy before raising interest rates further. But when President Trump openly criticizes the Fed, he inevitably reduced its perceived independence. If the Fed does not increase rates further, it creates a possibility--which clear-minded and hard-eyed financial markets will take into account--that the Fed is bowing to political pressure. Thus, if the Fed feels a need to assert its independence from President Trump's criticisms, it might feel a need to raise interest rates, rather than be  perceived as under political control.

2) President Trump has emphasized the importance of deregulation.  However, there is a strong case to be made that when it comes to financial regulation, additional steps need to be taken. The Dodd-Frank legislation back in 2010 was heavily focused on banks: having banks hold more capital, having regulators do stress-test scenarios of bank balance sheets, limiting certain risks banks could take, and so on. But banks are a diminishing part of the overall financial system. The so-called "shadow banking" sector is a broad category describing all the ways that borrowers can raise money outside of the banking sector, and investors can then purchase these loans. As a simple example, a money market mutual fund receives money from investors, who can be thought of as "depositors," and then invest the money in bonds, which can be thought of as lending the money to whatever government or private entity issued the bonds. But it isn't a bank.

I've written about the potential risks from "leveraged loans" and corporate debt more broadly. As another example, the new financial rules require many financial derivatives to be traded through a "central clearinghouse"--a company lilke the National Securities Clearing Corporation or the Options Clearing Corporation--but whether these clearinghouses will remain solvent in a financial emergency, and how they should be regulated, is not as clear as it should be. Some countries have the ability to impose rules that might impose, say, loan-to-income ratios if it seems that borrowing is getting out of hand. If that seems like a good idea for the US economy at some point, no US financial agency has that power. In short, whatever the broad merits of reducing the regulatory burden on the US economy, some parts of the financial sector could use a close and proactive look from regulators.

3) President "I am a tariff man" Trump has expressed strong concerns that interactions with the rest of the world are hurting the US economy. I disagree, but set aside the cosmic arguments over free trade and just think about the adjustment issues for a moment. A major pattern in the US and world economy in recent decades has been a shift to "global supply chains." This isn't just a matter of goods, but also international movements of data, services, and e-commerce more generally. A modern supply chain isn't a simple thing: it involves negotiations between sellers and buyers over technical specifications, delivery of output, as well as accounting, legal, and managerial issues. It isn't yet clear to me whether President Trump intends to settle his trade disputes by negotiating small changes and then declaring victory--which is the pattern with the proposed shift from the North American Free Trade Agreement (NAFTA) to a US-Mexico-Canada Trade Agreement (USMCA)--or if he truly intends to deliver a good swift kick to the global trading system as a whole. Even if the Trumpist argument that the US should become less involved in international trade is correct in the long run, a tectonic disruption of global supply chains built up over several decades will impose large and immediate costs on many US firms and their workers, as well as on US consumers.

Just to be clear, listing these kinds of risks should not be taken as a prediction that they are actually about to happen. The most likely prediction for 2019 is that it will be a lot like 2018, or perhaps a bit slower, unless something dramatic happens.

Thursday, January 17, 2019

How Does China's Higher GDP Translate into National Power?

Depending on what exchange rate you use for comparing GDP, China either already has a larger GDP than the US (using a purchasing power parity exchange rate) or will soon have a larger GDP than the US (using a market exchange rate). Stepping outside the economic issues here to the subject of international relations, does this higher GDP translate into greater international power? Michael Beckley tackles this question in "The Power of Nations  Measuring What Matters," appearing in the Fall 2018 issue of  International Security (43:2, pp. 7–44)

Beckley argues that most scholarly studies of international power focus on overall gross indicators like size of GDP, but that this approach can be misleading. He argues instead for a measure of power that combines GDP and per capita GDP, where the second measure is a rough way of capturing the efficiency with which a society employs its resources. By this admittedly rough-and-ready measure, the US remains much more powerful than China, thanks to its much higher productivity levels. 

Here's a taste of Beckley's argument (footnotes omitted):
Unfortunately, however, most scholars measure resources with gross indicators, such as gross domestic product (GDP); military spending; or the Composite Indicator of National Capability (CINC), which combines data on military spending, troops, population, urban population, iron and steel production, and energy consumption. These indicators systematically exaggerate the wealth and military capabilities of poor, populous countries, because they tally countries’ resources without deducting the costs countries pay to police, protect, and serve their people. A country with a big population might produce vast output and field a large army, but it also may bear massive welfare and security burdens that drain its wealth and bog down its military, leaving it with few resources for power projection abroad. ... 
Standard gross indicators are not good enough; they are logically unsound and empirically unreliable, severely mischaracterizing the balance of power in numerous cases, including in some of the most consequential geopolitical events in modern history. ... The hype about China’s rise, however, has been based largely on gross indicators that ignore costs. When costs are accounted for, it becomes clear that the United States’ economic and military lead over China is much larger than typically assumed—and the trends are mostly in America’s favor.
As an alternative, Beckley hearkens back to a suggestion originally made by the historian Paul Bairoch in a 1976 article, when he argued that the “strength of a nation could be found in a formula combining per capita and total GDP.” Beckley writes:
Bairoch did not elaborate on this point, but subsequent research supports his intuition: as noted, scholars already believe that GDP represents the gross size of a state’s economic and military output, and there is a large literature showing that GDP per capita serves as a reliable proxy for economic and military efficiency. ... Military studies also show that the higher a country’s GDP per capita, the more efficiently its military fights in battle. The reason is that a vibrant civilian economy helps a country produce advanced weapons, train skillful military personnel, and manage complex military systems. ... GDP per capita thus provides a rough but reliable measure of economic and military efficiency. ... Combining GDP with GDP per capita thus yields an indicator that accounts for size and efficiency, the two main dimensions of net resources. ...
To create a rough proxy for net resources, I follow Bairoch’s advice by simply multiplying GDP by GDP per capita, creating an index that gives equal weight to a nation’s gross output and its output per person. ... Future studies can experiment with ways to improve this measure by adjusting the weights or, even better, by expanding the databases created by the World Bank and the United Nations or developing new measures of net stocks of resources. For now, however, multiplying GDP by GDP per capita yields a primitive proxy that scholars can use to evaluate the importance of net resources in international politics.
Beckley applies this measure of power to a number of major international conflicts in the past that would otherwise be perplexing. One example is the conflicts between Britain and China from 1839-1911. China's GDP and defense budget were more than twice the size of Britain's, and yet Britain kept winning the battles. But China was a low-income country. "By standard indicators, China looked like a superpower in the nineteenth and early twentieth centuries. It had the largest GDP and military in the world until the 1890s, and the second largest GDP and military until the 1930s. During this time, however, China suffered a “century of humiliation” in which it lost significant territory and most of its sovereign rights, fighting at least a dozen wars on its home soil—and losing every single one of them."

Beckley offers a number of other  historical examples, but the case of modern China is perhaps of most immediate interest. He writes:

"OSince the 1990s, and especially since the 2008 financial crisis, hundreds of books and thousands of articles and reports have asserted that the United States’ economic and military edge over other nations is eroding and that the world will soon become multipolar. The main evidence typically cited for these trends is China’s rising GDP and military spending and various statistics that are essentially subcomponents of GDP—most notably, China’s massive manufacturing output; volume of exports; trade surplus with the United States; infrastructure spending; consumer spending; and large government bureaucracy and scientiªc establishment. The problem, however, is that these are the same gross indicators that made China look like a superpower during its century of humiliation: in the mid-1800s, China had the world’s largest economy and military; led the world in manufacturing output; ran a trade surplus with Britain; presided over a tributary system that extended Chinese trade and investment, infrastructure projects, and soft power across continental East Asia; and was celebrated in the West for its consumer market potential and tradition of bureaucratic competence and scientific ingenuity.

Obviously China is not as weak today as it was in the nineteenth century, but neither is it as powerful as its gross resources suggest. China may have the world’s biggest economy and military, but it also leads the world in debt; resource consumption; pollution; useless infrastructure and wasted industrial capacity; scientiªc fraud; internal security spending; border disputes; and populations of invalids, geriatrics, and pensioners. China also uses seven times the input to generate a given level of economic output as the United States and is surrounded by nineteen countries, most of which are hostile toward China, politically unstable, or both. Accounting for even a fraction of these production, welfare, and security costs substantially reduces the significance of China’s rise.

For a rough image the US-China power balance by different metrics, the first figure compares GDP. The second figure is the CINC measurement mentioned above. The third figure multiplies the size of GDP by per capita GDP. In this third sense, the US remains far more powerful than China.

The world is in the process of shifting from a situation in which the largest economies also tend to be high in per capita GDP to a situation in which many of the largest economies are populous middle-income countries, so Beckley's argument matters a lot. 

Wednesday, January 16, 2019

What Message is the Beveridge Curve Sending?

"The Beveridge Curve ... plots the job openings rate with respect to the unemployment rate. During an expansion, the job openings rate is high and the unemployment rate is low moving to points along the curve up and to the left. During a contraction, the job openings rate is low and the unemployment rate is high moving to points along the curve down and to the right. A shift in the Beveridge curve can indicate a structural shift in the economy due to industry-based structural mismatch and geography-based structural mismatch. For example, if the job openings rate and the unemployment rate are both high, this could shift the entire curve up and to the right."
These various patterns are apparent if you look at a recent Beveridge curve, which is published each month as part of the press release for the most recent Job Openings and Labor Turnover Survey statistics. This is the figure published in early January, which includes monthly data from December 2000 up through November 2018.
The key point here is that the Beveridge curve seems to have shifted since the start of the economic upswing back in 2009. Starting in 2000, through the recession of 2001, the upswing from 2001 to 2007, and the start of the Great Recession, the data on job openings and unemployment basically moves back and forth along the same line. As the Great Recession deepened, the Beveridge curve stretched out to the far lower right. But then when the economic recovery started in 2009, the Beveridge curve relationship did not retrace the earlier pattern from 2000-2009; instead, it moved out to the right, as shown by the purple line in the figure.

What does this shift in the Beveridge curve relationship mean? In a literal sense, it means that for a certain unemployment rate (on the horizontal axis), there is a higher rate of job openings (on the vertical axis). To put it another way, employers in the years after 2009 seemed more reluctant to fill their job openings, or as economists say, it appeared to be harder for employers to find a match when they listed a job among the workers who were applying for those jobs. The "matching efficiency" of the US labor market had declined.

Shifts in the matching efficiency of the labor market are not a new thing. Here's a figure from an article in the Journal of Economic Perspectives a few years ago, showing the Beveridge curve relationship from 1950 to 2011. The curve seems to have shifted out from the 1950s to the 1960s and 1970s, but then shifted back in the 1990s, 

Jessie Romero provides a short overview of the recent evidence about skill-based and geographic mismatch in "Help Wanted: Employers are having a hard time hiring. Not enough workers or not the right skills?" in Econ Focus (Federal Reserve Bank of Richmond, Third Quarter 2018, pp. 8-10). Romero cites various studies to the effect that in the Great Recession and its aftermath, mismatch of labor demand and supply across industries, places, and skill levels may have pushed up the unemployment rate by as much as one-third. These studies also suggest that while this higher level of mismatch often follows a recession, it usually lasts about three years. However, the Great Recession was so severe that the period of mismatch was extended.

As shown in the first figure above, the most recent Beveridge curve data has now looped all the way back around so that the combination of the job openings rate and the unemployment rate--and the extent of labor market mismatch--is similar to the US economic experience back around 2000.  While this is generally good news, Romero ends on a cautionary note:
"In addition, although the Beveridge curve has largely looped back to its pre-recession position, it still remains further to the right than it was for much of the postwar era. According to research by Thomas Lubik of the Richmond Fed and Luca Benati of the University of Bern (Switzerland), with each successive recession since the 1950s, matching efficiency has gone down — the unemployment rate implied by a given job vacancy rate has increased. A likely explanation for these successive rightward movements is technological change whose effects on the labor market are hastened by recessions. A large body of research has documented how such change has tended to benefit workers with more skills and more education. These forces might be masked by a hot economy for a time, but if things cool off, some workers, especially the more recent entrants to employment, might once again find themselves without a match."
In a post back in 2012 on the Beveridge curve, as it started to shift out to the right and loop upward, I finished with this thought:
[The]  Beveridge curve is apparently one more manifestation of an old pattern in academic work: Curves and laws and rules are often named after people who did not actually discover them. This is sometimes called Stigler's law: "No scientific discovery is named after its original discoverer." Of course, Steve Stigler was quick to point out in his 1980 article that he didn't discover his own law, either!
But William Beveridge is a worthy namesake, in the sense that he did write a lot about job openings and unemployment. For example, here's a representative comment from his 1944 report, Full Employment in a Free Society:
"Full employment does not mean literally no unemployment; that is to say, it does not mean that every man and woman in the country who is fit and free for work is employed productively every day of his or her working life ... Full employment means that unemployment is reduced to short intervals of standing by, with the certainty that very soon one will be wanted in one's old job again or will be wanted in a new job that is within one's powers.”

Tuesday, January 15, 2019

The Flynn Effect (Rising IQ Scores Over Time) Reverses

The "Flynn effect" refers to a pattern observed by James Flynn, a professor at the University of Otago in New Zealand. It points out that for most of the 20th century, scores on IQ tests have been rising.  The reasons behind this pattern have been a subject of controversy.  For example, are the rising IQ scores a result of some factor like improved nutrition, both prenatally and for young children? Are they a result of improved schooling? Or a  job environment that puts greater emphasis on cognitive skills? Is there something about the design of IQ tests, perhaps combined with  that has made scores go up even if underlying intelligence hasn't moved?

It's clear that intelligence has a genetic aspect: studies that looked at twins who were separated at birth and raised in different environments show a high correlation of their IQ scores. But rising average IQ scores over a couple of generations is clearly not the result of a sharp genetic shift; instead, the Flynn effect strongly suggests that differences in measured intelligence are not purely genetic, but also have a strong environmental component.  However, the Flynn effect now seems to be moving in reverse.

As a starting point, Flynn offers a readable overview of his perspectives on IQ research  in "Reflections about Intelligence over 40 Years" (Intelligence, September-October 2018, 70: pp. 73-83). A few snippets (citations omitted): 
A few years later, I documented what became called the `Flynn effect'. The 20th century had been dominated by massive IQ gains from one generation to another. Americans had gained 14 IQ points on the standard IQ tests (Stanford-Binet, Wechsler) between 1932 and 1976; and 14 nations had made massive gains on a whole range of IQ tests, the largest on Raven's Progressive Matrices. ... This phenomenon now covers at least 34 nations and is accepted by all scholars. The 21st century may well be different, with gains tailing off or reversing in some nations beginning in 1995, although
not in the US. ... 
After a few years of inactivity, my Catholic Youth Organization (CYO) basketball team came back to play the current team. They killed us. They had all sorts of skills we lacked, they could shoot with either hand, could pass with either hand, do fade-away jump shots. I doubt that any of them had superior genes for basketball. Rather it was the passage of time that had given them a basketball environment a world away from our own. I take it that it is easy to apply this to the realm of cognition. Within  a cohort, genetic quality tends to dictate how you respond at school, how hard you work, whether you join a book club, how you will do in high school, what university you attend – your genetic quality will eventually tend toward a matching quality of environment for cognition. Between cohorts spaced over time, different forces operate.
Since the industrial revolution began, social change has caused new cognitive exercise ... more schooling, more cognitively demanding work, and more cognitively demanding leisure. These environmental factors initially triggered a mild rise in average performance, but this rise was greatly magnified by feedback mechanisms and over a century average IQ escalated. As the average years of schooling rose, the rising mean itself became a powerful engine in its own right as people chased it to keep up. ...

I want to make it clear that although enriched environment dominated the 20th century, IQ gains are not destined to persist like the law of gravity. Factors that were immediate triggers of IQ gains included more adults per child in the home, more and better schooling, more people at university, more cognitively demanding jobs, and better  health and conditions of the aged. There are signs that these are beginning to show diminishing returns.
What are some of the "signs" which Flynn is referring? For an overview of the recent findings about recent reversals in the Flynn effect, Flynn and Michael Shayer wrote "IQ decline and Piaget: Does the rot start at the top? (Intelligence, January–February 2018, 66: 112-121). They write:
The IQ gains of the 20th century have faltered. Losses in Nordic nations after 1995 average at 6.85 IQ points when projected over thirty years. On Piagetian tests, Britain shows decimation among high scorers on three tests and overall losses on one. The US sustained its historic gain (0.3 points per year) through 2014. The Netherlands shows no change in preschoolers, mild losses at high school, and possible gains by adults. Australia and France offer weak evidence of losses at school and by adults respectively. German speakers show verbal gains and spatial losses among adults. ...

After our analysis, we will suggest two tentative hypotheses. First, trends on conventional tests show those at most risk of IQ decline are high school students aged 14 to 18. However, Piagetian results in Britain imply losses at earlier ages. Second, Piagetian tests signal something extra: conflicting trends between top scorers (those at the highest or formal level of cognitive development) and those in the early stages of the next level (concrete generalization). Large losses at the formal level may be accompanied by gains at the concrete level.
A recent study from Norway struck me as especially interesting, because in Norway many men 18-19 years of age were given standardized IQ tests as part of assessment for compulsory national service. With data from 1970-2009, one can look both at trends for 18-19 year-olds, but also look link together the scores of fathers and sons--and include other variables about a given family.  Using this data, Bernt Bratsberg and Ole Rogeberga argue that the "Flynn effect and its reversal are both environmentally caused" (PNAS,  June 26, 2018, 115, #26).
The results show that large positive and negative trends in cohort IQ operate within as well as across families. This implies that the trends are not due to a changing composition of families, and that there is at most a minor role for explanations involving genes (e.g., immigration and dysgenic fertility) and environmental factors largely fixed within families (e.g., parental education, socialization effects of low-ability parents, and family size). While such factors may be present, their influence is negligible
compared with other environmental factors.
The questions of how intelligence translates into economic outcomes and into broader human well-being are big ones, and I won't make even a feeble gesture at tackling them here. But intelligence is a real thing, albeit hard to measure, and it shapes lives and society. What looks like a reversal of the Flynn effect, apparently for broad-based reasons environmental reasons that reach across families, is worth some thought.

Monday, January 14, 2019

What if Most Americans Don't Care That Deeply about Trade?

"In fact, recent public opinion polling uniformly reveals that, first, foreign trade and globalization are generally popular, and in fact more popular today than at any point in recent history; second, a substantial portion of the American electorate has no strong views on U.S. trade policy or trade agreements; third, and likely due to the previous point, polls on trade fluctuate based on partisanship or the state of the U.S. economy; and, fourth, Americans’ views on specific trade policies often shift depending on question wording, especially when the actual costs of protectionism are mentioned. These polling realities puncture the current conventional wisdom on trade and public opinion—in particular, that Americans have turned en masse against trade and globalization ..."

Thus argues Scott Lincicome in "`The “Protectionist Moment' That Wasn’t: American Views on Trade and Globalization," written as an installment of the Free Trade Bulletin from the Cato Institute (November 2, 2018).

If you disagree with the statements above, your disagreement isn't with Lincicome (or with me), it's with the array of polling data that Lincicome presents. For example, on the issue of how Americans feel about trade: 
  • Pew (May 2018) found that American support for free trade agreements rebounded to pre-2016 levels, only a couple percentage points off its all-time high in 2014.
  • WSJ/NBC News (March 2018) found “Americans overwhelmingly think trade is more of an opportunity to boost the economy than it is a threat to it . . . by a 66%–20% margin. And that feeling transcends party lines, as Republicans, independents and Democrats agree that foreign trade is an opportunity for economic growth.”
  • Gallup (March 2018) found that “[a] strong majority of U.S. adults (70%) see foreign trade as an opportunity for U.S. economic growth through increased exports rather than a threat to the economy from foreign imports (25%)”—down from an all-time high in 2017 of 72 percent. Before that, “no more than 58% had held the positive view of trade.”
  • Monmouth (June 2018) found that 52 percent and 14 percent, respectively, of Americans in 2018 think that “free trade agreements are good or bad for the United States” up dramatically from 24 percent good and 26 percent bad in November 2015.
But perhaps the deeper lesson of the polling data seems to be that American opinions about free trade do not seem especially strong or robust. For example, my own guess is that some of the rise in support for trade is a reaction against President Trump's anti-trade rhetoric and policies--but that some of the same people who express support for trade now could switch sides if tariffs were imposed on imports by a politician or party that they supported.  

This figure shows the range of opinions from "very strong opposition" to "very strong support" on a range of issues. The black line shows that a much larger share of the opinions about trade are in the "neither favor or oppose" category than is true for the other issues.
Also, while it's always true that the phrasing of questions in a survey will affect the results, this affect seems especially strong on trade issues. Here are a couple of examples from Bloomberg surveys. If you ask a trade question like this, you get a strongly protectionist answer: 
“Generally speaking, do you think U.S. trade policy should have more restrictions on imported foreign goods to protect American jobs, or have fewer restrictions to enable American consumers to have the most choices and the lowest prices?” 
But if you ask a trade question like this, you get a strongly free trade answer:
“Are you willing to pay a little more for merchandise that is made in the U.S., or do you prefer the lowest possible price?”
This difference also seems to reflect actual consumer/voter behavior. American may cheer for politicians who promise "to protect American jobs," but they aren't very eager to pay actual higher prices to make this occur. Lincicome summarizes the evidence this way:
"[P]rotectionist policies emanating from the United States government today are most likely a response not to a groundswell of popular support for protectionism but instead to discrete interest group lobbying (e.g., the U.S. steel industry) or influential segments of the U.S. voting population (e.g., steelworkers in Pennsylvania). Protectionism therefore remains a classic public-choice example of how concentrated benefits and diffuse costs can push self-interested politicians into adopting polices that are actually opposed by most of the electorate."
It's interesting that President Trump has a number of times defended his protectionist policies as a necessary negotiating step to greater free trade. From a trade policy perspective, this justification is the tribute that vice pays to virtue.