DR Editor in BYU Studies Quarterly: “Ye Are No More Strangers and Foreigners”

I’m excited to announce that my article “”Ye Are No More Strangers and Foreigners”: Theological and Economic Perspectives on the LDS Church and Immigration” has been published in the latest issue of BYU Studies Quarterly. From the abstract:

Issue 57:1 CoverImmigration policy is controversial topic in 2018. In response to refugee crises and legal situations that can break up families, the LDS Church announced its “I Was a Stranger” relief effort and released a statement encouraging solutions that strengthens families, keeps them together, and extends compassion to those seeking a better life. This article seeks to shed light on a correct understanding of immigration and its effects. Walker Wright gives a brief scriptural overview of migration, explores the public’s attitudes toward immigration, and reviews the empirical economic literature, which shows that (1) fears about immigration are often overblown or fueled by misinformation and (2) liberalizing immigration restrictions would have positive economic effects.

From the editors:

Walker Wright’s article on religious and economic perspectives about immigration, strangers, and refugees is marvelously timely. He approaches the debate over immigration through a double lens: the Church’s official statements and scholarly research on the economic effects of immigration. He demonstrates that the Church’s accommodating approach is overwhelmingly supported by the research. Migration is often impelled by external pressures, but it is ultimately the voluntary response of those fleeing to improve their lives. Immigrants come unassigned, so people can reach out to them without needing to be asked (pg. 5).

The article is divided into the following sections:

  • “I Was a Stranger”
  • Migration in Scripture and Sacred History
  • Strangers, the Sin of Sodom, and Zion
  • Public Opinion on Immigration
  • The Economy as a Whole
  • Global Poverty
  • Refugees
  • Common Objections to Immigration
    • “Stealing” Jobs
    • Depressed Wages
    • Culture and Institutions
    • Fiscal Burden and Welfare Cost
    • Terrorism and Crime

Check it out. You can also access it on my Academia.edu page.

 

Total and Intangible Wealth: World Bank Report 2018

I’ve mentioned the World Bank’s measurement of intangible assets before. Its recent report–The Changing Wealth of Nations 2018: Building a Sustainable Future–updates this measurement:

Image result for human capitalTotal wealth in the new approach is calculated by summing up estimates of each component of wealth: produced capital, natural capital, human capital, and net foreign assets. This represents a significant departure from past estimates, in which total wealth was estimated by (1) assuming that consumption is the return on total wealth and then (2) calculating back to total wealth from current sustainable consumption…In previous estimates, produced capital, natural capital, and net foreign assets were calculated directly, then subtracted from total wealth to obtain a residual.

The unexplained residual, called “intangible capital,” was largely attributed to human capital…as well as to missing or mismeasured assets and possible effects of social capital. But the unexplained residual accounted for 50–85 percent of the total wealth indicator, making it a weak indicator for policy. This approach was taken because of the lack of data for directly measuring human capital. We now have a method and data for estimating human capital directly and will measure total wealth as the sum of each asset category. The advantage of the earlier approach was that the residual included human capital, unmeasured assets, and the influence of institutions and governance on wealth. The disadvantage was that the various components of the residual could not be disentangled and it was calculated assuming the same return on assets in all countries.

Human capital in the past was not measured explicitly but included as part of the “residual,” accounting for 50–85 percent of total wealth in past estimates. We apply the well-known Jorgenson Fraumeni lifetime earnings approach to measuring human capital globally. We use a unique database developed by the World Bank, the International Income Distribution Database, which contains more than
1,500 household surveys (pgs. 38-39).

This report

shows for the first time that much of intangible wealth is actually human capital, estimated as the net present value of the population’s future labor earnings. Human capital turns out to be the most important component of wealth, even though its share in total wealth decreased from 69 percent in 1995 to 64 percent in 2014 (table 2.2). After 2000, this decline in the share of human capital wealth was entirely due to upper-middle and high-income OECD countries, which together account for more than 80 percent of global wealth as well as most human capital wealth. The factors that led to this decline include the aging of the labor force (which reduces the remaining years of earnings) in many high-income OECD countries, as well as in China, which dominates the upper-middle-income country group, and declining wage shares in GDP, particularly in many high-income OECD countries (ILO 2015). By contrast, in low- and lower-middle-income countries, which account for the majority of the world’s population, the share of human capital in total wealth is rising (pgs. 46-47).

The new report calculates total wealth as follows:

Total wealth = Natural capital + Produced capital + Human capital + Net foreign assets

“This represents a significant departure from past estimates,” the report explains,

in which total wealth was estimated by assuming that consumption is the return on total wealth, and then calculating back to total wealth from current sustainable consumption (“top-down approach”). In previous estimates, produced capital, natural capital, and net foreign assets were calculated directly, then subtracted from total wealth to obtain a residual. The unexplained residual, called “intangible capital,” was largely attributed to human capital as well as to missing or mismeasured assets. Now with a direct measurement of human capital,[ref]See Ch. 6 for an explanation of the methodology for measuring human capital.[/ref] total wealth can be estimated as the sum of all categories of assets (pg. 212).

In turns out that the U.S. has $983,280 total wealth per capita with human capital making up $766,470 (see pg. 232). Other findings include:

  • The report found that global wealth grew 66 percent (from $690 trillion to $1,143 trillion in constant 2014 U.S. dollars at market prices).
  • The top 20 countries with the fastest growing wealth per capita were dominated by developing countries—including two of the biggest—China and India, which were both classified by the World Bank as low income countries in 1995 and are now ranked as middle-income.
  • Countries with large gains in per capita wealth also included smaller countries like Chile, Peru, Vietnam, as well as countries rapidly recovering from civil disturbances like Bosnia-Herzegovina, Ethiopia, Rwanda, and Sri Lanka as well as some of the resource rich countries in the former USSR, like Azerbaijan.
  • Per capita wealth declined or was stagnant in more than two dozen countries in various income brackets. These include several large low-income countries, some carbon-rich countries in the Middle East, and high-income OECD countries affected by the 2009 financial crisis. Declining per capita wealth implies that assets critical for generating future income may be depleted, and the rents generated from natural assets depletion are not invested properly, a fact often not reflected in national GDP growth figures.
  • Human capital is the largest component of global wealth, accounting for two thirds of total wealth globally. This points to the need to invest in people for wealth creation and future income generation.
  • While natural capital accounts for 9 percent of wealth globally, it makes up nearly half (47 percent) of the wealth in low income countries. More efficient, long-term management of natural resources is key to sustainable development while these countries build their infrastructure and human capital.

Breaking News: Communism Makes People Worse Off

From a recent study:

Our bivariate analyses show that the recent cultural factors examined—communist history and religion—are, taken alone, good predictors of the Human Development Index and its components (table 1). When incorporated alongside phylogeny and geography, phylogeny ceases to be a significant predictor of HDI or any of its components, meaning recent cultural factors combined with geography can account for covariation between HDI and cultural phylogeny (table 3). Communism significantly negatively predicts HDI, income and health indices, but religion ceases to be a significant predictor except for a negative correlation between Islam and education index. These results support a significant effect of communist history on the human development of countries, comparable to the effects of geography (which remains a significant predictor of HDI and income index), and more immediately important than cultural phylogeny or religion.

…Communist history shows a significant negative correlation with the national income of the countries in our dataset. Post World War II economic growth in communist countries was modest, especially during the 1970s and 1980s, relative to non-communist European countries [92], and the centrally planned economy of communist countries has long been held by economically liberal theoreticians to hamper conventional economic growth [9395]. Although the countries in the dataset had abandoned communism for most of the years in the dataset, the residual effect of communism appears to still be detectable. Institutional and cultural traits produced by communism and by dictatorship may continue to retard growth today, with corruption still regarded as higher in Eastern than Western Europe [96] and linked to lower national income [97]. It should also be noted, however, that many of the former communist countries (largely those in the former Soviet Union) also suffered major economic turmoil following the demise of their communist governments [98], and that this too may play a role in explaining the apparent effect of communism on income. Moreover, it must be noted that the communist countries in the sample are all Eastern European and Central Asian, and that these areas were less wealthy than Western Europe even prior to communism [92,99], and indeed Russia saw rapid economic growth following the advent of communism, although this lessened over time [92,100]. For all these reasons the results presented here must be treated with caution, and are primarily intended as a control in the context of examination of deep cultural effects on human development, not as a thoroughgoing analysis of the effects of communism on development.

Communism also shows a significant negative association with health index (i.e. normalized longevity), although only at p = 0.05 level. This confirms the stagnation and even decline of life expectancy in Europe under communism during the 1970s and 1980s, corresponding to years of low economic growth (see above), which has continued to set formerly communist countries back in terms of life expectancy until today [101,102]. The proximate causes for this low life expectancy are complex, but high alcohol consumption, smoking and poor workplace safety, as well as low quality diet and living conditions associated with lower income levels are implicated [101]. Most of the same caveats also apply here as to the economic effects of communism however, with lifespan decreasing rapidly in the former Soviet Union immediately following post-Soviet collapse [101], and lifespan having increased strongly in the Soviet Union prior to and immediately after World War II [103].

Longevity greatly increased during recent centuries in Europe in part due to generally rising living standards (and thereby nutrition [104]), with increasing health and longevity interacting with the economy in a positive feedback loop [105]. Communist history may thus have also influenced longevity via its effect on income, with income being a significant predictor of health index (electronic supplementary material, table S1). Consistent with this explanation, we find that communism is no longer a significant predictor of health index when controlling for income index.

Communism lowers human well-being. Who knew?[ref]There’s more to the study (such as Islam’s negative correlation with education), but this jumped out at me.[/ref]

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Would You Give Up Your Right to Vote for a Pay Raise?

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Over a third of Americans would for an immediate 10% annual raise, according to a new survey. Here are the results in full:

    • 40.06% would give up dental care for the next five years
    • 12.2% would break up with their partner or significant other
    • 53.55% would give up all social media accounts for the next five years
    • 88.61% would give up watching Game of Thrones for life
    • 43.86% would give up exercise for the next five years
    • 34.98% would give up the right to vote in all elections for life
    • 9.13% would give up their child’s or future child’s right to vote in all elections for life
    • 73.42% would give up all alcoholic beverages for the next five years
    • 17.93% would give up Social Security benefits for the next two years
    • ​18.9% would give up access to health insurance for the next five years
    • 50.65% would give up watching movies for the next three years
    • 55.9% would work an extra 10 hours per week for life
    • 15.27% would give up all of their vacation days for the next five years
    • 47.74% would give up all caffeinated products for the next two years
    • 50.4% would work one day every weekend for the next year
  • 5.33% would eat a single tide pod

Why would people give up this right? Because they have every incentive to do so. As explained by Jason Brennan,

There is some debate among economists and political scientists over the precise way to calculate the probability that a vote will be decisive. Nevertheless, they generally agree that the probability that the modal individual voter in a typical election will break a tie is small, so small that the expected benefit (i.e., p[V(D)V(R)]p[V(D)−V(R)]) of the modal vote for a good candidate is worth far less than a millionth of a penny (G. Brennan and Lomasky 1993: 56–7, 119). The most optimistic estimate in the literature claims that in a presidential election, an American voter could have as high as a 1 in 10 million chance of breaking a tie, but only if that voter lives in one of three or four “swing states,” and only if she votes for a major-party candidate (Edlin, Gelman, and Kaplan 2007).[ref]On average, a voter has a 1-in-60 million chance of changing the outcome of a presidential election.[/ref] Thus, on both of these popular models, for most voters in most elections, voting for the purpose of trying to change the outcome is irrational. The expected costs exceed the expected benefits by many orders of magnitude.

Consider the following costs:

[S]uppose my favored candidate (who is worth $33 billion more to the common good) enjoys a slight lead in the polls. She has a very small anticipated proportional majority. The probability that any random voter will vote for her is 50.5 percent. This is an election we would describe as “too close to call.” Suppose also that the number of voters will be the same as in the 2004 U.S. presidential election: 122,293,332. I vote for my favored candidate. In this case, the expected value (for the common good) of my vote for the better candidate is $4.77 x 10^-2650 , that is, approximately zero. Even if the candidate were worth $33 billion to me personally, the expected value for me of my vote would be, again, a mere $4.77 x 10^-2650 . That is 2,648 orders of magnitude less than a penny. In comparison, the nucleus of an atom, in meters, is about 15 orders of magnitude shorter than I am. In meters, I am about 26 orders of magnitude shorter than the diameter of the visible universe. In pounds, I am about 28 orders of magnitude less heavy than the sun. Even if the value of my favored candidate to me were dramatically higher, say ten thousand million trillion dollars, the expected value of my vote in our example—for a close election—remains thousands of orders of magnitude below a penny. For an election in which the candidate has a sizable lead, the expected utility of an individual vote for a good candidate drops to almost zero.

The Beneficence Argument appeals to the public utility of individual acts of voting. However, suppose all you care about is maximizing your contribution to the common good. If so, voting would not merely fail to be worthwhile— it would be counterproductive. It turns out that the expected disutility of driving to the polling station (in terms of the harm a driver might cause to others) is higher than the expected utility of a good vote. This is not hyperbole.

Aaron Edlin and Pinar Karaca-Mandic have estimated the expected accident externalities per driver per year in the United States—that is, the amount of damage the average driver imposes on others from accidents and reckless driving. The expected accident externalities range from as little as $10 in low-traffic-density North Dakota to more than $1,725 in high-traffic-density California. Suppose a North Dakotan takes five minutes to drive to the polling station. The average expected accident externality of a five-minute drive in North Dakota is $9.5 x 10^-5 , much larger than the expected benefit of a good vote in the previous example. So the voter imposes greater expected harm on her way to the polls than she could compensate for by a good vote.[ref]Jason Brennan, The Ethics of Voting, pgs. 19-20.[/ref]

Can’t say I blame people.

The Economic Impact of Immigration: UK Edition

Image result for brexit

Economist Jonathan Portes has an excellent summary of the research on immigration’s effects in the UK:

  • Employment: “To the considerable surprise of many economists, including me, there is now a clear consensus that even in the short-term migration does not appear to have had a negative impact on the employment outcomes of UK natives. Studies have generally failed to find any significant association between migration flows and changes in employment or unemployment for natives (see, for example, BIS 2014 for a review).  Since 2014, the continued buoyant performance of the UK labour market has further reinforced this consensus. Rapid falls in unemployment, now down to just over 4%, have been combined with sustained high levels of immigration. Nor is there any evidence that immigration has impacted the employment prospects of specific groups such as the young or unskilled. Crudely, immigrants are not taking our jobs – the lump of labour fallacy, that the number of jobs or vacancies in the economy is fixed (which generally refers to the medium to long term) turns out to be a fallacy in the short term as well.”
  • Wages: “While the evidence on wage impacts is less conclusive, the emerging consensus is that recent migration has had little or no impact overall, but possibly some, small, negative impact on low-skilled workers. Dustmann et al. (2013), using UK LFS data for the period 1997-2005, find that immigration put a downward pressure on the wages at the bottom of the distribution (below the 20th percentile), while the effect on the rest of the distribution (in particular above 40th percentile) is positive. Their estimates show that a 1% increase in the foreign-born/native population ratio leads to an increase of between 0.1% and 0.3% in average wages.”
  • Productivity: “Immigrants’ skills may complement those of natives.  A number of papers support this hypothesis: for example, Barone and Moretti (2011) found that low-skilled migration increased the labour force participation of highly skilled native women; Peri and Sparber (2009) and Foged and Peri (2016) found that low-skilled migration increased the wages of native low skilled workers.  In particular, they argue that natives may have a comparative advantage in jobs with more communication-intensive tasks with respect to foreign workers, and that immigration ‘pushes’ low-skilled natives to occupations with a higher intensity of such skills, increasing the level of specialisation in the economy and hence productivity, as signalled by the corresponding increase in wages. Immigration might also influence the level of human capital in the economy, either directly if immigrants have high educational attainment (Kerr and Lincoln 2010, Hunt and Gauthier-Loiselle 2010), or indirectly by increasing the incentive on natives to acquire human capital. Some evidence (Hunt 2017, McHenry 2015) suggests that increased low-skilled immigration increase school performance and outcomes for US natives…Looking at the service sector, Ottaviano et al. (2015) show that a 1% increase in immigrants’ concentration in local labour markets is associated with a 2% to 3% rise in labour productivity, measured as gross value added per worker, mainly as a result of the cost-cutting dynamics implied by immigration-induced labour supply shocks. In addition, immigration represents a substitute for the import of intermediate inputs and is associated with an increase in exports to immigrants’ countries of origin.   Rolfe et al. (2013) found that immigrants concentration within specific industries was associated with slight increases in productivity, but the impact was small. At the aggregate level, recent literature uses cross-country evidence to estimate the impact of migration on growth and productivity in advanced economies. Boubtane et al. (2015) find that migration in general boosts productivity in advanced economies, but by varying amounts; for the UK, the estimated impact is that a 1 percentage point in the migrant share of the working age population leads to a 0.4-0.5% increase in productivity. This is higher than in most other advanced economies and reflects the relatively high skill levels of migrants to the UK. Jaumotte et al. (2016) find that a 1% increase in the migrant share of the adult population results in an increase in GDP per capita and productivity of approximately 2%. This result is consistent across a variety of empirical specifications.  Perhaps surprisingly, the estimated aggregate impacts of high and low skilled migration are not significantly different (although the distributional implications are very different). In a within-country perspective, Peri (2012), with a state-based analysis in US, finds that a 1% increase in immigration raises total factor productivity by 0.5%, mainly thanks to increased specialisation induced by immigrants’ inflows.”
  • Fiscal: “Dustmann and Frattini (2014) found that recent migrants, especially those from the EU, had a more positive fiscal impact on average than natives.  Of course, it is hardly surprising that young migrants in employment make an initial positive fiscal contribution; proper assessment of fiscal impacts requires a life-cycle perspective (Preston 2014).   In this context, there are various reasons to expect the impact to still be positive (in particular, migrants tend to arrive after they have left compulsory, publicly financed education). However, a positive net impact on public finances at the national level does not preclude a significant impact on demand (and hence cost) at the local level, particularly if funding allocations do not adjust quickly (or at all) to reflect pressures resulting from migration (George et al. 2011). A notable recent example is the shortage of primary school places in some parts of the UK (especially London); this appears to be largely the result of poor planning on the part of central government, given the rise in the number of young children resulting from recent increases in migration (from both the EU and elsewhere). But broader concerns about the potential negative impacts on public services appear to be largely unsubstantiated: higher immigration are not associated, at a local level, with longer NHS waiting times (Giuntella et al. 2015); and in schools, increased numbers of pupils with English as a second language doesn’t have any negative impact on levels of achievement for native English speaking students (Geay et al. 2013). If anything, pupils in schools with lots of non-native speakers do slightly better.”
  • Prices: “Frattini (2008) analyses the impact on tradable, non-tradable goods and services prices across UK regions over the period 1995-2006 and shows that immigration is associated with a fall in prices for non-tradeable goods and services, but a rise in the price of tradeables.  Sá (2015) focuses on the impact on housing prices in UK local authorities from 2003 to 2010 and shows that immigration actually reduces house prices at a local level, since natives leave the area in response to high immigrant inflows; although this does not imply, of course, that immigration does not overall exert upward pressure on house prices at a national level.”

So what are the likely results of Brexit? He concludes,

The conclusion is that the reductions in migration resulting from Brexit are likely to have a significant adverse impact on UK productivity and GDP per capita. The broad scenarios (not forecasts) we depict imply that the negative impacts on per capita GDP will be significant, potentially approaching those resulting from reduced trade.  By contrast, the increase in low-skilled wages resulting from reduced migration is expected to be, if at all, relatively modest.

Does Diversity Lead to Distrust?

My article on the LDS Church and immigration should be out–hopefully by the end of the month–in the next issue of BYU Studies Quarterly. In it, I tackle five common objections to immigration:

  • Immigrants “steal” native jobs.
  • Immigrants depress native wages.
  • Immigrants undermine host country culture and institutions.
  • Immigrants are a fiscal burden and increase the welfare state.
  • Immigrants are criminals and terrorists.

But one objection that is gaining more steam is that diversity leads to distrust. This isn’t without some empirical backing (though this is likely unknown to most of those making the argument). According Bloomberg‘s Noah Smith, famed political scientist Robert Putnam found evidence over a decade ago that ethnic diversity via immigration leads to a decrease in trust (social capital).[ref]A later analysis of Putnam’s study found that it was only white people whose trust decreased.[/ref] Smith continues,

Image result for distrustPutnam isn’t alone in his finding — studies in Denmark, the United Kingdom, the Netherlands, and Europe have found similar results.

But this doesn’t mean that it’s a scientific fact that diversity decreases trust. There are plenty of studies that don’t support Putnam’s conclusion — or even find the opposite. For example, another study in the UK found no correlation between diversity and trust, while a third found that the negative relationship disappears after controlling for economic variables. Another Europe-wide study found no correlation, while yet another found that diversity is actually associated with a long-term increase in trust.

A casual look at international survey measures will show that — as [Megan] McArdle notes — ethnic homogeneity is no guarantee of a trusting society. Among rich countries, Scandinavia is the most trusting region, but diverse, immigrant-friendly places like Canada, Australia, New Zealand and Singapore actually score higher than homogeneous, low-immigration countries like South Korea, Russia, Japan and Poland…What’s more, even if diversity does decrease trust, the effect might not be that strong. Economist Bryan Caplan examined Putnam’s research and found that even if the sociologist’s numbers are completely correct, huge changes in diversity would reduce measures of trust only by a few percent.

An economist would also note that aside from simply asking people survey questions, researchers should look at how people actually behave. Ethnic diversity in Southern California has been linked to lower crime and higher home values. Studies reliably find that immigration reduces crime in the U.S., and this also appears to be true in Canada. Meanwhile, recent evidence on migration patterns show that Americans have tended to move to diverse neighborhoods since around 1990 — voting with their feet rather than their survey answers.

Furthermore, there is “a theory that prolonged, positive contact with people of other races reduces racial tensions. This “contact hypothesis” has plenty of support in the literature — studies show that having college dorm-mates of a different race, or serving in an integrated military, reduces discrimination. This suggests that over the long term, diverse neighborhoods will have a positive impact on society-wide trust. A recent survey of 90 papers found…[that] an increase in diversity might initially cause people to avoid interacting with their strange new neighbors, [but] over the long term it makes them realize that people of other races aren’t so scary after all.” Elsewhere, Smith points to research that

seems to show that Americans are increasingly open to living in diverse neighborhoods. A 2016 paper by the National University of Singapore’s Kwan Ok Lee finds that since 1990, white flight and white avoidance of black neighborhoods has decreased dramatically. In fact, white Americans in recent decades have tended to move toward diversity rather than away from it.

Urban economist Joe Cortright, blogging at City Observatory, summarizes the results. Lee looks at U.S. Census tracts, neighborhoods that on average have about 4,000 residents. In addition to the racial makeup of neighborhoods, she was able to track where individuals moved to and from.

Lee’s first finding is that American neighborhoods are becoming more diverse. Majority-white neighborhoods were about two-thirds of the total from 1970 to 1990, but during the next two decades that number was only 57 percent. The probability of single-race neighborhoods becoming mixed increased substantially. Meanwhile, a small but growing number of neighborhoods have a substantial numbers of whites, blacks and Hispanics or Asians.

…From 1990 to 2010, only one-fifth of mixed black-white neighborhoods became segregated — only half the rate of re-segregation that prevailed in earlier decades. White flight is still happening in some places, but much less than before. Meanwhile, multiracial neighborhoods tend to be the most stable — once a neighborhood becomes multiracial, Lee found that it had a 90 percent chance of remaining that way for at least 20 years.

Lee’s final finding is the most striking. She found that once Americans move to a mixed-race neighborhood, they tend to either stay there, or move to another mixed neighborhood. This is true for both white and black Americans. In other words, neighborhood diversity isn’t just a result of changing demographics, but of Americans choosing to live near people of other races.

Lee’s finding confirms the results of other studies. Despite much alarm over gentrification, it turns out that gentrified neighborhoods don’t lose their poor and minority populations. According to a 2009 study by Columbia University urban planning professor Lance Freeman, gentrification actually tends to increase diversity in the long term.

What about at the state level? There, diversity is increasing as well. Demographer William H. Frey has chronicled how both whites and minorities have been moving to diverse states like Virginia, Nevada, North Carolina, Colorado, Georgia and Washington. Texas, a majority-minority state, is still a leading destination for white migration.

Residential diversity isn’t the only kind of integration, of course. On other measures, the evidence is mixed — interracial marriage has climbed dramatically, but public schools have become more segregated by race. Meanwhile, the average numbers described in studies like Lee’s and Freeman’s mask considerable white flight in some areas.

And the most important caveat is the political one. Fear of increasing diversity at the national level was strongly correlated with support for President Donald Trump. Even if a majority of Americans are embracing the country’s increasingly diverse demographics, a strong and vocal minority is resisting the change with every weapon at its disposal.

Regarding this last point, I write in my upcoming paper,

A particularly interesting aspect of public attitudes toward immigration is that of political ignorance. Multiple studies have shown that political ignorance is rampant among average voters, and this holds true when it comes to immigration policy. As legal scholar Ilya Somin explains, “Immigration restriction . . . is one that has long-standing associations with political ignorance. In both the United States and Europe, survey data suggest that it is strongly correlated with overestimation of the proportion of immigrants in the population, lack of sophistication in making judgments about the economic costs and benefits of immigration, and general xenophobic attitudes toward foreigners. By contrast, studies show that there is little correlation between opposition to immigration and exposure to labor market competition from recent immigrants.” One pair of economists found that those voting to leave the European Union in the Brexit referendum, who were motivated largely by a desire to restrict immigration, “were overwhelmingly more likely to live in areas with very low levels of migration.” Similarly, voters who supported Donald Trump during the US election were more likely to oppose liberalizing immigration laws (even compared to other Republicans), but least likely to live in racially diverse neighborhoods. In short, both political ignorance and lack of interaction with foreigners tend to inflame anti-immigration sentiments. These sentiments are what George Mason University economist Bryan Caplan refers to as antiforeign bias: “a tendency to underestimate the economic benefits of interaction with foreigners.” In fact, economists take nearly the opposite view from the general public on immigration.

New RAND Report: Gun Control

From Vox,

RAND’s extensive report does not make any sweeping declarations about gun policy. It does, however, make clear that gun control research is very limited, calling on Congress to lift the NRA-backed funding freeze. It argues that this freeze has, by making it difficult to conduct better studies, led to a confusing empirical environment, where it’s easy for groups on both sides of the debate to cite shoddy work that supports their prior beliefs.

“The studies that have been done often reach opposite conclusions to each other,” Andrew Morral, the head of RAND’s gun policy initiative, told me. The lack of thorough research, he added, “creates this kind of fact-free environment in which people can cherry-pick any study that happens to support what their priors are on the effects of the law.”

Morral’s team spent two years reviewing US-based studies published over the past several decades, pulling out the most rigorous to try to find some “incontrovertible truths.” RAND concluded that, first and foremost, far more research is necessary. “Many of the matters that people disagree on when they disagree on gun policy have not been rigorously studied in ways that produce reasonably unambiguous results,” Morral said.

But there were some things that could be gleaned from the available evidence. While RAND as a nonpartisan group avoided any sweeping policy conclusions in its analysis, its review does seem to point in a direction, based on my own reading: More permissive gun policies lead to more gun deaths, while more restrictive policies lead to fewer gun deaths. Coupled with other evidence in this area, that supports the idea that more guns lead to more gun deaths.

A chart, based on RAND data, looking at the studied outcomes of different gun policies.

Vox summarizes,

On the gun control front, there’s moderate evidence that background checks reduce suicide and violent crime, limited evidence that prohibitions associated with mental illness reduce suicide, moderate evidence that those prohibitions reduce violent crime, and supportive evidence that child-access prevention laws reduce suicides and unintentional injuries and deaths.

Meanwhile, there’s limited evidence that concealed carry laws increase violent crime and unintentional injuries and deaths. And there’s moderate evidence that “stand your ground” laws — NRA-backed measures that expand when someone can use a gun or other weapons to defend himself — increase violent crime.

If you put this all together, it suggests that restrictive laws seem to lead to fewer gun deaths, while the permissive laws seem to lead to more gun deaths.

…The think tank found supportive evidence for child access prevention laws reducing suicide and unintentional injuries and deaths. And Morral agreed that the evidence is stronger on background checks and prohibitions associated with mental illness than other gun policies.

As for the correlation between gun availability and gun deaths, “RAND takes a more skeptical view. The report argued that it can be hard to disentangle the relationship between more guns and more gun deaths: Is it the abundance of guns leading to more gun deaths, or are people seeing a lot of violence in their communities and reacting to it by stocking up on guns to protect themselves? RAND concluded that there’s just not enough in the research it reviewed to solve this chicken-or-egg scenario.” In short, “more research is needed…Federal funding could go to surveys and on-the-ground research that could help address the gaps. The funding is something, however, that pro-gun groups like the NRA have worked against for years. And so far, their tactics have worked — keeping the federal freeze in place. So although there’s evidence that some gun control measures could work, we by and large remain blind to what specific solutions would work best and what all of their effects would be.”

Does Family Structure Really Matter When It Comes to Poverty?

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Not according to a recent op-ed in The New York Times. The authors–sociologists all–argue based on findings from their new study[ref]Working paper version here.[/ref]

that reducing single motherhood would not substantially reduce poverty. Single-mother families are a surprisingly small share of our population. Among households headed by working-age adults, 8.8 percent of people lived in single-mother households in 2013 — the most recent year we were able to analyze. The share of people in single-mother households actually declined from 10.5 percent in 1980 and has increased only modestly since 18=970, when it was 7.4 percent. True, compared with other rich democracies, America does have a relatively high portion of families headed by single mothers. Nevertheless, we still fall below Ireland and Britain and are quite similar to Australia and Iceland.

Because fewer people are in single-mother families than you’d think, even large reductions in single motherhood would not substantially reduce poverty. 

However, sociologist W. Bradford Wilcox takes issue with the way the NYT piece presents the evidence. He explains,

Nobody…is claiming that reducing the number of single-mother households will lead to lower poverty rates among elderly or childless men and women. The concern among poverty scholars has always been that single motherhood leads to higher rates of child poverty. And there is no denying the close connection between single parenthood and child poverty in America.

To begin with, children living in single-mother families are about five times as likely to be poor, compared with children living in married, two-parent families. This is clear in a recent analysis of trends in the official poverty rate from our colleague Ron Haskins at the Brookings Institution.

Moreover, research done by one of us, Isabel Sawhill, indicates that if the share of children in single-parent families had remained steady at the 1970 level, then the current child-poverty rate would be cut by about one-fifth, even after adjusting for the fact that single mother have different characteristics from married mothers. In other words, dramatic increases in single parenthood — from about 12 percent of children in 1970 to about 27 percent now — more recently have played an important role in fueling child-poverty rates.

Single parenthood is not the factor driving child poverty in America, but it isa factor.

What about Europe?

Well, it turns out that even in Europe children are more likely to be poor if they are living in a family headed by a single parent. Research done by social scientists Janet Gornick and Markus Jäntti indicates that children being raised by a single parent are about three times as likely to be living in a poor family as children being raised by two parents, even after accounting for generous welfare policies in Europe.

In fact, this is true even in Scandinavia. Relative to children in two-parent families, children in single-mother homes are about three times as likely to be poor in Denmark and Sweden, more than four times as likely to be poor in Norway, and nearly five times as likely to be poor in Finland, after taking into account their welfare policies.

Now, it’s true that the levels of child poverty in Scandinavia are markedly lower than those in the United States — indeed, about 75 percent lower because of their social policies. And it’s also true that the unique poverty risk associated with single parenthood generally goes away when you control for other factors, such as age, education, and employment, as Brady and his colleagues have done. What that misses is that mother-headed families are more likely to be formed as the result of an unplanned birth outside of marriage or a committed relationship, and that these unexpected births tend to occur at young ages, to interrupt a young woman’s education, and to make it less likely that she will ever marry or form a stable partnership and have the second income that such a partnership makes possible.

In other words, even today, one reason that two parents are generally better than one parent, economically speaking, is that having two parents in the home dramatically increases the odds not only that at least one parent is working full-time but also that there are two parents working on behalf of the children. And this is true even in Europe.

What’s more,

The social science tells us that children raised by single parents are significantly more likely to have children young, to drop out of high school, and to work less as young adults. Not surprisingly, the children of single-parent families are more likely to end up poor as young adults.

…Indeed, new research from economists Melissa Kearney and Phillip Levine indicates that young adults are at least ten percentage points less likely to be poor at age 25 if they were born to married parents, as opposed to an unmarried mother. These effects are especially strong for children born to mothers in the middle of the educational and age distribution — that is, for “children of mothers with high school degrees and mothers in their early/mid-20s.” In other words, in America at least, the long arm of single parenthood seems to extend into adulthood, increasing the likelihood that children of single parents will be poor as adults, compared with adults who were raised in intact, two-parent families.

Wilcox concludes, “It’s useful to point out that family structure is not destiny. But the evidence suggests it remains important and shouldn’t be dismissed as one important factor affecting children in particular.”

 

Does Gender Egalitarianism Reduce the STEM Field Gender Gap?

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Apparently not, according to a new study. Similar to findings in cross-country studies regarding gender differences in psychological traits, this study finds,

that, paradoxically, countries with lower levels of gender equality had relatively more women among STEM graduates than did more gender-equal countries. This is a paradox, because gender-equal countries are those that give girls and women more educational and empowerment opportunities and that generally promote girls’ and women’s engagement in STEM fields (e.g., Williams & Ceci, 2015).

In our explanation of this paradox, we focused on decisions that individual students may make and decisions and attitudes that are likely influenced by broader socioeconomic considerations. On the basis of expectancy-value theory (Eccles, 1983; Wang & Degol, 2013), we reasoned that students should at least, in part, base educational decisions on their academic strengths. Independently of absolute levels of performance, boys on average had personal academic strengths in science and mathematics, and girls had strengths in reading comprehension. Thus, even when girls’ absolute science scores were higher than those of boys, as in Finland, boys were often better in science relative to their overall academic average. Similarly, girls might have scored higher than boys in science, but they were often even better in reading. Critically, the magnitude of these sex differences in personal academic strengths and weaknesses was strongly related to national gender equality, with larger differences in more gender-equal nations. These intraindividual differences in turn may contribute, for instance, to parental beliefs that boys are better at science and mathematics than girls (Eccles & Jacobs, 1986; Gunderson, Ramirez, Levine, & Beilock, 2012). 

We also found that boys often expressed higher self-efficacy, more joy in science, and a broader interest in science than did girls. These differences were also larger in more gender-equal countries and were related to the students’ personal academic strength.

…We propose that when boys are relatively better in science and mathematics while girls are relatively better at reading than other academic areas, there is the potential for substantive sex differences to emerge in STEM-related educational pathways. The differences are expected on the basis of expectancy-value theory and are consistent with prior research (Eccles, 1983; Wang & Degol, 2013). The differences emerge from a seemingly rational choice to pursue academic paths that are a personal strength, which also seems to be common academic advice given to students, at least in the United Kingdom (e.g., Gardner, 2016; Universities and Colleges Admissions Service, 2015).

The greater realization of these potential sex differences in gender-equal nations is the opposite of what some scholars might expect intuitively, but it is consistent with findings for some other cognitive and social sex differences (e.g., Lippa, Collaer, & Peters, 2010; Pinker, 2008; Schmitt, 2015). One possibility is that the liberal mores in these cultures, combined with smaller financial costs of foregoing a STEM path…amplify the influence of intraindividual academic strengths. The result would be the differentiation of the academic foci of girls and boys during secondary education and later in college, and across time, increasing sex differences in science as an academic strength and in graduation with STEM degrees (pgs. 10-11).

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Are There Effective Gun Control Laws?

Guns are once again a hot topic with the latest shooting in Florida. I’ve written about gun control before. Ultimately, is there any evidence that gun control laws work? If so, which ones? According to a 2016 study in The Lancet,

The three laws most strongly associated with reduced firearm mortality were universal background checks for firearm purchase, background checks for ammunition, and requiring firearm identification by either microstamping or ballistic fingerprinting. We showed that federal-level implementation of these three laws would substantially reduce overall national firearm mortality. Finally, the three laws most strongly associated with reduced homicide-specific firearm mortality were universal background checks for firearm purchase, background checks for ammunition, and firearm identification; firearm identification was associated with reduced suicide-specific firearm mortality (pgs. 7-8).

Scientific American has a useful rundown of other laws, including:

  • Permits: “An effective solution would be to require people to apply, in-person, at local law enforcement agencies for gun purchase permits…In a 2009 study involving 53 cities Webster and his colleagues found this approach, which gives law enforcement officials discretion about who they gave permits to, was linked with a 68 percent reduced risk of guns being diverted to criminals post-sale. But after Missouri repealed its permit-to-purchase handgun law in 2007, firearm homicide rates increased by 25 percent, a jump that was not seen in neighboring states or the rest of the country, Webster’s team reported. Missouri’s repeal was also linked with a 52 percent increase in handgun murders of law enforcement officers in the line of duty.”
  • Ban anyone convicted of a violent crime from gun purchases: “In 1991 [California] passed a law preventing individuals with violent convictions from buying guns. And in a study published in JAMA The Journal of the American Medical Association in 2001 Wintemute and his colleagues studied its effects. Convicts who were allowed to buy guns before the law passed were nearly 30 percent more likely to be arrested later for a gun crime or other violent act compared with convicts who tried, but were unable, to buy guns after the law was passed. “That’s a big effect,” Wintemute says.”
  • Make all serious domestic abuse offenders surrender guns: “Some states are now passing state laws requiring individuals convicted of domestic violence crimes to surrender their firearms; an October 2017 study found that these “relinquishment” laws are nearly 50 percent more effective than non-relinquishment laws at reducing intimate partner violence. It would also help a lot to restrict guns from people with domestic violence restraining orders against them. In a 2010 study Webster and his colleagues found restrictions based on restraining orders were associated with a 19 percent reduction in the risk for intimate partner homicide in large U.S. cities. Such restrictions are in place in 35 states and Washington D.C. These changes are important because intimate partner violence is strongly tied to mass shootings: A 2015 report by the Congressional Research Service found more than one fifth of all public mass shootings between 1999 and 2013 were precipitated in part by domestic disputes. During this period there were also 127 nonpublic mass shootings in the U.S. that involved an individual killing at least four family members. Keeping people prone to domestic violence away from firearms would prevent many massacres.”
  • Temporarily ban alcohol abusers from firearms: “Federal law prohibits people who are addicted to and/or unlawfully using controlled substances from owning guns. But recent data suggest some nine million U.S. firearm owners also binge drink, which is a specific medical problem involving abuse of the substance alcohol. Wintemute’s research suggests people with DUIs (driving under the influence) are four to five times as likely as people with no criminal record to be arrested for a violent crime in the future. Based on these data, Wintemute proposes a temporary ban on gun possession among individuals who have had, in the past five years, two or more convictions for DUI or another crime that indicates alcohol abuse.”

Many proposed laws are already in place. Nonetheless, the more you know.[ref]Check out this post at Vox too.[/ref]

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