What Are the Effects of Economic Freedom at the State Level?

A brand new paper from the Mission Foods Texas-Mexico Center at SMU:

In this paper, we examine the relationship between institutional quality and bilateral trade patterns between Mexican states and U.S. states. We are contributing to the small, but growing, literature which uses gravity models to examine economic exchange at the subnational level (see Havranek and Irsova 2017 for a recent review of this literature). We are the first to explicitly incorporate institutional quality into a model of trade between the U.S. states and Mexican states, and the first to examine these sorts of relationships between the U.S. and Mexican states more generally. Poor institutions can be viewed as a cost for potential trading partners, and economic theory tells us that when an action becomes more costly, less of that action will be undertaken. Conversely, when an action becomes less costly, more of that action will be undertaken. We find that states with better institutional environments as measured by the Economic Freedom of North America index do, indeed, realize higher levels of trade. We also contribute to the literature examining trade border effects (Hillberry and Hummels 2002; Chen 2004; Head and Ries 2001) by examining the impact the border has on trade between the U.S. states and Mexican states. Finally, we use our dataset to examine the relationship between trade volume and three measures of economic prosperity (pg. 6).

The authors lay out their key findings and policy recommendations:

Economic institutions matter.

Minimum Wage & Low-Skilled Workers: More Evidence

Image result for minimum wage

Ready for yet another post on the minimum wage? From a recent paper in the Journal of Public Economics:

Our empirical analysis uses the fact that the 2007 through 2009 increases in the federal minimum wage were differentially binding across states. We base our “bound” designation on whether a state’s January 2008 minimum wage was below $6.55, rendering it bound by the entirety of the July 2009 increase. In the states we describe as “unbound,” the effective minimum wage rose, on average, by $1.42 between 2006 and 2012. In the states we describe as “bound,” the effective minimum wage rose, on average, by $2.04. Of the long-run differential, $0.58 took effect on July 24, 2009.

We use monthly, individual-level panel data from the 2008 panel of the Survey of Income and Program Participation (SIPP) to implement a combination of difference-in-differences and triple difference research designs. Because we use longitudinal employment records with data on wage rates, our implementation of these research designs has two key advantages. First, we are able to pinpoint “target” groups more intensely affected by minimum wage increases than the analysis groups in many studies. Second, we are able to pinpoint workers who were not directly affected yet, as evidenced by their wage rates, were only moderately more skilled than the “target” workers. We incorporate this second group of workers into our analysis as a “within-state control” group. That is, we use this group to construct a set of counterfactuals that proxy for otherwise unobserved shocks to the low-skilled labor market (pg. 53).

What do they find?:

  • “We find that increases in the minimum wage significantly reduced the employment of low-skilled workers. By the second year following the $7.25 minimum wage’s implementation, we estimate that targeted individuals’ employment rates had fallen by 6.6 percentage points (9%) more in bound states than in unbound states. The implied elasticity of our target group’s employment with respect to the minimum wage is −1, which is large within the context of the existing literature” (pg. 54).
  • The average monthly incomes of low-skilled individuals decreased. “Relative to low-skilled workers in unbound states, targeted individuals’ average monthly incomes fell by $90 over the first year and by an additional $50 over the following 2 years. While surprising at first glance, we show that these estimates can be straightforwardly explained through our estimated effects on employment, the likelihood of working without pay, and subsequent lost wage growth associated with lost experience. We estimate, for example, that targeted workers experienced a 5 percentage point decline in their medium-run probability of reaching earnings greater than $1500 per month” (pg. 54).

The researchers conclude,

We use data from the SIPP to investigate the effects of the 2007 to 2009 increases in the federal minimum wage on the employment and income trajectories of low-skilled workers. We estimate that the minimum wage increases enacted during the Great Recession had negative effects on affected individuals’ employment, income, and income growth. The SIPP data suggest that this period’s minimum wage increases reduced aggregate employment rates by at least half of a percentage point in states that were fully bound by the federal minimum wage’s rise from $5.15 to $7.25 (pg. 67).

Stuff I Say at School – Part VI: Economic Freedom & Corruption

The Assignment

Response to a group’s summary of Jakob Svensson’s “Eight Questions About Corruption.”

The Stuff I Said

The Fraser Institute’s Economic Freedom of the World (EFW) Index, published in its annual Economic Freedom of the World reports, defines economic freedom based on five major areas: (1) size of the central government, (2) legal system and the security of property rights, (3) stability of the currency, (4) freedom to trade internationally, and (5) regulation of labour, credit, and business. According to its 2018 report (which looks at data from 2016), countries with more economic freedom have substantially higher per-capita incomes, greater economic growth, and lower rates of poverty. Drawing on the EFW Index, Georgetown political philosophers Jason Brennan and Peter Jaworski point to a strong positive correlation between a country’s degree of economic freedom and its lack of public sector corruption.

Granted, a lack of corruption could very well give rise to market reforms and increased economic freedom instead of the other way around. However, recent research on China’s anti-corruption reforms suggests that markets may actually pave the way for anti-corruption reforms. Summarizing the implications of this research, Lin et al. explain,

Reducing corruption creates more value where market reforms are already more fully implemented. If officials, rather than markets, allocate resources, bribes can be essential to grease bureaucratic gears to get anything done. Thus, non-[state owned enterprises’] stocks actually decline in China’s least liberalised provinces – e.g. Tibet and Tsinghai – on news of reduced expected corruption. These very real costs of reducing corruption can stymie reforms, and may explain why anticorruption reforms often have little traction in low-income countries where markets also work poorly. China has shown the world something interesting: prior market reforms clear away the defensible part of opposition to anticorruption reforms.Once market forces are functioning, bribe-soliciting officials become a nuisance rather than tools for getting things done. Eliminating pests is more popular than taking tools away … A virtuous cycle ensues – persistent anticorruption efforts encourage market-oriented behaviour, which makes anticorruption reforms more effective, which further encourages market oriented behaviour.

Interesting enough, there is some evidence that suggests that more government hands in the pies increases corruption. For example, a 2017 study found that larger municipality councils in Sweden result in more corruption problems. A 2009 study found that more government tiers and more public employees lead to more bribery. Finally, a 2015 study showed that high levels of regulation are associated with higher levels of corruption (likely because of regulatory capture).

Do Most Americans Really Want What They Say They Want?

I hear a lot about how “most Americans” are in favor of “Policy XYZ.” The problem is that the social science shows that most Americans don’t know what they’re talking about. Do opinions change with more information or when costs are introduced? Two surveys from the Cato Institute seem to answer this in the affirmative.

The first is on federal paid leave. Seventy-four percent of the 1,700 Americans surveyed “a new federal government program to provide 12 weeks of paid leave to new parents or to people to deal with their own or a family member’s serious medical condition…Support slips and consensus fractures for a federal paid leave program, however, after costs are considered.” A 20 percentage point drop in support occurs when a $200 price tag is attached. Less than half are willing to pay $450 more in taxes for the program. When other potential costs are introduced (e.g., smaller future raises, reduction in other benefits, women less likely to be promoted, cut funding to other government programs), the majority of Americans find themselves opposing the program.

Less than half of men would be willing to pay even $200 more, while 55% of women would still be willing to pay $450 more. Support for the program drops across all political parties as costs are introduced, with 60% of Democrats still willing to fork over $1,200 a year to implement it (but only 22% of Republicans and 45% of Independents). “In sum,” writes Cato researcher Emily Ekins, “Democrats have a much higher tolerance threshold for taxes than the average American.”

Another survey looked at support for the Affordable Care Act’s pre-existing condition regulation. Out of the 2,498 Americans questioned, 65% support this aspect of the ACA. However, when costs are introduced, support drops. Furthermore, wealthier Americans are more willing to entertain trade-offs than lower-income ones.

Thomas Sowell has written, “There are no solutions; there are only trade-offs.” What “most Americans” want depends on whether or not trade-offs are kept in the dark.

The Economic Consequences of Tariffs

From a recent working paper:

We use impulse response functions from local projections on a panel of annual data spanning 151 countries over 1963-2014. The main analysis on aggregate data is complemented with industry-level data.

Our results suggest that tariff increases have an adverse impact on output and productivity; these effects are economically and statistically significant. They are magnified when tariffs are used during expansions, for advanced economies, and when tariffs go up. We also find that tariff increases lead to more unemployment and higher inequality, further adding to the deadweight losses of tariffs. Tariffs have only small effects on the trade balance though, in part because they induce offsetting exchange rate appreciations. Finally, protectionism also leads to a decline in consumption; this, together with our findings, suggests that tariffs are bad for welfare.

All this seems eminently sensible and bolsters the arguments that mainstream economists make against tariffs; our results can be regarded as strong empirical evidence for the benefits of liberal trade. And given the current global context, we take special note of the negative consequences when advanced economies increase tariffs during cyclical upturns (pg. 25-26).

Does Populism Reduce Economic Inequality?

The above comes from a recent study of The New Populism project. This reduction in economic inequality may lead some populist supporters to feel vindicated. However, the study continues by pointing out that “the fiscal policies of populists are less progressive than non-populists. This is what we might have expected; they are not reducing inequality as a result of government taxation or welfare structures.” The mechanism remains unknown, “maybe minimum wage policies, maybe moves towards formalization of the labour force, or limits on income generation of the very wealthy (or even possibly in the case of Venezuela, the very wealthy leaving, thereby reducing overall levels of market inequality). But they do reduce overall levels of market inequality” (pg. 5).

However, this isn’t the only effect of populists:

  • Populist leaders increase indirect (regressive) taxation.
  • Populism has no real impact on corruption, despite corruption often bringing populists to power.
  • “[P]opulist chief executives are more likely to infringe on the freedom and fairness of the electoral process than their non-populist counterparts” (pg. 14).
  • “[B]oth right and left populist chief executives seem more likely to embark on a mission to cut back on civil liberties” (pg. 15).
  • “We confirm a strong, negative effect of populism on press freedom. Not every decline can be attributed to populists, but almost every strong or moderate populist registers some decline” (pg. 17).
  • “Finally, populism in government is often associated with the centralization of power under the chief executive” and the erosion of executive constraints (pg. 18-19).

So giving power over to populist authoritarians who undermine democratic institutions and civil liberties is one successful avenue to economic equality. The others, according to historian Walter Scheidel, are “mass-mobilization warfare, violent and transformative revolutions, state collapse, and catastrophic epidemics. Hundreds of millions perished in their wake, and by the time these crises had passed, the gap between rich and poor had shrunk.”

What Was the Cost of Trump’s Trade War in 2018?

A new working paper confirms what economists have been saying about tariffs all along:

Economists have long argued that there are real income losses from import protection. Using the evidence to date from the 2018 trade war, we find empirical support for these arguments. We estimate the cumulative deadweight welfare cost (reduction in real income) from the U.S. tariffs to be around $6.9 billion during the first 11 months of 2018, with an additional cost of $12.3 billion to domestic consumers and importers in the form of tariff revenue transferred to the government. The deadweight welfare costs alone reached $1.4 billion per month by November of 2018. The trade war also caused dramatic adjustments in international supply chains, as approximately $165 billion dollars of trade ($136 billion of imports and $29 billion of exports) is lost or redirected in order to avoid the tariffs. We find that the U.S. tariffs were almost completely passed through into U.S. domestic prices, so that the entire incidence of the tariffs fell on domestic consumers and importers up to now, with no impact so far on the prices received by foreign exporters. We also find that U.S. producers responded to reduced import competition by raising their prices.

Our estimates, while concerning, omit other potentially large costs such as policy uncertainty as emphasized by Handley and Limão (2017) and Pierce and Schott (2016). While these effects of greater trade policy uncertainty are beyond the scope of this study, they are likely to be considerable, and may be reflected in the substantial falls in U.S. and Chinese equity markets around the time of some of the most important trade policy announcements (pg. 22-23).

What Drives Racial and Ethnic Inequality Today?

A brand new study offers some interesting insights into the question. Kay Hymowitz summarizes,

Using Census and ACS data, [John Iceland] shows that whites were the least likely of all groups to be poor throughout the decades studied (though, notably, their poverty rates inched up after 1980.) Although blacks and American Indians have become markedly less poor since 1959, they remain the groups with the highest— and fairly similar—odds of living in poverty. Hispanics never had poverty rates as high as those for American Indians and Blacks in the years studied, but their rates today, at 22.5%, are only marginally lower than those poorer groups (26.1 and 25%, respectively).

Iceland’s calculations also confirm that we are a much richer nation than we were in 1959. Affluence, defined as family income-to-poverty ratios five times the poverty threshold (or $120,180 as of 2015), has grown for all demographic categories, though at a faster pace for whites and Asians than others. (This “affluence” may strike New Yorkers and renters in other expensive cities as dubious, though the author checked his findings against alternative measures of poverty and affluence; they all showed the same basic trends.) 

Despite the massive declines in poverty, what are the main factors behind continuing inequality?

Taking the groups as a whole, he finds immigrant status to be the characteristic that best correlates with poverty, and education the trait most associated with affluence. However, the features most closely related to poverty and affluence differ among groups in fascinating ways. At a time of renewed concerns about racial inequality, the most striking story is for blacks. African Americans are more than three times as likely to be poor than whites without controls. With controls, the gap declines considerably—to 1.71.  Iceland estimates that female-headed households can now explain about one-third of the black-white poverty difference, age comes in second at 16%, and education at 15%; all-in-all, the three characteristics can explain two-thirds of the poverty gap between blacks and whites. 

Iceland’s findings on trends in minority poverty and affluence are consistent with a narrative of progress in racial relations. In 1959, family structure, education, and age explained less than half of the poverty and affluence gap between blacks and whites, for example; most of the divide was due to “unobservables” like discrimination, neighborhood, and social networks. Iceland confirms earlier research showing black and American Indian poverty plummeting in the 1960s; 57% of African-Americans and 60.3% of Indians started that decade poor. By the 1970s the number was 35.5% and 35.5%. Because the strong economy of the 1960’s lifted all ethnic and racial boats during the 1960s, black, Hispanic, Asian, American Indian, and white, however, the decade ended with inequality between the various groups more or less unchanged. In sum, between civil rights laws and economic growth, minority groups were able to make substantial economic progress in the 1960s, though not enough to catch up with whites.

But as discriminatory barriers fell, individual and family characteristics became more crucial for economic mobility. The author shows that “observables,” including family structure, age, and education, have considerably more explanatory power for poverty and affluence gaps today than they did in 1959, while unobservable factors, like discrimination, though still significant for blacks and American Indians, have nevertheless become less so.

What about other groups?

Education differences have the largest effect on the Hispanic and white poverty gap and that effect has grown over time; age and immigrant status play strong supporting roles. Education has been the prime mover for affluent Hispanics and American Indians; intact families, fewer children, and relocation to metropolitan areas also helped the latter group improve their outcomes.

Asians are the most educated of any group as well as the most stably married. These traits help explain the 35.8% of Asians who are affluent (vs. 32.9% of second-place whites) as well as why, though they have higher poverty rates than whites mostly due to immigration, they are still somewhat “protected” against poverty.

Some limitations and cautions:

It could be that family structure itself is partly a proxy for discrimination. If black men have trouble finding jobs because of prejudice, they are inevitably less “marriageable.” He notes as well that the data available has serious limitations. “Asian” was not a Census category until 1980; before that, people checked the Chinese, Japanese, Filipino, or Hawaiian box. It’s worth noting that Asian remains an awkward grouping, encompassing people of very different histories and cultures; in measuring affluence, Iceland shows, the Vietnamese don’t look at all like other Asians. “Hispanic” is similarly problematic. With controls, Cubans are as likely as whites to be affluent; that’s far from the case with other Hispanic subgroups.

Management Still Matters

I’ve said it before: management matters. I even published a paper on it. Harvard’s Raffaella Sadun lays out the case once more:

What we found was quite consistent across sectors and countries, namely a large and significant correlation between management and organizational performance. Figure 1 (Source), for example, shows the relationship between management and a variety of metrics for firm performance—including productivity, profitability, growth, and survival—among US manufacturing plants.

The correlation between management and performance appears to be similar across countries and (to our surprise) even in “public” sectors such as health care and education. For example, well-run hospitals appear to have lower mortality rates from Acute Myocardial Infarction (AMI, i.e heart attacks), and well-run schools enjoy better test scores among their pupils.

In subsequent research, my colleague Nick Bloom and colleagues set up a management “experiment,” in which a random set of Indian manufacturing firms were provided with a “dose” of management consultancy and compared to a control group. Their experiment showed that the relationship between management and firm performance appears to be causal.

Other researches have argued that the role of management may extend well beyond the performance of individual firms, and extend to whole economies. For example, Pellegrino and Zingales argue that people management gaps among Italian firms may be responsible for the weak productivity performance experience by the country since the early 90s by delaying the adoption of complementary and productivity enhancing technologies. In a recent paper, Schivardi and Schmitz extend this argument to Southern Europe more generally.

She identifies four major mechanisms for why management practices are so diverse across different countries:

1. There seem to be large informational barriers. Those prevent managers from having a clear understanding of the quality of their own practices, as well as the potential benefit that modern management practices could accrue to their organization. For example, when we asked managers to self-evaluate the quality of their own practices on a scale between 1 and 10, most managers rated themselves an 8. Their own scores were typically uncorrelated with our arguably more objective management score. 

2. Management adoption is strongly related to the education of the workforce, which, in turn, is shaped by differences in skill supply. This is not surprising, given the fact that many “best-practices” require significant numeracy and literacy skills.

3. Even when well-informed and with plenty skills available, managers may not be motivated to invest in new management practices, as the adjustment may be costly to the firm or to them personally (for example, relying on management practices may require less of their direct and personalized control, references). Research has shown the presence of a correlation between competitive pressure and management quality, which is in line with the classic idea in economics that competition reduces organizational slack.

4. Introducing new management practices in a firm requires a substantial buy-in from the employees, as its adoption rests on significant co-investments (i.e. learning new behavioral routines) that are hard to monitor and incentivize through standard contracting solutions. However, organizational frictions may prevent such co-investments from happening. For example, Susan Helper and Rebecca Henderson attribute GM’s decline and inability to fully implement productivity-enhancing managerial practices such as lean management to a fundamental lack of trust between managers and employees (employees suspected that the productivity improvements generated by lean would result in layoffs rather than generalized gains). This latter category points to the importance of softer aspects of organizations, such as corporate culture and leadership behavior, which may be able to overcome this type of resistance to change.

She concludes,

While much remains to be done, the evidence so far suggest that variations in this key factor of production may have large implications for performance, at both the firm and country level. Understanding why management quality varies across organizations will help us advance the field and develop better policies for improving management and productivity.