Stuff I Say at School – Part X: Direct Effects of Trade on Poverty

This is part of the Stuff I Say at School series.

The Assignment

A critical literature review of trade openness on poverty. This post consists of section on direct effects of trade on poverty as well as the conclusion.

The Stuff I Said

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The majority of studies on openness and poverty concentrate on trade’s effects on economic growth and, consequently, growth’s effects on poverty. As Panagariya (2019, pg. 136) notes, this means that “the literature directly linking trade openness and poverty is sparse.” Nonetheless, a few more recent studies have attempted to look at the direct linkage between trade liberalization and poverty.

Measuring trade openness by the trade-to-GDP ratio and average tariffs, Aisbett, Harrison, and Zwane (2008) confirm previous studies in a cross-country analysis showing a strong link between trade and increased aggregate income growth. However, when the direct link between trade and poverty is measured, the tie is weakened considerably. Nonetheless, the direct association between trade and poverty remains positive, if not always statistically significant. The authors recommend complementary domestic policies related to good governance and institutions in order to make trade optimal for the poor. However, a more recent study finds a stronger direct tie between trade and poverty. Updating Aisbett et al.’s (2008) data with more recent years and the World Bank’s new poverty headcount ratio, Devashish Mitra (2016, pg. 65) shows that in the period of 1981-2013, “a single percentage point increase in trade leads to a poverty decline of 0.149 percentage points.”

Petia Topalova (2007, pg. 293) explores the effect of trade liberalization—measured by the weighted tariff average—on various districts within India from the late 1980s throughout the 1990s and comes to more pessimistic conclusion: “trade liberalization led to an increase in poverty rate and poverty gap in the rural districts where industries more exposed to liberalization were concentrated.” However, a response article by Hasan, Mitra, and Ural (2007) actually reverses her results after more robust measurements are taken into consideration (i.e., the inclusion of non-tariff barriers, the avoidance of nontradable employment weights, better sampling data from state-level measures). They “find that states whose workers are on average more exposed to foreign competition tend to have lower rural, urban and overall poverty rates (and poverty gaps), and this beneficial effect of greater trade openness is more pronounced in states that have more flexible labor market institutions” (2007, pg. 75). A follow-up study by Cain, Hasan, and Mitra (2012) updates Hasan et al. (2007) with the latest available data and comes to the same conclusions, determining that 38% of the poverty reduction between 1987 and 2004 was due to international trade.

Maelan Le Goff and Raju Jan Singh (2014) examine a panel of African countries between 1981 and 2010 and find that trade openness increases poverty after controlling for GDP per capita, education, and institutional quality, indicating the need for complementary reforms. Andreas Bergh and Therese Nilsson (2014) analyze 114 countries from 1983 to 2007, breaking the poverty data down into four five-year periods. In order to test economic globalization’s causality, they control for (1) the number of years McDonalds has been in the country and (2) the preceding average level of economic globalization of the neighboring countries. They discover that while trade flows lead to reductions in poverty, the significance disappears once they control for income and growth. However, even after those controls, liberalized trade restrictions have a large poverty-reducing effect (along with information flows).

Despite some mixed results, this handful of studies seems to support the conclusions of the previous section that international trade ultimately leads to reduced poverty. Even still, complementary domestic policies are necessary for countries to reap the full benefits of trade.

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In her recent book, Kimberly Clausing (2019, pg. 65-66) writes, “Openness to the world economy has played an important role in one of the most encouraging developments in human history: the dramatic increase in worldwide living standards in recent years…International trade is not solely responsible for these impressive achievements, but it has played a key role.” This literature review fully supports Clausing’s view. Trade has done an enormous amount of good for the poor worldwide and will continue to do so as long as policymakers and the public steer clear of populist-fueled protectionism.

Stuff I Say at School – Part IX: Indirect Effects of Trade on Poverty

This is part of the Stuff I Say at School series.

The Assignment

A critical literature review of trade openness on poverty. This post consists of part of the introduction and the section on trade and economic growth.

The Stuff I Said

As the The Economist (2013) reports, “The world’s achievement in the field of poverty reduction is, by almost any measure, impressive.” The United Nations’ “aim of halving global poverty between 1990 and 2015 was achieved five years early…The [Millennium Development Goals] may have helped marginally, by creating a yardstick for measuring progress, and by focusing minds on the evil of poverty. Most of the credit, however, must go to capitalism and free trade, for they enable economies to grow—and it was growth, principally, that has eased destitution.” This last statement is at times controversial in the popular press. In order to engage the controversy, this review will survey the academic literature on the effects of trade liberalization on poverty. This will be explored through two main channels. First, through trade’s indirect effects on poverty via economic growth. Most research on trade liberalization and poverty is focused on the relationship between trade and growth. Other possible avenues associated with trade, growth, and poverty—such as innovation or institutional change —will largely be ignored. Only work that focuses specifically on the connection between trade and growth will be reviewed in this section. The final section will mine the scant research on direct effects of trade liberalization on poverty.

Economist and trade expert Jagdish Bhagwati (2004, pg. 64) argues that “freer trade is associated with higher growth and…higher growth is associated with reduced poverty. Hence, growth reduces poverty.” However, empirically establishing this connection between growth and poverty reduction is necessary, seeing that it is theoretically possible for the benefits of economic growth to not be distributed to the poorest segments of society. Using a sample of 92 countries over a 40-year period, David Dollar and Aart Kraay (2002, pg. 219) find that economic growth on average increases “the income of the poor to the same extent that it increases the income of the other households in society.” Kraay (2006) finds that the main explanation for cross-country differences in poverty shifts over time is the growth in average incomes: 70% in the short-run and 97% in the long-run, respectively. In a follow-up study, Dollar, Kleineberg, and Kraay (2016, pg. 81) look at a dataset of 121 countries over four decades and come to the same conclusion: “Incomes of the bottom 20 percent and bottom 40 percent of income distribution generally rise equiproportionally with mean incomes as economic growth proceeds.” In a book-length treatment on the economic reforms in their home country of India, Bhagwati and Arvind Panagariya (2013) find that the growth since the 1990s has reduced poverty nationwide in both rural and urban regions alike and among socially disadvantaged groups. These studies confirm that the connection between economic growth and poverty reduction is solid.

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According to Bhagwati (2004), trade openness produces growth through various channels, including specialization, economies of scale, increased competition (and, consequently, decreased domestic monopolies), promotion of macroeconomic stability, and increased foreign direct investment. Much of the empirical evidence supports this view that trade openness results in growth. David Dollar’s (1992) early analysis of 95 developing countries between 1976 and 1985 concludes that trade openness (what the author calls an “outward-orientation”) and per capita GDP growth are highly correlated. Those countries in the most open quartile experienced a per capita growth rate of 2.9 percent, while those in the most closed quartile languished at -1.3 percent. Similarly, Harvard’s Jeffrey Sachs and Andrew Warner (1995, pg. 45) show in a cross-country analysis that, between 1970 and 1989, “being open to international trade has been sufficient to achieve growth in excess of 2 percent for developing countries.” However, Sachs and Warner (1995, pg. 45, fn. 61) acknowledge that their “indicators of openness are associated with other market-based reform policies, which makes it difficult to identify the precise contributions of trade as compared to other policies.” Using the portion of total trade that relies on geographical factors as an independent variable, a study by Jeffrey Frankel and David Romer (1999) finds that a one percentage point increase in the ratio of trade to GDP raises income per person between 0.5 and 2 percent. Measuring trade openness by means of tariff revenues, nontariff barriers, and other liberalization indicators, Romain Wacziarg (2001) discovers a positive effect of trade openness on economic growth in 57 countries between 1970 and 1989. Halit Yanikkaya (2003, pg. 57) provides continual support for the idea that trade stimulates growth, finding a “strong and positive relationship between trade intensity ratios and growth.” However, contrary to previous studies, Yanikkaya also finds that trade barriers can promote growth under particular conditions. William Cline (2004) questions Yanikayya’s latter findings, noting their contradiction with previous scholarship and the likelihood of his measurements either understating or misgauging the effects of protection. On the flip side, Francisco Rodriguez and Dani Rodrik (2001) argue that many of the measurements used by Sachs & Warner (1995) as well as Frankel & Romer (1999) are flawed in their openness measurements, fail to establish causality, and ignore other complementary policies necessary to promote and sustain growth. Perhaps surprisingly, T.N. Srinivasan and Bhagwati (2001) also find methodological problems with various cross-country regressions. However, in their view, this undermines many of Rodriguez and Rodrik’s criticisms due to their heavy reliance on these kinds of studies. After examining the evidence from several country-specific studies, Srinivasan and Bhagwati determine that Rodriguez and Rodrik’s criticisms fall flat and that trade and growth go hand-in-hand. Nonetheless, in a later paper, Bhagwati and Srinivasan (2002, pg. 182) acknowledge the cross-country regressions’ “interesting” findings that “practically no country that has been close to autarkic has managed to sustain a high growth performance over a sustained period.” A follow-up study by Frankel & Andrew Rose (2002) addresses many of Rodriguez and Rodrik’s concerns, controlling for small city-states, geographical distance, and institutional quality. They determine, “In every case, regardless of whether the other controls are included or not, the openness variable retains most of its magnitude and all of its statistical significance in the presence of each of the three Rodriguez-Rodrik modifications” (2002, pg. 451; italics original). On the other hand, Rodrik, Subramanian, and Trebbi (2004, pg. 135) find that when the impact of geography, global integration (international trade), and institutional quality are compared, “the quality of institutions trumps everything else.” Yet, they also find that institutions and integration positively influence each other: “A unit increase in institutional quality increases the trade share by 0.45 units, while a unit increase in trade increases institutional quality by 0.22 units” (2004, pg. 143). Conversely, Francisco Alcala and Antonio Ciccone (2004, pg. 638) control for both geography and institutional quality and measure “real openness (imports plus exports in exchange rate U.S. dollars relative to GDP in purchasing power parity US$).” Their results show that trade has a significant and robust positive (and causal) effect on productivity. Marta Noguer & Marc Siscart (2005) also control for geography and institutional quality, finding that a 1% increase in the trade share of GDP leads to a similar increase in income per capita. Dollar & Kraay (2004) look at decade-by-decade changes in trade volume across 100 countries and find that within-country changes in trade volume have a strong positive relation with changes in growth. This results in increased income for the poor. Nonetheless, Dollar and Kraay recommend complementing open trade with strong safety nets; nets that are in turn better funded by trade-induced growth.

Research over the last decade continues to support these earlier findings. Wacziarg & Welch (2008, pg. 212) find that between 1950 and 1998, “countries that liberalized their trade regimes experienced average annual growth rates that were about 1.5 percentage points higher than before liberalization.” Vlad Manole & Mariana Spatareanu (2010) use data from 131 developed and developing countries and find that reductions in trade protections lead to higher levels of income per capita. Expanding the data from Sachs & Warner (1995) and Wacziarg & Welch (2008), David Weil (2013) finds that the average growth rate of income among more open countries was significantly higher (3.1% per year) than that of closed countries (1.5% per year). Antoni Estevadeordal & Alan Taylor (2013) explore the outcomes of liberalized trade policies in countries during two time periods: 1975-1989 and 1990-2004. Those countries that liberalized during these periods had about one percentage point higher growth rates compared to non-liberalized countries.

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Maureen Were (2015) performs a cross-country analysis of 85 countries from 1991 to 2011. In agreement with most of the literature, she finds that trade has a positive and significant effect on economic growth. However, among the Least Developed Countries (LDCs)—most of which are in Africa—the statistical significance disappears. Nonetheless, she notes that trade’s effects on both domestic and foreign direct investment (FDI) are positive and significant. However, Markus Brueckner & Daniel Lederman’s (2015, pg. 1318) study focuses specifically on sub-Saharan Africa and finds that “a 1 percentage point increase in the ratio of exports plus imports over GDP is associated with a short-run increase in GDP per capita growth of approximately 0.5% in a given year,” while the long-run effect reaches about 2 percent. Pam Zahonogo (2016) argues for a Laffer Trade Curve among sub-Saharan Africa. He finds that for most measures, the thresholds are virtually non-existent. However, when imports make up for more than 33.16% of GDP, the positive effects of trade on growth begin to decline. He suggests complementary policies that promote new investments, improve institutional quality, and develop human capital. Yet, it is feasible that higher barriers on imports may harm the poor. In their analysis, Pablo Fajgelbaum & Amit Khandelwal (2016, pg. 1116) find “a propoor bias of trade in every country. On average, the real income loss from closing off trade is 63% at the 10th percentile of the income distribution and 28% for the 90th percentile.” This is due to low-income consumers spending more on traded sectors compared to high-income consumers, who spend more on non-traded services. Furthermore, Furceri, Hannan, Ostri, & Rose (2019) examine a dataset of 151 countries from 1963 to 2014. According to their results, tariff increases negatively impact output, productivity, employment, and consumption. The authors conclude, “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” (2019, pg. 28). Perhaps most impressively, Arvind Panagariya (2019, pg. 98) has compiled “data on per capita incomes, good and services exports, goods and services imports, and goods and services exports as a proportion of GDP in constant 2005 U.S. dollars for more than two hundred countries over a period of fifty-four years between 1960 and 2013” (broken into three smaller periods: 1961-1975, 1976-1994, and 1995-2013). With incredible detail, he demonstrates a causal relation between trade and per capita income: those countries that experienced intensive growth in these various periods always maintained a high and/or expanding trade-to-GDP ratio.

Overall, the empirical literature seems to indicate that trade openness has a positive effect on economic growth. Growth in turn reduces poverty. Multiple literature reviews and book-length treatments have drawn similar conclusions. For example, Joshua Lewer and Hendrik Van den Berg’s (2003) review of the literature finds that, on average, studies point to a 1/5 (or more) percentage point increase in real GDP for every percentage point increase in trade. Winters, McCulloch, and McKay (2004) are slightly more cautious, but ultimately admit that the preponderance of evidence suggests that trade openness increases economic growth and income levels within countries. Alan Winters and Antonio Martuscelli (2014, pg. 498) review the more recent literature and conclude that “the evidence is very strong that greater openness is generally associated with higher levels of income and, equivalently, that trade liberalization is associated with temporary increases in growth. The relationship appears to be causal but is not absolutely invariable.” Douglas Irwin’s (2015, pg. 197) survey of the evidence finds that “greater trade openness—marked by rising trade and low or declining trade barriers—has been a feature of virtually all rapid-growth developing country experiences in the past fifty years.” Examining countries such as China, India, South Korea, Chile, and Vietnam, Irwin concludes that liberalized trade has been associated with greater growth and, consequently, declining poverty. Panagariya (2019) performs a similar analysis, dedicating extensive attention to economic “miracles” such as Hong, Kong, Singapore, Taiwan, South Korea, India, and China. He then turns his attention to other successes throughout Asia and Africa (and even moderate ones in Latin America). He writes, “I have shown that in each case, trade liberalization and expanding trade are integral parts of the success story” (2019, pg. 322).

While complementary domestic policies (e.g., improvements in institutional quality) are necessary to reap the full benefits of international trade, there appears to be no evidence that suggests trade has anything other than positive effects on growth. The majority of studies support the claim that trade reduces poverty through increased economic growth. Panagariya (2019, pg. 125) concludes, “Given this set of facts, any advice to the developing countries to opt for protectionist policies can only be viewed as purely ideological.”

What Were the Results of the Washing Machine Tariffs?

As reported by The Washington Post,

When economists at the University of Chicago and the Federal Reserve studied the 2018 duty on washing machines, they found the expected rise in retail prices from foreign manufacturers such as Samsung and LG. Surprisingly, though, these brands also increased dryer prices. Then domestic manufacturers followed suit, simply because they could.

All told, the research shows, U.S. consumers are spending an additional $1.5 billion a year on washers and dryers as a result of the tariffs. That’s an extra $86 for each washing machine and $92 for each dryer, the authors estimate. And less than 10 percent of that goes to the U.S. treasury — about $82.2 million — the study showed…Foreign manufacturers are passing some costs on to consumers, while domestic ones are simply pocketing extra profits, according to the study.

…Manufacturers also capitalized on buyer habits when they bumped up the price of dryers, which were not subject to the tariffs. “Many consumers buy these goods in a bundle,” Tintelnot said. “Part of the price increase for washers was hidden by increasing the price of dryers.”

In sum, “U.S. consumers shouldered 125 to 225 percent of the costs of the washing-machine tariffs. And the duty was mostly a dud on the job-creation front,” costing consumers about $815,000 for every one of the 1,800 jobs created.

That’s exciting. Looks like tariffs are exactly what they are cracked up to be.

Do Minimum Wage Hikes Drive Some Restaurants Out of Business?

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From a recent NBER paper (quoting from an earlier draft): 

As theory would suggest, we find robust evidence that the impact of the minimum wage depends on how close a restaurant is to the margin of exit, proxied by its rating. Looking at city-level minimum wage changes in the San Francisco Bay Area (the “Bay Area”), we present two main findings. First, at all observed minimum wage levels, restaurants with lower ratings are more likely to exit, suggesting that they are less efficient in the economic sense. Moreover, lower rated restaurants are disproportionately affected by minimum wage increases. In other words, the impact of the minimum wage on exit is most pronounced among restaurants that are closer to the margin of exit. 

…Our results suggest that a $1 increase in the minimum wage leads to an 14 percent increase in the likelihood of exit for the median 3.5-star restaurant, but no impact for five-star restaurants (the point estimate is in fact negative, suggesting that the likelihood of exit might even decrease for five-star restaurants, but the estimate is not statistically different from zero). These effects are robust to a number of different specifications, including controlling for time-varying county characteristics that may influence both minimum wage policies and restaurant demand, city-specific time trends to account for preexisting trends, as well as county-year fixed effects to control for spatial heterogeneity in exit trends.

…Overall, our findings shed on the economic impact of the minimum wage. Basic theory predicts that the minimum wage will cause firms that cannot adjust in other ways to cover their increased costs to exit the market. We find that lower rated firms (which are already closer to the margin of exit) are disproportionately impacted by the minimum wage. After a minimum wage increase, they are more likely to exit the market altogether and more likely to raise their prices (pg. 2-5).

This matches previous research, which finds that labor-intensive restaurants tend to exit and make room for capital-intensive restaurants. 

Who Bears the Cost of the Minimum Wage?

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From a forthcoming article in the American Economic Review (quoting from the draft version) on Hungarian minimum wage hikes:

Most firms responded to the minimum wage by raising wages instead of destroying jobs. Our estimates imply that out of 290 thousand minimum wage workers in Hungary, around 30 thousand (0.076% of aggregate employment) lost their job, while the remaining 260 thousand workers experienced a 60% increase in their wages. As a result, firms employing minimum wage workers experienced a large increase in their total labor cost that was mainly absorbed by higher output prices and higher total revenue. We also estimated that firms substituted labor with capital and their profits fell slightly. These results suggest that the incidence of the minimum wage fell mainly on consumers. Given the relatively small effect on employment, our results also suggest that minimum wages can redistribute income from consumers to low-wage workers without large efficiency losses. Our findings also indicate that the optimal level of the minimum wage is likely to vary across industries,cities and countries. In countries where low-wage jobs are concentrated in the local service sector (such as Germany or the U.S.) raising the minimum wage is likely to cause limited disemployment effects or efficiency losses. Moreover, in cities where mainly rich consumers enjoy the services provided by low wage workers this redistribution will be from rich to poor. The heterogenous responses across industries also underline the advantages of sector-specific minimum wage polices used in some European countries such as Italy or Austria. For instance, setting a higher minimum wage in the non-tradable sector than in the tradable sector can push up wages relatively more where it will generate more modest disemployment effects (pg. 23-24).

Passing the costs on to consumers fits with previous evidence. This also makes evident that the kind of industry (e.g., tradable vs. non-tradable) also matters when it comes to positive/negative effects of the minimum wage.

Stuff I Say at School – Part VIII: The Impact of Openness

This is part of the Stuff I Say at School series.

The Assignment

1. Do you feel that a country can thrive in an insular or isolated capacity? Is exchanges needed for a country to be successful? Do you see any examples of countries who have been reluctant to adopt new ideologies or integration?

2. What did we learn from the Columbian exchange that would be applicable to modern day society?

The Stuff I Said

1. While I think a country can thrive to some extent in isolation depending on a number of factors, it will not thrive as much as it could have had it been integrated into a larger exchange network. An extreme historical case is Tasmania: when the island was cut off from the mainland by rising sea levels, the population not only failed to progress, but actually regressed. Anthropologist Joseph Henrich surveyed the archaeological evidence and found that the isolation caused Tasmanians to lose a number of skills and technologies they had once possessed, including bone tools, cold-weather clothing, nets, fishing spears, barbed spears, etc. Even their canoeing skills and technologies worsened. Beyond comparative advantage, trade leads to innovation (what author Matt Ridley calls “ideas having sex”). And it is innovation–technological innovation in particular–that truly transforms standards of living. 

Protectionism and isolationism have had a bit of a global resurgence lately, but these positions fly in the face of the expert consensus as far as economic welfare is concerned (check out the survey data on tariffs at the bottom of the post). This populist backlash to globalization led to a string of recent academic books empirically and philosophically defending economic openness:

2. I’ll rely on Nobel laureate Angus Deaton for the next question:

The historian Ian Morris has described how increased trade around the second century CE merged previously separate disease pools that, since the beginning of agriculture, had evolved in the West, South Asia, and East Asia, “as if they were on different planets.” Catastrophic plagues broke out in China and in the eastern outposts of the Roman Empire. The Columbian exchange after 1492 is an even better-known example. Many historical epidemics started from new trade routes or new conquests.

…Yet globalization also opens its routes to the enemies of disease. We have already seen how the germ theory of disease–a set of ideas and practices developed in the North–spread rapidly to the rest of the world after 1945. Knowledge about drugs to control high blood pressure spread rapidly across the world after 1970, producing…synchronized declines in mortality…That cigarette smoking caused cancer did not have to be rediscovered country by country. While the origins of HIV/AIDS are in dispute, there is no dispute about its rapid spread from one continent to another. The scientific response–the discovery of the virus, the deduction of its means of transmission, and the development of chemotherapy that is transforming the disease from a fatal to a chronic condition–was extraordinarily rapid by historical standards, although hardly rapid enough for the millions who died as they waited. Today’s understanding of the disease, although still incomplete, has underpinned the response–not just in the rich world–and in the worst affected African countries rates of new infection have fallen in the past few years, and life expectancy is beginning to rise again (The Great Escape, pg. 150-151).


From Gregory Mankiw’s Principles of Economics, 7th ed. (pg. 32).

From the IGM Economic Experts Panel, University of Chicago

Stuff I Say at School – Part VII: The Importance of Institutions

This is part of the Stuff I Say at School series.

Summary & Commentary on Week’s Readings

Acemoglu et al argue that inefficient institutions persist for a number of major reasons. First, the lack of third-party enforcement of commitments prevents elites from relinquishing their monopoly on political power. Furthermore, the beneficiaries of the economic status quo are usually unwilling to risk their economic welfare through competition. This leads them to promote protectionism and further engage in rent-seeking activities. Institutions that encourage these kinds of activities fail to grow. We see this kind of conflict manifest in various areas of the economy, from labor and financial markets to regulations in pricing. The more institutions concentrate political power in the hands of the few, the more incentives are warped and distort paths to economic growth.

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In their book Why Nations Fail: The Origins of Power, Prosperity, and Poverty, Daron Acemoglu and James Robinson distinguish between inclusive and extractive institutions, with the former creating the conditions for prosperity. “Inclusive economic institutions,” they write,

…are those that allow and encourage participants by the great mass of people in economic activities that make best use of their talents and skills and that enable individuals to make the choices they wish. To be inclusive, economic institutions must feature secure private property, an unbiased system of law, and a provision of public services that provides a level playing field in which people can exchange and contract; it also must permit the entry of new business and allow people to choose their careers…Inclusive economic institutions foster economic activity, productivity growth, and economic prosperity (pg. 74-75).

On the other hand, extractive economic institutions lack these properties and instead “extract incomes and wealth from one subset of society to benefit a different subset,” empowering the few at the expense of the many (pg. 76).

The importance of getting institutions right is highlighted by Rodrik and Subramanian’s study. Three theoretical culprits have been blamed for the vast income inequality between countries: (1) geography, (2) integration (globalization, international trade), and (3) institutions. Regression analyses indicate that institutions trump all other explanations. This is also shown from the outset of Acemoglu and Robinson’s Why Nations Fail, in their story of Nogales, Arizona (United States of America) and Nogales, Sonora, (Mexico). Acemoglu and Robinson lay out their archetype story of two towns with the same essential culture, geography, and relative free trade (NAFTA), in most ways they are the same place. The only reason they are two towns is an institutional barrier between two separate countries. Yet one is rich and one is poor because of institutions. The direct effects of geography are weak at best, while there were no direct effects from integration. However, there were indirect effects of integration: institutions have significant, positive effects on integration, while integration has a positive impact on institutions. This, in some sense, creates a virtuous, growth-enhancing cycle. Rodrik and Subramanian point out that the institutional factors emphasized the most have largely been market-oriented (e.g., property rights, enforceable contracts). Yet, factors such as regulation, financial stabilization, and social insurance also matter in getting institutions right.

The interaction between political and economic institutions is an important insight. For example, even though most research finds that seemingly liberal political institutions like democracy have no direct impact on economic growth, more recent evidence from Acemoglu and colleagues suggests that they may in fact contribute to growth. What’s more, the evidence strongly suggests that economic openness—particularly international trade—contributes to growth. A 2010 study used data from 131 developed and developing countries and found that reductions in trade protections led to higher levels of income per capita. A World Bank study found that between 1950 and 1998, “countries that liberalized their trade regimes experienced average annual growth rates that were about 1.5 percentage points higher than before liberalization. Postliberalization investment rates rose 1.5-2.0 percentage points, confirming past findings that liberalization fosters growth in part through its effect on physical capital accumulation…Trade-centered reforms thus have significant effects on economic growth within countries” (pg. 212). A 2016 IMF paper found that trade liberalization boosts productivity through increased competition and greater variety and quality of inputs. All this suggests that Sachs and Warner were correct when they found “that open policies together with other correlated policies were sufficient for growth in excess of 2 percent during 1970-89” (pg. 45; fn. 61). Their findings also suggest “that property rights, freedom, and safety from violence are additional determinants of growth” (pg. 50). Acemoglu and Robinson in a 2005 paper found “robust evidence that property rights institutions have a major influence on long-run economic growth, investment, and financial development, while contracting institutions appear to affect the form of financial intermediation but have a more limited impact on growth, investment, and the total amount of credit in the economy” (pg. 988).

In short, inclusive institutions are necessary to fully reap the benefits of an open economy.

Does Good Management Produce More Equal Pay?

Nicholas Bloom–whose research on the economics of management I’ve relied on in my own work–and colleagues have an interesting article in Harvard Business Review:

For 2010 and 2015, the U.S. Census Bureau fielded the Management and Organizational Practices Survey (MOPS) in partnership with a research team of subject matter experts, including one of us (Nick), as well as Erik Brynjolfsson and John Van Reenen. The MOPS collects information on the use of management practices related to monitoring (collecting and analyzing data on how the business is performing), targets (setting tough, but achievable, short- and long-term goals), and incentives (rewarding high performers while training, reassigning, or dismissing low performers) at a representative sample of approximately 50,000 U.S. manufacturing plants per survey wave. We refer to practices that are more explicit, formal, frequent, or specific as “more structured practices.” From the MOPS and related data, researchers have demonstrated just how important the use of these structured management practices is for companies and even entire economies, since firms that implement more of these practices tend to perform better.  We wanted to know what effect these management practices have on workers.

We found that companies that reported more structured management practices according to the MOPS paid their employees more equally, as measured by the difference between pay for workers at the 90th (top) and 10th (bottom) percentiles within each firm.

The authors fully admit, “To be honest, it surprised us…If anything, we expected the opposite…We hypothesized that more structured management would lead to rewarding high-performers over others, therefore leading to a rise in inequality inside of the firm. As the chart above shows, the reality is exactly the reverse – and that remains true even after controlling for employment, capital usage, firm age, industry, state, and how educated the employees are.” They continue,

Our research finds that the negative correlation between structured management and inequality is driven by a strong negative correlation between the use of structured monitoring practices and inequality. By contrast, higher usage of structured incentives practices was positively correlated with inequality, albeit weakly. In other words, our finding seems to suggest that companies that collect and analyze specific and high-frequency data about their businesses tend to have a smaller gap between the earnings of workers at the top of the income distribution and the earnings of workers at the bottom of the distribution.

The authors offer several possible explanations:

Previous research shows that firms with more structured management practices are more profitable on average, and there’s long been evidence that when companies make extra profits they share some of them with workers. Perhaps companies with more structured practices allocate these profits such that less well-paid workers get more of the pie.

The relationship could also result from increased efficiency. Maybe firms with more structured practices have more efficient low-paid workers, as a response to training or monitoring practices, and their pay reflects that extra efficiency.

Finally, it could be that firms with more structured practices are more focused on specific tasks and rely more on outsourcing. More and more companies are outsourcing tasks like cleaning, catering, security, and transport. If outsourcing is more common for firms that use more structured practices, workers performing tasks outside of the companies’ core tasks would no longer be on those companies’ direct payrolls. If the jobs that are outsourced are lower-paying than the jobs that are held by employees, the companies’ pay data will become more equal.

Other research finds that paying employees higher wages

  • Motivates employees to work harder.
  • Attracts more capable and productive workers.
  • Lead to lower turnover
  • Enhance quality and customer service
  • Reduce disciplinary problems and absenteeism
  • Require fewer resources for monitoring
  • Reduces poor performance caused by financial anxiety

Looking forward to Bloom et al.’s published work.

Is Contract Enforcement Important for Firm Productivity?

Contract enforcement is a major player in measuring the ease of doing business in a country. A new working paper demonstrates the importance of enforceable contracts to firm productivity:

In Boehm and Oberfield (2018) we study the use of intermediate inputs (materials) by manufacturing plants in India and link the patterns we find to a major institutional failure: the long delays that petitioners face when trying to enforce contracts in a court of justice. India has long struggled with the sluggishness of its judicial system. Since the 1950’s, the Law Commission of India has repeatedly highlighted the enormous backlogs and suggested policies to alleviate the problem, but with little success. Some of these delays make international headlines, such as in 2010, when eight executives were convicted in the first instance for culpability in the 1984 Bhopal gas leak disaster. One of them had already passed away, and the other seven appealed the conviction (Financial Times 2010)

These delays are not only a social problem, but also an economic problem. When enforcement is weak, firms may choose to purchase from suppliers that they trust (relatives, or long-standing business partners), or avoid purchasing the inputs altogether such as by vertically integrating and making the components themselves, or by switching to a different production process. These decisions can be costly. Components that are tailored specifically to the buyer (‘relationship-specific’ intermediate inputs) are more prone to hold-up problems, and are therefore more dependent on formal court enforcement.

…Our results suggest that courts may be important in shaping aggregate productivity. For each state we ask how much aggregate productivity of the manufacturing sector would rise if court congestion were reduced to be in line with the least congested state. On average across states, the boost to productivity is roughly 5%, and the gains for the states with the most congested courts are roughly 10% (Figure 3).

Are Immigrants a Threat?

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From a new working paper:

The empirical evidence comes down decidedly on the side of immigrants being less likely to commit crimes. A large body of empirical research concludes that immigrants are less likely than similar US natives to commit crimes, and the incarceration rate is lower among the foreign-born than among the native-born (see, for example, Butcher and Piehl 1998a, 1998b, 2007; Hagan and Palloni 1999; Rumbaut et al. 2006). Among men ages 18 to 39—prime ages for engaging in criminal behavior—the incarceration rate among immigrants is one-fourth the rate among US natives (National Academies of Sciences, Engineering, and Medicine 2015).

…There is some evidence that the lower propensity of immigrants to commit crimes does not carry over to immigrants’ children. The US-born children of immigrants—often called the “second generation”— appear to engage in criminal behavior at rates similar to other US natives (Bersani 2014a, 2014b). This 4 “downward assimilation” may be surprising, since the second generation tends to considerably outperform their immigrant parents in terms of education and labor-market outcomes and therefore might be expected to have even lower rates of criminal behavior (National Academies of Sciences, Engineering, and Medicine 2015). Instead, immigrants’ children are much like their peers in terms of criminal behavior. This evidence mirrors findings that the immigrant advantage over US natives in terms of health tends to not carry over to the second generation (e.g., Acevedo-Garcia et al. 2010).

Although immigrants are less likely to commit crimes than similar US natives, they are disproportionately male and relatively young—characteristics associated with crime. Does this difference in demographic composition mean that the average immigrant is more likely than the average US native to commit crimes? Studies comparing immigrants’ and US natives’ criminal behavior and incarceration rates tend to focus on relatively young men, leaving the broader question unanswered. However, indirect evidence is available from looking at the relationship between immigration and crime rates. If the average immigrant is more likely than the average US native to commit crimes, areas with more immigrants should have higher crime rates than areas with fewer immigrants. The evidence here is clear: crime rates are no higher, and are perhaps lower, in areas with more immigrants. An extensive body of research examines how changes in the foreign-born share of the population affect changes in crime rates. Focusing on changes allows researchers to control for unobservable differences across areas. The finding of either a null relationship or a small negative relationship holds in raw comparisons, in studies that control for other variables that could underlie the results from raw comparisons, and in studies that use instrumental variables to identify immigrant inflows that are independent of factors that also affect crime rates, such as underlying economic conditions (see, for example, Butcher and Piehl 1998b; Lee, Martinez, and Rosenfeld 2001; Reid et al. 2005; Graif and Sampson 2009; Ousey and Kubrin 2009; Stowell et al. 2009; Wadsworth 2010; MacDonald, Hipp, and Gill 2013; Adelman et al. 2017). The lack of a positive relationship is generally robust to using different measures of immigration, looking at different types of crimes, and examining different geographic levels.2 Further, the lack of a positive relationship suggests that immigration does not cause US natives to commit more crimes. This might occur if immigration worsens natives’ labor market opportunities, for example.

The few studies that examine crime among unauthorized immigrants have findings that are consistent with the broader pattern among immigrants—namely, unauthorized immigrants are less likely to commit crimes than similar US natives (apart from immigration-related offenses).4 Likewise, studies that examine the link between the estimated number of unauthorized immigrants as a share of an area’s population and crime rates in that area typically find evidence of null or negative effects (pg. 3-5).

Comparatively, the effects of border control on crime is mixed. The authors conclude,

A crucial fact seems to have been forgotten by some policy makers as they have ramped up immigration enforcement over the last two decades: immigrants are less likely to commit crimes than similar US natives. This is not to say that immigrants never commit crimes. But the evidence is clear that they are not more likely to do so than US natives. The comprehensive 2015 National Academies of Sciences, Engineering, and Medicine report on immigration integration concludes that the finding that immigrants are less likely to commit crimes than US natives “seems to apply to all racial and ethnic groups of immigrants, as well as applying over different decades and across varying historical contexts” (328). Unauthorized immigrants may be slightly more likely than legal immigrants to commit crimes, but they are still less likely than their US-born peers to do so. Further, areas with more immigrants tend to have lower rates of violent and property crimes. In the face of such evidence, policies aimed at reducing the number of immigrants, including unauthorized immigrants, seem unlikely to reduce crime and increase public safety (pg. 11).