Evaluating the Distinctive Economic Impact of Historical Female Migration in the United States

A Woman’s Touch? Female Migration and Economic Development in the United States

By Viola von Berlepsch (London School of Economics), Andrés Rodríguez-Pose (London School of Economics) and Neil Lee (London School of Economics),

Abstract: Does the economic effect of immigrant women differ from that of immigrants in general? This paper examines if gender has influenced the short- and long-term economic impact of mass migration to the US, using Census microdata from 1880 and 1910. By means of ordinary least squares and instrumental variable estimations, the analysis shows that a greater concentration of immigrant women is significantly associated with lower levels of economic development in US counties. However, immigrant women also shaped economic development positively, albeit indirectly via their children. Communities with more children born to foreign mothers and that successfully managed to integrate female immigrants experienced greater economic growth than those dominated by children of foreign-born fathers or American-born parents.

URL: https://econpapers.repec.org/paper/cprceprdp/12878.htm

Circulated by NEP-HIS on 2018-05-08

Review by Fernando Arteaga (George Mason University)

Summary

What is the economic impact of female migration? The authors seek to answer the inquiry by using the United States in the late 19^th and early 20^th century as their study case. The goal of the paper is to highlight the distinctiveness of women immigration (compared to that of men), both in the processes that led women to migrate, the characteristics they had, and the places where they finally settled. The main thesis of paper stresses the long-lasting effect women have had; through their family role, as mothers, they facilitated the formation and transmission of social capital, which had a pervasive positive effect on income.

Female migrants in early America tended to settle mainly on urbanized areas in the Northeastern coast – compared to that of male immigrants (who settled mainly in the South and West). The migration levels of women, in absolute terms, were lower, and their marriage rates higher. More importantly, their labor participation rates were low: women tended to stay and work in domestic chores rather than find occupations in the market. These characteristics make female migration distinct to that of men, and motivate the goal of the paper in trying to assess their particular relevance.

 

 

Figure 1: Immigrant Women in the United States, 1880. By the nature of the variable, counties with a larger share of immigrant women imply a lower share of immigrant men.

 

The text relies on standard econometric analyses, based on intuition and on the literature of migration and culture transmission. The main data sources are the historical censuses of 1880 and 1910, which capture the amount of, male and female foreign-born population residents in each US county (among other data).  The paper presents two base regressions that aim to assess the direct and indirect economic impact of female migration, both in the short and the long term. The first model regresses economic income (GDP per capita by county) on female migration (foreign-born women as a share of the total population in the county). They find that the variables are negatively correlated: lack of labor market participation hindered the female contribution to income. The authors also found that this has had a long term negative effect (income today is also negatively correlated with female migration in late 19^th and early 20^th century) [1]. To correct for potential biases and to establish a causality linkage that goes strictly from migration to income, and not the other way around, the authors use three different instruments: a) the percentage of married persons; b) the number of persons living in a household; c) the urbanization rate of the county being examined. The first instrument accounts for the fact that female migrants tended to be married in larger shares than the rest of the population. The second accounts for the idea that migrants, especially women, tended to stay with members of their families through their lifetime. The last one maintains that female migrants favored settlement in urbanized zones. The validity of an instrument (marriage percentage, household size and urbanization) hinges upon it being correlated with the dependent variable (income) only by it causing the highlighted mechanism (female migration). The authors do several post-hoc statistical tests to evaluate the instrument’s validity and conclude that it is indeed a valid and strong one. In any case, the instrument variable outcomes do not change the results of the baseline ordinary least squares scenario, they just allow a more robust interpretation of them: it can be said that female migration did have a negative impact on income.

The second model emphasizes the indirect impact of migrant women. Maybe women themselves did not positively contribute to the economic wellbeing of their communities, but they could have done so through other means. The authors refer to the literature that stresses how mothers influence their children behavior and thus have an important role as social capital transmitters (which could positively affect economic wellbeing).  They regress economic income today on the share of children (in 1880 and 1910) born from: 1) a migrant mother and an American-born father; 2) a migrant father and an American mother; 3) both American parents. The standard base of comparison is the share of children that had both parents as immigrants [2].  By definition, the model can only capture the long-term effect of female migrants. The authors find that US counties with an historical larger share of children with migrant mothers are correlated with larger incomes today – in comparison to the other explanatory variables; having American parents is negatively correlated with income today; having a migrant father, and American mother, has a non-significant and null effect on economic outcomes today. The argument, again, rests on the case of social capital transmission: women, as mothers, matter very much.  To corroborate their OLS results they also use an instrumental variable. The authors assume that American-born women that had migrant mothers followed the cultural transmission pattern established by their forebears. They call this the “supply-push” component, which they estimate and use as their instrument. Just as the first model, the instrumental variable inclusion does not modify the basic results, it only permits to talk about causality from migrants in the past to better economic outcomes today.

In conclusion, the paper finds that female immigration, while having a negative direct short-term impact on economic income, has a long-lasting positive effect through the “cultural carrier” channel.

Comment

The paper is a very interesting one, being one of the few studies that aims to disentangle the impact of women as migrants compared to that of men. The results the authors present make intuitive sense. I would like to make just small technical comments based on the variables they use and how they use them.

First, related to the semantics of the concept of “migration.” Migration is normally thought as a flow variable, but here it is used as a stock variable. Given the data they use (measuring migrants as people classified as foreign born in two censuses) the authors cannot measure the impact of migration as a flow, only the impact of it in broad terms. This is not a problem. I just would have liked to see a minor explanation on the paper that clarified the interpretations that we could get out of this. In fact, I think it could explain why they find a negative impact of migrant women in income (if the variables were flows, through migration rates and economic growth, the results may be different).

Second, on a more technical note, I’m skeptic of the instruments being used. Even though the authors argue that they are valid and strong, I remain unconvinced. The authors show that all four of them are correlated with the dependent variable and uncorrelated with the error terms, yet there is almost no explanation, backed up by a narrative, of how exactly these instruments impact on income only through female migration. For each one of the instruments used I could think of other alternate channels by which they could impact income. For example, the use of percentage of marriage by county could indeed be correlated with female migration, but is that the only potential channel? Could it not be that maybe poverty or religion could be impacting income as well?

Lastly, I wish the narrative part could be explained in larger detail. For example, how exactly female migrants in 1880 have a direct impact on income in 2010. Or how exactly children of foreign mothers in 1880 and 1910 could affect income today. It is one thing to say that culture matters, it is another different thing to point how exactly it does. In fact, even though they do mention the pervasiveness of cultural traits through time, they fail to mention that this pervasiveness does not imply ipso facto a good outcome is assured. Sometimes, social capital is also correlated with bad outcomes.

[1] The authors do not provide a concise explanation of why this could be happening: how could a century year old female migration pattern directly impact economic wellbeing today?

[2] All the interpretations of results are in comparison to that baseline.

(Superstar) Firms and Inequality

The Fall of the Labor Share and the Rise of Superstar Firms

By: David Autor (MIT, NBER and IZA), David Dorn (University of Zurich and IZA), Lawrence F. Katz (Harvard University, NBER and IZA), Christina Patterson (MIT) and John Van Reenen (MIT, NBER and IZA)

Abstract: The fall of labor’s share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain. Existing empirical assessments of trends in labor’s share typically have relied on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and international sources and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms.” If globalization or technological changes advantage the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms with high profits and a low share of labor in firm value-added and sales. As the importance of superstar firms increases, the aggregate labor share will tend to fall. Our hypothesis offers several testable predictions: industry sales will increasingly concentrate in a small number of firms; industries where concentration rises most will have the largest declines in the labor share; the fall in the labor share will be driven largely by between-firm reallocation rather than (primarily) a fall in the unweighted mean labor share within firms; the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; and finally, such patterns will be observed not only in U.S. firms, but also internationally. We find support for all of these predictions.

URL: http://EconPapers.repec.org/RePEc:iza:izadps:dp10756

Distributed by NEP-HIS on: 2017‒05‒28

Review by: Sebastian Fleitas (University of Arizona)

In the last few years, inequality has been at the center of many political and academic debates. It turns out that, although less mentioned in these debates, the rapid growth of some developing countries in the last decades has actually decreased global inequality. But then, why is there a big debate about inequality? The issue is that, on the other hand, inequality in developed countries has been increasing over time. From the perspective of the functional distribution of income between labor and capital, one of the indicators of this increase in inequality is that the labor’s share of GDP has been falling in the United States and other countries in recent decades. These forces have generated winners and losers. As economist Branko Milanovic points out with his famous “elephant chart,” the middle class of the world and the very rich of the world are the two groups whose incomes have increased more rapidly. In contrast, it can be easily seen that there are large groups of people uncomfortable with increased inequality. Moreover, the factors assumed to be causing inequality have taken a vital role in political debates and recent elections.

“Elephant Chart”: Lakner & Milanovic (2016)

In this context, it is extremely important to understand what is driving these changes in inequality. There are different approaches to understand the increase in inequality in developed countries. The two main perspectives point to the importance of top incomes and changes in the tax system (e.g. Piketty and Saez, 2014), on one hand, and to changes in the labor market, mainly related to the incorporation of technological change that is more favorable to skilled workers (e.g. Autor, 2014), on the other. More recent approaches have begun to more directly incorporate the role of firms. For example, a growing literature estimates models to separate the firm’s and employee’s contributions to wage differences via double fixed-effects models, with many studies finding that firm wage effects account for approximately 20% of the overall variance of wages and have had an increasingly important role over time (e.g. Card et al., 2016). However, while we can all see that “superstar firms” like Apple, Microsoft, Google or many others in different sectors of the economy are growing very quickly, we still do not know what their effect of inequality is.

Do these “superstar firms” increase inequality because they are responsible for the decrease in labor’s share? The paper by Autor, Dorn, Katz, Patterson and Van Reenen addresses exactly this issue. If we are interested in understanding the role of firms in the increase in inequality, it is particularly important to answer the question of whether the decrease in labor’s share of income can be explained by technological changes occurring within firms, or if it is better explained by a rise of “superstar” firms, which tend to use new technologies and are more capital-intensive. The main argument of the authors is that markets have changed in such a way that firms with superior quality, lower costs, or greater innovation get disproportionately high rewards relative to previous periods. Since these “superstar firms” have higher profit levels, they also tend to have a lower share of labor in sales and value-added. Therefore, as these firms gain market share across a wide range of sectors, the aggregate share of labor falls. In this way, “superstar firms” are one of the drivers of the decrease in labor’s share (in favor of capital’s share) of value added.

Before they start developing the evidence for this argument, the authors clearly document the fall in labor’s share of GDP in the United States and other developed countries. After that, they formalize their main argument in a model of “superstar firms,” in order to derive the set of predictions that will be taken to the data. With this model in hand, the authors use several sources of information (U.S. Economic Census, KLEMS, UN Comtrade Database, and others) to run a series of regressions and decompositions to analyze the testable predictions of the model. First, the authors find that sales concentration levels have risen in most sectors. Second, they show that the larger decreases in labor’s share are observed in industries where concentration has increased the most. Third, by comparing the weighted and unweighted mean of labor’s share, the authors conclude that the fall in labor’s share has an important component of reallocation between (and not within) firms. Furthermore, they find that the between-firm reallocation of labor’s share is greatest in the sectors that are concentrating the most. Finally, these patterns are not only present in the US but also in many European countries.

Overall, all of these findings are consistent with the idea of a rise of “superstar firms” that have lower labor’s share, and which have gained more importance by concentrating large shares of sales in different sectors of the economy. It should be noted, however, that the authors do not provide a clean causal identification of the superstar firm model. The empirical exercises are done carefully and controlling for the factors that can more clearly affect the tested relationships. The use of fixed effects and trends by industry allow the authors to obtain identification exclusively from the acceleration or deceleration of labor’s shares and concentration conditional on these controlled trends. Thus, any potential threat to this identification strategy would have to come from other factors not captured by these trends or fixed effects and which are correlated with industry concentration and inequality.

This paper makes a major contribution by pointing out the role of “superstar firms” in explaining increasing inequality and opens some avenues for future research in a direction that had not been typically considered in the literature. In this sense, a particularly interesting direction would be to use the matched employer-employee databases with census data on sales to test if industry concentration has impacts on the firm component of wages and the within and between firm decomposition in each sector.

Finally, the paper addresses the question of what is the driver of the growth of these “superstar firms.” The main debate here is whether the rise of these “superstar firms” and industry concentration are associated with competitive forces, or if they are a signal of an economy with competition problems. Increased concentration can be a result of technological changes: some sectors could be introducing technologies that have a “winner takes all” aspect. An alternative, more worrisome story is that leading firms are less exposed to competition because they can create barriers to entry or have more lobbying power. The authors provide evidence that is somewhat comforting about this point. They show that concentration is greater in industries experiencing faster technical change, approximated either by patent activity or by total factor productivity growth. However, this evidence is still subject to debate. It could be the case that these originally innovative firms are now using their market power to generate barriers to entry. This can be even more important in some technology sectors where network effects generate an important advantage to the innovators. I think this discussion is actually one of the main directions where this stream of research can be expanded and complemented in the future. In this sense, for example, sector-specific partial equilibrium models could allow formalizing the product and labor markets under innovation dynamics, and such models could be estimated using data for specific industries and structural econometrics estimation techniques.

To sum up, I think that this paper makes a major contribution by pointing out the effect of “superstar firms” on the decrease of labor’s share of GDP, and therefore increased inequality in developed countries. Additionally, this paper opens several avenues for future work in order to generate more evidence consistent with the “superstar firms” model and, critically, to understand its causes and consequences at the individual micro level, especially using matched individual and firm level databases and sector-specific analysis. To understand the relationship between firms and inequality is a key task in a world of “superstar firms,” and these are key inputs for the discussion of, for example, the roles of tax policies, labor market institutions and their relationship with the increasing heterogeneity of firms.

REFERENCES

Autor, D. (2014). Skills, Education, and the Rise of Earnings Inequality Among the “Other 99 Percent.” Science 344 (6186), 843-851.

Card, D., Cardoso, A. R., Heining, J., & Kline, P. (2016). Firms and Labor Market Inequality: Evidence and Some Theory. National Bureau of Economic Research Working Paper 22850

Lakner, C., & Milanovic, B. (2016). Global Income Distribution: From the Fall of the Berlin Wall to the Great Recession. World Bank Economic Review 30(2), 203-232.

Piketty, T., & Saez, E. (2014). Inequality in the Long Run. Science 344(6186), 838-843.

 

 

“Empire State of Mind”: The Land Value of Manhattan, 1950-2013

What’s Manhattan Worth? A Land Values Index from 1950 to 2013.

by Jason Barr, Rutgers University (jmbarr@rutgers.edu), Fred Smith, Davidson College (frsmith@davidson.edu), and Sayali Kulkarni, Rutgers University (sayali283@gmail.com).

Abstract: Using vacant land sales, we construct a land value index for Manhattan from 1950 to 2013. We find three major cycles (1950 to 1977, 1977 to 1993, and 1993 to 2007), with land values reaching their nadir in 1977, two years after the city’s fiscal crises. Overall, we find the average annual real growth rate to be 5.1%. Since 1993, landprices have risen quite dramatically, and much faster than population or employment growth, at an average annual rate of 15.8%, suggesting that barriers to entry in real estate development are causing prices to rise faster than other measures of local well-being. Further, we estimate the entire amount of developable land onManhattan to be worth approximately $825 billion. This would suggest an average annual return of 6.3% since the island was first inhabited by Dutch settlers in 1626.

URL: http://d.repec.org/n?u=RePEc:run:wpaper:2015-002&r=his [this link will download a Word copy of the paper to your computer]

Review by Manuel A. Bautista González (Columbia University)

“All cultures have their creation myths, and according to cherished New York legend, the Manhattan real estate market was born when the Dutch paid $24 in shells to the Indians for an island that is today worth billions of dollars. The persistence of this story tells us more about the justifying strategies of our own times than about the past. The Manhattan real estate market, the myth implies, is as natural as its bedrock and harbor, and real estate magnates who today pursue “the art of the deal” are only fulfilling their forefathers’ vision of the profits embedded in Manhattan land. The conditions of Manhattan’s land and housing markets, far from being part of the natural order of things, are rooted in a social history. It is, after all, people who organize, use, an allocate the benefits of natural and social resources, and the value they assign to land depends on the larger set of social relations that organize property rights and labor. […] How did land become “scarce”? […] Who profited, who lost, and what difference did the flow of rents make to New Yorkers’ understanding of their social responsibilities within a shared landscape […] The myth that celebrates a real estate deal as New York’s primal historical act lends an aura of inevitability to the real estate market’s power to shape the city landscape and determine the physical conditions of everyday life. New Yorkers today live in the shadows of deals that have produced the glitter of Trump Tower, the polished facades of renovated brownstones, and the shells of abandoned buildings. These shadows especially darken the paths of those who are getting a bad deal: the more than 50,000 people who have been displaced onto the city’s streets and sleep in doorways, subway stations, railroad terminals, or temporary shelters. Contemporary politicians invoke this landscape of light and shadows to point to the contradictions of of our time: a city that can indulge extravagant displays of wealth cannot afford to house its people.”

(Blackmar 1989: 1, 12)

.

Debates over the high market value of real estate and the unaffordable price of housing occupy a constant place in the public spheres of the major cities of the world, especially in those where land is already a very scarce factor and vertical, intensive urban development takes place in the form of tall buildings, towers and skyscrapers. However, historical perspectives on the real estate and housing markets are for the most part lacking in these discussions. In their paper, Jason Barr, Fred Smith and Sayali Kulkarni attempt to fill the gap for New York City, a capital of capital like no other, to borrow from the title of the book by financial historian Youssef Cassis (Cassis 2007). In their work, published in NEP-HIS 2015-04-11, the authors develop a land value index between 1950 and 2013 in Manhattan, the island that defines the Big Apple like no other borough does.

According to the deflated value of their index, the real value of real estate in Manhattan since 1950 has increased at an (otherwise impressive) average annual growth rate of 5.1%. The authors identify three long cycles: the first one, 1950-1977, roughly coincided with the golden era of Western capitalism, a skyscrapers boom and the demise of urban industries; the second one, 1977-1993, began with the consequences of white flight to the suburbs and fiscal crises in the city and lasted until the financial Big Bang of the late 1980s and early 1990s; and the third one, 1993-2007, manifested the impact of financialization of the U. S. economy, the rise of Manhattan as a services powerhouse, and the emergence of New York as a truly global city, in the sense proposed by the sociologist Saskia Sassen (Sassen 2001).

View of Manhattan from Top of the Rock Observation Deck, Sunday, May 20, 2012, 5:13 PM EST. A gift from the author to the loyal audience of the NEP-HIS blog.

The authors go through the methodological problems of developing a land value index. The first problem has to do with whether one assesses the value of undeveloped land or whether one incorporates the constructions on it. The second problem is that of using either market prices or assessment of values for taxation purposes, for example. A third problem derives from the divergence of market prices and assessed values, a divergence which is considerable in the case of New York City during this period.