ArticlePDF Available

Corporations and Economic Inequality Around the World: The Paradox of Hierarchy

May 2010
Research in Organizational Behavior 30(1)

DOI: 10.1016/j.riob.2010.08.001

Authors:

Gerald F. Davis

University of Michigan

J. Adam Cobb

University of Texas at Austin

Using time-series data from the US since 1950 and from 53 countries around the world in 2006, this chapter documents a strong negative relation between an economy's employment concentration (that is, the proportion of the labor force employed by the largest 10, 25, or 50 firms) and its level of income inequality. Within the US, we find that trends in the relative size of the largest employers (up in the 1960s and 1970s, down in the 1980s and 1990s, up in the 2000s) are directly linked to changes in inequality, and that corporate size is a proximal cause of the extravagant increase in social inequality over the past generation. We conclude that organization theory can provide a distinctive contribution to understanding societal outcomes.

Lorenz Curve and Gini Index

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Comparison of Total and Domestic Employment Figures in US, 1993-2008

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Cross-National Comparison of Income Inequality and Employment Concentration, 2006

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Corporations and economic inequality

around the world: The paradox of hierarchy

Gerald F. Davis

Ross School of Business

University of Michigan

701 Tappan St.

Ann Arbor, MI 48109-1234

(734) 647-4737

gfdavis@umich.edu

J. Adam Cobb

Ross School of Business

University of Michigan

701 Tappan St.

Ann Arbor, MI 48109-1234

adamcobb@umich.edu

To appear in Research in Organizational Behavior

March 31, 2010

We thank Art Brief, Barry Staw, and seminar participants at the University of Michigan

for their excellent comments.

Abstract

Using time-series data from the US since 1950 and from 53 countries around the world in

2006, this chapter documents a strong negative relation between an economy’s

employment concentration (that is, the proportion of the labor force employed by the

largest 10, 25, or 50 firms) and its level of income inequality. Within the US, we find

that trends in the relative size of the largest employers (up in the 1960s and 1970s, down

in the 1980s and 1990s, up in the 2000s) are directly linked to changes in inequality, and

that corporate size is a proximal cause of the extravagant increase in social inequality

over the past generation. We conclude that organization theory can provide a distinctive

contribution to understanding societal outcomes.

The triumph of shareholder capitalism in the United States over the past

generation has corresponded to a dramatic increase in income inequality. The proportion

of the nation’s income going to the top 1% of earners has reached levels not seen since

the stock market boom of the 1920s (Piketty & Saez, 2003). No European country--

including Russia--surpasses the United States in inequality. Yet social scientists have yet

to explain convincingly how this came to be.

One economic explanation for increasing inequality focuses on technologically-

driven changes in the mix of skills required by the economy, which widens the wage gap

between those who have these skills (e.g., computer literate college graduates) and those

who do not. Similar explanations were offered to explain the rise in inequality during the

Second Industrial Revolution in the late 19th century. But cross-national comparisons

are inconsistent with this interpretation. France, for instance, has seen no substantial

change in inequality since the Second World War (Piketty & Saez, 2003), and Japan and

the Nordic countries—hardly technological slackers—are among the most equal nations

on Earth. Yet in the US, inequality has reached levels most comparable to countries like

Thailand and Senegal.

We propose that the most immediate cause of increasing (or decreasing)

inequality in advanced economies is aggregate change in corporate organization. More

specifically, change in the relative size of the largest organizations in an economy has a

direct and—we argue—causal relation to the degree of income inequality. Factors that

influence the size of organizations—technology, managerial methods, innovations in

organization design, power struggles over the purpose of the corporation—thereby

indirectly influence inequality. We present evidence that, both cross-nationally and over

time within the US, there is a very strong correlation between the level of corporate

employment concentration--the proportion of the labor force employed by the 10 or 25 or

100 largest domestic businesses--and income inequality at the societal level. Within the

US from 1950 to 2006, this correlation year-to-year was roughly -0.8. That is, the greater

the sizes of the largest employers relative to the size of the labor force, the lower the level

of economy-wide income inequality. When employment concentration increased during

the merger wave of the 1960s, inequality dropped to the lowest levels on record. As

corporations shrank due to bust-up takeovers, spinoffs, layoffs, and outsourcing during

the 1980s and 1990s, employment concentration declined, while inequality

correspondingly increased. The reasons for the merger wave and the the subsequent “de-

merger” waves are well-known from the literature in organization theory (e.g., Davis,

Diekmann, and Tinsley, 1994). At a deeper level, conceptions of what a corporation is

and to whom it is responsible shape whether typical corporations in an economy are large

or small. But it is this fact—greater or lesser employment concentration—that appears to

have a nearly mechanical effect on inequality.

Our findings reveal a paradox. Corporate hierarchies are the defining structures

of inequality in modern societies, and earnings inequality is greater in big firms than

small firms (Kalleberg & Vanburen, 1994). Commentators routinely lament the growing

gap between the compensation packages of CEOs and the average wages of their workers

(e.g. Frank & Cook, 1995). Yet societies in which employment is more concentrated

within large corporations are more equal than those in which employment is dispersed

among smaller firms.1 In Denmark, the most equal society in our sample, the ten largest

1 Throughout the paper, we use the Gini coefficient as our measure of income inequality at the economy-

wide level, and explain it in more detail later. The Gini coefficient reflects how the aggregate income of a

domestic corporations employ the equivalent of one-quarter of the workforce, and the

biggest Danish firm in 2006 had a workforce of over 270,000 (albeit not all employed in

Denmark). In Colombia, the most unequal country we study, the largest firms employ

less than one-quarter of one percent of the workforce, and the biggest Colombian firm

had just 7000 employees, in a country nearly ten times the size of Denmark. The US is at

the 70th percentile of inequality among nations, with about 3% of the workforce

employed by the biggest firms--numbers roughly comparable to Russia. Yet in 1969,

almost 6% of the US workforce was employed in the largest firms--just as the US had

achieved the lowest level of income inequality in its recorded history.

This “paradox of hierarchy” bears some resemblance to the famous ecological

fallacy. Robinson (1950) noted that correlations at the aggregate level need not

correspond to correlations at the individual level, and showed that the percentage of a

state’s population that is literate was positively correlated with its percentage of

immigrants, although individual immigrants were less likely to be literate than non-

immigrants. Similarly, although African-Americans voted for Barack Obama at near-

unanimous levels in the 2008 presidential election, four of the five states with the highest

proportion of African-Americans went for his opponent. Surprising compositional

effects are common in organization theory. For instance, March and Simon (1958)

showed how smart organizations could be comprised of dumb (boundedly rational)

individuals, while DiMaggio and Powell (1983) argued that individually rational

organizations could aggregate up into collectively irrational fields. The paradox of

society is divided: $1 divided among 100 persons would yield a Gini of 0 (perfect equality), while the same

dollar given to only one person would yield a Gini of 1 (perfect inequality). Unlike other measures of

dispersion, such as standard deviation, it does not vary with the scale used. Thus, very low-income

societies can have very high inequality, and vice versa. Empirically, the Gini declines with average income

in an economy—that is, on average richer societies are more equal than poorer societies.

hierarchy is analagous: unequal organizations aggregate into collectively more equal

societies.

In this chapter, we briefly review the literature on economic inequality and the

part played by organizations in social stratification. We then review some of the major

changes in corporate organization and the employment relation in the US since the end of

the Second World War and their implications for employment concentration. Next we

present evidence on the link between employment concentration and income inequality

among 53 countries, as well as time-series evidence for the US from 1950 to 2006. We

find a remarkably strong relation between the Gini coefficient—a measure of income

inequality—and the proportion of the labor force employed by the ten largest domestic

businesses. Around the world, clear regional patterns emerge: Nordic countries show

both the lowest levels of inequality and high levels of employment concentration; Latin

American countries show the highest levels of inequality and the lowest levels of

employment concentration; and Western European and Mediterranean countries are

largely in between. Former Communist countries (other than Russia and China) form an

intriguing off-diagonal, exhibiting both low inequality and relatively low employment

concentration. These groupings map onto different “varieties of capitalism” (cf. Amable,

2003), which in turn support divergent conceptions of corporate purpose and

organization. We conclude with a somewhat speculative discussion of the sources of this

relationship and its implications for future research on the effects of organizational forms

on social inequality. Our approach is frankly exploratory: to our knowledge, this is the

first paper to examine the correlates of employment concentration. But we believe the

results indicate that this may be a rich construct for further investigation.

Organizations and social inequality

Explaining social inequality is one of the defining problematics of sociology as a

discipline, animating theorists from Marx and Durkheim to Otis Dudley Duncan and

Jeffrey Pfeffer. By definition, inequality is a relational term. The unit of analysis for

examining inequality can be the group, the organization, the society, or the world

economy (e.g. Firebaugh, 1999 examines inequality among national averages). We focus

on the societal level--specifically, on inequality within a national economy as the unit of

analysis. The extant literature on social inequality is wide and deep, and we can only

engage a small segment of it.

Inequality is distinct from poverty. Poverty is a first-order problem, and among

low-income countries, policies for alleviating poverty take precedence over questions of

inequality. But above a threshold level of economic development, inequality is strongly

related to a range of social ills. Among the world’s developed economies, inequality is

correlated with lower life expectancies, higher rates of infant mortality, higher teenage

pregnancy rates, higher rates of homicide and other crime, higher rates of incarceration,

and higher rates of mental illness (see Wilkinson & Pickett, 2009 for a recent summary).

The most frequently replicated findings are correlations between inequality and life

expectancy at birth, and between inequality and infant mortality. The precise mechanism

of causation is controversial. Wilkinson and Pickett (2009) argue for several causal

pathways leading from inequality to social evaluation anxiety and stress, and from there

to health outcomes. (The link from stress to health outcomes is itself well-documented.)

Some studies have found the causal tie between inequality and aggregate health outcomes

to be elusive when other factors are taken into account (e.g. Mellor & Milyo, 2001), and

high-quality time series data are largely lacking. But even if inequality and other social

ills are correlated due to some third factor, it is worth unpacking what that third factor is.2

Prior research suggests that social inequality is not a fixed property of an

economy but varies over time within countries. Economists have attributed economy-

wide inequality to changes in technology and economic development (e.g. Acemoglu,

2002). The Kuznets Curve famously depicts the relation between economic development

and inequality. Economist Simon Kuznets, writing in the mid-1950s, discovered an

inverse-U relation between the level of industrialization of an economy and the level of

inequality (Kuznets, 1955). Inequality evidently increased with the level of

industrialization, but then declined afterwards.

Subsequent works found that the inverse-U relation was not an immutable law of

nature, and the years since Kuznets wrote have produced challenges to the simple version

of the Kuznets curve (e.g. Alesina & Rodrik, 1994; Perotti, 1993). In particular, the

cross-national regularities Kuznets found did not always hold over time within countries.

In the US, inequality dropped substantially during WWII and did not return to pre-War

levels for decades. The most equal year on record in the US was 1968. But more

recently there has been a vast upsurge in inequality, returning the US to a new Gilded

Age—perhaps more of an N-curve than an inverse-U. The implication of these findings

is that the source of the potential link between economic development and inequality is

2 Indeed, authors disputing the causal link between inequality and aggregate health outcomes suggest

something very similar to what we examine as their "third factor: "...industrial restructuring or other

employment shocks may have detrimental effects for individual health outcomes (through the loss of

insurance coverage or income), while at the same time increasing income inequality...Given the omission

of factors that simultaneously affect inequality and health, it should be no surprise to sometimes observe a

significant association between inequality and aggregate health measures, regardless of the sign of that

association" (Mellor & Milyo, 2001, p. 515)

ambiguous. Technology-based changes in required skills are one possibility, but the

direct evidence on this is not yet compelling.

Insert Figure 1 about here

Bureaucracy and social inequality

A separate literature on stratification in sociology focused on individual-level

attainment. The prototypical study would contain a regression in which individual

income, or socio-economic status, was modeled as a function of education, sex, race,

mother’s education, and so on (e.g. Blau & Duncan, 1967). A compelling critique of this

literature pointed out that attainment does not take place strictly at an individual level:

organizations are where stratification happens (Baron & Bielby, 1980; Pfeffer &

Langton, 1988). Decisions about hiring, evaluation, promotion, and firing take place

largely within bureaucracies, and the biggest bureaucracies had personnel departments

charged with rationalizing these processes. If women systematically earn less than men

and experience careers that stall out well below the top rungs of the hierarchy,

organizations are the primary mechanisms that make it happen (e.g. Beckman & Phillips,

2005). Studies documented the features of organizations associated with inequality within

the firm--e.g., larger firms showed more dispersed wages, as did non-unionized firms,

those with more diverse workforces, and those organized more hierarchically (Kalleberg

& Vanburen, 1994). Thus, the relevant unit of analysis for understanding differences in

individual incomes is the organization. Put another way, organizations are a primary

mechanism for generating inequality in society.

The literature on organizational stratification has empirical implications for

society-wide inequality, but these implications have rarely been directly tested

previously. A notable exception is a study by Sorenson & Sorensen (2007), who examine

the dispersion of wages within particular regions in Denmark. The authors suggest that

changes in inequality can result from changes in corporate demography due to two types

of differentiation. Vertical differentiation distinguishes organizations of the same kind

(e.g., those in the same industry) on a particular dimension such as productivity or status.

Increasing vertical differentiation by increasing the number of firms of the same type can

increase inequality by sorting the highest quality (most productive) workers into the

highest quality firms, thus increasing the dispersion of wages within that industry. On the

other hand, increasing horizontal differentiation (that is, diversity in the kinds of

organizations) can reduce inequality by sorting workers into firms that best match their

talents. The authors find that increased numbers of organizations in the same industry

operating within a region leads to increased earnings inequality, whereas wage inequality

declines with greater variation in the kinds of organizations within a region.

This argument about corporate demography can be extended to explain

developmental patterns in inequality at the national level. The Kuznets curve can be

partly attributed to changes in the nature and size of employers due to industrialization.

Economies of scale that became feasible at the turn of the 20th century encouraged the

growth of very large-scale production within single organizations, often created through

the consolidation of dispersed regional industries into national oligopolies (Chandler,

1977). As industries matured, they became more concentrated, bringing more of the

workforce under the control of a small number of firms. The managerial innovations

described by Chandler were accompanied by innovations in production methods that

encouraged vertical integration on a vast scale. Ford’s River Rouge plant in Dearborn,

Michigan, for instance, employed 75,000 persons when it was completed in 1927, more

than the US Department of War at that time--and it continued to grow during the Great

Depression and the Second World War. Employees in vertically integrated industries

were subject to more regularized bureaucratic wage policies within a firm than outside a

firm, as internal labor markets replaced external ones.

Of course, what this should mean for aggregate inequality depends on the

employment practices of the relevant organizations. On the one hand, corporate

hierarchies are the essence of inequality, from the pyramid-shaped organization chart to

the corporate jets that whisk executives to their golf outings, and earnings are more

dispersed in large firms than small ones. On the other hand, the procedures for

stratification--sorting and ranking--are regularized and rationalized. CEOs may be well-

paid relative to their employees, but the divergence probably does not compare with that

between feudal lords and their serfs, or between hedge fund managers and temps at a call

center. Moreover, organizations vary among themselves in their stratification

procedures, even within the same industry (Baron & Bielby, 1980), and increased

numbers of firms within an industry are associated with greater inequality within a region

(Sorensen & Sorenson, 2007). This may imply that more concentrated employment—

that is, more workers employed by relatively fewer firms—is associated with a more

equal society, while more dispersed employment is associated with greater inequality.

This tendency is amplified by the ascendance of “winner-take-all” markets, in

which rewards are both highly concentrated among top performers and payoffs are

determined by relative rather than absolute performance (Frank & Cook, 1995). Due in

part to the spread of information and communication technologies, and the increased

globalization of trade, the rewards available to the world’s best soprano, or golfer, or

lawyer, or children’s author, are now vastly greater than those available to the 4th-best

soprano, golfer, lawyer, or children’s author—even though the absolute differences in

performance may be quite modest. Frank and Cook (1995) note several markets in which

this dynamic has greatly increased incomes at the very top: book publishing, business

consulting, movies and television, fashion modeling, professional sports, and executive

compensation. Notably, it is only the last market—and particularly in the case of

CEOs—that the market dynamics play out primarily within large organizations.

Consider a thought experiment in which a society has only one employer (say, a

caricature of the USSR, or some large college towns). There would undoubtedly be a

gulf in compensation between those in the Politburo and agricultural laborers--or between

the football coach and an assistant professor of kinesiology. But it would not be the

ocean that separates contemporary oil oligarchs and street vendors in Russia today. An

illustration of this is the fact that in 2004, the 25 best-paid US hedge fund managers

collectively made more than all of the CEOs of the S&P 500 combined (Kaplan & Rauh,

2007). Most CEOs are comfortably within the top 1% of the income scale, of course, but

the truly stratospheric levels of pay occur outside corporate hierarchies. Similarly, while

entry-level employees at AT&T or GE may not have been lavishly paid, they

undoubtedly beat the annual incomes of the temps that now work the landscaping crew.

Inequality is closely linked to social mobility. Here too, changes in corporate

organization have led to changes in patterns of mobility. Mobility refers broadly to the

ability to improve one’s socio-economic status. Prior research has focused largely on

inter-generational mobility. That is, how much is one’s class position determined by the

class of one’s parents? How likely are those born into a family in the bottom quintile of

income to end up in a higher income bracket? Societies vary substantially in their levels

of social mobility. Surveying the recent evidence for Europe and North America, Corak

(2006) finds that half the children of poor parents in the US grow up to be poor adults,

and 40% of the children of high-income parents grow up to be high-income adults,

indicating relatively low levels of intergenerational mobility. In Denmark, on the other

hand, children of the poor rarely grow up to be poor themselves. And as the case of

Denmark illustrates, although policymakers often lament that inequality is the price one

has to pay for a vibrant economy, and that efforts to reduce inequality will inevitably

bring down average incomes, GDP per capita is negatively correlated with inequality

cross-nationally, while the most unequal countries are also the poorest.

As with inequality, organizations are central to individual economic mobility

through their hiring and promotion practices. During the post-War era in the US, the

largest employers adopted systems intended to maintain and develop employees over

careers that could extend up to retirement. Pensions and benefits rewarded extended

commitments to the firm by premising their payouts on one’s tenure with the company.

Put another way, once an employee was “vested,” he or she paid a price to change

employers (Cobb, 2010).

Internal labor markets buffered jobs within the firm from external market forces.

As Doeringer and Piore (1971) defined the term, an internal labor market was

characterized by external recruiting for entry-level jobs and internal recruiting for higher-

level jobs through promotion. Jobs were typically organized into promotion ladders that

provided clear paths to upward mobility. Formalized job analysis, which tied wages to

objective characteristics of the work rather than to external market comparisons, further

bureaucratized the employment relation. ILMs fit with practices of on-the-job training

and worker investments in firm-specific skills (Williamson, 1975). By protecting the

employment relation from the vagaries of the market, workers were guaranteed stable

income and firms vouchsafed their investments in “human assets,” encouraging long-

term attachments between workers and firms.

In recent decades, commentators have mourned the breakdown of the system of

internal labor markets and the “death of the career.” Peter Cappelli (1999) describes the

broad shifts in the employment relation in recent decades from a long-term commitment

to a relatively short-term tryst. Paul Osterman (1996) refers to the “broken ladders” that

have accompanied the breakdown of the traditional system of ILMs, making individual

career paths less orderly and more likely to span multiple employers. Pfeffer and Baron

(1988) were among the first to document the rise and organizational implications of

temporary employment, while Barley and Kunda (2004) analyzed the longer-term

prospects of the “hired gun” independent contractor. Richard Sennett (2006) describes

how the new “post-corporate” employment relation discourages investment in firm-

specific skills and encourages a shallow generalism rather than the kind of craft that

develops with long experience. (Of course, one can have high levels of skill and pay

without dedicating oneself to a particular organization—professionals such as surgeons,

accountants, lawyers, and consultants fit this category.) Eileen Applebaum and her

collaborators (2003) document how this new system has taken a particular toll on low-

wage workers. For a generation of employees, entry-level jobs have become dead-end

jobs: young men entering the labor force in the early 1990s were more than twice as

likely to be stuck in low-wage jobs ten years later than young men entering the labor

force in the early 1970s (Bernhardt, Morris, Handcock, & Scott, 1999).

We do not want to wax nostalgic for some lost golden era of the organization

man. Chinoy (1955) pointed out the stark divergence between the façade of corporate

meritocracy and the experience of workers on the line, who rarely enjoyed the upward

mobility promised by the American Dream. And Kafka is still the greatest chronicler of

life in a bureaucracy. But with the death of the bureaucratic career has come the death of

clearly-defined pathways to mobility. In a previous era--at least in theory--a kid from

Brooklyn could take a job in the mailroom and work his way up to the CEO’s office by

understanding the game and achieving the markers of accomplishment. But the trend

toward flattening hierarchies (documented by Rajan & Wulf, 2006) limits the promotion

prospects for those in management, and networks of contractors form no clear upward

ladder for individual workers. Today, mobility--both upwards and downwards--

resembles a game of chutes and ladders. Teenagers that create a clever social networking

website might find themselves billionaires when they sell their business two years later,

and homeowners that bought and sold their Las Vegas condo at the right time could retire

early on their real estate winnings. On the other hand, middle managers at major

corporations might find themselves unemployed when their firm is bought by a

competitor; design engineers and radiologists learn that their talents are more cheaply

replicated offshore; and those in the lower middle class can wind up in bankruptcy due to

a sudden illness or a poorly-timed home purchase.

The implication of this discussion is that if stratification happens in organizations,

then broad changes in organizational processes should lead to changes in inequality and

mobility at the societal level. We next discuss how the corporate world in the US has

organized and re-organized over the past half-century.

Corporate restructuring and trends in employment

concentration

The nature of corporate employment in the US has changed substantially since

Kuznets wrote in the 1950s. One master trend is the shift to post-industrialism, as the

largest employers have transitioned from manufacturers such as GM to retailers like Wal-

Mart. Along the way we experienced a major merger movement in the 1960s that greatly

increased employment concentration; a bust-up takeover wave in the 1980s that largely

undid the mergers of the 1960s; and the rise of the “virtual” or network organization, in

which networks of contractors organized by lead firms became perhaps the predominant

model of industry organization in manufacturing and, to a lesser extent, services.

(Following industry parlance we refer to this as the “OEM model,” for “original

equipment manufacturer.”)

Post-industrialism is the dominant trend in the composition of the American labor

force. In 1944, 45% of the non-farm workforce in the US was employed in

manufacturing--the high-water mark for industrial employment in the US (see Figure 2

below).3 This number quickly dropped with the end of the war and has maintained a

pattern of secular decline ever since. Nonetheless, for generations the largest corporate

employers were predominantly manufacturers of autos, steel, and oil. Eight of the top ten

in 1950, seven of the top ten in 1960, and eight of the top ten in 1970 were

manufacturers. In absolute terms, June 1979 saw the greatest number of employees in

manufacturing, at 19,676,000 (roughly 22% of the nonfarm labor force). The ten largest

3 Data in this section come from the US Bureau of Labor Statistics at www.bls.gov .

corporate employers in 1979 included GM, AT&T, Ford, Sears, GE, ITT, IBM, Kmart,

GTE, and Mobil. Many of these firms had topped the list since the days of the Great

Depression, and their personnel policies had shaped the fates of generations of

employees. Moreover, their human resource practices shaped the broader cultural

context of employment, including the personnel policies of their competitors through

pattern bargaining and suppliers through emulation and labor market competition (see

Jacoby, 1997; Levy & Temin, 2007, for historical accounts).

Insert Figure 2 about here

Insert Table 1 about here

Thirty years later, manufacturers employ a vanishingly small proportion of the

workforce. From the turn of the 21st century to the beginning of 2010, the US lost one-

third of its remaining manufacturing jobs, and at the time of this writing less than 9% of

the non-farm labor force works in manufacturing. Nine of the 12 largest domestic

corporate employers are in retail, with Wal-Mart at the top of the list; none were

manufacturers (Davis, 2009b).

The shift from manufacturing to service has changed the characteristic nature of

the employment relation among the largest employers. In manufacturing, large size

tended to correspond to long employment tenure and relatively high wage and benefit

packages. ILMs existed in part to vouchsafe firm-specific assets. Thus, in 2004 the

median autoworker had been with his or her employer eight years; the median employee

in electrical equipment and appliance manufacturing had been with their firm ten years;

and those in petroleum and coal products manufacturing had 11 years’ tenure (Davis,

2009a, chap. 3). Production employees in auto manufacturing in 2008 earned average

hourly wages of over $27. Today’s largest employers are in retail, where typical tenures

are quite short: just three years on average for full-time employees. Average wages for

sales employees in general merchandise stores (the most common occupation) were just

over $9 per hour in 2008.4 Correspondingly, employee turnover is often high: at Wal-

Mart, estimated turnover is 40% per year (Meyerson, 2009). The coexistence of both

gargantuan size and very high turnover, as at Wal-Mart, has not been seen for

generations—if ever.

At the same time, there have been several waves of corporate restructuring that

changed the boundaries of firms and industries. The merger wave of the 1960s

substantially increased the size of many corporations, as acquisitive conglomerates such

as ITT, LTV, Litton Industries, and Gulf + Western grew dramatically through

acquisition. ITT grew from 132,000 employees in 1960 to 392,000 in 1970 through

several hundred acquisitions that included Hartford Insurance, Sheraton Hotels,

Continental Baking (maker of Wonder Bread and Twinkies), Avis Rent-a-Car, Rayonier,

Cleveland Motor, and many others. In his 1997 apologia for the conglomerate, Harold

Geneen—who ran ITT through the 1960s and 1970s—explained that ITT was not just a

passive holding company, buying and selling companies in its portfolio, but a relatively

intrusive parent eager to impose its managerial practices on the companies it bought: “An

‘operating conglomerate’ is a centrally managed company that gets deep into each of its

operations…Its job is to own and operate companies—ideally, through its strong,

centralized management” (Geneen, 1997, pp. 21, 25). Thus did the human resource

practices of one corporation spread to dozens of industries.

4 Wage data come from the Bureau of Labor Statistics at www.bls.gov.

The biggest firms also grew even bigger during this decade. GM added 100,000

workers during the 1960s, and AT&T added almost 200,000 employees to its already vast

labor force. (For comparison purposes, the current incarnation of AT&T—still one of the

largest US employers—had a total of 281,000 workers as of its 2010 annual report.) By

the late 1960s, through both organic growth and acquisition, employment reached a level

of concentration in the US not seen before or since, providing a direct mechanism for the

homogenization of human resource practices. Corporate expansion continued at a more

modest pace through the 1970s, as growth by acquisition continued to be a dominant

corporate strategy, taught by business schools and spread by consultants bearing

growth/share matrix charts.

The relentless drive for growth that had characterized US corporations since the

beginning of the 20th century reached an abrupt halt during the 1980s. By the early part

of this decade, diversified firms such as ITT faced a chronic “conglomerate discount” in

which the stock market value of the whole was worth less than the parts would have been

worth as free-standing companies. Moreover, the strategy of diversification had spread

widely among US corporations: in 1980, the median large corporation operated in three

distinct industries (Davis, Diekmann, and Tinsley, 1994). This created a great

opportunity for takeover entrepreneurs that only required a few regulatory changes to

unleash--in particular, a policy of reduced scrutiny of intra-industry mergers announced

by the Reagan Justice Department in 1982, and a Supreme Court decision striking down

state anti-takeover laws the same year. The result was a wave of so-called “bust-up”

takeovers, in which undervalued conglomerates were purchased with the intention of

being split back up into their component parts and either operated as free-standing

companies or sold to buyers in related industries. During this decade, one in three

Fortune 500 firms was acquired or merged, resulting in a far more industrially-focused

corporate sector--and a managerial class much more attuned to share price (Davis,

Diekmann, & Tinsley, 1994).

The ambient threat of takeover prompted other firms to restructure by divesting

“non-core” businesses, and through both voluntary and involuntary restructuring the

largest employers substantially retrenched during the 1980s. GE’s employment under

CEO Jack Welch shrank from 400,000 to 300,000 between 1980 and 1985, and other

firms followed GE’s example. Meanwhile, AT&T was forced to break up into a long-

distance company and seven regional “Baby Bells” in 1984, and Lucent was

subsequently separated from AT&T in 1996. By the early 1990s, large-scale layoffs had

become a common (if not fully legitimate) element in the CEO’s toolkit (Budros, 1997),

and even prototypical career employers such as IBM and AT&T joined the movement to

“streamline” their employment. Those who had joined such firms out of college in the

expectation of a comfortable career protected by an internal labor market found a new

deal at work (Cappelli, 1999). Even the notion of what is “core” became more flexible.

In the American auto industry, which had been among the most vertically integrated in

the world, the two largest players spun off major parts suppliers into (more or less) free-

standing companies. GM spun off Delphi in 1999 (immediately creating a new Fortune

100 company), while Ford spun off Visteon the following year.

After the bust-ups of the 1980s and the advent of activist shareholders, corporate

elites became far more attuned to the consequences of their strategies for “shareholder

value,” not least because of the widespread adoption of option-based compensation

practices that tied their personal wealth to the company’s market value. The quest to

create shareholder value took on almost religious aspect among corporate elites.

Corporate mission statements of the late 1990s routinely announced that the corporation

existed to “create shareholder value,” with the company’s actual business (sodas,

sneakers, pharmaceuticals, online pornography) serving as means to that end (Davis,

2009a, chap. 3). Announcements of acquisitions, spinoffs, or restructurings in the 1990s

were inevitably accompanied by a nod to Wall Street, which made clear its preference for

“intellectual property” over tangible assets. This in turn led to the widespread adoption

of an OEM or network model of organization and the disaggregation of employment

across firms.

The prototype of the contemporary OEM corporation is Nike. Nike designs and

markets sneakers and athletic gear sold around the world, and its familiar “swoosh” logo

represents one of the most recognized brands ever created. Yet in spite of its global

dominance in athletic apparel, Nike employees a mere 34,300 persons. Quoting the

company’s 2009 10K, “Virtually all of our footwear is produced outside of the United

States. In fiscal 2009, contract suppliers in China, Vietnam, Indonesia and Thailand

manufactured 36%, 36%, 22% and 6% of total NIKE brand footwear, respectively... Our

largest single footwear factory accounted for approximately 5% of total fiscal 2009

footwear production.” The firm itself is the central node in a network of supply chains

stretching around the world, from production to distribution, but its own employees

engage primarily in the high-end tasks R&D and marketing.

The Nike model has been widely emulated across a variety of industries, to the

evident delight of Wall Street analysts. In explaining his own firm’s move to “de-

verticalize” by selling off its factories to contractors in 1997, Sara Lee CEO John Bryan

stated, “Wall Street can wipe you out. They are the rule-setters. They do have their fads,

but to a large extent there is an evolution in how they judge companies, and they have

decided to give premiums to companies that harbor the most profits for the least assets.”

Corporations increasingly look like the nexus-of-contracts described by financial

economists, with intellectual property (patents, trademarks, brands, product designs,

marketing savvy) residing at the center.

It is not just the manufacturing sector that has embraced outsourcing. Thanks to

the pervasive spread of high-speed Internet connections, services are also increasingly

susceptible to offshoring. Blinder (2006) estimated that perhaps 40 million service jobs

in the US faced competition from overseas, from tutoring schoolkids via Skype to

processing mortgage applications to decoding the human genome. Offshoring allows

firms to grow to great scale with relatively few direct employees. Indeed, California-

based Vizio—the largest brand of LCD televisions in the US, with a 22% market share—

had only 160 employees as of 2009, as assembly and supply chain management are done

by contractors in Taiwan (http://www.vizio.com/about/).

One result is that it is increasingly difficult to determine who actually produced

the goods and services we consume. Designer clothing has long been created by

contractors, of course. Consumer electronics are overwhelmingly produced by unknown

“board stuffers” such as Solectron, Ingram Micro, Jabil Circuit, and others--not Apple,

Hewlett-Packard, Sony, Dell, or other firms that furnished the brand. Dozens of

competing pet food brands are manufactured by the same vendor in Ontario--a fact that

was revealed when it turned out the chow had been tainted with melamine further up the

supply chain. Baxter Health’s blood thinner Heparin was recalled when it killed dozens

of patients and injured hundreds more due to toxins in the raw materials procured by its

Chinese manufacturer. And even prisoner interrogations and CIA assassinations have

been handed off to contractors (see Davis, 2009a for elaboration). Thus, due to broad

corporate restructuring toward an “OEM economy,” prospects for career advancement

within a particular firm are dim, as the more typical form of organization is the network

of contractors.

Corporate restructuring is one mechanism standing between the rise of finance

and increased inequality. Scholars have noted another: the meteoric rise of compensation

levels on Wall Street, which is disproportionately responsible for the rise in overall

inequality in the US (Kaplan & Rauh, 2007). Goldman Sachs employees earned an

average of more than $700,000 apiece in 2009, and their colleagues in hedge funds

routinely earned large multiples of this amount. As faculty in business schools can attest,

the most remunerative jobs by far are in finance, and particularly in the smaller free-

standing entities such as hedge funds.

Summarizing, the American economy has shifted in ways that are potentially

consequential for economic inequality, particularly if we view organizations as critical

mechanisms for stratification. Employment became far more concentrated during the

1960s due both to organic growth among the largest firms and through acquisition-driven

growth among the new conglomerates. During the 1980s, many of the largest firms were

acquired and broken back up, while others voluntarily restructured or downsized, thus

lowering overall employment concentration. This trend accelerated during the 1990s,

through layoffs and divestitures, and the 2000s, with the spread of the OEM model.

Data We now move to an exploration of newly-available data on the connection

between employment concentration and inequality both within the US and around the

world. Our expectation going in was that increased concentration would be modestly

associated with lower levels of income inequality. The findings show that this

relationship is surprisingly strong. We first describe the sources of the data and define

our measures. We then present time-series data for the United States from 1950 to 2006,

and cross-national comparisons for 53 countries in 2006.

Measuring social inequality: the Gini coefficient

The Gini coefficient measures the extent to which the distribution of income or

consumption among individuals or households deviates from a perfectly equal

distribution. The Lorenz curve (Lorenz, 1905) is a graphical representation of cumulative

income share on the vertical axis and the distribution of the population on the horizontal

axis. Specifically, each point on the Lorenz curve represents the share of income held by

X-percent of the population (see Figure 3 below). The Gini coefficient (Gini, 1913), the

most commonly used measure of inequality, measures the percentage of area that lies

between the Lorenz curve and a line of perfectly equality. The coefficient varies between

0, which represents complete equality and 1, which indicates complete inequality (i.e. one

person controls all income). Typically, the Gini coefficient is represented in percentage

terms. Because the Gini coefficient is scale independent it allows for comparisons across

countries or regions. The primary advantage of using the Gini coefficient to measure

inequality is that, unlike GDP statistics, it represents a distribution across the entire

population within a country. Absolute levels of average poverty or wealth are compatible

with either high or low inequality. In 2006, the Gini coefficient and GDP per capita were

correlated at the -0.43 level among 73 countries in the World Development Indicators

database. As Figure 4 shows, low levels of GDP per capita are consistent with a wide

range of levels of inequality, whereas high levels of GDP per capita are consistent with

both low and moderate levels of inequality.

Insert Figure 3 about here

Insert Figure 4 about here

US data

Historical Gini coefficient data for the United States came from the World Income

Inequality Database (2008). This database compiles longitudinal inequality data from a

variety of sources for 166 countries. It is common that there are multiple entries for a

country in a given year - typically based on calculations with different units of analysis

(e.g individual or household) and different definitions of income (e.g. net, gross,

disposable). Because slightly different measures of inequality are obtained based upon

the unit of analysis and income source it is important to use consistent measures over

time. There were two sources in the World Income Inequality Database that used the

same unit of analysis and definition of income in calculating the Gini coefficient for the

years 1950 to 2006. The Gini data for years 1950 to 1967 came from Brandolini (1998),

and the US Census Bureau provided data from 1968 to 2006. Household, gross monetary

income was used in all calculations and both sources relied on data taken from the

Current Population Survey.

Our primary independent variable is employment concentration, defined as the

ratio of the number of workers employed by the 10 (or 25, or 50, or 100) largest domestic

corporations and the size of the overall workforce. To the best of our knowledge, this

chapter is the first use of this measure in the literature. Of course, industrial organization

economists and antitrust authorities have long used the four-firm (or eight-firm)

concentration ratios based on sales to analyze the level of competition within an industry.

These statistics calculate the proportion of an industry’s total revenues accounted for by

the four largest participants; high concentration ratios were taken as evidence of

oligopoly. Our measure is analogous but differs in that (1) we are indifferent as to

industry, and (2) our denominator is the entire workforce of a nation.

Corporate employment data came from Compustat and company 10Ks. Firms

typically report the size of their overall workforce, both domestic and foreign, and this is

the number provided in Compustat. Some (but not all) also report separate figures for

domestic and foreign employment, but this is only available by manually reading annual

10K statements. We did this for all large US firms beginning in 1994 (the year the SEC

opened the possibility of on-line financial disclosures). Unfortunately, it was not feasible

to track archives of all annual 10K statements back until 1950. We opted instead to use

the Compustat figures for employment for consistency over time. During the years of our

study when both figures were available, the correlation between annual employment by

the top 10 employers using the Compustat figures for overall employment and the figures

for domestic-only employment from 10Ks was .95. This suggests that aggregate

domestic and global employment were roughly proportional, and that our measure of

concentration is a reasonable proxy. Figure 5 compares data from Compustat and our

hand-compiled data from corporate 10K statements for all available years.

Insert Figure 5 about here

Labor force data came from the United States Bureau of Labor Statistics

(www.bls.gov). The size of the labor force is defined as the sum of all employed and

unemployed persons. We also used a measure of labor force excluding farm workers and

one excluding non-government workers, and the results were similar.

We compiled employment concentration using the largest 10, 25, and 50

corporate employers, and found that these numbers were correlated at over .87 over time.

Because it was often difficult to consistently locate firms beyond the ten largest outside

the US, we use the 10-firm employment concentration ratio in our analyses. Based on 57

years of data from the US case, we argue that the size of the ten largest employers is

roughly proportional to the sizes of the next tiers of large employers. In other words,

employment concentration among the biggest firms is an indicator of a broader

underlying tendency toward large (or small) organizations relative to the size of the

economy.

Global data

For our cross-national comparison we report data for the year 2006, the most

recent year for which we have inequality data available. Gini and labor force size data

are available from the World Bank’s World Development Indicators (2008).

Data on the largest firms came from two sources, the WorldScope Global (2006)

database supplemented by data from the Orbis online database (2009). We downloaded

all companies available from WorldScope for the year 2006 and identified the 10 largest

companies per country. There were 37 countries for which there were enough companies

to create a reliable employment concentration figure. In an effort to include the

maximum number of countries as possible, we then used Orbis to construct measures for

countries not covered by WorldScope. One issue with the Orbis is that the employment

data for many companies is not available. Therefore, we examined the largest non-public

firms based on total revenue, keeping countries for which there was employment data for

7 of the largest 10 and 10 of the largest 15 firms in terms of revenue. This provided 18

additional countries to our sample, giving us 53 total countries.5

Findings

The United States, 1950-2006

Figure 6 shows the 3-year moving average of employment concentration and the

3-year moving average of the Gini coefficient for the United States between 1950 and

2006. The wave of industrial consolidation throughout of the 1960s and early 1970s had

considerable impact on employment growth among America’s largest firms. Between

1968 and 1973, the United States had its six highest years of employment concentration.

The lowest level of inequality came in 1968, when the Gini was 38.7. Of the ten years of

lowest inequality, six are among the ten years of highest employment concentration. The

cumulative effect of hostile takeovers, spin-offs and bust-ups in the 1980s had an equally

profound effect on employment among America’s largest companies. Employment

concentration began to decline from the early 1980s through the early 1990s where

concentration levels have remained low. The years 2003 and 2004 shared the highest

levels of inequality, where the Gini coefficient reached 46.4. Of the ten years of highest

inequality, five are among the ten years of lowest employment concentration.

Insert Figure 6 about here

5 Though used by other researchers in creating country-level measures of business concentration (e.g. La

Porta et al. 2007), one limitation of the WorldScope data is that it does not include privately-held

companies. This may understate the level of employment concentration in some countries.

Not surprisingly, the correlation between employment concentration and

inequality in the United States annually is very high, at -0.80. The data presented here

suggests that inequality and concentrated employment in the United States are highly and

negatively related over time. We would argue that these results are causal: employment

concentration, through the organizational mechanisms we have described above, lowers

overall income inequality across the economy.

Figure 7 provides an alternative way to visualize the historical trajectory of

employment concentration and inequality over time. Each point represents the values of

these two dimensions for a given year, and lines connect one year to the next, from the

beginning to the end of our sample period. A downward slope indicates changes over

time consistent with the narrative we have described. As is clear from the Figure, there

were three eras of significant shifts in the profile of concentration and inequality: the

1960s, when concentration increased and inequality declined; the 1980s, when

concentration decreased and inequality rose; and the 1990s, when concenctration further

decrased and inequality leapt. Interestingly, as Figure 7 shows, this trend reversed during

the 2000s, as employment concentration increased again, while inequality

correspondingly declined.

Insert Figure 7 about here

Alternative interpretations normally take two broad forms: the implied causal

relationship is actually reversed (in this case, inequality causes lower employment

concentration, rather than the other way around), or a third factor creates a spurious

relation. The first is difficult to rule out on statistical grounds: regressing inequality on

concentration yields much the same results as regressing concentration in inequality, with

various forms of lag and assorted control variables (size of the labor force,

unemployment, the proportion of the workforce in manufacturing—all of which have a

significant negative effect on inequality). But the best model fit by far (see Table 2

below), is one in which inequality in the current year is a function of employment

concentration in the current year, unemployment in the current year, and the proportion

of the workforce employed in manufacturing (which, as we have discussed, is

monotonically decreasing throughout the sample period—see Figure 2). Moreover, it is

difficult to conceive of a process in which inequality has a short-term effect on corporate

concentration in quite the same way that concentration has an almost mechanical effect in

reducing inequality. It is possible to theorize longer-term processes in which, say,

inequality reduces ambient trust in society, which in turn reduces the feasible size of the

largest organizations (cf. LaPorta, Lopez-deSilanes, Shleifer, & Vishny, 1997), but such

processes are unlikely to take place over the short periods in which we observe reversals

in trends in both concentration and inequality. We return to this interpretation when we

describe the cross-national findings below.

Insert Table 2 about here

Another alternative explanation for these findings is that increasing inequality is

due to declining rates of unionization. If true, this could create a potentially spurious

relation between employment concentration and inequality via rates of unionization.

Organized labor is often credited for the role it played in the dramatic growth of the

middle class in the U.S. during the 1950s and 60s (see Dubofsky, 1994; Levy & Temin,

2007). After the Second World War, a system of corporate-sponsored health care,

pensions, and wage security was enshrined in the so-called “Treaty of Detroit” (Bell,

1950), a grand labor agreement negotiated in 1950 between General Motors and the

United Auto Workers. The two cornerstones of this contract were that it linked wage

increases to productivity improvements and secure, long-term employment was

guaranteed for worker loyalty (Osterman, Kochan, Locke, & Piore, 2001, chap. 1). The

major features of the Treaty of Detroit eventually spread throughout many industries and

influenced human resource practices in most of the largest firms. The end result of this

process was sustained and dramatic improvement in wages and benefits for many

working-class citizens, and a corresponding decrease in inequality (Levy & Temin,

2007)—at least over part of the period we examine.

To illustrate, in 1922 the average machine operator in the auto industry earned 66

cents per hour. By 1940 (after the advent of the United Auto Workers) average earnings

were 96 cents per hour, and by 1957 they grew to $2.29 per hour (Macdonald, 1963, p.

138). Additionally, in 1947 General Motors paid an average of 18 cents per hour in

fringe benefits to employees; by 1960 that had increased to 72 cents per hour

(Macdonald, 1963, p. 40). That same machine operator in the early 1970s earned more in

real terms than a manager had earned in 1950 (Levy & Temin, 2007). There is little

debate that these wage and benefit increases were influenced by organized labor. Thus, it

is likely that declines in unionization help explain rising inequality; in fact, the

correlation between union density rates and the Gini coefficient is -0.59. However, as

Figure 4 indicates, rates of unionizaton have experienced an almost continuous secular

decline since the late 1950s, while inequality—like employment concentration—has

exhibited a more varied pattern. Indeed, the sharp decline in inequality from 1962 to

1972 coincides with significant decreases in unionization. Though we cannot rule out the

possibility that unionization density rates do not adequately reflect the influence of

organized labor on wage patterns, declines in unionization do not appear to be a sufficient

explanation to explain the changes in inequality in America over time.6

Insert Figure 8 about here

Of course, our examination of the post-War era in the US is essentially a case

study. Other explanations are more readily considered in the context of cross-national

comparisons, which we turn to next.

Cross-national comparisons, 2006

Figure 9 shows the link between employment concentration and inequality at the

country level. The correlation between income inequality and employment concentration

among our cross-section of countries is -0.47, providing additional evidence for a

relationship between inequality and the prevalence of large corporate employers within a

country. One of the most striking features of Figure 9 is the extent to which

“neighborhoods” in the diagram correspond to geographic regions which, in turn,

correspond to different models of national economic organization or “varieties of

capitalism” (cf. Hall & Soskice, 2001). Amable (2003) distinguishes five broad

configurations of capitalism at the national level: a social democratic or Nordic model; a

Meditarranean/Southern European model; a Continental European model, corresponding

primarily to Western Europe; an Asian model that encompasses Japan and Korea; and a

neoliberal (primarily Anglophone) model. Each has distinct clusters of features when it

comes to labor market institutions, social welfare provision, systems of financial

intermediation, and product market dynamics.

6 For example, it is possible that during this 10-year period non-union firms, in the attempt to stave off

organized labor, continued to increase wages thereby understating the influence of union strength during

this period

Insert Figure 9 about here

We find similar clustering in Figure 9 documenting the link between employment

concentration and inequality. The Nordic countries are spread over the bottom of the

lower right quadrant, with low inequality and relatively concentrated employment.

Continental European countries have higher inequality but generally lower levels of

employment concentration—although here we find, as did Amable (2003), that

Switzerland and the Netherlands are outliers, with high levels of employment

concentration relative to other non-Nordic European countries. Meditarranean countries

form a cluster with similar levels of inequality but less concentrated employment.

Intriguingly, Japan and Korea are clustered on the off-diagonal with most former state

socialist countries, Austria, and Germany, where both inequality and concentration are

relatively low. Other Asian countries (including China, Malaysia, the Philippines,

Thailand, and India) exhibit substantially higher levels of inequality and relatively lower

levels of concentration, undermining the notion of a single “Asian model.” Finally, we

find that the Anglophone countries defy a clear clustering and exhibit rather varied

patterns of inequality and concentration, with the US being particularly distinguished by

its high level of inequality.

We also find two other clusters that do not correspond to any identifiable “variety

of capitalism.” At the very highest levels of inequality and the lowest levels of

concentration are the Latin American countries. In Colombia, the most unequal country

in our sample, no single firm employs as many as 10,000 people—in spite of the fact that

the nation contains a population of 45 million people. (Denmark, by contrast, contains

just 5.5 million people but houses two firms employing over 200,000 persons each.)

Below the “Latin quarter” is a cluster of African and Asian countries, with moderate

levels of inequality but relatively low levels of concentration.

The United States is effectively in the middle, with moderate levels of

concentration and moderate-to-high inequality. It is comparatively close to countries

such Sri Lanka, Tunisia, Ghana, Senegal and the Russian Federation in terms of

inequality, while its neighbor to the north, Canada, much more closely resembles a

European country. In a sense, the US fits no cluster.

Broadly speaking, the cross-national results corroborate the pattern within the US

showing a link between the nature of corporate organization and society-wide levels of

inequality. But such a link is not a simple one-to-one matching. Rather, the observed

pattern of relations indicates that there is a “wedge”: low employment concentration is

compatible with both great inequality (the Latin American economies) and relative

equality (the former state socialist countries), but high concentration seems to drive out

inequality. We explore this idea in the next section.

Discussion

Both over time within the US and cross-nationally, income inequality covaries

strongly with the extent to which a substantial part of the labor force is employed by a

relatively small number of firms. The degree of employment concentration is a concept

new to the organizational literature, yet as our findings here document, there is good

reason to believe that it has a strong causal connection with economic inequality—

specifically, that increasing concentration reduces overall inequality.

Based on the American case, the link between concentration and inequality may

be straightforward. As more employees are brought within the control of a single

employer, their compensation becomes subject to bureaucratic rationalization. Salaries

vary by hierarchical level, of course, but the extent of disjunture from one level to the

next is limited, with the possible exception of the very apex. Extremes at the top and

bottom of the economy’s income distribution are more likely to occur outside the

corporate ambit. At the very top are winner-take-all markets for individual talents, or

boutique firms such as investment partnerships in which stratospheric salaries might be

shared by a small number of partners. The very bottom is characterized by intermittent

employment with relatively tentative attachments. Corporate employers occupy the

middle; to the extent that employment is concentrated within them, overall inequality is

reduced.

This account suggests that the logically prior question is, What accounts for

organizational size? Why is it that at some times and in some places “small is beautiful,”

while at other points bigger is better? Here, the cross-national evidence is rich with

implications. We find that low employment concentration is compatible with a wide

range of inequality, from relatively equal former socialist countries such as Hungary and

the Czech Republic to the wild extremes of inequality in Brazil and Colombia. But as

employment becomes more concentrated, the top levels of inequality are attenuated. As

with all cross-sectional comparisons (and particularly cross-national ones), a range of

alternative interpretations is possible. Perhaps a basic level of horizontal trust within a

society is necessary to build relatively large-scale organizations (cf. LaPorta et al., 1997),

and inequality corrodes trust. Put another way, relative equality engenders trust, which

enables large-scale organizing. This might help explain the paucity of large

organizations in countries with troubled histories such as Colombia, Chile, and

Argentina, and the relative gigantism of several companies in Scandinavia, where

ambient interpersonal trust is high. It also implies that, other things equal, former

socialist countries would have an easier path to growing large domestic businesses than

Latin countries. On the other hand, the case of Russia sits uneasily with this account, as

it is home to some of the largest firms in the world (such as Gazprom, Rosneft and

Lukoial – each among the 100 largest firms in the world), yet ambient trust is relatively

low, and inequality is moderate to high (at about the same level as the US).

Our findings suggest that variation in organizational size is likely to depend on

several factors, including interactions among technology, national culture, and

managerial ideologies. To date, this topic has received almost no attention. But it

suggests another avenue by which conceptions of the corporation, its purpose, and its

place in society influence broader social outcomes.

Conclusions

In this chapter we have introduced the concept of employment concentration and

linked it to inequality at the societal level. Focusing primarily on the case of the United

States, we have argued that employment concentration—the extent to which a large

proportion of the labor force is employed by the largest firms, rather than dispersed

among smaller firms—reduces the overall level of income inequality in an economy, as

more of the workforce is brought under the wage and employment practices of a smaller

set of firms. We call this the paradox of hierarchy: corporations are generally

hierarchical, with those at the top earning incomes many times larger than those at the

bottom, and larger firms are more hierarchical than smaller firms. Yet societies in which

more of the workforce is employed in the largest firms are more equal overall than those

where employment is spread more widely. Our data and narrative track this regularity

over the post-War American economy, documenting a clear co-movement between

employment concentration and inequality.

We attribute the most recent explosion of inequality in the US in part to finance-

driven corporate restructuring that has favored the dispersal of employment among OEM

networks. This organizational explanation contrasts with the standard economic account,

which attributes inequality to technologically-driven changes in the skill mixes required

by high-paying jobs. If the standard account were true, we might expect to see radical

increases in inequality among countries in the technological vanguard. But cross-national

comparisons belie this account, as many of the most technologically advanced economies

are also among the least unequal. Japan and the Nordic countries are among the most

economically equal societies in the world, and Germany and Korea experience far less

inequality than the US. We argue that organizational employment practices are the

proximal cause of more or less social inequality. As Pfeffer (2010) has recently argued,

environmental sustainability has become central on the agenda of corporate managers

even as “human sustainability” has fallen off. We hope that this paper provides one

avenue into addressing this concern.

Organizational practices are not the only factor influencing inequality, of course.

But the data we present suggest an intriguing theoretical role for organization theory in

linking economic change and societal outcomes, such as inequality. Our findings open

up a potentially fruitful new area of research. Availability of better data going forward

will allow a more fine-grained understanding of the processes generating societal

mobility and inequality. In future work, we anticipate analyzing cross-national data

similar to the American case we have analyzed here. If the US is not unique, then we

may be able to provide a robust explanation of social inequality rooted in organization

theory.

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Table 1. Largest 10 Employers in the U.S., 1950-2009

1990 2000 2008

General Motors Corp Wal-Mart Stores Wal-Mart Stores

Sears Roebuck & Co General Motors Corp United Parcel Service Inc

IBM Corp McDonald's Corp McDonald's Corp

Kmart Corp Unted Parcel Service Inc IBM Corp

Ford Motor Co Ford Motor Co Target Corp

Wal-Mart Stores Sears Roebuck & Co Yum Brands Inc

Pepsico Inc IBM Corp Citigroup Inc

General Electric Co General Electric Co Kroger Co

AT&T Corp Kroger Co Sears Holding Corp

Olsten Corp J C Penney Co General Electric Co

1950 1960 1970 1980

AT&T Corp General Motors Corp AT&T Corp AT&T Corp

General Motors Corp AT&T Corp General Motors Corp General Motors Corp

United States Steel Corp Ford Motor Co Ford Motor Co Ford Motor Co

General Electric Co General Electric Co General Electric Co General Electric Co

Sears Roebuck & Co United States Steel Corp ITT Industries Inc Sears Roebuck & Co

Bethlehem Steel Corp Sears Roebuck & Co Sears Roebuck & Co IBM Corp

Ford Motor Co Great Atlantic & Pacific Tea

Co IBM Corp ITT Industries Inc

Chrysler Corp Exxon Corp Chrysler Corp Kmart Corp

Exxon Corp Bethlehem Steel Corp Western Electric Co Inc Mobil Corp

Westinghouse Electric Corp ITT Industries Inc United States Steel Corp GTE Corp

Table 2. Time-series regression estimates of Income Inequality in the U.S., 1950-2006

Variables

Model 1

Coefficient Standard Error

Unemployment (%) -.551

***

.106

Union Density (%) -.024 .032

Employment Concentration (%) -2.947

***

.387

Constant

56.795

***

1.216

Observations 57

R2.7571

p < .05;

p < .01;

***

p < .001

Tests are two-tailed

Figure 1. Income Inequality in the U.S., 1950 - 2006

32 36 40 44 48

Gini Coefficient

1950 1960 1970 1980 1990 2000 2010

Year

Figure 2: Percentage of U.S. Labor Force Employed in Manufacturing and Services, 1938-2008

020 40 60 80

1940 1950 1960 1970 1980 1990 2000 2010

Year

% Labor Force in Manufacturing % Labor Force in Services

Figure 3. Lorenz Curve and Gini Index

Figure 4. Cross-National Comparison of Income Inequality and Average Wealth, 2006

Algeria

Argentina

Australia

Austria

Belarus

Brazil

Bulgaria

Burundi

Cameroon

Canada

Chile

China

Colombia

Congo

Cote d'Ivoire

Croatia

Czech Republi c

Denmark

Egypt

Finland

France

Germany

Ghana

Greece

Guatemala

Honduras

Hong Kong

Hungary Iceland

India

Indonesia Ireland

Israel

Italy

Japan

Jordan

South Kor ea

Malaysia

Mali

Mexico

Morocco

Netherlands

New Zealand

Norway

Pakistan

Panama

Peru

Philippines

Poland

Portugal

Romania

Russi an Fed

Senegal

Serbia

Singapore

Slovakia

Slovenia

South Af rica

Spain

Sri L anka

Sweden

Switzerland

Thailand

Togo

Tunisia

Turkey

Ukraine

United Kingdom

United States

Uruguay

Venezuela

Vietnam

20 30 40 50 60

Gini Coefficient

010,000 20,000 30,000 40,000

GDP per capita (constant 2000 US$)

Figure 5: Comparison of Total and Domestic Employment Figures in US, 1993-2008

2 4 6 8 10 12

Number of Employees (millions)

1993 1996 1999 2002 2005 2008

Year

Total Domestic Employees - Top 10 Firms Total Employees - Top 10 Firms

Total Domestic Employees - Top 50 Firms Total Employees - Top 50 Firms

Figure 6. Three-Year Moving Average of Income Inequality and Employment Concentration in the United States, 1950 - 2006

32 36 40 44 48

Gini Coefficient

02468

Ratio of Top 10 Employers to Labor Force

1950 1960 1970 1980 1990 2000 2010

Year

Employment Concentration Income Inequality

Figure 7. Income Inequality and Employment Concentration Plot in the U.S. by Year, 1950 –2006

1950

1951

1952

1953

1954

1955

1956

1957

1958

1959 1960

1961

1962

1963 1964

1965 1966

1967

1968

1969

1970

1971 1972 1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001 2002

2003 2004

2005

2006

38 40 42 44 46

Gini Coefficient

33.5 44.5 5

Ratio of Top 10 Employers to Total Labor Force

1960s:

Conglomerate mergers

increase concentration;

inequality declines

1980s:

Bust-up takeovers split

conglomerates back into

parts; inequality increases

1990s:

Quest for shareholder

value induces downsizing,

outsourcing

Figure 8. Three-Year Moving Average Income Inequality and Union Density in the United States, 1950 – 2006

32 36 40 44 48

Gini Coefficient

10 15 20 25 30 35

Ratio of Unionized Workers to Total Labor Force

1950 1960 1970 1980 1990 2000 2010

Year

Union Density Income Inequality

Figure 9. Cross-National Comparison of Income Inequality and Employment Concentration, 2006

Canada

United S tates

Australia

New Zealand

Cote d'Ivorie

Cameroon

Algeria

Egypt

Ghana

Morocco

Senegal

Tunisia

South A frica

Zimbabwe

China

Indonesia

India

Japan

S Korea

Sri Lanka

Malaysia

Philippines

Singapore

Thailand

Bulgaria

Belarus

Czech Rep

Croatia

Hungary

Poland

Romania Serbia

Russian Federation

Slovenia

Slovakia

Ukraine

Argentina

Brazil

Chile

Colombia

Mexico

Peru

Venezuela

Denmark

Finland Iceland

Norway Sweden

Austria

Belgium Switzerland

Germany

Spain

France

United K ingdom

Greece Ireland

Italy

Netherlands

Portugal

Turkey

20 30 40 50 60

Gini Coefficient

0 5 10 15 20 25 30 35

Ratio of Top 10 Employers to Total Labor Force

Economic inequality and carbon inequality: Multi-evidence from China's cities and counties

Article

Feb 2023
J ENVIRON MANAGE

Chong Xu

Despite economic inequality (EI) and carbon inequality (CI) are both core targets for sustainable development goals (SDGs), the current studies on EI and CI still lacks in-depth investigation, hindering to formulate policy towards better balancing social welfare improvement and carbon emission reduction. To address the gap above, the study comprehensively analyzed on the trends and drivers of EI and CI in a case of 262 cities over 2002–2019 and 1434 counties over 2005–2017 in China at individual level and aggregate level, respectively. Further, we explored the decoupling relationship between EI and CI and corresponding driver using an inequality-based decoupling decomposition model we proposed. We found that almost all cities, counties and corresponding sub-groups presented overall declining trends for EI and CI except for county groups over the period, where the within difference was the main driver. Further, the change of population proportion and the regional ranking have promoted the reduction of EI and CI at city- and county-levels. Decoupling analysis implied that the main decoupling state between EI and CI was weak negative decoupling for cities and counties, where the changes in regional ranking and per capita carbon emission were the negative and positive drivers, respectively. The study highlights the importance of reducing EI and CI simultaneously for policy implication.

The Influence of Accounting Information System and Religion Commitment Inventory on the Performance of Small and Medium Scale Enterprises in Jordan

Article

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Jun 2020

The study focuses on the influence of accounting information system on the performance of small and medium scale enterprises in Jordan, taking the role of religion commitment inventory as moderating variable. Hence, the study proposes a theoretical framework to examine the effect of religiosity towards the SMEs' business performance. A quantitative design with a simple random sampling and distributed by emails (online survey questionnaires) was distributed to 386 SMEs in Jordan. The data was analyzed using multiple regression technique. The finding indicates that the AIS and religiosity influences SMEs performance with mixed results. In this context, AIS and religiosity make a significant contribution to SMEs' by increasing business performance financially and non-financially. Finally, it is recommended that the use of AIS is essential for improving the performance of SMEs in Jordan.

Freedom is Just Another Word for Nothing Left to Lose: Entrepreneurialism and the Changing Nature of Employment Relations

Chapter

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Aug 2021

We explore the acceptance of new contingent work relationships in the United States to reveal an emergent entrepreneurial ideology. Our argument is that these new work relationships represent a new social order not situated in the conglomerates and labor unions of the past, but on a confluence of neo-liberalism and individual action situated in the discourse of entrepreneurialism, employability and free agency. This new employment relationship, which arose during the economic and social disruptions in the 1970s, defines who belongs inside an organization (and can take part in its benefits) and who must properly remain outside to fend for themselves. More generally, the fusing of entrepreneurship with neo-liberalism has altered not only how we work and where we work, but also what we believe is appropriate work and what rewards should accompany it. 2

Holistic Blended Values: Another Social Entrepreneurship Paradigm

Article

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Feb 2023

Helmi Muhammad

This study seeks to comprehend in-depth how social entrepreneurship (SE) practices from a business standpoint in Islamic boarding schools, as well as what values emerge in SE practices. The qualitative research design is descriptive exploratory, with a holistic single-case study conducted at the Sidogiri Islamic boarding school in Pasuruan, Indonesia. In-depth interviews, field observations, focused discussions, and a review of supporting documents were employed to collect data. In-depth interviews, field observations, focused discussions, and a review of supporting documents were used to collect data. Purposive sampling was used to select key informants, and the snowball sampling technique was used to select other informants based on key informant recommendations. After maintaining quality standards through data triangulation, observers and sources, and member checks, data analysis employs an interactive model. According to the findings, SE practices are implemented through a combination of corporate social responsibility programs, bottom-of-the-pyramid orientation, other SE activities, and spirituality. The distinction of SE development in the Islamic boarding school-based business perspective in Indonesia is this balance. The balance of the SE program, as reflected in the holistic blended value, is critical to the business's existence and sustainability. The last section goes over the implications and future research.

Sources of Financing of the Machine-Building Industry of the Rostov Region: Analysis and Evaluation

Chapter

Jun 2022

Purpose: Study of financing sources and assessment of the impact of the weighted average cost of capital on the profitability of assets, using the example of enterprises of the machine-building industry of the Rostov region. Methodology and Data: A summary of available studies confirms that industry in the Russian regions when choosing financing sources faces problems characteristic of emerging markets: high cost of bank financing sources, inaccessibility of alternative financing sources, low payment discipline of counterparties, and asymmetry of information. The research was carried out on a sample of industrial enterprises of the Rostov region using the postulates of the weighted average cost of capital and theories of choosing financing sources. Results: The analysis shows that in conditions of unfavorable choice and asymmetry of information characteristic of regional markets, industrial enterprises prefer the principles of hierarchy theory, which are less subject to information costs and minimize risks. It has been found that more cost-effective enterprises have higher financial independence. The weighted average cost of capital was found to be quite low. We assume that this is due to the fact that the price of borrowed sources of financing for industry is higher than its own. This is the reason for the non-public nature of most industrial enterprises, which, firstly, allows them to pursue a “soft” dividend policy, and secondly, makes sources of external financing inaccessible and expensive due to the high asymmetry of information. Originality: The hypothesis put forward about the positive impact of the size of industrial enterprises of the Rostov region on the choice of debt sources of financing is confirmed. The larger the size of the company, the higher the share of long-term borrowed sources of financing, which corresponds to hierarchy theory. We also found that in the formation of financing sources for small industrial enterprises of the Rostov region, internal factors are higher than macroeconomic ones.KeywordsMachine engineeringSources of financingEfficiency of capital useWeighted average cost of capitalRostov regionJEL CodeL64G32

Taking a Common Concern Approach to Economic Inequality: Implications for (Cooperative) Sovereignty over Corporate Taxation

Book

Full-text available

Mar 2022

Alexander Beyleveld

Are countries capable of reducing economic inequality under conditions of contemporary globalisation without cooperating and coordinating with other countries? While states are far from powerless to effect distributional change within their own sovereign space, Taking a Common Concern Approach to Economic Inequality makes the case that cooperation and coordination is indeed necessary, especially in relation to corporate taxation. It accordingly contemplates the utility of a transnational taxation system that is embedded in cooperative sovereignty through the recognition of rising economic inequality and its deleterious effects – including how increasingly unequal distributions within countries make transnational cooperation and coordination efforts less likely – as a common concern of humankind.

Socio-Economic Factors and Table Banking Loans Default Levels Among Women Groups in Machakos County, Kenya

Article

Full-text available

Feb 2022

Defaulting on a loan happens when one fails to make sufficient payments for an extended period. Lenders will deem a loan in default when the borrower haven’t paid the minimum required payment for a certain number of months as detailed in the loan contract. Loan defaults can happen with any type of loan, table banking being one of them. In Kenya as in most developing countries, table banking has been recognized and accepted by development agencies and the government as effective tool for economic development poverty alleviation and industrialization. It’s a proven method for women to spearhead their finances and experience economic perks through organized and calculated means. However, despite of their important role many of these table banking programs have collapsed because of problems in repayment. The general study objective was to investigate the effect of social economic factors on Table Banking loans default among Women in Machakos county, Kenya. The specific objectives were to determine the relationship between level of income, literacy level, borrowing experience as well as household demand and Table Banking loans default level among Women in Machakos County, Kenya. The study design was descriptive with a target population consisting of 22,500 women contained in all the 1500 women groups in Machakos County. A sample size of 384 women group members was selected through simple random sampling technique. Primary data on the selected women from the women groups were collected using structured questionnaires. The response rate was 342 women representing 89 percent. Data was analyzed using frequency distribution, chi-square tests and regression analysis. It was disclosed that there was a negative but significant association between level of income, literacy level, borrowing experience and household demand and table banking loan default level by women in women groups. Demographic factors also had a negative but significant relationship with table banking loan default level among women in women groups in Machakos County. For practice the study recommended that: Firstly, women should engage in extra financial activities to increase their income level. Secondly the uptake of loans should be with the reason of income generation and not necessarily meeting the households’ needs. This will ensure that the loans taken will be regenerated to assure repayment in time and minimize defaulting of the table banking loans. Thirdly the government should enhance entrepreneurship and financial management trainings including incorporating it through formal education. This study focused on socio-economic factors influence on women's default table banking loans, therefore, other influential factors and disciplines should be studied to useful to reduce the defaulting of table banking loans. The study was limited in Machakos County. Low biasness can be attained for all the Kenyan women groups, therefore, a study focusing on other locations and larger spheres of the population of the study should be done, that is, in county, regional and national levels.

L'influence du système de gouvernance de l'entreprise familiale sur sa performance sociétale : cas des entreprises familiales côtées

Thesis

May 2021

Yosra Meddeb

Au cours des deux dernières décennies, on s'intéresse de plus en plus aux facteurs et mécanismes favorisant la responsabilité sociale des entreprises. Ce champ de la recherche suscite plusieurs débats et spécifiquement dans un contexte de l'entreprise familiale.Selon des recherches antérieures, les entreprises familiales et non familiales diffèrent en ce qui concerne leurs performances sociétales mais les résultats dans ce domaine manquent d'unanimité. Ces différences dans les résultats reposent principalement sur l'hétérogénéité des variables prises en compte pour identifier l'entreprise familiale et l'implication de la famille. Ainsi, et afin de contribuer à une meilleure compréhension de la performance sociétale des entreprises familiales, nous adoptons une approche basée sur l'echelle F-PEC de mesure de l'implication familiale.

Causes of Inequality in South Korea from a Capitalism Variety Approach

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Full-text available

Jul 2021

Alejandro Perez

This article identifies the causes that have maintained a high level of inequality in South Korea, through the Varieties of Capitalism (VoC) approach, which classifies the country as a network economy. The study further elaborates on the discussion of the determinants of inequality in countries with a high Gross Domestic Product per capita (GDPp) and the operation of three negative complementarities that maintain these imbalances: gender, social spending, and poverty. To this end, data generated by the Organization for Economic Cooperation and Development (OECD) are methodologically and descriptively addressed. In conclusion, inequalities concerning gender, social spending, and poverty constitute a complex negative complementarity that permeates the income distribution of the Asian country.

Exploring the Recognition of New Common Concerns of Humankind: The Example of the Distribution of Income and Wealth within States

Chapter

May 2021

Alexander Beyleveld

This chapter contemplates addressing changes in economic distributions within states from the vantage point of international law. It does this by considering the potential of recognising changing economic distributions within states and the adverse effects that flow therefrom as a ‘common concern of humankind’. At the outset, a contemporary conceptualization of the ‘distributive autonomy’ of states is provided in light of recent economic globalization. The process for recognising new common concerns of humankind is subsequently examined and theorised before the paper sets out the potential and utility of recognising a distributional common concern, arguing that the raison d’être for sovereignty, itself a constitutive element of common concerns, is the marshalling of the state in order to enhance the welfare of the individuals in a given society through the provision of peace and stability. The predominant utility of recognising a distributional common concern of humankind, then, would be to rebalance sovereignty in a manner that would place greater emphasis on effectively ensuring the welfare of humankind, something which can be better – or perhaps only – accomplished through international coordination and cooperation, actions which in and of themselves are less likely to occur under conditions of growing economic inequality within states.

The Rise and Fall of Finance and the End of the Society of Organizations

Article

Full-text available

Aug 2009
AMP

Gerald F. Davis

Large corporations were a dominant force in American society for generations through their employment practices, expansion choices, and community connections. As the United States has shifted to a postindustrial economy, however, finance has increasingly taken center stage. This article documents shifts in corporate employment, institutional investment, corporate organization, financial services, governments, and household ties to financial markets over the past three decades. I argue that all these shifts can be seen as part of an interconnected movement toward a finance-centered economy, and that the recent economic downturn can be viewed as one outcome of this broader movement.

Building Sustainable Organizations: The Human Factor

Article

Feb 2010
AMP

Jeffrey Pfeffer

Variabilita e mutabilita

Article

Jan 1912

C. Gini

The Winner-Take-All Society

Article

Oct 1996

Markets and Hierarchies: Analysis and Antitrust Implications.

Article

Sep 1976

The Visible Hand: The Managerial Revolution in American Business

Article

Dec 1978
J AM HIST

Bringing the Firms Back in: Stratification, Segmentation, and the Organization of Work

Article

Oct 1980
AM SOCIOL REV

This essay examines the shift toward "structural" explanations in recent studies of inequality. After reviewing this body of research and some of its shortcomings, we examine its theoretical underpinnings, comparing "structuralist" perspectives on work organization derived from institutional economics and neo-Marxism to more orthodox accounts based on neoclassical and "industrialism" theories. This discussion suggests areas where the different perspectives overlap and diverge. We conclude that work arrangements within the firm and their trend are the focus of most "structural" perspectives on positional stratification; thus, empirical studies grounded at the organizational level are more likely to inform current debates about the "structure of work" than is the growing body of research about structural effects on individual attainment or covariation among industrial/occupational characteristics. Toward that end, an agenda for future research is outlined, focusing on three aspects of work organization: (a) the units which comprise the structure of work and the dimensions underlying economic segmentation; (b) the effects of sectoral differentiation on technical and administrative arrangements within firms; and (c) temporal changes in how enterprises organize production. We provide some illustrations of the kinds of empirical data and research hypotheses required to link research on segmentation and stratification more closely to studies of organizations.

Modern Manors: Welfare Capitalism since the New Deal

Article

Nov 1998
CONTEMP SOCIOL

Offshoring: The Next Industrial Revolution?

Article

Mar 2006
FOREIGN AFF

Alan S. Blinder

Economists who insist that "offshore outsourcing" is just a routine extension of international trade are overlooking how major a transformation it will likely bring--and how significant the consequences could be. The governments and societies of the developed world must start preparing, and fast.

The New Capitalism and Organizational Rationality: The Adoption of Downsizing Programs, 1979-1994

Article

Sep 1997

Art Budros

Since a “new capitalism” dominates economic life in America, we need to explain the development of the new economy's features. Although such work has begun, a core feature of the economy, downsizing, has been understudied, even though this phenomenon has eliminated some ten million U.S. jobs and generally has had negative human and organizational effects. In particular, little effort has been made to explore why firms downsize in the first place. Therefore, in this article I examine the causes of the adoption of downsizing programs among Fortune 100 firms from 1979 to 1994. I show that downsizings are affected by variables measuring crises and decisive events (associated with the new capitalism) — shareholder values, foreign consolidations, market share, productivity, employee compensation, deregulation, and business peaks; by institutional forces — the adoption effect and industry culture; and by firm traits — ownership status and firm size. I also distinguish between economically oriented and socially oriented organizational action in addressing the rationality of downsizers.

Corporations and Economic Inequality Around the World: The Paradox of Hierarchy

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