Immigrant Contributions to American Economic Development

Part of the Public Administration, Governance and Globalization book series (PAGG, volume 1)


Debate rages about the viability of current immigration policies in the United States. While America is known as a “nation of immigrants” we also know that at various times in the nation’s history the welcome mat to persons from other nations has been pulled. The nation’s doors have at times been wide open, yet at other times they were solidly closed. A question asked by natives is how well the “other” will fit with the American work ethic and the American ideal of economic success. Do immigrants contribute economically or do they drain the resources of others? Do immigrants enhance economic strength or do they hasten economic decline? Will immigrants bolster values that have promoted economic development or will they undermine them? Will immigrants embrace Protestant values in regard to work, self-sufficiency, education, saving, and risk taking? Central to Calvinist belief of the Massachusetts settlers were the beliefs that people should not lust after wealth or easy living, that reinvesting profits of one’s labor was acceptable, and that it is appropriate to seek occupations which provide the greatest earnings. According to Calvinism, success in one’s work is associated with being one of God’s “Elect” (Hill 1996).


Immigrant Group Chief Executive Officer Dominican Republic High School Diploma American Community Survey 


Debate rages about the viability of current immigration policies in the United States. While America is known as a “nation of immigrants” we also know that at various times in the nation’s history the welcome mat to persons from other nations has been pulled. The nation’s doors have at times been wide open, yet at other times they were solidly closed. A question asked by natives is how well the “other” will fit with the American work ethic and the American ideal of economic success. Do immigrants contribute economically or do they drain the resources of others? Do immigrants enhance economic strength or do they hasten economic decline? Will immigrants bolster values that have promoted economic development or will they undermine them? Will immigrants embrace Protestant values in regard to work, self-sufficiency, education, saving, and risk taking? Central to Calvinist belief of the Massachusetts settlers were the beliefs that people should not lust after wealth or easy living, that reinvesting profits of one’s labor was acceptable, and that it is appropriate to seek occupations which provide the greatest earnings. According to Calvinism, success in one’s work is associated with being one of God’s “Elect” (Hill 1996).

A review of American history indicates that immigrants have contributed greatly to the economic vibrancy and strength of the nation. From a relatively small collection of mainly English colonies, the United States expanded to a position of economic hegemony. According to the World Bank in 2008, the United States had a gross domestic product (GDP) of $14.2 trillion (market value of all final goods and services from a nation in a given year), far surpassing the GDP of its closest rivals Japan ($4.9 trillion), China ($3.9 trillion), and Germany ($3.7 trillion) (List of Countries by GDP 2009).

In light of contemporary anxiety about the continuity of American economic success and how immigrants may impact that success, it is useful to look at the economic experiences of immigrants. Literature concerning the economic contributions of immigrants is reviewed below. Empirical data is examined for various nationality groups. This data assesses earning of immigrant groups and surrogates of wealth. Finally, the chapter highlights the life experience of three highly successful immigrants.

Literature on Economic Impact of Immigrants

Studies of the economic impact of immigration appear to be turning increasingly negative. Harvard Professor George Borjas (1994, 1713) contends that since the 1980s the immigration discussion has been radically altered. Whereas pre-1980s studies suggested that the economic opportunities of immigrants radically improved over time, and within a decade or two earnings of immigrants reach or overtake earnings of natives, later studies focus on (1) the declining skills of immigrants in the post World War II period; (2) the dubious likelihood that recent immigrants will ever reach parity with the earnings of natives; (3) the impact of immigrants on earnings of unskilled natives; (4) the participation of recent immigrants in welfare programs; (5) the desirability of “filtering” in order to attract immigrants who will have higher earnings and are less likely to participate in public assistance programs; and (6) the strong correlation between skills of immigrants and skills of second-generation Americans (i.e., assumption of little change between generations; today’s differentials becoming embedded).

The empirical studies that have explored the economic impact of immigrants are mixed. Numerous studies have identified a negative impact on native wages (Borjas 2003; Camarota 1997; Topel 1994). Other studies have found a small or no impact on wages (Altonji and Card 1991; Card 1990); or a fiscal benefit (Passel and Clark 1994). Research indicates that immigration negatively impacts both unskilled and college-educated workers (Borjas 2003) and dampens native employment. Camarota (2007, 155) found that between March 2000 and March 2004 the number of native-born Americans holding jobs declined by 500,000 while the number of immigrant job holders increased by 2.3 million. Almost all the job increases in a relatively few states (Texas, New Jersey, Arizona, Maryland, Virginia, North Carolina, and Georgia) went to immigrants. Contrary to the view that immigrants only took jobs natives shunned, the data identified immigrant employment gains throughout the labor market, high-paying jobs as well as low-paying jobs.

Peter Brimelow, former editor of Forbes and founder of the anti-immigration organization VDARE, is an outspoken critic of American immigration policy. Brimelow claimed that the public debate about the economics of immigration does not reflect the professional consensus among labor economists. Referring to the social commentator Will Rogers (1879–1935), Brimelow states that the problem with the immigration debate is not “what folks don’t know, it’s what they know that ain’t so” (Brimelow 2007, 157). Brimelow concluded that (1) on balance, current mass immigration contributes essentially nothing to native-born Americans in the aggregate, (2) counting transfer payments, mass immigration is probably a net loss for native Americans, (3) immigration causes a substantial redistribution of income among the native born; this redistribution is from labor to capital.

Borjas (1995) estimated that in 1992 American owners of capital benefited from immigration while wages for American workers suffered. Further documentation of the economic impact of immigration is found in the 1997 publication of the National Research Council’s The New Americans: Economic, Demographic, and Fiscal Effects of Immigration (Smith and Edmonston 1997). This study was intended to describe academic views about immigration for the US Commission for Immigration Reform (the Jordan Commission). The study noted that (1) the “immigration surplus” (growth of national income of native-born Americans attributed to immigration) was small; (2) the fiscal expenses attributed to immigration outweigh the immigration surplus; (3) a wage depression occurred for native-born workers as a consequence of immigration. This wage depression was substantially higher for high school dropouts.

The impact of immigration appears to be more discernible in recent years. Two Columbia University professors documented losses to US natives from immigration (Davis and Weinstein 2002). Borjas (1990) initially found that immigration had little impact on native-born wage. He later reversed his position concluding that immigration had a significant impact on less-skilled workers (Borjas 1999). The long-term economic implication of immigration may not be known, Borjas stated (1994, 1713), “In a sense, we are only beginning to observe the economic consequences of the historic changes in the size, national origin mix, and skill composition of immigrants admitted to the United States during the past three decades. The Second Great Migration surely will alter the skill endowment of the labor force.” The Center for Immigration Studies (CIS), a nonpartisan research organization found that, when all taxes are paid (direct and indirect) and all costs are considered, illegal households created a net fiscal deficit at the federal level of more than $10 billion in 2002. The CIS also estimate that, if there was amnesty for illegal aliens, the net fiscal deficit would grow considerably (Center for Immigration Studies n.d.).

Opposing the view that immigration has a negative economic impact, Jason Riley, member of the Wall Street Journal editorial board, argued that more legal immigrants should be welcomed to the United States. According to Riley, today’s newcomers are fueling America’s prosperity and dynamism. Riley counters the view that immigrants are overpopulating the country, stealing jobs, depressing wages, bankrupting social services, filling prisons, resisting assimilation, and promoting big government. Although Riley admits immigration has economic costs he concludes that when costs are weighed against the gains, open immigration and liberal trade policies still make more sense than protectionism (Riley 2008).

A strong advocate of free labor markets, Riley contends that American open-immigration policies go a long way toward explaining the difference between robust economic growth in the United States and stagnation in Europe. The Irish are presented by Riley as an example of successful immigration. Ireland was the source country of the first mass migration to the United States flooding America in the middle of the nineteenth century. Throughout the 1800s, the United States absorbed Irish newcomers at more than double the rate of current Mexican immigration. According to Riley, most Irish immigrants were uneducated, many did not speak English, and they worked as domestic servants, ditch diggers, stevedores, and in other low-skill, labor-intensive jobs. The Irish were typically stereotyped as slow-witted drunks and ne’er-do-wells who would never acculturate to America. They, however, eventually did contribute to the American economy, producing civic leaders and businessmen, including Henry Ford. For example, according to the 2006 Census, 31% of Irish Americans had at least a bachelor’s degree versus 27% of the nation as a whole. The median annual income for households headed by an Irish American was $54,000, versus $48,000 for all households.

Although the Irish experience has been replicated by other large immigrant groups, the Irish experience is often ignored or played down when today’s new immigrants such as Latinos are considered. Riley concludes that a more open immigration policy is consistent not only with our traditions and morals but also in the economic interests of the United States. According to immigration supporters such as Jason Riley, immigrants facilitate flexible labor markets, increase overall productivity, and keep the US work force young and strong. The human capital immigrants provide to the nation is considered vital if the United States is to retain its edge in a twenty-first-century global marketplace (Riley 2008).

The think tank Cato Institution identified the following advantages of immigration: (1) Immigrants are self-selected on the basis of motivation, risk taking, work ethic, and other attributes beneficial to a nation; (2) Immigrants tend to come to the United States during their prime working years (the average age is 28); (3) Immigrants contribute to the workforce and make contributions to old-age entitlement programs, primarily Social Security; (4) Immigrants tend to fill niches in the labor market where demand is highest relative to supply; (5) Immigrants complement rather than directly compete with American workers; (6) Many immigrants arrive with extremely high skill levels, and virtually all, regardless of skill level, bring a strong desire to work; (7) Children of immigrants tend to reach high levels of achievement in American schools and in society at large.

According to the Cato Institute, the benefits of immigration are as relevant today as they have been throughout American history. The conclusions of Cato Institute is that the negative impact of immigration on the US workers is more than offset by the lower prices and wider range of goods made available because of immigration. As a result of immigration, Americans also benefit from higher returns on investment and from greater opportunities for skilled workers in industries that depend on immigrant workers. As support for their position, the Cato Institute refers to a study for the National Bureau of Economic Research. This study found a significant positive effect of immigration on average US wages, and on each group of workers with at least a high school degree. Only a small negative effect on wages of workers without a high school degree was found in the long run (Griswold n.d.).

Economic contributions may not be uniform for all nationality groups. This chapter identifies differences in earnings for the twenty largest immigrant groups in the 2007 workforce. Differences are identified with and without controlling for factors such as education, gender, race, and ability to speak English. Nation by nation data on factors such as education is further described. Housing values are reviewed as a surrogate for wealth. The yearly American Community Survey (ACS) is utilized as the source of data in the empirical analysis.

Description and Analysis of Data

American Community Survey Data

The Census Bureau takes a 1% samples in all counties and county-equivalents in the United States, and all municipios in Puerto Rico each year. This American Community Survey (ACS) is an ongoing effort to provide information in a timelier manner than the information collected every 10 years. Whereas the decennial census goes to every household in the United States, the 2007 ACS was issued to slightly more than three million addresses. Therefore the dataset consists of responses from approximately three million respondents.

Much like the full decennial census, the yearly ACS is designed to give communities accurate and up-to-date information about socioeconomic and housing conditions. The survey assists in producing statistics needed to manage federal programs and comply with federal laws or court decisions. The ACS survey is also helpful in determining how federal tax money is allocated annually to local communities. Additionally, state and local leaders, as well as planners and businesses, use the data in making important policy decisions (US Census Bureau 2008). This chapter utilizes “microdata” that is provided by the Integrated Public Use Microdata Series (IPUMS) of the US Census. IPUMS describes information collected on persons, families, and households (Ruggles et al. 2009).

Description of Immigrants in 2007

Data relating to the largest 20 immigrant groups and “rest of world” immigrants living in the United States in 2007 are presented in Table 4.1. This table offers a “snapshot” of the foreign born living in the United States. This includes both legal and illegal residents and does not distinguish between citizenship. The data is useful for comparative purposes as well as for identification of aggregate numbers of immigrants from specific nations. It extrapolates aggregate numbers of foreign born based on the 1% ACS sample.
Table 4.1

Estimate of foreign-born residents, total (in millions), 2007 ACS sample


Country of birth


Percent of foreign born


































El Salvador








Dominican Republic




































Other USSR/Russia




Rest of the World (128 countries)




Total Foreign Born



Total US



Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

Based on the 2007 ACS survey, an estimated 32,296,000 American residents were born outside the United States. This figure was extrapolated from the 1% sample of the ACS respondents who identified themselves as foreign born (n=322,960). What is apparent from the data is the relatively large percent of immigrants from Mexico (28.0%) and from one general region (Latin America) of the world. When immigrants from Central America or Caribbean countries were added to the Mexican totals, the proportion of immigrants from Mexico, Central America, and the Caribbean accounted for 40.8% of all foreign-born residents living in the United States. This figure does not include Latin American immigrants who were not born in “top twenty” countries of Mexico, Cuba, El Salvador, Dominican Republic, Columbia, Guatemala, Jamaica, and Haiti that are listed in Table 4.1.

The high proportion of migrants from Mexico and Central America should not be surprising. The border between the United States and Mexico represents the largest landed border separating the first world and the third world. Also, the per capita income levels of persons living in United States far exceed those of people living in Latin America. A combination of the spatial and economic dynamics appears to drive people to emigrate from Latin American nations.

Asian nations in the “top twenty” of foreign-born residents in 2007 included Philippines, India, China, Vietnam, Korea, Taiwan, and USSR/Russia. The share of Asian immigrants was 21.7%. Only four European countries (Germany, Poland, Italy, and England) were included in the top national places of birth for foreign-born American residents. The percent of foreign-born residents from these nations constituted less than 6% of the foreign-born totals in 2007. Immigrants from Canada comprised 2.8% of the total foreign born.

Many of the countries that make up the “top twenty” also have unique political and military relationships with the United States. The Philippines became a US protectorate following the Spanish-American War and remained one until 1946. The United States maintained and operated major facilities at Clark Air Base, Subic Bay Naval Complex, and several small subsidiary installations in the Philippines until November 1992. Currently, the United States conducts ship visits to Philippine ports and has large combined military exercises with Philippine forces (US Department of State 2009a). The United States has operated multiple military bases in Germany and Japan dating back to the end of World War II, and in Korea since the end of the Korean War. While no bases are in Vietnam, the large military conflict (1959–1975) resulted in many Vietnamese refugees immigrating to the United States.

The Cold War had a definite impact on the status of Cubans and their immigration to the United States. As the Communist government took power following the Cuban Revolution of 1959, Cubans with ties to the United States fled to the United States. Over the years Cubans have attempted to migrate to the United States with mixed results. The Cuban government permitted as many as 125,000 Cubans to leave the island nation for the United States during the Mariel boatlift of 1980.

Currently, the general policy regarding Cuban immigrants is that if an individual from Cuba reaches American soil and is out of American waters, he or she is allowed to remain in the United States. This controversial policy is often referred to as the “wet foot, dry foot policy.” In an attempt to reduce the number of dangerous immigration attempts, the United States and Cuba signed the September 9, 1994 Joint Communiqué and the May 2, 1995 Joint Statement, collectively known as the “Migration Accords.” These agreements permitted the processing of 20,000 travel documents per year to allow safe and legal migration of Cubans to the United States (US Department of State 2009b).

Current nationality patterns of immigration represent a departure from the patterns exhibited in earlier periods of American history. According to the Department of Homeland Security, between 1900 and 1909 there were approximately 8.2 million people who obtained Legal Permanent Resident Status (legal immigrants) and were granted admission to the United States. The vast majority (approximately 7.57 million of these immigrants) were from Europe. More than 2 million persons emigrated from Austria-Hungary; almost 2 million from Italy, and about 1.5 million from Russia during this time. Only about 7,000 permanent legal residents emigrated from Central America between 1900 and 1909 (Department of Homeland Security 2009).

How America’s immigrants are performing economically is a fundamental question for persons who are interested in patterns of assimilation. This inquiry directly addresses the question of to what extent immigrants contribute to the national income and national gross domestic product. Prior to looking at earnings it is useful to identify the extent to which foreign-born residents participate in the US workforce. Table 4.2 describes the total numbers of foreign-born workers in the United States in 2007, nationality composition of the foreign-born workforce, and likelihood of immigrants from specific nationality groups to be in the workforce.
Table 4.2

Foreign-born in the workforce (in millions) (2007)


Country of birth

Number of workers

Percent of all foreign workers

Percent working



























El Salvador



























1. 7








Dominican Republic

















1. 2























Rest of the world (128 countries)





Total foreign born





Total US




Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

A number of observations can be made based on the data presented in Table 4.2. First is the large number of immigrants from one nation (Mexico). Almost 29% of all foreign-born residents were born in Mexico. This is more than five times the percent of foreign-born workers from the next largest nation (Philippines). Second, immigrants from Mexico (61.9%), El Salvador (71.6%), Jamaica (68.6%), Honduras (68.3%), Haiti and Guatemala (67.9%), India (66.7%), and Peru (66.1%) all exhibited relatively high rates of labor force participation. These labor force participation rates are significantly higher than the 48.3% workforce participation rate of native-born Americans.

Poverty may be motivating people from these countries to participate in the workforce at a higher rate than native-born Americans and other immigrant groups. Many of the foreign-born residents from low-income countries may be male workers who remit payments to families back home. Spouses from these countries may feel greater pressure to work due to the relatively low earnings of others in their family.

In contrast, immigrants from Germany (45.1%), Korea (52.4%), Cuba (53.0%), Canada (53.2%), England (54.3%), China (55.1%), and Poland (58.5%) exhibited smaller proportions of their populations in the workforce. This might be attributed to more traditional family units (i.e., more homemakers) and from a lower pressure to work because of relatively high earnings of others in the family. The largest difference between national groups was found with regard to Germany (45.1%) and El Salvador (71.6%). The labor force participation pattern of German immigrants is similar to that of other European nations and Canada while the pattern identified for El Salvador is similar to that found for immigrants from other Latin American nations. Immigrant groups for the most part had significantly higher rates of workforce participation than that of native-born Americans. This is partially explained by the relatively high percent of retirees among the native born. To what extent earnings played a role in the different participation rates is discussed below.

Immigrant Earnings

Table 4.3 identifies salary and wage incomes of foreign-born residents for the “top 20” countries in the workforce. Incomes of native workers and incomes for the “rest of the world” are also provided. Differences in salary and wage incomes as well as t-statistics are described in the table. The t-value indicates whether there is as statistically significant difference in salaries and wages between native American and immigrant groups.
Table 4.3

Salary and wage incomes for those in workforce by place of birth (2007)


Salary and wage income


1. Guatemala



2. Mexico



3. Honduras



4. El Salvador



5. Dominican Republic



6. Haiti



7. Peru



8. Colombia



9. Jamaica



10. Vietnam



11. Cuba



12. United States



13. Poland



14. Philippines



15. Korea



16. Rest of the world



17. Germany



18. China



19. Taiwan



20. England



21. Canada



22. India



**Statistically significant at the 0.01 level

Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

Large differences exist in reported incomes by nation of birth. With the exception of Cuba (where no significant difference was found with US incomes) statistically significant differences at the 0.01 level were found for all nationality groups. Immigrants who were born in India, Canada, England, and Taiwan reported earnings that were more than $20,000 higher than earnings reported by native-born American workers. Conversely, respondents born in the Guatemala ($22,511), Mexico ($22,542), Honduras ($22,516), El Salvador ($24,509), and Dominican Republic ($26,032) all reported salary and earnings of more than $10,000 less than the average native-born earnings of $39,974.

Differentials existed between nations of Latin America. For example, incomes of immigrants who were born in Jamaica ($36,444) and Cuba ($38,824) were relatively high compared to incomes reported by other immigrants born in Latin America. This may be attributed to different levels of human capital (skill levels), different levels of motivation, or different levels of access to capital. Many of the early migrants from Cuba (following the 1959 revolution) were driven away by Cuba’s policies such as nationalization of American industry, agrarian reform, and the severance of economic ties between the United States and Cuba. In this first wave of migration, those who emigrated were Cuba’s elite. These migrants were from the upper and upper-middle classes who were likely to be executives, owners of firms, merchants, manufacturers, cattlemen, representatives of foreign companies, and established professionals who were familiar with the United States’ guardianship of Cuba.

The so-called “first wave” of Cuban migrants (1961–1964) consisted of those with greater social capital. The educational level of this group was also much higher than those in other waves of migration from Cuba. Middle merchants, middle managers, landlords, middle-level professionals, and a considerable number of skilled unionized workers became refugees of the first wave. Migration accelerated after the Catholic church was silenced, the electoral system collapsed, and private schools began to close. The Cuban immigrants of the first wave were not so much “pulled” by the attractiveness of a new society as “pushed” by internal politics (Pedraza n.d.).

A mixed picture emerges from Table 4.3. Of the 20 largest immigrant groups in the workforce, 11 nationality groups had incomes lower than native incomes; 9 had incomes that were higher. In general, immigrants from Europe and Asia reported higher wage and salary income; the one exception was Vietnam, where salary and wages were lower than those of native born. With the exception of Vietnam, immigrants in the lowest income nationality groups were from Central America, South America, or the Caribbean. These countries are geographically close and therefore have lower costs of migration. The data described in Table 4.3, in general, supports the view that immigrants who earn less than native-born Americans come from nearby and relatively poor countries.

Lower earnings may be attributed to low levels of education, gender, experience/age, race, or other factors. Those with less education and experience from poorer nations may be more desperate in their search to provide for themselves and their families. They may be more willing to accept low-paying jobs and poor working conditions. These workers fall into the secondary sector of the dual labor market (See  Chapter 2).

In contrast to the immigrants from poor nations, residents from other parts of the world might be “choosier” in where they wish to work. They are probably not “pushed” (as some of the migrants from Cuba and other nations) by political reasons. Residents from countries with few economic opportunities may be “pulled” to the United States by its higher gross national product and promise of economic success for hard working, ambitious individuals.

Migrants from Europe, in all probability, sacrifice more in terms of potential future earnings in their home country than migrants from undeveloped nations. This might be attributed to differences in human capital. The educational levels of immigrants from European and Asian countries are far superior to those commonly found among Latin American migrations. This education differential may enable Europeans and Asian to command higher salaries in the host country.

Economic conditions of the home country, in all probability, play a role in migration decisions. The opportunity costs of leaving an area where economic conditions are favorable are high compared to the cost of abandoning an area characterized by few opportunities and an expectation of long-term poverty. In the case of developing nations from Asia, highly skilled workers born in India, Korea, Taiwan, and China may be better compensated for their efforts in the United States than in their home countries.

Education is but one factor that might influence salary and wage income. Other factors such as gender, race/ethnicity, ability to speak English, and age may also account for earning differentials. One would assume, based on the evidence from the native population, that women, racial/ethnic minority, and the younger migrants would tend to earn less than more experienced white men. The ability to speak English is another constraint on earnings. One would assume that inability to speak English well exerts downward pressure on wages.

Ordinal least square multiple regression tests these assumptions; wage and salary income serves as the dependent variable. Nation of birth independent dummy variables for the 20 largest immigrant groups, education, gender, race/ethnicity, ability to speak English, and age serve as independent variables. Table 4.4 describes salary and wages by place of birth after these controls were introduced in the regression. The marginal impact of different levels of educational attainment (associates degree over bachelors, bachelors over high school, masters over bachelor, professional over bachelors, and doctoral over bachelors) is identified. The impact of race/ethnicity is observed through classifications of Black, Hispanic, and Asian/Pacific Islander. Age is identified in the 18–35 age group.
Table 4.4

Salary and wage incomes by workers’ place of birth, controlling for age, gender, race/ethnicity, education, and language (2007)


Unstandardized coefficients (measures income)

Standardized coefficient (measures relative effects)

Standard error





Country of birth:










































    Dominican Republic












    Rest of the world (128 countries)




    El Salvador






























    High school diploma




    Associates degree: marginal over HS

8,943 **



    Bachelors degree: marginal over HS




    Masters degree: marginal over BA




    Professional degree: marginal over BA




    Doctoral degree: marginal over BA






    Gender: female




    Age: 18−35




    Race: black




    Does not speak the English language well or at all




    Ethnicity: Hispanic




    Race: Asian and/or Pacific Islander




Adjusted R2: 0.191

**Statistically significant at the .01 level

*Statistically significant at the .05 level

Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

Gender, age, race/ethnicity, and language all help to explain nationality based differences in wages and salaries. The predictive powers of those variables, as ascribed by their standardized beta, are among the strongest in the model. As expected, immigrants who were female, younger, less educated, black or Hispanic, and less able to speak English were associated with lower salaries and wages. The standardized beta coefficient provides an indicator of the relative impact of each independent variable in the model.

The four most powerful predictors of salary and wage income in 2007 were two measures of education (the marginal effect of having a bachelor’s degree over a high school diploma and the marginal effect of having a professional degree over a bachelor’s degree), female gender, and age (18–35 cohort). The marginal impact of having a bachelor’s degree over a high school diploma was the most powerful predictor of income (standardized beta of 0.240). Gender also explained much of the income variation (standardized beta of –0.175) as well as age (standardized beta of –0.141).

The marginal effect of the bachelor’s degree refers to the additional income one receives as a result of having the bachelor’s degree compared to expected earnings with a high school diploma. This indicates that an individual with a bachelor’s degree would make about $35,012 ($25,866 plus $9,146) more annually than a high school dropout, holding all else constant. Those with a professional degree (MD, DDS, DVM, LLB, JD degree) would make $83,906 more than a high school dropout ($48,894 plus $25,866 plus $9,146). Holding all else constant females were expected to earn $17,497 less than males and young workers (age 18–35) were expected to earn $15,011 less.

Place of birth was a statistically significant factor in explaining income differences with native born Americans even after the control variables were introduced. Place of birth was a significant predictor of incomes for immigrants from Canada, England, India, China, Colombia, the Philippines, Peru, Korea, Jamaica, Germany, and the Dominican Republic. Incomes of immigrants from countries, such as Vietnam, El Salvador, Taiwan, Cuba, Guatemala, Haiti, Poland, and Honduras did not differ significantly from native-born American incomes. This suggests that these immigrants would have similar earnings as native-born Americans if they possessed similar characteristics such as levels of education and ability to speak English.

Much of the large expected difference in salary and wage income between Mexican immigrants and native-born Americans is accounted for by the control variables with the result that differences between Mexican immigrants and native-born residents shrink to the relatively small amount of $570 annually (from about $17,500 uncontrolled). Most of the differences in earning were accounted for by education and language ability. Statistically significant differences did not exist between native-born workers and immigrants from a number of Latin American and Caribbean countries (El Salvador, Guatemala, Cuba, Haiti, Honduras) once controls were introduced. Workers born in Canada, India, England, Jamaica, and Germany were expected to make more in wages and salary than American-born workers even after controlling for independent variables.

Immigrant Education

Table 4.5 further elaborates upon educational differences by nationality group. It identifies the proportions of foreign-born residents without high school diplomas, with high school diplomas, and with the associate, bachelor, masters, professional, and doctoral degrees.
Table 4.5

Educational attainment for workers by place of birth (2007)


Percent with educational attainment (t-statistic in parenthesis)


No HS diploma

HS diploma



Bachelor’s degree

Masters degree





United States









9.5 (0.15)

50.5 (−0.63)

7.3* (−2.55)

21.2 (0.77)

7.1 (−0.31)

3.9** (4.39)

0.6 (−0.68)


15.5 (1.79)

49.2 (−1.20)

10.7** (3.56)

15.8 (−1.77)

6.5 (−0.65)

1.6 (−1.51)

0.7 (−0.59)


21.0** (3.29)

48.7 (−1.40)

10.7** (3.50)

13.6** (2.84)

3.9 (−2.05)

1.7 (−1.25)

0.4 (−0.92)


6.9 (−0.54)

47.8 (−1.81)

9.8 (1.91)

16.2 (−1.58)

14.0** (3.38)

2.5 (0.89)

2.8* (2.48)


12.3 (0.92)

45.6* (−2.78)

8.4 (−0.48)

21.4 (0.85)

6.8 (−0.50)

3.3** (2.96)

1.2 (0.14)


16.1 (1.94)

45.3** (−2.90)

9.5 (1.42)

18.6 (−0.46)

5.8 (−1.05)

3.8** (4.01)

1.0 (−0.09)

Dominican Republic

29.6** (5.60)

45.3** (−2.90)

7.7 (−1.82)

12.3** (−3.46)

3.1* (−2.46)

1.8 (−1.07)

0.3 (−1.14)


6.3 (−0.72)

42.7** (−4.09)

9.0 (0.57)

19.2 (−0.19)

14.6** (3.73)

3.06* (2.25)

5.2** (5.98)


4.0 (−1.33)

40.6** (−5.02)

10.1* (2.41)

25.5** (2.83)

12.5* (2.59)

3.6** (3.60)

3.7** (3.85)

Rest of the World

11.2 (0.61)

38.8** (−5.79)

8.2 (−0.85)

22.3 (1.30)

12.0* (2.32)

3.9** (4.26)

3.6** (3.69)


48.2** (10.62)

38.7** (−5.83)

3.8** (−8.67)

6.8** (−6.04)

1.4** (−3.40)

0.8** (−3.42)

0.3 (−1.10)


21.67** (3.46)

38.7** (−5.84)

9.0 (0.60)

22.1 (1.19)

4.62 (−1.66)

2.8 (1.51)

1.1 (0.07)

El Salvador

49.8** (11.09)

37.7** (−6.31)

4.1** (−8.21)

6.8** (−6.04)

1.3** (−3.40)

0.3** (−4.98)

0.1 (−1.36)


54.9** (12.47)

36.5** (−6.82)

2.7** (−10.55)

4.2** (−7.27)

1.00** (−3.60)

0.5** (−4.37)

0.2 (−1.31)


5.2 (−1.00)

35.2** (−7.41)

6.2** (−4.46)

32.8** (6.27)

12.3* (2.46)

4.0** (4.75)

4.3** (4.73)


53.5** (12.09)

35.1** (−7.45)

3.3** (−9.56)

6.3** (−6.28)

1.4 (−3.40)

0.2** (−4.98)

0.2 (−1.24)


5.8 (−0.84)

34.25** (−7.82)

9.9* (2.19)

26.8** (3.44)

13.4** (3.05)

5.7** (9.06)

4.1** (4.34)


5.2 (−1.01)

32.4** (−8.63)

9.2 (0.90)

44.0** (11.58)

4.9 (−1.53)

3.6** (3.52)

0.8 (−0.45)


16.8* (2.14)

23.3** (−12.69)

4.6** (−7.20)

19.1 (−0.22)

20.4** (6.80)

3.1* (2.45)

12.7** (16.81)


2.7 (−1.70)

14.5** (−16.56)

6.9** (−3.15)

32.3** (6.00)

30.0** (12.02)

4.9** (7.00)

8.7** 11.04


4.6 (−1.18)

12.7** (−17.40)

3.2** (−9.82)

32.5** (6.15)

32.91** (13.55)

7.8** (14.45)

6.4** (7.68)

**Statistically significant at the 0.01 level

*Statistically significant at the 0.05 level.

Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

As identified above, 51.9% of US-born workers have a high school diploma as their highest level of schooling, 19.6% hold a bachelor’s degree, almost 9% have an associate’s degree, and about 9% are without a high school diploma or equivalency. About 10% of American workers have advanced degrees with 7.7% having a masters, 2.2% have a professional degree, and 1.1 have a doctoral degree.

The t-statistics identified in Table 4.5 describe difference in educational attainment between immigrants in the workforce and native-born Americans. Statistically significant differences were found in terms of the percentage of doctoral degrees for Chinese (12.7%) and Taiwanese (8.7%) immigrants (United States 1.1%). Higher percentages of professional degrees also characterized immigrants from Taiwan (4.9%) and India (7.8%) (United States 2.2%). Higher percentages of master’s degrees were found for immigrants from China (20.4%), Taiwan (30.0%), and India (32.9%) (United States 7.7%). Taiwan and India had also much lower percentages of their immigrants with only a high school degree, 2.7 and 4.6% respectively (United States 9.8%).

While Asian immigrants tended to be better educated than native-born Americans, an opposite pattern was found with regard to immigrants from Latin America. A higher proportion of high school dropouts were identified for immigrants from Mexico (54.9%), Guatemala (53.5%), El Salvador (49.8%) and Honduras (48.2%). Majorities of immigrants from some Central American countries do not have a high school degree. More than 90% of Mexican immigrants in the workforce do not have academic achievement beyond a high school diploma. Similar proportions are witnessed for the workers from Central American countries of El Salvador, Guatemala, and Honduras. Workers born in the United States were the most likely to have a high school diploma or equivalency as their highest level of schooling. Table 4.6 describes immigrant groups with large percentages of high school dropouts; these dropout rates are statistically higher than those found among American-born workers, at the 0.05 or 0.01 level.
Table 4.6

Immigrants groups with highest rates of high school dropouts, 2007

Country of birth

Percent high school dropout

1. Mexico


2. Guatemala


3. El Salvador


4. Honduras


5. Dominican Republic


6. Vietnam


7. Haiti


8. China


United States


Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

Immigrants from China had extreme scores on both ends of the educational spectrum. Almost 13% of Chinese immigrants living in the United States were in possession of the doctoral degree, about 3% had professional degrees, and about 20% had master’s degrees. Paradoxically for such a well-educated group, almost 17% of immigrants from China did not hold a high school degree. This may reflect a pattern where better-educated Chinese people have migrated to the United States as skilled workers in recent years while large number of less-educated Chinese migrated to the United States prior to 1965. In 1965 immigration laws were changed to give preference to skilled applicants as well as applicants with families living in the United States.

Unlike the bimodal pattern for education uncovered with China, immigrants from India and Taiwan, as a whole, are better educated. Less than 5% of immigrants from India did not hold a high school degree. Less than 3% of immigrants from Taiwan did not hold this degree. The nation of origin of immigrants who were more highly educated is displayed in Table 4.7.
Table 4.7

Highly educated immigrant groups (2007)


Percent with bachelor’s or advanced degree

Percent with bachelor’s degree

Percent with master’s degree

Percent with professional degree

Percent with doctoral degree

1. India






2. Taiwan






3. China






4. Korea






5. Philippines






6. Canada






7. England






8. Germany






9. Rest of the world






United States






Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

Immigrants from Asia and Europe had higher percentages of their population achieving bachelor’s degrees or beyond. Immigrants from China, India, Taiwan, Korea, Germany, England, and Canada have particularly large percentages of their populations holding doctoral degrees. Almost 80% of immigrants in the labor force from India had at least a bachelor’s degree and more than 75% of the immigrants from Taiwan held at least the bachelor’s degree. The proportion of American workers from India and Taiwan, holding a masters, professional, or doctoral degree was more than double that of the US-born worker. Immigrants from Germany, England, Canada, China, and Korea also have higher proportions of advanced degrees than native-born Americans. Vietnamese immigrants more closely followed the education pattern of immigrants in Caribbean nations than the pattern set by immigrants from Asia. In terms of higher education, the top nationality groups were dominated by immigrants from Asia, Europe, and Canada.

Immigrant Gender

Another important factor in explaining earnings of immigrants is that of gender. The regression described in Table 4.4 indicates women as a whole were expected to make $17,497 less per year than a man. This divide between male and female earnings may be the result of various factors. Historically, women have earned less and they have been passed over for promotions and raises. Also, women have tended to shoulder a greater role in the family structure and have worked fewer hours. Mothers looking for employment face disadvantages, including being less likely to be hired, being offered lower salaries, and facing a perception that they would be less committed to a job than men with families or women without children (Aloi 2005).

Another factor in explaining the lower earnings of women is that society still has not fully overcome the idea of “man’s work” and “woman’s work.” Certain professions such as engineering, finance, construction, and manual labor are dominated by men. Child care, early education teaching, and domestic work are mostly filled by women. Professions dominated by men usually are higher compensated than those that employ mostly women (Rose and Hartmann 2004). Table 4.8 compares the gender distribution of immigrant groups with native-born respondents to the 2007American Community Survey.
Table 4.8

Gender of US and foreign-born workers (2007)


Percent female

t- Statistic










Dominican Republic



























United States









Rest of the world (128 countries)






El Salvador















**Statistically significant at the 0.01 level

*Statistically significant at the 0.05 level

Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

The percentage of women that make up the workforce varies dramatically by nationality group. Women make up 48% of the US-born workforce, 57.6% of those born in the Philippines (many of them are actively recruited as nurses), 57.1% of those born in Jamaica, and 55.3% of those born in Germany. On the other extreme, only about a third of American workers from Guatemala and Mexico are women. Gender differences were statistically significant at the 0.01 level for immigrants from Guatemala, Mexico, India, Honduras, El Salvador, Cuba, the Philippines, Jamaica, Germany, the Dominican Republic, and Colombia. A relatively small proportion of females from India were in the workforce, suggesting that they may be staying at home or not immigrating. Different gender participation patterns were found between native-born Americans and immigrants from Taiwan and the “Rest of the World” composite variable at the 0.05 level. Speculatively, the data supports the image of men from Latin American nations striking out on their own in search of work and leaving their families behind.

Immigrants in the workforce from the Philippines, Jamaica, and Germany all had larger proportions of women in their workforce than native American proportions. Identifying specific reasons for this distribution is a fruitful topic for future research. According to data described in Table 4.4 immigrants from the Philippines are more likely to possess professional or bachelor degrees than native-born Americans. The data may reflect pay differentials in potential earnings that may exist when one compares remaining in a home country versus migrating to the United States.

Immigrant Age

Similarities exist when comparing age and gender variables. Immigrants from Guatemala, Honduras, Mexico, El Salvador, and India (countries whose workforce was dominated by men) also have the greatest proportion of workers who were between 18 and 35 years old in 2007. Table 4.9 compares proportions of native workers aged 18−35 with immigrant proportions in this age group.
Table 4.9

US and foreign-born workers age 18−35 (2007)


Proportion 18−35











El Salvador






Dominican Republic



United States









Rest of the world (128 countries)







































**Statistically significant at the 0.01 level

*Statistically significant at the 0.05 level

Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

The data described in Table 4.9, indicates that for some countries support exists for the image of young people coming to the United States in search of work. The data, however, does not support this image with regard to immigrants from Haiti, Peru, Colombia, Jamaica, and Cuba. An older cohort of workers was found for immigrants from Asia and Europe as well as Canada. The data in regard to India is particularly interesting. While immigrants from India make a great deal more money (see Table 4.3) and are more educated (see Table 4.5) than native Americans they also tend to be younger and male. The large proportion of younger Indian immigrants suggests that migration of working-age migrants is a relatively recent development.

In addition to income, wealth (as measured by home ownership and value of home) is another indicator of economic health and assimilation. These variables provide a measure of longer term stability than the 1-year income measure described in Table 4.3.

Immigrant Wealth

Wealth is correlated with home ownership and home value. Therefore, as problematic as it is, home ownership rates and home value may be the most reasonable proxy to measure wealth we can acquire through the ACS data. It is assumed that over time equity is built up in housing values and that those with higher housing values also have accumulated greater wealth. Many regard a person’s home as the source of his/her source of greatest equity. It is a source of emergency funding for many. It can be a source of funding for children’s college education for those who borrow on second mortgages. Because of mortgage financing, however, we cannot accurately assess the amount of equity built up in the homes which causes a limitation in our measure. Table 4.10 describes reported home values and percent of home ownership in 2007; the data refers to head of household place of birth.
Table 4.10

Home value by place of birth, Head of the Household (2007)


Home value


Percent home owner

1. Taiwan




2. India




3. Philippines




4. Korea




5. China




6. Rest of the World




7. England




8. Vietnam




9. Peru




10. Canada




11. Poland




12. Cuba




13. Haiti




14. El Salvador




15. Dominican Republic




16. Colombia




17. Jamaica




18. Guatemala




19. Honduras




20. United States




21. Mexico




22. Germany




**Statistically significant at the 0.01 level

*Statistically significant at the 0.05 level

Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

The data indicates that Asian and Indian immigrants owned more expensive homes than others and were more likely than others to own their homes. Relatively low proportions of immigrants from Honduras, Guatemala, Dominican Republic, and Mexico were home owners. Higher proportions of immigrants from Cuba, Jamaica, and Colombia owned their own homes than immigrants from other Latin American nations. Many factors might explain the large differences in home values between nationality groups.

Location is commonly viewed as one of the most important determinants of housing values. Differentials in where immigrants live therefore may account for at least some of the differences in housing value or cost. For example, many Asian immigrant groups have recently settled in California where house values are very high. In contrast, many German immigrants settled decades ago in the Midwest where land values were relatively low. Cost of housing may also relate to whether the home is located in a more densely populated metropolitan area or in a more rural area. People may pay a premium to be closer to their work in urban areas. Proximity to work is expected to lower the time of commuting to the place of employment and therefore should have a tangible value.

Another indicator of home values may be household composition. Multiple-head households have the opportunity to earn more income and therefore own more expensive units. Multiple-head households with families may also need more space and may be more willing to spend more of their income on housing.

A regression describes variation in home values by nationality group after controls were introduced. Table 4.11 describes home prices by immigrant group after controlling for location (state and metro status) and household composition (married, single head of family household, individuals living alone, nonfamily units). Some (the most impactful) but not all of the controls are described in Table 4.11. Controls were put in place for the 50 states, Washington, D.C., five measures of metro status, and seven measures of household composition. The regression created a normalized constant for a house in a generic central city by a “married couple, family household.” The control variables describe deviance from the normalized constant.
Table 4.11

Home values by head of household place of birth, controlling for state, metro status, and household composition (2007)


Unstandardized coefficient (measures home value)

Standardized coefficient (measures relative effects)

Standard error









Metro status: not in metro area




New York




New Jersey
















HH composition: female householder, lives alone




















HH composition: female householder, no husband present




HH composition: male householder, lives alone








Rest of the world
























El Salvador
















































Dominican Republic








Adjusted R2: 0.342

**Statistically significant at the 0.01 level

*Statistically significant at the 0.05 level

Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

A strong relationship exists between location and home values. As described in Table 4.11 owning homes in the states of California ($384,601), New York ($172,697), New Jersey ($219,118), Massachusetts ($239,338), and Florida ($126,743) all help to explain variations in home values. Large differences in price were also identified with respect to central city/nonmetro and household composition. Not unexpectedly, home prices were lower in nonmetro areas and higher in households of married couples. Holding state, household composition, and birth place constant, a home in a nonmetro area will be expected to be valued $94,890 less than a home in the central city.

Once location and household composition were controlled, the ordering of the value of a home began to resemble that of wages and salary found in Table 4.3. This convergence is displayed in Table 4.12, which shows the actual home values, estimated home value holding, location, and household type constant, the percentage change, and the most populous states of residence for immigrants.
Table 4.12

Estimate home value after controlling for state, metro status, and household size by place of birth of the Head of the Household (2007)


Most populous state of residence


Controlled estimate

Percent decrease

1st (%)

2nd (%)

3rd (%)

1. Taiwan



California (48.3)

Texas (8.6)

New York (6.7)

2. India



California (20.1)

New Jersey (11.4)

New York (9.4)

3. Philippines



California (46.9)

Hawaii (5.8)

New Jersey (5.4)

4. Korea



California (32.1)

New York (7.9)

New Jersey (6.2)

5. China



California (32.6)

New York (18.3)

Texas (4.3)

6. Rest of the World



California (17.7)

New York (16.1)

Florida (10.5)

7. England



California (18.0)

Florida (12.3)

New York (7.9)

8. Vietnam



California (42.9)

Texas (11.3)

Washington (4.1)

9. Peru



Florida (22.2)

California (18.2)

New Jersey (12.8)

10. Canada



California (16.6)

Florida (13.9)

New York (6.8)

11. Poland



Illinois (27.3)

New York (19.2)

New Jersey (11.2)

12. Cuba



Florida (76.6)

New Jersey 4.6

California (4.3)

13. Haiti



Florida (46.4)

New York (24.7)

New Jersey (7.9)

14. El Salvador



California (42.0)

Texas (13.0)

New York (7.1)

15. Dominican Republic



New York (49.1)

Florida (15.0)

New Jersey (13.3)

16. Colombia



Florida (38.6)

New York (15.2)

New Jersey (9.8)

17. Jamaica



New York (33.3)

Florida (31.3)

New Jersey (6.3)

18. Guatemala



California (36.6)

Florida (8.8)

New York (6.0)

19. Honduras



Florida (19.8)

Texas (14.2)

California (13.1)

20. United States



California (9.7)

Texas (7.5)

New York (5.8)

21. Mexico



California (40.2)

Texas (21.2)

Arizona (5.4)

22. Germany



California (13.9)

Florida (10.2)

New York (8.3)

Source: US Census Bureau, ACS 2007 (Ruggles et al. 2009)

Locations of residence for top immigrant groups are highly concentrated in just a few states. In particular, California has become a destination for many immigrant groups. Almost half of immigrants born in Taiwan, more than 40% of immigrants born in Vietnam, El Salvador, and Mexico reside in California. More than three-quarters of immigrants born in Cuba lived in the state of Florida in 2007; more than 40% of Haitian immigrants lived in Florida; about 50% of the immigrants from Dominican Republic, and about a third of immigrants from Jamaica lived in New York.

The value of homes for foreign-born residents from Mexico, El Salvador, Guatemala, and the Philippines decreased by over 50% of their value once the controls were introduced. Immigrants from Taiwan, Korea, China, and Vietnam also saw estimated value drops by over 40%. One reason for the declines in estimated value is the California residence for many of these immigrants. The state dummy variable of California is the most impactful variable in the model described in Table 4.12.

As described in Table 4.12, once control variables were introduced there was a large degree of convergence between values of immigrant homes and native American values. Given their incomes, immigrants from groups with lower salaries and wages are paying higher proportions of their income for housing. On average, estimated value of a native-American home is approximately five times yearly salary and wages. Many immigrant groups must pay 10 times yearly earning, if they were to purchase a new home. This high cost is probably reflected in the lower ownership rate among most immigrant groups.


Data described in this chapter indicate that dramatic differences exist between immigrant groups in terms of earnings and wealth. Much of these differences are accounted for by factors such as education, gender, age, race, and ability to speak English (for earnings), and location or family composition (for home value). Salary and wage differences as well as differences in home values, however, remain between immigrant groups after accounting for these factors.

In general, the data supported the image of immigrants from Latin America as earning less than native Americans, being less educated, younger, and more likely to be male. In contrast, immigrants from Asian nations earned more than native Americans and immigrants from Latin America. Asian immigrants were better educated and older. Immigrants from Asian nations in the workforce were more likely to be female. Immigrants from India were extremely well educated yet in terms of age and gender more closely followed the pattern of Latin American countries.

In regard to home value and home ownership, immigrants from Asia were much more likely to own their own homes and live in a higher valued home than immigrants from Latin America. Immigrants from Asia were also more likely to own their own homes than native-born Americans and to live in higher-value homes. The home value differences were apparent, even after controlling for location and household composition.

Many immigrants have influenced the American economy in a positive direction. In 2009, US News & World Report listed Chief Executives who had a great impact on the American economy (The Top 25 Market Movers of 2009, 2009). Three of these persons were immigrants: Vikram Pandit (India) was the Chief Executive Officer of Citigroup, Rupert Murdoch (Australia) is one of the wealthiest people in the world, and Nouriel Roubini (Turkey) served as a senior economist for the Council of Economic Advisers during the Clinton administration.

Other immigrants have also contributed to the economic development of the United States. The experiences of Andrew Grove, An Wang, and George Soros suggest that bright, ambitious people can still “make it” in America. All of them came to the United States without a great deal of income. Grove and Wang used their organizational and engineering talents to build large corporations and to expand the frontiers of technology. Both of them took advantage of educational opportunities available in the United States. Technological advances promoted by Grove and Wang helped to maintain the United States as a leader in the field of high technology. Soros became known for his acumen as an investor/speculator.

Case 4.1 Andrew Grove (Budapest, Hungary)

Andrew Grove’s Early Life

Andras Grof (Andrew Grove) was born on September 2, 1936 in Budapest, Hungary into a middle-class Jewish family. His parents, George and Maria, were not observant and considered themselves to be thoroughly assimilated Hungarians. Grove’s father was a partner in a medium-sized dairy business that was jointly owned with several friends. Andras’ father George served in a labor battalion clearing roads and building fortifications during World War II (Tedlow 2006, 18). When the German army invaded Hungary in 1944 Andras lived with a non-Jewish business associate of George Grof and took on a Slavic name. In 1945 when the Russians occupied Budapest Andras and his mother returned to their old home (Tedlow 2006, 27–28).

The war left an indelible mark on Grove. His father recounted tales of sadistic behavior by the Hungarians who guarded the labor battalion. Following the war, Grove’s mother opened a dairy store and his father secured a management position at a government-owned department store. The young Andras began to learn English and took piano lessons. After the fourth grade he began to attend a small school renowned for academic excellence. Among its graduates were a Nobel Prize winner in Physics, a Nobel Prize winner in Economics, and a pioneer game theorist, John von Neumann. Andras was a very good student performing better in his studies than his peers (Tedlow 2006. 38).

Grove’s father initially did well under the Communist regime in Hungary. He became the director of a government-owned company, however, he was accused of consorting with “bourgeois elements” and lost his job. George Grof was informed that he would never get another job that paid more than a quarter of his previous salary. Andras applied to the University of Budapest but initially was rejected because he was classified as a “class alien.” Through the intervention of a friend he was accepted.

Grove and his family developed a dislike for communism and linked it to “intangible but constant nagging fear” of being carried away in the middle of the night. In his autobiography, Grove expressed dissatisfaction with the shortages in Hungary of everything from sweaters to soap, the lack of basic food, incessant lines, inferior products, and pervasive sloganeering (Grove 2001, 168).

Escape from Hungary and Early Life in the United States

In October 1956 demonstrations against Communist rule in Hungary broke out. Grove’s aunt encouraged him to leave the country because the Russians were rounding up young people. It seemed as dangerous to stay in Hungary as to attempt escape. Eventually Grove made it to Vienna and with the help of an organization called the International Rescue Committee, he was taken to America. Grove was 20 years old, he had left his family, he possessed a smattering knowledge of English and German, the clothes on his back, and little else (Tedlow 2006, 57).

Grove arrived in New York in January 1957. He knew that his aunt’s sister lived in the Bronx and moved in with her family. Grove was motivated to come to America because of its mystique of wealth and modern technology as well as its image as a place with “lots of cars and plenty of Hershey bars” (Grove 2001, 226–227). Grove enrolled at City College of New York (CCNY) because it was a government-funded and tuition-free school. He majored in chemical engineering and, as in Hungary, excelled in his studies, finishing first in his engineering class. Grove called City College the quintessential American experience and in 2005 gave $26 million to their engineering school, the largest donation the school ever received (Tedlow 2006, 86).

Upon enrolling in college he decided to change his name from Andras Grof to Andrew Grove. Grove was similar to how his name had been pronounced in Hungarian (Grove 2001, 285). In 1962 Andy was able to secure passage to America for his parents. His father was 57 and his mother 55. At the time, Communist authorities in Eastern Europe were receptive to allowing people of this age to emigrate in order to save pensioner costs.

Grove worked as a busboy in New Hampshire during the summer of 1957 and met his future wife Eva Kastan there. Eva was an immigrant from Austria who fled to Bolivia at the age of 3 and moved to New York City when she was 18. They were married in 1958. Ironically, even though both were of Jewish origin they were married in a Catholic Church in deference to one of Eva’s relatives (Tedlow 2006, 69).

In 1960, Andrew Grove graduated from CCNY and moved to California. He found New York City too cold, wet, and ugly (Grove 2001, 282); in contrast he thought that San Francisco was special and that Berkeley was gorgeous. Andrew and his wife Eva calculated that with summer jobs, his wife’s income as a social worker, and frugality he would be able to attend graduate school. Grove’s financial situation was well suited for the publicly funded, tuition-free University of California at Berkeley. Andrew became a star performer and found Berkeley much lower-key, much calmer, and less confrontational than City College of New York. When he graduated with his PhD in 1963 he had many interviews. Fairchild Semiconductor Company, Bell Labs, and Lockheed showed great interest. Grove narrowed his choice to Fairchild and Bell Labs, choosing Fairchild partially because of its California location and partially because of Gordon Moore, an employee at Fairchild (Tedlow 2006, 81).

Andrew Grove’s Business Career

In July 1968 Grove joined Intel as its third employee, joining founders Robert Noyce and Gordon Moore. Prior to joining Intel Grove, Noyce, and Moore all worked at Fairchild Semiconductor. Moore hired Grove in 1963 to work at Fairchild soon after he earned a PhD in chemical engineering. When Intel was created, Grove became director of operations. Grove accumulated wealth over time through stock options; however, unlike Noyce and Moore he was not invited to buy stock in the company at its founding. As a result Grove’s financial assets did not approach those of Noyce, Moore, or venture capitalist Arthur Rock (Tedlow 2006, 119).

In 1979 Grove was named President of Intel, and in 1987 he became the company’s Chief Executive Officer. Grove was named Chairman and CEO in May 1997. Grove left an indelible mark on the company. Together with founders Bob Noyce and Gordon Moore, Grove presided over a remarkable period of engineering breakthroughs and financial success. In 1980, Intel was named one of the five best-managed companies (Dun’s Review) in the United States. In 1981, IBM selected Intel’s microprocessor for its personal computers. In 1982, Intel’s chip was adopted by the Ford Motor Company and the company passed $1 billion in annual revenue. Grove was named one of the 10 toughest bosses in America (Fortune magazine) in 1983 and in 1989 the National Academy for Engineering named an Intel microprocessor (Intel 480) one of the 10 outstanding engineering achievements for the advancement of human welfare.

Grove is widely credited for shifting the emphasis of the company away from memory chips to microprocessing. A key business decision made by Grove was to stop licensing chip designs of integrated circuits to competitors. Intel developed a new microprocessor in 1985 (i386 also known as 80,386) that became the central processing unit (CPU) of choice for personal computers. The company benefited greatly from the boom in personal computers in the late 1980s and 1990s (35 Years of Innovation 2003).

In 1992, Intel became the largest semiconductor company in the world (Grove 1996, 96). Intel’s technical breakthroughs had allowed personal computers to become lighter, smaller, more powerful, and less expensive. In 1998 Grove relinquished the CEO title. The Dow Jones Industrial average added Intel to its list of companies in 1998. In 2001, Intel built the world’s smallest (15 millionth of a meter) and fastest transistor. Grove stepped down as Chairman of Intel in 2005. After 2005 Grove remained a senior advisor to the company.

Andrew Grove’s Management Philosophy

Much of Grove’s management philosophy can be found in the books High Output Management (1983) and Only the Paranoid Survive (1996). Grove fostered a culture where “knowledge power” would trump “position power” and anyone could challenge anyone else’s idea. Data was required for proving one’s point (Tedlow 2005). Grove focused upon the concept of teamwork. He championed the idea that the output of a manager is achieved by a group (Grove 1983, 41).

Grove contended that a manager’s work by itself does not create output, the organization creates output. He believed that a manager must keep “many balls in the air” at the same time and shift attention to activities that will increase the output of the organization to the greatest degree. Much of Grove’s typical day was spent acquiring information. This information came from reading reports, talking to people inside as well as outside the organization, and listening to customer complaints. Grove (1983, 49) noted that an especially efficient way to get information was to visit a particular place in the company and observe what was going on there.

Grove believed that managers should be role models for people in the organization including subordinates, peers, and supervisors. He believed values should be transmitted by visible actions. How one handles his/her own time was perceived to be the most important aspect of being a role model and leader. Under Grove’s leadership at Intel, a one-on-one meeting between a supervisor and subordinate was the principal way their business relationship was maintained. The main purpose of the meeting was mutual teaching and exchange of information. The level of maturity of a subordinate determined the frequency of the one-on-one meetings.

In the book, High Output Management (1983, 89) Grove stated that the key to success in organizations was the middle manager who acted as the link in the chain of command. Middle managers could also see if holders of “knowledge power” meshed smoothly with personnel who held “position power.” Grove recognized that in information type businesses, in all likelihood, new hires possessed more up-to-date knowledge about technology. Even if veteran managers were once outstanding engineers they would not always be the most informed technical experts. Grove believed that a business like Intel had to employ decision-making processes that differed from those in more conventional industries.

Grove (1983, 89–91) developed a model of decision making that included at the first stage free discussion of all points of view and aspects of an issue. The second state of the model is reaching a clear decision. The last stage of the model involves everyone giving full support to the decision. Grove contended that organizations live “by people committing to support the decisions and moves of the business” (Grove 1983, 91). Grove realized that accepting decisions might be easier for senior managers who identify with the values of the organization and new college graduates used to working on teams in laboratory experiments.

An important feature of Grove’s model of decision making was that decisions should be made by people who are closest to the situation and know most about the issue. He thought technical understanding must be tempered with judgment and experience. At Intel, Grove often asked a senior person to attend a meeting where a decision would be made. Everyone at the meeting was to voice opinions as equals throughout the free discussion stage, ignoring status differences. Grove believed that status symbols hindered the flow of ideas, facts, and points of view.

In order to promote egalitarianism at Intel, Grove emphasized informal dress, partitions instead of offices, and the absence of perks such as reserved parking spaces. He believed “knowledge power” people had to interact with “position power” people daily. In order to elicit performance from employees, managers must determine why a person is not doing his or her job. Grove presents two possible reasons: (1) a person can’t do the job, and (2) a person is not motivated to do the job. If a person could not do his or her job, Grove recommended training. Alternatively, if a person was not motivated, the manager should create an environment which better motivated people. Grove believed that motivation came from within a person, accepting Abraham Maslow’s theory that motivation was tied to higher order needs (Grove 1983, 164).

Grove contributed to management philosophy by popularizing the motto, “Only the paranoid survive” (Grove 1996, 3–7). He was able to identify points in the life of a business when its fundamentals changed. This change may signal an opportunity to rise to new heights or the beginning of the end. Grove explained that competition in the mid-1980s from Japanese memory producers forced Intel out of memory chips and into the new field of microprocessors. Thousands of employees were laid off and factories were shut down. Grove recognized that if Intel had not changed their business strategy they would have been relegated to a relatively insignificant role in the industry.

Legacy of Andrew Grove

The legacy of Andrew Grove is the contributions he made in the development of personal computers and more specifically to the company he headed for many years. In 2007, Intel had net revenues of $38.3 billion, invested $5.8 billion in research and development, and invested $5 billion in additions to property, plant, and equipment (Intel 2007). Intel was recognized as the world leader in semiconductor technology, relentlessly focusing on innovation and growth. By 2008, Intel (incorporated in Delaware) employed approximately 84,000 workers.

Grove also acquired personal acclaim as an author and scientist. He has written over 40 technical papers and holds several patents on semiconductor devices. Grove taught a graduate course in semiconductor device physics at the University of California, Berkeley and at the Stanford University Graduate School of Business. He holds honorary academic degrees from the City College of New York (1985), Worcester Polytechnic Institute (1989), and Harvard University (2000). Grove’s first book on the physics of semiconductor devices has been used at many leading universities in the United States. One of his books on business management, High Output Management, has been translated into 11 languages.

In 1995 Grove received the Heinz Foundation Technology Award and was lauded for representing a story “as old as America,” the story of a young immigrant rising to great success. The donors of the award stated that Andrew Grove has played perhaps the single most pivotal role in the development and popularization of the twentieth century’s most remarkable innovation – the personal computer. The technologies pioneered by Grove and his associates, first at Fairchild Semiconductor and then at Intel – the company he co-founded in 1968 – made the entire personal computing revolution possible. The foundation noted that the world has barely begun to scratch the surface of the technological and economic benefits that the computer revolution can bring. They stated that Grove has always managed to maintain his focus on what he does best: developing even faster, more affordable, and more powerful technology. The foundation asserted that thanks to Grove’s genius and vision, millions of people now have instant and inexpensive access to the kind of information and entertainment about which even the privileged of earlier generations could only dream (The Heinz Awards 1995).

Further accolades followed. In 1997, Grove was named Time magazine Man of the Year. In 1998 he was named Distinguished Executive of the Year by the Academy of Management; in 2000 he was awarded the Medal of Honor by the Institute of Electrical and Electronics Engineering (IEEE) and in 2004 Grove was recognized as the Most Influential Business Person of the Last 25 Years by the Wharton School of Business and the Nightly Business Report. In an interview in Esquire magazine in 2000 Grove noted that immigration and immigrants are what made America what it is. He encouraged America to be vigilant as a nation to have a tolerance for difference, a tolerance for new people (Knowledge@Wharton 2002).

Case 4.2 An Wang (Shanghai, China)

An Wang’s Early Life

An Wang was born on February 7, 1920, one of five children. An Wang’s father taught English in a private elementary school about 30 miles from Shanghai and was a well-respected individual in his community. The elder Wang attended university for a year at a time when very few Chinese attended college. He practiced traditional Chinese medicine. The Wang family had a fairly reliable written history that went back more than 20 generations. Another history of the family went back another 25 generations but with less certainty. These written histories gave the Wang family a remarkable sense of continuity and permanence. Like most Chinese children, An grew up with a sense that their culture and family had been around for a very long period of time (Wang 1986, 13).

Wang’s grandmother instilled in him the teachings of the ancient philosopher Confucius (551 BC–479 BC). These teachings emphasized personal and governmental morality, correctness of social relationships, justice, and sincerity. Later in his life Wang maintained that Confucian principles (such as moderation, patience, balance, and simplicity) were important to his business success. In 1926 Wang skipped kindergarten, first grade, and second grade, entering school as a third grader. Wang discovered that he was very good at math but less so in history and geography. When he finished sixth grade Wang scored the highest of all applicants in a competitive test for entry into junior high. An discovered that his first love was in the sciences, particularly physics and math (Wang 1986, 19).

When An Wang was 13 he attended a prestigious high school in Shanghai. The school used some of the same math textbooks as was used in American colleges. Upon graduation from high school at the age of 16, Wang was accepted to Chiao Tung University, considered the “MIT of China.” He graduated from the university in 1940 and spent a year as a teaching assistant in electrical engineering. As the Japanese took control of Shanghai, Wang was sent to the interior of China to design and build radios and transmitters for Chinese troops. An was put in charge of a group that designed radio equipment (Wang 1986, 27).

While building radios in interior China, An learned about a program that sent Chinese engineers to the United States. As he did not have close family ties in China (both his parents had died after the Japanese invasion of Manchuria in 1931) An applied to the program and was accepted. He arrived in Newport News, Virginia in June 1945. Soon after arrival he decided to apply to an American graduate school and was admitted to Harvard University where some of the faculty at Chiao Tung University had studied. Wang attributed his admission to Harvard to luck and timing. In 1945 most young Americans were still in military service and Harvard had available openings. Wang benefited from the fact that the university he attended in China (Chiao Tung University) had a good reputation and many of its graduates had previously done well at Harvard (Wang 1986, 35).

Education and Inventions

In September 1945, Wang began his studies at Harvard and worked under the tutelage of two Nobel laureates: Edward Purcell and Percy Bridgman. In his autobiography Wang claims to have found his school work relatively easy, partly because of his experience designing and building radio and communications equipment in China. In two semesters he satisfied the requirements for a master’s degree in applied physics. After acquiring the master’s degree he was able to secure a position in Canada purchasing material for the Chinese government. He found this work tedious and applied to Harvard’s PhD program in Applied Physics. An was promptly accepted and offered a teaching fellowship that paid $1,000 a year in return for 10 hours a week as a laboratory instructor (Wang 1986, 38).

Less than 16 months after enrolling at Harvard Wang graduated with a PhD in Applied Physics. Except for the speed with which it was finalized, An did not consider his dissertation a major achievement. He did not think it made a fundamental contribution to the body of knowledge in electrical engineering, and had little to do with any of his later inventions. Wang recognized, however, that having a PhD from Harvard could assure customers of a one-man shop (such as Wang Laboratories when it began in 1951) that he knew what he was doing (Wang 1986, 43). Wang’s modesty is evident as he downplayed his academic achievements in his autobiography. Clearly not everyone who applies to Harvard University is readily accepted, nor do they find their studies relatively easy, nor do they graduate with a doctoral degree in such a short period of time.

Soon after graduation An went to work for Howard Aiken, Director of Harvard’s Computation Laboratory. The Computational Laboratory at Harvard had previously built one of the world’s first digital computers and was developing more advanced machines under a contract from the US Air Force. During his time at the Computational Lab, Wang’s supervisor (Howard Aiken) gave him the assignment of developing a way to store and retrieve data using magnetic devices. Wang initially was perplexed by the assignment but before long he was able to develop a process where one could read information stored in a magnetized ring by passing a current around it. Wang published an account of this innovation in a 1950 article co-authored with W.D. Woo, another Chinese native who worked at Harvard. Wang patented his invention and in 1956 after a lengthy patent dispute sold it to IBM for $400,000. Wang’s invention of magnetic cores remained a basic part of computers into the 1970s (An Wang Biography 2009; An Wang 2009; Pugh 1984, 88).

Wang claimed that when he made his breakthrough at the Computational Laboratory he had no idea of its eventual importance. Wang claimed that those working on computers in the late 1940s did not have a sense that they were making history. As a researcher at Harvard’s Computational Lab, Wang had a good deal of independence; nevertheless in 1951 he decided to leave the lab. Finding solutions to vexing engineering problems gave him confidence that he could make a living in the United States. His supervisor Dr. Aiken was pleased with his work; however, by Wang’s second year at the Computational Lab it became evident that Harvard’s commitment to computer research was waning.

Because Harvard did not pursue research in developing technologies once they had commercial application, Wang decided to try to strike out on his own. He did not know at that time that his invention for core memory would later make him wealthy. According to his personal account, the intellectual satisfaction of solving a problem was its own reward. Wang began to turn his attention to solving real-life problems as he did when he built radios for the Chinese military (Wang 1986, 61).

Wang Labs

An Wang started his own company a mere 6 years after coming to the United States. In 1951 he was married, had one child, and carefully weighed his options. An gave up his salary of $5,400 a year and drew down on his savings of a few hundred dollars to start his own business. He believed that he had a reasonable chance of earning around $8,000 in his first year. Wang read books about how to run a business, paid a small registration fee, and in 1951 established his business as a sole proprietorship. His initial capital was $600 in savings; he had no orders, no contracts, and no office furniture. Wang found office space at about $70 a month (Wang 1986, 75).

Wang was a risk taker and determined to succeed in his business. His actions ran counter to the conventional behavior of Chinese immigrants at the time. In the 1950s most of the Chinese who came to the United States for graduate studies chose academia for a career. Wang, however, believed that he could succeed as an entrepreneur. He was distressed to see the menial role Americans assigned to Chinese. In his autobiography, Wang stated that “a small part of the reason I founded Wang Laboratories was to show that Chinese could excel at things other than running laundries and restaurants” (Wang 1986, 77). He drew insights from the Confucian philosophy that allowed him to assimilate new ideas without destroying old ones.

Wang began by contacting people in government and industrial research labs who were interested in storing information. He attended trade shows, demonstrated his storage innovation, and within 3 weeks began selling magnetic memory cores. The fundamental idea behind his business was that digital electronics could make life easier for scientists whose chores involved counting, storing, and computing information (Wang 1986, 85).

By the fall of 1952 Wang won a contract that gave him $300 a week, the first steady stream of income for Wang Laboratories. He taught a course in electrical engineering at Northeastern University in Boston for the sum of $12 a lecture. When Wang sold his patent to IBM the annual income from Wang Laboratories was about $10,000 a year. Wang noted that in view of the tremendous increase in the size of the computer industry and the role of his invention in computers, he probable received a price that was less than the true value of his patent. However, Wang did not wish to spend all his time and energy fighting legal battles over the rights to his ideas (Wang 1986, 106).

In 1955 Wang Laboratories was incorporated, an act that removed Dr. Wang from any personal liability for debts of the company and removed from risk the money he obtained from the sale of his patent. In 1963 Wang Labs began manufacturing equipment for typesetting. Due to the success of these typesetting machines (Wang Labs also patented the innovations for the machines) sales at Wang Labs exceeded $1 million in 1964. Wang had signed an agreement where another company retained the right to manufacture the machines without paying a royalty, a decision he later regretted. Wang vowed to never again design and manufacture a product for others to market (Wang 1986, 121).

In 1965, Wang Labs developed a user-friendly desktop calculator. For a price of $6,500 Wang’s calculator could engage in more complex mathematical calculations (logarithms, exponents, roots) at a fraction of the cost of a mainframe computer. Between 1965 and 1971 Wang Labs gained a good reputation as a calculating company, at first selling its calculators to scientists and engineers. Lawrence Livermore Laboratory of the University of California at Berkeley as well as other nuclear laboratories purchased Wang’s calculator. Eventually Wang’s calculating machines were used in the financial services industry (Wang Laboratories 2009).

Wang and his associates next developed a calculator that was easier to use and less costly (Model 300). This calculator was priced at just under $1,700 and by 1967 its sales expanded to $6.9 million. The Wang computer was priced in line with the competition yet still managed to yield gross profit margins of 65–70% (Wang 1986, 134). Wang Laboratories expanded and opened offices in the United Kingdom, Belgium, and Taiwan; in 1967 the company went public, however, the Wang family, still retained control of a majority of the stock. At the end of the first day of trading on Wall Street, Wang Laboratories had a market capitalization of about 70 million dollars.

Wang resisted suggestions to change the name of the company noting that Du Pont has a French name and Levi Strauss has a Jewish name yet both companies did very well in the United States. He took great satisfaction from the fact that many of his employees benefited from the stock options that he offered to both senior and junior members of the company.

In the early 1970s Wang decided to abandon the calculator business (because he thought profit margins would decline) and focus his energies on general purpose computers. This was not an easy decision because at the time calculator sales comprised about 70% of Wang Laboratory’s revenue. In 1972 Wang Labs shipped its first general purpose computers. The company later began to manufacture word processors. As the company grew, it entered into the Fortune 500 (Wang 1986, 170). With their new products, Wang Labs ceased to be known as a calculator company and instead became known as a word processing company. Wang products that were introduced in 1976 and 1977 were technological breakthroughs and were in great demand. By 1982 Wang Labs had sales of more than a billion dollars (Wang Laboratories 2009; Wang 1986, 185, 199).

By the mid-1980s Dr. Wang delegated more responsibility to his executives and did not involve himself in the daily management of specific projects unless he thought there was a serious problem. He began to feel that the sense of urgency that permeated the company at its founding was lost (Wang 1986, 218). Like other computer companies, Wang Laboratories began to falter in the late 1980s and 1990s. A variety of factors may have contributed to the decline, These factors included (1) an inability to compete against other personal computers in the 1980s; (2) competition from companies such as Apple, IBM, Sun, and Hewlett-Packard; and (3) Dr. Wang’s insistence that his son succeed him. In 1986 Fred Wang (then 36 years old) became president of the company; in 1989, however, his father fired him. When An Wang died in 1990 Wang Laboratories ended the year with a record loss. In 1992 Wang Laboratories filed for bankruptcy. The three Wang tower buildings in Lowell, Massachusetts were sold.

Wang Laboratories emerged from bankruptcy and shifted its focus (from designer and manufacturer of computers) to network services. In the late 1990s Wang Laboratories changed its name to Wang Global. By 1999 the company had annual revenues of $3.5 billion. In 1999 it was acquired by Getronics of The Netherlands. In 2007 this company was acquired by the large Dutch telecommunications company, KPN NV (Wang Laboratories 2009).

Legacy of An Wang

An Wang died of cancer in 1990. He left behind an impressive legacy of scientific and business achievement. In 1988, Dr. Wang was inducted into the National Inventors Hall of Fame. He was named a fellow of the Institute of Electrical and Electronic Engineers, a fellow of the American Academy of Arts and Sciences, and in 1986 Dr. Wang was awarded the United States Medal of Freedom. The Medal of Freedom is the nation’s highest civilian award given for distinguished civilian service in peacetime, reserved for especially meritorious contribution to the national interests of the United States, world peace, or other public or private endeavors.

Dr. Wang founded the Wang Institute of Graduate Studies in Tyngsborough, Massachusetts which offered instruction in Software Engineering. In 1987 Dr. Wang transferred ownership of the institute to Boston University. Wang also contributed substantially to the Boston’s Metropolitan Theater which was renamed in 1983 the Wang Theater. Boston’s Metropolitan Center became known as the Wang Center for the Performing Arts. The An Wang Middle School in Lowell, Massachusetts is named in his honor. The An Wang Professorship of Computer Science and Electrical Engineering at Harvard University was established in his honor. At its peak in the 1980s, Wang Laboratories had annual revenues of $3 billion and employed over 40,000 people (Wang Laboratories 2009).

Wang attributed much of his success to his association with Harvard and the lucky timing of his arrival in the United States. He stated, “I never dismiss luck as a factor in a person’s destiny. How foolish it would be for a survivor of war and anarchy not to believe in luck. In fact, I believe that it is self-deceptive-even dangerous-to think that one’s life is entirely the product of one’s own decisions and actions” (Wang 1986, 44).

In 1955, An and his wife Lorraine became naturalized American citizens. Wang claimed that he was ambivalent about giving up his Chinese citizenship and did not think America was a utopia, especially as it was swept up with the paranoia of 1950s McCarthyism. He concluded, however, that Americans had the best system; a nation that did not always live up to their ideals, but had structures that allowed it to correct for wrongs by means short of revolution (Wang 1986, 83).

Wang remained deeply moral and ethical in his business dealings. He rejected the concept of the amoral corporation that maximizes its profits within rules set by the community. He believed that a company that oriented itself toward serving both its community and customers would reap long-term rewards. Wang contended that because the company bears his name he could not accept a lesser standard of behavior for the corporation than he demanded of himself. In his autobiography, he maintained that if in pursuit of his goals (of devising equipment that increased worker productivity and made jobs easier) his company exploited its employees, or its surrounding community, or pursued business in an unethical manner, it would negate whatever positive contributions it made. He concluded, “Ultimately, all a person has is his reputation. In my case, that reputation is shaped not just by my actions as an individual but also by the reputation of Wang Laboratories … My days are spent doing the things I really want to do. The satisfaction of turning an idea into something real never diminishes, and the great gift of change is that it continually replenishes the stock of new ideas that might be brought to life” (Wang 1986, 228, 239).

Case 4.3 George Soros (Budapest, Hungary)

George Soros’s Early Life

As a young child George Soros survived the dangers of persecution and war. His father Tivadar had a great influence on him. In 1914 when Tivadar was 20 years old he enlisted in the Austro-Hungary army thinking that service in World War I would be beneficial to his career. Tivadar, however, was captured by the Russians and spent a good deal of time as a prisoner of war. While imprisoned he began to embrace a philosophy of internationalism, anti-sectarianism, and cosmopolitanism that his son later supported. After escape and long travels Tivadar returned to Budapest in 1920, absent for almost seven years (Kaufman 2002, 14).

In 1924, Tivadar became a lawyer and married a distant cousin whose family was a part owner of a successful fabric shop. He and his wife, Erzebet, often went on hiking and skiing trips in the Alps. The war, however, had altered his yearning for conventional success. He began to work only about 2 h a day in his law practice and devoted more time to fostering harmony between peoples of different nations. George was born in 1930 and in 1936 his parents changed their name from Schwartz to Soros, wishing to adopt a less Jewish name (Kaufman 2002, 24).

In March of 1944 the German military took control of Hungary. Jews began to be transported, however, the Soros family was able to secure false documentation and scattered to different locations. All members of Tivadar’s immediate family (including George) acquired new names, birth dates, addresses, dates of baptism, and graduations. George posed as the godson of an employee of the government. Soros witnessed the siege of Budapest in early 1945. In the early days of Soviet occupation George was actively engaged in exchanging currency on the black market. In 1948 he acquired the necessary documents to leave Hungary and travel to London where he stayed with a distant relative (Kaufman 2002, 49, 52).

Soros did not feel welcome in England and took odd jobs such as dishwasher, house painter, busboy, and lifeguard. He enrolled in a commuter college but was dismissed. In the spring of 1949 Soros was admitted to the London School of Economics where he found himself in close proximity to prominent scholars such as Karl Popper (Kaufman 2002, 65). Soros openly embraced Popper ideas expressed in The Open Society and Its Enemies (1945) that societies that encourage continual arguments, refinements, and revisions about their own rules of governance are much more effective than those based on rigid dogma.

Soros later noted that his association with Popper represented the only bright spot during his time in England. While Soros held lofty ambitions and was able to graduate from the London School of Economics, he was not a stellar student and did not distinguish himself academically (Kaufman 2002, 74). He, however, found his passion in the world of finance.

Soros the Financier

While in London, Soros secured a position in finance but was not viewed favorably by his superiors. Soros was subsequently offered and accepted a position at a brokerage house in New York. He initially was denied a visa on the grounds that at 25 he was too young to qualify as a specialist whose services were urgently required in the United States. Soros obtained a visa only after it was noted that his position on Wall Street often took a toll on the health and nerves of workers, resulting in early death. Technically, the position was that of an arbitragist. At the time, this type of job entailed buying in one market and selling in another in order to take advantage of small variations in price. Before he left England, he scored a financial coup for his company. In September 1956 Soros left England for the United States (Kaufman 2002, 80).

Soros migrated to America because of the economic opportunity it offered. In 1956 he began work for an over-the-counter trading company, F.M. Mayer, and moved in with his brother who also lived in New York. Soros’ parents escaped Hungary in late 1956 during the nation’s revolt and by early 1957 they moved in with George who by then rented his own apartment. At work, Soros began to make valuable contacts including a future chief executive officer of the large investment company Bear Stearns. He began to put F.M. Mayer on the map. By his third summer in the United States Soros was prosperous enough to rent his own beach house in the Hamptons, a prosperous area of Long Island (Kaufman 2002, 90).

After about three years at F.M. Mayer, Soros took a position at a larger company. This gave him more independence to trade without going through others. George proved to be a shrewd trader. In 1967 Soros persuaded his bosses to let him set up an offshore fund (the First Eagle Fund) and manage it. In 1969, he started a second fund (Double Eagle Fund) with $250,000 of his own money. His Double Eagle Fund was based in Curacua, Dutch Antilles, allowing him to escape both SEC scrutiny and capital gains taxes (Slater 1996, 70).

Soros was one of the first to use the complicated financial instrument of derivatives. In 1973 Soros entered into a business partnership with a colleague, Jim Rogers, and started his own business. His wealth grew rapidly. In its first 5 years the Double Eagle Fund (managed by Soros) had grown from $4 to $17 million. When Soros started his own company with Rogers they created a new fund (Soros Fund) with many shareholders of Double Eagle joining this fund. Those who originally invested with Soros in 1969 in Double Eagle and who transferred their money to the Soros Fund enjoyed great success. A $100,000 investment in 1969 became worth more than $353 million by the end of 1997. Soros eventually changed the name of the Soros Fund to the Quantum Fund. In 1998, the overall value of the Quantum Fund was around $6 billion (Kaufman 2002, 135).

Clients of funds managed by Soros were mostly wealthy individuals rather than institutions. Original investors consisted of Europeans who had been dealing with Soros for many years. By 1975 Soros was beginning to be noticed on Wall Street. In 1976 his fund appreciated by around 62% compared to an increase in the Dow Jones Industrial average of about 23%. In 1980, the Soros fund increased by 102% compared to a rise of 22% in the Dow Jones average (Kaufman 2002, 137–138). By 1981, Soros was named “the World’s Greatest Money Manager” by Institutional Investor magazine. His record surpassed that of Warren Buffett the famous “Oracle of Omaha” (Slater 1996, 4). Though Soros had become wealthy he did not want to attract more investors and, compared to others, did not flaunt his wealth.

In 1992, Soros became world famous when his speculation on the value of the British pound reaped enormous profits. He secured profits of about $2 billion during the financial turmoil of 1992 (Slater 1996, 6). Soros was named “the man who broke the bank of England” by the magazine The Economist. Business Week dubbed him “the man who moves markets” (Slater 1996, 8).

Soros the Philosopher and Political Activist

Soros was deeply interested in philosophy since his days at the London School of Economics and developed a set of ideas to explain the relationship between thought and reality. He used his theory to predict, among other things, the emergence of financial bubbles. In his theory of reflexivity, Soros posited that beliefs alter facts and that markets offered a biased view of the future. Soros rejected the efficient market hypothesis (prices accurately took into account future developments) and promoted the view that prices were the result of perceptions which in turn were influenced by emotions.

According to Soros, prices were not passive reflections of value but helped create their own value. A second component of his theory was grounded in the idea of misconceptions. Soros believed misconceptions (divergences between participant thinking and the actual state of affairs) were always present. These divergences could create a situation of instability or boom/bust sequence. Sequences of boom or bust occurred when people bought in response to rising prices and sold in response to falling prices in a self-reinforcing manner. For Soros, capitalizing on instability (caused by herd mentality) was a lucrative way to make money (Slater 1996, 53).

Soros’ political philosophy reflected the sentiments of his father. He advocated open societies where free individuals respected one another’s rights within a framework of law. Unlike the case of fascism and communism, he believed that free markets were highly supportive of open societies. Soros noted, however, that free markets were not perfect because they only catered to individual need. He concluded that both the extremes of communism (which sought to abolish markets) and market fundamentalism (which sought to impose the supremacy of market values over all political and social values) were wrong (Soros 2000, xxiv). Soros claimed that a decline in professional standards and conflicts of interest were responsible for the economic problems of the 1990s. Both of these factors were viewed as symptoms of the glorification of financial gain irrespective of how it is achieved (Soros 2002).

As he acquired great wealth Soros became extremely active in philanthropy and politics. In the 1970s he began providing funds to help black students attend the University of Cape Town in South Africa. In 1992 and 1993 Soros donated $500 million and made commitments to give away another $500 million. In 1993, he bequeathed more money to Russia than many Western governments (Slater 1996. 13). In 2003, Soros stated that removing George W. Bush from office had become the central focus of his life. During the 2003–2004 election cycle Soros donated more than $23 million to groups that were dedicated to defeating Bush. After Bush’s 2004 reelection Soros gave money to groups that supported the goals the Democratic Party (George Soros 2009a).

Legacy of George Soros

In 2008, Soros had a net worth of approximately $9 billion and was ranked by Forbes magazine as the 101st richest person in the world (George Soros 2009a). Soros funded a variety of organizations to develop democratic institutions in Central and Eastern Europe. Most of these efforts were supported by Soros’s Open Society Institute. The Open Society Institute embraced the philosophy of Karl Popper. Soros received honorary doctoral degrees from the New School for Social Research (1980), the University of Oxford (1980), and Yale University (1991).

Soros financially backed a diverse array of liberal causes including legalizing the medical use of marijuana, humane treatment of the terminally ill, and improving math education (Times 25 Most Influential Americans 1997). In 1997 Time magazine named Soros as one of the 25 most influential Americans. He was the nation’s largest philanthropist in 1996 with $350 million in gifts. In 2007 Time magazine named Soros to its Time 100 stating that Soros’ network had spent $742 million in the United States alone, and he had given away more than $6 billion during his career (Caplan and Masters 2007).

Soros is the author of nine books and continuously writes essays. He remains controversial with many Americans critical of his policy positions. Soros opposed post-9/11 national security measures, promoted immigration, supported social welfare programs, defended civil liberties, opposed the death penalty, promoted racial preferences, and promoted taxpayer-funded abortion (George Soros 2009b).

Soros was married twice and divorced twice. He has five children. In 2007 Soros resumed more active trading. He contended that the economies of the developed world were headed for trouble and chose to invest in countries such as India and China (Soros 2008, 121). In the foreword to Soros’ book The Alchemy of Finance (2003, xii), former Federal Reserve Chairman Paul Volcker characterized Soros as an enormously successful speculator who was wise enough to largely withdraw when still way ahead of the game.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Urban Studies Institute, University of LouisvilleLouisvilleUSA

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