Iranian Immigrants in Los Angeles: The Role of Networks and Economic Integration (The New Americans: Recent Immigration and American Society) (The New ... Recent Immigration and American Society)

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Author: Claudia Der-Martirosian

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The New Americans Recent Immigration and American Society

Edited by Steven J. Gold and Rubén G. Rumbaut

A Series from LFB Scholarly

This page intentionally left blank

Iranian Immigrants in Los Angeles The Role of Networks and Economic Integration

Claudia Der-Martirosian

LFB Scholarly Publishing LLC New York 2008

Copyright © 2008 by LFB Scholarly Publishing LLC All rights reserved. Library of Congress Cataloging-in-Publication Data Der-Martirosian, Claudia. Iranian immigrants in Los Angeles : the role of networks and economic integration / Claudia Der-Martirosian. p. cm. -- (The new Americans : recent immigration and American society) Includes bibliographical references and index. ISBN 978-1-59332-240-3 (alk. paper) 1. Iranians--California--Los Angeles--Economic conditions--20th century. 2. Iranians--Employment--California--Los Angeles--History-20th century. 3. Iranians--Kinship--California--Los Angeles--History-20th century. 4. Iranians--Social networks--California--Los Angeles-History--20th century. 5. Iranians--California--Los Angeles--Ethnic identity--History--20th century. 6. Immigrants--California--Los Angeles--Economic conditions--20th century. I. Title. F869.L89I54 2008 304.8'7949405509048--dc22 2007043128

ISBN 978-1-59332-240-3 Printed on acid-free 250-year-life paper. Manufactured in the United States of America.

To the loving memory of my parents, Stella and George


Table of Contents

List of Tables …………………………………………... vii Acknowledgements .…………………………………... xi Preface …………………………………………...……. xiii Chapter 1: Economic Capital, Human Capital or Social Capital?……………………………………... 1 Chapter 2: The Iranian Survey .…………………….…. 17 Chapter 3: Timing of First Job ………………………… 33 Chapter 4: Shift in Occupational Status …..…………… 55 Chapter 5: Determinants of Income …………………… 71 Chapter 6: Self-Employment …………..……………… 87 Chapter 7: Ethno-Religious Groups ………………..… 105 Appendix A: Iranian Survey, Household Roster ….….. 123 Appendix B: Iranian Survey, Migration Experience….. 124 Appendix C: Iranian Survey, First Employment in U.S. 125 Appendix D: Iranian Survey, Current Employment……126 vii

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Appendix E: Iranian Survey, Network Ties …………..127 Appendix F: Iranian Survey, Employment in Iran ….. 128 Appendix G: Iranian Survey, Spouse’s Employment ...129 Appendix H: Iranian Survey, Study Questionnaire …...130 References ………………………………………..….. 145 Index ………………………………………….…..….. 159

List of Tables

Table 2.1: Socioeconomic Characteristics of Iranian Males, LA County …………………………….…… 28 Table 2.2: Socioeconomic Characteristics of Iranian Females, LA County …………………..….… 29 Table 2.3: Socioeconomic Characteristics of Armenian Iranian Males, LA County ...…………..……. 30 Table 2.4: Socioeconomic Characteristics of Armenian Iranian Females, LA County ………..………. 31 Table 3.1: Sample Characteristics, Iranian Males, LA County, 1987-88 …………………..……….. 48 Table 3.2: Network Measures by Timing of First Job, Iranian Males, LA County 1987-88…….….... 49 Table 3.3: Logistic Regression, Finding First Job in the U.S., Iranian Males, LA County 1987-88 ...... 50 Table 3.4: Logistic Regression, Finding First Job in the U.S., Iranian Males, LA County 1987-88 ...… 51 Table 3.5: Logistic Regression, Finding First Job in the U.S., Iranian Males, LA County 1987-88 ...… 52 Table 3.6: Period of Immigration by Network Measures Iranian Males, LA County 1987-88 ……...… 53 . ix

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List of Tables

Table 4.1: Last Occupation in Iran by First Occupation in the U.S., Iranian Males, LA County 1987-88 ..67 Table 4.2: Change in Occupational Status Between Last Job in Iran and First Job in the U.S., Iranian Male Wage & Salary Workers, LA County 1987-88..68 Table 4.3: Logistic Regression Predicting Positive Change in Occupational Status, Iranian Male Wage & Salary Workers, LA County 1987-88 ………. 69 Table 5.1: Sample Characteristics of Iranian Males, LA County 1987-88 ………………………… 82 Table 5.2: Mean Annual Income by Economic Embeddedness, Iranian Males, LA County 1987-88 ………….………………………..…. 83 Table 5.3: Multiple Regression Predicting Log (income) Iranian Males, LA County 1987-88 ………… 84 Table 5.4: Mean Annual Income by Strength of Tie, Iranian Males, LA County 1987-88 …………. 85 Table 5.5: Job Satisfaction by Strength of Tie, Iranian Males, LA County 1987-88 …………………. 86 Table 6.1: Sample Characteristics of Self-Employed, Iranian Males, LA County 1987-88 ………. 100 Table 6.2: Logistic Regression Predicting SelfEmployment, Iranian Males, LA County 1990 ……………………………………….....101 Table 6.3: Logistic Regression Predicting SelfEmployment, Iranian Males, LA County 1987-88 …………………………….…..….. 102

List of Tables

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Table 6.4: Economic Network Scale Items by Type of Tie, Iranian Males, LA County 1987-88 ………..103 Table 7.1: Characteristics of Ethno-Religious Group, Iranian Males, LA County 1987-88 ………. 119 Table 7.2: Top Occupational and Industrial Niches, Iranian Immigrants, LA County 1990 …………….. 120 Table 7.3: Mean Scores for Quality of Jobs, Iranian Occupational and Industrial Niches, LA County 1990 ………………………………….……. 121


Acknowledgements

It gives me great pleasure to write this section and thank those who have been supportive throughout the process of writing this book. The 1987-88 Iranian Survey in Los Angeles gave me the opportunity to work with a group of talented scholars - Professors Georges Sabagh, Ivan Light, Roger Waldinger and Mehdi Bozorgmehr - in the fields of Sociology and Middle Eastern Studies. The project, funded by the National Science Foundation (Grant #SES-8512007), took place at UCLA under the leadership of Georges Sabagh and Ivan Light, as Principal Investigators. Mehdi Bozorgmehr was the Project Director. I joined the project in 1986 as the Armenian Iranian Project Coordinator. Georges Sabagh was the heart and soul of the study. His knowledge of the Middle East and his clear vision for the project made it all possible. Ivan Light’s expertise in the field of entrepreneurship and immigration provided the theoretical backbone to the Iranian study. The successful completion of the project was primarily due to Mehdi Bozorgmehr’s persistence and hard work. Roger Waldinger’s passion for the field of immigration and his wealth of knowledge about the economic integration of immigrants inspired me to study this topic. Without the support of these great scholars, I couldn’t have completed this manuscript. As Project Coordinator, I experienced every phase of the study – questionnaire construction, translation of the questionnaire, sampling design, drawing the study sample, xiii

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Acknowledgements

training the interviewers, screening respondents, conducting in-person interviews, coding the questionnaire, creating the data set, and analyzing the data. During the data collection, one interviewer, Mr. Seboo Hovanessian, stood out as he went above and beyond the call of duty. Without his constant perseverance and dedication, we wouldn’t have had the success rate in completing the interviews and finishing the study in a timely manner. Writing a book requires countless hours of editing and proof reading. This book wouldn’t have come together without the meticulous reading of my colleague, Dr. Kathryn Atchison, and my husband, Dr. Shant Barmak. Shant read each chapter several times giving me constructive feedback. I couldn’t have done this without his loving support. My sister, Anita, has always inspired me to set high goals and work hard to reach them. I am ever so grateful to have her in my life for her encouragement and praise. My journey started with the love and support of my parents, Stella and George. They instilled in me the love of learning and were a constant support for me. This book is dedicated to the loving memory of my parents.

Preface

Writing this book and being involved in the Iranian Study was a personal journey. In the summer of 1977, a year prior to the Iranian Revolution, my parents decided to move to Los Angeles so my sister and I could continue our education in the U.S. At the time, my sister was 16 years old, about to enter her senior year of high school and prepare for college the following year. I was only 12, and although I was fluent in Armenian and Farsi, I had no knowledge of English. Until the Iranian Revolution started in late 1978, we believed our stay in the U.S. would be temporary. After the Revolution, for an Armenian – a Christian minority in Iran – returning to the newly established Islamic regime was not an option. Permanent residency in the U.S. became our only choice, and soon our focus shifted to getting my grandparents and close relatives to the U.S. My grandparents finally arrived to Los Angeles as refugees in 1981. We were all transplanted in a new country facing new challenges. Adjusting was difficult. My father would always joke that he studied the wrong language at the university – French instead of English! My sister and I continued our studies. As years went by and more Iranians migrated to Los Angeles, the transition to the new environment became easier. My parents became more active in the Armenian Iranian community as they were able to re-connect with family and friends who had also migrated from Iran. The immigration to the U.S. was a major turning point for our family. It was not a coincidence that I decided to study immigration and participate in the Iranian project at xv

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UCLA. Ever since our move, I was curious why we had chosen Los Angeles and not Washington D.C. or New York as my parents had contemplated settling in those cities. I became curious about the migration process – how did other Iranian families reunite? How did they adjust socially and economically? Why did they choose Los Angeles? I had so many questions and no answers. I began this work to answer these questions. After the passing of my parents, writing this book became even more critical. It is about the experiences of my parent’s generation. As first generation immigrants, they left Iran during uncertain times and started new lives thousands of miles away to provide better opportunities for their children. Just like 1978, today’s political climate, especially after 9/11, is even more tenuous and brings more attention to Iranian immigration to the U.S. This book is timely since it gives a background on how first generation Iranian immigrants entered into the U.S. labor market and the gap between their employment status in Iran and the U.S. My father was a successful Civil Engineer in Iran who had his own business. Entrepreneurship was an important part of his life in Iran but not in the U.S. The life stories of 557 Iranian male heads of households, just like my father, have been accumulated in this study to illuminate the Iranian experience of emigration to the U.S. three decades ago.

CHAPTER 1

Economic Capital, Human Capital or Social Capital?

INTRODUCTION Iranian migration to the United States began in the 1950’s. After the Iranian Revolution in 1978-79 Iranian immigration to the U.S. exploded with Los Angeles as the primary place of destination. This study documents the economic integration of Iranian immigrants in Los Angeles and examines its determinants by focusing on the role of immigrant network ties. Economic performance, the outcome measure, is conceptualized in two stages: initial, settlement stage and long-term, settled stage. The manuscript is divided into four main chapters where each chapter has a different dependent variable: length of time spent finding the first job (ch.3), shift in occupational status (ch.4), income (ch.5) and self-employment (ch.6). Chapter 2 describes the study design and methods, chapters 3 and 4 concentrate on the initial settlement stage, and chapters 5 and 6 focus on the settled stage. The U.S. Census, which is the most widely used and the largest data source for the foreign-born, does not contain data on network ties. The 1987-88 probability sample survey of 671 Iranian immigrants living in Los Angeles is used to study the effect of network ties on economic performance. This in-person questionnaire survey contains pre- and postmigration socioeconomic data, information about the migration process, and questions regarding the 1

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Iranian Immigrants in Los Angeles

types of help Iranian immigrants received and/or gave since their arrival to the U.S. This study borrows from the theory of social capital and social embeddedness, which was re-introduced to the field of economic sociology during the mid 1980’s (Bourdieu 1986; Granovetter 1985; Coleman 1988; Granovetter 1995) and applied to immigration studies in the mid 1990’s (Portes and Sensenbrenner 1993; Portes 1998; Portes 1995a, 1995b; Aguilera and Massey 2003; Waldinger and Lichter 2003; Giorgas 2000; Menjivar 2000). Having access to immigrant network ties does not necessarily mean that immigrants possess a high level of social capital. Social capital is a resource, which exists in the relations between individuals (Coleman 1988; Bourdieu 1986). As Portes (1998, 1995a) argued, "the resources themselves are not social capital, the concept refers instead to the individual's ability to mobilize them on demand" (Portes 1995a, p. 12). “The key concept is that social capital is not an individual characteristic or personality trait but a resource that resides in the networks and groups to which people belong” (Mouw 2006, p. 1). This study builds on this approach and measures social capital in terms of the extent to which immigrants have access to and are embedded in economic network ties. The general hypothesis of this study is that economic embeddedness affects how well immigrants perform in the labor market. HUMAN CAPITAL VS. SOCIAL CAPITAL According to the neoclassical economists, immigrants' economic success, which is often measured by their average earnings, is determined by their human capital characteristics, such as education, work experience and other labor-market related skills (Chiswick 1978, 1979; Borjas 1987). Human capital refers to skills and knowledge acquired by an individual. Chiswick (1978) who "pioneered the application of the concept of human capital to immigrant economic attainment" (see Portes 1995a, p. 23), argued that the longer immigrants stay in the U.S., the more likely they are to accumulate labor market related skills,

Economic Capital, Human Capital, or Social Capital

3

become fluent in English, and succeed economically (Chiswick 1978). "In an analysis of the earnings of immigrants, the number of years since migration is an important variable, and ignoring it would mask important differences between the native and the foreign born and among the foreign-born" (Chiswick 1978, p. 918). According to Chiswick (1979), the transferability of skills to the country of destination and "the self-selection of immigrants on the basis of innate ability and motivation for economic advancement" (1979, p. 358) are two important determinants of economic progress. When immigrants first arrive they have lower earnings than the native born with similar demographic characteristics because of the less than perfect transferability of skills. The disadvantage is greatest for refugees from countries with a different language and economy and least for economic migrants from countries with a language and economy similar to the destination. With the passage of time, however, immigrants acquire knowledge of the language and customs of the country of destination and adjust their skills and credentials to the new environment (Chiswick 1979, p. 358). Borjas (1987) built on this argument: "Recently, the focus has shifted from analyses of single cross-section data sets to studies of cohort or longitudinal data. The departure from these studies is the well-known fact that the analysis of a single cross-section of data cannot separately identify aging and cohort effects" (Borjas 1987, p. 531). For Borjas, aging effect refers to immigrants' acquisition of labor market related skills over time, whereas cohort effect refers to cohort differences in quality "caused by non-random return migration propensities and/or secular shifts in the skill mix of immigrants admitted to the United States" (Borjas 1987, p. 531). In both instances, aging and cohort effects refer to immigrants' individual characteristics. Sociologists have

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been dissatisfied with this approach (for a review, see Portes and Bach 1985, ch. 1). "Clearly, education, knowledge of English, and work experience are important factors affecting newcomers' employment prospects, but they do not suffice to fully explain occupational mobility and earnings (Portes 1995a, p. 23). Economists concentrate solely on the effects of individual skills and ignore the effects of the broader social structures. Sociologists view immigrants not simply as individuals, but "as members of groups and participants in broader social structures that affect in multiple ways their economic mobility" (Portes 1995a, p. 24). Every aspect of migration, decision to migrate, place of destination, and the settlement process, is network driven (Massey and Espinosa 1996; Portes 1995a; Tilly 1990; Boyd 1989; Light, Bhachu and Karageorgis 1993). Immigrants usually migrate into and settle in areas where co-ethnics have already established a community (see Portes and Rumbaut 1990, ch. 3). Moreover, "ethnic networks provide sources of information about outside employment, sources of jobs inside the community, and sources of credit and support for entrepreneurial ventures" (Portes and Rumbaut 1990, p. 88). To put it simply: networks migrate; ... By and large, the effective units of migration were (and are) neither individuals nor households but sets of people linked by acquaintance, kinship, and work experience who somehow incorporated American destinations into the mobility alternatives they considered when they reached critical decision points in their individual or collective lives. Longdistance migration entails many risks: to personal security, to comfort, to income, to the possibility of satisfying social relations. Where kinsmen, friends, neighbors, and work associates already have good contacts with possible destinations, reliance on established interpersonal networks for information minimizes and spreads the risks (Tilly 1990, p. 84).


5

"The subject of social networks is not new in international migration research" (Boyd 1989, p. 639). The field of economic sociology reintroduced the concepts of embeddedness and social capital (Granovetter 1985, 1990; Bourdieu 1986; Coleman 1988). Embeddedness questions the individualistic approaches to economic action and presumes that economic action is embedded in social relations. This theoretical framework has allowed immigration researchers to expand immigrant network theory and better explain how immigrant network ties affect immigrants' economic life (Portes and Sensenbrenner 1993; Portes 1995a; Portes 1998; Waldinger and Lichter 2003; Waldinger 1996; Aguilera and Massey 2003; Giorgas 2000). Social networks are among the most important types of structures in which economic transactions are embedded. These are sets of recurrent associations between groups of people linked by occupational, familial, cultural, or affective ties. Networks are important in economic life because they are sources for the acquisition of scarce means, such as capital and information, and because they simultaneously impose effective constraints on the unrestricted pursuit of personal gain (Portes 1995a, p. 8). EMBEDDEDNESS AND SOCIAL CAPITAL Most economists who follow the "new institutional economics" position argue that "behaviors and institutions previously interpreted as embedded in earlier societies, as well as in our own, can be better understood as resulting from the pursuit of self-interest by rational, more or less atomized individuals" (reviewed by Granovetter 1985, p. 482; see Williamson 1975). During the 1920s, some anthropologists, called the "formalists", agreed with this position and claimed, "even in tribal societies, economic behavior was sufficiently independent of social relations" (Granovetter 1985, p. 482).

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These two schools of thought exemplify a pure "markets" approach to human action. Granovetter (1985) disagreed with these approaches. He argued that since "most behavior is closely embedded in networks of interpersonal relations" (1985, p. 504), "economic action is (also) embedded in structure of social relations" (1985, p. 481). Granovetter borrowed this notion of embeddedness from the "substantivist" school of thought in anthropology, which was influenced by the works of Karl Polanyi (1944) and his associates (Polanyi, Arensberg and Pearson, 1957). Polanyi (1944) used the concept of embeddedness to illustrate the role of social forces in structuring precapitalist economies, but assumed that these forces would not operate in modern capitalist economies. By summarizing various findings, Granovetter (1985) illustrated that even in today's society, social expectations modify and even subvert the original intent of economic transactions. I assert that the level of embeddedness of economic behavior is lower in non-market societies than is claimed by substantivists and development theories, and it has changed less with "modernization" than they believe; but I argue also that this level has always been and continue to be more substantial then is allowed by formalists and economists (Granovetter 1985, pp. 482-483). According to Portes (1995a) "social capital is a product of embeddedness" (Portes 1995a, p. 13). Embeddedness is a general notion that questions the individualistic approaches to economic action, whereas social capital, with its distinct theoretical roots, is more specific. This concept was first introduced by Pierre Bourdieu (in French) and James Coleman (in English). Bourdieu (1986) differentiated between three types of capital: 1) Economic capital - "is immediately and directly convertible into money and may be institutionalized in the form of property rights" (Bourdieu 1986, p. 243). 2) Cultural capital - may be converted into economic capital under certain conditions and institutionalized in terms of educational qualifications.


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3) Social capital - is "made up of social obligations ("connections") which is convertible, in certain conditions, into economic capital and may be institutionalized in the form of a title of nobility" (Bourdieu 1986, p. 243). Bourdieu (1986) explained: Social capital is the aggregate of the actual and potential resources which are linked to possession of a durable network of more or less institutionalized relationships of mutual acquaintances and recognition - or in other words, to membership in a group - which provides each of its members with the backing of the collectivityowned capital, a "credential" which entitles them to credit, in the various senses of the word. The volume of the social capital possessed by a given agent thus depends on the size of the network of connections he can effectively mobilize and on the volume of the capital (economic, cultural or symbolic) possessed in his own right by each of those to whom he is connected (Bourdieu 1986, pp. 248-249). Like Bourdieu, Coleman (1988) defined social capital by its functions. For Coleman (1988) social capital differs from physical and human capital. Physical capital refers to tools, machines, other equipment and human capital refers to acquired skills and knowledge. According to Coleman, social capital "is not a single entity but a variety of different entities, with two elements in common: they all consist of some aspect of social structures, and they facilitate certain actions ... within the structure" (Coleman 1988, p. S98). Like physical and human capitals, social capital is a resource available to individuals to help them attain their economic or non-economic goals. But unlike human and physical capitals, social capital exists in the relations among individuals. For example, “the social capital of the family is the relations between children and parents” (Coleman 1988, p. S110). When explicating the concept of social capital, Coleman identified three forms:

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1) obligations and expectations, 2) information channels, and 3) social norms. He illustrated how these resources can be useful in attaining goals. In order to illustrate the usefulness of this concept, Coleman demonstrated how social capital in the family and in the community could create human capital in the example of high school graduation (see Coleman 1988). Influenced by Bourdieu and Coleman, Portes applied the concept of social capital to immigration studies. Following Bourdieu's definition of social capital, Portes (1995b) argued, "density of networks within an immigrant community increases social capital" (Portes 1995b, p. 258). According to Portes (1995a), social capital refers to the "capacity of individuals to command scarce resources by virtue of their membership in networks or broader social structures" (1995a, p. 13). These resources often include favors such as low- or free- interest loans, business or employment tips, price discounts, business advice, or other favors in economic transactions and social capital refers to the individual's ability to mobilize them (Portes 1995a). Even though Coleman believed that social capital is created "when the relations among persons change in ways that facilitate action" (Coleman 1990, p. 304), he did not over-emphasize the instrumental aspect of social capital. Coleman recognized that "a given form of social capital that is valuable in facilitating certain actions may be useless or even harmful for others" (Coleman 1988, p. S98). Portes (1995a) emphasized this point: It is important not to lose sight of the fact that the same social dynamics that produce altruistic gifts and concessionary favors can also constrain individual economic pursuits. Sociability is a twoway street and the resources gained from fellow community members and social network members, although in appearance "free" do carry hidden costs (Portes 1995a, p. 14). Portes and Sensenbrenner (1993), using empirical examples from the immigration literature, explored "the different forms in which social structures can affect


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economic action" (1993, p. 1346). They discussed four types of social capital: value introjections, bounded solidarity, reciprocity and enforceable trust. The use of examples from the immigration literature is not surprising since "immigrant communities represent one of the clearest examples of the bearing contextual factors can have on individual economic action" (Portes and Sensenbrenner 1993, p. 1322). In most immigration studies, specific measures of social capital and embeddedness are lacking (Portes 1995b, p. 262). “As a number of recent authors have pointed out, there is a considerable amount of ambiguity regarding the precise definition of social capital” (see Mouw 2006, p. 1). The Iranian study defines measures of social capital in terms of the extent to which immigrants give and/or receive economic and non-economic assistance, and distinguishes whether immigrants have access to economic/noneconomic network ties and whether or not they actually utilize these resources. By assuming immigrant networks include family members and close friends, the network theory does not discuss the nature of immigrant ties. In contrast, Granovetter's (1974, 1995) "strength of tie" hypothesis stresses the structural advantage of weak over strong ties. Weak ties have access to a wide range of choices that strong ties do not have access to (Granovetter 1974, 1995). Immigrants initially rely on strong ties (e.g. family ties), but later as they settle, their pool of weak ties increases and gives them access to different types of network ties. Immigrants who rely on weak ties might access better paying and more prestigious jobs. In this study, the strength of tie hypothesis is examined by considering the tie effect during the initial phase as well as the settled stages. IRANIAN IMMIGRATION TO THE U.S. Prior to 1950, the INS official data did not identify Iranians since their numbers were negligible (Bozorgmehr and Sabagh 1988; Lorentz and Wertime 1980). The period between 1950 and before the Iranian Revolution (1950-

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1977) marks the first immigration wave. According to INS data, in the 1960’s new Iranian immigrants arrived on average 369 per year increasing to approximately 1,253 per a year and reaching 2,351 in 1977. For non-immigrants, which included students and visitors, there was a sharp increase between 1950’s and 1970’s (Bozorgmehr and Sabagh 1988). During this phase, Migration to the U.S. was triggered by Iran’s gradually recovering economy and U.S. involvement in Iran. During WWII the Iranian economy had deteriorated due to foreign occupation and internal political instability. Iran’s economic condition further suffered in the course of the oil nationalization movement of 1951-1953. The West retaliated by boycotting Iranian oil, thereby drastically reducing the oil revenues and, as a result, the supply of foreign exchange. After the Shah was restored to power in 1953, American aid and the resumption of oil revenues rescued the economy and insured the Shah’s survival in those critical years. Thus began a period of direct U.S. influence in Iran. … The Iranian government embarked, as early as the 1960’s, on an industrialization program with an emphasis on the use of modern technology. Yet, Iran lacked the higher educational institutions to train enough skilled workers. An inevitable consequence of this policy was that it served as a major incentive for many Iranian students to study abroad, preferably in advanced industrial countries such as the United States (Bozorgmehr and Sabagh 1988, p.8-9). During the 1970’s while Iran was enjoying economic boom and explosion of oil revenues, there was not much incentive for Iranians to leave Iran. On the other hand, the U.S. economy in the 1970’s was struggling.- not much of an incentive for Iranian to migrate to the U.S. During this initial phase Iranian immigration to the U.S. was temporary where most Iranians who came to the U.S. were students


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pursuing higher education with the aspirations to return home for business opportunities. The U.S. was the preferred destination, “partly because of its close ties to Iran (at the time) but also because of the availability of educational and job opportunities in American society” (Bozorgmehr 1992, p. 127). As a result of the earlier interventionist role of Britain in Iran, and subsequently the increasing presence of Americans, the English language had become the standard foreign language taught in Iranian high schools. Familiarity with English directed high school graduates towards English speaking countries in pursuit of higher education. The choice of destination was narrowed to advanced industrial countries because Iranian students were mostly interested in technical education such as engineering to prepare for the rapidly industrializing Iranian economy (Bozorgmehr 1992, p. 127-28). The Iranian Revolution (1978-79), which marks the second phase of the Iranian immigration to the U.S., completely changed the migration pattern and the socioeconomic profile of Iranian immigration to the U.S. The political climate drastically changed during this period especially during the U.S. Embassy take over and the Iran Hostage Crisis in 1979. The departure of the Shah of Iran, Mohammad Rezah Pahlavi and the establishment of the Islamic regime solidified the permanency of the new era that took place so rapidly. These massive changes created political instability and caused much fear and uncertainty for many Iranians living in Iran and abroad. The political turmoil continued with the onset of the Iran-Iraq War in 1980 killing countless numbers of soldiers and civilians in the eight-year war. This continued political unrest forced many religious minorities to immigrate to the U.S. as refugees and asylees (Bozorgmehr 2000). Before the Revolution, Iranian students emigrated for educational reasons. After the Revolution many of the earlier students stayed in the U.S. and many new

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immigrants arrived as exiles or political refugees. “These exiles were disproportionately members of religious minorities who experienced, or feared, persecution in the Islamic Republic of Iran” (Bozorgmehr 2000, p.715). Since the mid 1990’s the Iranian immigration to the U.S. has slowed down. After 9/11 the acquisition of permanent residency has become harder and much more tedious for all Middle Easterners perhaps discouraging many to migrate to the U.S. Although traveling between Iran and the U.S. is easier today, the political climate between the two countries is very tenuous and speculative. CHARACTERISTICS OF IRANIAN IMMIGRANTS The 1990 U.S. Census enumerated about 285,000 foreignborn Iranians in the U.S., the largest number of Iranians outside of Turkey and Iran (Bozorgmehr 1995). The Census indicated that Los Angeles had the largest concentration of Iranian immigrants in the U.S. In 1990, approximately 35% (100,000) of the total U.S. Iranian population resided in the Los Angeles region, which includes the five counties (LA, San Bernandino, Ventura, Riverside and Orange). The Iranian population (including new immigrants and non-immigrants) in the Los Angeles region increased substantially between 1970 and 1990. During the 1970-80 period, the Iranian population grew six-fold and during the 1980-90 period it doubled (Bozorgmehr, Der-Martirosian and Sabagh 1996). The comparable number enumerated by the 2000 U.S. Census using the 5% PUMS data was about 338,000 Iran born and those of Iranian ancestry born elsewhere. This figure indicates less than a 5% increase since 1990. According to the 2000 U.S. Census, over half of Iranian immigrants (55%) lived in California, with Los Angeles still having the largest concentration of Iranian immigrants in California and the U.S. (see Bozorgmehr 2007). Iranian immigrants are one of the most distinctive groups in the U.S. They "constitute one of the most numerous new immigrant groups from the Middle East, and one of the highest status foreign-born groups in the United


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States" (Bozorgmehr and Sabagh 1988, p. 5). Many Iranian immigrants are highly educated and hold professional specialty and managerial positions (Bozorgmehr, DerMartirosian and Sabagh 1996; Bozorgmehr and Sabagh 1988). In 1980, the educational achievement of Iranians in the U.S. "(was) not only substantially higher than the educational level in urban Iran in 1976, but (was) also higher than that of natives and recently arrived immigrants in the United States" (Bozorgmehr and Sabagh 1988, p. 34). According to the 1990 U.S. Census, compared to other immigrant groups, "among males, Iranians (had) a much higher level of education than any group (65% with four or more years of college)" (Bozorgmehr, Der-Martirosian and Sabagh 1996 p.357) The Census also indicated that more than half of Iranian males held managerial and professional specialty positions (Bozorgmehr, Der-Martirosian and Sabagh 1996). In addition to their high socioeconomic status, Iranian immigrants are highly entrepreneurial (Light, Sabagh, Bozorgmehr and Der-Martirosian 1993; Light, Sabagh, Bozorgmehr and Der-Martirosian 1994), an important indicator of economic self-reliance and a common means for upward mobility. Iranians are not unique since other immigrant groups like Taiwanese, Asian Indians, and Israelis, have high status occupations (see Cheng and Yang 1996). Also, other immigrant groups, like Cubans, Koreans and Chinese, have high self-employment rates (Light and Bonacich 1988; Portes and Bach 1985; Cheng and Yang 1996; Min 1993). But what is distinctive about Iranians is the overlap between these two modes of economic incorporation: Iranian immigrants are professionals and high skilled entrepreneurs (see Bozorgmehr, DerMartirosian and Sabagh 1996). According to Portes and Rumbaut (1990) professional immigrants, compared to non-professionals, rely less on their networks and more on their skills and qualifications. Since Iranian immigrants are high skilled professionals and entrepreneurs, it is even more important to investigate the extent to which Iranian immigrants rely on co-ethnic networks ties for economic advancement.

14


Another distinctive characteristic of Iranian immigrants is the disproportionate over representation of ethnoreligious minorities, such as Bahais, Armenians, and Jews within this population (Bozorgmehr, Sabagh and DerMartirosian 1993; Bozorgmehr 1992). The Iranian ethnic economy is organized along these subgroups. "The Iranians in Los Angeles operated four distinctive ethnic economies, not one" (Light, Sabagh, Bozorgmehr and Der-Martirosian 1993). Light, Sabagh, Bozorgmehr and Der-Martirosian (1993) called this "internal ethnicity" in the ethnic economy, in which "each ethno-religious subgroup had its own ethnic economy, and these separate economies were only weakly tied to an encompassing Iranian ethnic economy" (Light, Sabagh, Bozorgmehr and DerMartirosian 1993, p. 581). Before the Islamic Revolution, approximately 2% of Iran's population constituted various minority groups (Bozorgmehr 1992), whereas in Los Angeles Iranian ethnoreligious groups comprise a much larger proportion of the total Iranian population (Light, Sabagh, Bozorgmehr and Der-Martirosian 1993). Muslims, Armenians, Jews and Bahais are the four largest Iranian subgroups in Los Angeles (Light, Sabagh, Bozorgmehr and Der-Martirosian 1993; Bozorgmehr 1992). In Iran only Jews and Armenians are officially recognized as minority groups (Bozorgmehr 1992). In addition to their minority status, these two groups have a long entrepreneurial tradition and have occupied middleman minority positions in Iran (Bozorgmehr 1992). The high self-employment rate among Iranians in Los Angeles is partly due to the presence of these minority groups. In addition to their entrepreneurial skills, these groups have had a long history of established communities in Iran. Once they arrived in the U.S., they developed an economic advantage over the Muslim majority since they could tap into an established community ties and networks. Furthermore, Armenian and Jewish Iranians in the U.S. are considered twice migrants or minorities, whereas Muslim Iranians are first-time migrants in the U.S. (see Espiritu 1989, and Bhachu 1993, for detailed discussions on twice migrants).


15

Survey studies of Iranian immigrants in the U.S. are rare. The 1987-88 Iranian survey is one of the few that provides detailed pre- and postmigration data. In addition to Muslim Iranians, data on economic and social characteristics were collected from three other Iranian ethno-religious groups: Jews, Bahais and Armenians. The next chapter describes in detail the study design and the sample characteristics of the 1987-88 Iranian survey.


CHAPTER 2

The Iranian Survey

STUDY DESIGN This chapter describes the study design for the 1987-88 probability sample survey of Iranian immigrant heads of households, and discusses the study variables and measures used in subsequent chapters. This chapter also compares the study sample characteristics with the 1990 PUMS (Public Use Micro data Sample) U.S. Census to illustrate the representativeness of the survey sample. Since the U.S. Census does not collect data on religion, Jewish, Bahai and Muslim Iranian subgroups could not be identified. However, using the 1990 U.S. Census ancestry data, this chapter presents census data on Armenian Iranians and compares the socioeconomic characteristics between the two data sources. According to the 1990 PUMS data, Armenian Iranians – a Christian minority group - comprised 25% of the total Iranian immigrant population in the U.S. This is a large percentage since all ethno-religious minority groups constituted only 2% of the Iranian population in Iran before the Islamic Revolution (Bozorgmehr 1992). To ensure that a minimum number of respondents from each of the three ethno-religious minority subgroups were included in the study, and address the problem of unlisted telephone numbers, Jewish, Bahai and Armenian Iranian community 17

18


lists were used to supplement the main sampling frame of eight LA County white-page telephone directories. From each telephone directory, 200 pages were randomly selected after a computer-generated list of random numbers had scrambled the numbers of the telephone directory pages. Persian-sounding names were identified in each selected page for all eight telephone directories. The vast majority of Persian surnames are distinctive and given the recency of their arrival in 1987, there were few surname changes in this population (for detailed description of the study design, see Bozorgmehr 1992). Only two telephone directories (Northwestern and Western) – which encompassed the highest concentration of Armenian Iranians and the lowest concentration of other Armenians - were used to identify Armenian sounding names. Since Armenian Iranian surnames are indistinguishable from other Armenian names (such as Lebanese Armenians and Armenians from Armenia) all Armenians names were extracted first and later screened by telephone. This method yielded 1,714 Persian names from the eight telephone directories and 1,059 Armenian names from the two directories. To exclude non-Iranian names, a separate list of uncertain names was created and this list was checked against a 1979 Immigration and Naturalization Service master list of 43,271 Iranian surnames. Given the low numbers of uncertain names, the list was later omitted from the final sampling frame. From the Armenian and Jewish community lists 500 names were selected (250 each) and 150 from the Bahai list. Prior to selecting the names, duplicates were dropped from the community lists. A total of 390 non-Armenian Iranians and 126 Armenian Iranians were interviewed from telephone lists. From the community lists, 69 Armenians, 45 Bahais and 39 Jewish Iranians were interviewed. The total sample of 671 Iranian householders includes 2 additional Muslim Iranians from the community lists. A total of 671 Iranian householders - 556 males and 115 females - were interviewed from August 1987 through March 1988 with a 30% refusal rate. Approximately 77%

The Iranian Survey

19

of the respondents' names were derived from the telephone directories and the remaining from Armenian, Jewish and Bahai community lists. Persian and Armenian speaking interviewers conducted in-person interviews, with 201 Muslim, 195 Armenian, 188 Jewish and 87 Bahai householders (Bozorgmehr and Sabagh 1989). SURVEY QUESTIONNAIRE Containing 172 items, the survey questionnaire was first developed in English and later translated into Persian and Armenian. Most Muslim, Jewish and Bahai respondents preferred to be interviewed in Persian rather than English. Among Armenian Iranians, the majority preferred Armenian rather than Persian or English. On average, the in-person interviews took one and a half hours. During these in-depth, structured interviews, Iranian heads of households answered questions on pre-migration characteristics, migration experience, and post-migration social and economic activities. In addition to answering questions regarding their own experiences, respondents answered questions regarding the household structure, expenses and income. Respondents were specifically instructed to answer more detailed questions regarding their own experiences and if married their spouses' employment status in Iran and the U.S., ethnicity of spouse, ethnicity of spouse's close friends, current residence of spouse's close and distant relatives, and spouse's social origins (i.e., parents' educational and occupational background). Overall, the survey generated over 940 variables and not all variables were used for this manuscript. The Iranian data set contains abundant information that includes both individual and household variables. Appendices A through G list brief description of the variables used in this study. Each Appendix is organized according to a major topic (e.g., Household Roster or Migration Experience). Appendix H lists the questions that were asked in the survey. The variable numbers listed in Appendices A thru G can be matched to the question

20


numbers listed in Appendix H for the exact wording of the survey questions. Appendix A lists the household roster that provides an overview of the demographic and socioeconomic profiles of all household members. The household head reported the employment status, educational background, and demographic characteristics of all household members. Appendix B lists migration variables, such as year of arrival, whether they arrived with relatives and/or friends, whether relatives and/or friends were living in Los Angeles at the time of arrival, sources of information before arriving to the U.S., and type of help received from relatives and friends at the time of arrival. In addition to these variables, respondents were also asked whether they received any organizational help when migrating to the U.S. They were also asked to indicate the visa status under which they entered the U.S., and whether or not they were permanent residents or citizens. Regarding employment status, respondents were asked to indicate whether their first job in the U.S. differed from their current job. If so, they reported the characteristics of the first job, such as type of work, industry and class of worker. During the interviews, respondents were asked to specify whether they had received any help to locate their first job (see Appendix C). For current employment, detailed questions were asked regarding the year they started working, type of work, industry and whether selfemployed or wage/salary (see Appendix D). If selfemployed, separate sets of questions were asked about the reasons for going into self-employment, whether incorporated or unincorporated, ethnicity of partners, employees and clients, and number of paid employees. For wage and salary workers, respondents were asked to report the ethnicity of supervisors and co-workers. For current employment, the network data are more detailed and extensive. Respondents were asked to indicate whether they gave and/or received help on a list of economic and non-economic items. They were also asked to rank the order of who helped them or whom they helped on these lists of items (see Appendix E).

The Iranian Survey

21

In addition to first and current employment experiences in the U.S., respondents were also asked to indicate whether they were employed full-time before migrating to the U.S. If so, they indicated the type of industry, occupation, and class of worker before leaving Iran. The survey asked respondents to indicate whether their first full-time job in Iran was the same as their last job before leaving Iran (see Appendix F). For the household head, the survey questionnaire asked employment information for four points in time: first job in Iran, last job in Iran, first and current jobs in the U.S. For the spouse, the survey included employment information for two points in time: last job in Iran and current job in the U.S. The survey also gathered a limited amount of economic network data about the spouse (see Appendix G). SURVEY VS. CENSUS To assess the representativeness of the Iranian survey sample, the socioeconomic characteristics of the Iranian sample was compared to the 1990 U.S. Census PUMS 5% sample. Since the Iranian survey was conducted in 198788, the 1990 census data was the obvious choice for comparison. To create a comparable match, Iran-born householders and spouses who had migrated before 198788 were selected from the 1990 census data. For Iranian men and women, there were only minor differences between the two samples when compared on level of education, employment status, and occupational and industrial distributions (see Tables 2.1 and 2.2). The two data sources differed in terms of self-employment rate. The self-employment rate for Iranian men was 59%; a figure, which is much higher than the 38%, reported in the 1990 Census data (Table 2.1). The self-employment rate for women was 26%, which is also higher than the 17% rate reported in the Census (Table 2.2). Nevertheless, the overall comparison indicated that the survey sample was representative of Iran-born householders and spouses living in Los Angeles who migrated before 1987.

22


Self-Employment Rates Design effect may be one possible reason for the discrepancy between the two self-employment rates. The 5% Census sample is based on a larger geographical base, and therefore, relies less on ethnically clustered areas. In contrast, the Iranian survey design targeted a specific immigrant group and included community lists, which may have inflated the number of Iranians living in ethnically clustered areas. Since immigrant entrepreneurship tends to occur near ethnically clustered neighborhoods, the Iranian survey sample might be over-represented in terms of selfemployment. Another possible explanation might be the oversampling of the minority groups especially the Jews since they have the highest rate of self-employment. According to the U.S. Census, 25% of all Iranians were of Armenian descent. Since Bahais, Jews and Muslims cannot be identified in the Census, there are no official data verifying their numbers. Hence, the determination of the sample size was based on this 25% census figure and the goal was to complete 200 interviews for each subgroup except for Bahais since they were the smallest Iranian subgroup in Los Angeles. These explanations are both plausible, but it is still puzzling that almost every other characteristic yields similar results in both the survey and the census samples. This brings us to the next possible explanation. The study questionnaire was constructed to include detailed questions regarding entrepreneurship, which might have prompted respondents to explain their employment situation in much greater detail. In fact, the questionnaire contained separate sets of questions for self-employed and wage/salary workers. If respondents indicated that they were currently self-employed, they answered thirteen additional questions regarding their business. If they indicated that they were wage/salary workers, they answered five other questions regarding their employment experience. Similarly, respondents answered different sets of questions depending upon whether they were self-employed in Iran.

The Iranian Survey

23

Unlike the survey questionnaire, the census identifies self-employed using limited amount of information - class of worker and self-employment income variables (Light and Rosenstein 1995). The census possibly underestimates the actual self-employment rate since it is not designed to gather detailed self-employment data. Another explanation for the census underestimation of self-employment is offered by Min (Forthcoming) where he explains, immigrants are more likely than natives to hold two jobs and “when a person has two jobs, one through employment and the other through self-employment, he/she may not report the self-employed job” in the census (Min Forthcoming, Ch. 4). The first two explanations suggest that the Iranian survey may have overestimated the self-employment rate, whereas the second explanation suggests that the census may have underestimated the Iranian self-employment rate. A combination of these explanations probably explains the discrepancy between the survey and census selfemployment rates. Armenian Iranians in the U.S. Census Since only one subgroup - Armenian Iranians - could be identified from the U.S. Census, Tables 2.3 and 2.4 compare survey and census data on Armenian-Iranian men and women. Once again, the percent self-employed was higher for the survey sample when compared to the census (45% versus 36%, see Table 2.3). This discrepancy was smaller for Armenian Iranians when compared to the overall sample (59% versus 38%, see Table 2.1). In addition to the over-representation of the self-employed, Armenian-Iranian male professionals were also overrepresented in the survey, while those in technical or sales occupations are under-represented (Table 2.3). For Armenian-Iranian women, the percents for each of the characteristics (presented in Table 2.4) were almost identical, except for the occupational distribution. The Armenian-Iranian female sample was slightly overrepresented in managerial/executive occupations and

24


under-represented in service occupations. In addition to having a representative Iranian sample, these data illustrated that at the subgroup level, the Armenian-Iranian sub-sample was also representative of the ArmenianIranian population in Los Angeles County. MEN OR WOMEN Given the budgetary restrictions, interviewing both heads and spouses from each household would have cut the survey sample size in half. Instead, the Iranian survey interviewed household heads where the respondent, just as in the U.S. Census, was the informant. If respondents answered the same number of questions for themselves as well as for their spouses, the questionnaire would have been twice as long. With 172 questions, the survey questionnaire was already long. Expanding it any further would have discouraged some respondents from participating in the study. Instead, if married, respondents were asked to answer a limited number of questions regarding the social and economic activities of their spouses. Among the 556 male householders, over three-fourths (n=462) were married at the time of the interview. And among the 115 female householders less than half (n=50) were married. Accordingly, the survey sample included 606 males (556 male heads of households and 50 male spouses), and 577 females (462 female spouses and 115 female heads of households). On the surface, given the equal number of males and females, it would seem reasonable to conduct comparable sets of analyses for both genders. Unfortunately, since only limited amount of spouse information was collected during the Iranian study, comparable analyses cannot be conducted for both household heads and spouses. Moreover, since the number of employed Iranian women heads of household was rather small (n=66), separate multivariate statistical analysis for females would be meaningless. Therefore in subsequent chapters, the data analyses are based on 556 Iranian male heads of households.

The Iranian Survey

25

STUDY VARIABLES AND MEASURES Dependent Variables In this study, various statistical methods are used to examine the effects of network ties on the economic integration of Iranian immigrant men living in Los Angeles. Each chapter has a different dependent variable For the purposes of this study, four different measures of economic integration are used. In chapter 3, the dependent variable is length of time spent before starting the first job. In most studies, this variable is measured in number of days, weeks or months spent looking for employment. In the case of the Iranian study, such data are lacking. Survey respondents were asked to indicate in what year they started working. The time elapsed is constructed by subtracting year started working from year of arrival to the U.S. In chapter 4, the dependent variable is shift in occupational status. For the Iranian survey, occupational and industrial data was coded using the 1980 U.S. Census occupational and industrial three-digit codes. The most serious problem in using the census-coding scheme was that self-employed and managers of self-owned businesses received a code of 243 or 019, respectively. "Unfortunately, the (1980 and 1990) U.S. Census occupational coding procedure does not discriminate between the different types of self-employment. For example, a grocery store owner and a major importer and exporter both receive the same code of 243” (Bozorgmehr 1992, p. 66). As such, when examining occupational status shifts between Iran and the U.S., the self-employed were excluded from the analysis since including the selfemployed would have inflated the "no-status-change" category. The dependent variable for chapter 5 is income. When developing the Iranian questionnaire, the study researchers were aware of the cultural norms with regards to selfdisclosure of income/earnings. In the 1987-88 Iranian survey, the individual earnings question was left out

26


fearing most respondents would refuse to answer this question. Instead respondents were asked to report their household income. In addition to this question, they were also asked to indicate the source of their household income. For the purposes of this study, the individual income variable was constructed by selecting male respondents who had marked head of household's income as primary source of household income. The dependent variable for chapter 6 is class of worker - self-employed versus wage/salary worker. This dependent variable was re-coded using the closed-ended question: "Are you: (1) working for a salary, wage, or commission for a private company, or (2) working for the federal, state, or local government, or (3) working in own business or profession which is: proprietorship not incorporated, or (4) partnership not incorporated or (5) corporation. Response categories 3, 4 and 5 were collapsed into selfemployed, and responses 1 and 2 were collapsed into wage/salary workers. Independent Variables The independent variables vary between chapters. Since chapters 3 and 4 focus on the initial settlement phase, the independent variables capture the effects of pre-migration characteristics. In these chapters, education is the highestlevel completed in Iran, knowledge of English is upon arrival, and work experience is in Iran. In chapters 5 and 6, the independent variables capture the effects of postmigration experiences after a few years of U.S. residence. The corresponding independent variables for chapters 5 and 6 are: highest level of education completed (anywhere), knowledge of English at the time of the interview, and years of work experience in the U.S. Except for age, all other control variables: marital status, period of immigration, and subgroup (Armenian, Bahai, Jewish and Muslim), remain the same in all four chapters. In chapters 3 and 4, age at immigration is used in the analysis, whereas

The Iranian Survey

27

in chapters 5 and 6, age at the time of the interview was entered in the analysis. The network variables vary between the two sets of chapters. In chapters 3 and 4, two network variables are included in the analyses. The first variable is the "general" economic help variable. Here respondents were asked to indicate the types of help that they received upon arrival economic and non-economic types of help. Economic items included: loan of money, finding a job, and identifying a business opportunity. Non-economic items included: free housing and meals, paid housing and meals, locating a place to live, and transportation. In addition to these variables, a "specific" network variable was also constructed where respondents answered whether they received any help finding the first job in the U.S., and specified who helped them to get this job. For chapters 5 and 6, two different network variables were constructed based on a list of economic and noneconomic items. Iranian respondents were asked to indicate whether they gave or received help on a list of items. Noneconomic items included: child or health care, housework, match-making, personal counseling, club or organizational referrals, moving a residence, transportation, meals, shopping, food, medical or dental referrals, consumer advice, and providing free housing. Economic items included: finding a job or business, referrals and references, professional information and advice, transportation to work, loans, discounts, legal, tax, or business advice, translation, employee or customer relations, free labor, goods or equipment. Respondents were also asked to indicate their relationship to people who helped them and whom they helped on these lists of economic and noneconomic items. The next chapter starts the data analysis for the first economic measure – timing of first job in the U.S.

Table 2.1 - Socioeconomic Characteristics of Iranian Males, LA County 1987-88 Survey

1990 PUMS

BA/BS degree or higher Employed Self-employed

66% 89% 59%

59% 84% 38%

Occupational Distribution: Managerial & executives Professional specialty Technical, sales & admin support Service Precision/crafts Operatives

18% 28% 40% 2% 8% 3%

22% 24% 32% 2% 13% 7%

Industrial Distribution: Construction Manufacturing Transportation/Communications Wholesale & retail trade Finance, insurance & real estate Business repair Professional services Agriculture, mining & public administration N

11% 17% 5% 27% 7% 13% 17% 3%

10% 15% 5% 29% 9% 10% 18% 3%

607

19,079

Data Sources: The 1987-88 Iranian Survey in Los Angeles, and U.S. Census Public Use Micro Data 5% Sample (PUMS), 1990

28

Table 2.2 - Socioeconomic Characteristics of Iranian Females, LA County 1987-88 Survey

1990 PUMS


32% 39% 26%

32% 47% 17%

Occupational Distribution: Managerial & executives Professional specialty Technical, sales & admin support Service Crafts/crafts Operatives

12% 20% 49% 10% 5% 4%

17% 19% 44% 13% 4% 3%

Industrial Distribution: Manufacturing Transportation/Communications Wholesale & retail trade Finance, insurance & real estate Business repair Professional services Agriculture, mining & public administration N

8% 3% 25% 19% 17% 26% 2%

7% 2% 26% 18% 15% 27% 5%

577

14,301

Data Sources: see Table 2.1

29

Table 2.3 - Socioeconomic Characteristics of Armenian Iranian Males, LA County 1987-88 Survey

1990 PUMS


35% 74% 45%

36% 77% 36%


25% 21% 21% 3% 22% 8%

23% 13% 27% 3% 25% 9%

Industrial Distribution: Construction Manufacturing Transportation/Communications Wholesale & retail trade Finance, insurance & real estate Business repair Professional services Agriculture, mining & public administration N

13% 19% 5% 19% 8% 17% 13% 6%

17% 15% 5% 23% 9% 12% 15% 4%

165

3,851


30

Table 2.4 - Socioeconomic Characteristics of Armenian Iranian Females, LA County 1987-88 Survey

1990 PUMS


20% 41% 14%

21% 42% 15%


19% 11% 50% 8% 4% 8%

9% 15% 54% 14% 5% 3%

Industrial Distribution: Manufacturing Transportation/Communications Wholesale & retail trade Finance, insurance & real estate Business repair Professional services Agriculture, mining & public administration N

11% 2% 19% 32% 18% 15% 3%

6% 2% 20% 26% 14% 25% 7%

182

3,641


31


CHAPTER 3

Timing of First Job

HUMAN CAPITAL To assess the economic attainment levels of immigrants, neoclassical economists often use cross-sectional U.S. Census data, mostly comparing the economic achievement of immigrants with that of the native-born for different immigration cohorts (see Borjas 1987, 1989; Chiswick 1978). They argue that socio-demographic variables such as education, labor market experience, age, marital status, and years since migration, are important predictors of how well immigrants do economically (Chiswick 1982, 1978; Borjas 1987). The returns on human capital characteristics for the native-born, as well as for the foreign-born, indicate that even though immigrants initially earn less than the native-born, after several years most immigrants' earnings equal, and in some cases, even exceed that of the nativeborn (Chiswick 1978). This perspective explains immigrants' labor market experience in terms of individual human capital. Since the 1970’s, sociological and historical studies have challenged this individualistic approach (for review see Portes and Bach 1985; also see Portes 1995). Factors beyond individual skills influence achievements of immigrant group members (Morawska 1990). These factors vary from structural determinants such as time, location, economic, and political environment to collectivist determinants which are socially embedded as opposed to individualistic strategies (Morawska 1990). 33

34


Recent writings in economic sociology and immigration studies emphasize that immigrant networks significantly shape immigrants' economic experience (Mouw 2006; Giorgas 2000; Portes 1998; Portes 1995; Boyd 1989; Portes and Sensennbrenner 1993; Massey and Espinosa 1996). In explaining how immigrants integrate into the U.S. labor market, one needs to consider individual as well as social determinants. In this chapter, in addition to human capital explanatory variables such as education, premigration labor market experience and English proficiency, network variables will be included measuring the extent to which Iranian immigrants mobilized immigrant network ties and received economic help. INITIAL SETTLEMENT Most quantitative studies assessing U.S. immigrants' economic behavior use census data. Even with human capital variables, such as education, the census contains limited information. It is almost impossible to measure the effects of pre-migration characteristics, even though in 1978, Chiswick indirectly estimated pre- and postmigration years of schooling and illustrated the significant effect of each variable on immigrants' earnings. Nevertheless, the census data can only be stretched so far. In addition to these shortcomings, the census does not allow one to examine immigrants' initial economic experience. One can only analyze this experience by collecting data on immigrants' first employment immediately after arriving to the U.S. Such data are not available in the census. Finally, using the census, one cannot ascertain how quickly immigrants find employment. When using the census data, one extracts the most commonly measured dependent variables - income and employment status. Time spent finding the first job is an economic outcome measure not often used but an important one to consider. Immigrants' initial economic experience in the new labor market can be better understood if one examines how quickly immigrants find employment. Immigrants' labor

Timing of First Job

35

market experiences are more favorable when they encounter shorter unemployment. By using the Iranian data set, and by examining whether Iranian immigrants found employment within first year of arrival, this chapter evaluates Iranian immigrants' labor market experience upon their arrival to the U.S. IMMIGRANT NETWORKS Every aspect of the migration process, including the decision to migrate or to stay, determination of the place of destination, and the adjustment process, are all influenced by kinship and co-ethnic networks in which immigrants participate (Light, Bhachu and Karageorgis 1993; Massey 1988; Morawska 1990; Hugo 1981; Boyd 1989). The role of immigrant networks as a determining factor promoting international migration has been studied extensively (see Massey, Alarcon, Durand and Gonzalez 1987; Mines 1984; Reichert and Massey 1979; White 1970). Terms such as "auspices of migration" - introduced by Tilly and Brown (1967) - and "migration chains" - introduced by McDonald and McDonald (1964) - all refer to the network ties established between sending and receiving communities facilitating the migration process. For Tilly and Brown (1967) auspices of migration were the "social structures, which establish relationships between the migrant and the receiving country before he moves," (1967, p. 142). Auspices of migration can range from kinship to such types as work related or organizationally arranged. McDonald and McDonald (1964) discussed two extreme possibilities: chain migration and impersonally organized migration. Chain migration was defined as "that movement in which prospective migrants learn of opportunities, are provided with transportation, and have initial accommodation and employment arranged by means of primary social relationships with previous migrants" (McDonald and McDonald 1964, p. 82). Impersonally organized migration was "conceived as movement based on impersonal recruitment and assistance" (McDonald and McDonald

36


1964, p. 82). Although recent writings no longer use terms such as "auspices of migration" and "chain migration", most immigration studies still place great emphasis on family, kinship, and friendship-based network ties (Portes 1998; Boyd 1989; Light, Bhachu and Karageorgis 1993; Portes 1995; Massey and Espinosa 1996). Migration networks are "sets of interpersonal ties that link migrants, former migrants, non-migrants in origin and destination areas through the bonds of kinship, friendship, and shared community origin" (Massey 1988, p. 396). During the initial phase, "international migration may originate in structural changes within sending and receiving societies, however, ... once begun, this migration eventually develops a social infrastructure that enables movement on a mass basis" (Massey 1988, p. 396). In 1990, Massey labeled this process "the cumulative causation of migration." Once set in motion, migrations create networks, which produce a self-sustaining process of promoting more migration. Borrowing from even more recent theoretical developments, Massey and Espinosa (1996) wrote, Social capital theory, posits a direct connection between networks and the costs and benefits of migration, and it emphasizes the non-recursive nature of relationship between international movement and network formation. Non-migrants are hypothesized to draw on the social capital embedded in ties to migrants to lower their costs and risks of movement and raise their benefits of U.S. employment (Massey and Espinosa 1996, p. 14). Studies of immigrants' integration have also documented the significant role networks play during the adjustment period. "Settlement and integration processes are influenced by kin and friendship ties" (Boyd 1989, p. 651). Personal ties provide wide range of assistance, making it easier for immigrants to find housing, employment, protection and companionship (Light, Bhachu and Karageorgis 1993; Lin and Dumin 1986; Massey, Alarcon, Durand and Gonzalez 1987; Boyd 1989;

Timing of First Job

37

Cornelius 1982). Immigrant networks facilitate the process of adjusting to a new way of life, and as they grow, these networks increase their efficiency, "thus maximally facilitating the introduction of new immigrant newcomers into them" (Light, Bhachu and Karageorgis 1993, p. 28). In reviewing this network literature, one should note that even when immigrants arrive with family members and/or friends, there are no guarantees that they will tap into these kinship or co-ethnic ties and receive economic help. Immigrants who arrive under the auspices of kinship have access to immigrant networks, but this does not mean that they will mobilize these resources. One way to conceptualize this is to consider the auspices of kinship as social structures that help generate social capital embedded in personal ties. Whether immigrants actually mobilize these social resources is a separate but an interrelated concept. Following this argument, the first hypothesis states: Network Hypothesis: Immigrants who mobilize economic network ties upon arrival find employment faster. In order to test this hypothesis, it is important to distinguish between whether immigrants arrive alone or with relatives and/or friends, and whether immigrants actually receive help from family members and/or coethnic friends. The first item refers to auspices of migration and the second refers to immigrant's ability to mobilize network ties and tap into these resources. To test this hypothesis, it is also important to further distinguish the types of help received from family and friends. Immigrants can obtain all types of help, ranging from finding employment to receiving free housing. The hypothesis specifically states economic network ties, which refers to the extent to which Iranian immigrants received specific economic assistance, ranging from locating a job to obtaining a business loan or advice. In the 1987-88 Iranian survey study, respondents were asked to indicate the types of help that they received when they arrived to the U.S. The types include: free housing and

38


meals, paid housing and meals, locating a place to live, transportation, loan of money, finding a job, and identifying a business opportunity. The last three items are components of the economic help variable and the rest of the items are included under the non-economic help heading. In fact, among the male sample, 12% indicated receiving economic help whereas half of the sample (51%) indicated receiving non-economic help. Thus, it is important to distinguish between these two concepts since non-economic network ties might not have a direct effect on economic outcomes. FIRST JOB IN THE U.S. Economic integration is best captured by longitudinal data. When lacking longitudinal data, researchers can determine economic integration through personal accounts of immigrants reporting their pre- and postmigration experiences. In the Iranian study, respondents were asked to report their job histories for four points in time: first job and last job in Iran, first and current job in the U.S. This chapter examines the determinants of time elapsed before finding the first job in the U.S. The next chapter examines the employment transition between Iran and U.S. by considering the shifts in occupational prestige scores between last occupation in Iran and first occupation in the U.S. Earnings, the most commonly used measure of economic success, capture only one aspect of immigrants' economic integration. By merely measuring immigrants' earnings at one point in time, one cannot possibly understand immigrants' economic experience. Instead, in this chapter, a proxy measuring the amount of time Iranian immigrants spent finding the first job is used as the dependent variable to better understand Iranian immigrants' initial labor market experience immediately after arriving in the U.S. Time elapsed before finding the first job is a measure not often used, but it is an important outcome measure to consider since the less time immigrants spend

Timing of First Job

39

looking for employment, the better economic situation they establish. In most studies, this variable is measured in terms of the number of days, weeks, or months that immigrants spend looking for their first job. In this study, Iranian respondents were asked to indicate the year they started working and the year they began to continuously live in Los Angeles. Since respondents were not asked to report the actual length of time they spent looking for employment, the year of arrival was subtracted from the year they started their first job in the U.S. This is used as a proxy measure of whether Iranian immigrants found employment during the first year of arrival or after one year. Over half (54%) of male householders found jobs within the first year of their arrival. The dependent variable was dichotomized (1=within first year, 2=after one year). DETERMINANTS OF FINDING THE FIRST JOB Education Within the human capital explanation (see Chiswick 1978; Borjas 1983, 1987), education has been singled out as the most important determinant of economic success. Higher levels of education are related to higher labor force participation, higher earnings and higher occupational status (Chiswick 1978; Borjas 1987; Blau and Duncan 1967; Featherman and Hauser 1978). For the purposes of this chapter, highest level of education completed in Iran is included in the analysis since human capital resources play a critical role in explaining immigrants' economic integration. Among the male sample, 22% did not complete high school, 48% completed high school, and 30% received bachelor's degree or higher in Iran (Table 3.1). In addition to this variable, respondents were also asked to indicate whether they received any additional schooling outside of Iran. Almost two thirds of the male sample received additional schooling outside of Iran (Table 3.1). Due to the availability of data, both the highest level of education (in Iran) and additional years of schooling (outside of Iran) are

40


included in the analysis. This method captures the effects of pre- and postmigration human capital characteristics. It should be noted that the hypothesized positive relationship between education and employment opportunities during the initial settlement period does not apply to highly specialized professional immigrants (M.A. degree or higher) who may have needed to take recertification programs to qualify to practice their specialization. The re-certification process might prolong the length of time to find the first job in the U.S. English Proficiency Another important human capital characteristic is English proficiency. "Language proficiency has long been viewed as one of the most important resources immigrants need in the new society" (Raijman and Semyonov 1995, p. 377; see Borjas 1983). As many researchers have noted, English proficiency allows immigrants to transfer their labor market skills into the U.S. economy. The ability to speak the native language increases employment opportunities and enhances the likelihood of upward mobility. This chapter includes knowledge of English at the time of arrival as an explanatory variable. Male Iranian householders were asked to report how well they spoke English when they arrived in the U.S. Four response categories were included: "very well," "well," "not well," and “not at all.” Due to the small cell sizes, the response categories were collapsed into “very well/well” and “not well/not at all” – dichotomizing the English proficiency variable. Among male Iranians, almost 40% reported "very well/well" and 60% reported "not well/not at all” knowledge of English at the time of arrival (Table 3.1). Job Experience Labor market experience in country of origin is another important pre-migration determinant. Prior labor market experience increases the likelihood of employment in the U.S., and accelerates the process of finding employment. During the interviews, respondents were asked to indicate

Timing of First Job

41

whether they had been employed before leaving Iran. If employed, they also indicated the type of occupation, industry and class of worker. In Iran, 27% of Iranian men were not in the labor force, while the rest were employed full-time (Table 3.1). The majority of Iranians not in the labor force were students who had not started working fulltime. Immigrant Cohort Effect In addition to the human capital variables discussed above, immigrant cohort effect is another important explanatory variable that needs to be considered (Chiswick 1978; Borjas 1989). Borjas explained the inference by most human capital theorists that most immigrant groups do quite well, and are positively selected is completely erroneous (Borjas 1989, p. 474). "The bias is due to the well known problem that a single cross-section regression cannot differentiate between aging and cohort effects" (Borjas 1989, p. 474). Cohort effects capture productivity (or ability) differences across different immigrant cohorts. In other words, the positive correlation between earnings and years-since-migration documented by cross-section regressions may arise either because immigrants do experience higher earning growth than comparable natives, or because more recent immigrant cohorts have lower productivities (or are more likely to be negatively selected) than immigrants from earlier waves (Borjas 1989, p. 474). In the case of Iranians immigrants, three distinct immigration cohorts can be identified: 1947-77, 1978-79, and 1980-87. Among the male sample, almost 30% arrived before 1978, 35% between 1978-79 and the rest (35%) after 1980 before 1987 (Table 3.1). The earliest cohort was mostly comprised of students who left Iran for higher education. The market experience of U.S.-educated Iranians might differ from later cohorts, most of whom

42


were political asylees/refugees escaping the political unrest caused by the Iranian Revolution. In some ways, later cohort’s (1980 to 1987) characteristics are similar to the 1978-79 wave. But in other ways, the two recent cohorts differ to the extent that the 1978-79 wave might comprise more economically secure immigrants who could afford to leave immediately after the Revolution began. On one hand, following the human capital argument, one would expect the most recent cohort, which is comprised of more refugees/asylees, to experience more economic hardship than previous groups. On the other hand, even though migrants may be disadvantaged economically, as Boyd explained, they also "enter an area with many more relatives, friends and contacts than did earlier migrants" (Boyd 1983, p. 652). The immigrant cohort effect is included in the analysis. Visa Status Upon Arrival In addition to human capital skills and immigrant cohort effects, Chiswick (1979) argued: It is useful to know whether the criteria for admitting immigrants into the United States are relevant for understanding their economic progress and impact. Immigration visas may be rationed on the basis of the person’s likely productivity in the country, whether the person has relatives in the country, or for humanitarian reasons, such as refugee relief (Chiswick 1979, p. 362). The U.S. Census data, "the principal source of information on the foreign born in the United States, do not provide any information on visa status at entry or at the time of the Census" (Jasso and Rosenzweig 1995, pp. 8687). However, in the Iranian study respondents were asked to indicate the type of visa category under which they came to the U.S. Almost half of the male Iranian sample (43%) arrived as temporary visitors, and 27% as students (Table 3.1). The rest of the sample arrived as refugees/asylees (15%), under the family reunification classification or as

Timing of First Job

43

returning permanent residents (15%) (Table 3.1). Given their disadvantaged situation, refugees/asylees are expected to be worse off economically, whereas "returning permanent residents" and those who arrived under the family reunification classification are expected to do well economically. Other Iranian immigrants, students and visitors who arrived with temporary visas, are expected to fall somewhere in between these two extremes, although, those with student visas might excel in the long run. Demographic control variables such as age at immigration and marital status are also included in the multivariate analysis. Age at immigration is likely to affect labor market integration. "The location of point transitions that occur within an individual's career trajectory has different consequences, depending on where they occurred during the individual's life course and career stage" (Raijman and Semyonov 1995, p. 377; see Elder 1990). For Iranian male householders, the mean age at immigration was 37, and the vast majority of the male sample was married at the time of the interview (Table 3.1). RESULTS Approximately three-fourths (70%) of Iranian male immigrants who received general economic help during the first year of arrival found employment faster (Table 3.2). In order to fully test the network hypothesis, non-economic network variable is included in the analysis. At the bivariate level, there is no association between receiving non-economic assistance and length of time spent finding the first job (Table 3.2). These two network measures are based on a general question in which respondents were asked to indicate the types of help they had received during their first year in the U.S. In addition to this question, respondents were also asked to indicate whether they had received any help from family and/or friends to locate their first job. This indicator is more specific. It differentiates between respondents who actually received help in locating the first job or business opportunity and those who did not. A cross-tabulation between this variable with the

44


dependent variable shows that Iranian immigrants who received specific economic help to locate their first jobs found employment faster (Table 3.2). Once again, there is a positive network effect. To confirm these findings, Tables 3.3, 3.4 and 3.5 illustrate the multivariate results using logistic regression since the dependent variable - length of time before finding first job in the U.S. - is dichotomous. The first model (Table 3.3) includes the general economic network variable and the second model (Table 3.4) includes the general noneconomic variable. The multivariate results indicate a positive economic network effect. The odds of finding a job within the first year of arrival is 2.5 (exp (0.912)) times (see Table 3.3) higher for Iranian male immigrants who received general economic help compared to Iranians who did not receive economic help from family and/or friends. Iranian immigrants who relied on co-ethnic network ties were more successful in finding jobs faster than those who did not receive help. The results in the second model (Table 3.4) indicate that non-economic network ties do not have a direct effect on how long it takes for immigrants to locate jobs. The third model (Table 3.5) includes the specific economic network variable. The most important finding in the third model is the significant parameter estimate of the specific economic network effect. In this case, as explained earlier, respondents indicated whether they had received help finding their first job or starting their first business. The positive network effect in this model confirms the first model's finding and supports the network hypothesis. Upon arrival, Iranian immigrants who mobilized economic network ties were more likely to find employment faster. In addition to the economic network effect, other significant predictors include: employment experience in Iran, English proficiency, type of visa upon entry, and cohort effect (see Tables 3.3, 3.4, and 3.5). Results indicate that Iranian immigrants who found employment within the first year of arrival were younger, more proficient in English, and had labor market experience in Iran.

Timing of First Job

45

For type of visa upon entry, the results indicate no significant difference between temporary visitors and refugees/asylees in terms of how long it took Iranian immigrants to find employment. But, returning residents and Iranians who entered under the family reunification classification found employment more quickly than refugees/asylees. This result shows the disadvantaged positions of Iranian refugees/asylees. Iranian students took even longer than refugees/asylees to find employment. This is not surprising since attending school usually prolongs entrance into the labor market (see Tables 3.3. 3.4 and 3.5). Surprisingly, both pre- and postmigration education variables do not have significant effects on whether Iranian immigrants found jobs within the first year after arrival. One might anticipate that higher levels of educational achievement in Iran would have accelerated the job search process. Even though the parameter estimates are not significant (in all three models), at least the direction of these estimates is in the predicted order. The two dummy coded education variables (high school diploma and college degree) both have positive estimates. This result indicates that Iranian high school and college graduates had a better chance of finding employment faster than Iranians who were high school dropouts. For the M.A. or higher educational levels, the parameter is not significant, but the parameter estimate is negative, which indicates that Iranian immigrants with high educational levels (M.A. or higher) took longer to find employment. This result captures the recertification process that professionals need to undergo before working in their specialized fields. The findings also indicate that more recent Iranian immigrants (1980-87) found employment faster than those who arrived before 1977. One possible explanation is that the earliest cohort included students who did not find employment immediately after arrival since they were attending school. But including the visa type upon entry into the regression equation has controlled this factor. Another explanation is that the economic opportunities in the 1980’s offered more possibilities compared to the 1970’s. This explanation is plausible since during the

46


1980’s Los Angeles did experience economic growth. Another explanation might be that availability of jobs and/or access to job information increased for later, more recent immigrant cohorts. A tabulation of period of immigration by the general economic network variable indicates that there is a slight percent increase. The most recent immigrant cohort (1980-87) was more likely to receive economic help (14%) compared to the earliest cohort (10%), even though the difference was modest (Table 3.6). The tabulation by the general non-economic network variable also confirmed the finding that more recent immigrants were more likely to receive help (57% vs. 46%) (Table 3.6). In the study, respondents were asked to indicate whether they were informed about economic opportunities in the U.S. The percent informed increased for each subsequent immigration wave. This figure is 54% for the first wave (1947-77) and 74% for the most recent wave (1980-87). This difference in percentages is rather large which indicates that more recent immigrants arrived to more established immigrant networks (Table 3.6). SUMMARY Thus far, the above findings confirm the importance of both individual and social determinants of whether Iranian immigrants found employment within the first year of arrival to the U.S. Four out of five significant predictors (pre-migration labor market experience, English proficiency upon arrival, visa type upon entry and network ties) are not available in the census data sets yet they all showed significant effects. Iranian immigrants who found employment faster tended to be younger, more proficient in English, had work experience in Iran, entered U.S. as returning residents (or under the family reunification classification), and were more embedded in economic coethnic ties. More recent immigrants also found employment more quickly than the earliest cohort. This is possibly another indirect measure of embeddedness. More recent immigrants, compared to earlier cohorts, have the economic advantage of entering into more established

Timing of First Job

47

immigrant network structures, thereby obtaining more access to job information and employment opportunities. Additional schooling outside of Iran was not a significant predictor of how quickly Iranians found employment in the LA labor market. Perhaps, it is too early to assess the impact of additional schooling since this chapter concentrates on the initial settlement phase. This variable is included in subsequent chapters to assess its impact during the more settled phase. As far as migration characteristics are concerned, the majority of Iranians arrived with temporary visitor or student visas, while the rest arrived as refugee/asylees or under the family reunification classification, or returning residents. Results indicated that Iranian refugees/asylees were the most disadvantaged group especially during the initial settlement phase. The most interesting result in this chapter is the significant network effect. For Iranian immigrants, networks sped up the initial job search process, which indicates a positive network effect during the early settlement phase. Immigrant networks, however, can constrain, as well as enhance, individual goals. The next chapter examines how immigrant networks affect occupational status shifts between Iran and the U.S. Immigrant networks might quicken the job search, but they might not lead to desirable or prestigious jobs, especially during the initial phase.

Table 3.1 - Sample Characteristics, Iranian Males, LA County 1987-88

Found employment w/in first year after arrival Highest level of education completed in Iran: Less than high school High school diploma BA/BS MA & + Employed in Iran Knowledge of English upon arrival: Not well/not at all Very well/well Additional schooling outside of Iran Period of Immigration: 1947-77 1978-79 1980-87 Immigration status/visa type: Refugee/Asylee Family/Return Temporary Visitor Student Received general economic help Received general non-economic help Received specific economic help Informed about job opportunities in U.S. Group: Muslim Armenian Bahai Jewish Currently married Age at immigration (mean) Age at time of interview (mean) N

Data Source: The 1987-88 Iranian Survey in Los Angeles

48

55% 22% 48% 17% 13% 73% 60% 40% 60% 30% 35% 35% 15% 15% 43% 27% 12% 23% 51% 61% 31% 25% 14% 30% 83% (37) (45) 557

Table 3.2 – Networks Measures by Timing of First Job, Iranian Males, LA County 1987-88 Found employment first year after arrival

Received Help:

Yes

No

General economic

70%

30%

61

General non-economic

53%

47%

123

Specific economic

60%

40%

273

Data Source: see Table 3.1

49

N

Table 3.3 – Logistic Regression, Finding First Job in the U.S., Iranian Males, LA County 1987-88 Explanatory Variables: Highest level of education completed in Iran: (Ref: Less than high school) High school diploma BA/BS MA & + Employed in Iran Proficient in English upon arrival Additional schooling outside of Iran Period of Immigration: (Ref: 1947-77) 1978-79 1980-87 Immigration status/visa type: (Ref: Refugee/Asylee) Family/Return Temporary Visitor Student Received general economic help Group: (Ref: Jewish) Muslim Armenian Bahai Currently married Age at immigration Model chi-square (df=17) Sample size Data Source: See Table 3.1

Parameter Estimate (Log odds) 0.542 0.415 -0.662 1.331*** 0.847** -0.075

0.551* 1.216*** 1.072* 0.415 -1.191* 0.912* -0.105 0.144 -0.650 -0.102 -0.030 155*** N=465

* p < .05, ** p

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