The Effect of Military Service on Educational, Occupational, and Income Attainment

SOCIAL SCIENCE RESEARCH ARTICLE NO.

25, 1–31 (1996)

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The Effect of Military Service on Educational, Occupational, and Income Attainment JAY D. TEACHMAN Department of Human Development, Washington State University, Pullman

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VAUGHN R. A. CALL Center for Studies of the Family, Brigham Young University We examine the relationship between military service and educational, occupational, and income attainment in three cohorts of young men spanning the period from the late 1960s to the early 1980s. This is a period covering the war in Vietnam, the end of the draft, and the beginning of the All-volunteer Force. We consider the effect of military service separately for African-American men and white men and take into account the potential confounding influence of unmeasured self-selection into the military. Our results indicate that there is a relationship between military service and subsequent attainment, but it varies according to race and is dependent on historical context. r 1996 Academic Press, Inc.

While socialization and the formalization of aspirations before and during the high school years, in conjunction with parental resources, have well-established causal linkages in the basic status attainment model (Blau and Duncan, 1967; DiPrete and Grusky, 1990; Duncan and Hodge, 1963; Duncan, Featherman, and Duncan, 1972; Grusky and DiPrete, 1990; Hauser and Featherman, 1977; Sewell, Hauser, and Wolf, 1980), the effect of events occurring between high school and adulthood are not well documented. The lack of information about how experiences in the young adult years affect the process of stratification is unfortunate given the variability of life-course trajectories (Hogan and Astone, 1986; Marini, 1984; Rindfuss, Swicegood, and Rosenfeld, 1987) and the potentially important

This research was supported by Grant HD-25274 from the National Institute of Child Health and Human Development. Address reprint requests to Dr. Jay D. Teachman, Department of Human Development, Washington State University, Pullman, WA 99164-6236. 1 0049-089X/96 $18.00 Copyright r 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

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role of particular life course events in shaping subsequent attainment (Campbell, 1983). For instance, sociologists have long speculated about the role played by military service in the status attainment process (Duncan and Hodge, 1963; Duncan et al., 1972). In this paper, we examine changes in the relationship between military service and subsequent educational, occupational and income attainment with data from three cohorts of young men spanning the period from the late 1960s to the early 1980s. This is a period covering the war in Vietnam, the end of the draft, and the beginning of the All-volunteer Force (AVF). We consider the effect of military service separately for African-American men and white men and take into account the potential confounding influence of unmeasured factors associated with self-selection of young men into the military. Our results indicate that the relationship between military service and subsequent attainment varies according to race and is strongly dependent on historical context. PRIOR LITERATURE Mason (1970) and Fligstein (1976) found that the occupational status of veterans of World War II and Korea exceeded that of non-veterans, consistent with the higher education of veterans of that era. Similarly, a number of authors have reported that veterans of World War II and Korea enjoy higher earnings than non-veterans (Browning, Lopreato, and Poston, 1973; Little and Fredland, 1979; Martindale and Poston, 1979). The literature is consistent in finding a positive effect of military service on the status attainment of veterans of these two earlier conflicts. The situation appears different for the Vietnam era, though. Rothbart, Sloane, and Joyce (1981) and Card (1983) reported that veterans of the Vietnam era had lower occupational status than non-veterans. Cohen et al. (1992) also reported lower occupational status for veterans of the Vietnam era but found that the difference could be explained by the fact that Vietnam veterans, contrary to the case for World War II and Korean veterans, obtained less education than non-veterans. The negative impact of military service during Vietnam extends to income as well, with veterans experiencing a deficit compared to non-veterans (Angrist, 1990; Berger and Hirsch, 1983; Martindale and Poston, 1979; Schwartz, 1986). An exception to this latter finding, though, is that African-Americans who served during Vietnam appear to enjoy higher incomes than non-veterans (Card, 1983; Martindale and Poston, 1979; Xie, 1992). Curiously, there is little research on the effect of military service on status attainment following the Vietnam conflict. The fact that the relationship between veteran status and subsequent attainment changed substantially between World War II/Korea and Vietnam, combined with considerable changes in the nature of military recruitment and training following the end of the draft in 1973, makes research on the post-Vietnam era important to consider. Available evidence implies that the impact of military service on status attainment may vary according to historical context.

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A few reports focusing on income suggest that the relationship between military service and attainment may have shifted once again following the inception of the AVF. Philips, Andrisani, Daymont, and Gilroy (1992) and Xie (1992) report that the income difference between veterans and non-veterans is positive for white men and nonexistent for African-American men. We are not aware of research that has examined the relationship between veteran status, educational attainment and occupational status for the period following Vietnam. Given that 10 to 15% of birth cohorts of young men have continued to serve in the military following the Vietnam war (Teachman, Call, and Segal, 1993), military service has the potential for far-reaching consequences for the process of status attainment. Failure to consider the effects of military service may serve to dampen our understanding of the complex nature of this process. Our goal, therefore, is to extend consideration of the impact of military service on educational, occupational and income attainment from the Vietnam era forward. In addition to the period surrounding the conflict in Vietnam, we consider the impact of military service in the 1970s (the period immediately following the inception of the All-volunteer Force) and early 1980s. As noted in the following section, we believe that military service affects subsequent attainment for several reasons: veterans possess different background characteristics than non-veterans, military service changes veterans, and military service acts as a signal about the human capital of veterans. Our basis for expecting shifts across historical time in the effect of military service on subsequent attainment is predicated on changes in one of more of these factors as they occur from one era to the next. Our selection of data bases is designed to produce data that reflect historical changes in these factors. The remainder of the paper is structured as follows. We first lay a conceptual foundation whereby we briefly outline our rationale for expecting military service to affect subsequent education, occupation, and income. Second, we discuss historical changes that lead us to expect variation across time in the linkage between military service and subsequent attainment. Third, we outline our selection of data bases. Fourth, we present our methodological approach. Fifth, we discuss our major results. We conclude by considering the implications of our results. CONCEPTUAL FOUNDATION There are at least three reasons why military service may be related to subsequent attainment. First, veterans may differ from non-veterans on relatively stable measured or unmeasured background characteristics that are related to attainment. Second, military service may alter veterans or their characteristics in some fashion that affects later attainment—we are particularly interested in the role military service plays in altering educational attainment. Third, employers may make use of veteran status as an indicator of ability or skill in a way that influences hiring decisions and thus occupational attainment and income.

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Differences on Background Characteristics Each branch of the Armed Forces uses a set of selection criteria for choosing recruits. Physical, educational, and mental criteria are applied in screening applicants for entry into the military—criteria that are positively related to success in the civilian sector (Eitelberg, Laurence, Waters, and Perlman, 1984).1 The application of such criteria ensures that veterans are not a random subset of the civilian population. Because recruitment standards exclude recruits who have the least education and who score lowest on standardized tests of mental ability, veterans are likely to enjoy greater success in school and the labor market than non-veterans. However, among individuals who meet the minimum requirements, those who enter the military are self-selected (Mare and Winship, 1984). Limited evidence suggests that self-selection results in recruits who have fewer socioeconomic resources and less well-honed abilities than would be the case if young adults who met the entrance requirements were randomly assigned to military service (Eitelberg, Laurence, Waters, and Perlman, 1984; Teachman et al., 1993). As such, the positive influence of recruitment standards on subsequent attainment is likely to be offset, fully or partly, by the self-selection of individuals who are less able or less motivated to take advantage of opportunities in the civilian world.2 Historically, the self-selection of qualified recruits has been affected by perceptions of the military as a desirable job choice, the draft, the array of job training and educational programs available to veterans and non-veterans, military versus civilian pay schedules, and civilian unemployment rates (Dale and Gilroy, 1983, 1984; Hexter and El-Khawas, 1988). For example, the beginning of the AVF was accompanied by a significant decline in the overall quality of military recruits compared to the Vietnam era (i.e., fewer recruits with a high school degree and lower scores on tests of mental aptitude)—a decline that reversed as the negative images of Vietnam faded and civilian job prospects weakened in the late 1970s and early 1980s (Eitelberg, Laurence, Waters, and Perlman, 1984; Moskos, 1981). In addition to historical variations in selectivity, race differences are also apparent. African-Americans are less likely to negatively self-select on criteria important to subsequent attainment than are whites (Teachman et al., 1993). Recruitment standards also result in a smaller proportion of African-Americans being eligible to enter the military (Eitelberg et al., 1984). Thus, the variation between veterans and non-veterans on measures such as high school graduation and standardized test scores is greater among African-Americans than whites. Similarly, the equality of opportunity offered by the military in terms of recruit1 For a review of selection criteria and how they might affect subsequent attainment see Teachman et al. (1993). 2 Ability and motivation may be tied to a number of different factors of which we do not possess measures. Skill in social interaction, knowledge of the world of work, placement in occupationally relevant networks, and drive for economic success are all examples of the sorts of unmeasured factors that might generate selectivity of recruits on occupational status.

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ment, pay and promotion (Daula, Smith, and Nord, 1990; Philips, Andrisani, Daymont, and Gilroy, 1992), combined with discrimination in the civilian sector, likely acts to further reduce negative self-selection on factors such as ability and motivation. Differences Induced by Military Service Veterans and non-veterans may vary on subsequent attainment because the military changes recruits or affects the characteristics they possess. Such change may be due to alterations in social psychological states, the creation of specific job skills or shifts in educational attainment. As far as we are aware, no research has documented the influence of military service on the social psychological makeup of recruits that would affect attainment in the civilian world. There is, however, evidence suggesting that veterans attribute to the military a positive influence on their sense of self that is of value to them in the civilian labor market (Gade, Lakhani, and Kimmel, 1991). Several researchers have argued that the military serves as a bridging environment whereby appropriate values and social skills necessary for success in mainstream American society are learned (Browning, Lopreato, and Poston, 1973; Little and Fredland, 1979; Martindale and Poston, 1979). The implication of this argument is that race and ethnic minorities, who may be less integrated into the cultural standards of mainstream America, will benefit most by military service. As evidence for this argument, there is a relatively consistent body of literature pertaining to the Vietnam era showing that minorities, especially African-Americans, are more likely to benefit economically from military service (Browning, Lopreato, and Poston, 1973; Card, 1983; Martindale and Poston, 1979; Xie, 1992).3 There is evidence indicating that skills obtained in the military are transferable to the civilian sector (Magnum and Ball, 1987). This argument is plausible for some military occupations, such as those involving technical skills. Over time, there has been greater transferability of skills from military to civilian jobs due to the increased technical requirements of waging war (Magnum and Ball, 1987, 1989).4 Additional support for this supposition is provided by the fact that increasing proportions of active duty military personnel are enrolled in postsecondary courses and are achieving post-secondary degrees (Hexter and ElKhawas, 1988). Finally, military service may affect occupational and income attainment through its relationship with educational attainment. Education is the most substantial and proximate determinant of occupational status and income, evidencing a strong, positive relationship. Because education is not a fixed background characteristic, military service may influence the amount and type obtained. Veteran status will 3

For an exception, see Berger and Hirsch (1987). For example, Magnum and Ball (1989, p. 243) report that the correspondence between military and civilian occupations is 45–50% for the post-1973 period compared to 25–30% for earlier periods. 4

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be associated with educational attainment insofar as recruits are self-selected on characteristics that are related to ability and educational aspiration. Military service may also alter educational aspirations, and veterans’ benefits (the GI Bill of Rights) affect access to education. Indeed, a small number of studies have documented a relationship between military service and educational attainment. These studies show that the nature of the relationship between military service and educational attainment has varied across time. For veterans of World War II and Korea, military service had a strong, positive relationship with ultimate education (Mason, 1970; Fligstein, 1976). As noted above, one study (Cohen et al., 1992) found that the lower educational attainment of veterans during the Vietnam era explained their lower occupational attainment. It is likely that the greater educational attainment of World War II and Korean veterans explains part or all of their greater occupational attainment. It also is reasonable to expect that shifts in the educational attainment of veterans and non-veterans are tied to the changes in the effect of military service on income noted above. Military Service as a Signal to Employers It has been suggested that military service acts as a signal to employers about the capabilities of potential employees above and beyond commonly available measures of human capital such as education (DeTray, 1982). In an environment with limited information about new hires, military service indicates to employers an established level of productivity, competence and motivation. That is, military service performs as a credential for nonspecific elements of human capital that are valued in the labor market.5 The validity of this signal or credential rests in the entrance requirements used by the Armed Forces and the fact that completion of a tour of duty indicates ability to perform adequately within a bureaucratic setting. The military has always used a set of relatively stringent entrance requirements. Thus, employers can infer that veterans possess a level of physical and mental capacity that exceeds the national average. In addition, successful completion of a tour of duty in the military indicates a willingness to accept orders, along with the maturity and motivation to see that those orders are fulfilled. Over time, veteran status has likely formed an increasingly positive signal to employers about human capital. This change stems from two sources. First, the military has used increasingly stringent entrance requirements. While one of two major entrance requirements, a high school degree, is generally available to employers, the other requirement, performance on ability tests, is not. Thus, with increasingly higher scores on mental aptitude tests required for entrance, employ5 We should make it clear that we necessarily speculate about the nature of the credentionaling process that occurs. We have no direct information about the value employers place on having successfully completed a tour of duty in the military. This would appear to be an area well worth pursuing in greater detail.

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ers can assume that veterans are a more select subset of the general population. Second, the increasingly technological environment within which military duties are performed indicates to employers that veterans might be better able to adapt to the requirements of post-industrial jobs. PROCEDURE: HISTORICAL CHANGES IN THE IMPACT OF MILITARY SERVICE We estimate models for the effect of military service on educational attainment, occupational status and income, including controls for background characteristics known to influence these outcomes. In turn, the model for occupational status includes a control for educational attainment, and the model for income includes controls for both educational attainment and occupational status. We use an estimation procedure that adjusts for the influence of unmeasured self-selection of recruits on each outcome. Because of the control for educational attainment, selectivity in the model for occupational attainment refers to unmeasured factors not related to education achieved. Similarly, because of the controls for education and occupation, selectivity in the model for income taps factors not related to either of these outcomes. We have no way to directly assess the effect of serving in the military on the social psychological makeup of veterans, their skills obtained that are applicable to the civilian labor force and whether employers use veteran status as a screening device when making new hires. Similarly, we cannot directly assess the effect of military service on aspirations and expectations for education, nor the effect of shifts in military and civilian educational benefits. Assuming that our models are adequately specified with respect to important background factors, any effect of military service on subsequent attainment therefore can be attributed to any one or a combination of relevant factors. However, by estimating models separately for three historical periods, we make use of change, or lack of change, in the character of military service and opportunities in the civilian sector to make indirect inferences about the basis of the impact of military service on attainment net of background characteristics and self-selection. The historical periods we examine include the Vietnam era, the period immediately following the inception of the All-volunteer Force, and the early 1980s. Below, we outline the changes that occurred across these historical eras that may have altered the relationship between military service and subsequent attainment. Education There are several reasons for expecting change across cohorts in the relationship between military service and educational attainment. First, we believe that the increasingly technical nature of military occupations over time (Magnum and Ball, 1989) has stimulated increased realization among recruits of the value of education. For example, increasing proportions of active duty military personnel

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are enrolled in post-secondary courses and are achieving post-secondary degrees, with a substantial increase following the beginning of the AVF (Hexter and El-Khawas, 1988). This pattern suggests that the relationship between military service and educational attainment should be increasingly positive (or less negative) over time. Second, substantial changes in both the GI Bill and educational assistance for non-veterans have shifted the structure of educational opportunities. Prior to 1960, the GI Bill provided educational opportunities that were not available to the general civilian population. After 1960, however, the value of civilian educational programs expanded to a point where they equalled or bettered educational benefits associated with military service (Cohen et al., 1986), shifting upward the overall level of education earned by American men. Thus, while veterans of the Vietnam era obtained more education than veterans of earlier eras, the increase in educational attainment among non-veterans was so substantial that veterans received less education than their civilian counterparts. Following the Vietnam era, GI Bill benefits were terminated. Recruits whose service did not include some period prior to 1976 were not eligible for the GI Bill.6 This change suggests that military service after 1976 should be associated with lower educational attainment. However, substantial downward shifts in civilian post-secondary education occurred. After reaching a high in 1968, the percentage of young men enrolled in college dropped precipitously. The percentage of young men enrolled in college bottomed out in 1979–1980 (U.S. Bureau of the Census 1990, 1991), a point corresponding to the beginning of our third historical era. The drop in college enrollment in the 1970s can be traced, in part, to changes in programs of financial assistance. After the mid-1970s, financial aid packages shifted from primarily grants to loans. As reported by Hauser and Anderson (1991), the percentage of all financial aid in the form of grants decreased from 80 to 46 across the 1975–1976 to 1985–1986 decade. Over the same period, the percentage of financial aid given in the form of loans increased from 17 to 50. Thus, at about the same time the GI Bill ended, there occurred a downturn in public support for education in the civilian sector. It is not clear, therefore, that the demise of the GI Bill in 1976 led to an increasingly negative relationship between military service and educational attainment. An answer must be determined empirically. Third, we also believe that the relationship between military service and educational attainment varies according to race. While college enrollments 6 In 1985, a ‘‘New GI Bill,’’ also known as the ‘‘Montgomery GI Bill,’’ was instituted (Hexter and El-Khawas, 1988). However, the data that we consider do not cover the post-1985 period. From 1982 to 1985, there were a variety of contributory programs in which contributions made by recruits would be matched by contributions from one or more of the services (also known as the Veterans Educational Assistance Program). While some members of the last cohort of individuals we cover may have been eligible for VEAP, the participation rate was much lower than for the Vietnam-era GI Bill or the New GI Bill (Hexter and El-Khawas, 1988).

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dropped rapidly among white men from the late 1960s to the late 1970s, before increasing again, the pattern for African-American men is much different. College enrollments among African-American men did not decline immediately following the 1960s. Indeed, the likelihood of enrollment generally increased until the mid-1970s, after which declines occurred until the 1980s. In other words, from the end of the 1960s to the 1980s, the pattern of college enrollment for African-Americans was the reverse for whites. Following Hauser and Anderson (1991), one source of the difference between African-Americans and whites in the likelihood of college enrollment is the shift from grants to loans as the primary source of tuition support. Because of the more precarious economic situation of African-Americans, even at the same income level as whites, it is likely that young African-Americans are more likely to discount the future value of a college education. Thus, after the shift from grants to loans, African-Americans were more likely than whites to choose alternatives other than college after high school graduation. Prior to 1976, combined with increasingly effective affirmative action programs, the emphasis on grants continued to draw an increasing proportion of young African-Americans into college. The increased likelihood of attending college that continued well into the 1970s thus suggests that any negative effect of military service on educational attainment for African-Americans persisted longer than for whites. Similarly, the rapid drop in college enrollment among African-Americans in the late 1970s and early 1980s suggests that the effect of military service on educational attainment was less negative for African-Americans. Occupational Status and Income With respect to occupational attainment and income, we also make inferences based on change, or lack of change, in the nature of civilian and military employment. First, we argue that the rigid, bureaucratic structure of military service has not changed appreciably over the period we consider in this paper. Thus, it is not likely that changes in the relationship between military service and occupational status and income, net of background factors, can be attributed to alteration of basic social psychological profile of veterans. Similarly, we have no reason to believe that changes in the military would have substantially impacted the likelihood that military service acted as a bridging environment for less advantageous recruits. Second, the growing technical nature of occupations in the Armed Forces suggests an increasingly positive relationship between veteran status and occupational status and income. As noted by Magnum and Ball (1989), veterans are increasingly likely to possess skills valued in the civilian labor market, and it is logical to expect that employers are more likely to place greater importance on veteran status as an indicator of such skills. This trend should be amplified by the dampening of any negative signal that may have been associated with military service during an unpopular war. These shifts suggest that military service

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following the Vietnam era should evidence an increasingly positive relationship with occupational status and income. Third, we make use of the fact that we have information on both whites and African-Americans to determine whether the hypothesis that the military serves as a bridging environment has merit. If the military provides an environment within which members of minority groups can learn to operate successfully in the majority run economy, then we expect that the relationship between military service and both occupational status and income is less negative for AfricanAmericans. Accordingly, we estimate models separately for whites and AfricanAmericans. We have no basis on which to expect that this sort of relationship should vary across time. DATA Our choice of data is motivated by several factors. First, the data must catch young adults beginning at those ages during which military service is most likely and must include information about dates of service. Second, the data must contain information about important background characteristics relevant to educational, occupational and income attainment that may serve as control variables. Third, the data must cover different historical periods and should be reasonably comparable so that historical changes in the relationship between military service and subsequent attainment can be inferred net of methods effects. We selected three data sets that meet these criteria. Each data set includes considerable specificity about military service and socioeconomic background. Moreover, each data set contains two or more waves of information. The period of potential military service runs from 1966 to 1986, and, while there are variations in how the data were obtained and the types of questions asked, we believe there is sufficient comparability between the surveys to make reasonable conclusions about change in the relationship between military service and subsequent attainment at various points in history. The first data base, the Career Development Study (CDS), was designed for the study of individual-level determinants of access to careers and the relationships between transitions made by adolescents as they move into young adulthood (Otto, Call, and Spenner, 1981). The study population consisted of males and females who were juniors and seniors enrolled in public high schools in the state of Washington during the 1965–1966 academic year. Respondents were chosen using a proportionate, stratified random sampling procedure and completed a classroom-administered questionnaire covering demographic background data, social psychological information, extensive information on high school experiences, and plans for the future. In 1979–80, or approximately 13 years later, contact was reestablished with over 98% of the original CDS sample (Call, Otto, and Spenner, 1982). The second interview gathered demographic and life history information about education, family, and military and work experiences since high school. We use information from the men who responded to the CDS follow-up in

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1979. We only consider men in our analysis because so few women entered the military during the period we examined. We recognize, however, the growing presence of women in the military and encourage investigation of the relationship between military service and the process of attainment for women. Almost all men in the CDS who served in the military did so during the Vietnam era (prior to 1973). The second data set, the National Longitudinal Study of the High School Class of 1972 (NLS), is also a study of access to career lines and educational progress. In the NLS data are background, demographic and life history information comparable to the data found in the CDS. The NLS has followed male and female respondents from their senior year in high school to early 1986, with intervening follow-ups in 1973, 1974, 1976, and 1979. The original sample was a stratified random sample of all high school seniors enrolled in public, private and churchaffiliated high schools in the United States (Riccobonno et al., 1981). We use information gathered from men in each of the six waves of the survey.7 The NLS data follow young men from approximately age 18 to approximately age 32, roughly the same age span covered in the CDS. However, the historical period covered by the NLS is different from that of the CDS. Men in the NLS were eligible to enter the service only after the end of significant involvement in Vietnam and are the first cohort of men since before World War II to be subject to all-volunteer Armed Forces. As noted above, this is also a period during which changes occurred in the GI Bill, civilian educational opportunities and the transferability of military skills to civilian occupations. The third data base, the High School and Beyond Study (HSB), is largely a replication of the NLS. Beginning in the spring of 1980, the HSB gathered base-year data on high school seniors and sophomores, using a stratified random sample of public, private and church-affiliated schools (National Opinion Research Center 1986). To date, three follow-ups to the HSB have been accomplished: 1982, 1984 and 1986. Like the CDS and NLS, the HSB contains information on background, demographic and life course characteristics. Because of the limited ages covered by the HSB, we restrict our attention to the senior cohort, using information on men gathered in all four waves of the survey.8 7 The original target sample was over 22,000 cases. However, for budgetary reasons, it was decided that an unbalanced subsample of these cases (14,489) would form the 1986 sample. Because the 1986 survey was not a random subsample of the original NLS respondents (which were themselves not a random sample of all high school seniors), weighted regression is necessary to achieve representativeness. However, the use of weights undermines the asymptotic theory upon which the calculation of the standard errors of the regression coefficients is based. Fortunately, weighted and unweighted regressions provide substantively similar regression coefficients. In order to provide unbiased estimates of standard errors, we report the unweighted regression coefficients. 8 Because we restrict consideration to white and African-American men, and because the HSB oversampled minority groups other than African-Americans, the sample we use, 2889, is considerably smaller than the actual number of men interviewed. As is the case for the NLS, weights are necessary to obtain unbiased parameter estimates. However, weighted and unweighted regression provide substantively similar results. In order to report unbiased estimates of standard errors, we use results from unweighted regressions.

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Young men in the HSB are followed from approximately age 18 to approximately age 24. This span of ages is smaller compared to the CDS and the NLS. However, this is sufficient time for most young men to enter the military, complete a tour of duty, and transition back to civilian status. A significant proportion of all military service among men in the HSB was completed by the 1986 follow-up (about 98%), and these men will have resumed civilian life, allowing comparison with the occupational experiences of men in the CDS and NLS. The HSB covers military experience during the early 1980s, a period nearly a decade following the inception of the AVF and during which college enrollments increased and public perceptions of military service became more positive. Potential Problems and Biases Does the restriction to Washington State reduce the comparability of results from the CDS to results obtained from the other surveys? Numerous comparisons of basic demographic information between the CDS and the U.S. Census show relatively minor variations. Models of the aspiration formation and status attainment processes estimated from the CDS data compare closely to models estimated from other regional and national data sets collected during the same period (Otto et al., 1981; Spenner et al., 1982). This underscores Campbell’s (1983) observation that studies of status attainment processes are robust in the presence of potentially substantial methods variance (see also Alexander, Eckland, and Griffin, 1975; Jencks, Crouse, and Mueser, 1983; Otto and Haller, 1979). Congruent with population values for Washington state, however, the CDS contains few non-whites (about 2%). Because the NLS and HSB are large, national samples, they contain much higher proportions of non-whites. Thus, the analysis of CDS data was restricted to whites. Comparable analyses for the NLS and HSB were run for whites and African-Americans separately. Due to small sample sizes, we did not conduct analyses for other race/ethnic groups. By sampling high school students, the CDS, NLS, and HSB miss some men who served in the military, particularly during the Vietnam years when the services used less selective entrance requirements. As such, our results should be interpreted as reflecting only the experience of men who reached the level of education used to select the various samples. To increase the comparability of our samples taken from the CDS, NLS and HSB data bases, we exclude all high school drop-outs. The exclusion of high school drop-outs allows us to make comparisons between cohorts without bias. However, we are unable to draw conclusions about the experiences of veterans who possess less than a high school degree. It is likely that the experiences of these veterans have changed substantially over time. With the implementation of higher educational standards, veterans without a high school degree are an increasingly select group. For example, it is most likely the case that these veterans possess unusually high scores on aptitude tests.

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The use of high school cohorts does have benefits, though. The CDS, NLS and HSB data contain reasonably large samples of men who entered their young adult years in unison. That is, while there is likely to be substantial inter-cohort variation with respect to contextual factors influencing educational, occupational and income attainment, intra-cohort variations are minimized. Men in a given cohort faced basically the same set of structural constraints and opportunities, including military recruitment standards, and policies.9 METHOD Our method is straightforward. We begin by presenting descriptive information about educational, occupational, and income attainment according to veteran status. Our measure of education obtained is limited by the information contained in the NLS. While each of the other data bases contains information on actual years of schooling completed, the NLS data only allow coding of categories— high school graduate, some college, college graduate, and graduate degree. We have coded data from the CDS and HSB to correspond to the NLS data, coding 1 for a high school graduate, 2 for some college, 3 for a college graduate, and 4 for a graduate degree. While we have lost some of the detail available in two of the data bases and no longer have a variable that is strictly interval, the results we present are robust to differences in coding and statistical procedure. The conclusions reached for the CDS and HSB data remain essentially the same if we use years of schooling in place of the NLS coding.10 The HSB data on educational attainment are truncated at six years following high school graduation and thus some care must be used in making comparisons with the CDS and NLS data. However, in results not shown here, we found that educational attainment in the NLS was virtually the same in 1979 as in 1986 (we were unable to perform a similar exercise using the CDS data), suggesting that most men in the HSB will have completed their education by 1986. We also found that our multivariate models estimated for the NLS data yielded the same results whether we used education obtained by 1979 or 1986. 9 There is a potential confounding factor with respect to the HSB data associated with the misnorming of the ASVAB mental ability test that all recruits must take before enlisting. Due to an error committed during the development of new ASVAB forms in 1976, percentile scores in reference to the normative population were not correct. The major effect of this misnorming was that between January 1976 and September 1980, ASVAB percentile scores were inflated, particularly in the lower ability range (Laurence, Ramsberger and Gribben, 1989). Consequently, it is possible that some of the HSB veterans were allowed into the military when they would not otherwise have qualified. Such an error would have an unknown effect on our results. However, we reestimated our models including a dummy variable for enlistment before and after September 1980 and found that our substantive conclusions were not changed. 10 Our conclusions about the influence of military service on educational attainment are also unchanged if we use an ordered probit procedure to analyze the data using the NLS coding. We chose to retain the simplest coding scheme and a least squares regression approach for ease of presentation. The use of least squares also allowed evaluation of the selectivity of military service with respect to educational attainment in a straightforward manner.

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To measure occupational status, we used Duncan SEI scores based on 1970 census occupational titles (Stevens and Featherman, 1981) for each data base. We used scores for current (or latest) non-military jobs held for at least six months.11 For veterans, the scores correspond to jobs held after military service. Current (or latest) job occurs at a younger age in the HSB (about age 24) than in the CDS or NLS (about age 30–32). Accordingly, caution must be used in making comparisons between the HSB and the other two data bases when considering status of current (or latest) job. Not only is it likely that occupational status for all men will be somewhat lower in the HSB, but veterans will have had less time to re-enter the labor force and overcome any disadvantages associated with their military service. Income is measured as the annual value of wages or salary associated with current (or latest) job held for at least 6 months in each data base. For veterans, income refers to jobs held after military service. Again, current (or latest) job in the HSB occurs at a younger age than in the CDS or NLS, requiring caution in interpreting results. All else being equal, income measured in the HSB will be lower, and veterans will have had less time to overcome short-term disadvantages associated with removal from the civilian labor market. To evaluate the relationship between military service and subsequent attainment in a multivariate framework, we first used ordinary least squares (OLS) regression. That is, we regressed each measure of attainment on an indicator of veteran status and a set of control variables known to influence attainment. As discussed above, the controls we used were taken from the standard model of status attainment and for all data bases included measures of number of siblings, father’s education, mother’s education, grade point average in high school, friend’s expectations for college, and educational expectations (Blau and Duncan, 1967; DiPrete and Grusky, 1990; Duncan, Featherman, and Duncan, 1972; Hauser and Featherman, 1977; Featherman and Hauser, 1978; Sewell, Hauser, and Wolf, 1980). For the NLS and HSB data bases, we also included a measure of mental ability based on standardized scores for reading, vocabulary and mathematics tests (National Opinion Research Center, 1986; Riccobono et al., 1981).12 The means and standard deviations of these variables are shown in Table 1. The codings of the variables are shown in Appendix Table 1. While we have included most variables commonly used in the standard attainment model, we do not include a measure of father’s occupational status. Unfortunately, father’s occupation in the HSB was measured in 17 broad 11 A number of men held civilian jobs prior to entering the military. We have elected not to institute a control for the status of these jobs, however. We base this decision on the fact that: (a) a majority of veterans entered the military immediately following high school and thus had no civilian labor force experience and (b) a majority of veterans who did work before entering the military did not have at least 6 months of experience in one job. 12 In order to increase comparability between data bases, we elected to use a summary measure combining the various test scores available. We also trichotomized the summary scale at the first and third quartile values in both the NLS and HSB data.

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TABLE 1 Means and Standard Deviations of Variables Used in Analysis of Effects of Military Service on Educational and Occupational Attainmenta CDS Variable

µ

Whites Veteran Number of sibs Father’s education Mother’s education Grade point average Friend expects college Expected education Mental ability Education obtained Occupational status Yearly income N Blacks Veteran Number of sibs Father’s education Mother’s education Grade point average Friend expects college Expected education Mental ability Education obtained Occupational status Yearly income N

NLS s

.41 .49 2.69 1.72 2.25 1.45 2.24 1.11 4.73 1.39 .84 .24 4.45 1.15 —b — 3.22 1.01 44.04 25.77 20556 11368 2935

µ

HSB s

µ

s

.10 .29 3.10 2.24 2.49 1.06 2.39 .95 5.52 1.38 .63 .46 4.40 1.04 2.12 .74 3.16 .88 45.06 21.02 29321 26869 4955

.12 .33 2.75 1.31 2.59 1.20 2.39 .97 5.85 1.41 .73 .44 4.31 1.40 2.16 .53 2.70 .88 32.66 18.23 14202 18075 1977

.17 4.81 2.11 2.10 4.98 .49 4.34 2.16 2.90 33.25 28551

.20 3.11 2.30 2.25 5.17 .75 4.23 1.70 2.43 27.05 13617

.38 3.59 .70 .67 1.29 .48 .87 .73 .81 19.34 18560 500

.40 1.44 .94 .98 1.35 .42 1.42 1.52 .73 14.92 17125 912

a Means and standard deviations for all exogenous variables, as well as N, are based on the sample used to estimate the equations for educational attainment. All values are slightly different for samples used to estimate other equations due to missing data. b Not available for the CDS data.

categories and is not consistent with the Duncan SEI score included in the CDS and NLS. However, we believe that the other background variables included in our model absorb most of the effect of father’s occupational status and, as a whole, constitute an adequate set of controls for preexisting circumstances that would lead veterans and non-veterans to vary on subsequent attainment.13 The OLS regression models do not take into account the self-selection of military recruits on unmeasured characteristics (such as ability, motivation and 13 We estimated models for occupational status using data from the CDS and NLS that included a control for father’s occupational status. None of the substantive conclusions described below are altered based on the results from these models.

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expectations about success in various segments of the labor market) associated with subsequent attainment. To evaluate the degree of selectivity, and to determine whether relationships estimated in the OLS regressions were biased by ignoring selectivity, we estimated the following equations jointly: Y 5 ay 1 bX 1 ZyGy 1 ey

(1a)

X* 5 ax 1 ZxGx 1 ex,

(1b)

where Y is educational, occupational, or income attainment; ay and ax are constant terms; X is observed veteran status; b is a coefficient indicating the relationship between veteran status and attainment; Zy is a vector of covariates for Y; Gy is a vector of coefficients indicating the relationship between the covariates and occupational attainment; X* is a latent construct indicating propensity to enlist in the military such that X 5 1 if X* . 0, X 5 0 if X* , 0; Zx is a vector of covariates for X*; Gx is a vector of coefficients indicating the relationship between the covariates and propensity to enlist in the military; and ey and ex are error terms. The equations are estimated jointly because of the likely endogeneity of military enlistment. That is, men may be self-selected into the military according to expected future attainment (because of differences in ability, motivation or other factors). If this is the case, then the two error terms, ey and ex, are correlated. In essence, the model involves sample selection. Models for sample selectivity have been acknowledged in sociology (Berk, 1983) and are based on the work of Heckman (1979). Our model is slightly different from the commonly estimated selectivity model, though, because the dependent variable is not truncated. Instead, we observe the attainment outcomes of both veterans and non-veterans.14 Madalla (1983, pp. 260–267) has described this problem as a treatment effects model (see also Greene, 1990, pp. 747–748). In this case, military service is the treatment. Like most social programs or treatments, individuals are not randomly assigned to treatment groups. Rather, individuals are presented with a choice of ‘‘treatments’’ and make choices about treatments based on future outcomes associated with placement in a treatment group. In other words, placement in a treatment group is itself endogenous to the outcome(s) being considered. If all covariates influencing the choice of treatment are properly measured, then the effect of the treatment on subsequent outcomes can be measured without bias. We do not believe that we have adequate measures of all factors affecting the choice 14 We elected to model educational attainment with a control for selectivity rather than try to separate education into before and after military service components. We did so because we believe that decisions about military service and education are made jointly. That is, we do not believe that individuals achieve a given level of education, are randomly selected into the military (at least net of the measured predictor variables), and then achieve a certain amount of additional education that depends upon the nature of military service and the benefits associated with such service. Rather, we argue that individuals choose between education and military service depending on the perceived outcomes of each. The selectivity model is an attempt to control for the resulting endogeneity of military service, resulting in what we believe is a better estimate of its effect on education obtained.

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of military service and estimate a treatment effects model in an attempt to capture unmeasured influences on the choice of treatment and thus subsequent outcomes. The model can be estimated through an instrumental variable procedure (because military service is endogenous) or through maximum likelihood procedures.15 The models we report were estimated by using the maximum likelihood procedure available in version 6.0 of LIMDEP (Greene, 1991). The procedure provides estimates of the structural coefficients (b, Gy, Gx) and the correlation, syx, between the error terms. It is the value of syx that indicates the direction and degree of selectivity. Positive values of syx indicate positive self-selection (military recruits would otherwise have higher attainment), while negative values of syx indicate negative self-selection (military recruits would otherwise have lower attainment). It is possible for Zy and Zx to contain identical elements. Identification in this case results from the non-linearity of the relationship between Zx and X. However, for purposes of identification, it is preferable for Zy and Zx to contain some unique elements. Fortunately, we have information in each of the three data bases concerning plans for future military service measured during high school. For the HSB and NLS data, two measures are available: whether the respondent plans to enter the military in the year following high school graduation and whether the respondent plans to make the military a career. For the CDS, the latter measure is available. We make use of these additional variables to predict the likelihood of military service and thus better identify the selectivity model we estimate. RESULTS The values of education obtained, SEI for current job and income for current job by historical period, race and veteran status are presented in Table 2. In each comparison for education and occupational status, white veterans evidence significantly lower attainment than white non-veterans.16 There is a significant difference between the income of veterans and non-veterans in the CDS data but not in the NLS nor HSB data. For African-Americans, there are fewer significant differences.17 Education and occupational status are lower for veterans in the NLS. No other differences are statistically significant. We are hesitant to draw firm conclusions based on the 15 The model may also be seen as a restricted version of an endogenous switching regression model (Greene 1990, pp. 748–750). The restriction comes from the fact that we do not allow the effects of the covariates to vary according to military service. Because we have no reason to expect military service to alter the returns to background characteristics (other than according to race), we estimated the more restricted form of the model. 16 In this analysis, we only pay attention to the difference between veterans and non-veterans in occupational attainment. As such, we do not consider trends over time in occupational status. It is interesting to note, though, that the decrease in occupational status between the period covered by the CDS and NLS data and the period covered by the HSB data. This decline in occupational status is congruent with that reported in the study by Grusky and DiPrete (1990). 17 This is not to be unexpected, though, given the much smaller sample size available for African-American men.

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TEACHMAN AND CALL TABLE 2 Mean Educational Attainment, Occupational Status and Income for Current Job According to Veteran Status CDS Veteran status

Whites All men Veteran Non-veteran

Ed. attn.

Occ. status

3.22 44.04 (2935) (2906) 2.93 37.61 (1231) (1219) 3.45 48.69 (1704) (1687)

NLS

HSB

Occ. Ed. Income Ed. attn. status Income attn.

20556 (2625) 19606 (1103) 21230 (1522)

3.16 (4955) 2.69 (496) 3.21 (4459)

Occ. status Income

45.06 29321 2.69 32.66 14202 (4018) (3577) (1977) (1442) (1325) 37.65 27467 2.48 26.43 14295 (327) (282) (240) (122) (108) 45.71 29479 2.71 33.24 14194 (3691) (3295) (1737) (1320) (1217)

Veteran–non-veteran difference 2.52* 211.08* 21624* 2.52* 28.06* 22012 2.23* 26.81* Blacks All men 2.90 33.24 28551 2.41 27.24 (500) (364) (321) (912) (548) Veteran 2.68 28.39 28321 2.41 25.43 (87) (55) (48) (181) (80) Non-veteran 2.95 34.11 28592 2.41 27.55 (413) (309) (273) (731) (468) Veteran–non-veteran difference 2.27* 25.72* 2271 2.00 22.12

101 13617 (483) 12745 (74) 13773 (409) 21019

* Difference between veterans and non-veterans is significant at p , .05.

information in Table 2, however, given the number of background factors that could account for differences between veterans and non-veterans.18 Accordingly, we turn directly to the multivariate models. The models we estimated are described above. It should be noted, though, that we regressed the log of income on the covariates, rather than income itself. We used log income as the outcome variable because income was seriously skewed to the right. Due to an increasing number of missing values, sample size declines as one progresses from a model for educational attainment to a model for log income. The results from the multivariate models without a control for mental ability are shown in Table 3. For whites, after the introduction of controls for the measured covariates, veteran status remains tied to statistically significant decrements in education in all three data bases (although the educational deficit measured on the bivariate level shown in Table 2 is substantially reduced). These results suggest a detrimental effect of veteran status on education. However, as witnessed by the statistically significant values of syx in all three data bases, there 18 We also note the small number of African-American veterans. We caution readers to recognize that the power to discriminate between veterans and non-veterans is substantially less for AfricanAmerican men compared to white men.

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is substantial negative self-selection of veterans with respect to educational attainment. That is, if they had not entered the military, veterans would otherwise have attained less education than non-veterans. For the CDS data, the control for self-selection reduces but does not eliminate the negative effect of military service on educational attainment. For the NLS and HSB data, the control for self-selection yields a positive, significant effect of military service on education obtained.19 In other words, compared to the level of education veterans would have attained if they had not enlisted, military service acts to increase the amount of education obtained. For African-Americans, there is no evidence of selectivity with respect to educational attainment. In the NLS data, military service is significantly and negatively related to education obtained. In the HSB data, there is no relationship between veteran status and education. With respect to occupational status for whites, the controls for background characteristics and educational attainment explain the veteran–non-veteran difference for the NLS data only. The association between military service and occupational status is reduced in the CDS and HSB data when the controls are introduced, but a significant negative relationship remains. When selectivity is taken into account, the value of syx for the CDS data indicates negative self-selection of veterans according to occupational status. Accounting for this negative self-selection reduces but does not eliminate the relationship between veteran status and occupational attainment that remains after differences on observed background factors are controlled. Thus, veterans of the Vietnam era appear to suffer a long-term deficit with respect to occupational attainment, just as they do for education. For the NLS data, the control for self-selection is nonsignificant and does not change the relationship between veteran status and occupational attainment. For the HSB data, though, the control for self-selection is marginally significant and indicates negative self-selection. When selectivity is controlled, the negative relationship between veteran status and occupational attainment becomes nonsignificant. Moreover, the sign of the coefficient for military service becomes positive. Because of the relatively young age of veterans in the HSB, this pattern suggests that as veterans accumulate greater civilian labor market experience, they may enjoy even greater positive returns with respect to occupational status. For African-Americans, the negative bivariate relationship between military service and occupational status in the NLS data becomes nonsignificant when the controls for background characteristics and educational attainment are instituted. For neither the NLS nor the HSB is there evidence that African-Americans are self selected into the military according to eventual occupational status. For income, the results are similar for both whites and African-Americans in 19 The positive effect of military service on the educational attainment of veterans in the HSB after controlling for selectivity is likely understated given the relatively short follow-up period considered (1980 to 1986). We believe that it is more likely that non-veterans will continue in school beyond 1986 than veterans, increasing the veteran-non-veteran comparison observed in 1986.

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Constant

syx

Occupational status

Education obtained

Expected education

Friend expects college

Grade point average

Mother’s education

Father’s education

Number of sibs

Whites Veteran

Variable

Ed.

2.49* (.065) .97* (.097)

2.08* (.033) 2.01 (.008) .05* (.012) .06* (.015) .24* (.012) .11# (.062) .26* (.016)

.68* (.084) .44* 2935

2.17* (.030) 2.01# (.008) .05* (.012) .06* (.015) .26* (.012) .10 (.061) .26* (.015)

Ed.

Occ.

2.20* (.084) 7.97* (3.084) —c

23.43* (1.04) 2.34 (.251) .81* (.340) .09 (.445) 1.57* (.370) 2.04 (1.93) 1.07* (.490) 8.19* (.562)

4.50* (2.562) .23* 2906

24.42* (.892) 2.35 (.247) .84* (.351) .11 (.445) 1.67* (.385) 1.87 (1.83) 1.01* (.482) 8.33* (.555)

Occ.

CDS Modela,b Log Inc.

2.73# (.397) 2.09 (.066) 2.05 (.120) .31 (.142) 2.22 (.151) 2.21 (.826) .01 (.188) 2.44# (.229) .04* (.01) 2.01 (.112) 98.64 (.110)

98.82* (.792) .03* 2625

2.73* (.277) 2.09 (.075) 2.05 (.109) .30* (.137) 2.21# (.119) 2.14 (.570) 2.01 (.148) 2.43* (.182) .04* (.01)

Log Inc.

.19* (.075) 2.03* (.004) .07* (.013) .03* (.015) .16* (.008) .38* (.023) .23* (.011)

Ed.

2.42* (.066) .84* .95* (.057) (.067) .43* — 4955

2.20* (.033) 2.03* (.004) .07* (.012) .03* (.014) .16* (.008) .40* (.023) .24* (.011)

Ed.

2.19 (2.111) 2.20 (.127) .58# (.333) .13 (.370) 1.91* (.229) 2.65* (.655) .73* (.326) 11.44* (.422)

Occ.

.03 (.082) 27.45* 27.61* (1.644) (1.852) .38* — 4018

2.52 (.974) 2.20# (.117) .58# (.338) .12 (.370) 1.90* (.225) 2.65* (.661) .72* (.320) 11.43* (.397)

Occ.

NLS Model Log Inc.

21.42 (1.075) 2.05 (.053) .09 (.138) 2.11 (.150) .05 (.096) .35 (.254) 2.08 (.123) .210 (.176) .01# (.006) .14 (.105) 100.01* 100.04* (.645) (.666) .02 — 3577

2.16 (.386) 2.05 (.046) .08 (.134) 2.11 (.146) .04 (.088) .35 (.258) 2.09 (.125) .195 (.170) .01# (.006)

Log Inc.

.29* (.132) 2.05* (.014) .04* (.016) .07* (.020) .11* (.015) .06 (.050) .15* (.019)

Ed.

2.38* (.100) 1.16* 1.24* (.103) (.201) .24* — 1977

2.11* (.053) 2.05* (.014) .04* (.017) .07* (.021) .12* (.014) .06 (.044) .15* (.016)

Ed.

4.58 (5.692) 2.04 (.337) 2.17 (.447) .19 (.521) .93* (.396) 1.56 (1.283) 2.24* (.457) 4.64* (.548)

Occ.

2.34# (.176) 6.17* 7.75* (2.680) (3.211) .18* — 1442

24.12* (.937) 2.04 (.352) 2.18 (.456) .14 (.546) 1.03 (.365) 1.53 (1.120) 2.27* (.417) 4.64* (.582)

Occ.

HSB Model Log Inc.

24.96* (2.112) .13 (.208) .07 (.241) 2.96* (.273) .23 (.229) .17 (.701) 2.73* (.255) 22.68* (.318) .01* (.001) .36* (.149) 99.28* 98.72* (1.492) (1.740) .12* — 1325

2.03 (.892) .14 (.194) .07 (.252) 2.95* (.305) .18 (.203) .20 (.614) 2.76* (.234) 22.66* (.329) .01* (.001)

Log Inc.

TABLE 3 Regression of Educational, Occupational and Income Attainment on Veteran Status and Background Variables—Without Control for Mental Ability

20 TEACHMAN AND CALL

2.31 22.14 (1.21) (3.303) .08 .06 (.134) (.188) 2.75 2.66 (.992) (1.117) 2.57 2.56 (.927) (1.114) .56 .57 (.347) (.482) 2.99 2.88 (.971) (1.315) .27 .24 (.531) (.691) 2.161 2.204 (.649) (.910) .03 .04 (.027) (.041) .08 2.05 .24 (.187) (.267) (.369) 1.51* 1.49* 29.45 29.64 97.42* 97.19* (.222) (.258) (5.991) (7.923) (3.110) (3.937) .24* — .39* — .05 500 364 321

2.27* 2.33* 22.65 23.45 (.086) (.145) (2.331) (4.80) 2.01 2.01 2.42# 2.42 (.010) (.010) (.253) (.324) .09 .09 .28 .32 (.071) (.078) (1.923) (2.001) .08 .08 23.10# 23.09 (.075) (.058) (1.814) (2.113) .16* .16* 2.77* 2.78* (.026) (.028) (.665) (.712) .26* .26* 2.04 2.06 (.073) (.073) (1.873) (1.964) .11* .11* 1.63 1.64 (.039) (.044) (1.022) (1.191) 10.20* 10.18* (1.155) (1.363)

2.94 (1.613) .16 (.428) .45 (.724) .89 (.663) 1.00* (.463) .60 (1.432) 1.99* (.496) 6.93* (.858)

5.10 1.36 23.87 (7.410) (1.140) (3.731) .14 2.17 2.16 (.456) (.309) (.322) .41 21.39* 21.39* (.686) (.528) (.584) .92 1.05* 1.09* (.616) (.483) (.527) .96* .25 .17 (.443) (.338) (.363) .58 .64 .51 (1.634) (1.013) (1.185) 1.97* 2.87* 2.81* (.575) (.365) (.415) 6.94* 2.60 2.68 (.772) (.677) (.611) .01# .01# (.003) (.003) 2.17 2.36 .46# (.301) (.379) (.261) 1.28* 1.32* 27.52 25.76 93.25* 94.09* (.138) (.167) (3.744) (4.873) (2.705) (3.061) .19* .26* — .05* — 912 548 483

2.00 .11 (.056) (.219) 2.01 2.01 (.016) (.016) .11* .11* (.028) (.025) .05* .05* (.026) (.023) .09* .10* (.017) (.018) 2.03 2.04 (.056) (.061) .10* .10* (.018) (.021)

a The first model for both educational attainment and occupational status are simple OLS regression models. The second model for both educational attainment and occupational status are estimated jointly with a model for military service using a maximum likelihood estimator. b Standard errors in parentheses. c A dash indicates that there is no measure directly analogous to R2. * p , .05, two-tailed test. # .05 , p , .10, two-tailed test.

R2 N

Constant

syx

Occupational status

Education obtained

Expected education

Friend expects college

Grade point average

Mother’s education

Father’s education

Number of sibs

Blacks Veteran

MILITARY SERVICE AND ATTAINMENT

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the NLS and HSB data.20 There is no relationship between veteran status and income in the NLS data. Nor is there any evidence that veterans are self-selected with respect to future income. Net of the control variables, there is no relationship between veteran status and income in the HSB data. However, for both whites and African-Americans in the HSB data, there is evidence of statistically significant and positive self-selection with respect to income. After controlling for this positive self-selection, the effect of veteran status becomes significant and negative for white men. In other words, net of the control variables and positive self-selection, military service lowers the income of white men. However, this pattern is at least partly due to the young age of men in the HSB. As was the case for occupational status, young veterans are likely at a disadvantage with respect to experience in the civilian labor market. As veterans gain such experience, it is likely that the significant negative effect of veteran status on income will wane. The CDS data indicate a pattern for income different from the NLS and HSB data. The effect of military service in the Vietnam era on income is negative. There is no indication of self-selection into the military with respect to subsequent income, and the effect of military service remains negative after the control for self selection is implemented. In Table 4, we summarize the results obtained after adding mental ability to the models shown in Table 3 for men in the NLS and HSB data. Given that the results parallel those already shown, we show only the effects of veteran status and mental ability. For whites, the only change of note occurs in the model for educational attainment using the HSB data. When mental ability is added to the model, the coefficient for veteran status fails to reach statistical significance after controlling for self-selection. However, significant negative self-selection is still evident in the model. Moreover, this self-selection accounts for the significant negative effect of veteran status on educational attainment that remains net of the measured control variables. Thus, in the HSB data, part, but not all, of the self-selection with respect to educational attainment witnessed in Table 3 can be explained by differences in mental ability. For African-American men in the NLS data, the control for mental ability does not change the effect of veteran status on the measures of attainment net of the measured control variables. Our attempts to estimate a model accounting for self-selection failed, though. We believe that the failure of these models to converge to an acceptable solution is due to the substantial amount of missing data for African-American men on the measure of mental ability. For the model of educational attainment, nearly one-half of the African-American men are missing a legitimate value for mental ability.21 One result of the small sample size is that 20 Note that coefficients from the model for log income are multiplied by 100 in order to ease presentation. 21 Another indicator of problems with the measure of mental ability can be seen in Table 1. Here,

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TABLE 4 Regression of Educational, Occupational and Income Attainment on Veteran Status and Background Variables—With Control for Mental Ability NLS Modela,b

Variable

Ed.

Ed.

Whites Veteran

2.19* .22* (.037) (.085) Mental ability .01 .01 (.015) (.015) syx 2.44* (.075) R2 .45* —c N 3606 Blacks d Veteran 2.36* (.150) Mental ability .11 (.071) syx R2 N

.30*

Occ.

Occ.

2.32 2.66 (1.155) (2.710) 2.02 2.02 (.418) (.420) .01 (.103) .38* — 2908 2.05 (.033) 2.04* (.016)

.46* 221

d

HSB Model Log Inc.

Log Inc.

Ed.

Ed.

Occ.

Occ.

Log Inc.

Log Inc.

.04 21.11 2.12* .18 24.92* 4.106 2.07 25.19* (.440) (1.254) (.056) (.137) (1.674) (6.276) (.941) (2.324) 1.96* 1.97* .09* .09* 1.90# 1.87 .611 .621 (.159) (.155) (.040) (.040) (1.046) (1.027) (.573) (.596) .13 2.29* 2.35# .37* (.130) (.112) (.187) (.160) .06* — .25* — .18* — .12* — 2611 1816 1326 1221 .27 (1.697) 1.28 (.803)

d

.06 221

2.03 (.061) .01 (.016)

.14 21.12 5.37 1.33 24.41 (.211) (1.741) (8.120) (1.231) (3.427) .01 .12 .08 2.05 2.04 (.025) (.327) (.534) (.225) (1.175) 2.26 2.39 .52* (.279) (.383) (.246) .19* — .26* — .06* — 406 767 466

a The first model for both educational attainment and occupational status are simple OLS regression models. The second model for both educational attainment and occupational status are estimated jointly with a model for military service using a maximum likelihood estimator.

b Standard errors are in parentheses. c

A dash indicates that there is no measure directly analogous to R2.

d

Selectivity model failed to converge.

* p , .05, two-tailed test. # .05 , p , .10, two-tailed test.

the model predicting entry into the military (not shown) fits very poorly, yielding a badly identified model of self-selection. The results for African-American men in the HSB data are more stable. Each of the models for self-selection converged adequately. There is no evidence that including the measure of mental ability changes the basic pattern of relationships shown in Table 3. SUMMARY AND DISCUSSION We have investigated the effect of military service on educational, occupational and income attainment for three cohorts of high school students. The period the average scores for mental ability are almost identical for white men between the NLS and HSB data. For African-American men, though, the average score in the NLS data is much higher than the average score in the HSB data. This suggests that for African-American men the pattern of missing values on the measure of mental ability in the NLS is not random—men with low scores are substantially under represented.

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covered includes the Vietnam era and the All-volunteer Force. Below, we summarize and interpret our findings. For African-American men, there is evidence from the NLS data that veterans in the first AVF cohort received less education than non-veterans—a difference that is not explained by differences on background characteristics, mental ability, nor self selection on unobserved variables. We believe that the negative effect of military service on educational attainment during this period is at least partly a function of the increased educational opportunities experienced by non-veteran African-Americans that continued well into the 1970s. As shown in Table 2, African-American veterans in the NLS obtained a relatively high level of education—about as high as white veterans. Nevertheless, non-veterans obtained an even higher level of education. The veteran–non-veteran difference in educational attainment becomes nonsignificant when using HSB data that correspond to a period during which both military and civilian support for higher education waned. There is little evidence to suggest that the occupational status of AfricanAmerican veterans differs from the occupational status of African-American non-veterans. While the status of current jobs is somewhat lower for veterans of the first AVF cohort (NLS), this difference is explained by differences on educational attainment and measured background characteristics. In neither the NLS nor the HSB data is there evidence that African-American men who served in the military are selected on unmeasured characteristics associated with subsequent occupational attainment. This result is consistent with previous research that indicates that the AVF military does not recruit from among less qualified men in the African-American population (Teachman et al., 1993). For AfricanAmerican men, the military’s lack of hiring discrimination, equality of working conditions and the apparent equality of promotion and pay are strong incentives to enlist (Daula, Smith, and Nord, 1990; Philips, Andrisani, Daymont, and Gilroy, 1992). The net result is that the military is a strong competitor with the civilian labor market for the best qualified young African-American men. However, the military does not appear to offer a competitive advantage to those who serve. We recognize, however, that we have data only for the AVF period. It is possible that for earlier periods, when recruitment standards were lower, less advantaged African-American men may have entered the military and benefitted from a bridging environment. Paralleling the case for occupational status among African-American men, there is no evidence that the income of African-American veterans is significantly different from non-veterans. Again, this may reflect the fact that the military is a strong competitor with the civilian labor market for the best qualified young African-American men but does not convey an income premium to those who serve. With respect to the educational attainment of whites, there is substantial negative selectivity into the military. This pattern is consistent with previous

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research (Teachman et al., 1993) that found that the military recruits less qualified individuals from the white population—contrary to the situation for AfricanAmericans. It is important to note, though, that the control for self-selection turns a negative relationship between military service and educational attainment into a positive relationship during the AVF (for both the NLS and HSB data). All else being equal, therefore, the military spurs the educational attainment of young white men during the AVF. Indeed, these results suggest that during the AVF the military has served as a bridging environment for less advantaged white men, although there is no evidence of bridging for African-American men. For the AVF period, there appear to be no negative consequences for occupational attainment associated with military service among white men, at least when selectivity is taken into account. For occupational status observed in the NLS, the educational attainment and background controls are sufficient to account for the negative bivariate relationship between military service and occupational attainment, and there is no evidence of selectivity. For occupational status in the HSB, a negative relationship between veteran status and occupational attainment remains after controlling for differences on educational attainment and background factors. The selectivity control, however, is marginally significant and reverses the sign of the coefficient for veteran status from negative to positive (although not significant). Because the cohort of men from the early 1980s is very young at the point we observe occupational status of current job, we are hesitant to place much emphasis on the negative selectivity control observed in the HSB. It is plausible to expect that negative selectivity is measuring the fact that veterans did not have sufficient time in the civilian labor force to catch up with their civilian peers by the time the last wave of the HSB was conducted. With information on later jobs, it may be the case that no selectivity would be observed. There is little evidence to suggest that white veterans in the AVF era earn less income than non-veterans. In the NLS data, which spans a longer period following military service than the HSB data, veterans have incomes no different from non-veterans and there is no evidence to suggest self-selection. There is positive self-selection in the HSB data that results in a negative effect of military service on income, but we believe this pattern of results is an artifact of the truncated income histories of men in this data base, particularly veterans. As the HSB cohort ages, the veteran–non-veteran differential is likely to diminish. Overall, (white) veterans of the Vietnam era stand out as suffering negative consequences from their military service. The lower educational, occupational, and income attainment of Vietnam veterans cannot be explained by differences on measured background variables. Veterans of the Vietnam era, however, were selected on unmeasured factors negatively related to subsequent attainment. While we cannot be sure, this pattern was likely exacerbated by draft policies, especially policies applicable to high school graduates. Prior to the middle of 1969 when the lottery system was invoked, the draft revolved around a complex

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set of exemptions (Baskir and Strauss, 1978; Card, 1983). Many of these exemptions pertained to higher education and occupations. Given these exemptions and the unpopularity of the war, it is probable that men with higher occupational aspirations avoided military service.22 It is important to note, though, that the control for selectivity does not reduce the effect of veteran status on subsequent attainment to zero—veterans of the Vietnam era experience less attainment than non-veterans. Net of differences on observed and unobserved background characteristics, veterans of the Vietnam era have less education, lower status jobs and make less money than non-veterans. This implies that the military somehow changed these men, or the environment in which they operated, in a fashion that led to lower attainment. It is possible that military service during a very unpopular war might engender psychological stress with long term consequences for success in education and the labor market. If one believes that this stress should be greater for veterans who were drafted or who saw combat in Vietnam, then controls for these variables should reduce the negative effect of veteran status on subsequent attainment. The CDS data contain information on both these variables. In results not reported here, we included these variables in the regression models and noted little change in the estimated coefficients for military service. This reduces (but does not eliminate) our confidence in an explanation based on alterations in social psychological states associated with service during the Vietnam era. With respect to occupational status and income, the available evidence concerning the use of Vietnam veteran status as a negative signal to employers is also slim. While a number of reports appear to document negative attitudes of employers toward Vietnam veterans (Figley, 1978; Figley and Leventman, 1980; Kohen and Shields, 1980; Hall-Sheehy, 1986), there are reports of neutral treatment of Vietnam veterans (D’Anton, 1983; U.S. Congress, 1980). The issue is difficult to measure, as discrepancies between the attitudes and behavior of employers may bias survey results. The problem is compounded by changes in signalling that are likely to occur over time and by veterans’ perceptions of employer hiring practices and thus the jobs they seek.23

22 This argument could be tested if we had information on occupational aspirations. A control for such aspirations should make the control for selectivity nonsignificant. 23 Our results are different from those found by Cohen, Segal, and Temme (1992) who report that the negative relationship between veteran status and occupational attainment can be explained by the lower educational attainment of veterans. While Cohen et al. use methods similar to ours, they use data from an older cohort of Vietnam veterans. While the veterans in the CDS graduated from high school in 1966 and 1967, the veterans in the data used by Cohen et al. graduated from high school prior to 1961. Thus, the Vietnam veterans analyzed by Cohen, Segal and Temme mostly served prior to the massive buildup of U.S. forces in Vietnam and growing unpopularity of the war after 1967. Consistent with Card’s (1983) results, we find that veterans who served during the height of the Vietnam conflict experienced lower occupational attainment, and this pattern cannot be explained by differences in educational attainment. That this is the period of increasingly negative public perceptions of the

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Although the difference is not sufficient to explain the contrast between veterans and non-veterans on occupational status and income, Vietnam veterans also acquired less education than non-veterans of the same era. This negative relationship persists even after accounting for significant negative selectivity with respect to military service and educational attainment. As noted above, one logical explanation for this difference is the rapid increase in support for civilian higher education during the period spanned by the Vietnam war. The relative value of the GI Bill was seriously eroded because of the massive expansion of educational benefits available to non-veterans. Overall, the results indicate the importance of considering historical context when examining the effect of military service on the process of status attainment. We have shown that service in the military can have a significant effect on subsequent socioeconomic attainment. However, the nature of the effect is dependent on the context of events surrounding such service. World War II is an example where military service positively affected the status attainment of millions of American veterans. Through government policies and preferences (i.e., the GI Bill), and perhaps good will generated by successful prosecution of the war, veterans of World War II obtained more education, attained higher occupational status and earned more money than non-veterans (Browning, Lopreato, and Poston, 1973; Cutright, 1974; Fligstein, 1976; Mason, 1970; Xie, 1992). Most likely due to changes in support for civilian education programs that left veterans at a comparative disadvantage, as well as a still ill-defined impact of military service on those who enlisted, the reverse is the case for veterans of the Vietnam era. Men who served during the height of the Vietnam conflict do less well than their civilian counterparts. Given that nearly 20% of cohorts of young men eligible to serve during the Vietnam era entered the military, the effects of veteran status are not localized in a small group of men. There are several arenas for subsequent research concerning the relationship between military service and subsequent socioeconomic attainment. While race and cohort variations in the effect of military service have been found in this paper, the underlying source of these differences remain unidentified. It would be valuable to directly address the extent to which military service alters the social psychological status of young men, whether service affects their educational and occupational aspirations, how responsive veterans are to changes in the GI Bill and the extent to which employers take military service into account when making decisions about hiring and promoting. It would also be useful to have explicit information about the nature of military occupations and how well they translate into civilian jobs. Finally, the growing presence of women in the military makes it critical to obtain more information about the impact of service on their subsequent attainment. military and its involvement in Vietnam lends some credence to the thesis of negative signalling. Certainly, however, the issue deserves closer scrutiny before a clear assessment can be made.

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APPENDIX TABLE A1 Coding of Variables Used in Analysisa Income Occupational status

Veteran

Race Number of sibs Father’s/mother’s education

High school grade point average

Friends’ plans for college Educational plans

Education obtained

Mental ability

Plan to enter the military in year after high school Plan to make military a career

In dollars Duncan SEI scores for first job held for at least six months using 1970 Census occupational codes 0 5 not served on active duty for six months or more 1 5 served on active duty 0 5 black 1 5 white Number of siblings 1 5 some high school 2 5 high school graduate 3 5 some college 4 5 college graduate 5 5 more than 4 years of college 85A 7 5 A and B 65B 5 5 B and C 45C 3 5 C and D 25D 1 5 D and F 0 5 not go to college 1 5 go to college 1 5 less than high school 2 5 high school 3 5 attend trade school 4 5 attend junior college 5 5 attend college 6 5 attend graduate school 1 5 high school graduate 2 5 some college 3 5 college graduate 4 5 more than 4 years of college 1 5 first quartile 2 5 second or third quartile 3 5 fourth quartile 0 5 no 1 5 yes 0 5 no 1 5 yes

a Slightly different questions and coding were used to obtain information in each of the surveys (CDS, NLS, HSB). Detailed coding decisions can be obtained on request.

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REFERENCES Alexander, K., Eckland, B., and Griffin, L. (1975). ‘‘The Wisconsin model of socioeconomic achievement: A replication,’’ American Journal of Sociology 81, 324–342. Angrist, J. (1990). ‘‘Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records,’’ American Economic Review 80, 313–336. Baskir, L., and Strauss, W. (1978). Chance and Circumstance: The Draft, the War and the Vietnam Generation, Vintage Books, New York. Berger, M., and Hirsch, B. (1983). ‘‘The civilian earnings experience of Vietnam-era veterans,’’ Journal of Human Resources 18, 453–479. Berk, R. (1983). ‘‘An introduction to sample selection bias in sociological data,’’American Sociological Review 48, 386–398. Blau, P., and Duncan, O. (1967). The American Occupational Structure, Wiley, New York. Browning, H., Lopreato, S., and Poston, D. (1973). ‘‘Income and veteran status: Variations among Mexican Americans, Blacks and Anglos,’’ American Sociological Review 38, 74–85. Call, V., Otto, L., and Spenner, K. (1982). Tracking Respondents: A Multi-method Approach, Lexington Books, Lexington, MA. Campbell, R. (1983). ‘‘Status attainment research: End of the beginning or beginning of the end,’’ Sociology of Education 56, 47–62. Card, J. (1983). Lives After Vietnam: The Personal Impact of Military Service, Lexington Books, Lexington, MA. Cohen, J., Segal, D., and Temme, L. (1986). ‘‘The educational cost of military service in the 1960s,’’ Journal of Political and Military Sociology 14, 303–319. Cohen, J., Segal, D., and Temme, L. (1992). ‘‘The impact of education on Vietnam-era veterans’ occupational attainment,’’ Social Science Quarterly 73, 397–409. Cutright, P. (1974). ‘‘The civilian earnings of White and Black draftees and nonveterans,’’ American Sociological Review 39, 317–327. D’Anton, M. (1983). ‘‘Personnel officer’s attitudes toward Vietnam era veterans,’’ Journal of Political and Military Sociology 11, 21–34. Daula, T., Alton Smith, D., and Nord, R. (1990). ‘‘Inequality in the military: Fact or fiction?’’ American Sociological Review 55, 714–718. Dale, C., and Gilroy, C. (1983). ‘‘The effects of the business cycle on the size and composition of the U.S. army,’’ Atlantic Economic Journal 11, 42–53. Dale, C., and Gilroy, C. (1984). ‘‘Determinants of enlistments: A macro-economic time-series view,’’ Armed Forces and Society 10, 192–210. DiPrete, T., and Grusky, D. (1990). ‘‘Structure and trend in the process of stratification for American men and women,’’ American Journal of Sociology 96, 107–143. DeTray, D. (1982). ‘‘Veteran status as a screening device,’’ American Economic Review 72, 133–142. Duncan, O., Featherman, D., and Duncan, B. (1972). Socioeconomic Background and Achievement, Seminar, New York. Eitelberg, M., Laurence, J., Waters, B., and Perlman, L. (1984). Screening for Military Service: Aptitude and Educational Criteria for Military Entry, Office of the Assistant Secretary for Defense, Washington DC. Elder, G. (1985). Life Course Dynamics: Trajectories and Transitions, 1968–1980, Cornell Univ. Press, Ithaca, NY. Featherman, D., and Hauser, R. (1978). Opportunity and Change, Academic, New York. Figley, C. (1978). ‘‘The legacy of Vietnam,’’ American Legion Magazine 105, 16–18. Figley, C., and Leventman, S. (1980). ‘‘Introduction: Estrangement and victimization,’’ in Strangers at Home: Vietnam Veterans since the War (C. Figley and S. Leventman, Eds.), pp. xxi–xxxi, Praeger, New York. Fligstein, N. (1976). The G.I. Bill: Its Effects on the Educational and Occupational Attainments of U.S. Males 1940–1973, Center for Demography and Ecology Working Paper 76–9, Madison, WI.

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Gade, P., Lakhani, H., and Kimmel, M. (1991). ‘‘Military service: A good place to start,’’ Military Psychology 3, 251–267. Greene, W. (1991). LIMDEP Users Manual, Econometric Software, New York. Greene, W. (1990). Econometric analysis, Macmillan, New York. Grusky, D., and DiPrete, T. (1990). ‘‘Recent trends in the process of stratification,’’ Demography 27, 617–638. Hall-Sheehy, J. (1986). ‘‘The unknown Vietnam vet manager,’’ Harvard Business Review 64, 117–121. Hauser, R. (1990). ‘‘The decline in college entry among African Americans: Findings in search of explanations,’’ in Race and Politics in American Society (P. Sniderman, P. Tetlock, and E. Carmine, Eds.), Stanford Univ. Press, Stanford. Hauser, R., and Anderson, D. (1991). ‘‘Post high school plans and aspirations of Black and White high school seniors: 1976–86,’’ Sociology of Education 64, 263–277. Hauser, R., and Featherman, D. (1977). The Process of Stratification, Academic, New York. Heckman, J. (1979). ‘‘Sample selection bias as a specification error,’’ Econometrica 47, 153–161. Hexter, H., and El-Khawas, E. (1988). Joining Forces: The Military’s Impact on College Enrollments, American Council on Education, Washington DC. Hogan, D., and Astone, N. (1986). ‘‘The transition to adulthood,’’ Annual Review of Sociology 12, 109–130. Jencks, C., Crouse, J., and Mueser, P. (1983). ‘‘The Wisconsin model of status attainment: A national replication with improved measures of ability and aspiration,’’ Sociology of Education 56, 3–19. Laurence, J., Ramsberger, P., and Gribben, M. (1989). Effects of Military Experience on the Post-service Lives of Low-Aptitude Recruits: Project 100,000 and the ASVAB Misnorming, HUMRRO, Alexandria, VA. Levy, F. (1987). Dollars and Dreams: The Changing American Income Distribution, Russell Sage Foundation, New York. Little, R., and Fredland, J. E. (1979). ‘‘Veteran status, earnings and race,’’Armed Forces and Society 5, 244–260. Kohen, A., and Shields, P. (1980). ‘‘Reaping the spoils of defeat: labor market experiences of Vietnam-era veterans,’’ in Strangers at Home: Vietnam Veterans since the War (C. Figley and S. Leventman, Eds.), pp. 118–211, Praeger, New York. Madalla, G. S. (1983). Limited-dependent and Qualitative Variables in Econometrics, Cambridge Univ. Press, Cambridge. Magnum, S., and Ball, D. (1987). ‘‘Military skill training: Some evidence for transferability,’’ Armed Forces and Society 5, 219–242. Magnum, S., and Ball, D. (1989). ‘‘The transferability of military-provided occupational training in the post-draft era,’’ Industrial and Labor Relations Review 42, 230–245. Mare, R., and Winship, C. (1984). ‘‘The paradox of lessening racial inequality and joblessness among Black youth: Enrollment, enlistment and employment, 1964–1981,’’ American Sociological Review 49, 39–55. Marini, M. (1984). ‘‘The order of events in the transition to adulthood,’’ Sociology of Education 57, 63–84. Martindale, M., and Poston, D. (1979). ‘‘Variations in veteran/nonveteran earnings patterns among World War II, Korea and Vietnam war cohorts,’’ Armed Forces and Society 5, 219–243. Moskos, C. (1981). ‘‘Making the all-volunteer force work,’’ Foreign Affairs 60, 17–334. Mason, W. (1970). On the Socioeconomic Effects of Military Service, Unpublished doctoral dissertation, Department of Sociology, University of Chicago. National Opinion Research Center. (1986). High School and Beyond 1980 Senior Cohort Data File Users Manual, Base Year Through Second Follow-up, Office of Educational Research and Improvement, U.S. Department of Education, Washington, DC. Otto, L., and Haller, A. (1979). ‘‘Evidence for a social psychological model of the status attainment process,’’ Social Forces 57, 887–913.

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Otto, L., Call, V., and Spenner, K. (1981). Design for a Study of Entry into Careers, Lexington Books, Lexington, MA. Philips, R., Andrisani, P., Daymont, T., and Gilroy, C. (1992). ‘‘The economic returns to military service: Race–ethnic differences,’’ Social Science Quarterly 73, 340–359. Riccobono, J., Henderson, L., Burkheimer, G., Place, C., and Levinsohn, J. (1981). National Longitudinal Study: Base Year (1972) Through Fourth Follow-up (1979) Data File Users Manual, Center for Educational Research and Evaluation, Research Triangle Institute, Research Triangle Park, NC. Rindfuss, R., Gray Swicegood, C., and Rosenfeld, R. (1987). Disorder in the life course: How common and does it matter?’’ American Sociological Review 52, 785–801. Rothbart, G., Sloan, L., and Joyce, K. (1981). ‘‘Educational and Work Careers: Men in the Vietnam Generation,’’ in Legacies of Vietnam: Comparative Adjustment of Veterans and their Peers (A. Egendorf, Ed.), Vol. 2, U.S. Government Printing Office, Washington DC. Schwartz, S. (1986). ‘‘The relative earnings of Vietnam and Korean-era veterans,’’ Industrial and Labor Relations Review 39, 564–572. Segal, M. (1986). ‘‘The military and the family as greedy institutions,’’ Armed Forces and Society 13, 9–38. Sewell, W., Hauser, R., and Wolf, W. (1980). ‘‘Sex, schooling and occupational status,’’ American Journal of Sociology 86, 551–583. Spenner, K., Otto, L., and Call, V. (1982). Career Lines and Careers, Lexington Books, Lexington, MA. Stevens, G., and Featherman, D. (1981). ‘‘A revised socioeconomic index of occupational status,’’ Social Science Research 10, 364–395. Teachman, J., Call, V. R. A., and Segal, M. (1993). ‘‘The selectivity of military enlistment.’’ Journal of Political and Military Sociology 21, 287–309. U.S. Congress. (1980). Myths and Realities: A Study of Attitudes toward Vietnam Era Veterans, Committee Print 89, U.S. Government Printing Office, Washington DC. U.S. Bureau of the Census. (1990). School Enrollment—Social and Economic Characteristics of Students: October 1988 and 1987, Current Population Reports, Series P-20, No. 443, U.S. Government Printing Office, Washington DC. U.S. Bureau of the Census. (1991). School Enrollment—Social and Economic Characteristics of Students: October 1989, Current Population Reports, Series P-20, No. 452, U.S. Government Printing Office, Washington DC. Xie, Y. (1992). ‘‘The socioeconomic status of young male veterans, 1964–1984,’’ Social Science Quarterly 73, 379–396.

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