Occupations after WWII: The Legacy of Rosie the Riveter. Andriana Bellou and Emanuela Cardia * Université de Montreal. June, 2014.

Transcription

1 Occupations after WWII: The Legacy of Rosie the Riveter Andriana Bellou and Emanuela Cardia * Université de Montreal June, 2014 Abstract WWII induced a dramatic increase in female labor supply, which persisted over time, particularly for women with higher education. Using Census micro data we study the qualitative aspects of this long term increase through the lenses of the occupations women held after the war. Almost two decades upon its end, we find that WWII had lasting effects on the occupational landscape. It entailed a significant shift towards blue-collar occupations, and in particular services, for women who were of working age during the war and to a decline in their likelihood of working in the clerical sector. The effects spilled over to the next generation of women who were too young to be working at the time of the war. This cohort was instead more likely to be working in clerical and professional/managerial occupations as well as in manufacturing, and much less likely to be working in services. The entry of these young women in white-collar jobs matched the decreased presence of the older cohort in these occupations, suggesting that WWII changed the long-term distribution of women across occupations and possibly, that women did not massively quit Rosie the Riveter jobs after the war. * Other affiliations: CIREQ, CIRANO, IZA (Bellou) & CIREQ (Bellou and Cardia). Contact information: andriana.bellou@umontreal.ca and emanuela.cardia@umontreal.ca 1

2 1. Introduction The general belief is that WWII had an important impact on the participation of women in the labor market. Prior to the war, married women were discouraged from working and in many cases there were policies in place not to hire or keep them once they married. These policies started to disappear in the early 1940s and had become very uncommon by the 1950s (Goldin, 1991). With nearly 16 million of men drafted, the shift in labor supply due to them leaving the market created an important shortage of manpower. This, together with a sense of patriotic duty, led to an unprecedented entry of women in the workforce not only to provide necessary services and goods, but also to contribute to war production. Despite this, the overall impact of the war on female labor market prospects remains unclear and has been the subject of scholarly controversy among historians. For some, like Chafe (1972), WWII was a watershed event that transformed the economic outlook of women. For others, like Campbell (1984), the direct changes were less dramatic, as - when men returned - many of the jobs offered to women during the war were taken away and a significant portion of the wartime female entrants exited the market. It is only recently that economists have started studying the effects of the war on women s labor supply using individual micro data. The overall evidence concords that WWII increased the latter substantially (Goldin, 1991; Acemoglu, Autor and Lyle, 2004; Fernandez, Fogli and Olivetti, 2004). While Goldin (1991), using the Palmer Survey data until 1950, concludes that these effects were rather transitory, more recently, Goldin and Olivetti (2013) show that long-run implications of WWII on women s labor supply are substantial and driven (in the short run as well as in the long run) almost exclusively by the group of women with at least a high school degree. These results seem to provide some support to the watershed view of WWII. If WWII was indeed a watershed event, it is reasonable to expect that it led not only to higher employment but also to significant gains in terms of the type of occupation women held, skilled versus unskilled, to reduced barriers to entry for married women and/or to a decrease in the gender earnings gap. One popular presumption is that after the war women left Rosie the Riveter occupations while they kept clerical, teaching and other white-collar jobs (Milkman, 1987; Kennedy, 1999; Goldin, 1991, Goldin, 2

3 1994). 1 Since the majority of women with at least a high school degree were employed in white-collar occupations (Goldin and Olivetti, 2013) and the war increased participation of this group, one might credit WWII for contributing to an expansion of female employment in professional/managerial and clerical sectors. In fact, between 1940 and 1960 women increased considerably their presence in clerical occupations, only negligibly in professional/managerial, while markedly decreased it in manufacturing. However, these are average shares and may reflect secular trends in place since the start of the century. If we disaggregate by age group (Table 1), the picture that emerges is different and suggestive of agespecific trends in manufacturing. 2 The share of all women 35 to 54 years old employed in this sector (and likely treated by the war) remained fairly stable over the two decades, while it decreased for women aged 18 to 34, most of them too young to be working during WWII. 3 These changes could suggest that the war might have changed the distribution of women across occupations and possibly, that women did not massively quit Rosie the Riveter jobs after the war. 4 Such potentially important transformations may have taken place for several reasons. Women were drawn into the wartime economy in large numbers, occupied various positions, and presumably accumulated valuable experience and market skills. Some of these jobs were of Rosie the Riveter - type, but women also substituted men in a wide array of white-collar occupations for which they had qualifications but may have been previously discouraged from working in. These acquired skills and work experiences, coupled with a possible gradual change in attitudes regarding the economic role of women, 1 Using the Palmer survey, Goldin (1991) finds that about half of the wartime female entrants left the labor market sometime after December Henceforth, the terms manufacturing and operatives will be used interchangeably. 3 Our calculations in Table 1 are based on a sample of white women, born in the United States, who were employed at the survey date and reported an occupation. The reference population for our tabulations is the employed agespecific female population. 4 When war production started, there was resistance in hiring women. However, as early as the spring of 1941, Herman (p. 262) reports that articles in magazines like the American Machinist and Business Week were describing stories of women being trained to handle even the most complex machinery. The famous Rosie the Riveter was painted by Norman Rockwell for the May cover of The Saturday Evening Post, with a riveting gun on her lap and her foot set on top of Mein Kampf, to inspire women to become wartime workers. Rosie the Riveter became the patriotic image of a working woman, created to encourage women to take up typical man manual jobs such as riveting. Riveting was actually a high-skill occupation and Kennedy (1999) suggests that the most typical jobs for women were low-skilled, such as welding. 3

4 might have enhanced their opportunities post-war and strengthened their presence even in more traditionally male-dominated sectors. 5 After the war, although many returning veterans may have taken back their old jobs, a significant share had interrupted their schooling and used G.I. Bill benefits to further their education (Bound and Turner, 2002; Stanley, 2003). This, together with war-related injuries, may have also extended the period women remained in the labor market. In addition, further complicating the impact of the war on labor markets, the GI Bill has been credited for increasing the educational attainment of returning men thereby changing their working potential in the market. As of now however, and to our knowledge, little is known about the long term impact of the war on the occupations women kept or more easily re-entered after the war ended. Goldin (1991), using the Palmer surveys, provides some information on the occupations married employed women 35 to 64 years old in 1950 held during WWII. As her sample, though, stops in 1950, no firm conclusions can be drawn from that study about the potentially lasting effects of WWII on the occupational distribution. More recently, Goldin and Olivetti (2013) explore whether the war s effect on female participation (weeks worked) extends to later decades (1960) but they do not identify how these effects were realized in terms of occupations. This paper aims at shedding light on this question and understand the implications of the war on the occupational distribution of women who were of working age at the time. What was the legacy of Rosie the Riveter jobs? What happened to women who entered various occupations to replace men who joined the Armed Forces? Did the war shape the occupational choices of younger generations of females, who were too young to have entered the market prior to its conclusion? To attempt answering these questions, we exploit Census information on occupations between 1940 (pre-) and 1960 (post-war). This data can provide important information, yet unused, that can help us gain some insights on the qualitative impact of the war on the economic outlook of women. We use this information to examine whether the war made a significant difference in the type of occupations women held before and after this event. We focus on its long term effects to allow sufficient time for the 5 The expression male-dominated is used henceforth to characterize occupations with typically higher employment shares of men relative to women. Operatives is one such example. 4

5 labor market to settle after the reintegration of veterans and for potential shifts in social norms to influence the perception of employers towards female workers. To achieve this we compare changes within states in the presence of women in five major occupation groups between 1940 and 1960 using the share of 18 to 44 years old registered men who were drafted or enlisted for the war as a measure of the decline in male labor supply induced by WWII. This identification strategy is akin to Acemoglu et al. (2004). We focus on two cohorts: women 35 to 44 and 45 to 54 years old respectively in The first cohort was 17 to 26 in 1942, right after the Pearl Harbor attack and the U.S. declaration of war to Japan. This cohort includes a large share of women who may have completed their education; some of them may not have been married, had children or started working; many decisions had still to be made. The older cohort was 27 to 36 years old in 1942, more likely to be married, have children and have made choices about whether to work or not and in which occupations. According to Goldin and Olivetti (2013), WWII had lasting effects on the labor supply of both groups. 6 Our results show that the two cohorts were permanently affected, in similar ways. In states with higher mobilization rates, the war permanently tilted their occupational paths towards blue-collar occupations, and predominantly services. The shift towards lower-skill jobs for wartime female workers could be related to the lower education received by some of them as a result of the war. As job opportunities in various sectors arose during the large scale mobilization, many women interrupted their schooling in order to enter the work force. The lack of higher education significantly limited their post- WWII labor market prospects. Furthermore, there is some limited persistence in their presence in manufacturing Rosie the Riveter - type of jobs, which suggests that some women who entered traditionally male-dominated occupations during the war, did not leave them or more easily re-entered or entered them later on. Finally, the war substantially decreased the likelihood that these cohorts work in 6 In contrast to Goldin and Olivetti (2013), we will not study the long term impact of WWII on female employment across occupations by the level of educational attainment of the respondent. This is because the latter can be endogenous to the war, especially for the younger cohort of women we examine. For more recent evidence on the impact of WWII on female education see Jaworski (2014). 5

6 the clerical sector. For men, instead, we find no significant long term effects on their distribution across occupations. The occurrence of these war-induced occupational patterns more than a decade after the war ended raises the question of whether this major event also permeated occupational choices of much younger generations, who could not have worked during the war. To answer this question, we extend our analysis to women 18 to 29 years old in 1960, who turned working age after WWII s end. We find that, in high mobilization states, their presence significantly increased in professional/managerial and clerical occupations but declined in the services. These patterns match the absence of the older cohorts of women from the former (clerical and professional/managerial) and their strong presence in the latter (services). Younger cohorts are also more likely to work in manufacturing-type jobs following the steps of the wartime Rosies. Looking at the overall long term impact of the war on female employment (18 to 54 year old women) across occupations, we find that these matching patterns entailed no overall change in their likelihood to be in manufacturing, or professional/managerial occupations. In these occupations there seems to have been a zero-sum redistribution across cohorts. The war is associated instead with an overall decrease in the likelihood of female work in services and an overall increase in the likelihood of employment in clerical jobs. The remainder of the paper is organized as follows. Section 2 presents the data and descriptive statistics and Section 3, the econometric methodology. Section 4 presents our main results. Section 5 discusses the long term implications of WWII for the occupational choices of men as well as of younger generations of women, who could not have worked during the war. Finally, Section 6 concludes. 2. Data and Descriptive Statistics Our main data sources are the 1940 and percent IPUMS files (Ruggles et al. 2010). Following Goldin and Olivetti (2013), we restrict the analysis to white women, born in the United States and not residing in institutional group quarters. To insure greater exogeneity, as in Fernandez et al. (2004) and in Goldin and Olivetti (2013), we use the state of birth as the reference state to establish a link 6

7 between the mobilization rate of men and women s occupational presence. We focus on two cohorts: women 35 to 44 and 45 to 54 years old respectively in These women were 15 to 34 years old in 1940 and hence were directly affected by the war as they could have entered the labor market in 1942 just after the official entry of the U.S. in the war. As in Acemoglu et al. (2004), Fernandez et al. (2004) and Goldin and Olivetti (2013), we employ state-level WWII mobilization rates for registered men 18 to 44 years old to measure the effect of the war. The latter reflect cross-state variation in the reduction in the labor supply of men who were drafted to serve in the Armed Forces. We examine the effects of the war on five occupation groups: professional and managerial (henceforth professional/managerial ), clerical, operatives and crafts (henceforth operatives/crafts ), services and other. The latter is a residual category which includes sales, laborers and farmers. We also consider two aggregates: white-collar for the first two occupation groups and blue-collar, for the remaining. 7 Table 1 begins the analysis by presenting female employment shares for the two sample years across four main occupation groups and by age. As already pointed out in the previous section, during the period we examine the clerical sector experienced the greatest expansion, while services uniformly contracted. Female employment in professional/managerial occupations remained stable as the increased presence of younger women was counteracted by the exit of older cohorts. While the share of women working in operatives and crafts overall declined, the age-specific statistics show that this was primarily driven by the younger women. The employment shares of the older female workers, the Rosies of WWII, experienced a mild decline. In subsequent sections, we examine whether these occupational shares were systematically influenced by WWII, while accounting at the same time for potentially confounding aggregate trends. Table 2 follows Acemoglu et al. (2004) in dividing states into three groups on the basis of WWII mobilization rates and calculating the means of female occupation shares in each group in 1940 and This exercise serves to detect whether there is any systematic correlation between WWII mobilization 7 We did not include occupations that were not present in the census in both decades. One example is accounting, which was therefore excluded. 7

8 rates and pre-wwii (1940) female occupational shares. The existence of such a relationship could threaten the validity of our identification strategy detailed in the following section. As the raw data tabulations in Table 2 reveal, there are no substantial differences in occupational shares across low, medium and high mobilization states for neither of the two cohorts of women. To control for possible preexisting trends that could invalidate our identification strategy (detailed in the following section), we include as covariates the shares of men working in each of the considered occupations in Econometric Specification To examine the long term impact of WWII on the likelihood that a woman i from cohort j in state s in year t is present in occupation k (as opposed to the baseline occupation ), we pool 1940 and 1960 data and estimate multinomial logit models of the following structure: ( ) (1) This model treats participation to each occupation group as a choice among multiple alternatives and takes into account the overall underlying occupational structure, which is likely varying over time. We estimate two main versions of specification (1). In the first one, being out of the labor force is considered as a choice, and is our reference category. We believe this is a relevant formulation as the decisions to enter the labor market during the war and to enter a given occupation might have been very closely linked. 8 In the second one, we focus on the employed population and we study the choice among various occupations as a function of the WWII mobilization. In this case, the reference category is clerical. Mob is the mobilization rate of men in the woman s state of birth s. The coefficient of interest is and measures whether in states with higher mobilization during WWII women experienced greater long term changes in their likelihood of being present in different occupations relative the reference group. X is a vector of 1940 state covariates: the share of males who were farmers, the share of non-white 8 Mulligan (1998), using data from a March 1944 national longitudinal survey conducted by the BLS, shows that industrial or occupational switches by women between December 1941 and March 1944 were fairly unimportant. Instead sizeable shifts from out of the labor force and into particular occupation groups took place outnumbering any switches between broadly defined industries. 8

9 males and male average education. These covariates, identified by Acemoglu et al. (2004), are included in order to account for confounding factors at the state level that might be correlated with mobilization rates as well as the outcome variable. Since the dependent variable is female occupational participation, we also include the 1940 share of males employed in defense-related industries and the 1940 share of men working in other occupations. 9 This is to account for initial cross-state differences in the demand for female labor in occupations/industries directly related to the war. Employment in 1940 in defense-related industries could reflect pre-existing state defense spending differences. During the war, the U.S. massively converted its industrial base to produce armament and war related goods. This production represented nearly two thirds of all Allied military equipment used in WWII (Herman, 2012). It is possible, then, that the regions experiencing this substantial transformation relied differentially on female workforce for production compared to the less affected areas. Moreover, while no profession received a blanket deferment, local draft boards had in practice a great deal of discretion and were allowed to provide exemptions from the draft on the basis of the relevance of the registrant s occupation for the nation. Men necessary in their civilian activity, national defense and to farm labor received a lot of deferments. Engineers and scientists, for instance, were considered as critical for homefront, wartime industries while lawyers were in demand for intelligence tasks in the military and for their legal training in the military justice system (Elder et al., 1999). In sum, occupational expertise was an important criterion for military induction and therefore prewar state differences in male occupational distributions likely determined both mobilization rates and demand for female labor across occupations. All aggregate controls are matched on the basis of the individual s state of birth and are interacted with a 1960 year dummy. D is a vector of individual characteristics which includes dummies for age, state of birth, and state of residence in order to account for cross-state migration. is a dummy for the year 1960 and any individual covariate, with the exception of state effects, is interacted with this time effect. 9 To define defense industries we follow Acemoglu et al. (2004). Defense industries correspond to IPUMS 1950 industry codes

10 Year effects control for unobservable factors that can systematically influence occupational shares uniformly across cohorts and states. Finally, sample line weights are employed in all calculations and standard errors are clustered by state of birth and census year. The identification strategy we employ essentially relies on variation in draft rates and occupational participation within states over time in order to gauge the effect of WWII on the presence of women across occupations. This methodology controls for any time invariant state characteristics that might be systematically correlated with mobilization rates as well as the outcomes of interest. The identifying assumption is that conditional on all the covariates as well as state and year fixed effects, mobilization rates are random. The lack of a systematic relationship between mobilization rates and prewar female occupational outcomes suggested by the statistics presented in Table 2, as well as the inclusion in the model of important pre-war state characteristics, provide some confidence in favor of the causal interpretation of our estimates. 4. Occupations and WWII The estimates from specification (1) are presented in Table 3. The sample used in Columns 1 and 4 includes all females in the relevant cohort while in Columns 2 and 5 only married females. In both cases, out of the labor force is the reference category. Married women were considerably constrained in their labor supply prior to 1940 due to the existence of marriage bars. As these loosened during the 1940s, married women altered significantly their short and long run work behavior in response to the war (Goldin and Olivetti, 2013). Our estimates will inform us of what this meant in terms of occupations. Columns 3 and 6 display estimates when the sample is restricted to the employed population. Clerical work is the omitted category in the latter case. Finally, Appendix Tables 1a and 1b report estimates from two robustness exercises for the baseline specification (total and employed sample). We check the 10

11 sensitivity of our results to the addition of region-year interactions between four Census region dummies and a 1960 dummy as well as to the exclusion of southern states. 10 The results overall suggest that the war permanently tilted the female occupational distribution for the cohorts who were directly treated towards low-skill, low-paying, brawn-intensive jobs. The vast majority of these women were less likely to be employed in white-collar occupations, and among these especially in clerical jobs, and significantly more likely to work in services or other low-skill jobs or to remain out of the labor force. The shift towards blue-collar occupations is a finding that also survives our robustness checks. Regarding their participation in manufacturing, we find little evidence of their presence by This occupation is more predominant in the southern states (see Appendix Tables) and among the oldest cohort of 45 to 54 year olds. This suggests that some of the Rosies of the war may not have entirely abandoned the occupations they entered in large numbers when men were mobilized. It is also possible that some of the women who left war-related manufacturing occupations when men returned, entered subsequently the service sector, where their presence is indeed more pronounced (also see Goldin and Olivetti, 2013). Evaluated at the median mobilization rate (0.476), our results suggest a 23 and 17 percent probability for 35 to 44 and 45 to 54 years old women, respectively, to be employed in services, conditional on employment. Finally, their decreased likelihood of being present or entering clerical occupations in high mobilization states indicates that the war did not directly contribute to the trend towards rising female shares in clerical work that the raw data reveal during this period (Table 1). The increased likelihood for women of working age during WWII of working in blue-collar occupations is consistent with recent evidence that WWII decreased educational attainment among women who were exposed to mobilization while in schooling age. These effects are more evident among cohorts born between 1915 and 1931 but also extend to cohorts born as early as in the 1900s (Jaworski; 2014). The unprecedented demand of workers in traditionally male-dominated sectors due to the large scale mobilization attracted many women into the market at the expense of not completing their 10 There are 16 states that are excluded: Delaware, Virginia, Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Texas, Kentucky, Maryland, Oklahoma, Tennessee, and West Virginia. 11

12 education. 11 They took up mostly low skill jobs, such as in manufacturing, which did not require a high school diploma. The lack of higher education as well as the return of the veterans limited subsequently their long term labor market options, even in sectors where they had acquired some experience during the war. 5. Discussion Overall, Table 3 suggests that in higher mobilization states women s labor markets underwent important changes. If anything, the war seems to have contributed to a deterioration in their occupational standing by strengthening their presence in tougher, low-skill, brawn-type jobs. 12 What about, however, their position against men? The vast majority of men interrupted their labor market careers and schooling to serve in the Armed Forces. When they returned, they faced a changing labor market: more women in the workplace, competition and possibly fewer opportunities in some occupations as well as better educational prospects due to the GI Bill. At the same time, after a long period of depression-related stagnation and war-related interruption in the production of many consumption goods, the after-wwii economy was quickly recovering. A decade after the end of WWII and after reintegration of veterans in the workforce was presumably completed, how did labor markets adjust? Did female workers permanently crowd-out returning veterans from certain jobs or did the latter simply re-occupy their prewar jobs forcing women to quit? The effects were likely different depending on whether the veterans were young or old; the older the more likely they resumed their old jobs. In the next section we examine whether the war induced gender-specific changes within different occupations. This will also allow us to assess whether the increased presence of young women in services can be ascribed to men exiting these 11 Jaworski (2014) reports that among women 14 to 19 in 1944 and not in school, 40.7% were employed in manufacturing, 19.9% in finance and service, 16.8% in retail trade, 4.5% in agriculture and the remaining in other sectors. 12 Unless, of course, it altered their economic outlook by improving their gender earnings gap and/or the skillrequirement of their job, within the occupation. The Census provides no information to assess the latter. With respect to the former, in an omitted analysis but available upon request, we did examine the potential long term effects of WWII on the gender earnings gap across occupations for white men and women who had worked more than 40 weeks in the past year. We found no evidence that WWII entailed an improvement or a deterioration in the relative pay between men and women between 1940 and 1960 in any of the major occupation groups we have considered. We found, however, that it induced a significant real wage decline for men in services, operatives/crafts and professional/managerial occupations. 12

13 occupations and whether the decreased presence of women in the clerical sector, can instead be ascribed to men entering. However, neither of these are necessary implications, as the changes in the occupational shares could be due to redistributions across occupations and/or different cohorts, or demographic groups not considered here. 5.1 Occupational Crowding-out Table 4 reports estimates of specification (1) using a sample of white men, 35 to 54 years old in 1960 who were employed. We use the same set of covariates as before with the exception of the 1940 state shares of men in various occupations. We do control, however, for the 1940 male shares in defenserelated industries. The empirical evidence from Table 4 suggests that the likelihood of male employment in various occupations relative to clerical did not substantially change between 1960 and 1940 as a function of the war. It is not evident that men are less likely to work in services in states with higher mobilization, which would be consistent with women crowding-out men from these jobs. We neither observe that men are more likely to be present in clerical work relative to other occupation groups, which would be consistent with men crowding-out women from these positions. The same applies to manufacturing-type occupations. An exception is perhaps employment in professional-managerial jobs, where men are less likely to work. This result, however, is only significant at the 10% level. Overall these results indicate that the long term implications of WWII on the presence across occupations of women who could have worked during the war are not due to crowding-in or crowding-out forces across gender. It is still possible that the return of the veterans implied a largely immediate (as opposed to a gradual, long term) exit/crowding-out of women from certain jobs, such as manufacturing, and that the pre-war steady-state was fairly quickly re-established in these occupations before The displaced women were instead pushed towards lower-end occupations, a trend amplified by their educational downgrading also induced by the war. This established occupational pattern, a result of WWII, may have persisted over time and until

14 5.2 WWII and occupational participation of post-wwii labor market entrants The shift in female employment more than a decade after the war s end towards services, other low-skill occupations and sporadically in certain areas in manufacturing and away from clerical work is interesting and naturally generates the question of whether the war also permeated the occupational choices of younger generations of workers. If it did, in which direction? Is it possible that the war altered stereotypes and attitudes regarding the role of women in the workforce? If such a change in perceptions indeed occurred, then one would expect persistent effects of the war on the labor market behavior of women who turned working age after WWII had ended. In Table 5, we study the occupational participation of white women who were 18 to 29 years old in 1960 and therefore 3 to 14 in Since these women could not have participated in the workforce during the war as they were too young but instead could have entered in its aftermath, their occupational choices over time would have only been indirectly affected by this event. Our estimates indicate that the war affected the occupational standing of this younger generation. In high mobilization states it significantly increased their presence in clerical, professional/managerial and manufacturing occupations (relative to remaining out of the workforce), while decreased it in services and in other residual occupation groups. Quantitatively, our estimates suggest that a 18 to 29 years old woman, in a state with the median mobilization rate, has a 15 percent probability of working in manufacturing, 2 percent probability of working in services, 9 percent in professional/managerial and close to 20 percent in clerical. Overall, it seems that the war implied a shift towards white-collar, higher-end jobs for this younger generation. These results are robust to the addition of region-year interactions and to the exclusion of southern states (Appendix Table 1c). Interestingly, none of these effects extend to younger men (Columns 3 and 4). Since the mobilization did not substantially alter the occupational presence of younger and older men in the long run, one explanation for the observed patterns among the youngest generation relies on the substitutability between younger and older women in production. In particular, the employment shares of 18 to 29 year olds could have matched changes in the shares of older cohorts, and these cohort- 14

15 dependent redistributions were war-related. 13 The war created excess demand for manpower in certain sectors that were more vital to the war effort. It also called for higher female participation in states with higher draft rates. Women who could work entered high demand occupations, mostly in manufacturing and services and perhaps less in clerical. Women who were 35 to 44 years old in 1960, were 20 to 29 years old in 1945, still in their prime childbearing years, and as a consequence of the war could have interrupted their schooling, put on hold marriage decisions and/or having children. At the war s end, many of these women exited the market, either permanently or temporarily to have children, and when they returned their lack of higher education probably restricted their entry into higher-end jobs (professional, managerial or clerical positions) that required more human capital. Moreover, the needs of the post-war economy also shifted production away from armaments and towards consumption goods. These structural changes likely took place differentially across states and depending on the extent of mobilization or war production during the war. While men largely re-occupied their pre-war jobs in the more male-dominated sectors, the newly-created demand shortages in professional/managerial and clerical sectors had to be filled-in by new and better-educated entrants. Young women may have filled-in positions in occupations older women were less likely to be present in or qualify for. They may have also replaced veterans who because of the war had interrupted their careers and lacked the human capital necessary to re-enter higher-education occupations. The war could have also partly modified perceptions about the women s potential in the market allowing qualified females to come closer to breaking the glass-ceiling in managerial and professional positions. We further explore the hypothesis of substitutability in production between cohorts in Table 6. We pool together all women 18 to 54 years old in 1960, and men respectively, and study their occupational responses to the draft in a multinomial logit framework as in specification (1). There are several interesting patterns that emerge. First, while in high mobilization states women 35 to 54 years old 13 This notion of competition and substitutability between young and old cohorts of women is also found in Doepke, Hazan and Maoz (2012). However, the authors theoretical model links fertility decisions to heterogeneous patterns of labor supply of younger and older women due to WWII, without deriving implications about changes in the occupational distribution. 15

16 in 1960 had mostly exited manufacturing, this exit was matched by the increased presence of younger women 18 to 29 years old in 1960 so that overall there was no change in the likelihood of female employment in that sector. Similarly there was no substantive increase in female employment in professional/managerial occupations, where younger women filled in for the older. Hence, the war seems to have produced a zero-sum redistribution of women across cohorts in these occupations. Second, the war entailed an overall decrease in the likelihood of female employment in services, which mainly reflects the pronounced outward mobility of the youngest women, who could not have contributed to wartime production. Third, these younger cohorts of women were instead directed to the clerical sector, where their employment probability significantly increased. The same happened for men who left professional/managerial and other occupations for clerical jobs. These indirect effects reveal how the war eventually contributed to the trend towards an expanding clerical sector, which is so pronounced in the aggregate data. 14 Finally, while the war did not overall increase the probability of female employment in manufacturing, it is still notable that it implied an increased entry of 18 to 29 years old women into that sector in high mobilization states continuing the pre-existing pattern of some of the wartime Rosies. What could explain this persistence? One possibility is that the war contributed to a change in perceptions about the tasks women could actually perform, including tougher jobs in manufacturing. Another hypothesis is that the war had intergenerational effects. Women 18 to 29 years old in 1960 were born between 1931 and 1942 and grew up witnessing a dramatic inflow of women in the workforce. The latter were likely their mothers, on average years old in 1960, and were employed as operatives in disproportionately larger numbers in the 1940s compared to other occupations (Goldin, 1991). The daughters of the wartime Rosies might have been more likely to follow suit when entering the labor market themselves. 14 One age group that has not been explicitly considered is that of women 30 to 34 years old in For this group we find a significant increase in their presence in clerical jobs in higher mobilization states. At the same time, among the employed women in this age group, there is a significant decrease in their likelihood of working in operative and craft-type occupations, in services as well as in professional-managerial jobs. It is also important to note that our interpretation of war-related changes in employment across occupations abstracts from potential movements in employment shares of other population groups that were excluded from the analysis. These are for instance individuals 55 years and older, non-whites and immigrants. 16

17 Finally, not only daughters might have been affected by the working behavior of their mothers but also the sons. The latter, been raised in a household where the mother displayed certain work patterns such as being employed as an operative were more open to the possibility that their wives later on would follow in their mothers footsteps. Fernandez et al. (2004) provide evidence in support of this mechanism. 7. Conclusion The war led to a substantial increase in the participation of women in the labor market, which persisted in the long run, mostly for women with high school education or more. Yet, it is unclear what this persistence meant in terms of occupations. In this paper, we study the qualitative implications of WWII on the labor markets by examining its long term impact on female employment across the occupational distribution. For the cohorts of women who were of working age during the war (35 to 54 years old in 1960), we find that the large scale manpower mobilization realized till the mid-1940s entailed a long-term shift towards blue-collar employment. In states that experienced higher mobilization, these women were more likely in 1960 to be working in services and other low-skill jobs or not working at all and less likely to be employed in the clerical or professional/managerial sectors. Their entry in manufacturing-type positions initiated during WWII is unremarkable by 1960, although some older women still had a higher probability of being employed in such jobs, especially in the south. It is possible that the women who were displaced from these jobs at the war s end, remained in the market or temporarily exited and reentered but, given their low education, were instead directed to services. We find no long-term effects for men of the same ages, which is consistent with the broader view that, when veterans returned, they largely re-occupied their pre-war jobs. Interestingly, we document that these occupational patterns induced by WWII had spillover effects on subsequent cohorts of women, who were too young to have worked during the war but could have entered at its conclusion. This much younger generation, in states that were more exposed to mobilization, had a higher likelihood of working in 1960 in white-collar clerical and 17

18 professional/managerial jobs as well as in manufacturing, and a significantly lower probability of working in services. Their war-related occupational distribution in 1960 matches the decline in the presence of the older cohorts in these same occupations. Our results suggest that the war largely entailed a long term redistribution within or across occupations and between cohorts of women, without increasing the overall presence of women in any particular occupation. Two exceptions to this are the overall decline in the probability of working in services along with the increase in the probability of being employed in the clerical sector. These results are due to the pronounced (war-related) shifts of the youngest generation out of services and into clerical work. All things considered, our analysis suggests that the war had no watershed effects on the occupational standing of the cohorts that were of working age during the war. The latter instead increased their presence in blue-collar occupations, which are typically considered as lower-skill, brawn-type jobs. The losses of these women, however, implied gains for the much younger generations of post- WWII female entrants, who strengthened their presence in white-collar, more high-skilled and brainintensive occupations. Hence, one unintended, qualitative impact of WWII seems to have been the occupational upgrading of the next generation perhaps along with a change in attitudes towards female workers. References Acemoglu, Daron, David H. Autor, and David Lyle (2004). Women, War and Wages: The Effect of Female Labor Supply on the Wage Structure at Mid-Century, Journal of Political Economy, 112 (3), pp Bound, John and Sarah E. Turner (2002). Going to War and Going to College: Did World War II and the G.I. Bill Increase Educational Attainment for Returning Veterans?, Journal of Labor Economics, 20(4), pp Campbell, D Ann (1984). Women at War with America: Private Lives in a Patriotic Era Cambridge, MA: Harvard University Press. 18

19 Chafe, William H. (1972). The American Woman: Her Changing Social, Economic, and Political Roles New York: Oxford University Press. Doepke Matthias, Hazan M. and Yishay D. Maoz (2012). The Baby Boom and World War II: A Macroeconomic Analysis, mimeo. Elder, Glen H. Jr., Dechter Aimée R. and Taniguchi Hiromi (1999). World War II Mobilization in Men s Worklives: Continuity or Disruption for the Middle Class?, CDE Working Paper No Fernández, Raquel, Alessandra Fogli, and Claudia Olivetti (2004). Mothers and Sons: Preference Formation and Female Labor Force Dynamics, Quarterly Journal of Economics 119 (4), pp Goldin, Claudia (1991). The Role of World War II in the Rise of Women s Employment, American Economic Review, 81 (4), pp Goldin, Claudia (1994). Labor Markets in the Twentieth Century. Working Paper Series on Historical Factors in Long Run Growth, no. 58 (June). Cambridge, Mass.: NBER Goldin, Claudia, and Claudia Olivetti (2013). Shocking Labor Supply: A Reassessment of the Role of World War II on Women s Labor Supply, American Economic Review P&P, 103(3), pp Herman Arthur (2012), Freedom s Force, Random House, New York. Jaworski, Taylor (2014). You are in the Army Now: The Impact of WWII on Women s Education, Work and Family, Journal of Economic History, 74(1), pp David M. Kennedy (1999). Freedom from Fear: The American People in Depression and War , Oxford University Press. Milkman, Ruth (1987). Gender at Work: The Dynamics of Job Segregation by Sex during World War II, Urbana: University of Illinois Press. 19

20 Mulligan, Casey (1998). Pecuniary Incentives to Work in the United States during World War II, Journal of Political Economy, 106(5), pp Ruggles, Steven, J. Trent Alexander, Katie Genadek, Ronald Goeken, Matthew B. Schroeder and Matthew Sobek (2010). Integrated Public Use Microdata Series: Version 5.0. Minneapolis: University of Minnesota. Selective Service System (1956). Special Monographs of the Selective Service System. Vols Washington, D.C.: Government Printing Office. Stanley, Marcus. College Education and the Midcentury GI Bills. Quarterly Journal of Economics 118, no. 2 (2003): Table 1: Employment Shares by Occupation & Age Cohort of women Professional/Managerial % Change Clerical % Change Operatives/Crafts % Change Services % Change (Age in 1960) ,164 0,168 2% 0,287 0,367 28% 0,24 0,181-24% 0,186 0,142-24% ,131 0,147 12% 0,317 0,461 45% 0,245 0,152-38% 0,179 0,122-32% ,218 0,162-26% 0,264 0,319 21% 0,218 0,215-0,1% 0,172 0,151-12% ,241 0,207-14% 0,175 0,279 59% 0,211 0,188-10% 0,235 0,16-32% Shares of women working in each of these occupations, over all employed women. 20

21 Table 2: Female Occupation Shares in Low, Medium and High Mobilization Rate States, All Education Groups: Younger Cohort: Females 35 to 44 years old in Low Medium High All Low Medium High All Operatives/Crafts (0.421) (0.396) (0.428) (0.413) (0.431) (0.380) (0.425) (0.411) Professional/Managerial (0.426) (0.405) (0.408) (0.412) (0.363) (0.373) (0.367) (0.368) Clerical (0.405) (0.455) (0.453) (0.441) (0.446) (0.477) (0.467) (0.466) Services (0.383) (0.384) (0.361) (0.377) (0.363) (0.362) (0.347) (0.358) Other (0.334) (0.317) (0.288) (0.343) (0.326) (0.312) (0.304) (0.314) Older Cohort: Females 45 to 54 years old in Low Medium High All Low Medium High All Operatives/Crafts (0.418) (0.387) (0.427) (0.408) (0.393) (0.375) (0.408) (0.390) Professional/Managerial (0.432) (0.434) (0.409) (0.427) (0.412) (0.401) (0.402) (0.404) Clerical (0.342) (0.387) (0.405) (0.379) (0.421) (0.461) (0.453) (0.448) Services (0.418) (0.430) (0.423) (0.424) (0.383) (0.362) (0.354) (0.366) Other (0.340) (0.318) (0.287) (0.318) (0.343) (0.329) (0.315) (0.330) Note: Statistics describe shares of women working in a given occupation relative to the employed population in the woman's age group. Sample line weights are used to calculate averages. Low-mobilization states (rate less than 45%): Georgia, Louisiana, N. Dakota, N. Carolina, S. Dakota S. Carolina, Wisconsin,Alabama, Arkansas, Mississippi, Virginia, Tennessee, Kentucky, Indiana, Michigan, and Iowa. Medium mobilization states (rate between 45% and 49%: Missouri, Texas, Maryland, Delaware, Vermont, Illinois, New Mexico,Nebraska, Minnesota, Florida, Ohio, West Virginia, New York, Wyoming, and Oklahoma. High mobilization states (rate greater than 49%): Kansas, Montana, Connecticut, Arizona, Colorado, New Jersey, Idaho, California, Maine, Washington, Pennsylvania, Utah, New Hampshire, Oregon, Rhode Island, Massachusetts. 21

22 Table 3: The impact of WWII mobilization rates on female employment across occupations (Multinomial Logit) All Married Employed All Married Employed (1) (2) (3) (4) (5) (6) Base: Out of Labor force Base: Clerical Base: Out of Labor force Base: Clerical Option: Operatives/Crafts mobilization* (1.513) (2.412)*** (2.567)** (1.752)** (2.824)** (1.685)*** Option: Services mobilization* (1.071)** (2.948) (1.988)*** (1.825) (3.101) (1.845)*** Option: Professional/Managerial mobilization* (1.183)** (2.100) (1.909) (1.632) (4.951) (1.865)*** Option: Clerical mobilization* (1.561)** (2.588) (2.122)*** (5.874) Option: Other mobilization* (2.407) (3.924) (3.259) (2.586) (4.501) (2.279)*** Option: White-Collar Cohort of years old Base: Out of Labor Force Base: White-Collar Cohort of years old Base: Out of Labor Force Base: White-Collar mobilization* (1.002)*** (1.873) (1.722)** (4.091) Option: Blue-Collar mobilization* (1.111) (2.002) (1.739)*** (1.499) (1.955) (0.760)*** Observations Note: Other covariates: 1940 male share farmers, non-whites, 1940 male average education, 1940 male share in defense industries, 1940 male shares in operatives, services, clerical and professional/managerial occupations, fixed effects for age, state of birth, state of of residence, year. Sample includes white women, born in the U.S, who were years old in Standard errors (parentheses) account for clustering on state of birth and census year. ***, **, * denote significance at 1%, 5% and 10% levels. Table 4: The impact of WWII mobilization rates on male occupational structure Cohort years old Reference category: Clerical (Employed Population) Cohort years old Option: N= N=82700 Professional/Managerial mobilization* (1.269)* (1.916)* Services mobilization* (2.324) (2.339) Operatives/Crafts mobilization* (1.001) (2.167) Other mobilization* (1.532) (1.380) Note: Sample includes white men 35 to 54 years old in 1960 and born in the U.S. Standard errors (parentheses) clustered by state of birth and year. ***, **, * indicate significance at 1%, 5% and 10% respectively. See text for definition of variables. Coefficients are estimates (log-odds) from a multinomial logit of occupational choice. 22