Job satisfaction among US Ph.D. graduates: the effects of gender and employment sector

Transcription

1 Job satsfacton among US Ph.D. graduates: the effects of gender and employment sector Phlppe Moguérou 1 IREDU, CNRS-Unversté de Bourgogne (Djon, France) and SPRU, Unversty of Sussex (Brghton, UK) Frst draft, January 2002 Abstract In ths paper we try to understand the determnants of job satsfacton. The populaton of Ph.D. graduates n the Unted States offered an nterestng bass to test new factors that are lkely to nfluence job satsfacton. Indeed, the Ph.D. group provdes a useful homogenety - same level of educaton - and an nterestng heterogenety - dfferent career outcomes amongst them, academc vs. non academc postons. Emprcally we use the Survey of Doctorate Recpents carred out by the Natonal Scence Foundaton n We estmate varous models on a sample of 30,000 Ph.D.s n scence and engneerng. Contrary to all the prevous studes, and more accordngly to expectatons, we fnd that females express themselves as less satsfed wth ther jobs than males, other thngs equal, at least for those who work n the academc sector. We show that the number of hours worked has a postve effect on the probablty of beng satsfed for males and a negatve effect for females. The absolute earnngs ncrease the probablty of beng satsfed. But when a measure of comparatve pay s ncluded n the models, the coeffcent related to the absolute wage s not sgnfcant anymore. More generally, we fnd that job satsfacton s explaned by dfferent sets of varables respectvely for males and females, and for academcs and non-academcs. Keywords: job satsfacton, professonal labor markets, Ph.D. JEL classfcaton: J28, J44. 1 IREDU-CNRS, Unversté de Bourgogne, 9 avenue Alan Savary, B.P , Djon Cedex, France. Tel: , Fax: , E-mal: phlppe.moguerou@u-bourgogne.fr. Or, untl Aprl 2002: SPRU, Unversty of Sussex, Mantell Buldng, Falmer, Brghton, BN1 9RF, UK. Tel: , Fax: , E-mal: p.moguerou@sussex.ac.uk. I would lke to thank the partcpants to the 2001 ZEW conference n Berln on unemployment, the partcpants to the 2001 IZA Summer School n Buch and my colleagues at IREDU and SPRU.

2 Introducton A majorty of economsts are stll reluctant to study job satsfacton. They vew personal judgments of satsfacton and other subjectve opnons as a black box that should be opened only by psychologsts and socologsts (Lévy-Garboua and Montmarquette 1997 p.1). But, many studes have tred to understand the determnants of job satsfacton followng the semnal papers of Hamermesh (1977), Freeman (1978) and Borjas (1979), and have consdered job satsfacton as an economc varable. 2 Snce then, economsts have been ncreasngly nterested n the assessment of subjectve well-beng. Recently, many studes have consdered the general well-beng of ndvduals 3 or more specfcally the well-beng at work,.e. job satsfacton. 4 Indeed, the satsfacton that workers derve from ther jobs may be vewed as an ndcaton to how they react to general economc condtons. It s a useful summary measure of numerous job characterstcs. And, perhaps more nterestngly, job satsfacton does also affect these general economc outcomes. In that sense, job satsfacton s an economc varable that s nterestng to study. It can predct labour turnover, absenteesm, productvty or dfferent events affectng the labour force. 5 Freeman (1978, p.8) noted that subjectve varables lke job satsfacton [...] contans useful nformaton for predctng and understandng behavor. Specfc groups have been studed such as lawyers, nurses or academcs. 6 In ths paper, we wll focus our analyss on ndvduals wth a doctorate n scence and engneerng who are employed n the USA. Three man elements have led us to consder the job satsfacton of ths specfc populaton as potentally nterestng to study. Many studes have shown that hgher educated workers are less satsfed than lower educated workers. 7 The common nterpretaton of ths fact s that job satsfacton depends on the gap between outcomes and aspratons, and that aspratons are ncreased by educaton. In consderng a unque level of educaton, we elmnate ths type of dffculty. The homogenety of the group that results from the study of a unque level of educaton may reveal other mechansms that are not vsble when consderng dfferent levels of educaton. Other studes have shown that females are more satsfed wth ther jobs than males. 8 The hgh nvestment n human captal necessary to obtan a Ph.D. may reverse ths fact. It may also have mportant consequences on the varables that explaned job satsfacton. In the USA, Ph.D.s have tradtonally two really dfferent types of careers. About half of them are employed n the academc sector. But, the busness and ndustral sector recrut 2 However, and despte the recent nterest of economsts for job satsfacton, ths noton remans an mportant doman of the psychologcal and organzatonal behavor researches. For a general survey of ths lterature, not really famlar for economsts, see Spector (1997). 3 Clark (1995, 2001), Ng (1996), Kenny (1999), Frey and Stutzer (1999), Blanchflower and Oswald (1997, 2000), Easterln (2001). 4 For example, among recent papers: Clark (1996, 1997, 1998), Brown and McIntosh (1998), Hamermesh (1999), Sloane and Wllams (2000), Clark et al. (1998), Blanchflower and Oswald (1999), Sousa-Poza and Sousa-Poza (2000), Sloane and Ward (1999, 2001), Jürges (2001). 5 Hamermesh (1977), Freeman (1978), Akerlof et al. (1988), Tsang et al. (1991), Clark and Oswald (1996), Lévy-Garboua et al. (1998), Clark et al. (1998), Clark (1999). 6 See respectvely: Laband and Lentz (1998), Shelds and Ward (2000) and Sloane and Ward (1999, 2001). 7 Clark and Oswald (1996) report that satsfacton levels are strongly declnng n the level of educaton, other thngs equal. See, among others, Clark (1995, 1997), Sloane and Wllams (1996). 8 See below for more detals on ths topc. 2

3 nearly the other half of them, and a mnorty (around 10%) are employed n local government or federal admnstratons. In the Unted States, the prvate sector has been establshed as a major employment sector for Ph.D.s for decades now. Thus, Ph.D. graduates face two dfferent labour market stuatons - academc vs. non academc postons. These two groups may have dfferent behavours n terms of job satsfacton. Thus, the homogenety - same level of educaton - and the dversty - career outcomes - of the Ph.D. group provde an nterestng bass to analyse the determnants of job satsfacton. The remanng of ths paper s organzed as follows. In secton I, we brefly revew the job satsfacton at the theoretcal level. We present the data used and we provde some basc facts about job satsfacton for Ph.D.s. In secton II, the emprcal modellng of job satsfacton s developed. In secton III, we proceed to a systematc analyss of the results from the models. Secton I. Job satsfacton: some basc facts Theoretcal background The frst model that can explan job satsfacton s related to the standard lfetme utlty mcroeconomc model. We can defne the utlty of an ndvdual from workng as: ( y h) U = u, where the utlty ncreases wth y, the ncome, and decreases wth h, the number of hours worked. In that specfcaton, the absolute level of wage enters drectly n the utlty functon. Here, we gve smply the statc verson of ths model. However, the nter-temporal nature of utlty could be taken nto account (Lévy-Garboua and Montmarquette 1997). However, other phenomena are lkely to nfluence the ndvdual utlty. The subjectve nature of ncome can be ntegrated n ths smple model. Indeed, the level of utlty may depend not only on the absolute level of ncome but also on a reference ncome to whch ndvduals compare ther earnngs. Ths relatve ncome captures the effect of relatve deprvaton, envy, jealousy or nequty (Clark 1995, p.2). In the case of job satsfacton, the annual salary s an mportant determnant of job satsfacton. But job satsfacton s also affected by relatve earnngs. Indvduals compare ther earnngs wth other group of ndvduals or have specfc expectatons concernng ther earnngs. 9 But as mentoned by Hamermesh (1999), t s not clear by whch mechansm changes n earnngs affect job satsfacton. Thus we rewrte the utlty functon as: ( y, y*, h X ) U = v, where y* s the relatve earnngs of the ndvdual and X a vector of ndvdual and job characterstcs. The utlty s expected to decrease wth y*. 9 The ntal dea was proposed by Hamermesh (1977). 3

4 Presentaton of the data The Survey of Doctorate Recpents carred out by the Natonal Scence Foundaton s desgned to provde nformaton about ndvduals wth doctoral degrees n scence and engneerng felds less than 75 years old. The scence and engneerng felds nclude ndvduals wth doctorate n hard scences but also Ph.D.s n socal scences. The Survey we use here was carred out n Aprl 1997 on about 35,000 ndvduals. It contans nformaton about educaton, work actvtes and hstory, soco-economc background... We have selected a sample of ndvduals from the 1997 SDR, males and 7756 females, who are employed full-tme n Aprl 1997, from a total sample of ndvduals. 10 Most ndvduals are employed n the academc sector (cf. table 1). Table 1. Broad sectors of employment of Ph.D.s (n percentage) Male Female Total Academc sector Government Industry Source: SDR 1997 Note: our sample. Job satsfacton s descrbed as a categorcal response that underlne the feelngs of ndvduals about ther jobs. These feelngs are represented by lmted number of dscrete choces. In the Survey of Doctorate Recpents, the overall job satsfacton s ranged n four categores. The exact queston asked to the ndvduals s: How would you rate your overall satsfacton wth the job you held durng the week of Aprl 15, 1997?. Four answers are possble: very satsfed, somewhat satsfed, somewhat dssatsfed and very dssatsfed. Table 2. Job satsfacton by gender and sector of employment (n percentage) All sectors Academa Government Industry Male Fem Total Male Fem Male Fem Male Fem Very satsfed Somewhat satsfed Somewhat dssatsfed Very dssatsfed Source: SDR Notes: our sample. Dfferent studes have specfcally consdered the mpact of race or gender on job satsfacton (Bartel 1981; Clark 1995, 1997; Groot and Brnk 1998; Sloane and Wllams 2000) and females are found to have hgher job satsfacton than males. Contrary to these earler studes, n the SDR survey, women are less satsfed than men wth ther jobs, except maybe for women workng n the busness/ndustry sectors. Ward and Sloane (1999) have showed for the UK academc professon that there were no sgnfcant dfferences between males and females regardng job satsfacton. But n all the other studes, women express 10 The ncluson of part-tme workers n the models has rased some dffcultes (partcularly wth the varable umber of hours worked). In the orgnal database, 6.7% of ndvduals work part-tme. 4

5 themselves as more satsfed wth ther jobs than men. The authors have tred to explan ths surprsng job satsfacton 11 dfferental by the dfferent nature of job and personal characterstcs, by the dfferent values or expectatons among males and females or by sample selectvty problems. Here, these basc statstcs seem to ndcate that the gender dfferental n the job satsfacton has the opposte sgn as usually. The age has an mpact on job satsfacton for both men and women An ncreasng satsfacton profle wth age seems to appear wth these basc data. Table 3. Job satsfacton by date of brth and gender (n percentage) < >1959 Males Very satsfed Somewhat satsfed Somewhat dssatsfed Very dssatsfed Females Very satsfed Somewhat satsfed Somewhat dssatsfed Very dssatsfed Source: SDR Notes: our sample. Secton II. Emprcal models for job satsfacton To precse these basc evdences, t s necessary to estmate models to take nto account the dfferent factors that are lkely to affect job satsfacton, and to assess ther relatve mportance, other thngs equal. Modellng the dscrete but ordnal nature of job satsfacton We wll respectvely denote the four job satsfacton outcomes ( very satsfed... very dssatsfed ) by y = 0, y = 1, y = 2 and y = 3 for the ndvdual. The outcome s dscrete but of ordnal nature. So, we would lke to estmate the followng model: y * = β ' x + u where y * s the ndependent unobserved varable, x the vector of dependent varables, u the vector of error terms and β the vector of parameters to estmate. The observed satsfacton varable y s related to the latent varable y * such as: 11 Surprsng f we consder that females have a dsadvantage postons n the labour market n terms of earnngs, promoton or job securty. 5

6 y y y y = 0 f y * 0 = 1 f 0 < y * µ = 2 f µ < y * µ 1 = 3 f µ < y 2 * 1 2 where µ 1 and µ 2 are two unknown threshold parameters to estmate. As we suppose u normally and dentcally dstrbuted across observatons wth mean 0 and varance 1, we have: Pr ( y = 0) = Pr( y * 0) = Pr( β ' x + u 0) = Pr( u β ' x ) = Φ( β ' x ) ( y = 1) = Pr( 0 < y * µ ) = Pr( y * µ ) Pr( y * 0) = Φ( µ + β ' x ) Φ( ' x ) Pr β ( y = 2) = Φ( µ + β ' x ) Φ( µ + ' x ) Pr 1 2 β ( y = 3) = 1 Φ ( µ + ' ) Pr 2 β x where Φ (). s the normal standard cdf. We proceed to the ML estmaton of the prevous model. We ncluded a sample selecton term, wth the estmaton of a probt model n a frst step, n the ordered probt but t has never been sgnfcant. It s useful to calculate the margnal effects for the dfferent probabltes. Indeed, only the sgn of the changes n Pr ( y = 0) and Pr ( y = 3) are unambguous 12. The margnal effects evaluated at the sample means are for the contnuous varables: Pr x Pr x Pr x ( y = 0) = φ( ˆ' β x)βˆ [ ]βˆ ( y = 1) = φ( ˆ µ + ˆ' β x) φ( ˆ' β ) 1 x [ ]βˆ ( y = 2) = φ( ˆ µ + ˆ' β x) φ( ˆ µ + ˆ' β ) Pr x 2 1 x ( y = 3) = φ ( ˆ µ + ˆ' β )βˆ 2 x where φ (). s the normal standard pdf. For a dummy varable d, the margnal effects are for the outcome j: ( y = j x, d = 1) Pr( y = j x, d = 0) for j 0,1,2, 3 Pr = It s the dfference between the two probabltes, when the dummy varable takes the value one and when t takes the value zero, as the other varables are at ther sample means. 12 n the general case. Greene (1999) underlnes that t s useful to be cautous wth ths type of models. 6

7 As descrbed n the theoretcal secton, four types of explanatory varables wll be ncluded: - Hours worked: we use the average number of hours worked durng a week declared by the ndvduals. Indvduals wth part-tme poston are not n the sample. However, when ncluded n the sample, these ndvduals report a level of satsfacton clearly lower than ndvduals who work full-tme. - Socal characterstcs such as age, gender, race/ethncty and famly related varables. - Job characterstcs: we wll nclude varables relatve to the sector of employment, the number of employees n the work structure, the man work actvty, the type of work arrangement (job securty) and the regon of employment. We have tred other combnatons to descrbe the job held by ndvduals. We have tred to replace the couple sector of employer-man actvty by a codfcaton n 17 categores of the occupaton and professon of ndvduals. But t seems that ths descrpton was less satsfactory that the frst one. We also nclude varous varables to control for geographcal effects (regon of employment) or scentfc felds (feld of Ph.D.). - Earnngs: the annual salary has been used. To take nto account the relatve earnngs, we have computed a wage equaton descrbed n the next secton. In table 1 n the appendx, basc statstcs are presented for the varables used n the emprcal estmatons. Absolute vs. relatve earnngs To take nto account the wage expectatons phenomenon, we compute a wage equaton and we ntegrate the resduals n our ordered probt model. The man assumpton of ths regresson s that ndvduals are lkely to compare ther earnngs wth a group of reference. Ths reference group s consttuted by ndvduals wth smlar stuatons n the labour market to themselves. One has an opnon about hs/her wage, hs/her true value, or has an dea to be well-pad or under-pad. Ths phenomenon takes nto account the envy or the jealousy that are lkely to play a role n the assessment of job satsfacton. The ftted values from the regresson represent what an ndvdual can expect on average n terms of earnngs wth hs/her dploma, basc socal characterstcs and type of job. Therefore, the resduals from the regresson are a measure of comparatve pay, dfference between actual pay and expected pay. The explanatory varables n the wage equaton are of three man types: soco-economc background, characterstcs of the job and felds of doctorate. 13 We ntegrate the feld of doctorate n ths regresson because workers are lkely to pay more attenton to observable characterstcs than to less observable sklls. And one essental characterstc of Ph.D. graduates s ther feld of doctorate. The estmated equaton s: ln w = z ' δ + v where w s the observed annual wage, z the vector of ndependent varables, δ the vector of 2 parameters to estmate and v the vector of error terms wth E ( ) = 0, V ( ) = σ and Cov ( v, v ) = 0 j j v v 13 We do not want to estmate a tradtonal wage equaton. We would lke to estmate the expected wage of ndvduals, or more exactly, what they can pretend to or expect to. 7

8 A sample selecton problem may arse as well n ths type of equaton. To deal wth t, we have computed a probt model and we have put the nverse Mll s rato n the wage equaton. The coeffcent related to ths varable has never been sgnfcant. Once ths equaton s estmated, we put the resduals, dfference between the observed and predcted values, w ˆ w = w exp( z 'δˆ ), n the ordered probt as an explanatory varable (n the vector x ). The coeffcent related to ths varable s expected to be postve: the hgher the actual wage compared to the expected wage, the hgher the job satsfacton. 14 Secton III. Man results We present the emprcal results for the dfferent estmated models. The job satsfacton for all sectors s frst revewed. Then, we examne the determnants of job satsfacton n the academc sector and n the busness and ndustral sector. Job satsfacton: overall results Some major determnants of job satsfacton appeared n the table 3 n the appendx whch presents the estmated coeffcents of sx models: the models one to three are estmated wthout the comparson pay dfferentals and the models four to sx nclude ths varable. The table 4 presents the margnal effects for the model 6. Results from separate estmatons for males and females are dsplayed n table 5. Before examnng the effects of the dfferent varables on the probablty of beng satsfed wth job, we have to note that the models presented n the appendx predct relatvely well the job satsfacton. We have computed the predcted probabltes for the model 6 table 3. The results are as follows (take the prevous expressons and evaluate them at the sample means wth the vector of estmated parameters): ( y = 0) = Φ( ˆ' β x) Pr = ( y = 1) = Φ( ˆ µ + ˆ' β x) Φ( ˆ' β x) Pr 1 = ( y = 2) = Φ( ˆ µ + ˆ' β x) Φ( ˆ µ + ˆ' β x) Pr 1 2 = ( y = 3) = 1 Φ( ˆ µ + ˆ' β x) Pr 2 = They are qute close to the observed frequences n the sample that are respectvely 0.521, 0.377, and Number of hours worked and earnngs The coeffcent of the varable number of hours worked s postve, contrary to the theoretcal predctons. One possble nterpretaton s that at ths level of educaton, and for the correspondng type of job, more hours worked are assocated wth more job satsfacton. 14 If the resdual s postve, the ndvdual s relatvely well-pad. He/she may have such a subjectve percepton of the stuaton. Therefore, hs/her job satsfacton may ncrease. 8

9 But males and females are really dfferent n that respect. In the table 5, we see than the coeffcent of the hours worked s negatve for women and strongly postve for men. The absolute annual salary has a postve effect on satsfacton as predcted by the theoretcal model. However, when the resdual from the wage regresson s added n the model, the absolute earnngs s not sgnfcant anymore. The coeffcent related to the comparatve earnngs s postve as expected: the hgher the earnngs (comparatvely to the reference group), the hgher the probablty of beng satsfed. Thus, the comparson pay may have a strong nfluence on job satsfacton. Males and females have dfferent behavour n that respect (cf. model 2, table 5). When the two varables are ncluded n the model of job satsfacton, the coeffcent of the annual salary s postve and sgnfcant for females and not sgnfcant for males. The coeffcent related to the measure of the comparatve pay s postve and sgnfcant for males and not sgnfcant for females. Thus job satsfacton s sensble to the absolute earnngs for females and to the relatve earnngs for males. But, we have to be cautous wth the nterpretaton of the coeffcent of the comparatve pay n the ordered probt model. Indeed, ths coeffcent s qute senstve to the specfcaton of the wage equaton. The estmates of the wage equaton are shown n the table 2 n the appendx. The tradtonal determnants of the earnngs of ndvduals are also found here (age, gender, employment sector...). More specfc elements to Ph.D.s have also an effect on the earnngs (felds of doctorate). A dummy varable had also been tested n the ordered probt model to account for the relatve nature of earnngs. Ths dummy s 1 for well-pad ndvduals (ndvduals wth a postve resdual) and 0 otherwse. The coeffcent of ths varable was always postve and hghly sgnfcant as expected. Ths specfcaton of the relatve pay s less senstve to the wage equaton specfcaton but s also less precse because only one dummy attempts to capture all the nformaton. When ths varable was ncluded n the ordered probt models, the coeffcent of the annual salary remaned postve and sgnfcant. Soco-economc varables These estmates confrm that females express themselves as less satsfed wth ther jobs than males. The coeffcent related to ths varable s negatve and sgnfcantly dfferent from zero n all the models except the model 1. The margnal effects for the model 6 that are dsplayed n table 4 show that beng a female decreases the probablty of beng very satsfed by 3.2%. The pecunary elements - and essentally the wage gap between males and females - are not suffcent to explan ths less well-beng at work for females. Indeed, the mpact of ths gender varable s renforced by the ncluson n the model of the resduals from the wage equaton. So, once taken nto account the pay dfferental between males and females, women are even more dssatsfed wth ther jobs than wthout takng nto account the pay gap. Non-US ctzens have a lower job satsfacton. Ths s also true, to a lesser extent, for Asans and under-represented mnortes who have a lower job satsfacton than Whtes. There s a strong effect from age. In the models one to sx, the date of doctorate award s used as a proxy from age. In the database, few ndvduals have earned a doctorate n a second part of ther career. But for those one, the date of award can be an ndcator of the begnnng of a new career. In other models that we estmated, the age profle was nearly the same as wth the date of award profle, but wth a more pronounced U shape for the former. Havng recently awarded doctorate decreases the probablty of beng happy at work comparatvely to the ndvduals at the end of ther career. But the ndvduals at md-career are the far less happy at work. Ths age profle s confrmed by the man studes that have been conducted snce then. 15 The separated estmatons for males and females - results are 15 See for example Clark et al. (1995, 1998) 9

10 presented n table 5 - show that the U-shaped age-profle n satsfacton s more clearly vsble for females than for males. Females are less satsfed n the mddle of ther careers. Males are less satsfed wth ther jobs durng nearly all ther career, comparatvely to the end of ther career where ther satsfacton s at the hghest level. We have ncluded varables related to the famly status of ndvduals n the models. The varable number of chldren has a sgnfcant postve effect on the job satsfacton, even f t s not one of the man determnants. 16 Ths varable does not have an effect for males but t s strongly sgnfcant for females. Ths s relatvely surprsng that such a varable not drectly related to job satsfacton has an effect on t. However, the job satsfacton reported by ndvduals may also reflect other elements of a broader satsfacton, as lfe satsfacton elements. 17 Sector of employment, work actvty and job securty All the varables that are related to the tradtonal work actvty of Ph.D. graduates ncrease the satsfacton of ndvduals. Ths s the case for the man busness for employer. The academc sector (educaton) has a strong postve effect on job satsfacton. But ths s only the case for males (cf. table 5). For females, ths coeffcent s not sgnfcantly dfferent from zero. Females are less satsfed when workng n the publc admnstraton or government sector. The ndvduals who work n the transportatons servces sector express themselves are less satsfed, but at a low level of sgnfcance. If the man actvty of ndvduals s research (appled or basc) or teachng, t ncreases ther probabltes of beng satsfed at work. But, once agan, these varables are only postve and sgnfcant for males. To the contrary, the coeffcents related to the varables employer relatons or producton are sgnfcantly negatve. The establshment sze s also an mportant varable to consder as Idson (1990) has shown. The smaller the work structure, the greater the satsfacton. An establshment sze of less than 10 employees ncreases the margnal probablty of beng very satsfed by 11.7% for the model 6. Ths effect s common to males and females. Workng on a short-term bass has a strong negatve effect on job satsfacton. It decreases the probablty of beng very satsfed wth job by nearly 9%. 18 Ths s not surprsng as the job securty s an mportant element of the well-beng at work. Workng from home more than 50% of tme work, or to a lesser extent, beng self-employed ncrease the job satsfacton. We have for nstance 19 few varables related to the work hstory of ndvduals. Indeed, the past condtons n the labour market may have an nfluence on the job satsfacton that ndvduals express today. If the ndvdual has been lad off on the two last years (between Aprl 1995 and Aprl 1997), hs/her satsfacton s clearly decreased by about 10%. Dummes for the regon of employment are ncluded n the explanatory varables. Only the coeffcents related to the Mddle Atlantc and South Atlantc regons are sgnfcant (and negatve). Fnally, to account for potental mpact of the scentfc dscplnes of doctorate, dummes for the feld of doctorate have been ncluded. Specfc effect of the feld of doctorate 16 The margnal probablty of beng very satsfed reported n the table 4 s 0.75% by addtonal chld. 17 See the lterature on the more general well-beng or happness. Among others, Blanchflower and Oswald (1997, 2000). 18 Workng through a temporary agency has the same effect but t s far less sgnfcant. Few ndvduals are n ths type of work arrangement at the level of Ph.D.. 19 Future development of ths paper wll try to ntegrate more dynamc elements n the explanaton of job satsfacton. 10

11 may arse especally for the younger people f there was an over-producton of Ph.D.s. or man evolutons affectng the scentfc labour market. 20 Ph.D.s n chemstry express themselves as less satsfed wth ther jobs but wth a low sgnfcant level. To the contrary, the psychology feld may have a postve effect. Job satsfacton by broad sector of employment Separate estmatons have been mplemented by broad sector of employment. Here, we make some comments on the estmated coeffcents for ndvduals employed n the academc sector (table 6) and for those employed n the ndustral sector (table 7). Academcs The results for the ndvduals employed n the academc sector are presented n the table 6. Three models have been estmated: one for males, one for females and another one for the whole sub-sample. In these models, a new codfcaton of jobs s used, closer from the academc standards than the prevous one. 21 Ths codfcaton s manly based on the felds of actvty and on the status of ndvduals. The reference s consttuted by postsecondary teachers n computer scences and mathematcs. Females express themselves as sgnfcantly less satsfed wth ther jobs n the academc sector. That confrms the mpresson we had wth the basc statstcs presented n the frst secton. Members of the under-represented mnortes are far less satsfed wth ther jobs. Ths s also the case for the non-us ctzens. Great dfferences can be observed n the sgn and sgnfcance of varables by gender. The year of doctorate award has no sgnfcant effect for females, as f ther (ds)satsfacton remans constant durng all ther careers. The number of hours worked decreases the probablty of beng satsfed for females but s not sgnfcant for males. The annual salary s lkely to nfluence the job satsfacton. The resdual from the wage equaton s postve, wth a hgh level of sgnfcant for males and a slghtly lower level for females. Even n the academc professon, pecunary advantages have an effect, to a certan extent, on the probablty of beng satsfed wth job (Sloane and Ward 1999). 22 One major common effect among males and females s the job securty. If they are employed on a temporary poston, the probablty of beng satsfed s largely decreased. There are some effects of the academc feld and status of ndvduals. Male academcs n socal scences have a hgher probablty of beng satsfed. Female academcs n bologcal scences have a lower probablty of expressng themselves as satsfed wth ther jobs. Busness/ndustry The estmated coeffcents for three models are dsplayed n table In another paper (Moguérou 2001), we developed a comparson between France and the Unted States n the producton of Ph.D.s n scence and engneerng. We show the specfc patterns but also the common trends n the scentfc labour market n the two countres. Specfcally, an over-producton of Ph.D.s was clearly vsble n France at the begnnng of the 1990s, and to a lesser extent, n the USA, n some scentfc felds. Ths overproducton had mportant consequences on labour market prospects for Ph.D. graduates but also on ther satsfacton towards ther Ph.D. programme and towards ther feld of study, but also on ther job satsfacton. 21 Some other varables were not sgnfcant anymore and have been excluded from the models (number of employees...) 22 But, t s true that we have few elements to take nto account the non-pecunary advantages of the academc professon. 11

12 The coeffcent related to the varable female s not sgnfcant for the sub-sample of ndvduals workng n the busness or ndustry sector. Females who work n ths sector are not less satsfed than men contrary to the females employed n the two other broad sectors (government and academa). We fnd a postve and strong effect on job satsfacton of the number of hours worked for males. Thus, males who work n the busness or ndustral sector are manly responsble for the postve sgn of ths varable n the whole sample (table 3). The effect of the number of hours worked s not sgnfcantly dfferent from zero for females n the busness/ndustry. The sze of the establshment s an mportant determnant of job satsfacton for Ph.D.s who work n the ndustral/busness sector, as are the man actvtes declared by ndvduals. The job nsecurty s also a key element to explan the job dssatsfacton. The pay comparson term has a postve effect on the satsfacton for males only. It s not sgnfcant for females. An nterpretaton of the dfferent coeffcents related to females who are employed n the prvate sector s maybe that females who make the choce to work n ths sector are hghly motvated and really decded to have such a career. Indeed, few females, relatve to males, undertake a career n the prvate sector, even nowadays. Concluson Some major conclusons can be drawn from ths study on job satsfacton for Ph.D. graduates n the USA. We have estmated varous econometrc models that attempt to catchup the factors that are lkely to nfluence job satsfacton. We showed that job satsfacton s explaned by dfferent sets of varables for males and females and that varables nether have the same effects on job satsfacton accordng to the employment sector. The socal characterstcs have stll an effect on job satsfacton at ths hgh level of qualfcaton. Contrary to all the prevous studes, and more accordngly to expectatons, females express themselves as less satsfed wth ther jobs than males, other thngs equal. But ths s only true for those who work n the academc sector. The varable gender s not sgnfcant for the females who work n the ndustral or busness sector. The race/ethncty and the ctzenshp status are also lkely to nfluence the job satsfacton, as well as famly related varables. A U-shaped age profle for job satsfacton s found for males and, to a lesser extent, for females. The job securty s a major determnant of job satsfacton n all sectors of employment and dentcally for males and females. A strkng fact s that the number of hours worked has a postve effect on the probablty of beng satsfed for males - and ths effect s especally strong for males who are employed n the busness or ndustral sector - and a negatve effect for females. Fnally, the coeffcent related to the varable earnngs s postve n all the estmated models, for males and females, and for academcs and non-academcs. But, when a varable to account for the pay comparson phenomenon s ncluded n the models - derved from the estmaton of a wage equaton -, generally the absolute level of pay s not sgnfcant anymore. Ths varable of comparatve earnngs has, as expected, a postve effect on the probablty of beng satsfed: the hgher the earnngs (comparatvely to a reference group), the hgher the probablty of beng happy at work. 12

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16 Table 1. Descrptve statstcs Varable Mean Female Number of chldren Race/ethncty: Asan Race/ethncty: mnortes Non US ctzen Number of hours worked pw Lad off on the two last years Annual salary Comparatve pay: resdual 4658 Employer man busness Agrculture, Forestry Botechnology Constructon or Mnng Educaton Fnance, nsurance Health Servces Informaton technology All other servces Manufacturng Publc admnstraton, gov Research Transportaton Servces Wholesale or retal trade Number of employees Under 10 employees employees employees employees employees employees Man actvty Accountng, fnance Appled research Basc research Computer Development Desgn Employee relatons, recrut Management Producton Servces Marketng, purchasng Qualty or prod. manag Teachng Alternatve work arrangements Employer contracted out Some other alternatve work Workng from home Workng short-term bass Self-employed Job sharng Workng through temp agenc Regon of employment New England Mddle Atlantc East North Central West North Central South Atlantc East South Central West South Central Mountan Pacfc Feld of doctorate Bologcal scences Other Lfe and Related Sc Chemstry, except Bochems Physcs and astronomy Other physcal scences Economcs Psychology Socology Other Socal Scences Chemcal Engneerng Cvl Engneerng Electrcal, Electroncs Mechancal Engneerng Other Engneerng Date of Ph.D. award pror to Source: SDR Notes. means of selected varables n our sample. 16

17 Table 2. Estmaton of the wage equaton Varable Coeff. Constant *** (0.025) Female *** (0.006) Race/ethncty: *** Asan (0.008) Race/ethncty: *** under-rep.mnortes (0.008) Non-US ctzen *** (0.010) Date of brth *** (0.013) *** (0.013) *** (0.013) (0.013) (0.013) ** (0.015) Regon of employment Mddle Atlantc ** (0.010) East North Central *** (0.010) West North Central *** (0.012) South Atlantc *** (0.011) East South Central *** (0.016) West South Central *** (0.012) Mountan *** (0.013) Pacfc * (0.010) Number of employees Under *** employees (0.012) employees *** (0.017) employees *** (0.013) employees *** (0.009) employees (0.012) ** employees (0.008) Man busness for employer Agrculture, *** (0.026) Forestry, or Fshng Botechnology 0.148*** (0.020) Constructon or Mnng (0.039) Educaton *** (0.015) Fnance, nsurance 0.157*** of real estate serv. (0.029) Health Servces (0.017) Informaton 0.108*** technology (0.018) All other servces (e.g.. socal...) (0.020) Manufacturng 0.069*** (0.016) Publc *** admnstraton, gov. (0.019) Research (0.015) Transportaton 0.051** Servces, utltes... (0.026) Wholesale or retal *** trade Man actvty Accountng, fnance 0.070** (0.028) Appled research 0.080*** (0.014) Basc research *** (0.015) Computer (0.018) Development 0.132*** (0.017) Desgn (0.021) Employee relatons, 0.183*** recrutng (0.029) Management 0.228*** (0.015) Producton *** (0.039) Servces 0.115*** (0.016) Marketng, purchasng 0.044* (0.024) Qualty or 0.054* productvty manag. (0.029) Teachng *** (0.015) Feld of Ph.D. Ph.D. n bologcal scences Other Lfe & Related Scences Chemstry, except Bochemstry *** (0.011) *** (0.013) *** (0.013) Physcs and ** astronomy (0.014) Other physcal *** scences (0.017) Economcs 0.048*** (0.018) Psychology *** (0.013) Socology *** (0.016) Other Socal *** Scences (0.016) Chemcal Engneerng 0.071*** (0.019) Cvl Engneerng (0.022) Electrcal, Electroncs eng *** (0.016) Mechancal Engneerng (0.019) Other Engneerng 0.032** (0.014) R Number of observatons Source: SDR Notes: ML estmaton of the wage equaton. Coeffcents wth s.e. n parentheses. *Sgnfcant at the 10% level, **Sgnfcant at the 5% level, ***Sgnfcant at the 1% level. 17

18 Table 3. Job satsfacton, all sectors of employment: ordered probt estmates Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Constant ** (0.092) ** (0.097) * (0.100) 0.233** (0.112) 0.367*** (0.127) 0.397*** (0.131) Female (0.016) ** (0.017) * (0.017) *** (0.018) *** (0.018) *** (0.018) Number of chldren 0.017*** (0.006) 0.018*** (0.007) 0.017*** (0.007) 0.018*** (0.006) 0.019*** (0.007) 0.019*** (0.007) Race/ethncty: Asan *** (0.021) *** (0.021) *** (0.021) *** (0.021) *** (0.021) *** (0.021) Race/ethncty: underrepresented mnortes *** (0.023) *** (0.023) *** (0.023) *** (0.023) *** (0.023) *** (0.023) Non US ctzen ** (0.027) ** (0.027) * (0.027) *** (0.027) *** (0.028) *** (0.028) Granted Ph.D. n *** *** (0.073) *** (0.073) *** (0.074) *** (0.075) *** (0.075) *** (0.071) *** *** *** (0.073) *** (0.074) *** (0.074) *** (0.071) *** (0.071) *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** (0.074) *** (0.074) *** (0.074) *** (0.074) *** (0.074) *** (0.074) *** (0.083) *** (0.083) *** (0.083) *** (0.083) *** (0.083) *** (0.083) Number of hours worked per week ** (0.0008) ** (0.0008) ** (0.0008) * (0.0008) ** (0.0008) 0.002* (0.001) Lad off on the two last years *** (0.035) *** (0.035) *** (0.035) *** (0.035) *** (0.035) *** (0.035) Annual salary *** (3.02-7) *** (3.07-7) *** (3.08-7) (8.57-7) (1.06-6) (1.06-6) Comparatve pay: resdual from the wage equaton *** (8.73-7) *** (1.04-6) *** (1.04-6) Man busness for employer Agrculture, Forestry, or Fshng (0.069) (0.070) (0.070) (0.070) (0.070) (0.070) Botechnology (0.056) (0.056) (0.056) (0.057) (0.057) Constructon or Mnng (0.106) (0.107) (0.107) (0.106) (0.107) (0.107) Educaton 0.216*** 0.206*** 0.204*** 0.162*** (0.042) 0.146*** (0.042) 0.145*** (0.042) Fnance, nsurance of real estate servces (0.081) (0.081) (0.081) (0.081) (0.082) (0.082) Health Servces (0.046) (0.046) Informaton technology (0.049) (0.050) (0.050) (0.050) (0.050) (0.050) All other servces (e.g.. socal, legal, busness) Manufacturng Publc admnstraton, government (0.044) (0.044)

19 Table 3 (contnued) Research Transportaton Servces, * * * utltes, or communcatons (0.070) (0.070) (0.070) Wholesale or retal trade (0.103) (0.103) (0.103) Number of employees Under 10 employees 0.384*** 0.377*** 0.376*** (0.044) (0.044) (0.044) employees 0.130*** 0.130*** 0.130*** (0.047) (0.047) (0.047) employees 0.108*** 0.105*** 0.103*** employees 0.075*** 0.072*** 0.075*** (0.024) (0.024) (0.025) employees 0.057* 0.056* 0.059* (0.034) (0.034) (0.034) employees (0.022) (0.022) (0.022) Man actvty Accountng, fnance (0.076) (0.076) (0.076) Appled research 0.134*** 0.138*** 0.137*** Basc research 0.181*** 0.184*** 0.183*** (0.040) (0.040) (0.040) Computer (0.047) Development (0.046) (0.046) (0.046) Desgn (0.056) (0.057) (0.057) Employee relatons, recrutng * * * (0.079) (0.079) (0.079) Management 0.110*** 0.109*** 0.107*** Producton *** *** *** (0.103) (0.103) (0.103) Servces (0.044) Marketng, purchasng (0.065) (0.065) (0.065) Qualty or productvty management (0.078) (0.078) (0.078) Teachng 0.122*** 0.125*** 0.124*** (0.040) (0.040) (0.040) Alternatve work arrangements Employer contracted out to another organzaton (0.039) (0.039) (0.039) Workng from home 50% or 0.131*** 0.131*** 0.129*** more of work tme Workng on a short-term bass, *** *** *** seasonal, as-needed (0.056) (0.056) (0.056) Self-employed 0.120** 0.117** 0.119** (0.051) (0.051) (0.051) Job sharng (0.144) (0.144) (0.144) Workng through a temp or * * * employment agency (0.129) (0.129) (0.129) Some other alternatve work arrangements (0.058) (0.058) (0.058) (0.070) * (0.104) 0.323*** 0.107** 0.092** 0.056** (0.025) 0.057* (0.034) (0.022) (0.076) 0.163*** 0.156*** (0.040) (0.047) 0.116** (0.046) (0.056) (0.080) 0.207*** (0.043) *** (0.105) 0.078* (0.044) (0.065) (0.078) 0.105*** (0.040) (0.039) 0.135*** *** (0.056) 0.121** (0.051) (0.144) * (0.129) (0.058) (0.070) * (0.104) 0.301*** 0.101** 0.087** 0.050** (0.025) 0.058* (0.034) (0.022) (0.076) 0.168*** 0.157*** (0.040) *** (0.046) (0.057) (0.080) 0.230*** (0.044) *** (0.105) (0.065) (0.078) 0.095** (0.040) (0.039) 0.135*** *** (0.056) 0.117** (0.051) (0.144) * (0.129) (0.058) (0.070) * (0.104) 0.299*** 0.101** 0.085** 0.052** (0.025) 0.060* (0.034) (0.022) (0.076) 0.168*** 0.156*** (0.040) *** (0.046) (0.057) (0.080) 0.227*** (0.044) *** (0.105) (0.065) (0.078) 0.095** (0.040) (0.039) 0.133*** *** (0.056) 0.120** (0.051) (0.144) * (0.129) (0.058) 19

20 Table 3 (contnued) Regon of employment Mddle Atlantc ** (0.030) ** (0.030) East North Central (0.031) (0.031) West North Central South Atlantc * (0.030) ** (0.030) East South Central West South Central (0.034) (0.035) Mountan (0.036) (0.036) Pacfc (0.029) (0.029) Feld of Ph.D. Ph.D. n bologcal scences (0.032) (0.032) (0.032) (0.032) Other Lfe & Related Scences (0.036) (0.036) Chemstry, except Bochemstry * * Physcs and astronomy Other physcal scences (0.047) (0.047) Economcs (0.049) (0.049) Psychology 0.092** 0.090** (0.039) Socology (0.044) (0.046) (0.046) Other Socal Scences (0.044) (0.044) Chemcal Engneerng Cvl Engneerng (0.060) (0.060) (0.060) (0.060) Electrcal, Electroncs and Communcatons Engnee (0.043) (0.043) (0.044) (0.044) Mechancal Engneerng (0.053) (0.053) (0.053) (0.053) Other Engneerng µ 1.057*** 1.031*** 1.062*** 1.485*** 1.618*** 1.649*** 1 (0.092) (0.097) (0.100) (0.112) (0.128) (0.131) µ 1.764*** 1.738*** 1.770*** 2.193*** 2.327*** 2.358*** 2 (0.093) (0.097) (0.101) (0.113) (0.128) (0.131) -2 log L Number of observatons Source: SDR Notes: ML estmaton of the ordered probt models. Coeffcents wth standard errors n parentheses. See the paper for detals. The reference for the man busness for employer s consttuted by the category other sectors. For the work actvty, t s the other man actvty category. For the regon, New England s the reference. And for the feld of doctorate, computer scences as reference. * Sgnfcant at the 10% level, ** Sgnfcant at the 5% level, *** Sgnfcant at the 1% level. 20