The Effects of Focused Area of Study on Self-Reported Skill Gains and Satisfaction of MBA Graduates

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1 The Effects of Focused Area of Study on Self-Reported Skill Gains and Satisfaction of MBA Graduates Andrew J. Hussey, University of Memphis, USA ABSTRACT Using a longitudinal survey of registrants for the Graduate Management Admission Test (GMAT), this paper estimates the effects of obtaining a specialized MBA degree by concentrating one s studies in one of a number of fields (finance, marketing, international business, etc.), relative to studying general management more broadly. We focus on identifying differential effects across areas of specialization among a wide array of reported skills gained through the MBA program, as well as general attitudes towards the value added of one s educational experience. Our results suggest considerable heterogeneity in the skills augmented by particular areas of study. In particular, we find that many MBA concentrators report lower skill gains relative to general management (most notably, team building skills). Those studying international business, however, reported greater enhancement of some skills. Results also differed by area of study in terms of the valuation of one s MBA, with international business concentrators viewing their experiences favorably, and MIS concentration viewing their experiences least favorably. Results are robust to the inclusion of several control variables, including those representing prior educational background, GMAT scores, initial skill levels, work experience, and heterogeneity in MBA program structure and quality. INTRODUCTION A large body of research has investigated the effects of education on student outcomes. In recent years, significant focus in the literature on higher education has been on the determination of differential effects across college majors (Arcidiacono, 2004; Altonji, 1993; Berger, 1988; Black, et al., 2003; Daymont and Andrisanti, 1984; Fitzgerald, 2000; Grogger and Eide, 1995; James et al., 1989; Loury and Garman, 1995; Monks, 2000; McDonald and Thornton, 2007; Thomas and Zhang, 2005). These studies typically focus on post-graduate earnings as an outcome, and have often found significant differences in both starting salaries and life-time earnings potential across certain majors. The current study contributes to this larger literature in a couple of ways. First we focus our analysis on the Master s of Business Administration, an increasingly important and common advanced degree, but for which the post-graduate outcomes have remained relatively understudied. Second, rather than focusing on earnings, as the vast majority of studies do, we consider the self-assessed valuation of MBA education among graduates. In particular, the goal of this paper is to investigate differential reported skill gains and attitudes toward the valuation of one s MBA education across areas of concentration within MBA programs. The value of the MBA has been estimated and especially debated among some scholars. Some studies have concluded that an MBA education is more about networking, or signaling one s pre-existing talents, rather than learning (e.g., Mintzberg, 2004; Hussey, 2009). Regardless, other studies have found significant monetary returns to an MBA (eg., Arcidiacono, et al. 2008; Holtom and Inderrieden, 2006). These studies typically perform their analyses without making distinctions between heterogeneous institutions, beyond a few measures of program quality, despite the fact that MBA programs have become increasingly diversified. In particular, many MBA programs now allow the opportunity for students to go beyond the core MBA curriculum, by tailoring additional coursework towards a particular area. According to Dierdorff and Rubin (2008), 56 percent of accredited conventional MBA programs now offer at least one concentration, and 93 percent of those offer at least 2. An additional 9 percent of MBA programs offer entirely specialized degrees. Despite this, only a handful of studies have investigated differences in outcomes across MBA focused areas of study. Grove and Hussey (2009) consider the monetary returns to various fields. We extend their analysis to non-monetary outcomes and graduate satisfaction. Baruch, Bell and Gray (2005) report similar

2 competencies and skill gains for general MBA and specialized MBA program graduates from one institution. We extend their analysis to a large cross-section of institutions. Using data from a large survey of GMAT registrants, we investigate differential effects of MBA focused areas of study on reported skill gains across a wide variety of managerial competencies. We also consider the value added of MBA education, in terms of career, personal growth and monetary investment, as reported by graduates focusing on different fields of study. In each case, we consider reported outcomes relative to observably similar individuals who did not focus their studies (ie., study general management in their degree program). We find evidence for considerable heterogeneity in skills gained across fields of study, as well as in attitudes toward the value added of their MBA degrees. The remainder of the paper proceeds as follows. In the next section, we discuss the data in more detail. We then outline the empirical methodology. Following that, the results are presented and discussed. We conclude with a broader discussion of the importance of our results, as well as the potential weaknesses of our study. DATA Our data come from the GMAT Registrant Survey, a longitudinal survey of a relatively large number of individuals who registered to take the Graduate Management Admission Test (GMAT), a requirement for admission into most Master s of Business Administration (MBA) programs. Sponsored by the Graduate Management Admission Council (GMAC), the survey was administered in four waves, beginning in 1990 and ending in The survey follows individuals who registered to take the GMAT, some of whom went on to complete MBAs and some of whom did not. The survey asks detailed questions about education and work experiences. It also asks more subjective questions dealing with individual attitudes toward business school, including the perceived value added of one s business school education. Furthermore, the survey data was combined with data from GMAT registration and testing files, giving us accurate information on GMAT scores, which are used as control variables in the analysis. The dependent variables in the analysis are drawn from questions in the fourth and final survey dealing with one s attitudes toward their MBA education. In particular, one question asks individuals to report the extent to which 16 skills or personal attributes were each enhanced by their graduate management school experience. The skills, which are generally deemed to be important in being a successful manager, are the following: Oral communication skills (presentation skills); Written communication skills; Function skills (skills obtained from your core courses); Analytical problem solving skills; Information systems/computer application skills; Team building skills; Understanding business in other cultures; Interpersonal skills; Ability to organize; Ability to work with people from diverse backgrounds; Ability to delegate tasks; Leadership skills; Ability to motivate others; Ability to adapt theory to practical situations; and Creativity. Each response varied from 1 (not at all enhanced) to 4 (very enhanced). Similarly, another question in the fourth survey provides a series of statements regarding one s perception of the value of their MBA. Such statements include: My graduate management education has Given me opportunities for changing jobs or moving up in my career ; Given me a sense of satisfaction and achievement ; Been worth my time and investment ; etc. The survey asks individuals to report the degree to which each statement is true or false, ranging from +3 (true) to -3 (false). Responses to each of these 14 statements, plus the 15 reported skill gains, constitute the dependent variables used in our analysis. In addition to GMAT scores, the data allow for several control variables not typically available to researchers. The surveys include a relatively complete employment history within the sample time-frame, allowing for the calculation of total work experience. In particular, we compute the total years of full-time (35 hours per week or more) work experience, to the nearest month, using reported durations of jobs within the sample time-frame, and a question in the initial survey wave reporting years of full-time work experience since the age of 21. We also include control variables relating to one s academic background, including both college and aspects of their MBA education. Specifically, we include undergraduate grade point average, undergraduate major area, and measures of undergraduate institutional selectivity obtained from Barron s Profiles of American Colleges. We also include indicators of whether the MBA program was part-time or full-time, and whether or not it was ranked in the top 10 or top 25 of U.S. News & World Report 1993 rankings. Since the reported skill gains of individuals is likely to be influenced by one s initial

3 perception of their skills, we include responses to a question in the initial survey (prior to enrollment in business school) which asks individuals to rate themselves on the same skills or personal attributes that were included in the skill gains questions corresponding to our dependent variable. In particular, we sum an individual s responses, each ranging from 1 (not at all have the characteristic or skill) to 4 (very much have the characteristic or skill), to create an overall index of self-assessed skills (call Skill Index). This measure has previously been used by Montgomery and Powell (2003) and Grove and Hussey (2008). 3,771 individuals responded to the fourth survey. Of these, we limit our analysis to individuals who completed an MBA sometime within the sample time frame. Since GMAT scores are used as control variables, we further limit our analysis to those who took the test and for whom we have scores. Missing values for the remaining control variables (demographics and educational background) decrease our usable sample further, resulting in a final sample size of 1,095 individual responses. Descriptive statistics of our sample are presented in Table 1, organized by one s reported major field of study. Because of small sample sizes for several of the possible fields listed in the survey, we collapsed many of them into a single category, Other Area, which includes the following fields: economics, entrepreneurial management, health care administration, industrial management, production/operations management, public policy or public administration, real estate, statistics or operations research, transportation, business strategy, and other. As seen in the table, significant differences exist across areas of study. In particular, individuals in many of the specialized fields often differ substantially from those studying general management. For example, those who concentrate their studies in finance are significantly more likely to be Asian, tend to be slightly younger with less work experience, have higher quantitative test scores, and are disproportionately located at top ranked schools. Those who study international business are more likely to be Hispanic, to be significantly younger and less experienced, and are more likely to attend school full-time. EMPIRICAL METHODOLOGY We use a regression framework to isolate the differential effects of obtaining MBA concentrations in particular fields on reported skills gained and the value added of the MBA, by controlling for a relatively large number of potentially confounding factors. Since our outcomes of interest are not continuous variables, but rather discrete numerical responses reflecting skills gained and the degree to which certain statements are either true or false, traditional linear regression models (eg., ordinary least squares) are not appropriate. Rather, we utilize a discrete choice framework. In particular, since the ordinal values of responses are meaningful, we use an ordered probit model (Maddala, 1992). That is, we estimate the following model: S i * = X i β 1 + Concentration ij β j + ε i, where S i * is latent (unobserved) variable representing underlying individual skills or value added of MBA and ε i is an error term. Rather than observing S i *, we observe actual discrete reponses, ie. S i = {1, 2, 3, 4}, where the realized value of S i depends on the continuous variable S i * exceeding certain thresholds. The threshold values are then estimated along with the β s of interest using maximum likelihood. Our coefficients of interest are β j, the coefficients on the MBA concentration variables, which represent the effect of focusing one s studies in a particular area on reporting greater skill gains, relative to those studying general management. Individuals are not likely to randomly choose to concentrate their MBA studies, nor to select a particular field based on random factors. The differences in variable means found in Table 1 confirm this. Thus, we control for a wide variety of initial characteristics of individuals (X i ), which may be correlated with both the study of certain fields and reported skill gains or attitudes about the value added of one s MBA education. Specifically, we control for initial reported skill levels, differences in undergraduate background, GMAT scores, demographic variables, work experience, and differences in MBA program structure and quality.

4 General Mgmt. Finance Marketing Accounting MIS International Business Other Area Female (0.484) (0.428) (0.499) (0.501) (0.484) (0.451) (0.501) Asian (0.269) (0.425) (0.348) (0.419) (0.333) (0.365) (0.250) Black (0.291) (0.308) (0.292) (0.317) (0.350) (0.223) (0.384) Hispanic (0.370) (0.320) (0.356) (0.396) (0.417) (0.485) (0.354) Age (6.349) (4.924) (4.259) (5.466) (6.455) (4.698) (6.109) Experience (6.780) (5.574) (5.099) (5.744) (6.880) (5.327) (6.693) Quantitative GMAT (7.928) (7.776) (7.682) (6.039) (8.123) (7.067) (8.996) Verbal GMAT (7.250) (6.904) (7.025) (6.723) (7.299) (8.690) (7.418) Undergrad GPA (0.406) (0.392) (0.389) (0.457) (0.368) (0.434) (0.427) Undergrad Highly Selective Undergrad Moderately Selective Table 1. Descriptive Statistics of Sample (0.400) (0.441) (0.458) (0.396) (0.393) (0.432) (0.373) (0.442) (0.460) (0.464) (0.469) (0.436) (0.473) (0.457) Social Sciences Major (0.336) (0.387) (0.384) (0.368) (0.294) (0.432) (0.391) Humanities Major (0.274) (0.242) (0.292) (0.126) (0.244) (0.329) (0.311) Engineering Major (0.400) (0.325) (0.371) (0.215) (0.315) (0.256) (0.354) Sciences Major (0.300) (0.281) (0.302) (0.215) (0.406) (0.256) (0.322) Part-time MBA (0.499) (0.500) (0.489) (0.499) (0.479) (0.467) (0.501) Executive MBA (0.315) (0.224) (0.174) (0.000) (0.294) (0.223) (0.143) Top 10 MBA (0.227) (0.314) (0.174) (0.000) (0.125) (0.223) (0.227) Top MBA (0.194) (0.366) (0.384) (0.246) (0.125) (0.131) (0.264) Skill Index (4.846) (5.147) (5.171) (5.096) (5.313) (5.025) (5.184) Observations Notes: Reported are means and (standard deviations). indicates that mean of variable is statistically different (at the 5 percent level) from that of general management.

5 RESULTS Ordered probit estimates of the relative effects of field of study on reported skill gains are displayed in Table 2. All coefficient estimates are relative to general management, the omitted category. Since the estimates are from an ordered probit model, we focus primarily on the sign and statistical significance of the estimates, rather than their magnitude. In general, many of the significant effects that are found are negative. That is, focusing one s studies seems to come at the expense of the augmentation of several managerial related skills. In particular, relative to those in general MBA programs without specialization, finance concentrators reported statistically significantly lower enhancement in the following areas: written communication, team building, interpersonal skills, leadership skills, and creativity. Accounting concentrators also reported fewer gains in team building skills, as well as less gains in the ability to work with people from diverse backgrounds and understanding business in other cultures. Those studying management information systems (MIS) also reported gaining less team building skills, and a lower ability to adapt theory to practical situations. Some fields resulted in significantly higher reported skill gains for some skills. Focusing one s studies in international business, in particular, resulted in no (significant) negative effects relative to general management. Conversely, international business concentrators reported higher gains in understanding business in other cultures and the ability to work with people from diverse backgrounds. Also, not surprisingly, MIS concentrators were significantly more likely to report gaining skills in information systems/computer application. In addition to reported skill gains, differential effects are found across major areas of study in the attitudes of MBA graduates toward the professional, intellectual and practical value of their education. These results are shown in Table 3. In several instances, concentrators report greater satisfaction toward their MBA experience than nonconcentrators (general management). For example, both finance and accounting concentrators are less likely to report that the education has not been important because they already had the credentials needed to do well in their career, and accounting concentrators were more likely to report that their education has given them opportunities for changing jobs or moving up in their careers. Both accounting and other area concentrators were more likely to report that their MBA provided them with some of the specific job skills needed to get ahead. Again, those who studied international business generally viewed their education favorably, being more likely to report that the MBA expanded their intellectual horizons and provided them with more practical skills and knowledge than their undergraduate education. MIS concentrators, on the other hand, frequently reported dissatisfaction with the value added of their MBA, both professionally (they were less likely to report that the MBA provided them with the qualifications needed for advancement), financially (they were more likely to report that the MBA was too expensive to be worthwhile, and that it required taking on large financial debts), and personally (they were less likely to report that the MBA gave them a sense of satisfaction and achievement, or that it expanded their intellectual horizons).

6 Table 2. Effects of MBA Concentration on Reported Skills Gained in Business School Finance Marketing Accounting MIS Human International Resources Business Other Area Oral communication Written communication Functional skills ** ** (0.109) (0.107) (0.110) (0.125) (0.123) (0.125) (0.165) (0.162) (0.166) (0.162) (0.161) (0.161) (0.198) (0.191) (0.203) (0.175) (0.173) (0.172) (0.107) (0.106) (0.108) Analytical problem solving (0.108) (0.123) (0.163) (0.157) (0.195) (0.169) (0.106) Information systems/ ** computer application (0.101) (0.116) (0.154) (0.162) (0.186) (0.159) (0.101) Team building ** * * * (0.107) (0.123) (0.160) (0.157) (0.193) (0.171) (0.171) Understanding business in other cultures Interpersonal skills Ability to organize Ability to work with people from diverse backgrounds Ability to delegate tasks Leadership skills Ability to motivate others Ability to adapt theory to practical situations ** ** ** (0.102) (0.118) (0.154) (0.152) (0.185) (0.187) (0.101) * ** (0.105) (0.121) (0.159) (0.156) (0.190) (0.168) (0.103) (0.103) (0.118) (0.156) (0.153) (0.193) (0.163) (0.102) ** ** * (0.103) (0.118) (0.154) (0.152) (0.186) (0.171) (0.101) (0.102) (0.116) (0.153) (0.151) (0.183) (0.161) (0.100) ** (0.103) (0.119) (0.155) (0.153) (0.188) (0.163) (0.102) (0.102) (0.117) (0.154) (0.152) (0.185) (0.162) (0.101) * (0.104) (0.119) (0.157) (0.154) (0.192) (0.164) (0.103) ** Creativity (0.103) (0.117) (0.156) (0.153) (0.186) (0.162) (0.101) Notes: Each row corresponds to a separate ordered probit regression. Standard errors below estimates (in parentheses). Each regression also included: quadratics in age and experience; indicator variables for female, black, Asian and Hispanic; skill index and quantitative and verbal GMAT scores; undergraduate GPA and indicators for undergraduate selectivity (highly selective and moderately selective); indicator variables for undergraduate major area (business, social sciences, sciences, engineering or humanities); indicator variables for part-time, executive, top 10 and top MBA program attended. * and ** indicate coefficient is statistically different from zero at the 5 and 10 percent levels, respectively.

7 Table 3. Effects of MBA Concentration on Attitudes Regarding Value Added of Education Human Resources International Business Other Area ** (0.104) (0.121) (0.163) (0.153) (0.193) (0.163) (0.103) My graduate management education has: Finance Marketing Accounting MIS Given me opportunities for changing jobs or moving up in my career. Not been that important because I already had the credentials that I need to do well in my career. Provided me some of the specific job skills I need to get ahead. Provided me some of the professional qualifications (the "ticket") I need for advancement Provided me with the right connections to get a good job. Proven too expensive to be worthwhile. Required me to take on large finanical debts. Given me appropriate role models and mentors. Given me a sense of satisfaction and achievement. Proven too intimidating because I was unable to compete with other students. Expanded my intellectual horizons. Provided me with more practical skills and knowledge than my undergraduate education. Provided knowledge that will allow me to apply my job skills more effrectively. Been worth my time and investment ** ** (0.099) (0.114) (0.151) (0.145) (0.180) (0.157) (0.097) ** ** (0.100) (0.115) (0.155) (0.148) (0.185) (0.159) (0.099) * (0.101) (0.118) (0.156) (0.148) (0.190) (0.161) (0.101) ** (0.098) (0.113) (0.149) (0.146) (0.180) (0.156) (0.096) * (0.104) (0.122) (0.162) (0.154) (0.194) (0.163) (0.104) ** (0.111) (0.129) (0.166) (0.164) (0.197) (0.172) (0.111) ** (0.097) (0.112) (0.149) (0.146) (0.180) (0.156) (0.096) ** * 0.384* * (0.108) (0.126) (0.162) (0.164) (0.212) (0.171) (0.109) * (0.125) (0.143) (0.189) (0.185) (0.244) (0.211) (0.122) ** * (0.103) (0.119) (0.155) (0.152) (0.187) (0.171) (0.103) ** (0.101) (0.116) (0.154) (0.151) (0.185) (0.169) (0.100) ** (0.101) (0.117) (0.155) (0.149) (0.186) (0.164) (0.101) * (0.107) (0.126) (0.167) (0.160) (0.196) (0.174) (0.109) Notes: Each row corresponds to a different ordered probit regression. Standard errors in parentheses. Sample included 1,069 observations. Each regression also included: quadratics in age and experience; indicator variables for female, black, Asian and Hispanic; skill index and quantitative and verbal GMAT scores; undergraduate GPA and indicators for undergraduate selectivity (highly selective and moderately selective); indicator variables for undergraduate major area (business, social sciences, sciences, engineering or humanities); indicator variables for part-time, executive, top 10 and top MBA program attended. * and ** indicate coefficient is statistically different from zero at the 5 and 10 percent levels, respectively. CONCLUSION This paper investigates differences in outcomes across MBA fields of study. We focus on both reported skill gains of graduates, as well as individuals perceptions of the value added (professional, personal and monetary) of their MBA education. We control for a relatively large set of potentially confounding variables, representing one s initial reported skill levels, differences in undergraduate background, GMAT scores, demographic variables, work experience, and differences in MBA program structure and quality. The estimation of multiple ordered probit models results in severally statistically different estimates across fields of study. In particular, we find that many MBA concentrators report lower skill gains relative to general management (most notably, team building skills). Those studying international business, however, reported greater enhancement of some skills. Results also differed by area of study in terms of the valuation of one s MBA, with international business concentrators viewing their experiences favorably, and MIS concentration

8 viewing their experiences least favorably. These results run contrary to those of Baruch, Bell and Gray (2005), who find similar competencies and skill gains for general MBA and specialized MBA program graduates from a single institution. However, our results support, and help to explain, those of Grove and Hussey (2009), who find differential monetary returns across MBA study concentrations. Some limitations of this study should be noted. First, both skill gains and value added measures are self-reported, so we cannot say for certain the extent to which particular skills were more or less enhanced across fields of study. Also, the list of skills addressed in the study, as well as the ways in which the MBA may influence post-graduate outcomes, is by no means exhaustive. To the degree that individuals report lower skill gains in some areas as compared to general management, it is possible that they gain specific skills in other, less managerially focused areas. Further research would ideally investigate objectively measured skills and competencies before and after MBA education with different areas of focus. Nonetheless, these results highlight the increasing role and importance of program and concentration heterogeneity available in graduate management education. REFERENCES Altonji, J., The demand for and return to education when education outcomes are uncertain, Journal of Labor Economics 11(1): Arcidiacono, P., Ability sorting and the returns to college major, Journal of Econometrics 121 (1-2): Arcidiacono, P., Cooley, J. and A. Hussey, The economic returns to an MBA, International Economic Review 49(3): Baruch, Y., Bell, M., and D. Gray, Generalist and specialist graduate business degrees: Tangible and intangible value. Journal of Vocational Behavior 67(1): Berger, M., Predicted future earnings and choice of college major, Industrial and Labor Relations Review 41: Black, D., Sanders S. and L. Taylor, The economic reward to studying economics, Economic Inquiry 41(3): Daymont, T. and P. Andrisani, Job preferences, college major, and the gender gap in earnings, Journal of Human Resources 19: Dierdorff, E. and R. Rubin, The relevance, requirements, and ramifications of specialized MBA programs, Working Paper, DePaul University. Fitzgerald, R., College quality and the earnings of recent college graduates, Education Statistics Quarterly 2(3). Grove, W. and A. Hussey, Returns to field of study versus school quality: MBA selection on observed and unobserved heterogeneity, Economic Inquiry, forthcoming. Holtom, B. and E. Inderrieden, Examining the value added by graduate management education, GMAC RR Hussey, A., Human capital augmentation versus the signaling value of MBA education, Working Paper, University of Memphis. James, E., Alsalam, N., Conaty, J. and T. Duc-Le, College quality and future earnings: Where should you send your child to college? American Economic Review 79(2): Loury, L. and D. Garman, College selectivity and earnings, Journal of Labor Economics 13: Maddala, G.S. (1992). Introduction to Econometrics, 2 nd ed., New York: Macmillan Publishers. McDonald, J. and R. Thornton, Do new male and female college graduates receive unequal pay? Journal of Human Resources 42(1): Mintzberg, H., Managers not MBAs: A hard look at the soft practice of managing and management development. Berrett-Koehler, San Francisco. Monks, J The returns to individual and college characteristics: Evidence from the National Longitudinal Survey of Youth, Economics of Education Review 19(3): Montgomery, M. and I. Powell, Does an advanced degree reduce the gender wage gap? Evidence from MBAs, Industrial Relations 42(3): Thomas, S. and L. Zhang, Post-baccalaureate wage growth within four years of graduation: The effects of college quality and college major, Research in Higher Education 46(4):

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