Meredith Turner / Sunday, January 1, 2017

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Overview of Results From the 2016 Income and Employment Survey

Amy DuVernet, Mark Poteet, Brandy Parker, Kate Conley, and Anne Herman

Have you been wondering about the latest SIOP salary report?

Itching to leverage data and insights in order to make your next move?

Hoping for some fresh numbers against which to benchmark or to cite when approaching your employer about that well-deserved raise?

Good news! These data have been collected and are now available in a variety of formats. Read on to learn more about key findings and trends found in the 2014 and 2015 income, benefits, and employment-related survey data. For those of you looking for more detail, the most recent technical report is available here and provides an in-depth reporting of the data collection effort, analyses, and results. For those who’d prefer a quick snapshot of the results, a summary of the major findings are visualized in an accompanying infographic available here. Finally, we’ve planned two additional articles to provide a deep dive into the major correlates of income data as well as gaps in the incomes reported by various subgroups.

Background

For the past 2 decades, SIOP has partnered with the Human Resources Research Organization (HumRRO) every 3 years to collect, analyze, and report income and employment information from its members. The 2016 survey marked a change in this arrangement; for the current survey, a volunteer SIOP committee was asked to administer, analyze, and report findings. This change aligns well with former SIOP President Steve Kozlowski’s call for a greater utilization of the volunteer forces available in our membership (2015).

As you review the results, you may notice some changes in style and output (e.g., infographic); we like to think our added touches contribute value to this continued effort. Of course, we would love to hear your feedback, answer any questions, or provide any additional information that we may have missed; email us your thoughts here.

Survey Preparation and Administration

The 2016 survey was administered using Sirota Survey Intelligence (“Sirota”); as such, Sirota personnel assisted in the survey design, programming, administration, and data collection. In addition, the chairs of multiple SIOP committees were asked to review the survey and offer feedback. Their review resulted in several updates, including an expanded list of certifications, revised background information categories (e.g., added “International Affiliate” to the membership item), and the deletion of a section focused on measuring the income and employment impact of the 2008–2009 recession. Additional reviews were conducted by members the Professional Practice and Membership Committees in order to ensure (a) proper operation of text boxes and response options, (b) proper item branching and page continuation, (c) inclusion of all relevant information, and (d) formatting and spelling accuracy.

The final draft of the survey was pilot tested with several members of the Professional Practice, Membership, and Scientific Affairs Committees. Representatives from Sirota, SIOP, and the income survey team reviewed respondents’ feedback, making final updates based on this review (e.g., expanding list of metro areas to measure respondents’ location, clarify survey instructions).

The survey was launched on June 16, 2016. Despite pilot testing, several respondents reported technical issues preventing survey completion. In response, the survey was paused while these issues were addressed. The survey was relaunched on June 21, 2016 and closed on July 18, 2016.

Sample Characteristics

A link to the survey was sent via electronic mail to 4,996 members of SIOP with active email addresses on record. A total of 1,199 responses were received, representing a 24% response rate. After data cleaning (which included removing respondents who did not provide income information for 2014 and 2015), a total of 1,120 usable responses remained. Characteristics of this sample can be seen in Table 1. For all analyses, we focused on data provided by the 1,069 respondents who indicated that they worked full time.

As has been the case in prior survey administrations, the percentage of female respondents has increased, representing 49% of current responses. Similarly, the percentage of master’s degree respondents has increased over time, from 7% in 2007 to 23% in the current survey. These results mirror SIOP membership population representation; 77% of SIOP members hold doctorate degrees, whereas 23% either hold a master’s degree or are considered ABD.

The current sample is also reasonably similar to the SIOP membership population as a whole with regard to membership types, industry, and years of experience. The sample included a slightly greater percentage of members than that of the population (62.2%) and slightly lower percentages of Associates, Fellows, and International Affiliates (23.1%, 6.3%, and 8.4 %, respectively). Although the percentage of respondents representing different industries was similar to that of the 2012 income and employment survey sample (Khanna, Medsker, & Ginter, 2013), the private sector was slightly overrepresented when compared with the SIOP membership population; 51.0% of the current sample reported working in the private sector whereas 46.3% of the SIOP membership population works in the private sector. Finally, the sample was fairly representative with regard to years since doctorate with slightly more of the sample reporting earning their degrees 25 or more years ago than is found in the overall SIOP membership population (25% in the population vs. 18% in the sample). A more detailed review of the representativeness of this sample is provided in the technical report here.

Table 1

Good News! Our Incomes Are Rising!

The median primary income for an I-O psychologist has been rising over time, with an average increase of approximately $1,700 per year for master’s level I-Os and $2,200 per year for doctorate level I-Os between 1999 and 2015. Figure 1 depicts the upward trend in earnings at both the master’s and doctorate level. This upward trend is in line with documented inflation rates, indicating that these two degrees have maintained their relative value over time.¹

Figure 1. Median Primary Income Over Time by Highest I-O Degree Achieved

What Impact Does One’s Degree and Experience Have?

Previous administrations of the SIOP salary survey have indicated that education and experience level influence reported earnings. For example, the correlation between years of work experience and 2012 primary income was .45 (p < .05) and between one’s highest degree obtained and income was .20 (p < .05; Khanna et al., 2013). The current survey produced similar results; both relationships were significant (p < .05), with the relationship between experience being stronger (r = .38) than that of degree earned (r = .23). Below we provide a breakdown of differences across these various background variables.

Degree. On average, terminal master’s degree programs are completed in 2.5 years whereas doctoral programs are completed in 5.3 years (Rentsch, Lowenberg, Barnes-Farrell, & Menard, 1997). What is the impact of those additional years of education? The difference in annual incomes reported across degree types is evident in Figure 1. Doctorate level I-Os reported earning 41% greater median primary income than did master’s level I-Os. The average incomes of respondents holding doctorate degrees ($138,944) were significantly greater than those of respondents holding master’s degrees ($93,943; t(1061) = 7.06, p < .001). Of note is the relative stability of this difference over time which peaked in 2011, when doctorate level I-Os reported earning 47% more, and hit its lowest point in 2000, when the reported incomes of doctorate level I-Os were 34% greater than those of master’s level I-Os.

Years of relevant experience. Beyond educational background, experience also plays an important role in determining I-O income. As relevant experience accumulates, I-Os report earning higher annual income. On average, I-Os with master’s earn $2,869 more for every year of experience; whereas, I-Os with doctorates earn an additional $3,047 for every year of experience.² Figure 2 provides a summary of median income by years of experience. Of note is the income plateau associated with 20 or more years of experience, indicating that, on average, income does not substantially increase beyond this point.

Figure 2. Median 2015 Primary Income by Years of Experience³

Starting salary. All you graduate students and recent grads out there may be wondering what you should expect to make as you begin your career. To provide an answer, we looked at the 2015 incomes of respondents who reported receiving their degree between 2013 and 2015. Those who recently received a doctorate degree earned a median primary income of $89,300 (n = 124) in 2015. Those with recent master’s degrees reported a median primary income of $67,000 (n = 67) in 2015.

Area of Employment

Previous administrations of this survey have identified various employment factors that are likely to impact income, including career path and employment location. For example, in 2012, the relationship between respondent’s status as an academic and income was small yet significant (r = -.13, p < .05); current results mirror those previous findings (r = -.17, p < .05). Below we summarize income differences across career path, industry, and location.

Career path. A little less than a third (28.8%) of respondents reported working as an academic; whereas over two-thirds represented the practitioner population. Results indicated that career path produced a significant impact on income (t(1063) = 2.77, p < .05). As seen in Figure 3, practitioners also reported slightly higher median incomes than academics in 2015.

Figure 3. Median Primary Income by Career Path³

Differences between the incomes earned across different career paths could be masked by a potential confound of career path with highest degree earned. Indeed, although only 3% (n = 10) of academic I-Os report a master’s as their highest degree earned, 31% (n = 297) of practitioners reported the same. Differences between these career paths become more pronounced when the highest degree earned is considered (see Figure 4); master’s level practitioners earned 33% more than master’s level academics, and doctorate level practitioners reported earning 23% more than their academic counterparts. Thus, career path does appear to produce a substantial impact on income when degree is taken into account.

One final point of interest pertains to the number of hours that each career path reported working on average per week. Whereas I-Os working in academia made 23–31% less than practitioners with the same qualifications, they reported averaging 5 additional work hours per week; the median number of hours that practitioners reported averaging per week was 45, whereas the median number of average hours per week reported by academics equaled 50.

Figure 4. Median 2015 Primary Income by Career Path and Highest Degree Earned

Industry. Survey respondents represented a number of industries ranging from IT and computers to government and military, with the two most common industries being academic (university or college) and consulting. Figure 5 provides the median annual income by industry for master’s and doctorate level I-Os combined. Self-employed consultants and I-Os working in IT reported the greatest median primary incomes, whereas those in state or local government reported the lowest annual median incomes. The results related to self-employed consultants are likely driven, in part, by the variable nature of this industry; indeed, the incomes reported by self-employed consultants ranged from $25,000 to $1,000,000, representing the greatest variance (σ = $177,180.91) in income within the industries investigated.

Figure 5. Median 2015 Primary Income by Industry³

Location

Although survey respondents represented a breadth of geographies, clusters of I-Os working in specific areas emerged. Table 2 presents the range of locations employing I-Os and provides median primary incomes associated with these areas for master’s and doctorate level I-Os combined. Washington DC represented the most common location for I-Os, followed by Chicago, IL. Median primary incomes adjusted for cost of living⁴ displayed a considerable amount of variance across location. Based on cost of living calculations, the Minneapolis/St. Paul, MN and Detroit, MI areas represent the locations in which I-Os earned the highest relative incomes; however, differences across geographic areas are likely impacted by differences in the percentage of doctorate respondents working in each area.

Table 2 presents the annual median income by location, including the percentage of doctorate and practitioner respondents working in each area. Locations with the lowest numbers of doctorate level I-O responding to the survey tended to also represent the areas where respondents reported receiving the lowest cost-of-living adjusted median incomes. For example, although respondents from Manhattan reported the lowest cost-of-living adjusted median incomes (i.e., $67,671), these respondents were also less likely to hold doctorate degrees than respondents working in other areas (i.e., 65% of respondents in Manhattan reported holding a doctorate degree vs. greater than 70% in other areas). Of note, is the dramatic difference in median income reported by respondents in Manhattan when compared with that of the 2012 survey; this and other differences over time are further explored in the technical report.

Table 2

Annual 2015 Primary Median Across Geographic Locations³

Conclusion

Overall, these data point to the maintained value of our professional services. Comparisons with previous years’ data collection efforts indicate that SIOP members report increases in median incomes that are in line with national inflation levels, ranging from a yearly increase of $2,869 for master’s level I-Os and $3,047 for doctorates.

The results further indicate that several factors impact the annual primary median incomes reported by SIOP membership. Education level has a significant impact on median income, with the median income reported by doctorate level I-Os being $34,318 greater than that of master’s level I-Os. Median income levels also varied across other employment-related factors, including relevant experience level, career path, industry of employment, and geographic location. In a future article, we’ll provide detail around the relative contribution of these variables to the prediction of I-O income. We’ll also take a closer look at gaps in income across various subgroups. Stay tuned for these additional insights and be sure to check out the technical report for greater detail around all of these findings.

Notes

^{^[1]} Using the United States Bureau of Labor Statistics (n.d.) Consumer Price Index inflation calculator, the median salary for a master’s level I-O reported in 1999 ($58,000) would produce the same buying power as a salary of $82,514.92 in 2015. The median salary for a PhD level I-O reported in 1999 ($83,000) would produce the same buying power as a salary of $118,081.70 in 2015.

² Values reflect unstandardized slope coefficients derived via simple regression analyses.

³ Figures 2, 3, and 5 and Table 2 contain combined data for master’s and doctorate level respondents. For a more detailed breakdown of primary income, please see the technical report here.

⁴ Cost of living calculated using the PayScale, Inc. Cost of Living Calculator (2016); all incomes were adjusted to their Washington, DC equivalent using psychologist as the job title.

⁵ Less than 10 respondents reported working in Miami, FL and Phoenix, AZ, therefore, incomes representing these US metropolitan areas were combined to protect respondent anonymity.

⁶ Less than 10 respondents reported working in Ottawa, Ontario; Vancouver, BC; Calgary, Alberta; and Toronto, Ontario; therefore, incomes representing these Canadian metropolitan areas were combined to protect respondent anonymity.

References

Bureau of Labor Statistics, U.S. Department of Labor. (n.d.). CPI inflation calculator. Retrieved from http://www.bls.gov/data/inflation_calculator.htm

Khanna, C., Medsker, G. J., & Ginter, R. (2013). 2012 income and employment survey results for the Society for Industrial and Organizational Psychology. Bowling Green, OH: Society for Industrial and Organizational Psychology. Retrieved from http://0-www-siop-org.library.alliant.edu/2012SIOPIncomeSurvey.pdf

Kozlowski, S. W. J. (July, 2015). President’s message. The Industrial Psychologist, 53(1), 6-10.

PayScale, Inc. (2016). Cost of living calculator. Retrieved from http://www.payscale.com/cost-of-living-calculator

Rentsch, J. R., Lowenberg, G., Barnes-Farrell, J., & Menard, D. (July, 1997). Report on the survey of graduate programs in industrial/organizational psychology and organizational behavior/human resources. The Industrial Psychologist, 35(1), 49-68.

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