Engineer Missouri
Prepared by: Thomas G. Johnson and James D. Rossi
Community Policy Analysis Center (CPAC)
University of Missouri – Columbia
September 15, 2013
Executive Summary
 Government projections suggest strong growth in employment in Science, Technology,
Engineering, and Mathematics (STEM) occupations over the coming years. Moreover, a
2009 survey of manufacturing firms revealed that 36 percent of firms reported a shortage
of scientists and engineers today. Despite the demand for these skills, the enrollment of
U.S. citizens and permanent residents in graduate programs has decreased since the early
1990s. The Missouri Economic Research and Information Center projects a total of
15,753 job openings by the year 2020 in engineering occupations in Missouri.
 Missouri ranks below the national average in the proportion of its workforce employed in
18 of 23engineering occupations for which data are available. Moreover, Missouri ranks
26th among U.S. states in engineers as a proportion of the workforce.
 Holders of STEM degrees earn 11 percent more per hour in non-STEM fields and 20
percent more per hour in STEM fields than their non-STEM degree holding counterparts.
 STEM occupations pay better than non-STEM occupations: in Missouri, workers
inSTEM sectors earn 29.7 percent more with a high school education, 32.4 percent more
with an associate’s or other post-secondary degree, and 32.4 percent more with a
bachelor’s degree than non-STEM workers. All engineering occupations for which data
are available report average salaries in excess of the state average salary.
 In 2011, there were over 9,200 undergraduate and 2,700 graduate students enrolled in
engineering programs at Missouri’s universities. During the 2010 – 2011 school year
Missouri’s universities awarded 1,635 bachelor’s degrees, 945 master’s degrees, and 136
doctoral degrees in engineering.
 A 2006 analysis revealed that among technology BS and MS graduates, 67 percent of
domestic students and 75 percent of foreign-born students were likely to stay in the areas
where they earned their degrees. Among doctoral degree holders (all fields of study)
working outside of academia, 52 percent of domestic students and 41 percent of foreign
students were likely to stay.
 Given the right economic conditions, the number of engineering jobs in a state can
increase on nearly a one-to-one basis with the number of graduates.
 There are nearly 50,000 engineers employed in Missouri earning an average salary of
$81,058. The roughly $4 billion in wages paid to Missouri’s engineers contributes an
additional 27,000 jobs to the Missouri economy, an extra $1.1 billion in wages to
Missouri workers, and $3.4 billion to state GDP.
 Missouri’s engineers contribute $218.6 million to Missouri’s state and local governments
annually.
 For every one additional engineer employed in a state’s workforce, state real gross
domestic product (GDP) increases by over $3 million.
 For every one additional engineer per 1,000 jobs, per capita state GDP increases by
$219.48 and real personal income per capita increases by $171.17.
 Missouri’s number of patents per 1,000 workers is less than half the national average.
High patenting regions have been found to produce as much as $4,300 more per worker
than low-patenting regions. For every 28.6 engineers working in a given state, one
additional patent is produced, on average.
 Missouri consistently ranks in the bottom third of U.S. states in high-technology
establishments as a percentage of all business establishments. This prevents Missouri’s
economy from growing through the first-mover advantage often enjoyed byhightechnology firms.
 Missouri lags behind other states in the amount of federal Small Business Innovation
Research Funding and venture capital investment. Increasing Missouri’s performance in
these two indicators is important to future economic growth.
Engineer Missouri
Thomas G. Johnson and James D. Rossi
I. Introduction
In his State of the Union addresses, President Barack Obama has frequently repeated a
clarion call for the United States to educate and train a new generation of workers and educators
in Science, Technology, Engineering, and Mathematics (STEM) skills to assure that the U.S.
remains competitive in the global economy (e.g. Robelen, 2011; Koebler, 2012; Brenchley,
2013). In December 2012, the Obama administration formally adopted this policy, declaring a
cross-agency-policy goal of increasing the number of STEM graduates by one million more
graduates in the next decade (Feder, 2012).
The U.S. Department of Commerce (2012) notes that not only was job growth in STEM
fields nearly three-times greater than in non-STEM fields over the period 2000 – 2010, but that
over the period 2008 – 2018 STEM fields are projected to have nearly twice as much job growth
as non-STEM fields.
The Bureau of Labor Statistics predicts that science and engineering jobs
are projected to grow by 21.4 percent during the period 2006 and 2016. Of this growth,
approximately 64 percent of the projected increase is in computer and mathematical scientist
occupations. Engineering jobs are predicted to grow by 10.6 percent over the period (National
Science Foundation, 2010)
Further, in a 2009 survey of the manufacturing sector, 36 percent of firms surveyed
reported moderate to severe shortages of scientists and engineers today with many seeing future
shortages a serious concern. Within specific industries, 74 percent of energy and resources
firms, 63 percent of aerospace and defense firms, 43 percent of industrial products firms, and 38
percent of consumer products and life sciences firms reported moderate to severe shortages of
scientists and engineers (Deloitte, 2009). A shortage of workers, all else equal, leads to higher
wages and lower unemployment for workers with those particular skills in demand, but at the
same time will limit the rate of economic growth in the economy.
It is also important to point out that STEM skills are also in demand in non-STEM
industries with nearly two-thirds of workers with STEM undergraduate degrees working in nonSTEM industries. Further, workers with STEM degrees in non-STEM fields earn 11 percent
more per hour than their non-STEM degree holding counterparts. When only STEM industry
occupations are considered, this earnings-differential increases to 20 percent (U.S. Department of
Commerce, 2012). the National Science Foundationfound that in 2003holders of science and
engineering bachelor’s degrees earned more than those without science and engineering degrees
in every year except in the first four years following graduation, (National Science Foundation,
2010).
STEM occupations typically require a college education. In fact, nearly 75 percent of
those in science and engineering occupations in 2007 held at least a bachelor’s degree. 43.8
percent of all workers in science and engineering jobs held a bachelors degree, 21.3 percent held
a master’s degree, 1.2 percent held a professional degree, and 6.7 percent held a doctorate degree
(National Science Foundation, 2010). As such, in order to produce a qualified supply of STEM
workers, it is imperative that enough educational opportunities exist.
Further, there is evidence that the U.S. is not remaining competitive in the production of
STEM degree-holders relative to other industrialized nations. Of even greater concern, the
enrollments of U.S. citizens and permanent residents in graduate programs have decreased since
their 1990s peaks. Additionally, an increasing percentage of students in STEM fields are
foreign-born (for example, in 1982 one-fourth of graduate students in science and engineering
fields were foreign born whereas now more than one-third are foreign born). Foreign student
enrollments are not a concern if we can retain these students post-graduation, however many
countries such as China, have created programs aimed at sending students to the U.S. for an
education and then providing economic incentives, such as employment and salary guarantees,to
assure that they return to their home countries(Committee on Prospering in the Global Economy
of the 21st century, 2007). Of the 27 Organization for Economic Co-Operation and Development
(OECD) countries for which data are availablein 2010, the U.S. ranked dead last in the
proportion of college graduates with degrees in engineering (OECD StatExtract, 2013).
It has been suggested that the declining share of science and engineering graduates is
hampering the U.S.’s comparative economic advantage. This reduced comparative advantage
will inevitably reduce America’s traditional dominance in high-tech industries, research and
development (R&D), and other scientific and engineering-related industries. Recovering this
comparative advantage will require a restructuring of the U.S. labor force and will require new
policies to adapt to the changing global environment (Freeman, 2005).
The structure of this paper is as follows: in the next section, Missouri’s need for
engineering graduates is discussed; in the third section, the state of engineering education in
Missouri is discussed; in the fourth section, factors influencing the migration patterns and
retention of engineering graduates are discussed; in the fifth section, the economic impact of
engineers on Missouri’s economy is presented; in the sixth section, the effect of engineers on
innovation and economic growth is discussed; in the seventh section, Missouri is compared with
other Midwestern states; and finally, in the seventh section, conclusions are offered.
II. Missouri and the Need for Engineers
The state’s current performance in training and retaining engineering graduates is best
exemplified by calculating location quotients1for various engineering occupations in Missouri.
A location quotient measures the share of employment in a given industry, in a given region,
relative to that industry’s share of employment in a reference region (in this case, the reference
region is the United States). For example, if a given occupation in Missouri comprised 4 percent
of total employment in Missouri compared with only 2 percent in the national economy, then that
occupation would have a location quotient of 2.00 in Missouri.
The interpretation of location quotients is as follows: 1) A location quotient of less than
1.00 indicates that there is less employment in that occupation than would be expected indicating
that there is either a shortage of jobs or potential employees in industries employing that
occupation; 2) a location quotient of 1.00 indicates that the employment in the occupation is
equal to the share found in the reference economy; and 3) a location quotient of greater than 1.00
indicates that employment in that occupationis relatively greater than in the reference economy
and that the economy has a comparative advantage in goods and services employing this
occupation. Location quotients greater than 1.00 often identify a region’s economic base and if
these are higher wage and productivity occupations then this is an indication that the region’s
1
economy performing well. When the larger location quotients are in lower wage and lower
productivity occupations, the region’s economy is generally underperforming.
Table 1 below provides a list of engineering occupations in Missouri2, their associated
location quotients, the number of persons employed in that occupation per 1000 jobs in the
Missouri economy, and Missouri’s rank relative to the other states. As can be seen in Table 1,
Missouri ranks below the national average for employment share in eighteen of the twentythreeoccupationsfor which employment shares were available and in the bottom half of states for
eighteen of those occupations. For all engineering occupations, Missouri ranks twentysixthamong U.S. states with a location quotient of only 0.80.
Table 1: Location Quotient and Number of Engineers per 1000 Jobs for Missouri 2012
Occupation Title3
Architectural and Engineering Managers
Cost Estimators
Software Developers, Applications
Software Developers, Systems Software
Architects, Except Landscape and Naval
Surveyors
Aerospace Engineers
Agricultural Engineers
Biomedical Engineers
Chemical Engineers
Civil Engineers
2
Location
Quotient
0.65
1.26
1.20
0.36
1.34
0.23
0.58
0.63
0.42
0.66
0.80
Number Per
1000 Jobs
0.938
1.881
5.412
1.072
0.850
0.75
0.356
0.012
0.061
0.163
1.592
State4
Rank
35(48)
9(50)
9(50)
36(48)
5(50)
43(50)
16(31)
17(19)
22(33)
29(45)
33(49)
The occupations included as engineering occupations were based on the Missouri Economic Research and
Information Center’s list of engineering occupations. The occupations were further refined to only include
engineering jobs that required at least a bachelor’s degree. A further modification was made to exclude natural
science managers and foresters based on the low percentage of engineers filling these occupations and the lack of
employment of these occupations within engineering firms based on the Bureau of Labor Statistics’ Occupation
Profiles. As such, the list of engineering occupations can be considered a conservative listing of engineering
occupations.
3
Data for some occupations were not disclosed because of insufficient numbers. These occupations have been
removed from the table. A full list of engineering occupations is available in Table A1 in the Appendix.
4
Due to disclosure requirements, the BLS does not report values for all states. The number of states with a reported
value is given in parentheses.
0.08
Computer Hardware Engineers
1.02
Electrical Engineers
0.73
Electronics Engineers, Except Computer
0.68
Environmental Engineers
0.92
Health and Safety Engineers, Except Mining Safety
Engineers and Inspectors
0.92
Industrial Engineers
0.77
Materials Engineers
0.70
Mechanical Engineers
1.52
Mining and Geological Engineers, Including Mining
Safety Engineers
0.59
Engineers, All Other
0.80
Materials Scientists
0.46
Engineering Teachers, Postsecondary
0.80
All Engineering Occupations
Source: Bureau of Labor Statistics, Occupational Employment Statistics
0.051
1.257
0.755
0.266
0.165
42(42)
18(50)
25(47)
39(50)
27(50)
1.550
0.134
1.353
0.089
22(50)
25(50)
33(50)
16(32)
0.553
0.049
0.121
19.226
32(48)
20(29)
38(40)
27(50)
At the national level, STEM workers out-earn their non-STEM counterparts at every
level of education (U.S. Department of Commerce, 2012). In 2010, STEM workers with only a
high school diploma or less earned 59.6 percent more per hour than non-STEM workers with
similar education ($24.82 hour and $15.55, respectively). Workers with some college or an
associate degree earned 40 percent more in STEM occupations ($26.63 versus $19.02).
Bachelor’s degree holders earned 26.7 percent more in STEM fields ($35.81 versus $28.27).
And STEM workers with a graduate degree earned 12.3 percent more than their non-STEM
counterparts ($40.69 versus $36.22).
In Missouri the pattern of higher wages for STEM workers follows the national pattern.
The Missouri Economic Research and Information Center (MERIC) estimates that workers in
STEM occupations, with only a high school education, earn 29.7 percent more than their nonSTEM counterparts. When those with an associate’s or other post-secondary degree are
considered, the pay differential increases to 32.4 percent more for STEM workers. For those
with a bachelor’s degree, the pay gap shrinks somewhat, but still remains at 27.3 percent (2012).
Each of the twenty six engineering occupationsfor which salariesare reportedpay a mean
salary in excess of the state mean salary ($41,170) as can be seen in Table 2. While many of
these occupations (22 of 24) pay below the national average salary for that occupation, it is
important to note that Missouri’s cost of living is below the national average, with a cost of
living of 93 percent of the national average in 2012 (Missouri Economic Research and
Information Center, 2013). However, the majority (17 of 24) of the occupations pay salaries less
than 93 percent of the national average for that occupation.
The need to educate, train, and retain an increased number of engineers is also
highlighted by employment projections for these occupations for the year 2020 (Tables 3 and 4).
The Missouri Economic Research and Information Center (2012) projects a total of 15,753 job
openings by the year 2020 including 6,704 growth openings and 9,049 replacement openings.
The greatest areas of need are found in the fields of applications software developers (2,513),
cost estimators (2,345), and mechanical engineers (1,708).
Table 2: Mean Annual Salary of Engineering Occupations in Missouri and the U.S., 2012
Occupation Title
Architectural and Engineering
Managers
Cost Estimators
Software Developers, Applications
Software Developers, Systems Software
Architects, Except Landscape and
Naval
Surveyors
Missouri
Mean Salary
U.S. Mean
Salary
State
Rank
$116,580
Missouri
Median
Salary
$114,100
$133,240
31(49)
$60,570
$84,600
$93,180
$72,170
$57,400
$83,430
$89,790
$68,820
$63,080
$93,280
$102,550
$78,690
23(50)
25(50)
25(50)
31(50)
$58,160
$50,910
$40,190
19(50)
$98,950
$101,170
Aerospace Engineers
$82,030
$82,390
Agricultural Engineers
$61,860
$58,140
Biomedical Engineers
$88,860
$87,530
Chemical Engineers
$73,550
$69,350
Civil Engineers
$81,110
$82,310
Computer Hardware Engineers
$87,440
$86,920
Electrical Engineers
$84,030
$81,690
Electronics Engineers, Except
Computer
$73,030
$68,510
Environmental Engineers
$74,930
$74,200
Health and Safety Engineers, Except
Mining Safety Engineers and
Inspectors
$77,540
$75,300
Industrial Engineers
$86,230
$86,450
Marine Engineers and Naval Architects
$78,360
$76,140
Mechanical Engineers
$81,320
$78,480
Mining and Geological Engineers,
Including Mining Safety Engineers
$86,300
$88,380
Engineers, All Other
$73,260
$67,250
Materials Scientists
$58,100
$51,650
Architecture Teachers, Postsecondary
$85,290
$80,140
Engineering Teachers, Postsecondary
$81,058
N/A
All Engineering Occupations
Source: Bureau of Labor Statistics, Occupational Employment Statistics
$104,810
$77,370
$91,200
$102,270
$84,140
$103,980
$91,810
$95,250
19(38)
3(19)
33(34)
33(45)
37(49)
38(44)
21(49)
34(48)
$85,140
$79,760
47(50)
25(50)
$82,100
$96,140
$84,770
$91,250
32(50)
9(18)
32(50)
17(32)
$93,330
$89,740
$78,770
$100,100
$93,492
27(48)
26(31)
24(24)
32(39)
33(50)
Table 3: 2010 and 2012 Employment and 2020 Projected Employment in Engineering
Occupations, Missouri
Occupation Title
Architectural and Engineering Managers
Cost Estimators
Software Developers, Applications
Software Developers, Systems Software
Architects, Except Landscape and Naval
Surveyors
Aerospace Engineers
Agricultural Engineers
Biomedical Engineers
5
NP indicates no projected value reported.
2010
Employment
2012
Employment
2,496
4,501
12,285
4,595
2,570
884
N/A
N/A
198
2,450
4,900
14,100
2,790
2,220
600
930
30
160
2020
Projected
Employment
2,655
5,983
13,521
5,697
2,942
1,010
NP5
NP
330
368
430
413
Chemical Engineers
4,629
4,150
5,187
Civil Engineers
219
130
246
Computer Hardware Engineers
3,544
3,280
3,866
Electrical Engineers
2,068
1,970
2,134
Electronics Engineers, Except Computer
786
690
886
Environmental Engineers
342
430
401
Health and Safety Engineers, Except Mining
Safety Engineers and Inspectors
3,338
4,040
3,644
Industrial Engineers
329
350
384
Materials Engineers
3,841
3,530
4,313
Mechanical Engineers
144
230
165
Mining and Geological Engineers, Including
Mining Safety Engineers
N/A
N/A
N/A
Nuclear Engineers
N/A
N/A
N/A
Petroleum Engineers
1,341
1,440
1,390
Engineers, All Other
83
130
87
Materials Scientists
104
0
108
Architecture Teachers, Postsecondary
320
310
327
Engineering Teachers, Postsecondary
48,895
49,290
55,689
All Engineering Occupations
Source: Bureau of Labor Statistics, Occupational Employment Statisticsand Missouri Economic
Research & Information Center
Table 4: Projected Engineering Job Openings by Occupation 2010-2020, Missouri
Occupation Title
Architectural and Engineering Managers
Cost Estimators
Software Developers, Applications
Software Developers, Systems Software
Architects, Except Landscape and Naval
Surveyors
Aerospace Engineers
Agricultural Engineers
Biomedical Engineers
Chemical Engineers
Civil Engineers
Computer Hardware Engineers
Electrical Engineers
Electronics Engineers, Except Computer
Environmental Engineers
Health and Safety Engineers, Except Mining
Growth
Openings
159
1,482
1,236
1,102
372
126
NP
NP
132
45
558
27
322
66
100
59
Replacement
Openings
487
863
1,277
478
522
192
NP
NP
44
118
940
52
854
499
173
74
Total
Openings
646
2,345
2,513
1,580
894
318
NP
NP
176
163
1,498
79
1,176
565
273
133
Safety Engineers and Inspectors
306
Industrial Engineers
55
Materials Engineers
472
Mechanical Engineers
21
Mining and Geological Engineers, Including
Mining Safety Engineers
NP
Nuclear Engineers
NP
Petroleum Engineers
49
Engineers, All Other
4
Materials Scientists
4
Architecture Teachers, Postsecondary
7
Engineering Teachers, Postsecondary
6,704
Total Projected Openings
Source: Missouri Economic Research & Information Center
727
91
1,236
32
1,033
146
1,708
53
NP
NP
295
27
17
51
9,049
NP
NP
344
31
21
58
15,753
III. Engineering Education in Missouri6
In 2011, there were over 9,200 undergraduate engineering students enrolled in Missouri
universities (Table 5). Of these students, over 8,500 were enrolled as full-time students while
570 were enrolled as part-time students. The Missouri University of Science and Technology
had the most undergraduate students enrolled, accounting for over 4,200 students. The
University of Missouri – Columbia had the second highest number of enrolled undergraduates
with over 2,500 students. Of the full-time students, 25.6 percentwere freshmen, 20.6 percent
were sophomores, 21.9 percentwere juniors and the remaining 31.8 percentwere seniors7.
Data for University of Missouri – St. Louis were not available.
A possible explanation for the larger senior class relative to the other classes is that some students take a 5th year to
complete their degree and would be included in the senior totals.
6
7
Table 5: Undergraduate Engineering Enrollment, Fall 20118
University9
Freshman
(FT10)
667
89
950
178
45
283
2,212
Sophomore
(FT)
470
97
760
127
19
305
1,778
Junior
(FT)
497
117
845
106
9
313
1,887
Senior
(FT)
786
182
1,331
131
10
319
2,749
Total
(FT)
2,420
485
3,886
542
83
1,220
8,636
Parttime
114
145
320
6
0
0
585
MU
MU-KC
S&T
SLU
SEMO
WU-SL
Total Undergraduate
Enrollment
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Truman (2013)
Missouri’s universities graduated a total of 1,635 students with bachelorof engineering
degrees during the 2010 – 2011 school year (Table 6). Not surprisingly, the Missouri University
of Science and Technology and the University of Missouri – Columbia graduated the largest
number of students, 785 and 422 respectively. The most common types of engineering degrees
were: 1) mechanical engineering (386 degrees awarded), 2) civil engineering (203), 3) and
computer science (196).
Table 6: Bachelor’s Degrees Awarded, 2010-2011, by School and Degree Field
Degree Field
MU
Aerospace
Architectural
Biomedical
Chemical
Civil
0
0
40
32
75
MU-KC S&T SLU
0
0
0
0
19
49
48
0
53
98
36
0
17
0
0
SEMO
WU-SL
Total
0
0
0
0
0
2
0
75
31
11
87
48
132
116
203
St. Louis University and Washington University – St. Louis are both private schools.
MU: University of Missouri, MU-KC: University of Missouri – Kansas City, S&T: Missouri University of Science
and Technology, SLU: St. Louis University, SEMO: Southeast Missouri State University, and WU-SL: Washington
University in St. Louis.
10
FT: Full-time
8
9
11
0
45
3
0
8
Computer
67
76
25
52
0
0
43
Computer Science
196
48
0
79
6
0
12
Electrical
145
0
9
0
0
0
0
Electrical/ Computer
9
Engineering
0
0
49
0
0
0
Engineering Management
49
0
0
0
0
3
0
Engineering Science &
3
Engineering Physics
0
0
13
0
0
0
Environmental
13
29
0
0
0
0
0
Industrial/ Manufacturing
29
111
25
173
19
0
58
Mechanical
386
0
0
36
0
0
0
Metallurgical & Materials
36
0
0
44
0
0
0
Mining
44
0
0
20
0
0
0
Nuclear
20
0
0
6
0
0
26
Other
32
0
0
20
0
0
0
Petroleum
20
Total Bachelor’s Degrees
422
78
785
81
3
266
1,635
Awarded
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Truman (2013)
In addition to the undergraduates, Missouri’s universities had 2,716 engineering graduate
students enrolled in the fall of 2011 (Table 7). Of these, 1,709 were enrolled in master’s
programs and 1,007 were enrolled in doctoral programs. The Missouri University of Science and
Technology had the greatest number of both masters and doctoral students with 694 and 352,
respectively. Washington University in St. Louis had the second largest number of both master’s
and doctoral students with 369 and 332 students, respectively. Southeast Missouri State
University does not award graduate degrees in any engineering disciplines.
Table 7: Graduate Engineering Enrollment, Fall 2011
University
MU
MU-KC
S&T
SLU
SEMO
Master's
318
301
694
27
0
Ph.D.
267
52
352
4
0
Total
585
353
1,046
31
0
369
332
701
WU-SL
Total Graduate Enrollment
1,709
1,007
2,716
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Truman (2013)
Missouri universities awarded over half as many master’s degrees (945) as they did
bachelor’s degrees during the 2010 – 2011 school year (Table 8). The Missouri University of
Science and Technology and Washington University in St. Louis awarded the most master’s
degrees with 427 and 202 degrees awarded, respectively. Electrical engineering was the most
common field of study for master’s graduates in 2010 – 2011, with 184 degrees awarded. Other
engineering degrees were the second most common with 150 degrees awarded.
Table 8: Master’s Degrees Awarded, 2010-2011, by School and Degree Field11
Degree Field
MU
MU-KC
S&T
SLU WU-SL Total
0
0
13
0
6
Aerospace
19
9
0
0
0
15
Biomedical
24
5
0
6
0
0
Chemical
11
14
9
40
0
6
Civil
69
7
0
9
0
7
Computer
23
12
77
27
0
28
Computer Science
144
40
97
35
0
12
Electrical
184
0
0
0
7
0
Engineering (General)
7
0
0
105
0
14
Engineering Management
119
0
0
16
0
25
Environmental
41
11
0
0
0
0
Industrial/Manufacturing
11
11
11
43
0
34
Mechanical
99
0
0
5
0
0
Metallurgical & Materials
5
0
0
14
0
0
Mining
14
6
0
7
0
0
Nuclear
13
0
0
95
0
55
Other
150
0
0
12
0
0
Petroleum
12
Total Master's Degrees
115
194
427
7
202
945
Awarded
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Truman (2013)
11
Southeast Missouri State University does not have a graduate degree program in engineering.
Missouri universities awarded 136 engineering doctoral degrees during the 2010 – 2011
school year (Table 9). The University of Missouri - Columbia had the highest number of Ph.D.
graduates with 52. The Missouri University of Science and Technology and Washington
University in St. Louis awarded 40 and 35 doctoral degrees respectively. The University of
Missouri – Kansas City awarded five engineering doctoral degrees during the 2010 – 2011
school year. St. Louis University did not award any doctoral degrees during this time.
Computer science and biomedical engineering were the most common doctoral degrees awarded
with 21 and 19 degrees awarded, respectively.
Table 9: Doctoral Degrees Awarded, 2010-2011, by School and Degree Field12
Degree Field
MU
MU-KC
S&T WU-SL Total
0
0
1
1
Aerospace
2
9
0
0
10
Biomedical
19
3
0
4
0
Chemical
7
2
0
3
3
Civil
8
0
0
2
2
Computer
4
8
4
4
5
Computer Science
21
0
0
8
5
Electrical
13
14
0
0
0
Electrical/Computer
14
0
0
2
0
Engineering Management
2
0
0
0
6
Environmental
6
1
0
0
0
Industrial/Manufacturing
1
7
1
6
2
Mechanical
16
0
0
12
0
Metallurgical & Materials
12
8
0
0
0
Nuclear
8
0
0
2
1
Other
3
Total Doctoral Degrees Awarded
52
5
44
35
136
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Truman (2013)
Missouri universities employed a total of 421 full-time tenured or tenure-track and 35
full-time non-tenured/ non-tenure track engineering teaching faculty members during the fall of
12
St. Louis University did not report any engineering doctoral degrees awarded during this period.
2011. The Missouri University of Science and Technology had the greatest number of full-time
tenured or tenure track faculty members with 157 faculty members. It also had the greatest
number of non-tenured/ non-tenure track full-time faculty members with 24. Missouri
universities also employed 136 part-time teaching faculty members (accounting for 35.91 fulltime equivalent positions). Washington University in St. Louis had the greatest number of parttime teaching faculty members employing 68 faculty members (Table 10). Missouri universities
also employed another 73 full-time engineering research faculty members during the fall of 2011
(Table 11). In addition to full-time employees, Missouri universities also employed 26 part-time
research faculty members (accounting for 19.1 full-time equivalent positions).
Table 11: Teaching Faculty, Fall 2011
Full-Time
Part-Time
Tenured/Tenure-Track
Non
Professor Associate Assistant Total T/T-T Total FTE13
52
43
19
114
9
9
8.2
MU
8
11
21
40
0
16
4.38
MU-KC
77
51
29
157
24
38
11.41
S&T
7
9
11
27
2
5
3.25
SLU
2
2
3
7
0
0
0
SEMO
36
23
17
76
0
68
8.67
WU-SL
182
139
100
421
35
136 35.91
Total
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges
Table 12: Research Faculty, Fall 2011
MU
MU-KC
S&T
SLU
SEMO
13
FTE: Full-Time Equivalent
Full-Time
25
0
11
1
0
Part-Time
3
0
11
0
0
FTE
8.5
0
4.14
0
0
36
12
6.46
WU-SL
73
26
19.1
Total
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges
IV. Retaining Engineering Graduates
A challenge faced by many states, particularly those centrally located in the U.S. is the
phenomenon of “brain drain”. Brain drain is the out-migration of young and often-highly
educated persons, the so-called “creative class”, to other cities which are alleged to have greater
amenities such as recreational opportunities, youth culture, climate, etc. (Florida, 2002).
Using a dynamic stock-and-flow model, Bound et al. (2004) find a weak long-term
relationship between the production of bachelor’s degree graduates and the concentration of
college graduates within a state’s labor force. However, they note that the presence of a greater
number of college graduates can attract employers of college graduates, especially for goods and
services which are produced for sale outside of the state (i.e. as state exports). For goods and
services primarily consumed locally (such as in the health care) there is little-to-no relationship.
While this study does not look specifically at STEM graduates, many STEM sectors
(manufacturing, engineering consultancies, etc.) fall into the first category (exporting sectors).
Hansen, Ban, and Huggins (2002) in a survey of recent college graduates from
Pittsburgh-area universities find that the school-specific characteristics such as reputation and
financial considerations were important in the selection of a school, proximity to friends and
family and amenities were major determinants of the decision to stay or relocate following
graduation and not financial considerations. They find that having attended a local area high
school, strong ties to family, and those concerned with housing costs or access to continuing
education were the prime factors in the decision to stay in the Pittsburgh area. Further, the
authors find that which university a student attended was highly correlated with the decision to
stay or leave (Duquesne graduates were likely to stay whereas Carnegie Mellon graduates were
likely to leave). The authors note the difficulty of reconciling policy implications with many of
these findings (e.g. family considerations, climate, etc.), but that others such as offering
competitive salaries and benefits, reducing the costs of tuition, career counseling, increasing
opportunities for women and minorities, and developing and promoting local amenities can be
influenced by policy-makers.
Using a random parameters logit model, Gottlieb and Joseph (2006), find that recent
technology graduates are not as strongly motivated by amenity factors as they are by economic
factors. However, when considering the decisions of technology doctorate holders (working
outside of academia), Gottlieb and Joseph find that doctorate holders are more responsive to
amenity factors than economic conditions. They attribute this finding to doctorate holders
having more bargaining power in hiring negotiations, less susceptibility to general labor market
conditions, and because they are making more long-run decisions because they have finished
their schooling. Most importantly, Gottlieb and Joseph find “a large and significant tendency
among college graduates to stay rather than migrate” (p 653), however, they are quick to caution
that simply increasing enrollments will not guarantee students stay put, particularly if job
opportunities are lacking. They do note that there is a greater tendency to stay when a graduate
is from the university’s home state, however, this “may reflect a selection effect rather than a
treatment effect” (p 654). Finally, they find that immigrant students (who held BS/MS degrees)
were more likely to stay in the areas they earned their degrees (75 percent) than domestic born
students (67 percent); however, for holders of doctorates, the opposite holds true with foreignborn students only 41 percent likely to stay relative to 52 percent of domestic-born students.
In a study of the migration patterns of U.S. born science and engineering doctorate
recipients, Sanderson and Dugoni (2002) find that doctorate recipients were more likely to
exhibit educational mobility both prior to finishing high school (35.5 percent) as well as when
first enrolling in university (37.8) than other undergraduates as a whole. Moreover, 71.1 percent
of doctorate holders received their degree from a university outside of the state in which they
enrolled as undergraduates. Upon graduation, 59.2 percent planned to work in a state other than
the one in which they earned their doctorate.
V. The Economic Impact of Engineers on Missouri’s Economy
There are a variety ways of estimating the economic impact of economic stimuli on a
regional or state economy. Each is based on different assumptions about the ways in which the
economy responds to the stimuli. The impacts of workers, such as engineers, are a source of
income, productivity, and innovation. One common approach is to view the income earned by
workers as a new source of demand for regional products thus generating additional income,
employment and government revenues through a multiplier effect. This so-called backward
linkage approach is used to estimate the impact of engineers on the economy of Kansas for
example (Center for Economic Development and Business Research, 2009).An alternative
assumption is that engineers increase the productivity of existing employers and coworkers, and
attract new employers to the state. These so-called forward linkages are less certain but when
they occur they lead to significantly larger impacts on the economy. In this study, we have used
both methods. The first offers a lower bound while the second is an upper bound on the impacts
that the state of Missouri can expect from additional engineers. This section estimates the lower
bound and the next estimates the upper bounds.
In 2012, there were nearly 50,000 engineers employed in Missouri earning an average salary
of $81,578 (Table 12). The salaries of entry level positions in engineering occupations ranged
from $34,980 for cost estimators to $80,340 for architectural and engineering managers.
Average salaries for engineering occupations ranged from $58,100 for postsecondary
architecture teachers to $116,580 for architectural and engineering managers. For experienced
workers, biomedical engineers were the lowest paid ($68,760) and again, architectural and
engineering managers were the highest paid ($134,700).
Table 12: Engineering Employment and Salaries in Missouri, 2012
Title
Architectural and
Engineering Managers
Cost Estimators
Software Developers,
Applications
Software Developers,
Systems Software
Architects, Except
Landscape and Naval
Surveyors
Aerospace Engineers
Agricultural Engineers
Biomedical Engineers
Chemical Engineers
Civil Engineers
Computer Hardware
Engineers
Electrical Engineers
Electronics Engineers,
Except Computer
Environmental
Engineers
Employment
Mean
Median
Experienced
2,450
Entry
Level
$80,340
$116,580
$114,100
$134,700
4,900
14,100
$34,980
$59,190
$60,570
$84,600
$57,400
$83,430
$73,360
$97,310
2,790
$62,390
$93,180
$89,790
$108,570
2,220
$44,650
$72,170
$68,820
$85,920
600
930
30
160
430
4,150
130
$35,800
$71,890
$62,650
$48,080
$61,170
$49,890
$53,050
$58,160
$98,950
$82,030
$61,860
$88,860
$73,550
$81,110
$50,910
$101,170
$82,390
$58,140
$87,530
$69,350
$82,310
$69,340
$112,480
$91,720
$68,760
$102,700
$85,380
$95,140
3,280
1,970
$60,110
$55,730
$87,440
$84,030
$86,920
$81,690
$101,100
$98,180
690
$48,530
$73,030
$68,510
$85,280
430
$47,770
$74,930
$74,200
$88,510
Health and Safety
Engineers, Except
Mining Safety
Engineers and
Inspectors
4,040
$55,150
$77,540
$75,300
$88,730
Industrial Engineers
N/A
$65,760
$86,230
$86,450
$96,460
Marine Engineers and
Naval Architects
350
N/A
N/A
N/A
N/A
Materials Engineers
3,530
$52,900
$78,360
$76,140
$91,090
Mechanical Engineers
230
$50,970
$81,320
$78,480
$96,490
Mining and Geological
Engineers, Including
Mining Safety
Engineers
N/A
N/A
N/A
N/A
N/A
Nuclear Engineers
N/A
N/A
N/A
N/A
N/A
Petroleum Engineers
1,440
$47,200
$86,300
$88,380
$105,850
Engineers, All Other
130
$49,680
$73,260
$67,250
$85,050
Materials Scientists
N/A
N/A
$58,100
$51,650
N/A
Architecture Teachers,
Postsecondary
310
N/A
$85,290
$80,140
N/A
Engineering Teachers,
Postsecondary
49,290
N/A
$81,578
N/A
N/A
All Engineering
Occupations
Source: Bureau of Labor Statistics, Occupational Employment Statistics and Missouri Economic
Research & Information Center
The economic impact of Missouri’s engineers can be found in Table 13. The direct
impactswere calculatedusing the information in Table 12. Engineering employment in Missouri
has an employment multiplier of 1.55 indicating that for every one engineer employed in
Missouri, an additional 0.55 jobs were created. The $4 billion in salaries paid to Missouri’s
engineers created an additional $1.1 billion in Missouri salaries and $3.375 billion in state GDP;
that is, for every $1 paid in salary to an engineer in Missouri, an additional $0.27 in salaries were
earned by other Missouri workers and state GDP increased by $0.84. For every one engineer
employed in Missouri, $150,062 in state GDP is created. The nearly $7.4 billion in economic
impact of engineers on Missouri’s economy represents over 3 percent of the nearly $222 billion
in state GDP.
Table 13: Economic Impact of Engineers in Missouri, 2012
Employment
Payroll
GDP
Earnings
Direct Effect
49,290
$4,020,970,795
$4,020,970,795
Total Effect14
76,427
$5,106,711,082
$7,396,539,954
Multiplier15
1.55
1.27
1.84
Source:Bureau of Labor Statistics, Occupational Employment Statistics, Missouri Economic
Research & Information Center, and IMPLAN
The impact of engineers on Missouri’s state and local government revenues totaled nearly
$219 million in 2012 (Table 14). Of this $219 million, approximately $21 million of revenues
were from corporate taxes, $89 million in sales tax, $66 million in property taxes (business and
personal), and $20 million in personal income taxes. For each engineer employed in Missouri,
$4,434 in tax receipts was collected by Missouri’s state and local governments.
Table 14: Fiscal Impact of Engineers on Missouri, 2012
Type of Tax
Corporate Taxes
Social Insurance Tax
Sales Tax
Business Property Tax
Other Business Taxes
Personal Income Tax
Personal Property Tax
Other Personal Taxes
Total Tax Revenue
14
Tax Revenues
$20,625,963
$3,216,029
$88,702,472
$66,095,656
$16,150,202
$20,292,526
$397,404
$3,077,546
$218,557,798
Total effect includes the direct effect of engineering employment and salaries and the effects of their purchases
and spending on the Missouri economy.
15
Multiplier is the ratio of total effect to direct effect. Thus, an employment multiplier of 2.5 indicates that for each
direct job created, 1.5 additional jobs are created in the regional economy.
Source:Bureau of Labor Statistics, Occupational Employment Statistics, Missouri Economic
Research & Information Center, and IMPLAN
If we consider the economic impacts of the projected growth in engineering jobs by the
year 2020 in Tables 3 and4, we see that in 2020, Missouri’s projected 55,689 engineers will
accountfor an additional 30,464 jobs in the state (Table 15).16 The $4.5 billion in salaries paid to
Missouri’s engineers will create an additional $1.2 billion in salaries and $3.8 billion in state
GDP (2012 dollars).
Table 15: Projected Economic Impacts of Missouri’s 2020 Projected Engineering
Employment (2012 Dollars)
Employment
Payroll
GDP
Earnings
Direct Effect
55,689
$4,514,063,389 $4,514,063,389
Total Effect
86,153
$5,732,948,064 $8,303,578,765
17
Multiplier
1.55
1.27
1.84
Source:Bureau of Labor Statistics, Occupational Employment Statistics, Missouri Economic
Research & Information Center, and IMPLAN
Moreover, if Missouri’s engineering employment reaches its projected 2020 levels, $245
million (2012 dollars) in tax revenues will accrue to Missouri’s state and local governments
(Table 16). Once again, the majority of the tax revenues will be from sales taxes ($99.6 million)
and property taxes ($74.6 million). Each individual engineer is projected to have an impact of
$4,405.89 on therevenues of Missouri governments.
Table 16: Projected Fiscal Impact of Missouri’s 2020 Projected Engineering Employment
(2012 Dollars)
16
This and other calculations here use the most recent IMPLAN multipliers to project employment impacts in 2020.
In fact, multipliers evolve over time as technology and economic structure changes. By the year 2020, engineering
jobs could have a higher or lower multiplier depending on changes in technology across the economy.
17
These multipliers are roughly equivalent to those estimated for the state of Kansas (Center for Economic
Development and Business Research, 2009).
Type of Tax
Tax Revenues
Corporate Taxes
$23,155,325
Social Insurance Tax
$3,610,410
Sales Tax
$99,580,056
Business Property Tax
$74,200,976
Other Business Taxes
$18,130,703
Personal Income Tax
$22,781,000
Personal Property Tax
$446,138
Other Personal Taxes
$3,454,946
Total Tax Revenue
$245,359,554
Source:Bureau of Labor Statistics, Occupational Employment Statistics, Missouri Economic
Research & Information Center, and IMPLAN
VI. Engineers, Innovation, and Economic Growth
In this section we consider alternative assumptions about the role that engineers play in
the state economy. Increased numbers of engineering graduates are correlated with increased
engineering jobs in the state. We regressed the number of engineering graduates18 by state for
the 2010 – 2011 school year on the increase in the number of engineering jobs by state between
2011 and 2012 (Table A2). We found that for every one additional graduate from a state
institution nearly one additional engineering job was produced (0.90 jobs per engineering
graduate) on average. These results indicate that given the right economic conditions, the
number of engineering jobs in a given state can increase on nearly a one-to-one basis with the
number of graduates. This, of course, is an average, and some states will increase their
engineering jobs more than their number of graduates, essentially capturing the graduates of
other states. Increased graduates must be complemented with attractive climates for employers.
Increasing the number of engineers in an economy has many beneficial effects. An
increased numbers of engineers leads to increases in state gross domestic product (GDP). We
18
Bachelor’s, Master’s and Doctoral graduates including computer science (outside engineering) graduates.
also examined the relationship between the number of engineers in the contiguous 48 states and
real GDP19 over the time period 1999 – 2012 (Table A3). Our analysis indicates that for every
one additional engineer in a given state, on average, that state’s real GDP increased by over $3
million per year. Increasing the relative percentage of engineers as a share of the state workforce
also yields economic benefits. Examining this relationship, the authors find that for every one
additional engineer per 1000 jobs in a given state’s economy, annual per capita real GDP
increases by $219.48(Table A4) and annual real personal income per capita increases by $171.17
(Table A5). Again, these results are based on average performance and a given state’s
performance will depend on other economic economic conditions. In summation, increasing the
number of engineers, all else equal, increases the size of a state’s economy, the productivity of
its workforce, and the incomes of its residents.
Comparing the results in this and the previous sections, we see that the earlier results,
presented in Table 13 indicate, that that state total GDP per engineer is only $148,000, while in
this section, we estimate that each additional engineer increases state total GDP by over $3
million. There are many reasons for this difference. First in table 13, we estimated only the
contribution to state GDP as engineers spend the earnings on goods and services. These impacts
ignore the effect of these engineers on the production side of the economy and their impact on
economy-wide productivity. By considering the experience of all states as they increase their
numbers of engineers we see that the impacts include not only the impacts of engineers’
increased earnings but also the impacts of the goods and services produced by the engineers and
their effect on the productivity of other workers in the economy.
19
Real GDP is GDP that has been adjusted to account for the effects of inflation.
In addition, the results reportedin table 13do not account for the structural change in the
state economy brought about by increasing the number of engineers; in the current sectionwe
account foradjustments in the state economy in response to the change in the number of
engineers.Increasing the number of engineers can lead to innovation which, in turn, can lead to
economic growth. Again, actually realizing the increase in state GDP from increasing the
number of engineers requires that other changes be made toeconomic development policy
changes, investments in infrastructure, etc.
Innovation has long been linked to economic growth. The economic argument here is
relatively straightforward: innovation increases the productivity of labor and other resources,
which, in turn, leads to economic growth20 (Barro, 2003; Barrow and Sala-i-Martin, 2005; Lucas,
1988; and Romer, 1990, 1994).Nobel laureate economist, Robert Solow (1957) found that over
half of the economic growth of the first half of the 20th century was the result of technological
advancements. Moreover, technological advances often lead to “spillovers”; that is, when the
benefits of a given advancement spill over to other industries, inventions, and individuals.
However, these spillovers can inhibit investment in education as the creators of the original
process are often unable to capture all of the benefits of their investment, but often bear the full
brunt of the costs of the research unless a government or other public body helps fund the
research (Griliches, 1992; Nelson and Romer, 1996).
A measure of the innovation related to engineering is the filing of patents21 (Griliches,
1998). Economic estimates of the value of a single patent are approximately half a million
20
Of course, many other factors such as trade, legal systems, and governance impact economic growth. A full
treatment is beyond the scope of this paper.
21
Many empirical studies utilize R&D expenditure as a proxy of innovation. However, as argued by Crosby (2000),
R&D expenditures measures the “input to innovation outputs….The relationship between R&D and innovation
dollars, not counting any benefits to society from the adoption of the technology (Hall, Jaffe, and
Trajtenberg, 2005). Moreover, Rothwellet al. (2013) find that patents do lead to regional
economic growth in the MSA regions of the U.S over the period 1980 – 2012 with highpatenting regions producing as much as $4,300 more per worker than low-patenting regions.
In a 2003 survey of scientists and engineers with prior work experience, the NSF found
that 2.6 percent of scientists and engineers had been named as an inventor on a U.S. patent
application from the fall of 1998 to the fall of 2003. Approximately 15.7 percent of doctoral
degree holders had been named as an inventor compared to only 0.7 percent of bachelor’s degree
holders (National Science Foundation, 2010).
However, as can be seen in Table 17, Missouri lags behind many other states in patent
production. Over the period 2003 – 2010, Missouri’s number of patents awarded per 1,000
workers employed in science and engineering occupations was nearly half of the national
average. Further, Missouri habitually ranked among the bottom states for patent production per
1,000 workers.
Table 17: Patents Awarded per 1,000 Individuals Employed in Science and Engineering
Occupations, 2003 – 2010
Year
2003
2004
2005
2006
2007
2008
2009
United States
17.7
16.6
14.3
16.6
14.2
13.4
14.2
Missouri
9.8
8.8
6.8
7.5
6.9
5.8
6.8
State Rank22
35(50)
36 (49)
41 (50)
39 (49)
39 (50)
38 (47)
35 (48)
outputs is likely to be time varying, possibly nonlinear, and is also likely to occur with uncertain lags ” (p 256)
whereas patents measure the output of innovation.
22
Number of states with data reported in parentheses.
19.4
9.5
35 (47)
2010
Source: National Science Foundation Science and Engineering Indicators, 2012
An examination of the relationship between engineers and utility patent filings for the
period 1999 – 2012 for the contiguous 48 states, the authors find a statistically significant
relationship between the number of engineers in a state and the number of patents filed. For
every additional engineer in a given state, on average, 0.035 additional patents would be filed in
a given year; that is, for each additional 28.6 engineers in a given state, 1 additional patent would
be filed every year (Table A6).
Another measure of the effect of engineers on an economy and their capacity to grow an
economy is the percentage of high-technology establishments of all business establishments in a
state. High technology firms are believed to grow an economy through “first-mover advantage”,
wherein by being the first to introduce a new good or service to the market, the firm gains a
competitive advantage which can lead to higher economic rents from their innovative activity
(Organization for Economic Co-Operation and Development, 2003). As can be seen in Table 18,
Missouri historically has been below the U.S. national average in every year for which data are
available. Moreover, Missouri has consistently ranked in the bottom third of all states for hightechnology establishments. The attraction of this type of businesses is paramount as they
represent a key potential employer of engineering graduates.
Table 18: High-Technology Establishments as a Percentage of All Business Establishments,
2003 – 200823
United States
Missouri
23
2005 data not available
2003
8.17
6.39
2004
8.19
6.35
2006
8.35
6.57
2007
8.46
6.64
2008
8.52
6.69
35
39
36
37
37
Rank Among States
Source: National Science Foundation Science and Engineering Indicators, 2012
One obstacle faced by Missouri has been a dearth of federal Small Business Innovation
Research (SBIR) funding over the past two decades. As indicated in Table 19, Missouri has
been in the bottom quartile of all states in regards to average annual federal SBIR funding per $1
million of GDP. Over the period 1988 to 2010, Missouri has, in fact, received anywhere from
approximately 16 percent to 30 percent of the national average for SBIR funding per $1 million
of GDP. It is important that Missouri’s policymakers and business leaders work together to
increase this SBIR fundingperformance to help stimulate business formation in key industries.
Table 19: Average Annual Federal Small Business Innovation Research Funding per $1
million of GDP, 1988-90 – 2008-10.
United States Missouri
State Rank
76
16
40
1988-90
91
15
38
1992-94
125
23
38
1996-98
121
27
47
2000-02
152
46
43
2004-06
88
24
42
2008-10
Source: National Science Foundation Science and Engineering Indicators, 2012
Missouri’s business formation has also been hindered by the slowdown of venture capital
funding following the dotcom bust of 2001. Missouri captures venture capital investments
ranging from a high of approximately one-third of the national average in 2001 to only 6 percent
of the national average in 2009 (see Table 20).
Table 20: Venture Capital per $1,000 GDP, 2001 – 2010
Year
2001
2002
United States
4.04
2.12
Missouri
1.36
0.4
State Rank
22
29
1.82
0.4
28
2003
1.78
0.3
30
2004
1.84
0.26
31
2005
1.96
0.28
26
2006
2.21
0.39
26
2007
1.98
0.36
31
2008
1.3
0.08
37
2009
1.5
0.25
32
2010
Source: National Science Foundation Science and Engineering Indicators, 2012
VII.
Benchmarking Missouri’s Engineering Labor Force and Education
Given the benefits of engineers to a state’s economy and labor force, it seems natural to
question how one’s state is performing relative to other states. To that end, data were gathered
from three other Midwestern states: Illinois, Michigan, and Ohio. For purposes of
benchmarking, these states were chosen for their geographic proximity, because they have major
urban centers, have major research-one universities, and because their performance in terms of
graduating and retaining engineers exceeds that of Missouri. Together these characteristics mean
that the performance of these states offer feasible goals for Missouri. Table 21, below, compares
these states and Missouri in terms of both engineers per 1,000 jobs and engineers per 1,000
residents as well as how these states rank among U.S. states. As can be seen, Michigan leads the
group in both engineers per 1,000 jobs and engineers per 1,000 residents followed by Ohio and
Illinois, respectively, in both categories.
Table 21: Engineers per 1,000 jobs and 1,000 residents, 2012
State
Illinois
Michigan
Missouri
Ohio
Rank
21
5
26
19
Engineers per
1,000 Jobs
20.45
32.18
18.91
21.36
Rank
21
6
25
16
Engineers per
1,000 Residents
8.96
12.76
8.19
9.35
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Bureau of Economic Analysis
The next metric under examination is the number of engineering graduates produced
annually per 1 million residents24 (Table 22). Michigan, again, outperforms its cohorts in the
production of bachelor’s, master’s, and all graduates, but is outperformed by Illinois in the
production of doctoral graduates. Missouri outperforms Illinois in the production of bachelor’s
degree graduates, but lags behind both Michigan and Ohio. Missouri ranks third in the
production of master’s degree graduatesoutperforming only Ohio. However, Missouri ranks last
among the cohort in doctoral degree graduates awarded, producing only two-thirds of as many as
Ohio and nearly half of that produced by Illinois and Michigan.
Table 22: Engineering Graduates per 1 million residents, 2010 – 2011
State
Bachelor's Master's Doctoral
All Degrees
233.97
164.27
38.93
437.17
Illinois
393.07
199.87
38.38
631.32
Michigan
272.02
157.22
22.63
451.86
Missouri
283.41
140.58
30.92
454.92
Ohio
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges, Bureau of Economic Analysis, and Truman (2013)
A major determinant of how many engineering graduates can be produced in a given state
is the number of faculty available to educate and train would-be graduates25. Table 24 below
shows the number of undergraduates students enrolled (both full- and part-time), full-time and
full-time equivalent faculty members (both teaching and faculty) and the ratio of enrolled
students to faculty members for the 2010 – 2011 school year. As can be seen in Table 23,
24
One million residents is used here instead of one thousand residents for purposes of scale. The relative
performance of each state is not affected by this scaling.
25
Of course, many other factors such as the quality of K-12 education in a given state impact the production of
engineers, but such discussion is beyond the scope of this paper.
Missouri has the smallest number of engineering students enrolled. While some of this is owing
to differences in state population, part of it is also attributable to Missouri’s ranking in the ratio
of students to faculty members, a category in which Missouri ranked last.
Table 23: Undergraduate Education, 2010 – 2011
Illinois
14,769
518
15,287
1,042.8
Michigan
18,876
1,485
20,361
1,306.4
Missouri
8,636
585
9,221
491.9
Ohio
20,923
1,472
22,395
1,248.6
Full-Time Students
Part-Time Students
Total Enrolled
Full-Time and FTE Teaching Faculty
Members
253.3
225.7
92.1
213.5
Full-Time and FTE Research Faculty
Members
1,296.1
1,532.1
584.0
1,462.1
Total Full-Time and FTE Faculty
Members
14.66
15.59
18.75
17.94
Total Enrolled per Full-Time Teaching
Faculty Member
11.79
13.29
15.79
15.32
Total Enrolled per Total Full-Time
Faculty Member
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Truman (2013)
Tables 24 and 25, below contain the same information as Table 23, but for Master’s and
Doctoral students, respectively. For master’s students, Illinois has the highest student-to-faculty
member ratio. For doctoral students, Missouri actually ranks first, but this is because their
doctoral enrollment is only one-third of the other states. The relatively low number of students
enrolled at the graduate level is likely a result of the low number of students enrolled at the
undergraduate level, which in many cases, feeds into graduate programs. Missouri’s low number
of enrolled students at the graduate level will hinder their production of master’s and doctoral
graduates which will, in turn, reduce the number of said graduates available in their labor force.
As such, it is imperative that efforts be made to increase the number of enrolled students as well
as the number of faculty available to train and educate these students.
Table 24: Master’s Education, 2010 - 2011
Illinois
2,901
1,162
4,063
1,042.8
Michigan
2,841
1,770
4,611
1,306.4
Missouri
997
712
1,709
491.9
Ohio
3,000
1,083
4,083
1,248.6
Full-Time Students
Part-Time Students
Total Enrolled
Full-Time and FTE Teaching Faculty
Members
253.3
225.7
92.1
213.5
Full-Time and FTE Research Faculty
Members
1,296.1
1,532.1
584.0
1,462.1
Total Full-Time and FTE Faculty
Members
3.90
3.53
3.47
3.27
Total Enrolled per Full-Time Teaching
Faculty Member
3.13
3.01
2.93
2.79
Total Enrolled per Total Full-Time
Faculty Member
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Truman (2013)
Table 25: Doctoral Education, 2010 - 2011
Illinois
3,118
169
3,287
1,042.8
Michigan
2,676
278
2,954
1,306.4
Missouri
885
122
1,007
491.9
Ohio
2,350
245
2,595
1,248.6
Full-Time Students
Part-Time Students
Total Enrolled
Full-Time and FTE Teaching Faculty
Members
253.3
225.7
92.1
213.5
Full-Time and FTE Research Faculty
Members
1,296.1
1,532.1
584.0
1,462.1
Total Full-Time and FTE Faculty
Members
3.15
2.26
2.05
2.08
Total Enrolled per Full-Time Teaching
Faculty Member
2.54
1.93
1.72
1.77
Total Enrolled per Total Full-Time
Faculty Member
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Truman (2013)
VIII. Conclusions
Despite the numerous economic and societal benefits that accrue from innovation and
technological advancement and the dire warnings issued in 2005’s seminal A Gathering Storm,
the outlook for the nation has actually diminished. Following the recession which startedin late
2007, funding for research has fallen in many areas, test scores in science and mathematics have
not increased, and many of our competitors have continued to catch up (Members of the 2005
“Rising Above the Gathering Storm” Committee, 2010).
In order to maintain or enhance its position in the US economy, and to contribute to the
restoration of US competitiveness in the global economy, it is imperative that Missouri takes
actions to increase the engineers employed in the state. One very direct way of encouraging this
is to increase the supply of engineering graduates. As has been shown in this report, engineering
occupations include well-paying jobs in high demand. Moreover, significant growth in these
occupations is projected in the next decade. In addition to the benefits that accrue to the
engineering graduate, Missouri benefits in terms of higher state GDP and higher personal
incomes for all its residents, and a stronger tax base.
A number of complementary strategies will be necessary to increase the number of
engineers in the state. First, the capacity of state engineering schools must be enhanced. Missouri
lags behind the nation and its peer states in a number of dimensions including faculty and
facilities. Next, increased numbers of high quality students from Missouri, other states and from
abroad must be recruited to Missouri’s schools of engineering. Improved facilities and larger
faculties will help with recruiting but other strategies such as funding for scholarships,
fellowships and work study will be necessary. Next, policies and strategies must be found to
retain Missouri graduates. This will involve vigorous placement programs, strong partnerships
with in-state employers, job-fairs, internships programs, and other innovative programs. Finally,
and possibly most importantly, the state must have a broad array of effective policies and
programs to attract, retain and grow firms that will employ engineers. Only a balanced and
comprehensive array of programs can raise Missouri’s performance to equal and exceed that of
its peer states.
The challenge is described very well by the Committee on Prospering in the Global
Economy in the 21st Century, who argued,
Without a renewed effort to bolster the foundations of our competitiveness, it is possible
that we could lose our privileged position over the coming decades. For the first time in
generations, our children could face poorer prospects for jobs, healthcare, security, and
overall standard of living than have their parents and grandparents(p. 223).
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Appendix
Table A1: Engineering Occupations
Standard Occupational
Classification Code
11-9041
13-1051
15-1132
15-1133
17-1011
17-1022
17-2011
17-2021
17-2031
17-2041
17-2051
17-2061
17-2071
17-2072
17-2081
17-2111
17-2112
17-2121
17-2131
17-2141
17-2151
17-2161
17-2171
17-2199
19-2032
25-1031
25-1032
Occupation Title
Architectural and Engineering Managers
Cost Estimators
Software Developers, Applications
Software Developers, Systems Software
Architects, Except Landscape and Naval
Surveyors
Aerospace Engineers
Agricultural Engineers
Biomedical Engineers
Chemical Engineers
Civil Engineers
Computer Hardware Engineers
Electrical Engineers
Electronics Engineers, Except Computer
Environmental Engineers
Health and Safety Engineers, Except Mining Safety Engineers
and Inspectors
Industrial Engineers
Marine Engineers and Naval Architects
Materials Engineers
Mechanical Engineers
Mining and Geological Engineers, Including Mining Safety
Engineers
Nuclear Engineers
Petroleum Engineers
Engineers, All Other
Materials Scientists
Architecture Teachers, Postsecondary
Engineering Teachers, Postsecondary
Table A2: Engineering Graduates 2010 – 2011 and Change in Engineering Jobs 2011 –
2012
Model
Graduates
OLS
0.8985**
(0.0847)
Intercept
-126.265
(243.370)
F-Test
112.55
2
R
0.7710
N
48
Source: American Society for Engineering Education, Profiles of Engineering & Engineering
Technology Colleges and Bureau of Labor Statistics, Occupational Employment
Statistics
Standard errors in parentheses; Statistical significance: * < 0.05, ** < 0.01
Table A3: Engineering Employment and Real GDP, 1999 – 2012
Model
Engineers
Fixed-Effects
3.019**
(0.3360)
Intercept
128636.3**
(14342.56)
F-Test
80.73
2
R
0.5492
0.9306
N
672
Source: Bureau of Economic Analysis, U.S. Economic Accounts and Bureau of Labor Statistics,
Occupational Employment Statistics
Robust standard errors in parentheses; Statistical significance: * < 0.05, ** < 0.01
Table A4: Engineering Employment per 1000 Jobs and Real GDP per capita, 1999 – 2012
Model
Engineers/1000 jobs
Random-Effects
219.4828**
(45.6734)
Intercept
36688.87**
(991.764)
Wald
114.45
2
R
0.1168
6525.8076
2028.2984
N
672
Source: Bureau of Economic Analysis, U.S. Economic Accounts and Bureau of Labor Statistics,
Occupational Employment Statistics
Standard errors in parentheses; Statistical significance: * < 0.05, ** < 0.01
Table A5: Engineering Employment per 1000 Jobs and Real Personal Income per capita,
1999 – 2012
Model
Engineers/1000 jobs
Fixed-Effects
171.1743**
(35.6495)
Intercept
31628.07**
(517.198)
F-Test
23.06
2
R
0.1457
0.2086
N
672
Source: Bureau of Economic Analysis, U.S. Economic Accounts and Bureau of Labor Statistics,
Occupational Employment Statistics
Robust standard errors in parentheses; Statistical significance: * < 0.05, ** < 0.01
Table A6: Engineering Employment and Utility Patent Filings, 1999 – 2012
Model
Patents
Fixed-Effects
0.0350**
(0.0109)
Intercept
371.3398
(464.602)
F-Test
10.35
2
R
0.5860
0.8865
N
672
Source: U.S. Patent and Trademark Office and Bureau of Labor Statistics, Occupational
Employment Statistics
Robust standard errors in parentheses; Statistical significance: * < 0.05, ** < 0.01