Manufacturing Skills and Skill Gaps
following Volatility and High Unemployment
Andrew Weaver
Massachusetts Institute of Technology
IST/Lisbon
June 25, 2014
(joint with Paul Osterman)
What are the Issues?
 Background
 High and persistent unemployment
 Firms complain they can’t find skilled workers
 Questions
 Does mismatch/gap exist between employer demands and the
supply of skills in the marketplace?
 If so, is it a simple/mechanical result of inadequate worker
skills, or are other more complex factors to blame (cyclical
demand, corporate strategy, communication among economic
actors, etc.)?
2
Relation to Uncertainty and
Industrialization Patterns
 Loss of domestic mfg. raises questions about trajectory of
industrial growth, economic development, job quality
 Policymakers need to understand this issue in order to foster
economic growth and improve economic outcomes for workers
 Common skill-biased technical change (SBTC) narrative leads to
focus on supply-side labor market frictions
 If problem is just structural/skills gap: long-term ed. attainment and worker
behavior
 If other factors matter, SBTC narrative may be misleading and other
interventions may be necessary
 Exhortations to increase STEM education may not solve the problem
 Institutional approaches may be required: making connections with local
labor market intermediaries, solving coordination/communication failures,
etc.
3
Presentation Goals
 Set boundaries on incidence of skill gaps
 Demonstrate simple skill mismatch story is inadequate
 Point to importance of intermediaries and institutions in
addressing challenges in skill supplies
4
Shortcomings of Existing Research
 Takes place at very abstract level without direct measurement
 Unemployment-vacancy indices (Sahin et al. 2012; Canon, Chen
and Marifian 2013)




Are sensitive to changes in firm strategy (recruitment, wages)
Are sensitive to cyclicality
Vague measure: hides mechanism (geography? skills?)
Only measure inter-industry mismatch (Modestino 2010; Lazear and
Spletzer 2012)
 Supply-Demand indices (Estevau and Tsounta 2011; Rothwell
2012)
 Use education as proxy
 Distorts demand measurement: college-educated barista
 Ignores within-education variation in skills
 Proxy on both sides: any regional or intra-industry variation generates
mismatch
5
Manufacturing Puzzle
 For manufacturing, important facts are inconsistent with skill
gap claims
 Deloitte and the National Association of Manufacturers
(2011) report survey results:
 600,000 unfilled jobs due to lack of qualified workers
 74% of manufacturers report lack of skilled production workers
had significant negative impact
 If demand exceeds supply for high-skilled manufacturing
workers, we would expect wages to increase
6
Manufacturing Wage Trends
Community College Wage Premium by Industry Sector
1.35
Ratio of AA to HS Wages
1.30
1.25
1.20
Mfg. Premium
Non-Mfg. Premium
1.15
1.10
1.05
2000
2001
2002
2003
2004
2005 2006
Year
2007
Source: CPS MORG (NBER) data.
7
2008
2009
2010
2011
Approach
 To answer questions about skill and mismatch, it’s necessary
to gather direct evidence on skill demands:
 What skills do employers demand?
 Which establishments demand high levels of skill?
 Do establishments, particularly those with high skill demands,
have trouble finding workers with these skills?
 To really narrow in on skills, important to focus on
industry/industry sector
 Paul Osterman and I designed and administered a nationally
representative survey of manufacturing plants to answer
these questions
 We conducted extensive fieldwork to identify critical factors
relating to institutions, regional eco-system
8
Our Survey
 Administered in late 2012, early 2013
 Random sample—Dun & Bradstreet database
 n=903
 36% response rate
 Focus on “core” production workers (Ben-Ner and Urtasun
2013, Osterman 1995)—62% of estab. employment
 Concrete skill questions: does this job require reading
complex technical manuals? algebra? geometry? etc.
 Defined skill gaps as prolonged core worker vacancies (> 3 mos.)
9
Basic Skill Demands
Basic Skill Demands for Core Production Jobs
All
Establishments
Basic reading (ability to read basic instruction manuals)
75.6%
Basic writing (ability to write short notes, memos, reports
less than one page long)
60.5%
Basic math (ability to perform all of math categories below)
74.0%
Addition and subtraction
Multiplication and division
Fractions, decimals, or percentages
10
Require basic reading, writing, and math
42.4%
Require use of computers several times per week or more
frequently
62.3%
Ability to use word processing software or ability to search
Internet for information
41.7%
Interpersonal/Problem-Solving/Soft
Skill Demands
Percent of Establishments Citing Interpersonal, Problem-Solving,
and Other Soft Skills as Very or Moderately Important for Core Jobs
11
Very
Important
Very or
Moderately
Important
Cooperation with other employees
Ability to evaluate quality of output
81.2%
71.0%
99.3%
95.8%
Ability to take appropriate action if quality is not
acceptable
76.3%
97.7%
Ability to work in teams
Ability to learn new skills
64.2%
50.1%
91.1%
89.3%
Ability to independently organize time or prioritize
tasks
45.6%
84.4%
Ability to solve unfamiliar problems
38.8%
83.0%
Ability to critically evaluate different options
35.7%
74.1%
Ability to initiate new tasks without guidance from
management
35.2%
80.9%
Extended Skill Demands
Extended Skill Demands for Core Production Jobs
All
Establishments
Extended reading (docs > 5pg.; trade jrn.; tech. docs)
52.6%
Extended writing (>1pg.)
22.1%
Extended math (ability to perform any of three math
38.0%
categories below)
Algebra, geometry, or trigonometry
31.5%
Probability or statistics
13.6%
Calculus or other advanced mathematics
7.4%
Extended computer
41.9%
Use CAD/CAM
28.4%
Use other engineering or manufacturing software
29.2%
Ability to write computer programs (such as
program a CNC machine for a new piece, etc.)
18.6%
Unique skill
12
25.9%
Skill Gap Evidence
Vacancies
90.0%
Percent of Establishments
80.0%
70.0%
76.3%
64.9%
60.0%
50.0%
40.0%
30.0%
17.4%
20.0%
10.2%
10.0%
7.6%
7.4% 5.6%
10.6%
0.0%
No vacancies
More than zero, less More than 5%, less than
More than 10%
than or equal to 5%
or equal to 10%
Vacancy Measure as a Percent of an Establishment's Core Employees
13
Any Vacancies
Long-Term Vacancies
What Skill Demands are Associated
with Hiring Difficulties?
 Demands for higher level reading, math, and unique skills are
significant predictors of long-term vacancies
 Computer and soft skills/problem-solving/initiative skills
are not
 So is this relationship between skill demands and hiring
problems an automatic/mechanical one?
 Examine high skill-demanding establishments
14
Which Establishments Demand High
Skills?
 Establishments that demand extended skills are characterized
by:
 high-tech
 cluster membership
 high-performance work organization (TQM/self-managed
team)
 frequent process (not product) innovation
 more foreign competition
 If the simple skill mismatch story is accurate, these
establishments should have significantly higher levels of hiring
difficulties
15
Long-Term Vacancies: Estab. Characteristics Models
High-tech
Above-avg. tech.
TQM pct.
Self team pct.
Product innovation
Process innovation
Industry cluster
Part of larger firm
More foreign comp.
16
Pct. LT vac.-- Pct. LT vac.-- LTV--Logit-- LTV--Logit-RF
RF+wage
RF
RF+wage
Pct. LT vac.
LTV--Logit
-0.01
(0.007)
-0.001
(0.006)
0.000
(0.000)
0.000
(0.000)
0.002
(0.007)
0
(0.007)
-0.052
(0.038)
-0.019
(0.033)
0.001
0.000
0.001
(0.001)
0.019
(0.038)
0.005
(0.038)
-0.014**
(0.007)
-0.001
(0.006)
0.002
0.000
0.002
(0.000)
0.001
(0.007)
0.002
(0.007)
-0.017**
(0.007)
-0.001
(0.006)
0.003
0.000
0.003
(0.000)
0.003
(0.007)
0.003
(0.007)
-0.068*
(0.037)
-0.024
(0.033)
0.004
0.000
0.004
(0.001)
0.018
(0.039)
0.013
(0.038)
-0.072*
(0.039)
-0.026
(0.034)
0.005
0.000
0.005
(0.001)
0.022
(0.040)
0.021
(0.039)
0.017***
(0.006)
0.003
(0.007)
0.002
(0.007)
0.119***
(0.032)
0.024
(0.037)
0.019
(0.038)
0.014**
(0.006)
0.003
(0.006)
0.001
(0.007)
0.013**
(0.006)
0.001
(0.007)
0.001
(0.007)
0.117***
(0.032)
0.032
(0.037)
0.027
(0.039)
0.117***
(0.033)
0.031
(0.038)
0.025
(0.039)
Long-Term Vacancies: Red. Form Cont’d
County pop. density
County unemp. rate (2011)
Pct. change in core emp. last 2 yrs.
0.000
0.000
0.000
0.000
(0.000)
(0.000)
(0.000)
(0.000)
-0.148
-0.129
-0.795
-0.695
(0.122)
(0.124)
(0.711)
(0.721)
0.016
0.016
(0.024)
(0.025)
-0.011*** -0.012***
(0.004)
Standardized division wage
Low wage
R-Squared
N
0.003
0.005
(0.003)
(0.017)
0.121***
0.18
(0.032)
(0.160)
0.036
0.034
0.050
0.073
0.040
0.038
783
784
766
738
766
738
Source: PIE Manufacturing Survey. * p<0.10, ** p<0.05, *** p<0.01
17
(0.004)
Summary of Results
 No widespread problem with skill gaps
 It is worth paying attention to the minority of establishments
reporting difficulties
 Skills are important
 Extended math is important
 Extended reading is surprisingly prominent
 Unique skills: may reflect internal training decline
 However, many establishment characteristics associated with
higher skill demands (high-tech, HPWS, process innovation)
are not associated with hiring difficulties
 This implies no simple/mechanical relationship between
higher skill demands and hiring problems: other factors
mediate relationship
18
What’s Going On?
 Skills are critical, but skill gap formulation is not necessarily the





best way to frame the issue
American skill production system has been changing
Decline in mfg. establishment size (Holmes 2011; Henly and
Sanchez 2009)
Small firms provide less internal training (Lynch and Black 1998)
External training actors like community colleges are more
important than they once were
But system is disaggregated
 More potential for coordination failures and underinvestment in
public goods
19
Intermediaries/Institutions are
Important
 Rochester story




Kodak
Monroe Community College
Rochester Regional Photonics Cluster (RRPC)
Addressed coordination failure
 Intermediaries and institutions are critical for matching supply and
demand, as well as coordinating increases in skill demands and
supplies
 Challenge coming from volatility/uncertainty:
 Simple SBTC story says high returns to education/skills will provide
should provide incentive for supply side of labor mkt.
 However, volatilty may destroy the very institutions and
intermediaries necessary to raise skill levels on both supply and
demand side
20
Thank You
Andrew Weaver
weaver55@mit.edu
21
Our Survey










22
Production in the Innovation Economy (PIE) project
Administered in late 2012, early 2013
Dun & Bradstreet database
Establishment approach: Bloom and Van Reenen 2007, Lynch and
Black 1998
Manufacturing establishments, excluding baking, printing, and
publishing
Random sample, stratified by estab. size (>10 emp.)
Targeted plant managers (identified appropriate person)
$10 incentive
n=903
36% response rate
Survey Design
 Focus on “core” production workers (Ben-Ner and Urtasun
2013, Osterman 1995)—62% of estab. employment
 Battery of concrete skill questions (>30)
 Examples
 Reading
 Basic: Does this job require reading basic instruction manuals?
 Extended: Does this job require reading complex technical documents
or manuals? Any document that is longer than five pages? etc.
 Math
 Basic: Does this job require mathematical operations involving
multiplication and division?
 Extended: Does this job require mathematical operations involving
probability and statistics? Algebra, geometry, or trigonometry? etc.
23
Survey Design (2)
 Concrete questions re skill gaps
 Defined skill gaps as prolonged core worker vacancies (> 3
mos.)
 Background data on establishment and workforce







24
Industry
Employment/financial trends
Innovation
Training
Age structure
Sex composition
etc.
Hypotheses
 H1: If skill gaps are a widespread problem in manufacturing,
then long-term vacancies will be a widespread problem
 Benchmark from Deloitte survey:
 74% of mfg. firms suffered from lack of skilled production workers
 H2: If demand for higher skills mechanically leads to hiring
problems, the establishments characterized by the highest
skill demands should experience greater problems
 Higher level skill demands (math, reading, etc.) should be
associated with hiring problems
 If high-tech or other types of establishments have higher skill
demands, they should have more severe hiring problems
25
Analysis of Establishments
with Hiring Difficulties
 Two dependent variables:
 Long-term vacancies as a percentage of total core workers (OLS)
 Indicator for long-term vacancies (Logit)
 First estimate models with skill variables as regressors, then with
high-skill establishment characteristics as regressors
 Reduced form controls
 Supply: county unemployment rate (2011), county population
density
 Demand: change in core workers over past two years
 Wage measures (mgmt. strategy): standardized by Census geographic
division (2011 to avoid simultaneity)
 All models control for establishment size
26
Long-Term Vacancies: Skill Models
Any extended skill
Pct. LT vac.
LTV
0.016***
(0.006)
0.073**
(0.035)
Extended reading
Extended writing
Extended math
Extended computer
Unique skill
New skills
Evaluate quality
R-Squared/Pseudo
R2
0.025
N
869
* p<0.10, ** p<0.05, *** p<0.01
27
0.023
870
Pct. LT vac.-detailed
skills
LTV-detailed
Pct. LT vac.-detailed,
red. form
LTV-detailed,
red. form
0.012**
(0.006)
-0.002
(0.007)
0.017***
-0.006
0.007
(0.006)
0.013**
(0.006)
-0.002
(0.006)
0.001
(0.006)
0.465***
(0.178)
-0.12
(0.205)
0.531***
-0.187
-0.11
(0.179)
0.442**
(0.177)
0.263
(0.172)
-0.252
(0.187)
0.011*
(0.006)
-0.003
(0.007)
0.019***
-0.006
0.007
(0.006)
0.015**
(0.006)
-0.003
(0.006)
0.002
(0.006)
0.513***
(0.189)
-0.143
(0.215)
0.608***
-0.197
-0.062
(0.185)
0.553***
(0.185)
0.224
(0.180)
-0.282
(0.192)
0.052
831
0.053
832
0.082
778
0.060
778
Implications
 Demanding high skill levels is not necessarily a ticket to
trouble
 A wider range of institutional policies responses may be
relevant
 Targeted policies may have the potential to affect hiring
outcomes even holding current worker skill levels constant
 Institutional relationships (e.g., between firms and community
colleges or labor market intermediaries)
 Incentives for firm-level human resource/training policy
 Policies that reduce risk of mfg. career for job applicants
28
Further Research Agenda
 PIE Survey
 Institutional and other factors that mediate skill and hiring
problems
 Community college density: determinants and implications
for economic growth
 LPNs and job ladders
 Social entrepreneurship and philanthropic capital markets
29
Extended Skill Demands: Logit Analysis
High-tech industry
Above-average tech.
TQM pct.
Self team pct.
Frequent product innovation
Frequent process innovation
Industry cluster
Part of larger firm
More foreign competition
Pseudo R-Squared
N
30
* p<0.10, ** p<0.05, ***p<0.01
Any
Extended
Skill
Extended
Reading
Extended
Math
Extended
Computer
Unique Skill
Extended
Writing
0.172***
(0.032)
0.019
(0.032)
0.001***
0.000
0.001
(0.001)
0.288***
(0.038)
0.039
(0.035)
0.001
0.000
0.002***
(0.001)
0.026
(0.039)
0.001
(0.033)
0.0003
0.001
0.001**
(0.001)
0.143***
(0.043)
0.059*
(0.036)
0.001***
0.000
0.0005
(0.001)
0.006
(0.037)
0.087***
(0.032)
0.001*
0.000
0.001**
0.000
0.025
(0.036)
-0.018
(0.030)
-0.0001
0.000
0.001
0.000
0.032
0.006
-0.06
-0.025
-0.014
0.038
(0.037)
(0.041)
(0.040)
(0.041)
(0.038)
(0.034)
0.078**
0.081**
0.076**
0.125***
0.036
0.02
(0.037)
0.073**
(0.030)
-0.025
(0.035)
0.059*
(0.035)
0.066
804
(0.040)
0.062*
(0.034)
0.01
(0.039)
0.062
(0.040)
0.082
797
(0.037)
0.066**
(0.032)
-0.089**
(0.038)
0.112***
(0.040)
0.043
796
(0.040)
0.093***
(0.034)
-0.088**
(0.039)
0.119***
(0.041)
0.061
795
(0.036)
0.095***
(0.031)
-0.039
(0.036)
0.027
(0.037)
0.038
800
(0.034)
-0.023
(0.029)
0.029
(0.033)
-0.019
(0.033)
0.013
792
Size Distribution
40.0%
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
<20
20-99
PIE
31
100-249
250-499
County Business Patterns 2010
500+
Weighting and Validation
 Small establishments somewhat more likely to respond than
large estab.
 For all descriptive statistics we use size weights based on the
employment-weighted proportion of establishments of
various size classes in the Census Bureau’s County Business
Patterns (CBP) data
 Validate aggregate workforce data with CPS: close match
32
Validation with CPS
33
PIE
CPS (2012)
Hourly wage
16.95
16.49*
Union
18.1%
13.7%*
Female
26.7%
26.6%
Age 30 or less
20.6%
21.3%
Age 31-40
27.5%
22%*
Age 41-55
35.8%
38.8%*
Age 56 plus
16.1%
17.9%*
*=significant differences at 95 percent level or higher.
Geographic Distribution
PIE Survey
West
18%
South
26%
34
Northeast
21%
Midwest
35%
Geographic Comparison
40.0%
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Northeast
PIE survey
35
Midwest
South
County Business Patterns 2011
West
Industry Distribution
NAICS
36
311
312
313
314
315
316
321
322
323
324
325
326
327
331
332
333
334
335
336
337
339
NAICS 3-Digit Industry
Food mfg.
Beverage and tobacco product mfg.
Textile mills
Textile product mills
Apparel mfg.
Leather and allied product mfg.
Wood product mfg.
Paper mfg.
Printing and related support activities
Petroleum and coal products mfg.
Chemical mfg.
Plastics and rubber products mfg.
Nonmetallic mineral product mfg.
Primary metal mfg.
Fabricated metal product mfg.
Machinery mfg.
Computer and electronic product mfg.
Electrical equip, appliance, and comp. mfg.
Transportation equipment mfg.
Furniture and related product mfg.
Miscellaneous mfg. + other
PIE Survey Pct.
of Estab.
4.5%
1.2%
0.6%
2.4%
1.3%
0.1%
3.4%
1.4%
3.6%
0.8%
6.4%
6.0%
3.4%
3.4%
22.2%
12.0%
7.7%
3.1%
5.4%
3.0%
8.4%
Industry Comparison
NAICS
PIE Survey CBP Pct. of
Pct. of Estab. Estab. 2011
PIE-CBP
311
312
313
314
315
316
321
322
Food mfg.
Beverage and tobacco product mfg.
Textile mills
Textile product mills
Apparel mfg.
Leather and allied product mfg.
Wood product mfg.
Paper mfg.
4.5%
1.2%
0.6%
2.4%
1.3%
0.1%
3.4%
1.4%
8.6%
1.7%
0.8%
2.1%
2.4%
0.4%
4.7%
1.5%
-4.1%
-0.5%
-0.2%
0.3%
-1.2%
-0.3%
-1.3%
-0.1%
323
324
325
326
327
331
332
333
Printing and related support activities
Petroleum and coal products mfg.
Chemical mfg.
Plastics and rubber products mfg.
Nonmetallic mineral product mfg.
Primary metal mfg.
Fabricated metal product mfg.
Machinery mfg.
Computer and electronic product
mfg.
Electrical equip, appliance, and comp.
mfg.
Transportation equipment mfg.
Furniture and related product mfg.
Miscellaneous mfg. + other
3.6%
0.8%
6.4%
6.0%
3.4%
3.4%
22.2%
12.0%
9.4%
0.8%
4.4%
4.3%
5.2%
1.6%
18.8%
8.1%
-5.8%
0.0%
2.0%
1.6%
-1.8%
1.8%
3.4%
3.9%
7.7%
4.4%
3.3%
3.1%
5.4%
3.0%
8.4%
2.0%
3.9%
5.6%
9.3%
1.1%
1.5%
-2.6%
-0.9%
334
37
NAICS 3-Digit Industry
335
336
337
339
Occupational Wage Comparison
Average Hourly Wages by Selected Manufacturing
Occupations
2008
2011
% change
Production occupations
15.87
16.74
5.5%
Machinists
18.17
19.51
7.4%
Industrial Engineering Technicians
22.89
24.42
6.7%
Mechanical Engineering Technicians
23.74
24.92
5.0%
Industrial Engineers
35.47
37.56
5.9%
Source: BLS Occupational Employment Statistics.
38
Extended Skill Demand Models (2)
High tech
Above-avg. tech
TQM pct.
Self team pct.
Frequent prod. innovation (g)
Frequent process innovation
Industry cluster
Part of larger firm (g)
More foreign comp.
Employment size FE (g-2nd)
R-Squared
N
LR test (Chi2) p-value--prop. odds
39
Brant test p-value
* p<0.10, ** p<0.05,
Extended Skill Index
Pr(index=3)
Extended Skill Index Pr(index=3)
Gen. Ord. Logit
0.095***
(0.021)
0.016
(0.016)
0.0004**
(0.0002)
0.001**
(0.0003)
-0.012
(0.019)
0.047***
(0.018)
0.034**
(0.015)
-0.025
(0.018)
0.048**
(0.020)
x
0.031
778
0.097***
(0.020)
0.0004
(0.015)
0.0004**
(0.0002)
0.001***
(0.0002)
-0.065***
(0.024)
0.051***
(0.018)
0.035**
(0.015)
-0.060***
(0.018)
0.049***
(0.018)
x
0.042
778
0.158
0.801
0.096
***p<0.01
Quantifying the Skill Gap
Core vacancies as pct. of total estab. emp.
Core long-term vacancies as pct. of total estab. emp.
Core long-term vac. as pct. of total vac.
Core workers as pct. of total estab. emp.
1.1%
0.5%
48.4%
62.0%
Est. total PIE vac. pct. if vac. are proportional
JOLTS vacancies as pct. of total CES mfg. emp. (Aug. 2011)
1.8%
2.0%
JOLTS vacancies as pct. of total CES mfg. emp. (4Q 2012)
2.0%
Deloitte implied vacancies as pct. of total CES mfg. emp. (Aug. '11)
5.1%
Implied long-term vac./emp. (based on long-term vac. pct. of total vac.)
PIE
0.9%
JOLTS (4Q 2012)
1.0%
Deloitte
2.4%
40
Implied total PIE mfg. vacancies
213,712
Implied PIE long-term mfg. vacancies
103,390
PIE long-term vacancies as pct. of mfg. unemployed (4Q 2012)
11.6%
Skill Gap Robustness (1)
 What if we miss skill gaps because we’re looking at a point in
time
 Hiring funnel (based on attempt to hire in last two years)
Hiring Funnel for Core Workers
41
Mean
Median
75th-weeks
25th-others
Weeks required to recruit and hire applicant
(start of process to extension of offer)
5.9
4.0
6.0
Typical number of applications received per open
core position
23.8
10.0
5.0
Typical number of interviews conducted per open
core position
5.9
5.0
3.0
85.4%
95.0%
80.0%
Acceptance rate by applicants who are extended
an offer
Source: PIE Manufacturing Survey.
Skill Gap Robustness (2)
Alternative Measures
42
Ever reduced production due to vacancies
17.7%
Have vacancy and ever reduced prod.
7.6%
Long hire times over past two yrs. (>=3 mos.)
10.9%
Long-term vac. OR vac. + reduced prod.
25.6%
Long-term vac. OR prior long hire times
34.1%
Why Manufacturing?
 Manufacturing is interesting test case for structural mismatch
 Arguments about mismatch/spiking skill demands are commonly
applied to manufacturing
 Deloitte and the National Association of Manufacturers (2011) report survey
results:
 600,000 unfilled jobs due to lack of qualified workers
 74% of manufacturers report lack of skilled production workers had significant
negative impact
 Capital intensive / sensitive to technology shocks
 Key theories: tech. shocks drive mismatch (Brynjolfsson and McAfee 2012,
Autor, Levy, and Murnane 2003)
 STEM skills are important
 Idea of vacancies in industry with millions of laid off workers implies
structural gap
 Broad sector with a lot of variation (high-tech/low-tech,
domestic/export, etc.)
 12% of GDP; 70% of industry R&D
43