south dakota competitiveness: state and cluster economic performance
DESCRIPTION
Harvard Business SchoolProfessor Michael E. PorterNational Governors Association Winter MeetingFebruary 26, 2011TRANSCRIPT
1 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
South Dakota Competitiveness:
State and Cluster Economic Performance
Prepared for Governor Dennis Daugaard
Professor Michael E. Porter National Governors Association Winter Meeting
February 26, 2011
2 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
South Dakota Performance Snapshot
• Processed Food
• Heavy Machinery
• Production Technology
Prosperity
Innovation
Productivity
Labor Mobilization
Cluster Strength
Leading Clusters
Position Trend
Top quintile
3rd quintile
4th quintile
2nd quintile
Lowest quintile
3 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
State Comparative Performance
4 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
South Dakota Competitiveness Overall Economic Performance Indicators
Note: Ranks are among the 50 US states plus the District of Columbia. Growth calculated as compound annual growth rate. *Real annual rate.
Prosperity
Cluster
Gross State Product per capita, 2009 Share of State Traded Employment in Strong Clusters, 2008
• In South Dakota: $47,156 Rank: 21 • In South Dakota: 20.9% Rank: 48
• In the US: $46,093 • In the US: 41.8%
• State difference to US: 2.3%
Change in Share of National Employment in Strong Clusters, 1998-2008
Growth in Gross State Product per capita, real annual rate, 1999-2009 • In South Dakota: 0.11% Rank: 20
• In South Dakota: 2.74% Rank: 3 • In the US: -0.06%
• In the US: 0.86%
Share of Employment in Traded Clusters, 1998-2008
• In South Dakota: 27.7% Rank: 30
Productivity • In the US: 27.4%
Gross State Product per labor force participant, 2009 Change in Share of Employment in Traded Clusters, 1998-2008
• In South Dakota: $86,045 Rank: 25 • In South Dakota: -1.3% Rank: 20
• In the US: $92,382 • In the US: -2.2%
• State difference to US: -6.9%
Labor Mobilization
Growth in Gross State Product per labor force participant*, 1999-2009
• In South Dakota: 2.73% Rank: 4 Population, 2009
• In the US: 1.09% • In South Dakota: 812,373 Rank: 46
• % of US: 0.26%
Average private wage, 2008
• In South Dakota: $31,402 Rank: 49 Population growth, annual rate, 1999-2009
• In the US: $42,435 • In South Dakota: 0.80% Rank: 24
• State difference to US: -26.0% • In the US: 0.96%
Private wage Growth, annual rate, 1998-2008 Labor Force Participation, 2009
• In South Dakota: 3.56% Rank: 16 • In South Dakota: 72.5 Rank: 1
• In the US: 3.32% • In the US: 65.4
Employment, 2010 (December)
Innovation Output • In South Dakota: 423,290 Rank: 46
• % of US: 0.30%
Patents Per 10,000 Employees, 2009
• In South Dakota: 1.36 Rank: 48 Employment growth, annual rate, 2000-2010 (December)
• In the US: 6.83 • In South Dakota: 0.58% Rank: 11
• In the US: 0.11%
Growth in total patents, annual rate, 1998-2009
• In South Dakota: -0.76% Rank: 24 Unemployment, 2010 (December)
• In the US: 0.23% • In South Dakota: 4.6% Rank: 3
• In the US: 9.4%
Traded establishment formation, annual growth rate, 1998-2008
• In South Dakota: 2.27% Rank: 15 Change in Unemployment, 2000-2010 (December)
• In the US: 1.79% • In South Dakota: 1.8% Rank: 3
• In the US: 5.5%
5 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
$30,000
$35,000
$40,000
$45,000
$50,000
$55,000
$60,000
$65,000
$70,000
-1.0% -0.5% 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5% 4.0%
U.S. GDP per
Capita: $46,093
High and rising
prosperity versus U.S.
Long Term State Prosperity Performance 1999 to 2009
Notes: Real GDP figures in 2005 chained US dollars from the Bureau of Economic Analysis. Growth rate is calculated as compound annual growth rate. D.C. excluded
U.S. GDP per Capita
Real Growth Rate: 0.86%
Gross Domestic Product per Capita Real Growth Rate, 1999 to 2009
Gro
ss
Do
mes
tic P
rod
uct
pe
r C
ap
ita,
20
09
High but declining
versus U.S.
Low and declining
versus U.S. Low but rising versus U.S.
Illinois
Wyoming
North Dakota
South Dakota
Delaware
Alaska Connecticut
Wisconsin
Nevada
Arizona
New York New Jersey Massachusetts
California
West Virginia
Mississippi
Vermont Oklahoma
Iowa Nebraska
North Carolina
Georgia Florida
Michigan
Idaho South Carolina
Texas
Oregon
Rhode Island Louisiana
Pennsylvania Kansas
New Hampshire
Arkansas
Maine
Colorado
Washington
Virginia
Minnesota
Hawaii Maryland
Alabama Montana Kentucky
New Mexico
Missouri Ohio
Indiana Utah
Tennessee
6 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
$30,000
$35,000
$40,000
$45,000
$50,000
$55,000
$60,000
$65,000
$70,000
-6.0% -4.0% -2.0% 0.0% 2.0% 4.0% 6.0%
Near Term State Prosperity Performance U.S. States, 2007 to 2009
Notes: Real GDP figures in 2005 chained US dollars from the Bureau of Economic Analysis. Growth rate is calculated as compound annual growth rate.
U.S. GDP per Capita
Real Growth Rate: -1.87%
U.S. GDP per
Capita: $46,093
Gross Domestic Product per Capita Real Growth Rate, 2007 to 2009
Gro
ss
Do
mes
tic P
rod
uct
pe
r C
ap
ita,
20
09
Illinois
Wyoming
North Dakota
South Dakota
Delaware
Alaska Connecticut
Wisconsin
Nevada
Arizona
New York New Jersey Massachusetts
California
West Virginia
Mississippi
Vermont Oklahoma
Iowa
Nebraska
North Carolina
Georgia Florida
Michigan
Idaho South Carolina
Texas
Oregon
Rhode Island
Louisiana
Pennsylvania Kansas
New Hampshire
Arkansas
Maine
Colorado
Washington Virginia
Minnesota
Hawaii Maryland
Alabama
Montana
Kentucky New Mexico
Missouri Ohio
Indiana Utah
Tennessee
High but declining versus U.S.
Low and declining versus U.S. Low but rising versus U.S.
High and rising
prosperity versus U.S.
7 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
State Private Sector Wage Performance 1998-2008
U.S. Average Wage
Growth: 3.32%
U.S. Average
Wage: $ 42,435
Wage Growth (CAGR), 1998-2008
Ave
rag
e W
ag
e,
20
08
High and rising wages
relative to U.S.
Source: Census CBP report; private, non-agricultural employment. Growth is calculated on nominal wage levels.
$30,000
$35,000
$40,000
$45,000
$50,000
$55,000
$60,000
2.0% 2.5% 3.0% 3.5% 4.0% 4.5% 5.0% 5.5%
Illinois
Wisconsin
Wyoming
New York
North Dakota
Michigan
Massachusetts Connecticut
New Jersey
Alaska
California
Washington
Delaware Maryland Minnesota
Colorado Delaware
Virginia
Indiana
Idaho South Carolina
West Virginia
Mississippi
Tennessee
Hawaii
Ohio
Georgia
New Hampshire
Rhode Island
Louisiana
Oklahoma
New Mexico
Arkansas
South Dakota Montana
Pennsylvania
Iowa
Maine Kentucky
Alabama
Nebraska Utah
North Carolina
Vermont
Arizona
Nevada Kansas Florida
Missouri
Oregon
High but declining versus U.S.
Low and declining versus U.S. Low but rising versus U.S.
8 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
$60,000
$70,000
$80,000
$90,000
$100,000
$110,000
$120,000
$130,000
$140,000
$150,000
-0.5% 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5%
Long Term State Labor Productivity Performance 1999-2009
Source: Bureau of Economic Analysis. Notes: Growth rate calculated as compound annual growth rate (CAGR).
Gross Domestic Product per Labor Force Participant Real Growth Rate, 1999-2009
Gro
ss
Do
mes
tic P
rod
uct
pe
r L
ab
or
Fo
rce
Pa
rtic
ipa
nt,
20
09
Highly productive and
productivity rising versus U.S.
High but declining versus U.S.
Low and declining versus U.S. Low but rising versus U.S.
U.S. GDP per Labor Force
Participant Real Growth: 1.09%
U.S. GDP per Labor Force
Participant: $92,382
Illinois
Wyoming
North
Dakota South
Dakota
Delaware
Alaska
Connecticut
Wisconsin
Nevada
Arizona
New York
New Jersey Massachusetts
California
West Virginia
Mississippi
Vermont
Oklahoma
Iowa
Nebraska North Carolina
Georgia
Florida Michigan
Idaho South Carolina
Texas
Oregon Rhode Island
Louisiana
Pennsylvania
Kansas
New Hampshire
Arkansas
Maine
Colorado Washington Virginia
Minnesota
Hawaii
Maryland
Alabama
Montana
Kentucky
New Mexico Missouri
Ohio
Indiana Utah
Tennessee
9 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
$60,000
$70,000
$80,000
$90,000
$100,000
$110,000
$120,000
$130,000
$140,000
$150,000
-8.0% -6.0% -4.0% -2.0% 0.0% 2.0% 4.0% 6.0% 8.0%
Near Term State Labor Productivity Performance 2007-2009
U.S. GDP per Labor Force
Participant Real Growth: -0.97%
U.S. GDP per Labor Force
Participant: $92,382
Gross State Product per Labor Force Participant Real Growth Rate, 2007-2009
Gro
ss
Sta
te P
rod
uct
pe
r L
ab
or
Fo
rce
Pa
rtic
ipa
nt,
20
09
Highly productive and
productivity rising versus U.S.
Source: Bureau of Economic Analysis. Notes: Growth rate calculated as compound annual growth rate (CAGR).
High but declining versus U.S.
Low and declining versus U.S. Low but rising versus U.S.
Illinois
Wyoming
North Dakota
South
Dakota
Delaware
Alaska
Connecticut
Wisconsin
Nevada
Arizona
New York
New Jersey Massachusetts
California
West Virginia
Mississippi
Vermont
Oklahoma
Iowa
Nebraska North Carolina
Georgia
Florida
Michigan
Idaho South Carolina
Texas
Oregon
Rhode Island
Louisiana
Pennsylvania
Kansas
New Hampshire
Arkansas
Maine
Colorado Washington
Virginia
Minnesota
Hawaii
Maryland
Alabama
Montana Kentucky
New Mexico Missouri Ohio
Indiana Utah
Tennessee
10 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Losing Jobs Gaining Jobs
Long Term State Job Growth 2000 to 2010
Source: Bureau of Labor Statistics
Nu
mb
er
of
Jo
bs 2
01
0
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
9,000,000
-2.0% -1.5% -1.0% -0.5% 0.0% 0.5% 1.0% 1.5% 2.0%
California (15,945,558) Texas (11,202,388)
U.S. Average Growth Rate: 0.11%
New York
Florida
Pennsylvania Illinois
Ohio
Michigan
Virginia
Washington
Arizona
Georgia North Carolina New Jersey
Massachusetts
Indiana
Missouri
Wisconsin
Tennessee Maryland Minnesota
Colorado
Alabama
Mississippi
West Virginia
Delaware Rhode Island Hawaii Maine
Nebraska
Montana Vermont Alaska
Utah Nevada
New Mexico Idaho
New Hampshire
Wyoming
South Dakota North
Dakota
Arkansas Kansas Iowa
Oregon Connecticut
Oklahoma
Kentucky Louisiana
South Carolina
Job Growth Rate (CAGR), 2000-2010
11 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Losing Jobs Gaining Jobs
Near Term State Job Growth 2007 to 2010
Source: Bureau of Labor Statistics
Job Growth Rate (CAGR), 2007-2010
Nu
mb
er
of
Jo
bs 2
01
0
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
9,000,000
-4.0% -3.5% -3.0% -2.5% -2.0% -1.5% -1.0% -0.5% 0.0% 0.5% 1.0%
California (15,945,558) Texas (11,202,388)
U.S. Average Growth Rate: -1.52%
New York
Florida
Pennsylvania
Illinois
Ohio
Michigan
Virginia
Washington
Arizona
Georgia North Carolina
New Jersey
Massachusetts
Indiana Missouri
Wisconsin Tennessee
Maryland
Minnesota
Colorado
Alabama
Mississippi West Virginia
Delaware Rhode Island
Hawaii Maine Nebraska
Montana Vermont Alaska
Utah Nevada
New Mexico Idaho New
Hampshire
South Dakota North Dakota
Arkansas Kansas
Iowa
Oregon Connecticut Oklahoma
Kentucky Louisiana South Carolina
Wyoming
12 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Long Term State Unemployment Rate 2000 to 2010
Change in Employment Rate, 2000 to 2010
Un
em
plo
ym
en
t R
ate
, 2
01
0
Source: Bureau of Labor Statistics
Unemployment rising
3.0
5.0
7.0
9.0
11.0
13.0
15.0
0.01.02.03.04.05.06.07.08.09.010.0
Nevada
North Dakota
South Dakota
Nebraska
New Hampshire
Vermont
Wyoming Hawaii
Iowa
Kansas
Montana
Alaska Louisiana
Virginia Oklahoma
Minnesota Maine Maryland
Utah Wisconsin
Arkansas New York Texas
Pennsylvania New Mexico
Delaware Massachusetts
Colorado Connecticut
Indiana
Georgia
South Carolina
Rhode Island
Michigan Florida
California
Kentucky Oregon
Mississippi
Washington
West Virginia Idaho
Illinois Alabama
New Jersey U.S. Average
Unemployment Rate: 9.4%
Change in US Average
Employment Rate: 5.5%
Ohio North Carolina
Missouri
Arizona
Tennessee
Below average
unemployment
Above average
unemployment
%
%
%
%
%
%
%
%
% % % % % % % % % %
13 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
3.0
5.0
7.0
9.0
11.0
13.0
15.0
0.01.02.03.04.05.06.07.08.09.010.0
Near Term State Unemployment Rate 2007 to 2010
Change in Employment Rate, 2007 to 2010
Un
em
plo
ym
en
t R
ate
, 2
01
0
Source: Bureau of Labor Statistics
Unemployment rising
U.S. Average
Unemployment Rate: 9.4%
Change in US Average
Employment Rate: 4.4%
Nevada
North
Dakota
South Dakota Nebraska
New Hampshire
Vermont
Wyoming Hawaii Iowa
Kansas
Montana
Alaska Louisiana
Virginia Oklahoma Minnesota
Maine Maryland
Utah Wisconsin
Arkansas New York Texas
Pennsylvania New Mexico
Delaware Massachusetts
Colorado Connecticut
Indiana
Georgia
South
Carolina Rhode Island
Michigan Florida
California
Kentucky Oregon Mississippi
Washington
West Virginia
Idaho Illinois Alabama
New Jersey
Ohio North Carolina
Missouri Arizona Tennessee
Below average
unemployment
Above average
unemployment
%
%
%
%
%
%
%
%
% % % % % % % % % %
14 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
0
2
4
6
8
10
12
14
-5% -4% -3% -2% -1% 0% 1% 2% 3%
Long Term State Patenting Performance U.S. States, 1999 to 2009
Growth Rate of Patenting, 1999 to 2009
Pa
ten
ts p
er
10
,00
0 E
mp
loye
es
, 2
00
9
Source: USPTO, Bureau of Labor Statistics. Note: Growth rate calculated as compound annual growth rate (CAGR). 3,000 patents issued in 2009 =
U.S. average Growth Rate
of Patenting: -0.30%
Arkansas (-6.9%, 0.76) Louisiana (-6.0%, 1.34)
Montana (-5.7%, 1.58)
South
Dakota
West Virginia
Alaska
Idaho
Pennsylvania
Mississippi
Washington (+8.0%, 13.53)
Oregon (+4.9%, 10.31)
New Jersey
Ohio
Delaware
Vermont
California
Massachusetts
North Carolina
North Dakota Wyoming
Georgia
Nebraska Maine
Utah
Michigan
Minnesota
Colorado
New Hampshire
Connecticut
Wisconsin
Rhode Island
Kansas
Nevada Virginia
Iowa
Texas Arizona
New York
Illinois
Maryland
Indiana
New Mexico
Florida
Tennessee
Missouri
South Carolina Kentucky
Alabama
Hawaii
Oklahoma
U.S. average Patents per
10,000 Employees: 5.96
High and improving
innovation rate versus U.S.
High and declining
innovation
Low and declining innovation Low and improving innovation
15 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
South Dakota Patents by Organization
Rank Organization Patents
2005-2009
Rank Organization
Patents 2005-2009
1 Gateway 2000, Inc. 52 24 Citibank N.A. 1
2 Freezing Machines, Inc. 11 24 Citicorp Credit Services, Inc. 1
3 Daktronics, Inc. 10 24 Hutchinson Technology Inc. 1
4 Westendorf Manufacturing Company, Inc. 7 24 Kirin Beer Kabushiki Kaisha 1
5 Amesbury Group Inc. 6 24 Lisle Corporation 1
6 South Dakota School Of Mines And Technology 5
24 Newell Operating Company 1
7 Tyco Electronics Corporation 4 24 Pioneer Hi-Bred International, Inc. 1
8 Vishay Dale Electronics, Inc. 3 24 Pulizzi Engineering, Inc. 1
8 Bright Planet Corporation 3 24 Stryker Corporation 1
8 Ramvac Dental Products, Inc. 3 24 Ashland Products, Inc. 1
8 Ridley Block Operations, Inc. 3 24 Lodgenet Entertainment Corporation 1
8 Control Systems Technologies, Llc 3 24 Halliburton Energy Services, Inc. 1
13 Ccl Label, Inc. 2 24 Lockheed Martin Corporation 1
13 Foto-Wear, Inc. 2 24 Penn State Research Foundation, Inc. 1
13 Illinois Tool Works Inc. 2 24 Amcol International Corporation 1
13 Sencore Incorporated 2 24 Novartis Ag (Formerly Sandoz Ltd.) 1
13 Dekalb Genetics Corporation 2 24 Sioux Steel Company, Inc. 1
13 Tyson Fresh Meats, Inc. 2 24 Alamo Group Inc. 1
13 Larson Manufacturing Company Of South Dakota, Inc. 2
24 South Dakota Soybean Processors 1
13 Sydell Incorporated 2
24 International Molded Packaging Corporation 1
13 Tower Stool, L.L.C. 2 24 Cnh America Llc 1
13 Slydog, Inc. 2 24 Prairie Ridge Partners 1
13 Kirin Holdings Kabushiki Kaisha 2 24 Hardware Specialties, Inc. 1
24 Alza Corporation 1 24 Depuy Mitek, Inc. 1
24 Astec Industries, Inc. 1 24 Six-O, Ltd. 1
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
Universities and Research Institutions
Government Organizations
16 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
The Impact of Cluster Mix and Cluster Strength on Wages U.S. States, 2008
State
State Traded Wage versus
National Average
Cluster Mix Effect
Relative Cluster
Wage Effect State
State Traded Wage versus
National Average
Cluster Mix Effect
Relative Cluster
Wage Effect
New York 34,578 5,188 29,390 North Carolina -10,673 -5,131 -5,543
Connecticut 20,008 6,898 13,109 Missouri -10,953 -1,634 -9,319
Massachusetts 17,308 5,191 12,117 Rhode Island -11,089 -1,370 -9,719
New Jersey 12,157 4,638 7,519 Florida -11,780 -1,473 -10,307
California 9,597 121 9,476 Oklahoma -12,225 1,533 -13,758
Maryland 6,435 2,778 3,657 Alabama -12,301 -4,713 -7,588
Washington 4,827 3,058 1,769 Tennessee -13,063 -3,987 -9,076
Virginia 2,550 945 1,605 Vermont -13,095 -2,936 -10,159
Illinois 2,501 -61 2,562 Indiana -13,309 -5,495 -7,814
Alaska 2,386 -3,044 5,431 Nebraska -14,659 41 -14,699
Texas 1,400 2,796 -1,396 Utah -14,947 327 -15,274
Colorado 753 2,292 -1,539 South Carolina -15,256 -5,694 -9,562
Delaware 612 13,346 -12,733 Nevada -15,429 -2,829 -12,600
Louisiana -4,172 573 -4,745 Maine -15,826 -726 -15,100
Minnesota -4,404 43 -4,448 North Dakota -16,437 2,940 -19,378
Wyoming -4,423 1,408 -5,831 Iowa -16,963 -2,602 -14,361
Michigan -4,981 -2,534 -2,447 New Mexico -16,991 -125 -16,866
Pennsylvania -5,182 -1,064 -4,118 Kentucky -17,303 -5,013 -12,291
New Hampshire -6,359 1,224 -7,584 West Virginia -17,357 -4,290 -13,067
Georgia -7,262 -1,923 -5,338 Arkansas -17,616 -5,171 -12,445
Arizona -8,662 1,557 -10,219 Hawaii -18,103 -14,124 -3,980
Kansas -8,828 1,820 -10,648 Idaho -18,636 -1,567 -17,069
Ohio -9,766 -1,436 -8,330 Mississippi -20,859 -6,165 -14,694
Oregon -9,774 -2,355 -7,420 South Dakota -21,211 955 -22,166
Wisconsin -10,479 -3,341 -7,138 Montana -22,488 -3,494 -18,994
Cluster mix: a region’s particular mix of lower and higher average wage clusters
Relative cluster wage: a region’s cluster wage relative to the average national wage in that cluster
The cluster mix and the cluster wage level effects add up to the total difference between a region’s average wage and the
national average wage. On average, the wage level effect is responsible for 76.3% of the total difference in state wages to the
national average.
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17 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Effect of Urban and Rural Areas on Average State Wages U.S. States, 2008
State
Average Overall Wage
Difference to U.S.
Metro-Rural Mix
Relative Metro Wage
Relative Rural Wage State
Average Overall Wage
Difference to U.S.
Metro-Rural Mix
Relative Metro Wage
Relative Rural Wage
New York 15,412 982 14,078 353 Nevada -4,560 815 -5,752 377
Connecticut 10,919 1,013 9,592 315 Louisiana -4,739 -630 -4,764 655
Massachusetts 10,197 1,674 8,333 190 Kansas -5,371 -2,175 -2,535 -661
New Jersey 8,488 1,631 6,765 92 North Carolina -5,505 -1,262 -3,796 -446
Alaska 6,538 -1,438 5,158 2,818 Tennessee -5,992 -538 -4,973 -481
California 5,584 1,476 3,844 265 Florida -6,132 -128 -6,074 70
Illinois 3,427 411 3,277 -261 Indiana -6,225 -630 -5,665 70
Washington 3,013 832 2,122 58 Oklahoma -6,501 -2,030 -4,496 25
Delaware 2,664 -191 2,895 -40 Hawaii -6,583 -1,892 -4,871 179
Maryland 2,201 1,159 775 267 Utah -7,054 169 -7,273 50
Virginia 1,182 509 709 -36 Vermont -7,280 -6,080 -968 -232
Minnesota 1,024 -903 2,130 -202 Nebraska -7,419 -2,652 -3,621 -1,146
Colorado 539 -110 -66 714 Alabama -7,544 -1,206 -5,701 -636
Texas 325 350 -234 209 Maine -7,697 -2,479 -5,243 24
New Hampshire -504 -2,856 924 1,428 Kentucky -7,978 -2,179 -5,285 -515
Pennsylvania -1,184 262 -1,480 34 Iowa -8,096 -3,123 -4,509 -464
Michigan -1,785 -165 -1,576 -44 New Mexico -8,531 -1,843 -6,548 -140
Rhode Island -2,143 1,720 -3,846 -17 South Carolina -9,137 -609 -8,203 -325
Wyoming -2,478 -6,929 -2,304 6,755 Arkansas -9,482 -2,207 -6,283 -992
Georgia -3,136 -120 -2,542 -475 Idaho -9,766 -1,928 -6,872 -966
Ohio -3,925 -224 -3,799 98 North Dakota -9,973 -2,963 -6,607 -403
Arizona -3,962 937 -4,897 -2 West Virginia -10,074 -3,104 -7,013 43
Oregon -4,116 -359 -3,505 -251 South Dakota -10,976 -3,811 -5,475 -1,690
Wisconsin -4,336 -910 -3,419 -7 Mississippi -11,446 -4,569 -5,493 -1,383
Missouri -4,540 -573 -3,103 -865 Montana -11,792 -5,468 -5,495 -829
Note: Data are based on private, non-agricultural employment.
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
Metro-rural mix: average wage impact from a state’s relative proportion of metro and rural regions
Relative metro wage: average wage impact from state relative performance in metro regions
Relative rural wage: average wage impact from state relative performance in rural regions
On average 66.3% of the average wage gap in a state is due to the metro wage effect.
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18 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Composition of the South Dakota Economy
and Cluster Performance
19 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Composition of Regional Economies, United States
Local Clusters
• Serve almost
exclusively the
local market
• Not exposed to
cross-regional
competition for
employment
71.7% of
employment
61.8% of income
3.5% of patents
27.4% of
employment
37.3% of income
96.4% of patents
Traded Clusters
• Serve markets in other
regions and countries
• Free to choose location
• Exposed to competition
from other regions
Source: Michael E. Porter, Economic Performance of Regions, Regional Studies (2003); Updated via
Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School (2008)
Resource-based Clusters
• Location determined by
resource availability
• <1% of income,
employment, and patents in
the U.S.
20 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Overall Composition of the South Dakota Economy, 2008
SD 27.0%
SD 72.0%
SD 1.0%
US 27.4%
US 71.7%
US 0.9%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Traded Clusters Local Clusters Natural EndowmentDependent
Perc
en
t o
f To
tal
Pri
va
te E
mp
loym
en
t
Note: Data throughout this section of the report are based on private, non-agricultural employment.
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
21 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Composition of the South Dakota Economy Employment by Traded Cluster, 2008 Rank in US
Note: Ranks are among the 50 US states plus the District of Columbia. Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
Employment, 2008
606070
8098130140184245
375447514535560585662
7349359371,0651,078
1,292
1,3071,327
1,6871,787
2,2923,439
3,656
3,6574,2814,4404,446
5,3295,490
7,7008,488
10,43113,103
0 2,000 4,000 6,000 8,000 10,000 12,000 14,000
Aerospace Vehicles and Defense 47Fishing and Fishing Products 38
Apparel 47
Leather and Related Products 48Aerospace Engines 40Biopharmaceuticals 47
Communications Equipment 45Oil and Gas Products and Services 46
Sporting, Recreational and Children's Goods 39Construction Materials 45
Furniture 44Forest Products 48
Lighting and Electrical Equipment 40Pow er Generation and Transmission 46
Motor Driven Products 37Jew elry and Precious Metals 23
Agricultural Products 43Textiles 34
Prefabricated Enclosures 34Medical Devices 38
Chemical Products 42Analytical Instruments 44
Metal Manufacturing 43
Information Technology 45Plastics 41
Transportation and Logistics 49Automotive 40
Entertainment 46Building Fixtures, Equipment and Services 35
Production Technology 36Distribution Services 43
Education and Know ledge Creation 47Heavy Construction Services 46
Publishing and Printing 34Heavy Machinery 23
Hospitality and Tourism 50
Business Services 50Processed Food 34
Financial Services 35
South Dakota overall employment rank = 47
22 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
1.6%
-1.0% -0.8% -0.6% -0.4% -0.2% 0.0% 0.2% 0.4%
Change in South Dakota share of National Employment, 1998 to 2008
So
uth
Da
ko
ta’s
na
tio
na
l e
mp
loym
en
t s
ha
re, 2
00
8
Employees 2,300 =
Composition of the South Dakota Economy Specialization by Traded Cluster, 1998 to 2008
South Dakota Overall Share of US
Traded Employment: 0.28%
Overall change in the South
Dakota Share of US Traded
Employment: + 0.02%
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
Added Jobs
Lost Jobs
Employment
1998-2008 Heavy Machinery
Information Technology
Lighting and Electrical
Equipment
Jewelry and Precious Metals
Processed Food
Building Fixtures,
Equipment and
Services
Prefabricated Enclosures
Production
Technology
Financial
Services Publishing
and Printing
Textiles
Chemical Products
Business Services
Entertainment
Hospitality and Tourism
23 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
0.0%
0.1%
0.2%
0.3%
0.4%
-0.15% -0.10% -0.05% 0.00% 0.05% 0.10% 0.15%
Change in South Dakota share of National Employment, 1998 to 2008
So
uth
Da
ko
ta’s
na
tio
na
l e
mp
loym
en
t s
ha
re, 2
00
8
Employees 2,300 =
Composition of the South Dakota Economy Specialization by Traded Cluster, 1998 to 2008 (continued)
South Dakota Overall Share of
US Traded Employment:
0.28%
Overall change in the South
Dakota Share of US Traded
Employment: + 0.02%
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
Added Jobs
Lost Jobs
Employment
1998-2008
Hospitality and
Tourism Sports, Recreation and Children’s Goods
Heavy
Construction
Services
Plastics
Automotive
Business Services
Fishing and
Fishing Products
Construction
Materials
Motor Driven Products
Agricultural
Products
Distribution
Services
Entertainment
Power Generation and Transmission
Medical
Devices Analytical Instruments
Furniture
Leather and Related Products
Apparel
Aerospace Vehicles and Defense
Oil and Gas Products and Services
Biopharmaceutical
Communication Equipment
Transportation and Logistics
Educational and Knowledge Creation Forest Products
Metal
Manufacturing
Aerospace Engines
24 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
South Dakota Job Creation by Traded Cluster 1998 to 2008
Jo
b C
rea
tio
n,
19
98
to
20
08
-10,000
-8,000
-6,000
-4,000
-2,000
0
2,000
4,000
6,000
8,000
10,000F
ina
ncia
l S
erv
ice
s
Bu
sin
ess S
erv
ice
s
Pu
blish
ing
an
d P
rin
tin
g
Pro
du
ctio
n T
ech
no
log
y
He
avy C
on
str
uctio
n S
erv
ice
s
Dis
trib
utio
n S
erv
ice
s
Ed
uca
tio
n a
nd
Kn
ow
led
ge
Cre
atio
n
Bu
ild
ing
Fix
ture
s, E
qu
ipm
en
t a
nd
Se
rvic
es
He
avy M
ach
ine
ry
Ch
em
ica
l P
rod
ucts
Tra
nsp
ort
atio
n a
nd
Lo
gis
tics
Ho
sp
ita
lity
an
d T
ou
rism
Au
tom
otive
Pla
stics
Te
xtile
s
Ag
ricu
ltu
ral P
rod
ucts
Co
mm
un
ica
tio
ns E
qu
ipm
en
t
Co
nstr
uctio
n M
ate
ria
ls
Fis
hin
g a
nd
Fis
hin
g P
rod
ucts
Me
dic
al D
evic
es
Ae
rosp
ace
En
gin
es
Oil a
nd
Ga
s P
rod
ucts
an
d S
erv
ice
s
En
tert
ain
me
nt
Ae
rosp
ace
Ve
hic
les a
nd
De
fen
se
Mo
tor
Dri
ve
n P
rod
ucts
Bio
ph
arm
ace
utica
ls
Sp
ort
ing
, R
ecre
atio
na
l a
nd
Ch
ild
ren
's G
oo
ds
Fo
rest P
rod
ucts
Le
ath
er
an
d R
ela
ted
Pro
du
cts
Po
we
r G
en
era
tio
n a
nd
Tra
nsm
issio
n
Me
tal M
an
ufa
ctu
rin
g
Pre
fab
rica
ted
En
clo
su
res
Je
we
lry a
nd
Pre
cio
us M
eta
ls
Ap
pa
rel
Fu
rnitu
re
An
aly
tica
l In
str
um
en
ts
Lig
htin
g a
nd
Ele
ctr
ica
l E
qu
ipm
en
t
Pro
ce
sse
d F
oo
d
Info
rma
tio
n T
ech
no
log
y
Net traded job creation,
1998 to 2008:
+9,690
Indicates expected job creation
given national cluster growth.*
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
* Percent change in national benchmark times starting regional employment. Overall traded job creation in South Dakota, if it matched national benchmarks, would be + 546
25 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
$0 $20,000 $40,000 $60,000 $80,000 $100,000 $120,000 $140,000
ApparelFootwear
TextilesConstruction Materials
Fishing and Fishing ProductsLeather and Related Products
Sporting, Recreational and Children's GoodsMotor Driven Products
Lighting and Electrical EquipmentTobacco
Communications EquipmentMedical Devices
BiopharmaceuticalsAerospace Vehicles and Defense
Power Generation and TransmissionHospitality and Tourism
EntertainmentEducation and Knowledge Creation
FurniturePlastics
Forest ProductsPublishing and Printing
Transportation and LogisticsJewelry and Precious Metals
Aerospace EnginesAnalytical Instruments
Building Fixtures, Equipment and ServicesAgricultural ProductsMetal Manufacturing
Prefabricated EnclosuresAutomotive
Business ServicesProcessed Food
Heavy MachineryProduction Technology
Distribution ServicesFinancial Services
Heavy Construction ServicesChemical Products
Information TechnologyOil and Gas Products and Services
South Dakota Wages by Traded Cluster vs. National Benchmarks
Wages, 2008
South Dakota average
traded wage: $32,563
l Indicates average
national wage in
the traded cluster.
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
U.S. average traded
wage: $57,706
26 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
South Dakota Employment in Highest Wage Clusters, 2008
Total private, non-agricultural employment in South Dakota: 337,816.
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
= 12.5% of
total private
employment
27 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Furniture Building
Fixtures,
Equipment &
Services
Fishing &
Fishing
Products
Hospitality
& Tourism Agricultural
Products
Transportation
& Logistics
South Dakota Cluster Portfolio, 2008
Plastics
Oil &
Gas
Chemical
Products
Biopharma-
ceuticals
Power
Generation &
Transmission
Aerospace
Vehicles &
Defense
Lightning &
Electrical
Equipment
Financial
Services
Publishing
& Printing
Entertainment
Information
Tech.
Communi
cations
Equipment
Aerospace
Engines
Business
Services
Distribution
Services
Forest
Products
Heavy
Construction
Services
Construction
Materials
Prefabricated
Enclosures
Heavy
Machinery
Sporting
& Recreation
Goods
Automotive
Production
Technology Motor Driven
Products
Metal
Manufacturing
Apparel
Leather &
Related
Products
Jewelry &
Precious
Metals
Textiles
Footwear
Processed
Food
Tobacco
Medical
Devices
Analytical
Instruments Education &
Knowledge
Creation
LQ > 4
LQ > 2
LQ > 1.
LQ, or Location Quotient, measures the state’s share in cluster employment relative to its overall share of U.S. employment.
An LQ > 1 indicates an above average employment share in a cluster.
28 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
-0.1% 0.0% 0.1% 0.2% 0.3% 0.4% 0.5% 0.6% 0.7% 0.8% 0.9%
Change in Share of National Employment, 1998 to 2008
Na
tio
na
l e
mp
loym
en
t s
ha
re, 2008
Employees 450 =
South Dakota Share of US
Heavy Machinery Employment:
1.59%
Change in South Dakota Share of
US Heavy Machinery
Employment: +0.34%
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
Added Jobs
Lost Jobs
Employment
1998-2008
South Dakota Heavy Machinery Cluster, 1998-2008 Specialization by Subcluster
Farm Machinery
Construction Machinery
Machinery Components
Railroad Equipment and Rental
29 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
South Dakota Top 50 Subclusters by National Employment Share, 2008
Rising national employment share
Declining national employment share
Subcluster Cluster Employment
Employment
Rank in U.S.
Employment
Share in U.S.
Change in
Employment
Share in U.S.
1998-2008
1 Signs and Advertising Specialties Publishing and Printing 3,750 6 4.2% 2.4%
2 Construction Machinery Heavy Machinery 2,500 14 2.7% 0.8%
3 Specialty Fabric Mills Textiles 750 15 2.7% 0.7%
4 Trucks and Trailers Prefabricated Enclosures 696 16 2.7% 0.0%
5 Explosives Heavy Construction Services 175 18 2.6% 1.9%
6 Milling Processed Food 1,940 14 2.2% 0.1%
7 Meat and Related Products and Services Processed Food 5,323 17 1.8% -0.3%
8 Transformers Power Generation and Transmission 375 19 1.7% 1.1%
9 Farm Machinery Heavy Machinery 2,545 22 1.6% 0.1%
10 Machinery Components Heavy Machinery 435 18 1.6% 0.4%
11 Industrial Trucks and Tractors Production Technology 375 23 1.4% 1.4%
12 Ammunition Chemical Products 360 17 1.4% 0.8%
13 Peripherals Information Technology 760 19 1.3% 0.1%
14 Farm Material and Supplies Wholesaling Distribution Services 1,108 28 1.3% 0.7%
15 Processed Dairy and Related Products Processed Food 750 21 1.3% -0.1%
16 Motorcycles and Bicycles Sporting, Recreational and Children's Goods 175 16 1.2% 1.2%
17 Depository Institutions Financial Services 10,814 28 1.2% 0.8%
18 Specialized Machinery Motor Driven Products 60 29 1.1% 0.4%
19 Furniture and Fittings Building Fixtures, Equipment and Services 1,040 30 1.0% 0.4%
20
Process Equipment Sub-systems and
Components Production Technology 2,645 33 0.9% 0.4%
21 Fabricated Materials Building Fixtures, Equipment and Services 385 28 0.9% 0.2%
22 Small Arms Aerospace Engines 88 22 0.8% 0.2%
23 Jewelry and Precious Metals Products Jewelry and Precious Metals 642 19 0.8% -0.2%
24 Wood Cabinets, Fixtures and Other Products Building Fixtures, Equipment and Services 2,101 34 0.8% 0.3%
25 Fishing and Hunting Fishing and Fishing Products 60 27 0.8% 0.7%
30 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
South Dakota Top 50 Subclusters by National Employment Share, 2008 (continued)
Rising national employment share
Declining national employment share
Subcluster Cluster Employment
Employment
Rank in U.S.
Employment
Share in U.S.
Change in
Employment
Share in U.S.
1998-2008
26 Photographic Equipment and Supplies Publishing and Printing 175 32 0.7% 0.4%
27 Primary Construction Materials Heavy Construction Services 1,369 39 0.7% 0.3%
28 Electronic Components Analytical Instruments 1,087 31 0.7% -0.2%
29 Electrical Parts Lighting and Electrical Equipment 395 33 0.6% -1.0%
30 Irrigation Systems Agricultural Products 224 32 0.6% 0.0%
31 Cut and Crushed Stone Construction Materials 235 37 0.6% -0.5%
32 Glass Automotive 375 31 0.6% 0.6%
33 Precision Metal Products Metal Manufacturing 445 32 0.6% 0.2%
34 Entertainment Venues Entertainment 2,431 42 0.6% -0.3%
35 Farm Management and Related Services Agricultural Products 480 34 0.6% 0.3%
36 Collectibles Jewelry and Precious Metals 10 32 0.5% 0.2%
37 Baked Packaged Foods Processed Food 1,195 39 0.5% -0.1%
38 Photographic Services Publishing and Printing 60 39 0.5% 0.2%
39 Paper Products Publishing and Printing 255 35 0.5% 0.2%
40 Paper Containers and Boxes Processed Food 722 37 0.4% 0.1%
41 Accommodations and Related Services Hospitality and Tourism 6,849 47 0.4% 0.0%
42 Small Vehicles and Trailers Automotive 60 29 0.4% 0.1%
43 Specialty Fabric Processing Textiles 175 34 0.4% 0.4%
44 Intermediate Chemicals and Gases Chemical Products 647 38 0.4% 0.3%
45 Transportation Support and Operations Transportation and Logistics 203 41 0.4% 0.2%
46 Prefabricated Wood Products Forest Products 444 43 0.4% 0.0%
47 Surgical Instruments and Supplies Medical Devices 810 35 0.4% 0.0%
48 Printing Services Business Services 60 33 0.4% 0.3%
49 Office Furniture Prefabricated Enclosures 60 32 0.4% 0.4%
50 Refrigeration and Heating Equipment Motor Driven Products 385 33 0.3% 0.1%
31 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
2,365
4,785
5,522
6,274
7,274
8,001
8,144
11,000
12,258
15,497
16,059
16,919
17,029
29,820
31,791
56,433
0 10,000 20,000 30,000 40,000 50,000 60,000
Local Industrial Products and Services 48
Local Education and Training 45
Local Household Goods and Services 46
Local Entertainment and Media 46
Local Personal Services (Non-Medical) 47
Local Utilities 41
Local Logistical Services 48
Local Community and Civic Organizations 48
Local Food and Beverage Processing and Dist 46
Local Retail Clothing and Accessories 45
Local Financial Services 44
Local Motor Vehicle Products and Services 43
Local Commercial Services 49
Local Real Estate, Construction, and Develo 46
Local Hospitality Establishments 47
Local Health Services 44
South Dakota Employment by Local Cluster 2008
Employment, 2008
Rank in US
Note: Ranks are among the 50 US states plus the District of Columbia. Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
South Dakota overall employment rank = 47
32 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
South Dakota Job Creation by Local Cluster 1998 to 2008
Jo
b C
rea
tio
n, 1
99
8 t
o 2
00
8
-4,000
-2,000
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000L
oca
l H
ea
lth
Se
rvic
es
Lo
ca
l R
ea
l E
sta
te,
Co
nstr
uctio
n, a
nd
De
ve
lo
Lo
ca
l H
osp
ita
lity
Esta
blish
me
nts
Lo
ca
l C
om
me
rcia
l
Se
rvic
es
Lo
ca
l R
eta
il C
loth
ing
an
d A
cce
sso
rie
s
Lo
ca
l U
tilitie
s
Lo
ca
l P
ers
on
al S
erv
ice
s
(No
n-M
ed
ica
l)
Lo
ca
l M
oto
r V
eh
icle
Pro
du
cts
an
d S
erv
ice
s
Lo
ca
l L
og
istica
l S
erv
ice
s
Lo
ca
l C
om
mu
nity a
nd
Civ
ic O
rga
niz
atio
ns
Lo
ca
l F
ina
ncia
l S
erv
ice
s
Lo
ca
l In
du
str
ial P
rod
ucts
an
d S
erv
ice
s
Lo
ca
l E
du
ca
tio
n a
nd
Tra
inin
g
Lo
ca
l H
ou
se
ho
ld G
oo
ds
an
d S
erv
ice
s
Lo
ca
l E
nte
rta
inm
en
t a
nd
Me
dia
Lo
ca
l F
oo
d a
nd
Be
ve
rag
e P
roce
ssin
g
an
d D
ist
Net local job creation,
1998 to 2008:
+ 43,850
Indicates expected job creation
given national cluster growth.*
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director. * Percent change in national benchmark times starting regional employment. Overall local job creation in South Dakota, if it matched national benchmarks, would be +34,460
33 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
$0 $10,000 $20,000 $30,000 $40,000 $50,000 $60,000 $70,000 $80,000
Local Hospitality Establishments
Local Retail Clothing and Accessories
Local Community and Civic Organizations
Local Personal Services (Non-Medical)
Local Food and Beverage Processing and Dist
Local Entertainment and Media
Local Education and Training
Local Household Goods and Services
Local Motor Vehicle Products and Services
Local Logistical Services
Local Real Estate, Construction, and Develo
Local Health Services
Local Commercial Services
Local Industrial Products and Services
Local Financial Services
Local Utilities
South Dakota Wages by Local Cluster vs. National Benchmarks
Wages, 2008
South Dakota average local
wage: $29,656
l Indicates average
national wage in
the local cluster.
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
U.S. average local
wage: $36,911
34 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Appendix:
Chart Descriptions, Interpretation, and Sources
35 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
State Snapshot The snapshot chart summarizes the relative performance of a state on levels and trends in five key
measures. The circles in the chart indicate quintile of performance as shown in chart legend.
1. Prosperity: State GDP per capita and 10-year trend
2. Productivity: Average private wage and 10-year trend
3. Labor Mobilization: Total labor force as a share of civilian population and 10-year trend
4. Innovation: Utility patents per 10,000 workers and 10-year trend
5. Cluster Strength:
• A “strong cluster” is identified by relative employment rank in the top 20% across all states. A
state’s “cluster strength” is in turn the state’s total share of traded employment in these strong
clusters.
• A positive trend in cluster strength is indicated by a state’s increasing national cluster share
across these strong clusters.
Leading Clusters: A listing of the state’s strong clusters is included. A state may have more than five strong
clusters; the top five by employment size in the state are shown in this section.
36 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Components of Regional Economies
Source: Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School
A state’s or region’s economy can be divided into traded clusters, local clusters, and natural endowment
industries:
Traded clusters include those industries that compete across regions, and which tend to concentrate in
particular locations. Traded clusters are the engines of regional economic competitiveness. While they
account for only about a third of employment, they achieve the highest wages and productivity levels and
drive demand for localized businesses.
Local clusters involve activities serving almost exclusively the local market. Local clusters are present in
every region in roughly the same proportions. They employ the majority of people in any regional economy,
so their efficiency is critical for competitiveness in traded clusters. However, they cannot prosper over the
long run without success in the traded clusters.
Natural Endowment-dependent industries concentrate at natural resource sites. They account for a small
and declining share of national employment but can be relatively high wage.
The Cluster Mapping Project data presented in this report focuses primarily on traded clusters, though it
contains some information about other categories of industries. The performance of traded clusters holds
the key to present and future competitiveness.
37 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Employment by Traded Cluster
Source: Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School
Within the broad category of traded clusters, a state’s economy can be divided into individual clusters.
Clusters are geographically proximate groups of interconnected companies and associated institutions in a
particular field, linked by commonalities and complementarities. Examples include automotive producers in
Michigan and Ohio, information technology in Silicon Valley, and money management in Boston.
The 41 traded clusters (and their 264 component subclusters) utilized in the Cluster Mapping Project were
developed using statistical analysis of the actual patterns of business location in the U.S. economy.
Clusters and subclusters are listed at the end of this appendix.
Interpretation:
This chart gives total employment in the state economy by each traded cluster.
Employment by cluster gives a more detailed profile of the activities in the state economy that make up the
job base. It can be used to understand the importance of the health of various groups or industries on the
overall prosperity of the region. z
Also shown on the chart are employment ranks for
each cluster versus those in the 50 U.S. states plus
D.C. Ranks above the region’s overall share of
national employment are an indication of cluster
specialization in the state and are highlighted on the
chart.
38 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Specialization by Traded Cluster
Source: Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School
While other charts in this report focus on absolute employment and changes in employment, the
Specialization chart shows the region’s competitive position by traded cluster.
The size of each cluster “bubble” is proportional to the number of jobs in the region.
The location of each cluster bubble on the chart identifies a cluster’s relative performance in the US
economy:
• Clusters on the top half of the chart have local employment levels that are more than
proportionate to the region’s overall employment. These are clusters in which the region is
relatively specialized.
• Clusters on the right half of the chart are growing employment at a faster rate than the national
average for those clusters. These are clusters in which the region is gaining position in terms of
relative employment.
When present, a gray shaded area on the chart indicates that further detail is available on a second version
of the chart immediately following the current page.
Strong and growing position
Cluster is growing faster
The region’ share
of cluster employment Strong and growing
position
than the US average
relative to its size
39 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Specialization by Subcluster
Strong and growing position
Subcluster is growing faster than average for the cluster
High share of national employment relative to average for the cluster
Strongest and fastest growing positions
The specialization by subcluster chart is interpreted similarly to the specialization chart for all traded clusters.
Additional insight on particular cluster strengths and trends in cluster composition can be observed.
Please note that only one or a few subcluster charts were included in this report. Specialization charts and
other data for all subclusters are available online at the Cluster Mapping Project reached from
www.isc.hbs.edu.
40 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Job Creation by Traded Cluster
Source: Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School
This chart shows the overall net change in traded jobs in the state over the period from 1998 to 2008 and the
net gain or loss by traded cluster. The clusters are arranged in order of net jobs created. The blue bars
provide benchmarks for job creation based upon rates of growth in the cluster throughout the U.S.
Interpretation:
This chart allows a state to identify its biggest job generators and job losers among traded clusters over the
last decade. A few clusters often account for a large majority of the overall employment gain. Clusters with
job losses are a cause for concern. It is helpful to compare job performance with the policy priorities a region
has set.
Comparison of job growth relative to the U.S. benchmarks provides insights into the strengths and
weaknesses in the region’s economy and shifts in the region’s competitive position. A region might not be
participating in a cluster which is surging nation-wide; or a region might be gaining market position in an
important cluster.
41 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Wages by Traded Cluster
Source: Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School
The state’s clusters are listed in order by average wage. The yellow bars show the benchmark average
wage for the cluster nationally. The average wage across all traded clusters in the region is indicated by the
green dashed line.
Wages are a direct measure of a cluster’s productivity and competitiveness. Clusters that are exceptionally
productive (the value of output produced per unit of labor) can sustain higher wages.
Note: The wages for some clusters may not be reported due to data suppression in the underlying
government reports. When few employers in an industry are present in a given region, wage and precise
employment figures are omitted to protect the confidentiality of the data.
Benchmark lines provide a comparison to wages in the cluster across the U.S.
42 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Employment in Highest Wage Clusters
The ten highest wage traded clusters in the state are shown in decreasing order, with the width of the
columns proportional to the number of workers in each cluster. The area of each cluster is thus equivalent to
the overall wage sum the cluster generated in the state.
The chart displays how the average wage in the state’s traded clusters is built up by highest
wage clusters. Some high wage clusters may have a small impact on overall wage levels because of their
small size, the case in some high wage clusters. Some large, high wage clusters are often those in services.
The comparison to the U.S. average wages by cluster (on the previous chart) gives an initial benchmark to
evaluate the composition of average wages in the state economy. States can increase wages in two different
ways: (1) increase the employment in high wage clusters relative to low wage clusters and/or (2) increase
the state’s relative wages in given clusters. In practice, the second effect dominates as the explanation for
why state wages differ.
43 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Cluster Portfolio
Source: Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School
Cluster Linkages
Our research on clusters, in addition to deriving a model of 41 distinct traded clusters, provides a measure
for the the strength of the links between these traded clusters. The strength of these links is summarized
visually in the portfolio diagram below by the relative positioning and overlapping of cluster circles.
Location Quotient (LQ)
The Location Quotient is a ratio measure of the concentration of a cluster in a state relative to that state’s
average share of employment in the U.S. traded economy. So, LQ is a measure of a cluster's level of
concentration within a state, with an LQ > 1 indicating higher than average concentration in that state.
Interpretation
Using Location Quotient as the measure of cluster concentration in the state, we overlay the state’s cluster
portfolio on the model of cluster linkages with three color levels as below. The pattern of a state’s portfolio
relative to the cluster linkages will often indicate paths of opportunity for development in clusters.
44 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Top Subclusters by National Employment Share
Source: Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School
This chart selects the sub-clusters in the region with the highest National Employment Shares. The
subclusters are grouped by cluster and ordered by subcluster National Employment Share.
Sub-clusters with a high share of national employment may form the basis for developing a competitive
position in a cluster. Strengths in a breadth of related sub-clusters are an indication of an established
position in a cluster.
45 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Patents by Organization
Source: Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School
This table lists by organization the top patent recipients in the region for the most recent five-year
period. Patents are assigned to regions according to the inventor’s address of residence. In the case of
multiple inventors from different locations, the patent is assigned fractionally to each region. Universities and
research institutes are highlighted in blue and government agencies in green.
Interpretation:
Patenting is the best single measure of innovation output. States and regions with a healthy level of
innovation tend to have patents originating from a variety of corporations across a number of fields as well as
significant patenting from universities and research institutes. Concerns about innovative capacity arise
when the patenting rate is low, patents originate principally from a government agency, or patenting is
dominated by only a few large firms.
Defining the Appropriate Region Massachusetts in BEA Economic Areas
46 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
A Note on Regions
The political boundaries of a state often encompass many distinct regional economies or portions of
larger regional economies. A comprehensive approach to economic development should reflect both the
distinct economies within a state as well as the often strong linkages to economies in neighboring states.
The map on the following page shows the intersection of the state with the Economic Areas defined by
the U.S. Bureau of Economic Analysis (BEA.) We find that the Economic Areas are a very meaningful unit of
geography for exploring the specialization and linkages in the U.S. economy. BEA's 179 economic areas
cover the entire U.S. and define the relevant regional markets surrounding metropolitan or micropolitan
statistical areas. They consist of one or more economic nodes - metropolitan or micropolitan statistical areas
that serve as regional centers of economic activity - and the surrounding counties that are economically
related to the nodes.
Please note that while this report has focused exclusively on the state, the website of the Cluster
Mapping Project reached from www.isc.hbs.edu provides similar data and analyses for all Economic Areas
(and Metropolitan Areas) in the U.S.
Note: There are 177 Economic Areas in the continental U.S. and one each for Alaska and Hawaii.
47 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Defining the Appropriate Region South Dakota in BEA Economic Areas
Source: Prof. Michael E. Porter, Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School; Richard Bryden, Project Director.
Data from Bureau of Economic Analysis 2010.
Rapid City, SD
Sioux City-Vermillion, IA-NE-SD
Sioux Falls, SD
Aberdeen, SD
Minneapolis-St. Paul-St. Cloud, MN-WI
Bismarck, ND
48 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
Traded Clusters and Subclusters in the US Economy
See http://www.isc.hbs.edu/cmp/help.html for Excel listing.
Source: Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School
Aerospace Engines Chemical Products Furniture M etal M anufacturing Processed FoodAircraf t Engines Int ermediat e Chemicals and Gases Furnit ure Fabricat ed Met al Product s Milk and Frozen Dessert s
Precision Met al Product s Packaged Chemical Product s Wood Mat erials and Product s Met al Alloys Baked Packaged Foods
Ot her Processed Chemicals Furnishings Primary Met al Product s Cof f ee
Aerospace Vehicles and Defense Ref ract or ies Tableware and Kit chenware Precision Met al Product s Processed Dairy and Relat ed Product s
Aircraf t Leat her Tanning and Finishing Fast eners Meat and Relat ed Product s and Services
Missiles and Space Vehicles Ammunit ion Heavy Construction Services Wire and Springs Flour
Def ense Equipment Special Packaging Final Const ruct ion Met al Processing Specialt y Foods and Ingredient s
Treat ed Garment s Subcont ract ors Iron and St eel Mills and Foundries Milling
Agricultural Products Primary Const ruct ion Mat erials Nonf errous Mills and Foundries Candy and Chocolat e
Farm Management and Relat ed Services Communications Equipment CeramicTile Met al Furnit ure Malt Beverages
Soil Preparat ion Services Communicat ions Equipment Equipment Dist r ibut ion and Wholesaling Environment al Cont rols Paper Cont ainers and Boxes
Irr igat ion Syst ems Elect r ical and Elect ronic Component s Fabricat ed Met al St ruct ures and Piping Pumps Met al and Glass Cont ainers
Packaging Specialt y Of f ice Machines Explosives Saw Blades and Handsaws Food Product s Machinery
Fert ilizers General Indust r ial Machinery
Agricult ural Product s Construction M aterials Heavy M achinery Laundry and Cleaning Equipment Production TechnologyWine and Brandy Tile, Brick and Glass Const ruct ion Machinery Met al Armament s Machine Tools and Accessories
Cigars Plumbing Fixt ures Farm Machinery Process Equipment Sub-syst ems and Component s
Milling and Ref ining Wood Product s Railroad Equipment and Rent al M otor Driven Products Hoist s and Cranes
Cut and Crushed St one Mining Machinery Mot ors and Generat ors Process Machinery
Analytical Instruments Gum and Wood Chemicals Machinery Component s Bat t er ies Indust r ial Pat t erns
Laborat ory Inst rument s Rubber Product s Valves and Pipe Fit t ings Mot orized Equipment Fabricat ed Plat e Work
Opt ical Inst rument s Ref r igerat ion and Heat ing Equipment Indust r ial Trucks and Tract ors
Process Inst rument s Distribution Services Hospitality and Tourism Appliances Ball and Roller Bearings
Search and Navigat ion Equipment Merchandise Wholesaling Tourism At t ract ions Specialized Pumps
Elect ronic Component s Apparel and Accessories Wholesaling Tourism Relat ed Services Specialized Machinery Publishing and PrintingCat alog and Mail-order Wat er Passenger Transport at ion Tires and Inner Tubes Publishing
Apparel Food Product s Wholesaling Accommodat ions and Relat ed Services News Syndicat es
Men's Clot hing Farm Mat erial and Supplies Wholesaling Boat Relat ed Services Oil and Gas Products and Services Signs and Advert ising Specialt ies
Women's and Children's Clot hing Transport at ion Vehicle and Equipment Dist r ibut ion Ground Transport at ion Oil and Gas Machinery Phot ographic Services
Hosiery and Ot her Garment s Hydrocarbons Phot ographic Equipment and Supplies
Accessories Education and Knowledge Creation Information Technology Oil and Gas Explorat ion and Drilling Radio, TV, Publisher Represent at ives
Knit t ing and Finishing Mills Educat ional Inst it ut ions Comput ers Oil Pipelines Print ing Services
Research Organizat ions Elect ronic Component s and Assemblies Pet roleum Processing Print ing Input s
Automotive Educat ional Facilit ies Peripherals Oil and Gas Trading Paper Product s
Mot or Vehicles Pat ent Owners and Lessors Sof t ware Wat er Freight Transport at ion Services Specialt y Paper Product s
Aut omot ive Part s Supplies Communicat ions Services Inked Paper and Ribbons
Aut omot ive Component s Plastics Of f ice Equipment and Supplies
Forgings and St ampings Entertainment Jewelry and Precious M etals Plast ic Mat erials and Resins
Flat Glass Video Product ion and Dist r ibut ion Jewelry and Precious Met al Product s Plast ic Product s Sporting, Recreational and Children's GoodsProduct ion Equipment Recorded Product s Cost ume jewelry Paint s and Allied Product s Sport ing and At hlet ic Goods
Small Vehicles and Trailers Ent ert ainment Equipment Cut lery Synt het ic Rubber Games, Toys, and Children's Vehicles
Ent ert ainment Relat ed Services Collect ibles Mot orcycles and Bicycles
Biopharmaceuticals Ent ert ainment Venues Power Generation and TransmissionBiopharmaceut ical Product s Leather and Related Products Elect r ic Services TextilesHealt h and Beaut y Product s Financial Services Leat her product s Turbines and Turbine Generat ors Fabric Mills
Cont ainers Deposit ory Inst it ut ions Fur Goods Transf ormers Specialt y Fabric Mills
Securit ies Brokers, Dealers and Exchanges Coat ed Fabrics Porcelain, Carbon and Graphit e Component s Specialt y Fabric Processing
Building Fixtures, Equipment and Services Insurance Product s Relat ed Product s Elect ronic Capacit ors Text ile Machinery
Plumbing Product s Healt h Plans Accessories Yarn and Thread Mills
Drapery Hardware Risk Capit al Providers Prefabricated Enclosures Carpet s and Rugs
Fabricat ed Mat erials Invest ment Funds Lighting and Electrical Equipment Recreat ional Vehicles and Part s Wool Mills
Heat ing and Light ing Real Est at e Invest ment Trust s Light ing Fixt ures Mobile Homes Fibers
Furnit ure and Fit t ings Passenger Car Leasing Elect r ic Lamps Trucks and Trailers Finishing Plant s
Clay and Vit reous Product s Bat t er ies Casket s Specialt y Apparel Component s
Floor Coverings Fishing and Fishing Products Swit chgear Elevat ors and Moving St airways Women's and Children's Underwear
St eam and Air-condit ioning Fish Product s Elect r ical Part s Of f ice Furnit ure Tire Cord and Fabrics
St one and Tile Work Fishing and Hunt ing Met al Part s Household Ref r igerat ors and Freezers
Wood Cabinet s, Fixt ures and Ot her Product s Processed Seaf oods Aluminum Processing TobaccoConcret e, Gypsum and Ot her Building Product s M edical Devices Cigaret t es
Footwear Surgical Inst rument s and Supplies Ot her Tobacco Product s
Business Services Foot wear Dent al Inst rument s and Supplies Tobacco Processing
Management Consult ing Specialt y Foot wear Opht halmic Goods Specialt y Packaging
Online Inf ormat ion Services Foot wear Part s Medical Equipment
Comput er Services Diagnost ic Subst ances Transportation and LogisticsComput er Programming Forest Products Biological Product s Air Transport at ion
Phot ocopying Paper Product s Bus Transport at ion
Market ing Relat ed Services Paper Mills Marine Transport at ion
Prof essional Organizat ions and Services Paper Indust r ies Machinery Ship Building
Engineering Services Pref abricat ed Wood Buildings Transport at ion Arrangement and Warehousing
Laundry Services Wood Part it ions and Fixt ures Trucking Terminal
Facilit ies Support Services Airport s
Bus Terminals
49 NGA 2011 – South Dakota – Rich Bryden Copyright © 2011 Professor Michael E. Porter
About This Report
This report was prepared in conjunction with Prof. Michael E. Porter’s presentation before the National
Governors Association Winter Meeting on February 26, 2011. It draws on data and analysis from the Cluster
Mapping Project and other sources at the Institute for Strategy and Competitiveness, Harvard Business
School; Richard Bryden, Project Director. Additional information may be found at the website of the Institute
for Strategy and Competitiveness, www.isc.hbs.edu. None of this information may be duplicated,
disseminated or copied without express written consent from the Institute for Strategy and Competitiveness.
This report is available electronically at http://www.isc.hbs.edu/stateprofiles.htm.