Transcript Shift share examples

Regional Analysis Methods
Benchmarking, Location Quotients,
Shift-share
Agenda
• Review
• Shift-Share
– What is it?
– How do you do it?
– What does it mean?
• Tools for interpreting
– Cautions and limits
• Multipliers
• Policy Map?
First Assignment – Q1
• What was the population of Allegheny
County in 2000 and 2004 (Census or
BEA)?
– 2000: 1,279,817 (BEA - REIS or Census July
1est.)
– or 2000: 1,281,666 (Census 2000 (SF1) April 1 estimate)
– 2004: 1,247,512 (BEA-REIS)
First Assignment Q2-4
• How many total jobs were available in
Allegheny County in 2004?
– 861,868 (BEA total employment)
• How many Allegheny County residents
were employed in 2004?
– 604,203
(BLS, CPS/LAUS)
• What was the total "covered" employment
in 2004?
– 685,878
(BLS, QCEW)
Second Assignment - I
• When you are benchmarking one region
against another, there are many factors to
consider in the selection of an appropriate
benchmark. Name two (2):
• If you are studying a region with dynamic
annual changes, what is the best method to
calculate the growth rates?
• You should never use a location quotient for
what purpose?
Second Assignment Part 2
• There a several considerations for
interpreting a location quotient. Name two
(2):
• What is the difference between a firm and
an establishment?
How do we interpret Pgh’s Growth?
Pittsburgh, 1969-2000
1,600,000
1,400,000
State and local
1,200,000
Military
Federal, civilian
1,000,000
Services
Finance, insurance, and real estate
800,000
Retail trade
Wholesale trade
Transportation and public utilities
600,000
Manufacturing
Construction
400,000
Mining
Agricultural services
200,000
2000
1999
1998
1997
1996
1995
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1993
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1991
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1989
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We can look at a basic view
Pittsburgh, 1969-2000
600,000
Manufacturing
500,000
Services
400,000
300,000
200,000
100,000
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Or a little more complexity
Pittsburgh, 1969-2000
1,000,000
900,000
800,000
Resource based
700,000
600,000
Federal
Government
Local Serving
500,000
Mfg & Trade
400,000
300,000
200,000
100,000
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Basic benchmarking can be helpful
Annual Employment Growth, 1969-2000
6.0%
Pittsburgh
United States
4.0%
2.0%
0.0%
-2.0%
-4.0%
-6.0%
Basic benchmarking can be helpful
Employment Change, 1970-1993
800,000
700,000
600,000
500,000
400,000
300,000
200,000
100,000
0
San Diego
Boise
Tucson
Fresno
Memphis
New Orleans
Toledo
Pittsburgh
But these descriptions still
haven’t explained much
Location Quotients
Interpretation
Formula
Region
Industry
Total
Nation
Industry
Total
Location Quotient
High
Important industries
that may require
attention
Important growth
industries
Industries of little
promise to local
economy
Potential emerging
industries
Low
Low
Employment Growth
High
Shift-Share
• What are the 3 components of a shift-share
analysis?
• A competitive industry is defined as
WHAT?
• Explain
– National share
– Industry Mix
– Regional Shift
• What are the limits of shift-share?
Albuquerque, 1970-1990
Albuquerque
• 127 % total
employment
growth
• +190,000
Jobs
• What
explains this
growth?
Region Total
Target Region
AGSVC
CON
FARM
FED
FIRE
MFG
MIL
MIN
RETAIL
STLGOV
SVC
TRAN
WHSALE
1970
150,901
Year 1
552
9,028
1,165
11,193
12,471
10,453
7,600
1,388
25,424
19,322
36,971
8,253
7,081
1990 Absolute
342,529
Year 2
2,268
18,634
1,729
14,599
26,569
26,240
8,134
1,313
59,987
44,475
107,068
14,904
16,609
191,628
Ri
1,716
9,606
564
3,406
14,098
15,787
534
-75
34,563
25,153
70,097
6,651
9,528
Three factors…
• Growth of the national economy
• Presence of growth industries (or
declining ones)
• Local competitive factors
Albuquerque
Region Total
Employment
Change
1970
1990 Absolute
Percent
150,901
342,529
191,628
127%
Projected
at National
Ave.
83,770
Diff btw
US &
actual ch.
Projected
Regional
Mix
Shares
107,858
14,595
93,263
Brief Glossary
•
•
•
•
R = actual regional change
N = change due to national growth
M = Industry mix effect
S = regional shift effect
Growth of the U.S. Economy
• If Alb had grown at the U.S. rate, it would
have added 83,770 jobs.
• The growth of the U.S. economy accounted
for 83,770, or 44% of the actual change.
• Alb in fact added more than 191,000 jobs –
so something else must explain the region’s
growth
The mix of industries in the region
• The presence of growth industries were not
a major factor in the region’s performance.
Growth industries on the whole accounted
for 8% of the actual change, which equaled
14,595 jobs.
• Must add jobs faster than the nation as a
whole to have a positive Mix effect
Local competitive factors
• The shift-share analysis estimates that 49%
of the growth in employment is the result of
local competitive conditions.
• 93, 263 of the jobs created in Albuquerque
were due to these local advantages
• These advantages were spread across every
industry but one – Mining.
Albuquerque Industry Data
Target Region
AGSVC
CON
FARM
FED
FIRE
MFG
MIL
MIN
RETAIL
STLGOV
SVC
TRAN
WHSALE
Year 2
2,268
18,634
1,729
14,599
26,569
26,240
8,134
1,313
59,987
44,475
107,068
14,904
16,609
Ri
Ri pct
1,716
9,606
564
3,406
14,098
15,787
534
-75
34,563
25,153
70,097
6,651
9,528
311%
106%
48%
30%
113%
151%
7%
-5%
136%
130%
190%
81%
135%
Mi
Si
668
504
-748
-5,037
2,548
-6,287
-5,503
135
2,266
-1,527
29,770
-1,884
-312
742
4,090
665
2,229
4,627
16,271
1,818
-981
18,183
15,953
19,803
3,954
5,909
What are the key industries?
We can combine statistics on
economic growth, the shift-share, and
specialization (LQs) to highlight
leading and lagging industries.
Finding Key Industries
Identify the
non-competitive
factors
Fix them if possible
Leading
Sustain
Prepare for transition
Manage decline
Do nothing
Develop the value chain Buyers & Supplier
Competitive
Lagging
Not Competitive
Innovate
Watch the market
Minimize investment
State and Local Gov
• It is a large industry in the region with
considerable growth.
• It is not a growth industry nationally – but
this industry does not move on strictly
national dynamics.
• It is a desirable goal to growth this
industry?
Manufacturing
• Still somewhat small – only 7% of regional
employment, less then 27,000 employees.
• Potential emerging sector in the region, but
the sector is declining nationally
– Can Alb capture more of this industry and for
how long?
– Are there subsectors in which the region has a
concentration and an advantage that are
growing?
Services
• Employment in Services accounts for 25% of the
region’s employment (comparable to the US
share).
• The industry grew by 70,000 jobs in the region
(190%), well above national and industry growth
• Local factors were positive, but contributed less to
the growth than national and industry factors.
Shift-share + benchmarking
Shift-Share Comparison, 1970-1993
600,000
Regional Shift
400,000
Industry Mix
200,000
0
San Diego
-200,000
-400,000
-600,000
Boise
Tucson
Fresno
Memphis
New
Orleans
Toledo
Pittsburgh
You may need to normalize the data
Regional Shift as a Proportion of Total Change
1.00
0.50
San Diego
(0.50)
(1.00)
(1.50)
(2.00)
(2.50)
(3.00)
(3.50)
Boise
Tucson
Fresno
Memphis
New Orleans
Toledo
Pittsburgh
The level of industry detail impacts
the shift-share analysis
Absolute Change
National Effect
Industry Mix
Local Shift
2digit 4 digit
-10132 -10132
-9450 -9450
690.71 -2759
-1373 2075.2
• More detail increases the accuracy of the
industry mix effect and the local shift.
The time frame impacts the shiftshare
1969-2000
1969
2000
1,128,141 1,384,664
R
256,523
N
991,947
M
-4,278
S
-731,146
1969-1988
1969
1988
1,128,141 1,205,775
R
77,634
N
571,936
M
-6,419
S
-487,883
1989-2000
1988
2000
1,205,775 1,384,664
R
178,889
N
297,892
M
29,909
S
-148,912
256,523
869,827
23,491
-636,795
Aggregated
• If the industry structure changes dramatically then a longer
time frame distorts the industry mix effect.
Strategies for missing data
• Ignore it
• Find an alternative source
• Estimate missing midpoint data with an average or
linear projection
• Use the proportion of the industry from a higher
level of geography
• Project the missing data based on regional growth
• Project the missing data based on national industry
growth
Comparing the 3 "Solutions" to missing data
Comparing the 3 "Solutions" to missing data
Complete Data
Incomplete Data
Partial Data
R
106,225
71,221
99,926
N
67,610
67,610
61,972
M
5,990
5,990
11,259
S
32,625
-2,379
26,695
For Construction
Complete Data
Incomplete Data
Partial Data
R
10,973
10,973
10,973
N
3,694
3,694
3,694
M
1,963
1,963
1,963
S
5,316
5,316
5,316
1 – estimate nondisclosed data
2 – ignore nondisclosed data or assume = 0
3 – exclude missing sectors entirely
Multipliers
• What is a multiplier?
– Based on industry input-output
• How do you use them correctly
– Change in final demand
– Substitution
– Total vs. direct vs. indirect jobs
• Sources
– RIMS II
– IMPLAN
– REMI