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Ec 596 Economic Research and Publication Office of Economic Analysis Josh Lehner Portland State University April 15, 2010
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Ec 596Economic Research and Publication
Office of Economic Analysis
Josh Lehner
Portland State University
April 15, 2010
2
Overview
• My Research Project– Origination, Plan, Analysis
• Presentation and Writing• Publication of Results• Advisor’s Role• What I Do• Future Research• Possible Project Ideas• State of the State (pending)
3
My Research Project
• Retail Sales Tax Discrepancy• Washington – Oregon; Portland – Vancouver
• Intuitively it should have an affect• Empirically does it?
• If so, what are the consequences?
• Panel Data• FE, Spatial
• Calculated fiscal impacts
4
Project Origination
• Previous employer – CREDC• How Vancouver fits into MSA
• PSU courses
• Regional/Urban Economics is interesting• Highly marketable
• Original idea: price point survey• Literature Review and Advisor changed my mind
• Broader, more macro level analysis
5
Plan and Design
• Idea
• Literature Review• Theoretical and Empirical
– Methodologies
• Find citation/reference but no paper – email author
• Read paper, if useful, write proper citation immediately– Download paper
• Short summaries combined into one larger file
• Don’t be intimidated by fancy math or what appears to be fancy math
6
Plan and Design (cont)
• Modify Idea as needed
• Specify model/equation with all possible variables (easier to downsize)
• Core and Choice Variables
• Identify needs, sources, descriptions
• Build Data Set
• Univariate, multivariate• Further methodological research, learning (Hausman)
• Statistical program learning
7
Misc. Data and Model
• Panel data• Need a set of items, data over time
– Countries, States, Counties, Firms– Balanced panel best (especially for spatial)– May be able to compute missing values – it depends
• Time Series or Cross Sectional• Index, Forecasting, VAR
• Don’t reinvent the wheel• Literature review helps formulate ideas
8
Summary of Project
9
Reexamining the Border Tax Effect:
A Case Study of Washington State
Rossitza Wooster & Josh Lehner
Prepared for PNREC
May 19th, 2009
10
Overview
• What is the Border Tax Effect?
• Previous Estimates
• Model
• Empirical Results
• Conclusion
11
What is the “Border Tax Effect”?
• Why it occurs:• Neighboring jurisdictions with different tax structures• Border residents purchase goods in lowest taxing
jurisdiction to avoid higher costs
• What it affects:• Governments’ tax revenue
– Public goods and services
• Societal welfare– Illegal tax evasion
• Other Issues• Political “3rd rail” in Northwest• Economic efficiencies (consumption tax)
12
Washington State
• No income tax
• Rely heavily on sales tax
• 20% of population lives in border counties
• Most regressive tax structure in nation (Institute of Taxation and Economic Policy, 2000)
6.0%7.5 – 9.5%
0.0%
13
Is there a Border Tax Effect?
• Washington’s border counties generate far less retail sales than their peers in both Washington and Oregon
Washington-Oregon Border : Real Per Capita Retail Sales
$0
$2,000
$4,000
$6,000
$8,000
$10,000
$12,000
$14,000
$16,000
1992 1997 2002 2007
OregonCounties
WashingtonCounties
14
Previous Estimations
• West Virginia – 1988• 2 Previous Washington studies
– Lorrie Jo Brown (1990)• 1975-1987 data
• Price elasticity -1.8 (SR), -2.4 (LR)
– John Beck (1992)• 1984-1988 data
• Legislative Changes
• Price elasticity between -2 and -3.2
• Other Examples: State-level analysis, Event studies, Alcohol taxes, Canada and E.U. (tax harmonization)
15
Data
• 39 Washington counties
• 15 years (1992-2006)
• 585 observations
• 9 final variables• Tried many more
• 5,265 data points in Fixed Effects model
16
The Model: VariablesVariable Type Description Expected Sign
Sales Dependent Real Per Capita Taxable Sales NA
Inc Standard Real Per Capita Personal Income +
Price Standard Home County Tax Rate Relative to Neighboring County Tax Rate
-
Border Standard Binary Indicator For Border Counties NA
Travel Standard Mileage Distance Between Counties, Adjusted By Gasoline Index
+
Unemp Control County Specific Unemployment Rate -
Youth Control Percentage of County 18 Years And Younger
+
Elderly Control Percentage Of County 65 Years And Older
-
RetailEst Control Retail Establishments Per 1,000 Population
+
17
Price Variable
• Prices Assumed To Be Equal In Competitive Market
• Measures Relative Price Of Goods• Key Variable: Sales Tax Effect• Expected Sign: -• Expected Range: -2 to -11
• Brown: -2.4
• Beck: -2.0 to -3.2
)1(
)1(
NN
HH
tP
tPprice
18
Travel Variable
• Distance Between County Seats• Exceptions (Brown): Eastern Washington
• U.S. Energy Information Administration• Controls For Cost Of Gasoline
• Expected Sign: +
2006GPI
GPIDistTravel t
19
Descriptive Statistics (Univariate)
VariableOverall Interior Counties Border Counties
Mean Std Dev Mean Std Dev Mean Std Dev
Sales*** 11,612 4,161 12,843 4,179 9,413 3,090
Inc*** 28,060 5,491 28,840 6,343 26,666 3,035
Price*** 1.020 0.031 1.002 0.002 1.059 0.024
Travel*** 67.424 52.519 95.245 45.231 17.742 13.310
Unemp 7.377 2.479 7.425 2.215 7.292 2.895
Youth*** 27.691 3.726 28.063 4.103 27.027 2.823
Elderly*** 14.078 3.700 13.680 3.432 14.790 4.047
RetailEst*** 3.680 1.132 3.880 1.188 3.315 0.921
N 663 663 375 210 585585 375 210
*** Difference-in-means test of interior versus border counties is significant at the 1% level
20
Model Specifications
• 4 Models: Fixed Effects & SAR, Semi-Log & Log
• 1992-2006
• Fixed Effects
• Spatial Autocorrelation
itcontrolit
itiititit
Xtravel
incomeborderpricepricesales
54
3210
ln
ln)*ln(ln
ititit MeasureSalesWVariablesDemandMeasureSales )(10
21
Spatial Specification
ititit MeasureSalesWVariablesDemandMeasureSales )(10
Rho – coefficient, check significance level
W * SalesMeasure – spatially lagged dependent variable
W – weighing matrix, row standardized, symmetric, queen contiguity
SalesMeasure – per capita sales
Epsilon – normal error term
22
342,225 Data Points in Matrix
23
Model (1): Semi-Log Specification; Dependent Variable = Salesit
Model (2): Double-Log Specification; Dependent Variable = ln(Sales)it
FE SAR FE SAR
Intercept-117,268.77 ***
(18,622)-110,203.90 ***
(17,438)-3.094 * (1.591)
-2.474(3.460)
Ln(Real, Per Capita Income) 10,048.16 ***
(1,003)10,048.162 ***
(951)0.856 *** (0.090)
0.856 *** (0.085)
Ln(County Relative Price)71,078.39 **
(32,193)71,078.41 ** (30,523)
6.730 *** (2.182)
6.730 *** (2.069)
Ln(CountyPrice*Border) -104,389.46 ** (40,371)
-104,389.48 *** (38,277)
-9.843 *** (3.397)
-9.843 *** (3.221)
Ln(Travel)2,455.59 *** (370)
181.04(163)
0.249 *** (0.035)
0.036 *
(0.019)
Ln(Unemployment Rate)-83.902(208)
-83.902(197)
0.028 (0.021)
0.028(0.020)
Ln(Youth Percentage)8,678.53 *** (2,748)
8,678.53 *** (2,605)
1.160 *** (0.265)
1.160 *** (0.251)
Ln(Elderly Percentage)-4,956.94 * (2,775)
-4,956.94 * (2,631)
-0.499 * (0.262)
-0.499 ** (0.249)
Ln(Retail Establishments)1,614.50 *** (471)
1,614.50 *** (447)
0.143 *** (0.048)
0.143 *** (0.046)
Spatially Weighted Retail Sales (W ∙ Sales Measureit)
3.80e-08 (0.339)
5.54e-08 (0.339)
Time Dummies Yes Yes Yes Yes
Number of Observations 585 585 585 585
R2 / Log-Likelihood 0.3547 -4742.84 0.3193 694.08
24
Price ElasticityModel (2): Double-Log Specification; Dependent Variable = ln(Sales)it
FE SAR
Intercept-3.094 * (1.591)
-2.474(3.460)
Ln(Real, Per Capita Income) 0.856 *** (0.090)
0.856 *** (0.085)
Ln(County Relative Price)6.730 *** (2.182)
6.730 *** (2.069)
Ln(CountyPrice*Border) -9.843 *** (3.397)
-9.843 *** (3.221)
Ln(Travel)0.249 *** (0.035)
0.036 *
(0.019)
Ln(Unemployment Rate)0.028 (0.021)
0.028(0.020)
Ln(Youth Percentage)1.160 *** (0.265)
1.160 *** (0.251)
Ln(Elderly Percentage)-0.499 * (0.262)
-0.499 ** (0.249)
Ln(Retail Establishments)0.143 *** (0.048)
0.143 *** (0.046)
Spatially Weighted Retail Sales (W ∙ Sales Measureit)
5.54e-08 (0.339)
Time Dummies Yes Yes
Number of Observations 585 585
R2 / Log-Likelihood 0.3193 694.08
• -3.113• Good, Expected Result
– Significant at 1% level
• Previous Literature: -2 to -11• Washington Studies:
– Brown, 1990: -1.8, -2.4– Beck, 1992: -2 to -3.2
• Why Larger?– Time Span Of Study– Consumer Behavior
• Internet
• Bargain Shopping
25
Price EffectModel (1): Semi-Log Specification; Dependent
Variable = Salesit
FE SAR
Intercept-117.268 ***
(18,622)-110,203 ***
(17,438)
Ln(Real, Per Capita Income)
10048 ***
(1,003)10,048 ***
(951)
Ln(County Relative Price)71,078. **
(32,193)71,078 ** (30,523)
Ln(CountyPrice*Border) -104,389 ** (40,371)
-104,389 *** (38,277)
Ln(Travel)2,455 *** (370)
181 (163)
Ln(Unemployment Rate)-83.902(208)
-83.902(197)
Ln(Youth Percentage)8,678 *** (2,748)
8,678 *** (2,605)
Ln(Elderly Percentage)-4,956 * (2,775)
-4,956 * (2,631)
Ln(Retail Establishments)1,614 *** (471)
1,614 *** (447)
Spatially Weighted Retail Sales (W ∙ Sales Measureit)
3.80e-08 (0.339)
Time Dummies Yes Yes
Number of Observations 585 585
R2 / Log-Likelihood 0.3547 -4742.84
• When Converting Units, A 1% Increase In The Tax Differential, Results In $333 Decrease In Per Capita Sales
• Following Brown and Beck
• Calculate “Lost” Sales And Revenue Due To The Border Tax Effect
26
“Lost” Sales And RevenueWith Full Tax Harmonization
County Total Taxable Retail Sales (2006)
Estimated Gain in Taxable Retail Sales
Estimated State Tax Revenue
Estimated Local Tax Revenue
Asotin $183,624,442 $6,614761 $429,959 $33,074
Benton $2,303,245,278 $404,105,660 $26,266,868 $4,849,268
Clark $4,866,777,344 $967,864,073 $62,911,165 $5,807,184
Columbia $29,770,738 $10,431,561 $678,051 $146,042
Cowlitz $1,337,394,181 $246,912,462 $16,049,310 $2,469,125
Garfield $15,899,676 $5,291,463 $343,945 $52,915
Klickitat $162,750,735 $46,204,117 $3,003,268 $231,021
Pacific $195,060,498 $53,466,762 $3,475,340 $534,668
Pend Oreille $89,831,028 $6,367,568 $413,892 $70,043
Skamania $87,112,482 $24,539,598 $1,595,074 $122,698
Spokane $7,278,765,098 $281,190,667 $18,277,393 $4,217,860
Wahkiakum $24,290,624 $9,865,906 $641,284 $98,659
Walla Walla $718,942,577 $153,521,385 $9,978,890 $2,302,821
Whitman $410,491,705 $23,420,572 $1,522,337 $304,467
Total $17,703,956,406 $2,239,796,555 $145,586,776 $21,239,844
27
“Lost” Sales And RevenueWith 1% Reduction in Tax Differential
CountyTotal TaxableRetail Sales
Estimated Gain in Taxable Retail Sales
Estimated State Tax Revenue
Estimated Local Tax Revenue
Asotin $183,624,442 $6,217,875 $404,162 $31,089
Benton $2,303,245,278 $52,481,255 $3,411,282 $629,775
Clark $4,866,777,344 $136,318,884 $8,860,727 $817,913
Columbia $29,770,738 $1,320,451 $85,829 $18,486
Cowlitz $1,337,394,181 $32,921,662 $2,139,908 $329,217
Garfield $15,899,676 $705,528 $45,859 $7,055
Klickitat $162,750,735 $6,600,588 $429,038 $33,003
Pacific $195,060,498 $7,128,902 $463,379 $71,289
Pend Oreille $89,831,028 $4,218,514 $274,203 $46,404
Skamania $87,112,482 $3,505,657 $227,868 $17,528
Spokane $7,278,765,098 $149,031,053 $9,687,018 $2,235,466
Wahkiakum $24,290,624 $1,315,454 $85,505 $13,155
Walla Walla $718,942,577 $19,190,173 $1,247,361 $287,853
Whitman $410,491,705 $13,792,115 $896,487 $179,297
Total $17,703,956,406 $434,748,110 $28,258,627 $4,717,530
28
Conclusion
• Purpose: Quantifiably Show Border Tax Effect In Washington State
• -3.11 Price Elasticity
• $145.6 Million In Lost State Revenue
• $21.2 Million In Lost Local Revenue
• Future Work• Internet Sales
• Washington Sales Tax Policy Changes
29
Presentation of Results
• Final Class(es) – all students
• Format – similar to what I just did, only better– Condensed version of paper
• Brief opening on issue
• Review of existing literature and issues
• Model specification
• Empirical results
• Conclusion and future work
• It’s been rumored that beverages calm the nerves
30
Writing Style
• Practice– Previous work experience– Literature review (other academic readings)
• Professional, careful edits– Proofread many, many times (take breaks - days)
• Proper citations (Harvard System)– Can always change for specific journal if needed
• Know your audience– Use proper jargon
• Elasticity, economies of scale, diminishing rate of return
31
Publication
• Long Process• Still not physically published – 20 months and counting
– October issue a possibly (26 months)
• Profs have multiple projects running at various stages
• Finished Project June 2008• Clean Graphics, Re-write/Edit• Submit Paper Sept 2008
• Contemporary Economic Policy• Upload to SSRN
• Wait• Mid-December, Journal designates “major revision”
• Not very good, but not horrible enough to throw out
32
Publication (cont)
• Through holiday break and into Jan and Feb worked evenings and weekends
• Respond to referee comments (3 referees, ~25 comments)• Learned Spatial analysis• Used county specific fixed effects
• Resubmit end of February 2009• Wait• Wait some more• Acceptance June 2009, no revision required• Administrative issues (forms, copyright release)• Online “sneak peek” January 2010• Physical publication possibly in October 2010
33
Role of Advisor
• Help cultivate ideas (sounding board)
• Help sort literature that is relevant• Discard tangential papers
• Don’t be afraid to ask questions• Don’t need to understand everything in a paper at first
• Help understand data issues and methodology• Also, statistical programs
• Help with edits, clarification of thoughts
• Provide honest critique, constructive criticism
34
What do I do?
• Oregon Office of Economic Analysis• Forecast economy, tax revenues, population, prisons,
highway cost allocation study
• Oregon Economic Model• Personal income, employment, housing
• Oregon Index of Leading Indicators• Oregon Dollar Index
• Export Markets (International developments)
• Western U.S. states
35
My Future “Fun” Research
• Micro– Firm/Item level retail sales
• Indexes for retail environment over time
• Identify market opportunities/vulnerabilities
• Market structure
• Macro– Border Tax Effect
• U.S. Economic Census data
• Both sides of the river
• Do results hold up?
36
Economic Census
• How do results compare?
• Simulations of tax changes
Washington-Oregon Border : Real Per Capita Retail Sales
$0
$2,000
$4,000
$6,000
$8,000
$10,000
$12,000
$14,000
$16,000
1992 1997 2002 2007
OregonCounties
WashingtonCounties
37
Research Projects – 2008
• Hedonic Models– Urban Amenities
• Johnson Reid
– Energy Star• Energy Trust of Oregon
• Survey – Discount Rate
• Voting Behavior– Same-sex marriage
• Non-empirical– Voting
– Corporations
38
Possible Research Projects
• Economic Activity Indexes– Leading, Coincident, Lagging
• Regional
• Unemployment Rate Analysis
39
Economic Activity Indexes
• The Conference Board• Methodology
• DSFM Program– State Coincident Indexes (Philly Fed)– Alan Clayton-Matthews
• http://users.rcn.com/alancm/dsfm/index.html
• Dallas Federal Reserve– Texas Metro Indexes
• Oregon– OILI – Oregon Office of Economic Analysis– UO Index – Tim Duy, University of Oregon
40
Leading Indicators10 of 11 Indicators are Positive
Oregon Index of Leading Indicators(Six-Month Annualized Percent Change, through February 2010)
-30%
-20%
-10%
0%
10%
20%
30%
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010-10.0%
-6.7%
-3.3%
0.0%
3.3%
6.7%
10.0%
Leading Index (Left Axis) Diffusion Index <50 Nonfarm Employment (Right Axis)
Recession in Oregon
41
Oregon Dollar IndexOregon Dollar index
70
85
100
115
130
145
160
175
190
Jan-95 Jan-96 Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10Time
Oregon dollar index Fed weighted exchange index
42
Oregon IndexesOregon Indexes of Leading Indicators
(Six Month Annualized Percent Change, through February 2010)
-30.0%
-20.0%
-10.0%
0.0%
10.0%
20.0%
30.0%
Jan
-97
Jan
-98
Jan
-99
Jan
-00
Jan
-01
Jan
-02
Jan
-03
Jan
-04
Jan
-05
Jan
-06
Jan
-07
Jan
-08
Jan
-09
Jan
-10
-10.0%
-6.7%
-3.3%
0.0%
3.3%
6.7%
10.0%
OEA UO Index Total Nonfarm Employment (R)
43
Recession Probability(through February 2009)
Program Source: Prof. Jeremy Piger, Univ of Oregon
Oregon Probability of Recession
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jan-
90
Jan-
91
Jan-
92
Jan-
93
Jan-
94
Jan-
95
Jan-
96
Jan-
97
Jan-
98
Jan-
99
Jan-
00
Jan-
01
Jan-
02
Jan-
03
Jan-
04
Jan-
05
Jan-
06
Jan-
07
Jan-
08
Jan-
09
Jan-
10
1,200
1,300
1,400
1,500
1,600
1,700
1,800
Probability of Recession (L) Oregon Nonfarm Employment (R)
44
Pros and Cons
• Strengthen Time Series abilities• Leading forecasts Coincident which forecasts Lagging
• Learn a new program (DSFM)• Use a Gauss program designed by the Fed
• Rewrite for other platform(s)?
• Customize for region• People would use it
• Publishable? Probably not• May not involve a regression…
45
Unemployment Rate Analysis
• Oregon consistently has a high rate – Why?– Migration – “The young and the restless”
– Unemployment Compensation
– Seasonality in Employment
– JOLT/BED data• “Churn”
– Industry Mix• Durable Manufacturing
– Wood Products, High Technology
– Exports
46
Unemployment Rates
0
2
4
6
8
10
12
14
1976 1980 1984 1988 1992 1996 2000 2004 2008
0
5
10
15
20
25
30
35
U.S Unemp Rate
Oregon Unemp Rate
Oregon Rank (R)
47
Unemployment Benefits
• Generous benefits?• Duration of the unemployment?• Industry mix?
UI Benefits Paid (Jan 2005 - Mar 2010)
$0
$50,000,000
$100,000,000
$150,000,000
$200,000,000
$250,000,000
$300,000,000
$350,000,000
Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Jul-09 Jan-10
Total
Regular Program
48
Employment Turnover
Employment "Churn" (1992 - 2009 Q2)
10%
12%
14%
16%
18%
20%
22%
1992Q1 1994Q1 1996Q1 1998Q1 2000Q1 2002Q1 2004Q1 2006Q1 2008Q1
Per
cen
t o
f P
riva
te E
mp
loym
ent
eith
er G
ain
ing
or
Lo
sin
g a
Jo
b U.S.
Oregon
49
Employment Turnover
Employment "Churn" (1992 - 2009 Q2)
12
13
14
15
16
17
18
19
20
21
22
1992Q1 1994Q1 1996Q1 1998Q1 2000Q1 2002Q1 2004Q1 2006Q1 2008Q1
California IdahoNevada OregonUnited States Washington
50
Seasonality in Employment
0.920
0.940
0.960
0.980
1.000
1.020
1.040
1.060
1.080
1.100
Jan-90 Jan-91 Jan-92 Jan-93 Jan-94 Jan-95 Jan-96 Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09
Alaska Idaho Oregon US
51
What Not To Do
52
Oregon Exports
Oregon Exports by Industry
2008 Q4 2009 Q4Y/Y % Change
Total All Industries 4,237.9 4,374.9 3.2%
Computer And Electronic Products 1,805.1 1,995.3 10.5%
Agricultural Products 543.6 712.6 31.1%
Machinery, Except Electrical 301.2 333.8 10.8%
Chemicals 420.9 289.0 -31.3%
Transportation Equipment 245.4 211.7 -13.7%
Waste And Scrap 79.7 112.5 41.1%
Primary Metal Manufacturing 168.3 101.9 -39.5%
Food And Kindred Products 94.2 108.2 14.9%
Wood Products 96.1 94.6 -1.5%
Paper 103.9 60.9 -41.4%
Oregon's Total Exports (1Q 1997 - 4Q 2009, current dollars)
0.0
1,000.0
2,000.0
3,000.0
4,000.0
5,000.0
6,000.0
Q1
19
97
Q3
19
97
Q1
19
98
Q3
19
98
Q1
19
99
Q3
19
99
Q1
20
00
Q3
20
00
Q1
20
01
Q3
20
01
Q1
20
02
Q3
20
02
Q1
20
03
Q3
20
03
Q1
20
04
Q3
20
04
Q1
20
05
Q3
20
05
Q1
20
06
Q3
20
06
Q1
20
07
Q3
20
07
Q1
20
08
Q3
20
08
Q1
20
09
Q3
20
09
($ m
illi
on
)
-40.0
-30.0
-20.0
-10.0
0.0
10.0
20.0
30.0
40.0
(% c
ha
ng
e)
Year-over-year percent change(right scale)
Total Exports(left scale)
5353
Exports by Industry
Oregon Exports by Major Industry(1Q 1997 - 4Q 2009, current dollars)
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
2,200
2,400
Q1 1997
Q3 1997
Q1 1998
Q3 1998
Q1 1999
Q3 1999
Q1 2000
Q3 2000
Q1 2001
Q3 2001
Q1 2002
Q3 2002
Q1 2003
Q3 2003
Q1 2004
Q3 2004
Q1 2005
Q3 2005
Q1 2006
Q3 2006
Q1 2007
Q3 2007
Q1 2008
Q3 2008
Q1 2009
Q3 2009
($ m
illi
on
)
Computer And Electronic Products
Agricultural Products
Machinery, Except Electrical
Chemicals
Transportation Equipment
Source: WISERTrade
5454
Exports to China
Oregon Export Markets (1997 - 2009)
0
2
4
6
8
10
12
14
16
18
20
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Vo
lum
e ($
bill
ion
)
All Other China
0.8% 1.4%
1.4%
2.7%
5.1%
6.8% 5.6%7.1%
6.5%
9.1%8.7%
12.8%
19.9%
Source: WISERTrade
55
Pros and Cons
• Huge Panel Data Set (FE, RE, Spatial)• Socio/Economic Factors (age, sex, education, etc)
• Industry Mix, Seasonality
• Unemployment Benefits, Avg Duration
• Public Expenditures (education, health, etc)
• Extremely useful to policymakers, public, me
• Large existing literature
• Publishable? Possibly, depending upon model
• Forecast? VAR is standard method
56
Other Research Possibilities
• County data – tourism, voting• Airport statistics (Fuel, recessions, income growth, +/- airlines)• Seasonal factors• Migration – Drivers Licenses, IRS• Indexes – Oregonian, Home Prices• LAUS v CES v Benchmarking• Prisons, Crime• Tobacco Consumption• ARRA impacts?• Cluster Analysis – Athletic Apparel in Portland• Sporting events attendance demand model• Transfer fees, player salaries (inequality)• CEO “union”• International Trade – elasticities, products, cross-sectional data?
57
Contact Information
(503) 378-4052
www.oregon.gov/das/oea
oregoneconomicanalysis.wordpress.com
twitter.com/OR_EconAnalysis
58
State of the State
59
The U.S. Economy in Recovery
• Financial crises generally do not lead to V-shaped recoveries
• What will take the place of fading fiscal stimulus and the inventory cycle
• Consumers remain cautious, weakening the strength of the recovery
• Employers are expected to begin hiring soon
• Tax revenues are down sharply, forcing tough decisions for local, state and federal governments
Copyright © 2010 Global Insight, Inc.
60
-8
-6
-4
-2
0
2
4
6
8
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
3
4
5
6
7
8
9
10
11
Real GDP Growth Unemployment Rate
(Annual percent change, 2005 dollars) (Percent)
Unemployment Rises as the Economy Contracts
Copyright © 2010 Global Insight, Inc.
61
U.S. Recession Employment Losses
-7.0%
-6.0%
-5.0%
-4.0%
-3.0%
-2.0%
-1.0%
0.0%
1.0%
0 3 6 9
12
15
18
21
24
27
30
33
36
39
42
45
48
51
54
57
60
63
Number of Months from NBER Peak
% f
rom
NB
ER
Pe
ak
1948 19531957 19601969 19731980 19811990 20012007 Recovery
Employment Losses (through March 2010)
20011990
1981
1973
1953
62
2007 2008 2009 2010 2011
Real GDP 2.1 0.4 -2.4 3.0 3.0
Consumption 2.6 -0.2 -0.6 2.4 2.7
Residential Investment -18.5 -22.9 -20.5 0.8 27.5
Bus. Fixed Investment 6.2 1.6 -17.8 1.7 7.6
Federal Government 1.3 7.7 5.2 3.8 -2.5
State & Local Govt. 2.0 0.5 -0.2 -1.2 0.4
Exports 8.7 5.4 -9.6 11.9 7.8
Imports 2.0 -3.2 -13.9 10.2 7.9
(Percent change)
U.S. Economic Growth by Sector
Copyright © 2010 Global Insight, Inc.
63
2007 2008 2009 2010 2011
Industrial Production 1.5 -2.2 -9.7 5.1 4.7
Payroll Employment 1.1 -0.6 -4.3 -0.5 1.8
Light Vehicle Sales (Millions) 16.1 13.2 10.3 11.8 13.8
Housing Starts (Millions) 1.34 0.90 0.55 0.67 1.19
Consumer Price Index 2.9 3.8 -0.3 1.9 2.0
Core Consumption Deflator 2.3 2.3 1.7 1.2 1.9
Federal Funds Rate (%) 5.0 1.9 0.2 0.2 1.7
10-Year Treasury Yield (%) 4.6 3.7 3.3 3.9 4.1
(Percent change unless noted)
Other Key U.S. Indicators
Copyright © 2010 Global Insight, Inc.
64
(Year-over-year percent change)
-4
-2
0
2
4
6
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
All-Urban CPI Core CPI Employment Cost Index
Food and Energy Prices Swing Consumer Price Inflation
Copyright © 2010 Global Insight, Inc.
65
0
20
40
60
80
100
120
140
1998 2000 2002 2004 2006 2008 2010 2012
0
2
4
6
8
10
12
14
Crude Oil (Left scale) Natural Gas (Right scale)
($/barrel, WTI) ($/million Btu, Henry Hub)
A Sharp Retreat in Oil and Gas Prices
Copyright © 2010 Global Insight, Inc.
66
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1976 1980 1984 1988 1992 1996 2000 2004 2008 2012
Major Trading Partners Other Important Trading Partners
(Real Trade-Weighted Dollar Index, 2005=1.0)
U.S. Dollar Recovered Briefly
Copyright © 2010 Global Insight, Inc.
67
Risks to the Forecast
Pessimistic (20% Probability):
• Inventory cycle and stimulus fade, no sustained expansion
• Home prices, starts, sales, and construction fall more sharply
• A true double-dip recession in which Real GDP falls again
Optimistic (20% Probability):
• Financial rescue and fiscal stimulus plans gain traction
• Business investment and exports show more robust growth
• Housing and consumer markets rebound more quickly
Copyright © 2010 Global Insight, Inc.
6868
-8
-6
-4
-2
0
2
4
6
8
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Baseline (60%) Pessimistic (15%) Optimistic (25%)
(Percent change, annual rate)
Real GDP Growth in Alternative Scenarios
Copyright © 2010 Global Insight, Inc.
6969
Bottom Line
• The technical recession in the U.S. ended during the summer, with the unemployment rate toping out at 10.1% in the fourth quarter of 2009. The labor market will remain weak with unemployment averaging 9.6% in 2010.
• Credit markets are slowly returning to pre-Lehman collapse days but risk premiums are still present.
• The housing market will continue to remain fragile. Housing starts marginally improved in the second half of 2009 off their historic lows. Prices will decline into 2010.
• Inflation is not a threat today or even next year but the stage is set for carefully executed exit strategies to avoid inflation in the future.
• Economic growth returned in the third quarter and the fourth quarter saw strong growth, but it will remain below potential throughout 2010.
• With furlough days and reduced weekly hours, employment gains will lag the recovery – another “jobless” recovery.
Copyright © 2009 Global Insight, Inc. Office of Economic Analysis
70
Oregon
71
• 10.6% unemployment rate for March 2010 (Mar US rate is 9.7%) is up from the latest lowest rate of 5.0% in April 2007 and down from the highest rate of 11.6% in May and June 2009.
• 35th fastest job growth at -3.03% for all states for February 2010 over February 2009.
• Total nonfarm employment dropped -5.7% year-over-year for the 4th quarter of 2009. Job losses (S.A.) from February 2008 to December 2009 (up 1,000 in January). The last six months’ losses averaged 3,250 per month versus 10,017 per month over the first six months of 2009.
• -0.1% personal income growth for 4th quarter of 2009 over 4th quarter of 2008. Annualized 4th quarter 2009 growth at 3.8%.
• Oregon exports increased 3.2% in the 4th quarter compared to the same period last year but finished 2009 down 23% over 2008. (Export growth is positive Q/Q and is expected to follow the global economy)
Recent Oregon Economy Facts
72
End of Recession in Oregon?
• The recession in Oregon either ended this summer or is close to ending– the Oregon economy generally follows the US economy – the Oregon Index of Leading Indicators (OILI) has been increasing
the past eight months (July - February) – other economic indicators, the University of Oregon Leading Index
and the Philadelphia Federal Reserve State Coincident Index, are generally following the trend of the OILI;
– the Oregon unemployment rate has stabilized since mid-2009– the job loss rate in the state has greatly slowed since last April– Average weekly work hours in manufacturing have recently
increased but still below expansion periods. – signs of improving conditions at publicly traded companies in
Oregon show improvements in stock prices. • Expecting a “jobless” recovery.
73
0 100 200 300 400 500 600 700 800
Energy
Housing
Community Services
Workforce
Natural Resources
Public Safety
Transportation
Health & Human Services
Education
Employment
Millions
Funds Awarded
Funds Expended
Oregon and ARRA
Oregon’s spending allotment is $3.9 billion, plus tax relief measures. Through December 31st, $2.5 billion has been awarded with $1.7 billion spent.
Source: www.oregon.gov/recovery
74
Labor Force Growth(through February 2010)
Seasonally Adjusted (Index Jan 1990 = 100)
95
100
105
110
115
120
125
130
135
140
Jan
-90
Jan
-91
Jan
-92
Jan
-93
Jan
-94
Jan
-95
Jan
-96
Jan
-97
Jan
-98
Jan
-99
Jan
-00
Jan
-01
Jan
-02
Jan
-03
Jan
-04
Jan
-05
Jan
-06
Jan
-07
Jan
-08
Jan
-09
Jan
-10
OR Labor Force
US Labor Force
OR Emp
US Emp
75
Unemployment Rate by Region, January 2010(Not seasonally adjusted for counties)
Source: Oregon Employment Department Office of Economic Analysis
10.6%
11.7%12.2%
14.4%15.1% 12.5%
Oregon: 11.8% (seasonally adjusted: 10.7%)U. S.: 10.6% (seasonally adjusted: 9.7%)
76
Historical Comparison
Recession 1981-82 1980-82 1990-91 2001 2008-?? *
U.S. Oregon U.S. Oregon U.S. Oregon U.S. Oregon
Employment
Loss (in 000s) 2,734.3 123.3 1,498.3 12.3 2,657.3 60.1 7,020.3 150.2
% Change (2.99) (11.50) (1.37) (0.97) (2.01) (3.69) (5.09) (8.64)
Duration
Peak-to-Trough 5 Qtrs 12 Qtrs 5 Qtrs 3 Qtrs 9 Qtrs 10 Qtrs 8 Qtrs 8 Qtrs
Return to Peak 8 Qtrs 28 Qtrs 10 Qtrs 5 Qtrs 15 Qtrs 16 Qtrs 20 Qtrs 24 Qtrs
* Estimates based on Global Insight and OEA forecasts
77
Historical Comparison(through February 2010)
Oregon Employment Loss by Recession
-12%
-10%
-8%
-6%
-4%
-2%
0%
0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
Number of Months from Employment Peak
% J
ob
Lo
ss f
rom
Pea
k E
mp
loym
ent
1948 1953 19571960 1969 19731980 1990 20012007 Recovery
19731969 1960 1948
19531990
2001 1980
78
1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
1,700,000
1,800,000
1,900,000
1990Q1 1992Q1 1994Q1 1996Q1 1998Q1 2000Q1 2002Q1 2004Q1 2006Q1 2008Q1 2010Q1 2012Q1 2014Q1
Oregon’s Lost Decade?
2000 Q11,605,857
2003 Q21,567,494
2010 Q11,588,089
2010 Q41,602,375
2008 Q11,738,243
2000 Q41,627,407
79
Signs of Life(1st Quarter 2010)
Nat. Resources
Construction
Wood Products
Metals & Machinery
Electronics
Trans. Equipment
Food
Retail TradeWholesale Trade
T/W/Util
Information
Finance
Prof. & Bus. Services
Educational Services
Health Services
Leisure & Hospitality
Govt excl Education
Public Education
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
-20% -15% -10% -5% 0% 5% 10%Year-over-year % change
Qtr-
to-q
tr %
chan
ge
Contracting Newly Slowing
Newly Expanding Expanding
80
Initial ClaimsOregon
Unemployment Benefit Initial Claims (1st week 2002 - Mar 27, 2010)
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000
22,000
2002 2003 2004 2005 2006 2007 2008 2009 2010
4-Week Moving Average
Raw
81
Initial Claims(through February 2010)
Initial Claims per 1,000 Labor Force (SA)
0
1
2
3
4
5
6
7
1987M01 1989M01 1991M01 1993M01 1995M01 1997M01 1999M01 2001M01 2003M01 2005M01 2007M01 2009M01
Oregon
U.S.
82
Housing Starts: Oregon & U.S.
Office of Economic Analysis
Housing Starts Index (1973-2007 Average = 100)
0
50
100
150
200
1973
Q1
1975
Q1
1977
Q1
1979
Q1
1981
Q1
1983
Q1
1985
Q1
1987
Q1
1989
Q1
1991
Q1
1993
Q1
1995
Q1
1997
Q1
1999
Q1
2001
Q1
2003
Q1
2005
Q1
2007
Q1
2009
Q1
2011
Q1
2013
Q1
2015
Q1
U.S. (1.55 million)
Oregon (21,200)
Oregon (December GI)
Previous Oregon Forecast
83
Oregon Housing Permits(through February 2010)
Oregon Housing Permits (Monthly, SA 3 MMA)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
Jan
-90
Jan
-91
Jan
-92
Jan
-93
Jan
-94
Jan
-95
Jan
-96
Jan
-97
Jan
-98
Jan
-99
Jan
-00
Jan
-01
Jan
-02
Jan
-03
Jan
-04
Jan
-05
Jan
-06
Jan
-07
Jan
-08
Jan
-09
Jan
-10
Total Permits
Single Family
84
Mortgage Loans
• 6.88 percent of all loans past due (4th Quarter, 2009)– 2001 peak 3.72%, rising since early 2007
– Oregon ranks 8th best nationally (US average is 10.44%)
• 2.98 percent of all loans in foreclosure (4th Quarter, 2009)– Higher than 2002 (1.34%) and rising since late 2006
– Oregon ranks 25th best nationally (US average is 4.58%)
• Combined 9.86 percent ranks 10th best nationally– US average is 15.02 percent
Source: Mortgage Broker’s Association
85
Oregon was Late to the Run Up in Prices (Jan 2005 - Dec 2009)
Source: LoanPerformance
Housing Price Index(12-month percentage changes)
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
50%
DEC-09JUN-09DEC-08JUN-08DEC-07JUN-07DEC-06JUN-06DEC-05JUN-05
Oregon CaliforniaWashington IdahoArizona Nevada
CA
NV
ID
AZ
OR
WA
86
-25
-20
-15
-10
-5
0
5
10
15
20
25
30
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Selected State and US House Price Appreciations
Source: Federal Housing Finance Agency
Annual Percentage Change in FHFA House Price Indexes through 2009 Q4
CaliforniaWashington
Oregon
US
87
(20)
(15)
(10)
(5)
0
5
10
15
20
25
30
35
40
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Selected Oregon MSA House Price Appreciations
Annual Percentage Change in FHFA MSA House Price Indexes through 2009 Q4
Source: Federal Housing Finance Agency
Medford
PDX-Vanc-Bevrtn
Bend
Salem
Eugene-Springfield
88
Risks to the Forecast…
Downside • Double Dip in Housing• Higher Oil Prices• Premature Policy Tightening• After Shocks from the Financial Crisis• China Bubble?
Upside• V-Shaped Recovery in Other Parts of the World• Quicker, Stronger Release of Pent-up Demand• Stronger Growth in Total Factor Productivity
Upside – Downside?• Passage of Measures 66 and 67• Health Care Reform
89
Bottom Line for the Oregon Economy
• The “technical” recession in Oregon ended late summer or late 2009. Expect a “jobless” recovery.
• Job losses will continue into the first quarter of 2010, with only mild job growth the rest of the year.
• Housing prices may still decline into 2010 but looking more like a bottom has been reached in housing permits.
• Housing will not lead during the recovery. First sectors likely to come back: profession and business services, health care services, computer and electronic products, retail.
90
Contact Information
(503) 378-4052
www.oregon.gov/das/oea
oregoneconomicanalysis.wordpress.com
twitter.com/OR_EconAnalysis
