Competitive Pressure and the Decline of the Rust Belt Simeon Alder1
David Lagakos2 1 Notre
Dame
2 UCSD
and NBER
3 UCLA
and NBER
January 19, 2017
Lee Ohanian3
The Rust Belt
. . . or, as of November 8, 2016 . . .
Four Facts About Rust Belt Since WW II 1. Rust Belt share of economic activity declined slowly & persistently
2. Rust Belt wages substantially higher than average after end of WW II
3. Weak productivity growth in Rust Belt industries
4. In 1980s, Rust Belt decline slowed, wage premia declined & productivity growth increased
Our Theory ◮
Theory explores two channels of Rust Belt’s decline: 1. lack of competition and inefficient rent sharing in labor markets (where unions have ability to hold up firms) 2. effect of foreign competition in product markets on aggregate innovation
Our Theory ◮
Theory explores two channels of Rust Belt’s decline: 1. lack of competition and inefficient rent sharing in labor markets (where unions have ability to hold up firms) 2. effect of foreign competition in product markets on aggregate innovation
◮
Lack of competition in labor markets + pro-growth effect of international trade ⇒ depresses innovation in Rust Belt compared to “Rest of Country”
Our Theory ◮
Theory explores two channels of Rust Belt’s decline: 1. lack of competition and inefficient rent sharing in labor markets (where unions have ability to hold up firms) 2. effect of foreign competition in product markets on aggregate innovation
◮
Lack of competition in labor markets + pro-growth effect of international trade ⇒ depresses innovation in Rust Belt compared to “Rest of Country”
◮
Economic activity shifts to region with faster productivity growth
Related Literature
◮
Competition and productivity: Acemoglu & Akcigit (2011), Bloom, Draca and Van Reenan (2011), Cole & Ohanian (2004), Aghion et al (2005), Holmes (1998), Holmes & Schmitz (2010), Herrendorf & Texeira (2011), Schmitz (2005), Parente & Prescott (1999), Pavcnik (2002), . . .
◮
Unions and economic performance: Holmes (1998), Taschereau-Dumouchel (2012), Bridgman (2011), Dinlersoz and Greenwood (2012), Acikgoz and Kaymak (2012)
◮
Rust Belt; Blanchard & Katz (1992), Feyrer, Sacerdote and Stern (2007), Glaeser and Ponzetto (2007), Yoon (2012)
This Talk
1. Four facts + evidence for lack of competition 2. Model 3. Quantitative analysis
1. Four facts + evidence for lack of competition 2. Model 3. Quantitative analysis
.25
Rust Belt Employment Share .3 .35 .4 .45 .5
.55
Rust Belt Employment Share Declined
1950
1960
1970
1980
Aggregate Aggregate, excluding Sun Belt
1990
2000
Manufacturing
1.00
1.05
Relative Wage 1.10
1.15
1.20
Rust Belt Wages High
1950
1960
1970 Simple Ratio
1980
1990 With Controls
2000
Rust Belt Productivity Growth Low Labor Productivity Growth in Rust Belt Industries Annualized Growth Rate, % 1958-1985
1985-1997
1958-1997
Blast furnaces, steelworks, mills
0.9
7.6
2.8
Engines turbines
2.3
2.9
2.5
Iron and steel foundries
1.5
2.3
1.7
Metal forgings/stampings
1.5
2.8
1.9
Metalworking machinery
0.9
3.5
1.6
Motor vehicles/equipment
2.5
3.8
2.9
Photographic equipment/supplies
4.7
5.1
4.9
Railroad locomotives/equipment
1.6
3.1
2.0
Screw machine products
1.2
1.1
1.2
Rust Belt weighted average
2.0
4.2
2.6
Manufacturing weighted average
2.6
3.2
2.8
Rust Belt was Technological Laggard
◮
◮
Autos, steel, rubber did not adopt latest technologies: ◮
National Academy of Sciences: producers did not adopt long-available technologies
◮
McKinsey productivity studies: lagging technologies
◮
Literature comparing productivity to other countries: US producers were behind others
Frequently cite bad labor relations as important factor
Lack of Competition in Labor Markets
◮
Many Rust Belt industries had powerful unions (UAW, USW,...)
◮
Industry studies: earned rents through hold up/strikes
◮
◮
steel strikes of 1950s
◮
GM strike of 1970, Caterpillar strikes
◮
Bridgestone/Firestone recalls
Broad agreement that union power declined in 1980s Work Stoppages
Conflicted Labor Relations and Inefficient Rent Sharing
◮
Big literature concludes inefficient rent sharing in Rust Belt
◮
Producers and unions agree with this conclusion, in colorful language, on occasion:
Conflicted Labor Relations and Inefficient Rent Sharing
◮
Big literature concludes inefficient rent sharing in Rust Belt
◮
Producers and unions agree with this conclusion, in colorful language, on occasion: ◮
”We are tired of fighting with these bast****.”
◮
”UAW did not trust employers, they were our adversaries.”
◮
”Management refuses to show us the books.”
◮
”When profitable, we accept union demands & recoup with higher prices. Strikes risk ruining the company.”
◮
”We went on strike because we didn’t trust what they told us.”
Inefficient Rent Sharing and Low Productivity Growth Literature emphasizes that labor conflicts contribute to low investment and productivity: ◮
National Academy of Sciences: collective bargaining contracts that grew from adversarial and bitter relationships negatively affected technology and innovation
◮
Census Bureau: Bad labor relations negatively affect productivity and costs
◮
Literature comparing US to Japan: High U.S. costs reflect bad labor relations
◮
President of Germany’s auto union: German workers don’t strike. American unions are destructive because of a hostile environment. American unions can’t be constructive if their as*** are always getting kicked.
(Lack of ?) Competition in Output Markets International Trade
◮
Low import-to-GDP ratios until 1980s, followed by gradual rise
◮
Rust Belt industries (marginally) less “exposed” in 1950 than manufacturing elsewhere, but imports rise more rapidly
(Lack of ?) Competition in Output Markets International Trade & FDI
◮
Low import-to-GDP ratios until 1980s, followed by gradual rise
◮
Rust Belt industries (marginally) less “exposed” in 1950 than manufacturing elsewhere, but imports rise more rapidly
◮
Limited FDI pre-1980s, followed by uptick in traditional Rust Belt industries outside Great Lakes region: ◮
Japanese, German, Korean auto manufacturers in SC, TN, AL, KY, TX,. . .
◮
Minimills in GA, FL, AL, TN,. . .
(Lack of ?) Competition in Output Markets International Trade & FDI
◮
Low import-to-GDP ratios until 1980s, followed by gradual rise
◮
Rust Belt industries (marginally) less “exposed” in 1950 than manufacturing elsewhere, but imports rise more rapidly
◮
Limited FDI pre-1980s, followed by uptick in traditional Rust Belt industries outside Great Lakes region:
◮
◮
Japanese, German, Korean auto manufacturers in SC, TN, AL, KY, TX,. . .
◮
Minimills in GA, FL, AL, TN,. . .
Is rise of imports/FDI cause or consequence of decline?
1. Four facts + evidence for lack of competition 2. Model 3. Quantitative analysis
Households
◮
Economy populated by unit measure of individuals
◮
Labor supply inelastic
◮
Individuals have linear preferences and discount future consumption: ∞ X δ t Ct t=0
Final Good ◮
Final good produced from continuum of intermediates indexed by i (industry), j (variety), and origin: Yt =
Z
1
yt (i)
σ−1 σ
0
yt (i) =
Z
0
where
∗
1
yt (i, j)
σ σ−1 di
ρ−1 ρ
dj +
Z
0
1
yt∗ (i, ˜)
ρ−1 ρ
ρ ρ−1 d˜ ,
denotes varieties produced abroad
◮
Final output consumed or used for investment
◮
Intermediates are gross substitutes in production and ρ>σ>1
Intermediate Goods
◮
Industries i ∈ [0, λ) located in Rust Belt (R)
◮
Industries i ∈ [λ, 1] located in Rest-of-Country (S)
◮
Competition in labor markets varies by region (captured by time-varying union bargaining power βt )
Intermediate Goods
Each intermediate firm (producing variety j in industry i) has access to production and innovation technologies. 1. Production is linear in labor: yt = zt · ℓt 2. By investing C x, z, Z units of the final good, firm can enhance idiosyncratic productivity by 100 · x percent next period: zt+1 = zt (1 + xt )
International Trade
◮
Intermediate varieties are tradable between US and Rest-of-World
◮
International trade in intermediates is subject to time-varying (symmetric) iceberg costs τt ≥ 1
◮
Final goods and labor are non-tradable internationally
◮
Trade is balanced period-by-period
Labor Markets
◮
Labor market competitive in Rest-of-Country
◮
Rust Belt labor market governed by union
◮
Individual worker’s union status denoted by υ ∈ {0, 1} and unionization rate in economy denoted by U ∈ [0, 1]
◮
Workers retire with probability ζ each period (regardless of union status)
◮
Access to Rust Belt jobs restricted to union members
◮
Non-members can apply for vacant Rust Belt jobs and new union members are selected randomly from applicant pool
Union
◮
Union bargains with (individual) Rust Belt producers over profits
◮
Protocol is Nash with time-varying bargaining weight βt
◮
Results robust to alternative protocols (e.g. micro-founded take-it-or-leave-it bargaining) TIOLI
Dynamic Model Exogenous State Variables
◮
Two exogenous state variables: 1. union bargaining power β ≥ 0 2. iceberg trade cost τ ≥ 1
◮
Exogenous state follows a Markov process:
(βH , τH ) (βL , τL )
◮
(βH , τH )
(βL , τL )
1−ǫ 0
ǫ 1
βH > βL and τH > τL , by assumption
Dynamic Model Aggregate Endogenous State Variables
◮
Aggregate unionization rate U with law of motion: U ′ = (1 − ζ) U + M F (1 − U )
◮
1 1 Set of productivities Z ≡ z(i, j) i,j=0 ∪ z ∗ (i, j) i,j=0 with law of motion: Z ′ = Z × (1 + X)
Dynamic Model Idiosyncratic Endogenous State Variables
◮
Intermediate firm’s productivity z(i, j) with law of motion: z ′ (i, j) = z(i, j) 1 + x(i, j)
◮
Worker’s union status υ with following law of motion: ◮
◮
If υ = 1, then
If υ = 0, then
υ′ =
(
υ′ =
(
1 with probability 1 − ζ, 0 otherwise 1 with probability f (1 − ζ) if R, 0 with probability 1 − f if R or if S
Intermediate Firms’ Static Problem (Production) ◮
Individual producer indexed by i (industry) and j (variety): n o Π Z, U, z(i, j); β, τ = max p(i, j)·y(i, j)−n(i, j) , p(i,j), n(i,j), y(i,j)
subject to
y(i, j) = z(i, j) · n(i, j) y(i, j) = P (Z, U ; β, τ )σ−1 P (i; Z, U ; β, τ ) ρ−σ {z } | {z } | agg. price index
ind. price index
· X(Z, U ; β, τ ) p(i, j)−ρ {z } | agg. expenditures
◮
Profit-maximizing price is Dixit-Stiglitz markup: p(i, j) =
ρ −1 ρ−1 z(i, j)
Intermediate Firms’ Dynamic Problem (Innovation) In the Rest-of-Country: V S (Z, U, zS ; β, τ ) = maxxS >0
In the Rust Belt:
n
ΠS (Z, U, zS ; β, τ )
−P (Z, U ; β, τ ) · C(xS , zS , Z) h io +δE V S (Z ′ , U ′ , zS′ ; β ′ , τ ′ ) ,
V R (Z, U, zR ; β, τ ) = maxxR >0 {(1 − β)ΠR (Z, U, zR ; β, τ ) −P (Z, U ; β, τ ) · C(xR , zR , Z) io h ′ ′ R ′ ′ ′ +δE V (Z , U , zR ; β , τ ) ,
Worker’s Problem
W (Z, U, M, υ; β, τ ) = max W R (Z, U, M, υ; β, τ ), W S (Z, U, υ; β, τ )
Value of non-union worker in Rust Belt:
n W R (Z, U, M, 0; β, τ ) = f (Z, U, M ; β, τ ) w + R(Z, U ; β, τ ) +δ (1 − ζ)E W (Z ′ , U ′ , M ′ , 1; β, τ ) o +ζE W (Z ′ , U ′ , M ′ , 0; β, τ ) + 1 − f (Z, U, M ; β ′ , τ ′ ) n o × w−u ¯ + δζE W (Z ′ , U ′ , M ′ , 0; β ′ , τ ′ ) , where u ¯ ≥ 0.
Worker’s Problem (cont’d)
Value of union worker in Rust Belt: W R (Z, U, ·, 1; β, τ ) = w + R(Z, U ; β, τ ) n +δ (1 − ζ)E W (Z ′ , U ′ , M ′ , 1; β ′ , τ ′ ) o ζE W (Z ′ , U ′ , M ′ , 0; β ′ , τ ′ )
Value of any worker in the Sun Belt:
W S (Z, U, υ; β, τ ) = w + δE W (Z ′ , U ′ , υ ′ ; β ′ , τ ′ )
Balanced Trade
◮
Domestic labor is num´eraire
◮
Trade balance requirement pins down foreign wage w∗ (τ, Z)
1. Four facts + evidence for lack of competition 2. Model 3. Quantitative analysis
Quantitative Analysis
◮
How big is model’s decline in Rust Belt employment share?
Quantitative Analysis
◮
How big is model’s decline in Rust Belt employment share?
◮
Discipline quantitative exercise by extent of competition 1. from foreign producers (regional trade shares, 1950-2000) and 2. in labor markets (estimated wage premiums, 1950-2000)
◮
Import shares are low and wage premiums high initially, then move in opposite directions starting in 1980s
Calibration
◮
Calibrate to manufacturing sector
◮
Model and data period = 5 years
◮
Set δ = 0.965 to match 4% annual interest rate
◮
Set σ = 2.7 (Broda and Weinstein, 2006) and ρ = 4
◮
Normalize initial domestic productivities to 1
State of Competition
◮ ◮
State of competition denoted by θt ≡ (βt , τt ) Ex post path {θ1950+5t }Tt=0 evolves deterministically with transition from H to L in 1985
Cost of Innovation
Cost function in units of domestic final good for i ∈ {R, S}: C x(i, j), z(i, j), Z = α · x(i, j)γ · where α > 0, γ > 1,
z(i, j) ρ−1 ρ 2−ρ D(Z) ρ−1
,
2−ρ h i 1−σ i 1−σ 1−σ h ρ−1 ρ−1 ∗ ρ−1 1−ρ ∗ ρ−1 1−ρ D(Z) = λ ZR + ZR + (1 − λ) ZS + ZS
Calibration Parameters and Target Moments
◮
(τH , τL ) – iceberg trade costs
◮
∗ zR,1950 – foreign Rust Belt productivity in 1950
◮
(βH , βL ) – union’s bargaining weight
◮
λ – share of varieties produced by Rust Belt
◮
α – linear (scale) parameter of cost function
◮
γ – curvature parameter of cost function
Calibration Parameters and Target Moments
◮
aggregate import shares: 4% (pre-1985) and 9% (post-1985)
◮
∗ zR,1950 – foreign Rust Belt productivity in 1950
◮
(βH , βL ) – union’s bargaining weight
◮
λ – share of varieties produced by Rust Belt
◮
α – linear (scale) parameter of cost function
◮
γ – curvature parameter of cost function
Calibration Parameters and Target Moments
◮
aggregate import shares: 4% (pre-1985) and 9% (post-1985)
◮
Rust Belt import share: 8% (pre-1985)
◮
(βH , βL ) – union’s bargaining weight
◮
λ – share of varieties produced by Rust Belt
◮
α – linear (scale) parameter of cost function
◮
γ – curvature parameter of cost function
Calibration Parameters and Target Moments
◮
aggregate import shares: 4% (pre-1985) and 9% (post-1985)
◮
Rust Belt import share: 8% (pre-1985)
◮
Wage premium: 12% (pre-1985), 4% (post-1985)
◮
λ – share of varieties produced by Rust Belt
◮
α – linear (scale) parameter of cost function
◮
γ – curvature parameter of cost function
Calibration Parameters and Target Moments
◮
aggregate import shares: 4% (pre-1985) and 9% (post-1985)
◮
Rust Belt import share: 8% (pre-1985)
◮
Wage premium: 12% (pre-1985), 4% (post-1985)
◮
Initial Rust Belt employment share of 51.3%
◮
α – linear (scale) parameter of cost function
◮
γ – curvature parameter of cost function
Calibration Parameters and Target Moments
◮
aggregate import shares: 4% (pre-1985) and 9% (post-1985)
◮
Rust Belt import share: 8% (pre-1985)
◮
Wage premium: 12% (pre-1985), 4% (post-1985)
◮
Initial Rust Belt employment share of 51.3%
◮
1.8% TFP growth (1950-2000)
◮
γ – curvature parameter of cost function
Calibration Parameters and Target Moments
◮
aggregate import shares: 4% (pre-1985) and 9% (post-1985)
◮
Rust Belt import share: 8% (pre-1985)
◮
Wage premium: 12% (pre-1985), 4% (post-1985)
◮
Initial Rust Belt employment share of 51.3%
◮
1.8% TFP growth (1950-2000)
◮
8.5% Investment-to-GDP ratio (1950-2000) (value added share of R&D, advertising, and intangible expenditures)
Rust Belt Employment Share in Model and Data Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
1950
1960
1970
1980
1990
MSA-Level Evidence
2000
Conclusion
30
40
Import Shares in Model and Data
Import Share 20
Steel & Autos
Rust Belt, model
10
Aggregate, model
0
Aggregate, data
1950
1960
1970
1980
1990
2000
year
Conclusion
Robustness Checks & Counterfactuals Robustness Checks σ = 2.7, ρ = 3.5
σ = 3, ρ = 4.5
σ = 2, ρ = 4
σ = 3, ρ = 4
Counterfactuals high trade costs: τH = τL = 3.5
low trade costs: τH = τL = 2.7
free trade: τH = τL = 1
autarky: τH = τL → ∞
strong unions: βH = βL = .24
weak unions: βH = βL = .04
no unions: βH = βL = 0
I/GDP = 9%
I/GDP = 8%
Additional Evidence
◮
Estimates of R&D intensity by industry from 1970s
◮
TFP growth: Rust Belt vs. Japan
◮
Adoption rates for key technologies
Post-1980 Growth
Conclusion
TFP
Adoption
R&D
R&D by Industry: Evidence ◮
Report of U.S. Office of Technology Assessment (1980)
◮
Average manufacturing industry: R&D to Sales of 2.5%
◮
Industries with highest ratio:
◮
◮
Communications equipment: 15.2%
◮
Aircraft and parts: 12.4%
◮
Office and computing equipment: 11.6%
Rust Belt industries: ◮
Autos: 2.1%
◮
Rubber and Plastics: 1.2%
◮
Steel: 0.4% Additional Evidence
Productivity Growth: United States versus Japan
◮
Steel (Lieberman and Johnson, 1999) US: TFP growth < 1 percent per year 1950 to 1970 Japan: TFP doubled over same period
◮
Autos (Fuss and Waverman, 1991) US: 1.6 percent per year in 1970s Japan: 4.3 percent per year in 1970s Additional Evidence
Technology Adoption: Evidence
◮
Industry studies find that Rust Belt producers were slow adopters (compared to producers elsewhere)
◮
Two new technologies in steel of 1950s and 1960s: ◮
Basic oxygen furnace
◮
Continuous casting methods
0
10
Percent 20 30
40
50
Fraction of Steel Made Using Continuous Casting Process
1968
1970
1972
1974
1976
1978
year US
Japan
Germany
Italy
France
Additional Evidence
Post-1980 Growth
Conclusion
Signed Confession
From 1980 Annual Report of American Iron and Steel Institute: “Inadequate capital formation in any industry produces meager gains in productivity, upward pressure on prices, sluggish job creation, and faltering economic growth. These effects have been magnified in the steel industry. Inadequate capital formation ... has prevented adequate replacement and modernization of steelmaking facilities, thus hobbling the industry’s productivity and efficiency.”
Did Productivity Growth Pick up After 1980s? ◮
◮
Steel: ◮
US vertically integrated mills (mostly in Rust Belt)
◮
11 percent TFP growth from 1982 to 1987; 16 percent 1992 to 1997
◮
Source: Collard-Wexler and De Loecker (2012), Lieberman and Johnson (1999)
Autos: ◮
Pick up seen in cars per worker at GM, Ford and Chrysler
◮
From annual reports; most operations in Rust Belt
◮
Working on TFP numbers Other Predictions
Conclusion
Conclusion
◮
Relative to the rest of the US, Rust Belt declined in economic terms (employment, value added) from 1950 to 2000
◮
Theory emphasizes lack of competition as force of Rust Belt’s decline
◮
Quantitative model can generate sizeable share of employment loss
◮
Consistent with historical evidence
Union with TIOLI Offers ◮
Union makes take-it-or-leave-it offer b ∈ [0, 1]
◮
If firm accepts, unionized workers receive w plus per capita share of b · ΠR
◮
If firm rejects, union calls a strike and ◮
succeeds with probability β (i.e. production is halted for one period and ΠR = 0)
◮
fails with probability 1 − β (i.e. production resumes, workers get w, firm receives ΠR )
◮
Union offers b ∈ [0, β] since firm rejects any b > β
◮
In practice, β = b for empirically relevant parameterizations
Return to Nash bargaining
Work Stoppages Affecting 1,000+ Workers
Labor Markets
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Rust Belt Employment Share in Model and Data σ = 2.7, ρ = 3.5
Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Robustness Checks
Rust Belt Employment Share in Model and Data σ = 2.7, ρ = 4.5
Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Robustness Checks
Rust Belt Employment Share in Model and Data σ = 2, ρ = 4
Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Robustness Checks
Rust Belt Employment Share in Model and Data σ = 3, ρ = 4
Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Robustness Checks
Rust Belt Employment Share in Model and Data τH = τL = 3.5
Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Counterfactuals
Rust Belt Employment Share in Model and Data τH = τL = 2.7
Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Counterfactuals
Rust Belt Employment Share in Model and Data Free Trade (τH = τL = 1) 0.55
Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
0.3
1950
1960
1970
1980
1990
2000
Counterfactuals
Rust Belt Employment Share in Model and Data Autarky (τH = τL → ∞)
Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Counterfactuals
Rust Belt Employment Share in Model and Data βH = βL = 0.24
Data Model
Rust Belt Employment Share
0.5
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Counterfactuals
Rust Belt Employment Share in Model and Data βH = βL = 0.04
Rust Belt Employment Share
0.5
0.45
0.4
Data Model 0.35
1950
1960
1970
1980
1990
2000
Counterfactuals
Rust Belt Employment Share in Model and Data βH = βL = 0
Rust Belt Employment Share
0.5
0.45
0.4
Data Model 0.35
1950
1960
1970
1980
1990
2000
Counterfactuals
Rust Belt Employment Share in Model and Data = 9%
Data Model
0.5
Rust Belt Employment Share
I/GDP
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Counterfactuals
Rust Belt Employment Share in Model and Data = 8%
Data Model
0.5
Rust Belt Employment Share
I/GDP
0.45
0.4
0.35
1950
1960
1970
1980
1990
2000
Counterfactuals
Measures of “Wage Premia”
◮
Run Mincer-type regression for 1950 log wi,m = α · SCHi,m +
4 X
βj ·
j=1
◮
Wage premium for MSA m: πm
◮
Crude but useful proxy
j EXPi,m +
M X
m=1
Dm · πm + εi,m
6.0
Employment Growth Low Where Premiums High ORL PHX
Employment Growth 1950 to 2000 0.0 2.0 4.0
AUS
RAL
GRB SJO ATL SDG SLC SAC DAL ABQ HOU DEN NSV COM WAS CHR NOR LTL SAT MIA BAT KAL SEA GRR TAC JCK JSV MAD STO FRE SCR MININD AUG MOB TUL PTV CLB CHO SAG LUB ELP OKC RCM ATC GRN HAR WIC MNT FTW LNG WAC ASHYOR SHV SYR LAN KNX LIN LIN WLM CDR RCF SPO KAN GALLOS RCH MEMCOR OMA SXF DES BRK AMR LUI HAM DAY SAV POR NOL ROA REA ALT EVABEA JCS ALL BAL TER STL CIN CLM AKR PEO MIL TOP BIR TOL PRO JOH MUN ALBPHI CAN RAC CLE DET UTI ERE DEC TRE CHI BNG BOS WIF SPH SOB SIXDAV DUL HRT PIT SPR PUE SFR WAR BUF MAN BRG NHANYO FLI WOR TAM
CHT
GNA
−0.4
−0.2
0.0 Wage Premium in 1950
0.2
0.4
Employment: Model and Data
Industry Employment Growth and Unionization
1 0 −1 −2 −3 −4 −5
Employment Growth Rate: Rust Belt − Rest of US
2
Employment Growth and Unionization Rates: Rust Belt − Rest of US
−0.1
0.0
0.1
0.2
0.3
0.4
Unionization Rate: Rust Belt − Rest of US
Employment: Model and Data
