Bye Bye, G.I. - The Impact of the U.S. Military Drawdown on Local German Labor Markets Jan Peter aus dem Moore1

Alexandra Spitz-Oener2

1 Humboldt Universität Berlin 2 Humboldt Universität Berlin, IAB, IZA, CASE

Tagung des SFB 649 "Ökonomisches Risiko" Motzen, 1 July 2011

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Motivation & Research question

Bases of U.S. Forces in Germany

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Motivation & Research question

Bases of U.S. Forces in Germany

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Motivation & Research question

U.S. Forces in Germany - Historical Evolution

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Motivation & Research question

Motivation - Economic impact of military base closures Base closures constitute a large, exogeneous shock at local level

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Motivation & Research question

Motivation - Economic impact of military base closures Base closures constitute a large, exogeneous shock at local level Strong public interest (e.g. subsidies for regional development)

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Motivation & Research question

Motivation - Economic impact of military base closures Base closures constitute a large, exogeneous shock at local level Strong public interest (e.g. subsidies for regional development) But: challenges for empirical research ▸ Identication of causality (endogeneity bias) ▸ Data availability

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Motivation & Research question

Motivation - Economic impact of military base closures Base closures constitute a large, exogeneous shock at local level Strong public interest (e.g. subsidies for regional development) But: challenges for empirical research ▸ Identication of causality (endogeneity bias) ▸ Data availability The drawdown of U.S. Military Forces in Germany provides a unique "natural experiment"-type setting: ▸ Exogeneous as drawdown decisions follow U.S. military rationale ▸ Strong regional variation in withdrawal 'treatment' intensity and timing ▸ Separation of direct vs. indirect (spill-over) eects

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Motivation & Research question

Motivation - Economic impact of military base closures Base closures constitute a large, exogeneous shock at local level Strong public interest (e.g. subsidies for regional development) But: challenges for empirical research ▸ Identication of causality (endogeneity bias) ▸ Data availability The drawdown of U.S. Military Forces in Germany provides a unique "natural experiment"-type setting: ▸ Exogeneous as drawdown decisions follow U.S. military rationale ▸ Strong regional variation in withdrawal 'treatment' intensity and timing ▸ Separation of direct vs. indirect (spill-over) eects

Research Question

What is the impact of the U.S. drawdown on the regional labor market? ☀ Spill-over eects into private sector employment ☀ Spill-over eects into private sector wages aus dem Moore (HU Berlin)

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Outline

Outline Motivation & Research Question Related Literature Historical Background - U.S. Forces Stationing and Withdrawal in Germany Empirical strategy Data sources Results Robustness Checks Conclusion & Future Work

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Related Literature

Related Literature 1

Adjustment to regional shocks

Blanchard/Katz (1992), Decressin/Fatas (1995), Moretti (2010, 2011)

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Related Literature

Related Literature 1

Adjustment to regional shocks

2

Impact of Military Base Realignment and Closures (BRAC)

Blanchard/Katz (1992), Decressin/Fatas (1995), Moretti (2010, 2011)

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Related Literature

Related Literature 1

Adjustment to regional shocks

2

Impact of Military Base Realignment and Closures (BRAC)

Blanchard/Katz (1992), Decressin/Fatas (1995), Moretti (2010, 2011) ▸

Germany ☀ Some early descriptive/case studies for U.S. withdrawal in Germany: Bebermeyer/Thimann (1990), Eisbach et al. (1991), Blien et al. (1992, 1993), Gettmann (1993), BICC (1995) ☀ Eects of Bundeswehr base realignments on local economy, crime: Paloyo et al. 2010a, 2010b

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Related Literature

Related Literature 1

Adjustment to regional shocks

2

Impact of Military Base Realignment and Closures (BRAC)

Blanchard/Katz (1992), Decressin/Fatas (1995), Moretti (2010, 2011) ▸

▸ ▸

Germany ☀ Some early descriptive/case studies for U.S. withdrawal in Germany: Bebermeyer/Thimann (1990), Eisbach et al. (1991), Blien et al. (1992, 1993), Gettmann (1993), BICC (1995) ☀ Eects of Bundeswehr base realignments on local economy, crime: Paloyo et al. 2010a, 2010b US - Krizan (1998), Hookers/Knetters (2001), Poppert/Herzog (2003) Sweden - Andersson et al. (2007)

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Related Literature

Related Literature 1

Adjustment to regional shocks

2

Impact of Military Base Realignment and Closures (BRAC)

Blanchard/Katz (1992), Decressin/Fatas (1995), Moretti (2010, 2011) ▸

▸ ▸

3

Germany ☀ Some early descriptive/case studies for U.S. withdrawal in Germany: Bebermeyer/Thimann (1990), Eisbach et al. (1991), Blien et al. (1992, 1993), Gettmann (1993), BICC (1995) ☀ Eects of Bundeswehr base realignments on local economy, crime: Paloyo et al. 2010a, 2010b US - Krizan (1998), Hookers/Knetters (2001), Poppert/Herzog (2003) Sweden - Andersson et al. (2007)

Other specic/exogeneous regional economic shocks ▸ ▸

Regional impact of coal boom and bust: Black et al. (2002, 2003, 2005a, 2005b) Spill-over eects from million dollar plants: Greenstone/Moretti (2003), Greenstone/Hornbeck/Moretti(2010)

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Historical Background

U.S. Forces in Germany - Stationing and Drawdown Process Initial stationing locations after World War II

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Historical Background

U.S. Forces in Germany - Stationing and Drawdown Process Initial stationing locations after World War II ▸ American occupation zone ▸ Availability of installations/barracks ▸ NATO, "Forward strategy": two major lines of defense against potential Soviet invasion

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Historical Background

U.S. Forces in Germany - Stationing and Drawdown Process Initial stationing locations after World War II ▸ American occupation zone ▸ Availability of installations/barracks ▸ NATO, "Forward strategy": two major lines of defense against potential Soviet invasion CFE treaty process with USSR: negotiations on limits to total troop levels in Western Europe

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Historical Background

U.S. Forces in Germany - Stationing and Drawdown Process Initial stationing locations after World War II ▸ American occupation zone ▸ Availability of installations/barracks ▸ NATO, "Forward strategy": two major lines of defense against potential Soviet invasion CFE treaty process with USSR: negotiations on limits to total troop levels in Western Europe Fall of the Berlin wall, German reunication, CFE treaty

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Historical Background

U.S. Forces in Germany - Stationing and Drawdown Process Initial stationing locations after World War II ▸ American occupation zone ▸ Availability of installations/barracks ▸ NATO, "Forward strategy": two major lines of defense against potential Soviet invasion CFE treaty process with USSR: negotiations on limits to total troop levels in Western Europe Fall of the Berlin wall, German reunication, CFE treaty Selection criteria for U.S. base closures (i) Ensuring that the forces would meet military and operational requirements (ii) Decreasing support costs and increasing eciency of base operations (iii) Minimizing personnel moves (iv) Reducing environmental impact (v) Considering the proximity of training areas, the quality of housing and facilities, the local political and military environment, the concerns of host nations, and the base's proximity to road and rail networks.

(Source: U.S. General Accounting Oce 1991, 1994) aus dem Moore (HU Berlin)

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Historical Background

U.S. Forces in Germany - Structure of demand in the German economy 1

Bases as direct employers of German civilian workers (≈71,000 in 1990)

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Historical Background

U.S. Forces in Germany - Structure of demand in the German economy 1 2

Bases as direct employers of German civilian workers (≈71,000 in 1990)

Demand by U.S. bases for goods and services from German companies (≈4.2 bn DM in 1986) ▸ Construction, repair, maintenance ▸ Real estate (rented homes & apartments) ▸ Food, gasoline, mail and railway, services etc.

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Historical Background

U.S. Forces in Germany - Structure of demand in the German economy 1 2

3

Bases as direct employers of German civilian workers (≈71,000 in 1990)

Demand by U.S. bases for goods and services from German companies (≈4.2 bn DM in 1986) ▸ Construction, repair, maintenance ▸ Real estate (rented homes & apartments) ▸ Food, gasoline, mail and railway, services etc. U.S. Forces as private consumers in the local economy (≈2.1 bn DM in 1989) ▸ Hotels, restaurants, bars, entertainment ▸ Rental cars, car dealerships, gas stations ▸ Groceries, daily necessities

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Data

Data sources 1

Data on U.S. Army Stationing and Withdrawal in Germany ▸ ▸ ▸ ▸ ▸ ▸

Number of U.S. personnel (Soldiers, U.S. Civilian, German employees) All US Army and Airforce Bases in West-Germany Reporting dates: 1988, 1990, 1992, 1995, 1999, 2001, 2002-2009 Exact geographic base location (geocoded) Information on date(s) of announcement of base reduction/closure, actual nal closure (exact to the day) Some add. information on type of base, area size, estd. replacement value etc.

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Data

Data sources 1

Data on U.S. Army Stationing and Withdrawal in Germany ▸ ▸ ▸ ▸ ▸

2

▸

Number of U.S. personnel (Soldiers, U.S. Civilian, German employees) All US Army and Airforce Bases in West-Germany Reporting dates: 1988, 1990, 1992, 1995, 1999, 2001, 2002-2009 Exact geographic base location (geocoded) Information on date(s) of announcement of base reduction/closure, actual nal closure (exact to the day) Some add. information on type of base, area size, estd. replacement value etc.

IAB employment and wage data from IAB Beschäftigungshistorie and IAB Betriebshistorikpanel (BHP)

(BeH) ▸ ▸ ▸

100% sample of individual employment spells for 4 Bundesländer (Hessen, Rheinland-Pfalz, Bayern, Baden-Württemberg, Bayern) BeH individual variables: info on start/end of employment spells, age, nationality, education, full-time/part-time, occupation, gross daily wage BHP employer variables: location (district), industry, rm size

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Data

Data sources 1

Data on U.S. Army Stationing and Withdrawal in Germany ▸ ▸ ▸ ▸ ▸

2

▸

Number of U.S. personnel (Soldiers, U.S. Civilian, German employees) All US Army and Airforce Bases in West-Germany Reporting dates: 1988, 1990, 1992, 1995, 1999, 2001, 2002-2009 Exact geographic base location (geocoded) Information on date(s) of announcement of base reduction/closure, actual nal closure (exact to the day) Some add. information on type of base, area size, estd. replacement value etc.

IAB employment and wage data from IAB Beschäftigungshistorie and IAB Betriebshistorikpanel (BHP)

(BeH) ▸ ▸

3

▸

100% sample of individual employment spells for 4 Bundesländer (Hessen, Rheinland-Pfalz, Bayern, Baden-Württemberg, Bayern) BeH individual variables: info on start/end of employment spells, age, nationality, education, full-time/part-time, occupation, gross daily wage BHP employer variables: location (district), industry, rm size

Regional statistical data from Federal and Regional Statistical Oces ▸

Area, Total population/population density, employment, unemployment rate, net migration, classication of area types (BBR)

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Empirical strategy

Empirical approach (1) - Employment 1

Panel Di-in-Di logYkt αk δt TIk

=

0

Year k

U .S .Mil

1990−

U .S .Mil

population

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= αk + δt + β × TIk × 1 [t > Year0k ]) + kt

1990

2002

-

(1)

District xed eects Year xed eects Measure of treatment intensity Year of 1st announcement of withdrawal in district

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Empirical strategy

Empirical approach (1) - Employment 1

Panel Di-in-Di logYkt αk δt TIk

=

U .S .Mil

1990−

= αk + δt + β × TIk × 1 [t > Year0k ]) + kt

U .S .Mil

population

1990

2002

-

(1)

District xed eects Year xed eects Measure of treatment intensity Year of 1st announcement of withdrawal in district

0 ⇒ Inclusion of State-by-Year-Eects Year k

logYkt = αk + δt +ηst +β × TIk × 1 [t > Year0k ]) + kt

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Empirical strategy

Empirical approach (1) - Employment 1

Panel Di-in-Di logYkt αk δt TIk

=

U .S .Mil

1990−

= αk + δt + β × TIk × 1 [t > Year0k ]) + kt

U .S .Mil

population

1990

2002

-

(1)

District xed eects Year xed eects Measure of treatment intensity Year of 1st announcement of withdrawal in district

0 ⇒ Inclusion of State-by-Year-Eects Year k

logYkt = αk + δt +ηst +β × TIk × 1 [t > Year0k ]) + kt

(2)

⇒ Inclusion of linear/quadratic district specic time trends

logYkt = α0k + α1kt + α2kt + δt + ηst + β × TIk × 1 [t > Year0k ]) + kt α0k α1k α2kt

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-

(3)

District specic intercept District specic coecient on linear time trend District specic coecient on quadratic time trend U.S. Drawdown & Local Labor Markets

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Empirical strategy

Empirical approach (2) - Employment 2

Dynamic specication ▸

Exploiting regional variation in timing of 1st announcement date to explore pattern of lead/anticipatory and lagged eects: +6

logYkt = α0k +α1kt +α2kt +δt +ηst + ∑ (τs × TIk × 1 [t = Year0k + s ])+kt s =−5

τs

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-

(4)

Period treatment eects

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Empirical strategy

Empirical approach (3) - Wages 1

Micro estimation at individual level logWikt

= α0k +α1kt +α2kt +δt +ηst +β × TIk × 1 [t > Year0k ])+ Xikt γ +ikt Xikt

-

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Individual level covariates (age, age2 , nationality, education, rm size, occupation)

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Empirical strategy

Empirical approach (3) - Wages 1

Micro estimation at individual level logWikt

= α0k +α1kt +α2kt +δt +ηst +β × TIk × 1 [t > Year0k ])+ Xikt γ +ikt Xikt

2

-

Individual level covariates (age, age2 , nationality, education, rm size, occupation)

2-step estimation at District x Industry level Step 1. logWijkt j

ηjkt

-

(5)

(6)

= ηjkt + Xijkt γ + µijkt

Industry index (i=1,⋯, 8) District X Industry eects (conditional on individual level covariates)

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Empirical strategy

Empirical approach (3) - Wages 1

Micro estimation at individual level logWikt

= α0k +α1kt +α2kt +δt +ηst +β × TIk × 1 [t > Year0k ])+ Xikt γ +ikt Xikt

2

-

Individual level covariates (age, age2 , nationality, education, rm size, occupation)

2-step estimation at District x Industry level Step 1. logWijkt j

ηjkt

-

(5)

(6)

= ηjkt + Xijkt γ + µijkt

Industry index (i=1,⋯, 8) District X Industry eects (conditional on individual level covariates)

Step 2. ηˆjkt = α0k + α1kt + α2kt + δt + ηst + βj × TIk × 1 [t > Year0k ]) + ξjkt (7)

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Empirical strategy

Treatment vs. control districts & treatment intensity

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Empirical strategy

Sample specication Employment ▸

▸ ▸ ▸ ▸

Full-time, private sector employment Age 25-55 Education variable improved via imputation procedures proposed by Fitzenberger et al. (1999, 2006) Crosssamples for reporting date 30/06 in each year, collapsed on district level Employment spell is recorded at employer's location

Wages ▸

▸ ▸

10 percent subsample for males age 25-55 Gross real daily wages, deated by common price index for West Germany Imputation of right-censored wages separately by education groups (Gartner, 2005) with full set of available covariates

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Empirical strategy A

Table Appendix

Descriptive Statistics

Table 1: Selected district characteristics by treatment status 1990

2002

Treatm. (1)

Contr. (2)

Diff. (3)

Treatm. (4)

Contr. (5)

Diff. (6)

195,130 (21,082)

125,259 (7,377)

69,871*** (22,336)

207,210 (21,373)

138,093 (8,061)

69,118*** (22,843)

703 (97)

347 (54)

356*** (111)

729 (98)

370 (54)

359*** (112)

24,451 (1,165)

22,002 (1,057)

2,449 (1,573)

30,079 (1,492)

27,206 (1,451)

2,874 (2,081)

5.3 (0.2)

4.8 (0.2)

0.5 (0.3)

7.6 (0.2)

6.6 (0.3)

1.0*** (0.4)

Urban

.429 (.059)

.250 (.056)

.179** (.082)

.429 (.059)

.250 (.056)

.179** (.082)

Conurban

.443 (.060)

.583 (.064)

-.140 (.087)

.443 (.060)

.583 (.064)

-.140 (.087)

Rural

.129 (.040)

.167 (.048)

-.038 (.063)

.129 (.040)

.167 (.048)

-.038 (.063)

Hesse

.229 (.050)

.067 (.032)

.162*** (.060)

.229 (.050)

.067 (.032)

.162*** (.060)

Rhineland-Palatinate

.171 (.045)

.183 (.050)

-.012 (.068)

.171 (.045)

.183 (.050)

-.012 (.068)

Baden-Wuerttemberg

.214 (.049)

.233 (.055)

-.019 (.074)

.214 (.049)

.233 (.055)

-.019 (.074)

Bavaria

.386 (.058)

.517 (.065)

-.131 (.087)

.386 (.058)

.517 (.065)

-.131 (.087)

70

60

70

60

Demographics Population Population density (inhabitants per sqkm) Socio-economic outcomes GDP per capita† (EUR) Unemployment Rate Area type

Geographic distribution

N

Notes: †Due to data limitations, GDP per capita reported in 1990 column are 1992 values. * Significant at 10%, ** at 5%, *** at 1%.

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Results

Employment

Impact of withdrawal on employment (baseline) Table 4: Estimated impact of U.S. military withdrawal on total district employment, 1975-2002 Dep. variable: Total employment (log)

(1)

(2)

(3)

(4)

U.S. WD treatment (%)

-.015** (.006) .987

-.018*** (.006) .989

-.015** (.006) .987

-.017*** (.006) .989

-.016** (.008) .985

-.021*** (.008) .986

-.011*** (.003) .997

-.010*** (.002) .998

No No No

Yes No No

Yes Yes No

Yes Yes Yes

3,640

3,640

3,640

3,640

A. - All

2

R

-.009*** (.003) .998

-.007*** (.002) .998

B. - Male U.S. WD treatment (%) R2

-.008*** (.003) .997

-.005** (.002) .998

C. - Female U.S. WD treatment (%) 2

R Other covariates: State by year dummies District x time trends District x time2 trends N

Notes: Each cell reports the coefficient on the treatment variable for one regression. All regressions include district and year fixed effects. Robust std. errors clustered at district level in parentheses. * Significant at 10%, ** at 5%, *** at 1%.

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Results

Employment

Dynamic pattern of withdrawal eect on employment Table 8: Dynamic pattern of impact of U.S. military withdrawal on total employment at district level Dep. variable: Total employment (log) WD announcement𝑡−5 WD announcement𝑡−4 WD announcement𝑡−3 WD announcement𝑡−2 WD announcement𝑡−1 WD announcement𝑡0 WD announcement𝑡+1 WD announcement𝑡+2 WD announcement𝑡+3 WD announcement𝑡+4 WD announcement𝑡+5 WD announcement𝑡+6𝑓 𝑜𝑟𝑤𝑎𝑟𝑑 Other covariates: State by year dummies District x time trends District x time2 trends R2 N

aus dem Moore (HU Berlin) Notes:

(1)

(2)

(3)

(4)

-.002 (.002) -.003 (.003) -.005 (.003) -.005 (.003) -.006 (.004) -.009* (.005) -.011** (.005) -.012** (.006) -.015** (.006) -.017** (.007) -.019** (.008) -.019** (.008)

-.002 (.002) -.004 (.003) -.005* (.003) -.006 (.004) -.007* (.004) -.010** (.005) -.012** (.005) -.015*** (.006) -.018*** (.006) -.020*** (.007) -.022*** (.008) -.023*** (.009)

-.002 (.001) -.003** (.002) -.005** (.002) -.006** (.003) -.006* (.003) -.009** (.004) -.012*** (.004) -.014*** (.005) -.017*** (.005) -.019*** (.006) -.022*** (.006) -.022*** (.007)

-.001 (.001) -.003* (.001) -.004** (.002) -.005* (.002) -.005* (.003) -.008** (.004) -.010** (.004) -.012*** (.005) -.015*** (.005) -.017*** (.006) -.019*** (.006) -.018*** (.007)

No No No

Yes No No

Yes Yes No

Yes Yes Yes

.987 3,640

.989 3,640

.998 3,640

.998 3,640

U.S. Drawdown & Local Labor Markets All regressions include district and year fixed effects. Robust std.

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Results

Wages

Eect on industry wages

Table 1: Impact of U.S. military withdrawal on wages by industry Dep. Variable: Real wages (log) by industry

(1)

(2)

(3)

(4)

1 Basic materials U.S. WD treatment (%)

.006 (.005)

.004 (.004)

U.S. WD treatment (%)

.002 (.003)

U.S. WD treatment (%)

-.000 (.002)

.001 (.001)

U.S. WD treatment (%)

.001 (.002)

.002* (.001)

-.001 (.002)

-.001 (.002)

2 Investment goods .003 (.003)

.001 (.001)

.001 (.001)

3 Food and consumption goods -.001 (.001)

-.001 (.001)

4 Construction -.000 (.001)

-.001 (.001)

5 Retail/Repair U.S. WD treatment (%)

.000 (.002)

U.S. WD treatment (%)

.013* (.007)

U.S. WD treatment (%)

.006 (.009)

U.S. WD treatment (%)

.006 (.005) Yes

.000 (.001)

.001 (.002)

.002 (.002)

6 Transport/Information .010*** (.003)

-.001 (.002)

-.005*** (.002)

7 Corporate services .003 (.005)

-.004** (.002)

-.005** (.002)

8 Private household services

Individual level covariates

.004 (.004) Yes

.002 (.003) Yes

.001 (.003) Yes

Notes: Each cell reports the coefficient the treatment for one regression. aus dem Moore (HU Berlin) U.S. Drawdown &onLocal Laborvariable Markets

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Results

Wages

Eect on industry wages by rm size (1)

Table 1: Impact of U.S. military withdrawal on industry wages by firm size category Dep. Variable: Real wages (log) by industry

(1)

(2)

(3)

(4)

1 Basic materials U.S. WD treatment (%) U.S. WD treatment (%) X small U.S. WD treatment (%) X medium

.012*** (.005) -.026*** (.006) -.019*** (.004)

.011*** (.004) -.026*** (.005) -.018*** (.004)

.004* (.003) -.020*** (.005) -.013*** (.004)

.004* (.002) -.020*** (.005) -.013*** (.004)

2 Investment goods U.S. WD treatment (%) U.S. WD treatment (%) X small U.S. WD treatment (%) X medium

.006* (.003) -.032*** (.005) -.019*** (.003)

.007** (.003) -.031*** (.005) -.018*** (.003)

.004*** (.001) -.029*** (.004) -.016*** (.003)

.004*** (.001) -.029*** (.004) -.016*** (.003)

3 Food and consumption goods U.S. WD treatment (%) U.S. WD treatment (%) X small U.S. WD treatment (%) X medium

.005** (.002) -.014*** (.005) -0.006 (.003)

.006** (.003) -.014*** (.005) -.006* (.004)

.019*** (.004) -.029*** (.006) -.014*** (.005)

.020*** (.005) -.029*** (.007) -.014*** (.005)

.004** (.002) -.013*** (.005) -.005 (.003)

.003* (.002) -.013*** (.005) -.005 (.004)

4 Construction U.S. WD treatment (%) U.S. WD treatment (%) X small U.S. WD treatment (%) X medium

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.017*** (.004) -.030*** (.007) -.015*** (.005)

.016*** (.004) -.031*** (.007) -.015*** (.005)

Continued on next page

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Results

Wages

Eect on industry wages by rm size (2) 5 Retail/Repair U.S. WD treatment (%) U.S. WD treatment (%) X small U.S. WD treatment (%) X medium

.011*** (.004) -.019*** (.005) -.009*** (.003)

.011*** (.004) -.019*** (.005) -.009*** (.003)

.012*** (.003) -.019*** (.005) -.009*** (.003)

.013*** (.003) -.019*** (.005) -.010*** (.003)

6 Transport/Information U.S. WD treatment (%) U.S. WD treatment (%) X small U.S. WD treatment (%) X medium

.029*** (.008) -.052*** (.015) -.019** (.008)

.026*** (.007) -.050*** (.014) -.016** (.007)

.012*** (.004) -.047*** (.014) -.014* (.007)

.009*** (.004) -.047*** (.015) -.014* (.008)

7 Corporate services U.S. WD treatment (%) U.S. WD treatment (%) X small U.S. WD treatment (%) X medium

.020** (.008) -.032*** (.005) -.025*** (.004)

.017*** (.006) -.030*** (.005) -.024*** (.004)

.008*** (.003) -.023*** (.005) -.019*** (.004)

.007** (.003) -.023*** (.005) -.019*** (.004)

8 Private household services U.S. WD treatment (%) U.S. WD treatment (%) X small U.S. WD treatment (%) X medium

aus dem Moore (HU Berlin)

.037*** (.005) -.057*** (.007) -.032*** (.007)

.035*** .028*** .026*** (.006) (.006) (.007) -.057*** -.050*** -.049*** (.008) (.008) (.008) -.032*** -.028*** -.028*** (.007) (.007) (.007) Continued on next page

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Robustness Checks

Robustness checks Selection of treatment and control districts Local shocks coinciding with U.S. drawdown process ▸

▸ ▸

graph In-migration from Eastern Germany after the fall of the Berlin wall Regional subsidy programms

Bundeswehr reductions

Serial correlation - Alternative Std. Errors Heteroscedasticity - Weighting by regional Kreis size Level of aggregation/spatial nature Inuence of FX eect Heterogeneity of eect between U.S. Air Force vs. U.S. Army bases aus dem Moore (HU Berlin)

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Robustness Checks

Robustness checks

Table 9: Robustness analyses for impact of U.S. military withdrawal on total employment Dep. Variable: Total employment (log) - All 1. Baseline Table 4-A. estimates 2. Exclude treatment districts with pop. > most populous control district N=3,472, N(treatment)=64, N(control)=60

3. Exclude districts in urban areas N=2,380, N(treatment)=40, N(control)=45

4. Include only treatment districts with U.S. force presence N=1,960, N(treatment)=70, N(control)=0

5. Keep only treatment districts with complete closure by 1995 N=2,800, N(treatment)=40, N(control)=60

6. Include border districts

(1)

(2)

-.009*** (.003)

-.007*** (.002)

-.009*** (.003)

-.007*** (.002)

-.012*** (.003)

-.009*** (.003)

-.008*** (.003)

-.005*** (.002)

-.006** (.003)

-.004** (.002)

-.004 (.003)

-.004* (.002)

-.013** (.005)

-.008* (.004)

8. Weight by district population in 1990

-.006*** (.002)

-.006*** (.001)

9. Cameron-Gelbach-Miller two-way clustering

-.006*** (.002)

-.005*** (.002)

10. Cluster by labor market region †

-.009*** (.003)

-.007*** (.002)

-.010* (.006)

-.008 (.005)

-.009*** (.003)

-.005*** (.002)

-.009*** (.003) -.018*** (.006)

-.006*** (.002) -.021*** (.005)

Yes Yes No

Yes Yes Yes

N=5,180, N(treatment)=89, N(control)=96

7. Exclude districts with Bundeswehr reduction 1991-2001 N=1,372, N(treatment)=49, N(control)=20

11. Aggregate on level of labor market regions ‡ N=2,156, N(treatment)=48, N(control)=32

12. Include control for FX effect 13. Separate treatment group by "U.S. Army" vs "Air Force" districts U.S. WD treatment (%) - Army (N=67) U.S. WD treatment (%) - Air Force (N=3) State by year dummies District x time trends District x time2 trends

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Conclusion & Future Work

Conclusion Employment

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Conclusion & Future Work

Conclusion Employment ▸

The U.S. drawdown in Germany is associated with signicant negative spill-over eects into local private sector employment.

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Conclusion & Future Work

Conclusion Employment ▸ ▸

The U.S. drawdown in Germany is associated with signicant negative spill-over eects into local private sector employment. The magnitude of the baseline eect is equivalent to a drop of ≈1-2 log points in employment growth for the full withdrawal in an average district.

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Conclusion & Future Work

Conclusion Employment ▸ ▸ ▸

The U.S. drawdown in Germany is associated with signicant negative spill-over eects into local private sector employment. The magnitude of the baseline eect is equivalent to a drop of ≈1-2 log points in employment growth for the full withdrawal in an average district. The heterogeneity of the eects conrms the higher vulnerability of young, low to middle educated workers in occupations/industries susceptible to suer most from a drop in local private demand.

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Conclusion & Future Work

Conclusion Employment ▸ ▸ ▸ ▸

The U.S. drawdown in Germany is associated with signicant negative spill-over eects into local private sector employment. The magnitude of the baseline eect is equivalent to a drop of ≈1-2 log points in employment growth for the full withdrawal in an average district. The heterogeneity of the eects conrms the higher vulnerability of young, low to middle educated workers in occupations/industries susceptible to suer most from a drop in local private demand. The dynamic eect pattern indicates that adverse eects persist even several years after the withdrawal.

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Conclusion & Future Work

Conclusion Employment ▸ ▸ ▸ ▸ ▸

The U.S. drawdown in Germany is associated with signicant negative spill-over eects into local private sector employment. The magnitude of the baseline eect is equivalent to a drop of ≈1-2 log points in employment growth for the full withdrawal in an average district. The heterogeneity of the eects conrms the higher vulnerability of young, low to middle educated workers in occupations/industries susceptible to suer most from a drop in local private demand. The dynamic eect pattern indicates that adverse eects persist even several years after the withdrawal. The eects are robust to a number of alternative specications.

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Conclusion & Future Work

Conclusion Employment ▸ ▸ ▸ ▸ ▸

The U.S. drawdown in Germany is associated with signicant negative spill-over eects into local private sector employment. The magnitude of the baseline eect is equivalent to a drop of ≈1-2 log points in employment growth for the full withdrawal in an average district. The heterogeneity of the eects conrms the higher vulnerability of young, low to middle educated workers in occupations/industries susceptible to suer most from a drop in local private demand. The dynamic eect pattern indicates that adverse eects persist even several years after the withdrawal. The eects are robust to a number of alternative specications.

Wages (preliminary) ▸ ▸

The results suggest a downward adjustment of local industry wage growth primarily within small rms The eects are heterogeneous across industries

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Conclusion & Future Work

Future work 1

Extensions/Robustness (for wage analysis) ▸ ▸ ▸ ▸

More disaggregate industries? Interaction by education group? Inuence of collective bargaining agreements/work councils? Dynamic pattern?

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Conclusion & Future Work

Future work 1

Extensions/Robustness (for wage analysis) ▸ ▸ ▸ ▸

2

More disaggregate industries? Interaction by education group? Inuence of collective bargaining agreements/work councils? Dynamic pattern?

Eects from base land use & location, later redevelopment

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Conclusion & Future Work

Future work 1

Extensions/Robustness (for wage analysis) ▸ ▸ ▸ ▸

More disaggregate industries? Interaction by education group? Inuence of collective bargaining agreements/work councils? Dynamic pattern?

2

Eects from base land use & location, later redevelopment

3

What are the eects of the stationing & drawdown on individual decision-making? ▸ ▸ ▸ ▸

Migration Participation Occupational trajectories, labor turnover Endogeneous skill aquisition

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Conclusion & Future Work

Future work 1

Extensions/Robustness (for wage analysis) ▸ ▸ ▸ ▸

More disaggregate industries? Interaction by education group? Inuence of collective bargaining agreements/work councils? Dynamic pattern?

2

Eects from base land use & location, later redevelopment

3

What are the eects of the stationing & drawdown on individual decision-making? ▸ ▸ ▸ ▸

4

Migration Participation Occupational trajectories, labor turnover Endogeneous skill aquisition

What are the (long-run) eects of the U.S. presence & drawdown on individual preferences, culture?

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Appendix

U.S. Forces in Germany - Total presence

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Appendix

Announcement dates

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Appendix

Descriptive Statistics (2) - Employment distribution Sex

Female Nationality

Foreign

Age groups

25-35 yrs 36-45 yrs 46-55 yrs

Education

High Medium Low

Firm size

100 N

aus dem Moore (HU Berlin)

Treatm.

1990 Contr.

.353 (.004) .089 (.005) .418 (.003) .291 (.001) .291 (.003) .055 (.005) .710 (.005) .211 (.005) .336 (.011) .200 (.005) .465 (.015) 70

.352 (.006) .082 (.005) .427 (.004) .286 (.001) .288 (.003) .042 (.003) .716 (.005) .222 (.006) .366 (.012) .202 (.005) .432 (.015) 60

Di.

Treatm.

2002 Contr.

.001 (.007) .008 (.007) -.009* (.005) .005*** (.002) .004 (.005) .014** (.006) -.007 (.007) -.010 (.008) -.030* (.016) -.002 (.007) .033 (.021)

.364 (.004) .088 (.005) .332 (.002) .392 (.001) .276 (.002) .093 (.007) .746 (.007) .125 (.003) .373 (.011) .212 (.004) .415 (.014) 70

.356 (.005) .083 (.005) .342 (.003) .389 (.001) .269 (.002) .073 (.005) .772 (.006) .124 (.004) .398 (.013) .209 (.005) .393 (.016) 60

U.S. Drawdown & Local Labor Markets

Di.

.007 (.007) .005 (.007) -.010*** (.004) .003 (.002) .007** (.003) .021** (.009) -.026*** (.009) .000 (.005) -.025 (.017) .003 (.007) .022 (.021) 01-07-2011

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Appendix

Descriptive Statistics (3) - Employment distribution Occupation

1 Production, mining, basic materials workers 2 Craft/construction workers 3 Professionals 4 Associate Profes. /Technicians 5 Clerks and sales workers 6 Transport/Security profes. and workers 7 Research/Education profes. and artists 8 Elementary services workers N

aus dem Moore (HU Berlin)

Treatm.

1990 Contr.

.365 (.009) .080 (.004) .103 (.005) .136 (.003) .174 (.004) .091 (.002) .010 (.001) .040 (.001) 70

.383 (.010) .096 (.004) .091 (.004) .130 (.004) .158 (.004) .096 (.002) .007 (.001) .039 (.001) 60

Di.

Treatm.

2002 Contr.

-.017 (.013) -.015*** (.006) .012* (.007) .007 (.005) .016*** (.006) -.005* (.003) .002** (.001) .001 (.002)

.315 (.010) .060 (.003) .115 (.006) .154 (.003) .198 (.006) .099 (.002) .012 (.001) .047 (.002) 70

.339 (.010) .072 (.004) .106 (.005) .151 (.004) .173 (.004) .106 (.003) .009 (.001) .045 (.002) 60

U.S. Drawdown & Local Labor Markets

Di.

-.023 (.014) -.012** (.005) .010 (.007) .004 (.005) .024*** (.007) -.007* (.004) .003* (.002) .002 (.002)

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Appendix

Descriptive Statistics (4) - Employment distribution

Industry

1 Basic materials 2 Investment goods 3 Food and consumption goods 4 Construction 5 Retail/Repair 6 Transport/Info. 7 Corporate svcs. 8 Private HH. services N

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Treatm.

1990 Contr.

.094 (.007) .271 (.015) .149 (.009) .100 (.004) .169 (.006) .052 (.003) .117 (.006) .047 (.003) 70

.097 (.012) .278 (.017) .167 (.011) .116 (.005) .158 (.006) .049 (.003) .089 (.005) .046 (.003) 60

Di.

Treatm.

2002 Contr.

-.003 (.014) -.007 (.023) -.018 (.014) -.016** (.007) .012 (.009) .003 (.004) .028*** (.008) .001 (.004)

.081 (.006) .238 (.014) .119 (.008) .079 (.004) .181 (.005) .062 (.003) .185 (.011) .055 (.003) 70

.085 (.011) .254 (.016) .129 (.009) .094 (.005) .182 (.007) .066 (.005) .136 (.007) .054 (.003) 60

U.S. Drawdown & Local Labor Markets

Di.

-.004 (.012) -.016 (.022) -.010 (.012) -.015** (.006) -.002 (.009) -.004 (.006) .049*** (.013) .001 (.004)

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Appendix

Descriptive Statistics (5) - Industry wages (in logs)

Industry

1 Basic materials 2 Investment goods 3 Food and consumption goods 4 Construction 5 Retail/Repair 6 Transport/Info. 7 Corporate svcs. 8 Private HH. services N

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Treatm.

1990 Contr.

4.555 (.027) 4.611 (.016) 4.441 (.010) 4.423 (.011) 4.482 (.018) 4.406 (.031) 4.608 (.017) 4.249 (.034) 70

4.553 (.052) 4.552 (.015) 4.403 (.012) 4.394 (.009) 4.412 (.024) 4.351 (.010) 4.542 (.017) 4.159 (.048) 60

Di.

Treatm.

2002 Contr.

.002 (.059) .059*** (.022) .038** (.016) .029** (.014) .070** (.030) .054* (.032) .067*** (.024) .090 (.059)

4.569 (.022) 4.675 (.022) 4.425 (.014) 4.374 (.010) 4.422 (.017) 4.319 (.043) 4.538 (.030) 4.052 (.046) 70

4.567 (.052) 4.611 (.016) 4.384 (.011) 4.357 (.009) 4.423 (.039) 4.242 (.028) 4.412 (.048) 4.003 (.090) 60

U.S. Drawdown & Local Labor Markets

Di.

.002 (.057) .064** (.028) .041** (.018) .017 (.014) -.001 (.043) .077 (.051) .126** (.057) .048 (.101)

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Appendix

Evolution of employment by treatment status, 1975-2004

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Appendix

Evolution of unemployment rate by treatment status, 1984-2004

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Appendix

Employment results (2) - Age groups Dep. Variable: Employment (log) by age group U.S. Military (%) 2

R

U.S. Military (%) 2

R

U.S. Military (%) 2

R

State by year dummies District x time2trends District x time trends N Other covariates:

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(1)

(2)

25-35 yrs. -.016*** -.011*** (.004) (.003) .995 .998 25-35 yrs. -.015*** -.009*** (.005) (.003) .995 .997 25-35 yrs. -.016*** -.014*** (.004) (.003) .994 .997 Yes Yes Yes Yes No Yes 3,640 3,640

(3) (4) A. - All 35-45 yrs. -.007 -.003 (.005) (.004) .996 .997 B. - Male 35-45 yrs. -.007 -.001 (.005) (.004) .995 .997 C. - Female 35-45 yrs. -.006 -.006 (.004) (.004) .995 .997 Yes Yes Yes Yes No Yes 3,640 3,640

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(5)

(6)

45-55 yrs. -.002 -.005* (.003) (.003) .996 .998 45-55 yrs. .001 -.003 (.003) (.003) .996 .998 45-55 yrs. -.008** -.010*** (.003) (.003) .995 .998 Yes Yes Yes Yes No Yes 3,640 3,640 01-07-2011

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Appendix

Employment results (3) - Education groups Dep. Variable: Employment (log) by education group U.S. Military (%) R

2

U.S. Military (%) 2 R

U.S. Military (%) 2

R

State by year dummies District x time2trends District x time trends N Other covariates:

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(1)

(2)

High -.008 -.004 (.006) (.005) .996 .997 High -.008 -.005 (.006) (.005) .995 .997 High -.013 -.008 (.008) (.007) .993 .994 Yes Yes Yes Yes No Yes 3,640 3,640

(3)

(4) A. - All Medium -.008*** -.007*** (.002) (.002) .998 .998 B. - Male Medium -.008*** -.006*** (.003) (.002) .997 .998 C. - Female Medium -.006** -.008*** (.002) (.002) .998 .998 Yes Yes Yes Yes No Yes 3,640 3,640

U.S. Drawdown & Local Labor Markets

(5) -.010** (.004) .994 -.002 (.005) .991

(6) Low -.010*** (.003) .996 Low

-.004 (.004) .994

Low -.014*** -.014*** (.004) (.004) .995 .997 Yes Yes Yes Yes No Yes 3,640 3,640 01-07-2011

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Appendix

Employment results (4) - Selected occupations Dep. Variable: Employment (log) in selected occupations U.S. Military (%) 2

R

U.S. Military (%) 2

R

(1)

(2)

Craft/construction workers -.011** -.010** (.005) (.004) .989 .993 Craft/construction workers -.011** -.010** (.005) (.004) .989 .993

(3) (4) A. - All Clerks/sales workers -.003 -.005** (.003) (.002) .997 .998 B. - Male Clerks/sales workers -.002 -.002 (.003) (.003) .995 .997 C. - Female Clerks/sales workers -.003 -.006** (.003) (.002) .998 .999 Yes Yes Yes Yes No Yes 3,640 3,640

State by year dummies District x time2trends District x time trends N

Craft/construction workers .004 .004 (.021) (.018) .940 .959 Yes Yes Yes Yes No Yes 3,640 3,640

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U.S. Military (%) 2

R Other covariates:

(5)

(6)

Elem. svcs. workers -.010* -.014*** (.005) (.005) .992 .995 Elem. svcs. workers -.011* -.021*** (.007) (.006) .984 .989 Elem. svcs. workers -.010* -.012*** (.006) (.006) .992 .994 Yes Yes Yes Yes No Yes 3,640 3,640 01-07-2011

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Appendix

Employment results (5) - Selected industries Dep. Variable: Employment (log) in selected industries U.S. Military (%) 2

R

U.S. Military (%) 2

R

U.S. Military (%) 2

R

State by year dummies Kreis x time2trends Kreis x time trends N Other covariates:

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(1)

(2)

Construction -.006 -.004 (.005) (.004) .989 .993 Construction -.007 -.004 (.005) (.004) .988 .993 Construction .005 .001 (.009) (.008) .989 .993 Yes Yes Yes Yes No Yes 3,640 3,640

(3)

(4) A. - All Retail/Repair -.001 -.001 (.004) (.003) .995 .997 B. - Male Retail/Repair .000 -.000 (.005) (.003) .993 .996 C. - Female Retail/Repair -.003 -.001 (.005) (.004) .995 .997 Yes Yes Yes Yes No Yes 3,640 3,640

U.S. Drawdown & Local Labor Markets

(5)

(6)

Private hh. services -.011* -.012* (.006) (.006) .994 .996 Private hh. services -.008 -.012 (.009) (.010) .991 .994 Private hh. services -.013** -.012** (.005) (.005) .993 .995 Yes Yes Yes Yes No Yes 3,640 3,640 01-07-2011

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Appendix

Bundeswehr reductions 1991-2001

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