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CES Lecture on „International Trade and
Labor Market Outcomes“ – Part I
„Real Exchange Rate Shocks and
Employment Adjustment“
Christoph Moser – ETH Zurich
Outline
This CES lecture will start by sketching general recent trends
in international trade. New trade theories and stylized
empirical facts have been established due to the increased
availability of micro data. The main focus of the lecture will
be on the discussion of the following three questions:
1) Is there an impact of real exchange rate changes on
employment and how do firms adjust to gains or losses in
international competitiveness? 2) What is the role of
offshoring (international outsourcing and vertical FDI) on
productivity and labor market outcomes in industrialized
countries? 3) Why do firms more open to international trade
pay higher wages and which groups of workers tend to profit
most?
CES Lecture – Moser – Part I
2
Some Recent Trends in
International Trade
CES Lecture – Moser – Part I
3
Recent Trends and Stylized Facts
ƒ Increased availability of micro data.
ƒ New stylized facts and new theories to explain them,
since „traditional theories“ of international trade partly at
odds with new empirical regularities.
ƒ Number of micro-based stylized facts emerged since
mid 1990s: Firms envolved in international trade tend to
be larger, more productive, more skill- and capitalintensive, and pay higher wages than non-trading firms.
CES Lecture – Moser – Part I
4
Blablu
b
Source: Bernard et al., 2007.
10
Density
0
0
2
5
4
Density
10
6
15
8
20
Share of High-skilled Workers, German plants, 2005
0
.2
.4
.6
(mean) share_hi_u
.8
1
0
.2
.4
.6
(mean) share_hi_u
.8
1
Source: LIAB, Institute of Employment Research; unweighted; own calculations.
ƒ Share of high-skilled workers: non-exporting (left-hand side) vs.
exporters with an export share of at least 20 percent (right-hand side).
CES Lecture – Moser – Part I
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0
Proportion of plants by openness class
.2
.4
.6
.8
Distribution of Export Share - Plant Data
0
1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100
Note: LIAB, Institute for Employment Research. Proportions are weighted by inverse
drawing probabilit ies.
CES Lecture – Moser – Part III
7
Proportion of employees by openness class
0
.1
.2
.3
Distribution of Export Share - Employee Data
0
1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100
Note: LIAB, Institute for Employment Research. Proportions are weighted by inverse
drawing probabilities.
CES Lecture – Moser – Part III
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Distribution of Export Share - Employee Data
-.1
Change in Percentage Points
-.05
0
.05
Change in Proportion of Employees by Openness Class from 1993 to 2007
0
1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100
Source: LIAB, Institute for Employment Research.
CES Lecture – Moser – Part I
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Source: Bernard et al., 2007.
Source: Bernard et al., 2007.
Source of Potential Welfare Gains
ƒ Pavcnik (2002) analyzes productivity effects in the wake
of trade liberalization in Chile in the late 1970s and early
1980s.
ƒ Roughly two-thirds of 19 percent aggregate productivity
growth due to greater survival and growth of highproductivity plants.
ƒ One-third due to within-plant producitivity gains.
ƒ Within-industry reallocation of resources more important
than across-industry reallocation.
ƒ Reallocation of resources from low- to high-productivity
firms raises average industry productivity Æ additional
source of welfare gains.
CES Lecture – Moser – Part I
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International Trade is Rare
ƒ Do these differences already exist before export activity
starts (self-selection)?
ƒ Exporting is a relativey rare activity:
ƒ Only 4 percent of all firms in the United States export in
2000.
ƒ Even in relatively more open industries share of exporters
relatively low and ...
ƒ ... those firms that do export only ship a relatively small
portion of their total shipments abroad.
ƒ Substantial variation across and within industries.
CES Lecture – Moser – Part I
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Blablu
b
Source: Bernard et al., 2007.
Summary statistics by industry, Germany (1993 – 2005)
Industry
agriculture
Total
Export
Employment Share
(avg.)
Export
Share
(max.)
Net Flows
(avg.)
Job
Creation
(avg.)
Job
Destruction
(avg.)
Gross
Flows
(avg.)
23711
1.24%
100.00%
-0.01%
5.73%
5.68%
11.34%
168309
2.28%
100.00%
1.19%
4.25%
3.06%
7.29%
82866
1.16%
100.00%
-0.30%
5.27%
5.61%
10.84%
paper, textile,
furniture
chemical, wood
101193
4.16%
100.00%
-1.28%
4.14%
5.21%
9.15%
347047
4.48%
100.00%
-0.62%
5.46%
6.07%
11.54%
machinery, motor
vehicles
construction
566487
6.02%
100.00%
-0.66%
5.07%
5.73%
10.79%
143579
0.26%
100.00%
0.11%
8.01%
7.82%
15.75%
retailing
205637
2.73%
100.00%
-1.27%
5.18%
6.36%
11.42%
logistics
105972
5.91%
100.00%
0.62%
7.76%
7.13%
14.80%
banking, insurance
109710
1.08%
80.00%
-2.09%
2.72%
4.79%
7.49%
35741
0.38%
100.00%
2.46%
9.67%
7.18%
16.75%
education
125786
0.28%
50.00%
0.49%
5.69%
5.17%
10.84%
health care
199743
0.07%
55.00%
0.10%
5.56%
5.45%
10.95%
services
142086
2.36%
100.00%
-0.25%
5.56%
5.68%
11.10%
98284
0.85%
100.00%
-0.98%
6.56%
7.31%
13.59%
439739
0.60%
45.00%
0.58%
5.41%
4.76%
10.08%
mining and energy
food
restaurants
sport, entertainment
public administration
Note: IAB establishment panel; averages are weighted by sampling probability of corresponding strata.
15
International Trade is Concentrated and Scarce
ƒ Bernard et al., (2007) document that international trade
is extremely concentrated across firms in the U.S.
manufacturing sector in 2000:
ƒ Top 1 percent of trading firms by value account for 80
percent of the value of total trade.
ƒ Top 10 account for 95 percent of the value of total trade.
ƒ Cencentration not confined to U.S. firms.
CES Lecture – Moser – Part I
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Blablu
b
Source: Bernard et al., 2007.
Source: Bernard et al., 2007.
International Trade is Concentrated and Scarce
Source: Neary, 2010.
CES Lecture – Moser – Part I
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Importers and Exports ... Look Quite Similar
Source: Bernard et al., 2007.
Exporters Change Their Product Mix
Source: Bernard et al., 2010.
Real Exchange Rate Shocks and
Employment Adjustment
Following slides mainly based on:
Moser, Christoph, Dieter Urban and Beatrice Weder di
Mauro (2010), „International Competitiveness, Job
Creation and Job Destruction – An Establishment-level
Study of German Job Flows,“ Journal of International
Economics, Vol. 80, pp. 302-317.
CES Lecture – Moser – Part I
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Agenda
ƒ Motivation
ƒ Literature review and institutional setting
ƒ Data set and summary statistics
ƒ Empirical strategy and results
ƒ Discussion
CES Lecture – Moser – Part I
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Motivation (I)
„We should not be the only area in the world where
the currency is not put at the service of growth and jobs [..]
not destroying the competitiveness.“
French President Sarkozy
CES Lecture – Moser – Part I
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Motivation (II)
Objective threefold:
ƒ How large is the effect of a loss (or gain) in international
competitiveness of German firms on employment?
ƒ Does the adjustment mechanism work through changes in
the job creation or job destruction rate?
ƒ What is the role of German labor market institutions on the
adjustment process?
CES Lecture – Moser – Part I
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Main results (I)
ƒ The effect of loss (or gain) in international
competitiveness of German firms on employment small
in magnitude and comparable to findings for the U.S.
ƒ In contrast to the U.S., adjustment process works
through job creation rather than job destruction of
surviving firms.
- Suggestion that differences in the adjustment channel stem
from a much more regulated labor market.
- Probability of bankruptcy depends inter alia positively on a
loss in international competitiveness.
- Once attrition through bankruptcy is taken into account in
estimates Æ adjustment in Germany also via job
destruction.
CES Lecture – Moser – Part I
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Main results (II)
ƒ Role of German labor market institutions:
- Gross job flow rate relatively low in Germany.
- Islands of deregulation: fixed term contracts spur job
creation, but not destruction.
- Job destruction through discrete events like outsourcing,
sales or closure of parts of the establishment, or through
bankruptcy.
CES Lecture – Moser – Part I
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Literature review
ƒ Job flows:
ƒ Davis et al. (1996), Davis and Haltiwanger (1999), Gomez-Salvador et
al. (2004).
ƒ Real exchange rates and job/worker flows:
ƒ Klein et al. (2003), Gourinchas (1998), Burgess and Knetter (1998),
Gourinchas (1999), Biscourp and Kramarz (2007), Campa and
Goldberg (2001).
ƒ German labor market:
ƒ Hunt (2000), IMF (2006), OECD (2004), Eger (2004), Bauer et al.
(2007), Grund (2006), Goerke and Pannenberg (2005), Addison and
Teixeira (2005).
ƒ IAB establishment data:
ƒ Kölling (2000), Bauer and Bender (2004), Addison and Teixeira (2006),
Zwick (2004), Schank et al. (2007).
CES Lecture – Moser – Part I
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Labor Demand and Exchange Rate Swings
ƒ Klein et al., (2003) propose a demand-driven theoretical
framework.
ƒ Campa and Goldberg (2001) discuss three channels of
currency exposure:
- Export exposure
- Import competition
- Cost exposure through imported intermediate inputs
CES Lecture – Moser – Part I
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German Labor Institutions (I)
ƒ
Protection Against Dismissal Law (PADA, Kündigungsschutzgesetz):
- Main source for general rules governing statutory protection against
dismissal.
- Termination of an employment relationship by the employer „socially
justified“:
- i) dismissal upon lack of capability („personenbedingte Kündigung“).
- ii) dismissal upon misconduct („verhaltensbedingte Kündigung“).
- iii) dismissal upon redundancy („betriebsbedingte Kündigung“).
•
•
ƒ
Jobs really abolished.
Criterion of social selection („Sozialauswahl“).
Social compensation plan („Sozialplan“) in case of collective
dismissals (Works Constitution Act, „Betriebsverfassungsgesetz“).
CES Lecture – Moser – Part I
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German Labor Institutions (II)
ƒ
Uncertainty about firing costs.
- Predominantly judge made law.
- On average, 265,000 cases closed by German labor courts from 19992002 Æ nearly one out of four layoffs brought before court.
- (Voluntary) severance payments.
ƒ
ƒ
ƒ
Islands of deregulation: fixed-term contracts.
Overall index of employment protection: Germany still ranks
no higher than 20th among 28 industrialized countries (OECD,
2004).
Restructuring and outsourcing to lower fixed costs:
- National outsourcing: Under Civil Code § 613a (“Bürgerliches
Gesetzbuch”) existing labor contracts remain legally effective in the
case of a takeover, if the same workforce continues to pursue the same
tasks.
- Plant relocation abroad seems easier to undertake.
CES Lecture – Moser – Part I
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Data (I)
ƒ
Main data source IAB establishment panel:
- Institute for Employment Research of German Labor Agency.
- Representative, stratified sample of German establishments
of all sectors included in the employment statistics register
from 1993 to 2005.
- Stratum defined over 16 industries, 10 categories of
establishment size and 16 German regions (Laender).
- Participation of firms voluntary.
- Surveyed by professional interviewers (response rate above
80 percent).
- Establishments that refuse to answer are replaced by
random draws from the same stratum.
CES Lecture – Moser – Part I
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Data (II)
ƒ Some preliminary observations:
- The real exchange rate apparently went throught a full cycle.
- Quite some (plant) heterogeneity between and within industries.
- German gross job flows much lower than U.S. gross job flows.
ƒ Definition of job reallocation:
- Our definitions for the rates of job creation, job destruction,
job net flows and job gross flows:
ΔX it
wor ker_ flowit =
0.5 ⋅ employmentit + 0.5 ⋅ employmentit −1
- In spirit of Davis and Haltiwanger (1999), but captures job
reallocation within establishment.
CES Lecture – Moser – Part I
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Data (III)
.005
.01
.015
.02
.025
.03
Export share vs. wage cost based real exchange rate
1990
1995
2000
2005
Year
mean export share of all firms (weighted)
wage-cost based real effective exchange rate (scaled by factor 1/20)
CES Lecture – Moser – Part I
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Data (IV)
Aggregate employment
10
15
20
25
30
Weighted total sample West Germany
1990
1995
2000
2005
Year
sample aggregate employment (in 100000) in West Germany
sample aggregate employment - all exporting firms (in 100000)
sample aggregate employment - all non-exporting firms (in 100000)
Data source: IAB establishment panel
CES Lecture – Moser – Part I
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Table 1: Summary statistics by types of establishments (excerpt)
Type
Export share
(high)
(low)
Size
(n<20)
(n>20<500)
(n>500)
Fixed term
(high)
(low)
Restructuring (yes)
(no)
Number of
Observations1
Net
Flows
(avg.)
Job
Creation
(avg.)
Job
Destruct.
(avg.)
Gross Flows
(avg.)
56838
82556
57743
64786
15596
44966
94428
11604
127790
0.50%
-0.42%
-0.41%
1.04%
-0.94%
3.69%
-1.12%
-3.84%
-0.11%
5.78%
6.12%
6.03%
6.19%
4.03%
10.15%
5.11%
9.38%
5.94%
5.23%
6.47%
6.37%
5.02%
4.98%
6.36%
6.17%
13.17%
5.97%
10.90%
12.49%
12.31%
11.05%
8.94%
16.34%
11.20%
22.28%
11.82%
Notes: Averages are weighted by sampling probability of corresponding strata. If not otherwise indicated subgroups
denoted as “high” and “low” correspond to above average and below average, respectively;
1 Number of observations corresponds to non-missing values of net flows.
ƒ Average job creation (6.0 percent) and job destrution rate (6.2 percent) low
compared to other European countries (Gomez-Salvador et al., 2004).
ƒ Job creation and destruction rates of 9.1 and 10.2 percent in the United
States (Davis et al., 1996) between 1973 and 1988.
ƒ Job reallocation a la Davis-Haltiwanger 9.3% vs. 12.2% (our measure).
CES Lecture – Moser – Part I
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Table 2: Summary statistics by industry
Industry
agriculture
Total
Export
Employment Share
(avg.)
Export
Share
(max.)
Net Flows
(avg.)
Job
Creation
(avg.)
Job
Destruction
(avg.)
Gross
Flows
(avg.)
23711
1.24%
100.00%
-0.01%
5.73%
5.68%
11.34%
168309
2.28%
100.00%
1.19%
4.25%
3.06%
7.29%
82866
1.16%
100.00%
-0.30%
5.27%
5.61%
10.84%
paper, textile,
furniture
chemical, wood
101193
4.16%
100.00%
-1.28%
4.14%
5.21%
9.15%
347047
4.48%
100.00%
-0.62%
5.46%
6.07%
11.54%
machinery, motor
vehicles
construction
566487
6.02%
100.00%
-0.66%
5.07%
5.73%
10.79%
143579
0.26%
100.00%
0.11%
8.01%
7.82%
15.75%
retailing
205637
2.73%
100.00%
-1.27%
5.18%
6.36%
11.42%
logistics
105972
5.91%
100.00%
0.62%
7.76%
7.13%
14.80%
banking, insurance
109710
1.08%
80.00%
-2.09%
2.72%
4.79%
7.49%
35741
0.38%
100.00%
2.46%
9.67%
7.18%
16.75%
education
125786
0.28%
50.00%
0.49%
5.69%
5.17%
10.84%
health care
199743
0.07%
55.00%
0.10%
5.56%
5.45%
10.95%
services
142086
2.36%
100.00%
-0.25%
5.56%
5.68%
11.10%
98284
0.85%
100.00%
-0.98%
6.56%
7.31%
13.59%
439739
0.60%
45.00%
0.58%
5.41%
4.76%
10.08%
mining and energy
food
restaurants
sport, entertainment
public administration
Note: Averages are weighted by sampling probability of corresponding strata.
36
Empirical strategy (I)
ƒ Our reduced form baseline estimation equation (Klein et al., 2003):
wor ker_ flowit = β1 ⋅ job _ creationit −1 + β 3 ⋅ job _ destructionit −1 + β 3 ⋅ competitivenessit +
+ β 4 ⋅ int erest _ ratet + β 5 ⋅ Re al _ GDP _ growtht + β 6 ⋅ apprenticeshipit +
+ β 7 ⋅ fixed _ term _ contractit + β 8 ⋅ sales _ growthit + β 9 ⋅ Avg _ wageit +
+ β10 ⋅ restructuring it + β11 '⋅sizeit + d i + ε it
where wor ker_ flowit ∈ { job _ creationit , job _ destructionit , net _ flowit , gross _ flowit }
CES Lecture – Moser – Part I
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Empirical strategy (II)
ƒ
Explanatory variable of main interest (competitivenessit):
- Interaction term between the percentage change of the wage-costs
based real exchange rate (vis-à-vis 32 major trading countries) and the
firm specific export share in sales (opennessit)
- Hourly wage costs for production workers (U.S. Bureau of Labor
Statistics).
competitiv eness it = Δ wage _ cos ts t ⋅ openness it
where the wage costs and export share (opennessit) are defined as
hourly _ wage _ cos ts _ Germanyt Exportsjt
wage _ cos tst = ∑
⋅
,
hourly _ wage _ cos ts jt
j∈C
∑ Exportsit
t −1
Exportsiτ
1
.
opennessit = ∑
2 τ =t − 2 Total _ Re venuesiτ
i∈C
38
Empirical strategy (III)
ƒ Three sample selections:
- Balanced panel: 410 establishments.
- Attrition sample: Additionally, all establishments that went bankrupt (550).
- Unbalanced panel: Questionaire responds at least during five years (5000).
ƒ Different estimation techniques:
- Ordinary Least Squares.
- Fixed Effect.
- Dynamic panel estimator:
• Blundell-Bond (A): Competitiveness assumed as exogenous.
• Blundell-Bond (B): Competitiveness assumed as predetermined.
- IPW-GMM estimator:
• Strata sampling weights.
• Attrition estimator.
CES Lecture – Moser – Part I
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Empirical strategy (IV)
ƒ Dynamic panel growth regression:
p
yit = ∑ α l ⋅ yi ,t −l + β 0 + β1 ⋅ xi ,t −1 + β 2 ⋅ z i ,t −1 + η i + ε it , for t=1+p…T, (1)
l =1
ƒ Arellano Bond (1991) estimator:
[
]
(2)
E Wi Δε i = 0
[
'
⎡ yi1 xi1...xip zi1 ...ziT
⎢
0
⎢
Wi =
⎢
...
⎢
0
⎢⎣
]
[
0
yi1 yi 2 xi1 ... xi, p+1 zi1 ... ziT
...
...
]
⎤
⎥
⎥
⎥
...
0
⎥
0 yi1 ... yi,T − p−1 xi1 ...xi,T −1 zi1 ...ziT ⎥⎦
...
...
CES Lecture – Moser – Part I
0
...
[
]
40
Empirical strategy (V)
ƒ Blundell Bond (1998) estimator:
E [Δ y i ,t −1 ' (η i + ε it )] = 0
for t=p+1,…,T
(3)
where qˆit = P(sit = 1 wi,t −1 ) and pi, p+1 = qˆi, p+1
(4)
(5)
sit
pit
(6)
ƒ IPW-GMM attrition estimator:
sit = 1[wit −1δ t −1 + υit ]
pit = pi ,t −1 ⋅ qˆit
[
]
E Wi Δei = 0
'
where
Δeit = Δε it ⋅
⎡
sit ⎤
E ⎢Δyi,t −1ε it ⎥ = 0
pit ⎦
⎣
(7)
ƒ IPW-GMM estimator with strata weights:
- Replace survival probability by sampling probability of each stratum.
41
Blablu
Table 3: Dependent variable net flows – balanced panel
b
Job creation (t-1)
Job destruction (t-1)
Competitiveness
Interest rate
Real GDP growth
Apprenticeship
Fixed term contract
Sales growth
Avg. wage
Restructuring
R-squared
Observations
Firms
Hansen p-value
AR(1) p-value
AR(2) p-value
Notes:
OLS
(1)
0.2461***
(3.17)
-0.1123*
(1.70)
0.0013***
(3.34)
0.0016
(1.17)
0.1748
(1.43)
-0.0911***
(3.48)
0.2779***
(2.83)
0.0068
(1.18)
0.0011
(0.35)
-0.0121
(1.60)
0.17
3203
Fixed Effect
(2)
0.0095
(0.18)
0.0792
(1.45)
0.0016***
(3.96)
0.0022
(1.54)
0.1198
(0.95)
-0.1156**
(2.42)
0.2248***
(3.35)
0.0089
(1.63)
-0.0115
(1.49)
-0.0078
(1.04)
0.40
3203
Blundell Bond
(A)(3)
0.1111
(1.53)
0.0099
(0.16)
0.0015***
(3.32)
0.0019
(1.43)
0.1500
(1.08)
-0.0633**
(1.97)
0.3017***
(3.06)
0.0010
(0.18)
-0.0092**
(2.21)
-0.0093
(1.16)
Blundell Bond
(B)(4)
0.1119
(1.54)
0.0048
(0.08)
0.0012***
(2.74)
0.0018
(1.30)
0.1488
(1.10)
-0.0640**
(2.00)
0.3003***
(3.05)
0.0009
(0.16)
-0.0103**
(2.49)
-0.0092
(1.18)
3203
412
0.305
0.000
0.160
3203
412
0.166
0.000
0.152
Firm-clustered t statistics in parentheses; * significant at 10%; ** significant at 5%; *** significant at 1%.
Blablu
Table 4: Dependent variable job creation/job destruction –
bbalanced panel – Blundell Bond (excerpt)
Job creation (t-1)
Job destruction (t-1)
Competitiveness
Fixed term contract
Restructuring
Observations
Firms
Job Creat.(A)
(1)
0.1385**
(2.25)
0.0456
(0.77)
0.0009***
(3.33)
0.3066***
(3.64)
0.0098*
(1.80)
3207
412
Job Creat.(B)
(2)
0.1475**
(2.41)
0.0438
(0.74)
0.0007**
(2.54)
0.3039***
(3.63)
0.0089*
(1.67)
3207
412
Job Destr.(A) Job Destr.(B)
(3)
(4)
0.0276
0.0358
(0.86)
(1.12)
0.0365
0.0399
(1.21)
(1.32)
-0.0006
-0.0005
(1.60)
(1.48)
0.0048
0.0035
(0.13)
(0.18)
0.0191***
0.0182***
(3.04)
(2.94)
3205
3205
412
412
Notes: Firm-clustered t statistics in parentheses; * significant at 10%; ** significant at 5%; *** significant at
1%. Further control variables estimated but not shown (interest rate, real GDP growth, apprenticeship, sales
growth, avg. wage).
CES Lecture – Moser – Part I
43
Blablu
Table 5: IPW GMM estimator with strata weights
Net Flows
Job Creation
Job Destruction
b
(1)
(2)
(3)
Job creation (t-1)
Job destruction (t-1)
Competitiveness
Interest rate
Real GDP growth
Apprenticeship
Fixed term contract
Sales growth
Avg. wage
Restructuring
Observations
Firms
Hansen p-value
AR(1) p-value
AR(2) p-value
0.0137
(0.19)
-0.0470
(0.71)
0.0015**
(2.43)
0.0038*
(1.70)
0.1435
(0.72)
-0.0472
(1.32)
0.1151
(1.14)
0.0019
(0.26)
0.0017
(0.37)
-0.0071
(0.74)
3203
412
0.209
0.000
0.231
0.2256***
(2.92)
0.0895*
(1.77)
0.0011***
(2.56)
0.0040***
(2.98)
-0.0186
(0.09)
-0.0986***
(3.40)
0.1453**
(2.37)
0.0026
(0.35)
-0.0127***
(2.66)
0.0128
(1.29)
3207
412
0.080
0.000
0.139
0.2119**
(2.07)
0.1375***
(2.64)
-0.0004
(0.77)
0.0002
(0.07)
-0.1607
(1.15)
-0.0501
(1.33)
0.0302
(0.44)
0.0010
(0.12)
-0.0143**
(2.47)
0.0199**
(2.55)
3205
412
0.111
0.000
0.107
Gross Flows
(4)
0.4375***
(2.62)
0.2280***
(2.91)
0.0007
(0.95)
0.0041
(1.20)
-0.1763
(0.62)
-0.1475***
(2.60)
0.1754**
(2.10)
0.0039
(0.29)
-0.0269***
(2.83)
0.0327**
(2.18)
3203
412
0.196
0.000
0.107
Notes: Firm-clustered t statistics in parentheses; * significant at 10%; ** significant at 5%; *** significant at 1%.
Blablu
bTable 6: IPW-GMM attrition estimates (excerpt)
Job creation (t-1)
Job destruction (t-1)
Competitiveness
Fixed term contract
Restructuring
Observations
Firms
Net Flows
(1)
0.2282***
(3.41)
-0.0260
(0.42)
0.0019***
(3.74)
0.3817***
(4.76)
-0.0198**
(2.24)
3211
493
Job Creation
(2)
0.2352***
(3.86)
-0.0252
(0.44)
0.0010***
(2.96)
0.3487***
(4.28)
0.0048
(0.95)
3215
493
Job Destruction
(3)
0.0087
(0.29)
-0.0000
(0.00)
-0.0009**
(2.02)
-0.0317
(1.60)
0.0247***
(3.60)
3213
493
Gross Flows
(4)
0.2456***
(3.58)
-0.0262
(0.38)
0.0001
(0.19)
0.3182***
(3.64)
0.0295***
(3.55)
3211
493
Notes: Firm-clustered t statistics in parentheses; * significant at 10%; ** significant at 5%; *** significant at 1%.
Further control variables estimated but not shown (interest rate, real GDP growth, apprenticeship, sales growth, avg.
wage).
CES Lecture – Moser – Part I
45
Blablu
bTable 7: Dependent variable bankruptcy
Job destruction (t-1)
Competitiveness
Sales growth (t-1)
Invest. Growth (t-1)
Invest. Expected (t-1)
Firm size (t-1)
Logit
(1)
2.0906***
Logit
(2)
1.809***
Logit
(3)
1.8672***
Probit
(4)
1.0230***
(3.47)
0.0693**
(2.02)
-0.9462*
(1.91)
-0.4700***
(3.42)
-0.2436
(1.51)
-0.1064**
(2.39)
(2.97)
0.0834**
(2.38)
-0.6975
(1.60)
-0.2354
(1.54)
-0.4654***
(3.30)
-0.1767***
(3.64)
0.3329***
(4.64)
(3.06)
0.0768**
(2.07)
-0.7188
(1.62)
-0.2137
(1.46)
-0.4095***
(2.93)
-0.1761***
(3.56)
0.3197***
(4.39)
1.0852
(3.19)
0.0376**
(1.96)
-0.3005
(1.56)
-0.0744
(1.51)
-0.1767***
(2.93)
-0.0812***
(3.87)
0.1485***
(3.99)
0.4749
(1.39)
0.06
3617
(1.20)
0.06
3617
Past outsource
Fixed term contract (t2)
Pseudo R-squared
Observations
0.05
3719
0.06
3719
Notes: Robust t statistics in parentheses; * significant at 10%; ** significant at 5%; *** significant at 1%.
CES Lecture – Moser – Part I
46
Further results
ƒ
ƒ
ƒ
Robustness:
- Unbalanced sample (about 21,000 observations).
- Sample with German exporters (about 5,600
observation).
Competitiveness variable interacted with 14 industry
dummies:
- 7 out of 14 industries exhibit significant interaction term.
- Industries outside manufacturing.
- Important to include all sectors into the analysis.
Proxy variable for imported intermediate inputs interacted
with competitiveness.
CES Lecture – Moser – Part I
47
Blablu
bTable 8: Capital Goods Price Competitiveness(excerpt)
Job creation (t-1)
Job destruction (t-1)
Competitiveness
Competitiveness*
price competit.
Fixed term contract
Restructuring
Observations
Firms
Net Flows
(1)
0.1123
(1.56)
0.003
(0.00)
0.0013***
(3.00)
0.0010**
(2.05)
0.3013***
(3.06)
-0.0091
(2.24)
3203
412
Job Creation
(2)
0.1491**
(2.45)
0.0421
(0.71)
0.0008***
(2.98)
0.0012***
(3.06)
0.3049***
(3.65)
0.0090*
(3.60)
3207
412
Job Destruction
(3)
0.0373
(1.16)
0.0426
(1.41)
-0.0006
(1.58)
0.0002
(0.38)
0.0036
(0.10)
0.0182***
(2.95)
3205
412
Gross Flows
(4)
0.1864***
(2.85)
0.0858
(1.19)
0.0002
(0.10)
0.0013**
(2.09)
0.3086***
(3.68)
0.0273***
(3.22)
3203
412
Notes: Firm-clustered t statistics in parentheses; * significant at 10%; ** significant at 5%; *** significant at 1%.
Further control variables estimated but not shown (interest rate, real GDP growth, apprenticeship, sales growth, avg.
wage).
CES Lecture – Moser – Part I
48
Conclusion
ƒ
ƒ
The effect of loss (or gain) in international competitiveness of
German firms on employment small in magnitude and
comparable to findings for the U.S.
In contrast to the U.S., adjustment process works through job
creation rather than job destruction.
- Suggestion that differences in the adjustment channel stem
from a much more regulated labor market.
- Once attrition through bankruptcy is taken into account Æ
adjustment via job destruction.
- Probability of bankruptcy depends inter alia positively on a loss
in international competitiveness.
CES Lecture – Moser – Part I
49
Other Recent Studies on Exchange Rate Effects
ƒ Other potential channels of firm adjustment?
ƒ Ekholm et al. (2012) exploit a sharp real appreciation of
the Norwegian Krone in the early 2000s:
- Data captures all three sources of currency exposure.
- Negative effect on hours worked, but some positive
productivity effects (when the pressure is on).
ƒ Nucci and Pozzolo (2010) use an Italian sample of
manufacturing firms from 1984 to 1998:
- Export and import real effective exchange rate based on 24
trading partner countries.
- Document effect on employment and hours worked.
- Survival of firms not depending on exchange rate fluctuations.
CES Lecture – Moser – Part I
50
Thank you for your attention.
CES Lecture – Moser – Part I
51
References
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ƒ
ƒ
ƒ
ƒ
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