catherine fuss (national bank of belgium). firm dynamics and employment adjustment: the role of...

Firm dynamics and employment

adjustment: the role of multinationals

P. Blanchard (U.Paris Est Créteil, ERUDITE), E. Dhyne (BNB, U. Mons) C. Fuss (BNB, ULB), C. Mathieu (U. Paris Est Créteil, ERUDITE)

The views expressed in this paper are those of the author and do not necessarily reflect the views of the National Bank of Belgium.

Eesti Pank seminar, Tallinn, January 23 2013

Introduction: the role of multinational firms (MNFs)

Importance of MNFs for Belgium

MNFs are large employment providers ...

...

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Inwards FDI flows/GDP

Belgium 84 88 91 113 129 100 120 177 169 201 192 EU 27 29 32 34 36 34 41 44 36 45 45 US 28 25 19 22 23 22 25 25 17 21 23

Source: UNCTAD (2009)

Notes: sample of firms with at least once: average number of employees>0, tangible fixed assets>100, with main activity in the manufacturing, construction or market services sectors.

INTRODUCTION EMPLOYMENT DYNAMICS PROBABILITY OF EXIT LABOUR ADJUSTMENT COSTS CONCLUSION

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Domestic firms

employment(x1000) 1087 1116 1137 995 983 967 987 1030 1051 1088 1118 1123 average per firm 9 9 9 8 7 7 7 7 7 7 8 8

MNFs





...

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010


Belgium 84 88 91 113 129 100 120 177 169 201 192 EU 27 29 32 34 36 34 41 44 36 45 45 US 28 25 19 22 23 22 25 25 17 21 23


1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Domestic firms


MNFs







...

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010


Belgium 84 88 91 113 129 100 120 177 169 201 192 EU 27 29 32 34 36 34 41 44 36 45 45 US 28 25 19 22 23 22 25 25 17 21 23


1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Domestic firms

employment (x1000) 1087 1116 1137 995 983 967 987 1030 1051 1088 1118 1123 average per firm 9 9 9 8 7 7 7 7 7 7 8 8

MNFs

employment (x1000) 508 522 539 714 707 713 710 689 706 709 688 657 average per firm 261 270 266 267 252 238 239 249 264 270 273 267





… but MNFs may be characterised by higher employment volatility

international reallocation is easier

home bias in adverse time

Two reasons of employment losses

firm exit

labour adjustment by incumbents

→ outline of the talk

Employment dynamics during the crisis : firm exit vs incumbents adjustment

The footlose nature of multinationals

Labour adjustment costs


Employment dynamics during the crisis

Job creation - job destruction (Davis, Haltiwanger and Schuh, 1996)

Dataset and variables definition

sources: Survey on FDI + (annualised) annual accounts

sample: manufacturing, construction and market services over 1997-2010

exit in t if in t+1 no employment, no total assets, tangible fixed assets<100.

MNF if owned by at least 50% by a foreign company, or having outwards FDI of at least 10%



(in thousands) 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Domestic firms ∆L Incumbents 48 41 37 31 6 4 16 23 31 43 38 -8 (# firms) 106.83 114.26 119.00 122.27 125.72 129.29 132.07 135.32 137.70 139.42 140.82 141.36 ∆L exiters -22 -31 -26 -31 -27 -21 -19 -19 -21 -23 -27 -29 (# firms) 2.28 3.02 3.65 3.68 3.64 3.58 3.92 3.56 4.14 4.49 4.81 5.51

MNFs ∆L Incumbents 4 -3 12 17 -10 -12 -2 -2 10 4 -8 -36 (# firms) 1.90 1.90 1.99 2.63 2.76 2.95 2.93 2.72 2.62 2.59 2.50 2.41 ∆L exiters -6 -4 -14 -7 -6 -8 -4 -5 -4 -5 -3 -12 (# firms) 0.05 0.04 0.04 0.05 0.06 0.06 0.06 0.06 0.06 0.06 0.04 0.08 Notes: Exit year = last year the firm is observed and no employment, no positive total assets, no tangible fixed assets>100. Incumbents are firms observed in t and t-1



more domestic firms have exited in 2008

(in thousands) 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009






incumbent MNFs start downsizing in 2008

(in thousands) 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009







domestic incumbents start downsizing in 2009, and exits remain substantial

(in thousands) 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009







domestic incumbents start downsizing in 2009, and exits remain substantial

MNFs exits increased in 2009 and incumbent MNFs downsizing increased in 2009

(in thousands) 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009




The probability of firm exit

The footlose nature of multinationals

Conclusions from previous studies

Van Beveren (2007), for Belgium, Alvarez & Görg (2009); Bernard & Jensen (2009);

Bernard & Sjoholm (2003); Görg & Strobl (2003)

MNFs have a smaller unconditional probability of exit than domestic firms

Controlling for firm and sector-level characteristics, MNFs have a similar or even

higher exit probability than domestic firms

→ random effects Probit model for the probability of exit

including sunk costs in addition to traditional variables

taking two sources of endogeneity into account



Firm-level variables

size (measured by employment) and age

TFP estimated using Ackerberg et al. procedure extended to account for firm exit

sunk costs = fraction of investment (in tangible and intangible capital) that is not leased and cannot be resold on second-hand market

δ : depreciation rate measured by the yearly sector-level mean γ : resale rate, approximated by the average sector-level ratio of sales and disposals

over the capital stock.

sunk costs represent barriers to entry and are lost in case of exit → barriers to exit in the case re-entry is likely.

Sector-level variables

sector growth of value added

competition: Herfindahl index of firm' turnover

→ MNFs are larger, older, more productive and bear larger sunk costs

they operate in sectors with higher growth and lower competition


sunkit = (PIitIit - PI

itIleasedit) + (1-δit)(1-γit).(PK

it-1Kit-1 - PKit-1Kleased

it-1)


Random effects Probit model

Endogeneity into account endogeneity wrt individual effects (Mundlak)

Endogeneity wrt decision to exit (Rivers-Vuong IV two-step procedure) e.g. "the shadow of death" (Griliches and Regev, 1995)

→ TFP, sunk costs and size potentially endogenous

step 1: regress endogenous variables on one lag of the enodgenous varable and MNF, age, competition, sector growth, sector dummies

step 2: include teh fitted value and residual of step 1 in the Probit

test of endogeneity: t-stat of step 1 residual

instruments: one lag of endogenous variable, MNF dummy, competition, sector growth, scetor dummies



Notes: Estimation over 1998-2008. All equations include year and nace 1-digit sector dummies; *** significant at the 1% level, ** at the 5% level, * at the 10% level.

Probit models for the probability of exit - marginal effects

(1) (2)

MNFit -0.028*** 0.058***

log(TFPit) -0.037***

Ageit 0.050***

log(Sunkit) -0.015***

log(Sizeit) -0.046***

Competitionst -0.019*

Sector growthst 0.004

log L -152155 -116413

MNFs have a higher (unconditional) probability of exit than domestic firms



Notes: Estimation over 1998-2008. All equations include year and nace 1-digit sector dummies; *** significant at the 1% level, ** at the 5% level, * at the 10% level.

Probit models for the probability of exit - marginal effects

(1) (2)

MNFit -0.028*** 0.058***

log(TFPit) -0.037***

Ageit 0.050***

log(Sunkit) -0.015***

log(Sizeit) -0.046***

Competitionst -0.019*

Sector growthst 0.004

log L -152155 -116413

• conditional on firm an sector char., MNFs are more likely to exit (5.8 pp)

• sunk costs act as barriers to exit


Labour adjustment costs of incumbents

Labour adjustment of incumbents

Barba Navarretti, Checci, Turini (2003) estimate labour demand equations

and find that MNFs adjust employment faster than domestic firms

→ suggests lower adjustment costs

Why would adjustment costs be different?

all firms operating in Belgium face the same labour market legislation and institutions?

economies of scale in human resources management, no labour indivisibility issues

use of flexible contracts and procedures

higher bargaining power wrt governments and unions (Haskel et al. 2007)

international production scope allows for employment reallocation

→ reallocation threat that reinforces bargaining power


Labour adjustment costs of incumbents Dataset

1998-2007

Survey on FDI + (annualised) annual accounts

+ Social Security Data (remuneration and employment by type of worker)

firms with at least 10 employees and that report detailed annual accounts

maufacturing, construction, trade, market services

Estimation of labour adjustment costs

dynamic labour demand equation based on structural Euler equation for net employment

flows (Pfann and Palm, 1993, Alonso-Borrego, 1996, Mathieu and Nicolas, 2006)

cubic labour adjustment costs function (Alonso-Borrego, 1998)

differences between blue-collar and white-collar workers (Bresson et al., 1992, Abowd and

Kramarz, 2003, Kramarz and Michaud, 2010)

differences between employment downsizing and employment upsizing (Goux et al. 2001;

Lundgren and Sjöstom, 2001, Mathieu and Nicolas, 2006)

differences between MNFs and domestic firms


Labour adjustment costs of incumbents: derivation

Adjustment costs function (Alonso-Borrego, 1998)

differences between blue-collar workers and white-collar workers

convexity: aB and aW

asymmetry: when dB, dW<0 downsizing cost are larger than upsizing costs

cross adjustment term: when g<0, adjusting both LB and LW in the same direction reduces costs but substitution between LB and LW increases costs

Euler equation for worker-type j

assuming Cobb-Douglas production function and Cournot competition:

β is the discount factor

αj is the Cobb Douglas coefficient of type j labour

µ is the markup


Labour adjustment costs of incumbents: estimation

Euler equation for worker-type j

Differences between domestic firms and MNFs

Estimation by System GMM i.e. firms form rational expectations

the discount factor is set to β = 0.97 (robustness β = 0.95, 0.99)

αj/µ obtained from estimates of production function

TFP estimated by Ackerberg et al. (2006) procedure

( ) [ ]( )( ) [ ]( )( ) [ ]( )k

titkititMNF

jtit

jitit

jMNF

j

jtit

jitit

jMNF

jjitj

it

itjst

LELMNFggLELMNFdd

LELMNFaaWLQP

1,

21,

2

1,

+

+

+

∆−∆++∆−∆+

+∆−∆+=−

ββ

βµ

α


Labour adjustment costs of incumbents: Estimates of production function coefficients

αK/µ αB/µ αW/µ

Food and textile 0.178 (0.011)

0.424 (0.015)

0.388 (0.016)

Wood, paper, chemicals, metal and non metal products, machinery 0.161 (0.006)

0.358 (0.009)

0.437 (0.009)

Equipment and recycling 0.138 (0.011)

0.354 (0.013)

0.433 (0.018)

Energy and construction 0.106 (0.007)

0.502 (0.007)

0.338 (0.006)

Trade and hotels and restaurants 0.126 (0.005)

0.176 (0.005)

0.561 (0.008)

Communication and financial intermediation 0.163 (0.005)

0.268 (0.006)

0.361 (0.007)

Real estate and business activities 0.179 (0.013)

0.071 (0.018)

0.612 (0.034)

Note: Estimates based on the 1997-2005 period; 58594 observations and 8688 firms; Bootstrap-standard errors in brackets.

Allowing for market power → estimates of αK/µ, αB/µ, αW/µ (Griliches - Mairesse, 1995)

Ackerberg, Caves and Frazer (2006)

assuming that capital, blue-collar workers and white-collar workers are fixed inputs

Labour adjustment costs of incumbents: estimates

baseline

aB 291.84***

aBMNF -93.67

dB -7.99**

dBMNF 7.98**

aW 1191.58***

aWMNF -692.26***

dW -20.98**

dWMNF 14.40

g -283.13***

gMNF 185.13

Sargan 30.41

Notes: 37553 observations and 5544 firms over the period 1998-2006. Joint estimation for blue-collar workers and white-collar workers by SGMM estimation. All equations include year and sector dummies. *** significant at the 1% level, ** significant at the 5% level, * significant at the 10% level.



baseline

aB 291.84***

aBMNF -93.67

dB -7.99**

dBMNF 7.98**

aW 1191.58***

aWMNF -692.26***

dW -20.98**

dWMNF 14.40

g -283.13***

gMNF 185.13

Sargan 30.41



0

100

200

300

400

500

600

700

domestic firms multinational firms

∆LB = +1 ∆LW = 0 ∆LB = 0 ∆LW = +1

Total adjustment costs for a net employment increase of 1

Labour adjustment costs of incumbents: explanations

Home bias

MNFs protect home employment, and downsize abroad → Belgian MNF dummy:

More intensive/efficient use of labor flexibility tools

fixed-term contract turnover

early retirement dummy

Higher bargaining power wrt unions

sample split according to compulsory union representation at the firm level (employees>=50)

Firm size

alternative specification (see later)

( ) [ ]( )( ) [ ]( )( ) [ ]( )k

titkititproxyitMNF

jtit

jitit

jproxyit

jMNF

j

jtit

jitit

jproxyit

jMNF

jjitj

it

itjst

LELproxygMNFggLELproxydMNFdd

LELproxyaMNFaaWLQP

1,

21,

2

1,

+

+

+

∆−∆+++∆−∆++

+∆−∆++=−

ββ

βµ

α



baseline Bel. MNF turn ftc early ret. no unions unions

aBMNF -93.67 -96.21 -12.17 48.54 248.15 -64.50

aBproxy -24.72 -166.36* -456.12***

dBMNF 7.98** 7.85** 4.91 4.53* 8.31* 8.22**

dBproxy 0.36 2.37 17.13***

aWMNF -692.26*** -704.23** -691.96*** -564.39** -952.03 -498.99*

aWproxy 285.21 -518.61** 179.24

dWMNF 14.40 12.07 14.95* 7.76 -54.76** -11.47

dWproxy -8.30 5.79 5.23

gMNF 185.13 159.24 223.70** 257.46*** -454.82 182.96

gproxy 166.12 -276.51 -55.03

Sargan 30.41 34.77 38.12 42.26 22.07 32.07

Notes: 37553 observations and 5544 firms over the period 1998-2006. aB, aW dB, dW, g not reported. Joint estimation for blue-collar workers and white-collar workers by SGMM estimation. All equations include year and sector dummies. *** significant at the 1% level, ** significant at the 5% level, * significant at the 10% level.



Bel. MNF turn ftc early ret. no unions unions

aBMNF -93.67 -96.21 -12.17 48.54 248.15 -64.50

aBproxy -24.72 -166.36* -456.12***

dBMNF 7.98** 7.85** 4.91 4.53* 8.31* 8.22**

dBproxy 0.36 2.37 17.13***

aWMNF -692.26*** -704.23** -691.96*** -564.39** -952.03 -498.99*

aWproxy 285.21 -518.61** 179.24

dWMNF 14.40 12.07 14.95* 7.76 -54.76** -11.47

dWproxy -8.30 5.79 5.23

gMNF 185.13 159.24 223.70** 257.46*** -454.82 182.96

gproxy 166.12 -276.51 -55.03

Sargan 30.41 34.77 38.12 42.26 22.07 32.07

Notes: 37553 observations and 5544 firms over the period 1998-2006. aB, aW dB, dW, g not reported. Joint estimation for blue-collar workers and white-collar workers by SGMM estimation. All equations include year and sector dummies. *** significant at the 1% level, ** significant at the 5% level, * significant at the 10% level.




0

100

200

300

400

500

600

700


base turn. ftc = 0.44 early ret. unions

Total adjustment costs for alternative specifications, ∆LW = +1

Labour adjustment costs of incumbents : the role of size

Meghir, Ryan, Van Reenen (1996) specification for quadratic adjustment costs

Cubic adjustment cost function without size

Cubic adjustment costs function à la Meghir et al. → L it-1-1, Lit-1

-2

Generalised adjustment cost function → θ1, θB2 θB3, θW2, θW3

+ allowing for differences in aB, aW, dB, dW, g between MNFs and domestic firms

( ) 13232

113

12

13

12

1 3232θ

−

θ−

θ−

θ−

θ−− ∆∆+∆+∆+∆+∆=∆∆

itWit

Bitit

Wit

W

itWit

W

itBit

B

itBit

B

itWit

Bit LLLgLLdLLaLLdLLaL;L;LAC

WWBB


( ) 12

11 2 −

−−

∆= it

it

ititit L)

LL

(cL;LAC

( ) 11

21

311

221

311

21 3232

−−

−−

−−

−−

−−− ∆∆+∆+∆+∆+∆=∆∆ it

Wit

Bitit

Wit

W

itWit

W

itBit

B

itBit

B

itWit


( ) Wit

Bit

Wit

WWit

WBit

BBit

BWit

Bit LLgLdLaLdLaL;LAC ∆∆+∆+∆+∆+∆=∆∆

3232

3232

Labour adjustment costs of incumbents : the role of size

Generalised adjustment cost function → θ1, θB2 θB3, θW2, θW3

Estimation of θj by random grid search.

Model and Moment Selection Criterion based on Hansen-J statistics

θ<0 → lower adjustment costs for larger firms, but the impact is limited

reduction in adjustment costs for ∆LB=1

-1.9% for domestic firms with L=10

0.001% for domestic firms with L=200

( ) 13232

113

12

13

12

1 3232θ

−

θ−

θ−

θ−

θ−− ∆∆+∆+∆+∆+∆=∆∆

itWit

Bitit

Wit

W

itWit

W

itBit

B

itBit

B

itWit


WWBB


Labour adjustment costs of incumbents: estimates no control

for size controlling

for size Meghir

specification

aB 291.84*** 782.19*** 16333.13***

aBMNF -93.67 -14.42 205.19**

dB -7.99** -12.70** -2862.81***

dBMNF 7.98** 11.17** -11550.40

aW 1191.58*** 1470.24*** 59616.48***

aWMNF -692.26*** -685.85*** 161.80

dW -20.98** -37.95*** -38557.80***

dWMNF 14.40 27.99** 179522.00

g -283.13*** -5700.69 -7415.29*

gMNF 185.13 -8836.83* 2958.09

Sargan 30.41 24.68 30.32



Labour adjustment costs of incumbents: estimates no control

for size controlling

for size Meghir

specification

aB 291.84*** 782.19*** 16333.13***

aBMNF -93.67 -14.42 205.19**

dB -7.99** -12.70** -2862.81***

dBMNF 7.98** 11.17** -11550.40

aW 1191.58*** 1470.24*** 59616.48***

aWMNF -692.26*** -685.85*** 161.80

dW -20.98** -37.95*** -38557.80***

dWMNF 14.40 27.99** 179522.00

g -283.13*** -5700.69 -7415.29*

gMNF 185.13 -8836.83* 2958.09

Sargan 30.41 24.68 30.32



0

100

200

300

400

500

600

700


no control for size

control for size; L=200

Total adjustment costs for ∆LW=1

Conclusion

1. MNFs are large emplyoment providers --- but ajust more and differently

e.g. during 2008-2009

most employment losses in domestic firms were due to exits

most employment losses in MNFs due to employment cuts by incumbents

2. Differences in exit probabilities

MNFs have a smaller unconditional probability of exit than domestic firms

Controlling for firm and sector-level characteristics, MNFs have a significantly higher

probability of exit than domestic firms, but the difference is small (5.8 pp)

3. Differences in labour adjustment costs

adjustment costs are smaller for MNFs, especially for white-collar workers

not (or only very partially )explained by flexible labour management practices or firm size

→ possible interpretation stronger bargaining power vis-à-vis unions and governements

thanks to threat of closure/delocalisation?


THANK YOU FOR YOUR ATTENTION

catherine fuss (national bank of belgium). firm dynamics and employment adjustment: the role of...

Economy & Finance

belgium mnfs

mnfs employmentx1000

mnfs employment x1000

employment adjustment

sample of firms

firm dynamics

domestic firms employmentx1000

large employment providers