Antidumping Protection and Market Power of Domestic Firms?

Jozef Konings* and Hylke Vandenbussche**

(*) University of Leuven and CEPR, London

(**) University of Leuven, CEPR

Journal of International Economics, 2005

I. LiteratureTrade Liberalisation and the effects on Markups

(P/MC) J. Levinsohn (1993), JIE : Turkey

Harrison (1994), JIE: Chile N. Pavcnik (2002), RevEcStud: Chile Krishna and Mitra (1998), JDE: India Tybout (2000), JEL, overview

Conclusion: ‘Trade Liberalisation disciplines firms’ Markups’

Antidumping and the effect on Markups (P/MC)

theoretical papers suggest AD-protection facilitates collusion Veugelers and Vandenbussche, EER (1999); Staiger and Wolak (1989); Prusa (1992)

Harrison, (1991) and Prusa (1997) : increasing foreign import values as a result of AD-

Blonigen and Prusa (2001): ‘empirical work on the domestic price effects of AD- is lacking’

II. Methodology Roeger, JPE (1995) Solow (1957): relationship output growth q=log(Q/K) and

capital/labor input ratio n=log(L/K) under Perfect competition

=factor share earned by labor, over sales

= is the Hicks-neutral rate of technical progress = productivity growth rate

Hall (1988) shows that the primal Solow residual (SR) under imperfect competition into a technology component and a markup component µ=P/MC.

In order to estimate the SR, an IV approach is essential due to a correlation between the explanatory variable on RHS and the Hicks neutral technological progress

wL

PQ

( 1)t t it

t t t ttSR q n n

Roeger (1995) constructs a method based on Hall (1988) but which does not require the use of instruments to estimate the SR. This method stems from subtracting the dual or price based Solow residual (DSR) from the primal Solow residual (SR), thereby getting rid of the

(1)

(2)

(1 ) ( 1) ( )

l l t lit it it it it it itSR q l k l k

(1 ) ( 1) ( )l l l it

it it it it it ittDSR w r p w r

w= log of wage rate r= log of the rental price of capital pit = log of the price of firm i in period t

PQ

wL

=labor’s share in saleswL

PQ

Subtracting (2) from (1) we get

(3)

( ) ( ) (1 ) ( )

( 1) ( ) ( )l l

it it it it it it it

t it it it itl

NSR p q w l r k

w l r k

After including material inputs M (e.g. Basu and Fernald, 1995; Oliviera-Martins and Scarpetta, 1999) and after rewriting (1) becomes

(4)

( ) ( )it it it itp q r k

( ) ( ) ( ) ( )l m l m

it it mit it it itt w l p m r k

1 itity x Rewriting (4) we get

the growth rate in sales per value of capital

a composite explanatory variable that represents the growth rates in the various values of the input factors weighted by their respective share in total sales.

ity

itx

Equation (4) shows that in order to obtain an estimate of the markup (), we need information on

sales growth, growth in the wage bill, growth in material costs and growth in the value of capital

Our testable equation (5) then becomes:

1 2

1 2 3it it it

it

it

jt

jt

y

x x AD x GDP

AD GDP

AD : Either dummy equal to 1 for the years during which antidumping protection applies (from 1997 onwards) or a ‘trade weighted-duty’

GDPjt: annual GDP growth per EU country j to control for business cycle effects on markup

1 = the markup before protection

2 = the change in the markup during AD protection

3 = the change in the markup ratio due to business cycle fluctuations

III. Data Company accounts of 4,000 European producers involved in

antidumping investigations including small firms Time series of company accounts: 1992-1999 involving balance

sheet and Income statement items Event year: antidumping initiations in 1996 This allows us to measure markups before 1996 and during

antidumping protection Sunset Clause: AD-measures last 5 years In 1996: 15 different antidumping cases were initiated (15 is about

the average filings per year) 10 cases led to sufficient information in order to apply the Roeger

(1995) method for estimating markups: sales (P.Q), wage bill (W.L), material costs (PM.M), value of capital (RK.K)

We matched the 8-digit trade classification of the good under AD-investigation with the EU import competing firms producing them

NOTES: We have financial information at the firm

level not at the level of the product line UNDERESTIMATION of the effects of AD protection on EU markups.

We control for potential ‘selection bias’ of the AD- measures by using a two-stage Heckman procedure

IV. Results 1 21 2 3it it it itit jt jty x x AD x GDP AD GDP

Protection cases

(1)

Termination Cases

(2)

Counterfactual (3)

(1) Corrected for Selection

Bias

1

1.163*** (0.010)

1.25*** (0.012)

1.21*** (0.007)

1.178*** (0.030)

2 0.079*** (0.013)

0.011 (0.015)

-0.006 (0.01)

0.087** (0.036)

3 -0.086 (0.059)

-1.08** (0.577)

-0.036 (0.043)

-0.12 (0.154)

Inverse Mills

-

-

-

0.002 (0.003)

R2 0.83

0.8 0.85 0.83

Number of observations

8708 7214 15591 8708

Estimation Results for Pooled Cases (Fixed Effects), using AD Duty levels

Protection

Cases

(1)

Protection

Cases

(3)

Protection Cases

(using lagged imports t-2)

(4)

1= P/c 1= P/c 1= P/c

1

1.163*** (0.008)

1.59*** (0.066)

1.74*** (0.09)

2= P/c 2= P/c 2= P/c 2

0.302*** (0.037)

-

-

X interacted with log of dumping imports

-

-0.028***

(0.004)

-0.036***

(0.006) X interacted with log of non-

dumping imports -

-0.013 (0.010)

-0.018 (0.013)

3

-0.101* (0.058)

-0.198***

(0.058)

-0.30*** (0.077)

R2 0.83

0.83

0.81

Number of observations

8708

8708

5934

Estimations case-by-case using Fixed Effects

1 21 2 3it it it itit i jt jty x x AD x GDP AD GDP Markup

1 before

protection (2)

Before AD

(3)

Markup 2

change after

protection (4)

During AD

(5)

R2

Protection cases

Cotton fabrics 1.27*** (0.028)

P > MC 0.065*** (0.038)

P > MC 0.86

Leather Handbags

1.24*** (0.011)

P> MC 0.055*** (0.014)

P> MC 0.89

Farmed Atlantic Salmon

1.039 (0.030)

P > MC 0.129** (0.07)

P > MC 0.75

Seamless Pipes and Tubes

0.993 (0.033)

P = MC -0.049 (0.06)

P = MC 0.75

Polyester Fibre and yarns

1.088* (0.050)

P > MC 0.191*** (0.075)

P > MC 0.72

Bed Linen 1.61*** (0.064)

P>MC 0.36*** (0.101)

P>MC 0.90

Stainless steel fastner

1.17*** (0.019)

P > MC 0.091** (0.023)

P > MC 0.91

Termination Case (1)

Markups 1

before protection

(2)

Before AD

(3)

Markups 2

change after

protection (4)

During AD

(5)

R2

Synthetic Fibre ropes

1.19*** (0.039)

P>MC 0.033 (0.044)

P>MC 0.88

Luggage & Travel Goods

1.27*** (0.013)

P>MC 0.007 (0.017)

P>MC 0.83

Video Tapes 1.38*** (0.175)

P>MC 0.080 (0.24)

P>MC 0.63

Figure 3: Evolution of Imports in tons in

‘Seamless Steel Tubes Case’

Evolution Imports Seamless Steel Pipes and Tubes

0

50000

100000

150000

200000

250000

300000

350000

400000

450000

500000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

years

Imp

ort

s in

met

ric

ton

s

EXTRA-EUR Dumping Non-Dumping

Figure 4: Evolution of Imports in tons in ‘Leather Handbags’

Evolution Imports Leather Handbags

0

2000

4000

6000

8000

10000

12000

1 2 3 4 5 6 7 8 9 10

years

Imp

ort

s in

met

ric

ton

s

EXTRA-EUR Dumping Non-Dumping

IV. Robustness Checks

CounterFactual Markups 1

before protection

Markups 2

change after protection

R2

Processing of Meat 1.131*** (0.008)

0.000 (0.012)

0.95

Processing of fruit and vegetables

1.175*** (0.026)

-0.005 (0.035)

0.80

Grain Mill Products

1.132*** (0.020)

-0.016 (0.028)

0.89

Wine 1.153*** (0.026)

-0.021 (0.032)

0.84

Outwear 1.338*** (0.019)

0.020 (0.026)

0.79

Inorganic basic chemicals

1.223*** (0.042)

0.067 (0.056)

0.77

Plastics in primary form

1.203*** (0.022)

0.033 (0.031)

0.86

Cement 1.344*** (0.044)

-0.074 (0.053)

0.80

Copper 1.217*** (0.039)

-0.105** (0.050)

0.83

Metal Structures 1.224*** (0.023)

-0.031 (0.030)

0.80

Table 6: Results For Counterfactual (Fixed Effects)

Table 7: Initiator and Single Product Effects Initiator

Effect Single

Product Firms

Multiple product

firms 1= P/c 1= P/c 1= P/c

X

1.21*** (0.01)

0.929

(0.045)

1.169*** (0.011)

2= P/c 2= P/c 2= P/c X X AD-dummy

0.061*** (0.013)

0.14** (0.062)

0.075*** (0.014)

X X AD-dummyX initiator dummy

0.196** (0.09)

-

-

X X country GDP growth -0.082 (0.06)

0.20

(0.27)

-0.057 (0.063)

R2 0.87

0.74

0.83

Number of observations

6997

475

8236

V. Conclusion Market power of European firms increases on average

by 8% points during Antidumping protection. When import diversion is strong, effects of AD protection

on markups is largely offset This result is robust to estimation techniques (OLS, fixed

effects, correcting for selection bias) Our results are likely to be underestimates, the rise in

markup we find is stronger for single product firms The rise in markup is strongest for ‘Initiators’ The increase in Markup (P/MC) can be an increase in

price OR an increase in productivity lowering MC The productivity paper shows that at least part of the

increase in markups is driven by efficiency gains