1. Brixen, September 09 Heterogeneous Responses of Firms to Import Protection Journal of International Economics by Jozef Konings (*) and Hylke Vandenbussche (**) (*) Catholic University of Leuven and CEPR (**) Université Catholique de Louvain-la-Neuve, CORE, KUL and CEPR

2. Brixen, September 09 I. Introduction EU firm-level data to examine the effect of Import protection on Total Factor Productivity of import- competing EU firms Most frequently used form of Trade Protection is Antidumping Protection (AD) AD protection is supposed to keep “unfair imports” out, but is often aimed at fostering the interests of inefficient domestic producers An important question is then: how antidumping import protection affects the productivity of domestic import-competing firms?

3. Brixen, September 09 Summary of Findings Two key Results: 1) Average productivity effect of AD protection is positive and significant, but the productivity of firms in protected sectors remains below that of domestic firms never involved in AD cases, which questions the desirability of protection. We find evidence of productivity-improving investment at the firm level during protection 2) But Heterogeneity across firms !  Highly productive firms are negatively affected by AD protection with productivity falling during protection  Lowly productive firms are positively affected by AD protection with productivity rising during protection.

4. Brixen, September 09 II. Methodological issues We estimate firm-level TFP with Olley and Pakes method We control for Exits in TFP estimations Several price deflators are used to make sure that productivity effects are not price effects Difference-in-difference analysis with matched control group to control for endogeneity of AD and selection effects We introduce firm heterogeneity; we construct a firm-level measure of “distance-to-the-frontier” where distance is an indication of how productive each firm is relative to the most productive firm in its four-digit EU industry

5. Brixen, September 09 III. Data Self-constructed data set of new Antidumping (AD) cases, initiated in one of these years 1996, 1997, 1998 Identification of import-competing Eruopean firms (1993- 2003) affected by the AD intiations In total, 29 new AD Investigations were initiated resulting in about 40,000 firm level observations In 17 cases the outcome was protection Duties range between 13% and 82% with an average of 27%. In 12 cases the case was terminated without protection We collect firm-level data for the EU import-competing sectors based on the NACE 4 digit sector the dumped product belongs to. around 26,069 firm-year observations on Protected firms and about 15,598 firm-year observations on Terminations.

6. Brixen, September 09 IV. Results of TFP estimation with Olley&Pakes Method Estimating coefficients in Production function With y: log of value added deflated first with producer prices and for robustness with unit values of intra-EU exports l: log of employment, k: log of fixed tangible asset;  it: unobservable productivity shock;  it: white noise

7. Brixen, September 09 Olley and Pakes STEP 1 Olley & Pakes correction: measuring the unobservable productivity shock by obervables This will allow us to estimate β l and β k consistenly which will allow us to calculate tfp and tfp growth We apply a correction for potential price effects by using first industry price deflators and afterwards unit values of intra-EU trade in products affected by AD protection

8. Brixen, September 09 Comparing Average Total Factor Productivity Across Groups

9. Brixen, September 09 Antidumping Protection and TFP of firms α i : firm-fixed effect AD-EFFECT: interaction term with a value of 1 for all affirmative AD-firms for years of protection. Gives the differential effect of productivity of treatment group (affirmative AD-firms) versus control group YEAR_DUMMIES: common time effect for all firms (business cycles,…) COUNTRY_DUMMIES: control for location specific effects COUNTRYxLOCATION: to control for differences in shocks across EU countries

10. Brixen, September 09 Control groups 1) Termination cases: firms that filled but did not obtain protection 2) Matched Control group matched sampling technique (Heckman et al. 1997): We first estimate a multi-nominal logit model to estimate the probability of « AD-filing and AD- protection » similar to Blonigen and Park (2005). Than we select a « matched control group » of NACE 4d sectors with same probability of AD- protection but that never got protection

11. Brixen, September 09 Matched control group: Multi-nominal logit model: Probability of AD protection

12. Brixen, September 09 The Effect of AD Protection on Firm Level TFP

13. Brixen, September 09 How do EU Prices respond?

14. Brixen, September 09 “Distance-to-the-frontier” DISTANCE ij,1993 = defined in the initial year of our data period Average Distance in Sample 34% with Standard deviation of 20%. This means average firm is about one third as efficient as most efficient firm in its industry

15. Brixen, September 09 “Distance-to-the-frontier” and Single versus Multiple sector firms

16. Brixen, September 09 Robustness checks

17. Brixen, September 09 Who wins, who looses from protection?

18. Brixen, September 09 Where do Average Productivity Improvements come from? During protection, protected firms  shed more labor  invest more in R&D  Pay higher wages  Invest more in capital than non-protected firms Other channels that increase productivity: Product- switching ? (Bernard, Redding and Schott, 2006)

19. Brixen, September 09 V. Conclusion Import protection affects differen firms differently! Import protection is good for the Productivity of lowly productive firms. Protection is bad for the Productivity of highly productive firms Protection induces lowly productive firms to engage in Productivity Improvement