Overcoming Free Riding A Cross Country Analysis of Firm - - PowerPoint PPT Presentation

Overcoming Free Riding

A Cross Country Analysis of Firm Participation in Antidumping Petitions Kara M. Reynolds American University

Introduction

• The growth in the imposition of antidumping

(AD) protection over the past 10 years has been well-documented and studied.

• Much of the previous research has studied the

degree to which macroeconomic and political factors have caused this increase.

• How do firms make the decision to request AD

protection?

Free-Riding

• All firms within an industry benefit from most

forms of trade protection.

• Only those who actively lobby for protection, or

submit the AD petition, have to pay the costs.

• The industry’s ability to seek protection suffers

from the free-riding problem.

▫ Firms prefer to let their competitors file the antidumping petition. If all firms choose to free- ride, the industry will forgo requesting AD protection.

Firm Participation in AD, 1995-2005

Heterogeneity Across Industries

Heterogeneity Across Countries

Research Goals

• Empirically estimate the determinants of the firm

decision to file for AD protection.

• Explore potential heterogeneity in the severity of the

free-riding problem across industries and countries.

• Preliminary evidence suggests that more firms

participate the lower the cost of filing for AD protection.

• Little evidence that firms perceive that their

participation will increase the expected benefits associated with AD petitions.

Literature Review

• Demand for AD protection

▫ Knetter and Prusa (2003), Feinberg (2005) ▫ Feinberg and Reynolds (2006,2007)

• Theoretical Models of Rent-Seeking and Trade

▫ Grossman and Helpman (1996) ▫ Magee (2002)

Free Riding in AD

• Herander and Pupp (1991)

▫ Representative firm contributes to petition if expected benefits exceed the costs. ▫ Benefits– contributing may increase the probability that petition will be successful. ▫ Empirical results…

Number of firms participating decreases with expected costs per firm. Free-riding less severe when benefits concentrated among few firms and when firms represented by trade association. Probability of protection increases with participating firms.

• Olson (2004)

A S imple Model of Firm Behavior

• Firms contribute to AD petition if the expected

benefits of contributing exceed the costs.

• Firms derive benefits from contributing if the

expected level of protection associated with petition increases from their participation.

petition successful from profits in Increase : B . successful be ill petition w y that Probabilit : ) ( ) ( * π π π π Costs B B B B

NC C C C NC C

− − + − =

Dependent Variable

• Number of firms filing the AD petitions

considered by 10 countries between 1995 and 2005.

▫ Argentina, Australia, Canada, China, EU, India, Mexico, New Zealand, U.S. and South Africa

• Global AD Database

▫ Includes domestic firms filing each petition and HS codes associated with each petition. ▫ Data supplemented with case information from the country.

Explanatory Variables

• Number of participating firms should increase

with the expected benefits and decrease with the expected costs.

• I do not observe the firm’s perceived impact on

the probability of success or the expected level

• f protection.
• I include variables that have been found to

impact the probability of success and variables I expect to impact the value of benefits.

Costs B B B B

NC C C C NC C

− − + − = ) ( ) ( * π π π

Explanatory Variables

• Insignificant coefficients could have two

interpretations

1. Variables do not impact the probability of success and expected benefits.

• 2. Variables do impact the probability success or

benefits, but firms do not believe that their contribution matters.

Costs B B B B

NC C C C NC C

− − + − = ) ( ) ( * π π π

Probability of S uccess

• UN’s COMTRADE Database

▫ One-Year Growth in Imports from the Country Under Investigation ▫ Targeted country’s share of the total imports of the product.

• World Bank’s World Development Indicators

(WDI)

▫ Two-year appreciation of country’s real exchange rate. ▫ Two-year growth in country’s real GDP.

Probability of S uccess

• World Bank’s Trade, Production and Protection

Database (TPP)

▫ Size of the Industry ▫ Average Value Added of three digit ISIC industry between 1995 and 2004

Benefits of Protection

• Total Value of Imports from Country Targeted in

Petition (COMTRADE)

• Number of firms in the industry

▫ Number of establishments in the three-digit ISIC industry (TPP).

Expected Costs

• Number of petitions filed simultaneously by the

industry.

• Trade Association
• Union
• Country-Specific Factors

▫ Political Regime. Polity variable from the Polity IV Project. ▫ Level of Development (WDI).

Empirical Methodology

• Parameters of the model estimated using a panel

count model.

▫ Explanatory variable a discrete count of firms.

ijp ijp =

) E(y µ

x + w + = ) ln(

ijp ij ij ijp

β γ δ µ

1) + (y ) exp(- = ) x , w | Pr(y

ijp y ijp ijp ijp ij ijp

ijp

Γ µ µ

Overdisperion

• Poisson model assumes that the mean number
• f firms is equal to the variance.
• Summary statistics and GOF tests suggest the

data exhibits over dispersion—or the variance is greater than the mean.

▫ Mean is 2.9, while variance is 7.25

• Solution—Negative Binomial Model

Unobserved Heterogeneity

• Unobserved heterogeneity in panels can be

measured as fixed effect or random effect.

• If unobserved component is correlated with the

explanatory variable, random effects will result in biased coefficients.

• Hausman tests suggest that random effects are

inappropriate in this case.

Unconditional FE NB Model

ijp ijp ij ijp

= ) x , w | E(y µ

ijp ijp ij ij ijp

x + w + = ) ln( ε β γ δ µ +

ijp ijp ijp ij ijp

x w y µ κµ ) 1 ( ) , | var( + =

ijp ijp y ijp

r y

ijp

µ κ κ κ θ θ θ

θ

+ = = Γ Γ + Γ , 1 , ) ( 1) + (y ) r

• (1

)r ( = ) x , w | Pr(y

ijp ijp ijp ijp ij ijp

Empirical Problems

• Fixed effects models do not allow for the

estimation of the impact of petition invariant factors.

• Omitted variable bias

▫ Total number of firms in the industry

• Sample selection bias

Results from the FE NB Model

Variable (1)b Benefits Target's Share of Imports 0.748** (2.42) Target's One-Year Import Growth 0.991* (1.71) GDP Growth 3.508 (1.54) Exchange Rate Appreciation 1.408* (1.75) Log(Imports) 1.007 (1.64) Costs Association 1.630** (9.15) Union 1.070 (0.98) Cumulated Cases 1.027**

(5 23)

FE versus RE

Variable FE RE Benefits Target's Share of Imports 0.748** 0.665** (2.42) (3.48) Target's One-Year Import Growth 0.991* 0.990** (1.71) (1.75) GDP Growth 3.508 2.485 (1.54) (1.32) Exchange Rate Appreciation 1.408* 1.166 (1.75) (0.83) Log(Imports) 1.007 1.011** (1.64) (2.48) Costs Association 1.630** 1.674** (9.15) (10.04) Union 1.070 1.100 (0.98) (1.41) Cumulated Cases 1.027** 1.028** (5.23) (5.55)

Addition of Petition Invariant Characteristics (Benefits)

Variable (1)b (2)c (3)c (4)c Benefits Target's Share of Imports 0.748** 0.665** 0.676** 0.807 (2.42) (3.48) (3.35) (1.42) Target's One-Year Import Growth 0.991* 0.990** 0.991 0.991 (1.71) (1.75) (1.64) (1.26) GDP Growth 3.508 2.485 3.637* 0.302 (1.54) (1.32) (1.76) (0.96) Exchange Rate Appreciation 1.408* 1.166 1.277 0.887 (1.75) (0.83) (1.31) (0.40) Log(Imports) 1.007 1.011** 1.010** 1.003 (1.64) (2.48) (2.30) (0.52) Log(Value Added) 1.153** (2.97) Log(Number of Establishments) 1.155** (2.45)

Addition of Petition Invariant Characteristics (Costs)

Variable (1)b (2)c (3)c (4)c Costs Association 1.630** 1.674** 1.677** 2.388** (9.15) (10.04) (10.07) (12.19) Union 1.070 1.100 1.089 (0.98) (1.41) (1.25) Cumulated Cases 1.027** 1.028** 1.028** 1.001 (5.23) (5.55) (5.54) (0.11) Log(GDP per Capita) 1.126** 1.025 (2.91) (0.46) Polity 0.981 0.972 (1.15) (1.56) θ 0.000 0.367** 0.330** 0.174** (0.00) (7.27) (7.02) (4.97)

S ummary

• Very strong evidence that more firms participate

when the costs of participation are lower.

• Other parameters estimates suggest that fewer firms

participate when the probability of success is higher.

▫ Share/Growth in Imports, GDP Growth

• The results provide only weak evidence that firms

believe their contribution will increase the probability that the petition will be successful and/or the level of protection.

▫ Exchange Rate, Total Value of Imports

Determinants of Inj ury Decisions

Variable Parameter Elasticity Number of Petitioning Firms

• 0.3073***
• 0.5911*

(0.1024) (0.3134) Exporter’s Share of Imports 0.9581*** 1.8428* (0.3279) (0.9684) One-Year Growth in Imports 0.0671 0.1291 (0.2985) (0.5765) Cumulated Casesa 0.6023*** 1.1584*** (0.1051) (0.4942) Nonmarket Economya 0.4522*** 0.8697*** (0.1322) (0.4244) Exporter’s GDP per Capita

• 1.8374
• 3.5339

(4.6645) (9.0870) Exchange Rate Change

• 0.4977*
• 0.9572

(0.2895) (0.6605) Importer’s GDP Growth

• 0.4856
• 0.9340

(1.9827) (3.8589) Exporter’s GDP Growth 1.8258*** 3.5118* (0.8329) (2.1254) Developing Countrya 0.1611 0.3099 (0.4277) (0.8336) Industry’s Share of Total

• 0.1181
• 0.2271

Employment (0.1839) (0.3711) Five-Year Decrease in Tariffs

• 1.3358
• 2.5711

(1.1072) (2.3572)

Conclusion

• More firms will participate the lower the cost of

participating.

▫ Costs fall as number of petitions filed increases, the presence of a trade association, and with the level of development of the country.

• Most evidence suggests that fewer firms

participate if they expect the probability of a successful petition to be high.

• Little evidence that firms believe their

contribution increases the likelihood of a successful petition (perhaps rightly so).