Anti-Dumping Measures and International Pricing Policy: An Australian Study

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ABSTRACT

The number of anti-dumping initiatives by governments all over the world has increased significantly during the recent years. This has a potential effect on the international pricing policy of firms.

This research focuses on the impact of the anti-dumping measures on the international pricing policy of firms and any strategic measures that the firms take to counter the anti-dumping actions. An a priori model of the impact of anti-dumping measures on international firm's pricing policy has been developed based on literature review and tested using structural equation modelling technique. Data for the research has been gathered from 178 Australian international marketers. Results of the study show that there is an agreement among the participating firms that the current anti-dumping laws of different countries are often confusing and there is no uniform definition of what may be called as ' dumping'. There is a general perception among the participating firms that more and more governments are using this as another non-tariff barrier.

Results of this study also show that international firms are finding concentrating in less sensitive product categories, cooperation with local competitors and differentiation through enhanced services and trading up as good strategic measures, to counter the effects of anti-dumping actions.

INTRODUCTION

International pricing is one of the most critical issues that international firms face. A potential obstacle for international pricing policies is the antidumping laws that increasing number of governments are using to counter dumping practices (Miranda, Torres and Ruiz, 1998). International firms need to take antidumping laws into account when determining their international pricing policies.

In developing a pricing policy a firm has to consider both external environment in which it has to compete and also the internal factors which condition and control the courses of action open to the firm. One of the major elements of an international firm's external environment for pricing purposes is host country's government policies of which antidumping measures are a part. A World Bank study showed that the impact of dumping duties in the United States manufactured goods sector has boosted average tariffs in that sector from nominal 6 percent to actual 23 percent (The Financial Times, 1993). To minimise risk exposure to antidumping actions, international marketers might pursue various marketing strategies (Kostechi, 1991).

The research questions this paper addresses are: Do international marketers take into account antidumping measures in the host country while setting their international prices? Do they take any strategic measures to counter the anti-dumping impost?

CONCEPTUAL FRAMEWORK

The definition of dumping is usually pretty murky. Different economists have defined dumping differently. One approach defines imports as dumped if the products are sold below their cost of production. The other approach characterises dumping as selling goods in a foreign market below the price of the same goods in the home market. World trade Organisation defines dumping as "the sale of a product for export at a price below its 'normal Value'" (WTO, 2003). According to WTO definition "normal value" is usually the domestic price of the product in the exporting country. If this price cannot be used for comparison purposes, normal value may be calculated on the basis of the price of the product when sold to a third country, or as a constructed value including per unit fixed and variable costs plus reasonable amount for profits. Obviously, the definition is not clear-cut, and gives the host country advantage to take leverage out of the confusion.

The number of antidumping initiatives has increased in recent years. Most of the antidumping actions take place in the USA and the European Union countries. However, antidumping measures are increasingly initiated in other countries including the developing ones. The increased concern and enforcement by countries reflects the changing attitude among all countries towards dumping (Business Europe, 1996). Economists often equate this trend with protectionism (Bhagwati, 1988). The gradual removal of traditional trade barriers like tariffs and quotas has encouraged countries to increasingly use non-tariff barriers like antidumping measures to protect their home industries.

Local producers usually have advantages over the importers in case of antidumping litigations. This is because plaintiffs (local producers) usually face no penalties for baseless complaints. According to a recent editorial of the Australian Financial Review (Australian Financial Review, 2002) on Australia's anti-dumping law, "there is probably no such industry and it is no coincidence that Australia's anti-dumping law does not actually require the complainant to show predation". The complaint handling process is lengthy and often the importer has to submit a bond after preliminary investigation establishes possible case of dumping till the final outcome of the investigation. This increases the cost of the importers and as a result adds up to the price to the advantage of the local producer. Often though the final outcome is different from the preliminary findings. For example, according to the Productivity Commission of Australia, the Anti-Dumping Authority's investigations "resulted in a final finding different from the Custom's preliminary finding in more than 40 per cent cases" (Australian Financial Review, 2002). Plaintiffs also have a home advantage (Bhagawati, 1988).

According to Anderson (1992) antidumping actions are often used as a tactical tool by countries to foster voluntary export restraints. Pricing tends to be relegated to a secondary role in the formulation of competitive strategies. To a large degree this is because price is highly visible and readily understood by consumers, competitors as well as governments. Anti dumping measures usually help drive up the price of the imported products to protect the local producers. Increasingly however, international marketers are using different tactical and strategic initiatives to counter the anti-dumping measures. Michel Kostecki (1991) recommends exporters to consider some marketing strategies to minimise risk exposure to anti-dumping actions. His recommended strategies include: (1) trading up from low-value to high-value products via product differentiation, (2) differentiate product by adding support services to core products, (3) reallocation of the firm's marketing efforts from vulnerable products to less sensitive products, and (4) entering into cooperative agreements with local competitors.

Overall, the following conceptual model can be drawn for this research:

METHODOLOGY

When one looks at the evolution of basic and applied knowledge in marketing, frequently, the progression is from a simple, unidimensional idea or concept into a more complex, multidimensional representation (Bagozzi, 1994). One way to represent multidimensional constructs is with a second-order confirmatory factor analysis (CFA), an approach taken in this research.

The characteristic of the data in this research required usage of multivariate technique(s). The statistical technique selected for this purpose is structural equation modelling (SEM). Structural Equation Modelling (SEM) has become a useful methodology for specifying, estimating, and testing hypothesised interrelationships among a set of substantive meaningful variables. Accordingly, the IMSP constructs developed through literature review and the a priori model developed based on the constructs was tested using SEM technique.

The target population was defined as Australian international marketers, both inbound and outbound. Questionnaires were sent to 500 randomly selected Australian exporters/importers of which 178 completed ones were returned. Respondents were asked to indicate a degree of their agreement or disagreement on an ordinal type 1-7 Likert scale with statements related to the research.

In a study of empirical research reports in international marketing, Aulakh and Kotabe (1992) found the mean sample size as 197.6 and response rate as 40.5 per cent. In this survey, out of the 500 companies 178 responded, giving a response rate of 35.6 per cent, which is close to the standard and expectations. After thorough editing of the 178 questionnaires returned, all of them were found satisfactory. In SEM, one approach is always to test a model with a sample size of 200, because 200 is proposed as being the "critical" sample size (Hair et al, 1992).

All data collected was codified and entered into EQS--the SEM software used, for final analysis. All SEM techniques are distinguished by two characteristics: (1) estimation of multiple and interrelated dependence relationships, and (2) the ability to represent unobserved concepts in these relationships and account for measurement error in the estimation process.

For the data set (N=178) a univariate kurtosis value >0.512 was not normal. Several variables yielded values greater than this, indicating some non-normality of the data. Therefore, the ML robust estimation method was used to re-estimate the model, as the robust estimation is more suitable when the data is suspected of being non-normal (Bentler, 1995). The robust method also provides robust standard errors, which have been corrected for non-normality (Byrne, 1994).

RESULTS

No problems were encountered in running the a priori structural model. The distribution of standardised residuals for this model was symmetric and was optimally dispersed suggesting good specification of the a priori model. Further, the model converged after only seven iterations. No special problems were encountered during optimisation, and all parameter estimates were in order, indicating successful convergence. [chi square] (395, N = 178) = 598.543, p < .001, the Comparative Fit Index (CFI) 0.978, Robust Comparative Fit Index (RCFI) 0.981, Bentler-Bonett Normed Fit Index (BBNFI) 0.950, and Bentler-Bonnett Nonnormed Fit Index (BBNNFI) 0.978, indicated a good fit for the model. Moreover, all the t-ratios were significant (more than 1.96). Wald test did not support dropping any of the parameters. Thus all variables were retained. In most instances, the association in a structural equation model are necessary but not sufficient evidence of causality. In other words, one might argue that a particular model is consistent with a set of causal propositions, although the data on which the model is based might be equally consistent with other causal propositions. In the end, associations in structural equation models are interpreted no differently from associations in traditional statistical models. Accordingly, the appropriate inference is that variables are reliably associated in the context of the model but the exact nature of the association cannot be demonstrated.

Table 1 shows the factor loadings and the t-ratios where as table 2 shows the univariate statistics.

The distribution of the model was optimally symmetric and centred around zero suggesting no problem in the specification of the model. Based on the findings of this research the a priori model shown in Figure 1 is confirmed as the model of the host country's anti-dumping measures and its impact on international firm's pricing policy.

[FIGURE 1 OMITTED]

CONCLUSION

Results of this study show that there is a widespread agreement among the international marketers that the current anti-dumping laws are often confusing and there is a lack of clear-cut definitions of "fair" price and dumping. This is giving governments opportunity to use the measure as another non-tariff barrier. Governments are increasingly using the anti-dumping measures, often unduly, in favour of their domestic industries. The implication of this is that, to make international trade a leveller playing field WTO should try to standardise the definition and application of the anti-dumping laws among the member countries.

Though the current anti-dumping laws are generally viewed negatively by the international marketers, according to the findings of this study, they have accepted such laws as part of reality in the market place and takes appropriate strategic measures while developing their international pricing policy. Such strategic measures include, concentrating in less sensitive product categories, cooperation with local competitors and differentiation through enhanced services and trading up. These strategies reflect their perception that governments often use anti-dumping measures as a tool for voluntary restraint. Accordingly international marketers take pricing measures that are more acceptable to the local competition and government. However, such strategies are not suitable to many international marketers, particularly those from the developing countries that can compete only on the basis of low price strategies taking advantage of their generally low cost base. Further research needs to be carried out to establish whether the current anti-dumping laws disadvantage such firms.

REFERENCES

Anderson, J. E. (1992). Domino dumping, I: Competitive exporters. American Economic Review, 82(1), March, 7-19.

Aulakh, P. S. & M. Kotabe (1992). An Assessment of Theoretical and Methodological development in international marketing: 1980-1990. Journal of International Marketing, 2(1), 5028.

Bagozzi, R. P. (1994). Structural equation models in marketing research: Basic principles. In R. P. Bagozzi, (Ed.) Principles of Marketing Research. Massachusetts: Blackwell Publishers.

Bentler, P. M. (1995). EQS Structural Equation Program Manual. Multivariate Software Inc.

Bhagwati, J. (1988). Protectionism. Cambridge, Mass: The MIT Press.

Business Europe (1996, January 15). Anti-dumping Assault on 'Fortress Europe'. 4.

Byrne, B. M. (1994). Structural Equation Modelling with EQS and EQS Windows: Basic Concepts, Applications and Programming. Sage Publications.

Hair, J. F. Jr., R. E. Anderson, R. L. Latham & C. B. William (1992). Multivariate Data Analysis with Reading (3rd ed.) Macmillan.

Kostechi, M. M. (1991). Marketing strategies between dumping and anti-dumping action. European Journal of Marketing, 25(12), 7-19.

Miranda, J., Torres, R. A & T. Ruiz (1998). The International Use of Anti-dumping: 1987-1997. Geneva: World Trade Organisation.

The Australian Financial Review. Anti-dumping needs review. Retrieved June 19, 2002, from http://www.afr.com.au/editorial/20000619

The Financial Times (1993, November 25). Negotiators Down in the Dumps over U.S. Draft, 6.

World Trade Organisation. Goods: Rules on trade remedies. Retrieved July 4, 2003, from http://www.wto.org.

Syed H. Rahman, University of Western Sydney

Table 1: Factor Loadings and t-ratios

F1    Antidumping measures:                  Factor Loading    t-ratio
      (external factor)                                        (Robust)

V1    Antidumping action is often            0.554             3.884
      utilised as a tactical tool
      to foster voluntary export
      restraint (VER)

      There is huge power imbalance
V2    between plaintiffs (local              0.517             3.325
      producers) and defendants

      The concept of "fair" price
      is usually murky

V3                                           0.620             3.984

      Number of antidumping actions
      is rising.

V4                                           0.642             4.014

F2    Marketing Strategies                   Factor Loading    t-ratio
      (internal factor)                                        (Robust)

V5    Trading-up                             0.644             3.772

V6    Service enhancement                    0.628             3.401

V7    Establishment of communication         0.520             2.983
      channels with local competitors

V8    Entering into cooperative              0.532             3.120
      agreements with competitors

V9    Reallocation of the firm's             0.638             4.121
      marketing efforts from vulnerable
      products to less sensitive products

Table 2: Univariate Statistics

Variable     Mean     Standard Deviation

V1          5.4410          1.2353
V2          5.4308          1.2755
V3          5.5967          1.1161
V4          5.8667          1.1018
V5          5.8771          1.2406
V6          5.5990          1.2383
V7          5.4312          1.6575
V8          5.4340          1.5969
V9          5.8772          1.1260

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