Testing for market power in multi-product industries across multiple export markets.

• Author: Yerger, David B.

1. Introduction

   A large body of theoretical literature has developed in the past 15 years incorporating various models of imperfect competition into international trade theory.(1) Empirical work testing for imperfect competition in export markets, however, has been much more limited. In particular, the empirical evidence in support of widespread imperfect competition in U.S. export and import sectors is somewhat scant and mixed.(2) One technique for assessing the existence of market power in export markets has been developed by Knetter [33] who estimated a reduced form single equation in which the export price to a specific market for a good was a function of the exchange rate, a country specific dummy variable, and a time dummy. Knetter rejected the null hypothesis of perfectly competitive markets in nearly all of the U.S. and German export markets studied.(3) His methodology has been adopted by other researchers who have rejected the perfect competition hypothesis in other U.S. export markets.(4)

   While this technique has the admitted advantage of requiring minimal data for hypothesis testing, it also suffers some shortcomings which limit the insights into an export sector's market structure that it can provide. The technique cannot distinguish between marginal cost pricing across export markets and marginal cost plus constant mark-up pricing. This limits the conclusions one can draw from such analysis. Another limitation of the analysis is that even when marginal costs are equal across markets, the results only permit one to accept or reject the hypothesis of perfect competition. No insights regarding the magnitude of the price markups, the similarity of industry pricing to monopoly pricing, the sources of the market power, or the variation in market power across destination markets are provided by the results.

   This paper addresses the above issues by extending the methodologies of the "New Empirical Industrial Organization" (NEIO)(5) approach to testing for market power in domestic markets. The extension allows one to simultaneously analyze industry behavior in both domestic and export markets. This paper's specific contribution to the literature utilizing NEIO techniques to analyze international markets is the development of a reasonably straight-forward model which links an industry's factor and goods markets. A short-run multi-product, multi-factor cost function is simultaneously estimated along with multiple country-specific export demand and firm supply curves. The model permits a number of interesting market structure questions to be addressed including:

   i. Testing on a destination-specific basis the hypotheses of both perfectly competitive and monopoly pricing behavior by firms in the industry.

   ii. Estimates on a destination-specific basis of the degree of markup by firms over their marginal costs, and of the relative importance of the markets' demand structures (how inelastic) versus the competitive behavior of the firms in establishing the markup.

   iii. Testing for changes in the degree of markup over time and for the source of the change in markup: changes in demand elasticity versus firm behavior.

   Although some prior work has utilized a multi-product cost function framework, output was simply divided into domestic and aggregate export markets [9]. Existing work modelling country specific export demand and firm supply curves has not directly linked the factor and goods markets equilibrium through information on factor prices and usage levels [4; 5].

   The model is used to examine the pricing behavior of the U.S. non integrated wood pulp industry (SIC 2611) over the period 1963-1987. The key results of this study relate to the different conclusions drawn about the prevalence of market power in U.S. wood pulp exports depending upon the method of analysis. Results from the single-equation analysis indicate widespread imperfect competition in U.S. exports for one of the pulp types modelled: pulp derived from dissolving chemical processes. For the other good modelled, pulp derived from sulphate based processes, the single equation analysis does not produce either a clear rejection or acceptance of the hypothesis that U.S. exporters price above marginal cost. In contrast, the structural model's estimates suggest that export pricing above marginal cost was widespread across markets for both types of pulp. Within any given export market, however, the margin on pulp derived from dissolving chemical processes exceeded the margin on pulp derived from sulphate based processes. This information on the export margin differences was not revealed by the single equation analysis.

   Section II highlights important characteristics of the U.S. wood pulp export industry and reports the results of the reduced form single equation approach to testing for market power in U.S. wood pulp exports. In section III the structural model is developed which permits the econometric identification of the degree of market power in U.S. chemical pulp and sulphate pulp exports. Section IV reviews the data used in the model's estimation, results are presented in section V, and a summary of the major findings along with concluding remarks are in section VI.

2. The U.S. Wood Pulp Industry

   The output from U.S. non integrated wood pulp mills (SIC 2611) can be divided into three 5 digit SIC categories: pulp from dissolving chemical processes, pulp from dissolving sulphate processes, and pulp from dissolving sulphite processes. Chemical pulp is used as an input in producing higher valued specialty papers while the sulphate and sulphite pulps are used in the production of lower valued newsprint and cardboard production. The average export prices and their share in the export bundle are shown in Figures 1 and 2 for each of the pulp types. Not surprisingly, chemical pulp prices are higher across the sample period 1963-87, but note how closely tied the sulphite and sulphate prices remain over the sample. The other key point is that sulphate pulp's share of the total export bundle steadily increased over the period as chemical pulp's share declined while sulphite pulp remained a very minor component of the bundle.

   Given the shifting composition of the export bundle, estimating the industry's output as an aggregated 4-digit good could introduce estimation errors, particularly if the composition of the export bundle varies across destination markets. Consequently, in the structural model developed in section III output is divided into two types: pulp from dissolving chemical processes (hereafter chemical pulp), and pulp from either dissolving sulphate or sulphite processes (hereafter sulphate pulp). This division reflects the goods different end-product uses and effectively folds the minor sulphite pulp category in with the dominant sulphate pulp product.(6)

   The non integrated wood pulp industry was selected for analysis because exports are an important share of output (approximately 35%), these exports are diversified across many markets, and the competitiveness of the industry has a number of policy implications. Perfectly competitive markets have been assumed in a number of models of global wood products trade [1; 14; 20], but the appropriateness of the assumption has been questioned by some researchers(7) so the findings of this study may be of interest to those involved in global modelling of the wood products sector.

   Knetter [33] tests for imperfect competition by estimating the following equation for each good modelled:

   ln [p.sub.it] = [[Theta].sub.t] + [[Gamma].sub.i] + [[Beta].sub.i] ln [s.sub.it] + [u.sub.it] (1)

   where

   [p.sub.it] is the pre transportation and shipping price in $'s of U.S. exports to country i at time t, [[Theta].sub.t] is a time effect,

   [[Gamma].sub.i] is a country effect,

   [s.sub.it] is the bilateral exchange rate in foreign currency units per $,

   [u.sub.it] is the regression disturbance.

   Table I. Results of Single Equation Estimation of Price Discrimination across Export Markets

   [[Gamma].sub.i] [[Beta].sub.i]

   Chemical Pulp

   Argentina -.504(*) (.022) .020(*) (.004) Austria .013 (.021) .189(*) (.060) Belgium -.358(*) (.020) .048 (.073) Brazil .084(*) (.021) .011(*) (.005) Canada -.465(*) (.026) .234 (.142) France .020 (.020) -.089 (.070) India -.399(*) (.020) .056 (.055) Italy .052(*) (.023) -.058 (.038) Japan -.405(*) (.020) .072 (.060) Mexico -.010 (.022) .032 (.021) Netherlands -.407(*) (.021) .054 (.070) Spain .075(*) (.021) -.074 (.042) U.K. -.470(*) (.022) .072 (.062) West Germany .081 (.053) Yugoslavia -.435(*) (.020) .019 (.012)

   Sulphate Pulp

   Argentina .034 (.028) .020(*) (.003) Australia .050 (.026) -.336(*) (.093) Belgium -.034 (.025) .009 (.089) Brazil .178(*) (.026) -.024(*) (.006) Canada -.060 (.032) .168 (.176) France -.011 (.044) .013 (.089) Italy -.002 (.030) -.042 (.049) Japan -.022 (.025) -.070 (.071) Mexico -.041 (.027) -.023 (.014) Netherlands -.024 (.028) .005 (.007) South Korea -.141(*) (.025) -.044 (.037) Spain .012 (.027) .024 (.053) U.K. .002 (.027) -.083 (.076) Venezuela -.099(*) (.025) .034 (.061) West Germany .031 (.063)

   * Indicates significance at the 5% level

   Standard errors in parentheses. Parameter estimates are from estimating equation (1) in paper. Under the assumption of constant marginal cost for a good across destination markets, three different market structure hypothesis can be tested using equation (1).(8) Under the null of perfect competition, both [[Gamma].sub.i] and [[Beta].sub.i] equal zero since [[Theta].sub.t] captures all marginal cost effects over time. Under the null of imperfect competition with constant elasticity of demand, [[Gamma].sub.i] can be non zero since mark-ups can vary across markets but [[Beta].sub.i] still equals zero. Lastly, under the null of imperfect competition with non constant elasticity of demand both [[Gamma].sub.i] and [[Beta].sub.i] can be non zero.

   As a point of reference for the structural model estimation, equation (1) was estimated for...