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Journal of Agricultural & Food Industrial Organization

Ed. by Azzam, Azzeddine

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U.S. Brewing Industry Profitability: A Simultaneous Determination of Structure, Conduct, and Performance

Sanjib Bhuyan
  • Corresponding author
  • Department of Agricultural, Food and Resource Economics, Rutgers University, New Brunswick, NJ, USA
  • Email:
/ Michael McCafferty
  • Department of Agricultural, Food and Resource Economics, Rutgers University, New Brunswick, NJ, USA
  • Email:
Published Online: 2013-11-06 | DOI: https://doi.org/10.1515/jafio-2013-0008

Abstract

The U.S. brewing industry plays an important role in the U.S. economy. Although the number of firms has increased in the industry, the industry overall has remained very concentrated, with a three-firm concentration ratio of 81% in 2000 (Stack 2000). Increasing concentration in the U.S brewing industry raises public policy concerns due to the potential impact of concentration on market performance and efficiency, for example, the recent decision by the U.S. Department of Justice (DOJ) to block the proposed merger between AB–InBev and Mexico’s Groupo Modelo. Employing an improved version of the structure-conduct-performance (SCP) approach, we examine the relationship between concentration and profitability in the U.S. brewing industry. Our results support the hypothesis that market concentration impacts market performance. We, however, did not address the issue of collusive conduct or market power explicitly.

Keywords: brewing industry; SCP; oligopoly; profitability; market power

JEL Classification: L13; D43

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About the article

Published Online: 2013-11-06


For a background on the SCP approach, see Chapter 6, “Empirical Industrial Organization,” in Waldman and Jensen (2013).

According to the U.S. Department of Justice’s merger guidelines, an industry is considered “moderately concentrated” if the HHI exceeds 1,500; it is “unconcentrated” if the HHI is below 1,500 (U.S. Department of Justice 2010).

Because HHI accounts for the mean and variance of firms in the industry thereby accounting for both the number and size distribution of firms within an industry, we highlight the use of HHI index to measure market concentration in the U.S. brewing industry. For comparison with other highly concentrated industries, the HHI’s for cigarettes, breakfast cereals, and automobiles were 3,100, 2,446, and 2,506, respectively. The average index for all manufacturing industries is 91 (U.S. Department of Commerce 2012).

Similar conclusions were made in more recent studies, such as Slade (2004) and Rojas (2008).

It should be noted that there have been more than 200 horizontal mergers in the brewing industry since 1950 (Tremblay and Tremblay 2005, 187–203). This would lead one to believe that this has been a significant factor in the increase in concentration in the industry. However, macro-brewer mergers have been the exception in terms of merging and not the norm. Tremblay and Tremblay (1988) find that most mergers had little effect on the size of the major macro-brewers and therefore had little effect on industry concentration.

For a more detailed discussion of the SCP approach, its critics, and other approaches in industrial organization, please see chapter 1 of Tremblay and Tremblay (2012).

We thank one of the reviewers for constructive comments that helped strengthen this section.

MES is commonly used as a proxy for technological advancement in the manufacturing industry because technological change in the industry required greater automation (by firms) and economies of scale in production. Thus, MES is a measurement of scale economies. Examples of earlier studies using MES as a proxy for technological change include Iwasaki, Seldon, and Tremblay (2008) and Steigert, Wang, and Rogers (2009).

Interpolation of variables was done by regressing a time variable on each variable to be interpolated, i.e., once the parameters were estimated, the missing data were interpolated as a function of time. An example of the procedure is as follows:.

Data used in this study will be made available as per journal policy.

For additional details on the 2SLS (and 3SLS) approach see Wooldridge (2003).

We thank a reviewer for suggesting that we address the issue of robustness of our results.

This follows the following: A is total industry advertising, PQ is value of shipments, and δ is the elasticity of output demand with respect to advertising. This indicates that advertising to sales increases with the profitability or the Lerner index, .

On the other hand, we can expect to see a positive impact of advertising on profitability when advertising is “constructive” because such advertising increases market demand by attracting new customers and benefits all firms in the market (Tremblay and Tremblay 2012, chap. 15).


Citation Information: Journal of Agricultural & Food Industrial Organization, ISSN (Online) 1542-0485, ISSN (Print) 2194-5896, DOI: https://doi.org/10.1515/jafio-2013-0008. Export Citation

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