Abstract
The present study estimates the degree of market power in the major US beef and pork export destinations. The recently developed stochastic frontier (SF) estimator is used. Estimations of market and time-specific Lerner indices are provided. Balanced panel data between 1980 and 2011 were employed. The average Lerner index is 39% for the US beef exports and is the highest in the markets of ASEAN, Hong Kong/China, Japan, South Korea, and Taiwan. For the US pork exports, the average Lerner index is 16% and is the highest in the markets of Mexico and Taiwan.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The present work concentrates on the measurement of the degree of market power exerted by the US meat packers and does not account for bilateral oligopoly power.
Vertically integrated agribusiness firms are able to exercise oligopoly power in the domestic and/or the export markets. The goal of the present study is to examine the exertion of oligopoly power in international meat export markets. Panagiotou and Stavrakoudis (2017, 2018) and Lopez et al. (2018) have employed the stochastic frontier methodology in order to obtain market power estimates for the domestic meat industry.
Kumbhakar et al. (2012) point out that modeling approach can be applied to estimate the mark-up in output markets in any industry. Accordingly, the present study adopts their modeling to the estimation of market power in the US meat industry, where the output is the products of beef and pork. In the seminal article, the authors utilize a panel data: annual observations on sawmilling firms for the period 1974–1991. Likewise, the present study employs a panel data set as well: annual observations on the US major exporting meat markets for the period 1980–2011. The stochastic frontier estimator of market power is produced following the methodology of the seminal paper.
In the present study, the number of major export markets are twelve for the case of the US beef exports and eleven for the case of the US pork exports.
According to the GATS-FAS, for the beef exports, the leading export destinations for the market of Central/South America are the countries of Chile, Peru, Colombia, Guatemala, Honduras, and El Salvador; for the ASEAN market, the countries of Indonesia, Philippines, and Vietnam; for the market of EU(28), the countries of Netherlands, Italy, and Germany; for the Caribbean market, the countries of Dominican Republic, Jamaica, and the Bahamas; for the market of the Middle East, the countries of Egypt, the United Arab Emirates, and Kuwait; and for the market of Africa the countries of South Africa, Cote D’Ivoire Angola, and Gabon.
According to the GATS-FAS, for the pork exports, the leading export destinations for the market of Central/South America are the countries of Colombia, Chile, Peru, Honduras, Guatemala, and Panama; for the ASEAN market, the countries of Philippines, Singapore, and Vietnam; for the market of EU(28), the countries of UK, Germany, and Netherlands; for the Caribbean market, the countries of Dominican Republic, the Bahamas, and Trinidad and Tobago; and for the market of Oceania, the countries of Australia and New Zealand.
Variable Yit is endogenous since it is a component of the dependent variable in Eq. 8. In order to solve the problem of endogeneity, we adopt the methodology by Panagiotou and Azzam (2010), where beef exports are modeled as a two stage game. In the first stage, the exported quantity is determined, whereas in the second stage of the game, price is determined. In the empirical part of their study, Panagiotou and Azzam (2010) treat the exported quantity of beef as exogenous. This study adopts the same setting.
The present study has estimated the costs of producing beef and pork, for the domestic and the export markets, respectively.
A table of the calculated distances can be also found in the online Supplementary Material.
Frozen, chilled, prepared, and/or preserved beef are some of the products that were reported for the years 2004–2006.
References
Arnade C, Pick D, Gopinath M (1998) Testing oligopoly power in domestic and export markets. Appl Econ 30(6):753–760
Baltagi BH (2013) Econometric analysis of panel data, 5th edn. Wiley, New York
Coelli T, Henningsen A (2013) Frontier: stochastic frontier analysis. Available at: http://CRAN.R-Project.org/package=frontier
Felt M-H, Gervais J-P, Larue B (2011) Market power and import bans: the case of Japanese pork imports. Agribusiness 27(1):47–61
Henneberry SR, Mutondo JE (2009) Agricultural trade among NAFTA countries: a case study of US meat exports. Review Agricultural Econ 31(3):424–445
Kumbhakar SC, Baardsen S, Lien G (2012) A new method for estimating market power with an application to Norwegian sawmilling. Review of Industrial Organization 40(2):109–129
Kumbhakar SC, Lovell CK (2003) Stochastic frontier analysis. Cambridge University Press, Cambridge
Lopez RA, He X, Azzam A (2018) Stochastic frontier estimation of market power in the food industries. J Agricultural Econ 69(1):3–17
Miljkovic D, Marsh JM, Brester GW (2002) Japanese import demand for US beef and pork: effects on US red meat exports and livestock prices. J Agricultural Appl Econ 34(3):501–512
Miljkovic D, Brester GW, Marsh JM (2003) Exchange rate pass-through, price discrimination, and US meat export prices. Appl Econ 35(6):641–650
National Bureau of Economic Research–Manufacturing Industry Database (2017) NBER-CES Manufacturing Industry Database. Available at: http://www.nber.org/nberces/. –Accessed Sept 2017
Norwood FB, Lusk JL (2018) Agricultural marketing and price analysis. Waveland Press, Long Grove
Panagiotou D (2008) Trade bans, imperfect competition and welfare: BSE and the US beef industry. ETD collection for University of Nebraska - Lincoln. AAI3315057. Available at: http://digitalcommons.unl.edu/dissertations/AAI3315057
Panagiotou D (2018) Collusion-enhancing effects of the own-and cross-price demand elasticities in merging multiproduct food industries: the case of chicken and red meat in the United States. Outlook on Agriculture 47(3):223–232
Panagiotou D (2019) Market power effects of the livestock mandatory reporting act in the US meat industry: a stochastic frontier approach under uncertainty. J Industry Compet Trade 19(1):103–122
Panagiotou D, Azzam AM (2010) Trade bans, imperfect competition, and welfare: Bse and the US beef industry. Canadian Journal of Agricultural Economics/Revue canadienne d’agroeconomie 58(1):109–129
Panagiotou D, Stavrakoudis A (2017) A stochastic production frontier estimator of the degree of oligopsony power in the US cattle industry. J Industry Compet Trade 17(1):121–133
Panagiotou D, Stavrakoudis A (2018) A stochastic frontier estimator of the aggregate degree of market power exerted by the US meat packing industry. J Industrial Business Econ 45(3):387–401
Plain R (2014) Economic impact of U.S. pork trade, 1986-2014. Available at: https://agebb.missouri.edu/mkt/exportUSpaper.htm. Working paper, University of Missouri-Columbia Accessed November, Accessed November 2017
R Core T (2017) R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2014
Reed M, Iswariyardi A (2001) Competitive forces in the Japanese beef market. In: Annual meeting of the international agricultural trade research consortium (IATRC), Auckland, New Zealand
Reed MR, Saghaian SH (2004) Measuring the intensity of competition in the Japanese beef market. J Agricultural Appl Econ 36(1):113–121
Scalco PR, Lopez RA, He X (2017) Buyer and/or seller power? An application to the Brazilian milk market. Appl Econ Lett 24(16):1173–1176
United States Department of Agriculture – Economic Research Service (2017) Livestock and meat international trade data. Available at: https://www.ers.usda.gov/data-products/livestock-and-meat-international-trade-data/. Accessed Sept 2017
United States Department of Agriculture – Foreign Agricultural Service (2017) Global agricultural trade system. Available at: https://apps.fas.usda.gov/gats/default.aspx. Accessed Oct 2017
U.S. Meat Export Federation (2017) Statistics and trade access-export statistics. Available at: https://www.usmef.org/usmef-statistics-and-trade-access/export-statistics/. Accessed Sept 2017
U.S. Meat Export Federation (2019) Statistics and trade access-export statistics. Available at: https://www.usmef.org/export-resources/u-s-suppliers/. Accessed July 2019
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Panagiotou, D., Stavrakoudis, A. A Stochastic Frontier Analysis Approach for Estimating Market Power in the Major US Meat Export Markets. J Ind Compet Trade 20, 569–586 (2020). https://doi.org/10.1007/s10842-019-00319-y
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10842-019-00319-y