Dynamics of retail pricing: a case study of fluid milk
AbstractPurpose – The purpose of this paper is to present a new model to empirically analyze retail pricing dynamics led by the competition between retailers, using fluid milk markets of three US metropolitan areas as a case study. The research is important for Chinese public policy makers to find the reasons of retail price fluctuations and provides policy makers with the direction and rationale to intervene in retailing markets. Design/methodology/approach – This paper empirically applies dynamic oligopolistic competition model using Markov switching regression. The dataset used in this study includes 58 four-week-ending observations covering the period from March 1996 to July 2000 for three cities, Boston, Dallas, and Seattle. Findings – The empirical results illustrate the Markov switching regression not only successfully identifies the Markov perfect equilibrium in each market, but decomposes the retail price series into the corresponding equilibrium regimes. The forecasting power of the model is surprising so it can serve as a price monitor of the government. Additionally, the model reveals the different consumer welfare implications given different price regimes. The welfare analysis shows that consumers are most likely to be worse off through price fluctuations, while they are not always better off through a sticky (stable) price series in a market. Research limitations/implications – The first limitation of the paper is the retail price data is four-week ending. If a cycle evolves faster within four weeks, the model would overestimate the duration and underestimate the amplitude of cycles. So the study serves as an upper bound of the reality. The second limitation is the number of regimes. More than three regimes studied in a Markov switching regression may cause a series of empirical issues. However, if we integrate several regimes into one regime, we will lose rich information about the competitiveness of the markets. Practical implications – This paper is the first work to apply the dynamic pricing analysis to food industry by using fluid milk market as a case study. This paper empirically identifies four retail pricing regimes in fluid milk price series and evaluates the characteristics of the regimes. Social implications – This paper assesses the welfare implications of each pricing regime. The results show that the forecasting power of the model is strong in fluid milk retail market. Therefore, the study could serve as a price monitor to the public policymaker. Originality/value – This paper presents the first study to apply dynamic oligopolistic competition model to food marketing research. JEL classification: D24, Q16, O47
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Bibliographic InfoArticle provided by Emerald Group Publishing in its journal China Agricultural Economic Review.
Volume (Year): 3 (2011)
Issue (Month): 2 (May)
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Find related papers by JEL classification:
- D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
- O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Chung-Huang Huang & Ping-Yi Huang & Yuan-Yun Ling, 2009. "Pesticide use and the effect of trade liberalization on environment for rice production," China Agricultural Economic Review, Emerald Group Publishing, vol. 1(1), pages 58-72, February.
- Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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