The impact of market deregulation on milk price: A dynamic panel data approach

Fotis, Panagiotis and Polemis, Michael (2018): The impact of market deregulation on milk price: A dynamic panel data approach.

Abstract

The scope of this paper is to investigate the impact of market deregulation on the competitiveness of raw milk producers in Greece along the suggested lines of OECD (OECD, 2014). The study uses a dynamic panel data approach, to assess changes in the relative competitiveness of milk producers as a result of certain deregulation policies imposed by the Greek government in two phases (May 2014 and September 2015). In order to account for the presence of cross-sectional dependence and non-stationarity, the empirical analysis implements novel panel econometric methodology namely Common Correlated Effects (CCE) and Augmented Mean Group estimators (AMG). Our sample uses micro level data drawn from the 45 Greek regions spanning the period from January 2010 to October 2017. By comparing the wholesale prices of milk affected by regulation before and after the policy changes, we infer that abolishing regulation led to an increase in the prices of the wholesalers and thus in their profitability levels. Moreover, we argue that the openness of the relevant milk market segment had significant implications to the level of competition in the sector. Lastly, our empirical findings which confirm the OECD competition guidelines in the milk sector remain rather robust under different empirical methodologies and sample splitting, providing a focal point to policy makers and government officials for the ex-post evaluation of the deregulation strategies.

• Item Type: MPRA Paper
• Language: English
• Keywords: Deregulation, Competition; Milk price, Dynamic panel models, OECD
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C23 - Panel Data Models ; Spatio-temporal Models; L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance; L - Industrial Organization > L5 - Regulation and Industrial Policy > L51 - Economics of Regulation; L - Industrial Organization > L5 - Regulation and Industrial Policy > L52 - Industrial Policy ; Sectoral Planning Methods

References

Abito, J.,Besanko, D., and Diermeier,D. (2016). Corporate Reputational Dynamics, Private Regulation, and Activist Pressure. Strategy Beyond Markets. Advances in Strategic Management,34: 235–299.

Albæk, S, Møllgaard P., and Overgaard P.B (1997). Government-Assisted Oligopoly Coordination? A Concrete Case. Journal of Industrial Economics, 45(4): 429-443.

Apergis, N. (2016). Environmental Kuznets curves: New evidence on both panel and country-level CO2 emissions. Energy Economics 54(C): 263-271.

Bouamra-Mechemache, Z., Requillart, V., Coregalori, C., Trevisiol, A. (2008). Demand for diary products in the EU. Food Policy, 33: 644-656.

Bond, S., and Eberhardt, M. (2009). Cross-section dependence in nonstationary panel models: a novel estimator. MPRA Paper 17692, University Library of Munich, Germany.

Carranza, J.E, Clark, R., and Houde, J.F. (2015). Price controls and market structure: Evidence from gasoline retail markets. Journal of Industrial Economics, 63(1):152-198.

Choi, I. (2001). Unit root tests for panel data. Journal of International Money and Finance,20(2): 249-272,

Choi, Chi., Young, Ling Hu and Masao Ogaki (2008), Robust Estimation for Structural Spurious Regressions and a Hausman-type Cointegration Test. Journal of Econometrics, 142, 327-351.

Chudik, A. and M. H. Pesaran (2015) Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics, 188, 393–420.

Coakley, Jerry, Ana-Maria Fuertes and Ron P. Smith (2006). Unobserved heterogeneity in panel time series models. Computational Statistics & Data Analysis,0(9): 2361-2380.

Davis, L.W. and KilianL. (2011). The Allocative Cost of Price Ceilings in the U.S. ResidentialMarket for Natural Gas. Journal of Political Economy, 119(2): 212-241.

Eberhardt, M., and Teal F. (2010). Productivity Analysis in Global Manufacturing Production. Economics Series Working Papers 515, University of Oxford, Department of Economics.

Fotis, P., and Polemis, M. (2018). Sustainable development, environmental policy and renewable energy use: A dynamic panel data approach. Sustainable Development, (forthcoming).

Fotis, P., Karkalakos, S. and Asteriou, D., (2017). The relationship between energy demand and real GDP growth rate: the role of price asymmetries and spatial externalities within 34 countries across the globe. Energy Economics. 66, 69-84.

Genakos, C., Koutroumpis, P. and Pagliero, M. (2018) The impact of maximum markup regulation on prices. Journal of Industrial Economics (forthcoming).

Halkos, G., and Polemis M. (2017). Does financial development affect environmental degradation? Evidence from the OECD countries. Business Strategy and the Environment, 26(8): 1162–1180.

Hendel, I., Lach, S and Spiegel. Y (2017). Consumers' activism: the cottage cheese boycott. Rand Journal of Economics, 48(4): 972-1003.

Im, K.S, Pesaran, M.H., Shin Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics,115(1): 53-74.

Kahal, Y (2011). Examination of the Need for Regulation on Dairy Products. Ministry of Agriculture and Rural Development,2011.

Kao C. (1999). Spurious regression and residual-based tests for cointegration in panel data.Journal of Econometrics 90:1–44.

Kao, C. and Chiang, M. H (2000). On the estimation and inference of a cointegrated regression in panel data. Advances in Econometrics 15, 179-222.

Kapetanios, G., Pesaran, M.H., and Yamagata. T. (2011) Panels with non-stationary multifactor error structures.Journal of Econometrics,60(2): 326-348.

Katsoulacos, Y., Konstantakopoulou, I., MetsiouE., and Tsionas.E. (2014). Quantitative Price Tests in Antitrust Market Definition with an Application to the Savory Snacks Markets. Journal of Agricultural and Food Industrial Organization, 12(1): 1–33.

Lewandowski, P. (2006). PESCADF: Stata module to perform Pesaran's CADF panel unit root test in presence of cross section dependence. Statistical Software Components S456732, Boston College Department of Economics.

Maddala, G.S. and Wu, Shaowen. (1999). A Comparative Study of Unit Root Tests With Panel Data and A New Simple Test. Oxford Bulletin of Economics and Statistics 61, 631-652.

Merryman, S. (2004). XTFISHER: Stata module to compute Fisher type unit root test for panel dataStatistical Software Components S448201, Boston College Department of Economics.

OECD (2014). OECD Competition Assessment Reviews: Greece, OECD Publishing.http://dx.doi.org/10.1787/9789264206090-en.

Ofek, Y. (2012). The Influence of Maximum Price Regulation Removal on Milk Products Prices in Israel During the Period1999–2011. Mimeo, 2012.

Pedroni P. (1999). Critical values for cointegration tests in heterogeneous panels withmultiple regressors. Oxford Bulletin of Economics and Statistics, 61:653–70.

Pedroni, P. (2000). Fully Modified OLS for HeterogeneousCointegrated PanelsInNonstationary Panels, Panel Cointegration and Dynamic Panels. Advances in Econometrics,edited by Badi H. Baltagi, T. B. Fomby, and R. C. Hill, Vol. 15,93–130.

Pedroni, P. (2001). Purchasing Power Parity Tests in CointegratedPanels.Review of Economics and Statistics 83:727–31.

Pesaran, M.H (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4): 967-1012.

Pesaran, M.H., and Smith, R.P. (1995). Estimating long-run relationships from dynamic heterogeneous panels.Journal of Econometrics,68(1): 79-113.

Pesaran, H., (2003). A Simple Panel Unit Root Test in the Presence of Cross Section Dependence, Cambridge Working Papers in Economics 0346.

Pesaran, M.H, (2015). Time Series and Panel Data Econometrics. Oxford University Press.

Phillips, P.C.B., and Loretan, M. (1991). Estimating Long-run Economic Equilibria. Review of Economic Studies, 58(3): 407-436.

Phillips, P. C. B., and P. Perron. (1988). Testing for a Unit Root in aTime Series Regression. Biometrika 75:335–346.

Phillips, P.C.B., Sul, D., (2003). Dynamic panel estimation and homogeneity testing under cross section dependence. The Econometrics Journal 6, 217–259. Regulation (EC) No 853/2004 of the European Parliament and the Council of 29 April 2004, OJ L139/55 (laying down specific hygiene rules for on the hygiene of foodstuffs). Regulation (EC) No 852/2004 of the European Parliament and the Council of 29 April 2004, OJ L139/1.

Roodman, David (2009) 'A Note on the Theme of Too Many Instruments', Oxford Bulletin of Economics and Statistics, Department of Economics, Vol. 71(1), pp.135-158.

Saikkonen, P, (1991). Asymptotically Efficient Estimation of Cointegration Regressions.Econometric Theory,7(01): 1-21.

Stock, J H., and M W. Watson (1993). A simple estimator of cointegrating vectors in higher order integrated systems. Econometrica 614, 783-820.

Westerlund J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics. 69:709–48.

Wilson, R.R., and Thompson, G.R. (1967). Demand, Supply, and Price Relationships for the Dairy Sector, Post-World War II Period. Journal of Farm Economics, 49(2): 460-71.

Viscusi, W.K., Vernon, J.M. and Harrington, J.E (2005). Economics of Regulation and Antitrust, Fourth Edition. MIT Press.