The article is devoted to problem of detection of overt or tacit collusion equilibrium in the context of choice of the appropriate econometric method, which is determined by the amount of information that the observer possesses. As a particular method to be used we have chosen a collusion marker coherent with an equilibrium of the proper model of strategic interaction – the presence of structural disturbances in the price process variance for phases of collusion and competition. We than used a proper econometric tool, namely Markov Switching Model with switching in variance regimes in order to verify its functionality in a context of a research. We applied the model to cement industry of India in a period of 1994–2009. We have reached some promising effects in discovery of collusion and competition phases, partially confirmed by facts from functionality of the industry and by reference research.
explicit and tacit collusion, collusive equilibrium, cartel detection, cement industry, price variance, Markov switching model
[1] Abrantes-Metz R., Froeb L., Geweke J., Taylor C., (2006), A variance screen for collusion, International Journal of Industrial Organization 24, 467-486.
[2] Anand S., (2009), Identifying cartels using economic evidence, a case study of Indian cement industry, Competition Commision of India, New Delhi.
[3] Athey S., Bagwell K., Sanchirico C., (2004), Collusion and price rigidity, Review of Economic Studies, 71, 317-349.
[4] Bejger S., (2009), Ekonometryczne narzedzia detekcji równowagi zmowy w branzy, AUNC Ekonomia XXXIX, 125.
[5] Bejger S., (2010), Collusion and seasonality of market price – a case of fixed market shares, Business and Economic Horizons, 2, 48-59.
[6] Bejger S., (2010a), Detekcja równowagi zmowy w branzy z wykorzystaniem analizy falkowej – model teoretyczny, AUNC Ekonomia XLI, 7-26.
[7] Bejger S., Bruzda J., (2010), Detekcja równowagi zmowy w branzy z wykorzystaniem analizy falkowej – weryfikacja empiryczna, AUNC Ekonomia XLI, 27-42.
[8] Bejger S., (2011), Polish cement industry cartel – preliminary examination of collusion existence, Business and Economic Horizons, 4, 88-107.
[9] Bolotova Y., Connor J.M., Miller D.J., (2008), The impact of collusion on price behavior: Empirical results from two recent cases, International Journal of Industrial Organization 26, 1290-1307.
[10] Cement Manufacturer Association Annual Report 2009-10, dokument elektroniczny: http://www.cmaindia.org/portal/static/AnnualReport2009-10.pdf.
[11] Connor J., Helmers G., (2006), Statistics on modern private international cartels, 1990-2005, Dept. of Agricultural Economics, Purdue University, Working Paper #06-11.
[12] Davidson J., (2004), Forecasting Markov-switching dynamic, conditionally heteroscedastic processes, Statistic and Probability Letters, 68(2), 137-147.
[13] Hamilton J.D., (1989), A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica 57, 357-384.
[14] Hamilton J.D., Susmel R., (1994), Autoregressive conditional heteroscedasticity and changes in regime, Journal of Econometrics 64, 307-333.
[15] Harrington J.E., (2005), Detecting cartels, working paper, John Hopkins University.
[16] Konkluzje postanowienia MRTPC, dokument elektroniczny: http://www.baionline.in/media/data/MRTP2.pdf.
[17] Krolzig H.M., (1998), Econometric Modelling of Markov-Switching Vector Autoregressions us-ing MSVAR for Ox, Working paper.
[18] Maskin E., Tirole J., (1988), A theory of dynamic oligopoly II, Econometrica 56, 571-599.
[19] Piłatowska M., (2003), Modelowanie niestacjonarnych procesów ekonomicznych. Studium metodologiczne, Wydawnictwo UMK, Torun.
[20] Rotemberg J., Saloner G., (1990), Collusive price leadership, The Journal of Industrial Economics, 39, 93-111.