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A forecasting approach to estimating cartel damages : The importance of considering estimation uncertainty

In this study, I consider the performance of simple forecast models frequently applied in counterfactual analysis when the information at hand is limited. Furthermore, I discuss the robustness of the standard t-test commonly used to statistically detect cartels. I empirically verify that the standard t-statistics encompasses parameter estimation uncertainty when one of the time series in a two-sided t-test has been estimated. Thereafter, I compare the results with those from a corrected t-test, recently proposed, where the uncertainty has been accounted for. The results from the study show that a simple OLS-model can be used to detect a cartel and to compute a counterfactual price when data is limited, at least as long as the price overcharge inflicted by the cartel members is relatively large. Yet, the level of accuracy may vary and at a point where the data used for estimating the model become relatively limited, the model predictions tend to be inaccurate.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:sh-41021
Date January 2020
CreatorsProhorenko, Didrik
PublisherSödertörns högskola, Nationalekonomi
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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