Browsing by Author "Van Jaarsveld, Rossouw"

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    The econometrics of discrete structural change and its applications in models of price overcharge
    (Stellenbosch : Stellenbosch University, 2021-03) Van Jaarsveld, Rossouw; Boshoff, Willem H.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Economics.
    ENGLISH SUMMARY : This dissertation studies unexplored time series issues related to tests of structural change and the modelling thereof. The practical application is centred around the estimation of price effects in collusive markets. The results, however, is more generally relevant, since structural change is inherent in many economic relationships. The dissertation is organized into three main chapters. The first part deals with the dating of structural breaks, i.e. determining the dates of structural breaks. The second part deals with the impact of non-stationarity when modelling structural changes. The third part deals with a practical application and provides guidance for practitioners. In cases where the date of the structural change is unknown, two econometric approaches can be followed. One method, is to apply a regime-switching or time varying-parameter model. The second approach is to use structural break tests to determine the break dates, and subsequently construct a dummy variable to control for the breaks in a regression model. In the first part, we investigate how various structural break tests can translate into parameter bias. The results are contrasted to regime-switching and time varying-parameter models to better understand the conditions under which these two approaches can be used interchangeably. Given that structural change may take various forms, we investigate the comparative performance of multiple techniques on different forms of structural change. Specically, we evaluate various forms of changes in the mean of the data generating process. To assess the performance of these methods, we rely on simulation evidence. Related, we also discuss complications of numerical optimization techniques and regime-switching models in simulation studies. The results are discussed in the framework of overcharge, where parameter estimates play a central role in the punishment of cartels. The second part deals with the impact of nonstationarity on dummy variable coecients. This part provides evidence for the conditions under which the distribution of the dummy variable parameter will differ significantly from the t-distribution. This is important since time series models are used in civil litigations by plaintiffs who are required to prove that the cartel had a significant impact on prices. Congruent with the first part, we illustrate how incorrect conclusions can be reached when the dummy variable is misspecified and t-statistic are used to draw inference. In other words, when the break dates are misdated and the nonstationary nature of the data caused the distribution of the dummy variable parameter to differ from the t-distribution. Related, we show how cointegration tests are influenced when the break dates are misspecified. We provide a discussion of the extent to which error correction modelling can be used to address some of these issues and emphasize specification problems that are specific to the estimation of overcharge. To demonstrate the practical insights of the simulation studies in the first and second part, I apply the various techniques to a European competition case. This part also provides guidance for practitioners.