Browsing Doctoral Degrees (Economics) by browse.metadata.advisor "Boshoff, Willem H."
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- ItemA critical examination of collusion, the pricing behaviour of a multi-product cartel and the cartel enforcement record in South Africa(Stellenbosch : Stellenbosch University, 2021-03) Muzata, Tapera Gilbert; Boshoff, Willem H.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Economics.ENGLISH SUMMARY : In this dissertation three research questions relating to collusion and cartel enforcement in South Africa were examined. The first question entailed examining the characteristics of detected cartels, together with the institutional features of selected key South African cartels. The author found that South African cartels incorporated some of the institutional features reported in the literature, including compensation schemes, joint ventures, sub-contracting arrangements, and entry or expansion deterrence strategies. In some selected key cartels, firms participated in collusion at two successive levels of the value chain, giving the cartels greater control over pricing throughout the value chain. Communication and monitoring were found to often involve a mix of various forms, including firm-level mechanisms (notably sales infrastructure) that complemented the centralised communications mechanisms discussed in the literature. To help fully explain collusion under conditions of imperfect information, the theory should account for the complementarities among various forms of communication and monitoring used by cartels. In addition, the author found trade policy to be an inexpensive tool used by some cartels to weaken threats from imports. The second question concerned the pricing dynamics of a cartel involving multi-product firms and where the cartel faces periods of instability, producing distinct collusive phases. Like single product cartels, a multi-product cartel raises prices above competitive levels, but to varying degrees on different products. Cartel overcharges also vary over collusive phases, influenced by the demand and supply conditions in each phase. This suggests that a multi-product cartel maximises profits by imposing overcharges that vary by product and over collusive phases in response to changing market conditions. The assumptions about the nature of the transition between collusion and competition affects overcharge estimates. This dissertation provides arguments that penalties and damages estimates, reflecting overcharges, should consider product-level and phase-specific overcharges, rather than relying on averages. Finally, the dissertation examined the cartel enforcement record from a deterrence perspective, focusing on the drivers of cartel enforcement, the duration of cases from initiation to final decision, and the subsequent impact on the deterrence-effect of penalties. Leniency, settlements and penalties, supported by increased funding for the Competition Commission are considered to be the main drivers of cartel enforcement in South Africa. Contrary to expectation, the author found that these have not reduced the duration of cases. Instead, case duration increased progressively over the study period. Delays in penalising firms have resulted in firms paying significantly discounted penalties, weakening the deterrence effect of penalties. To preserve the deterrence effect of penalties, the author argues that an optimal cartel enforcement policy should account for these delays and should focus on higher present-value penalties for those firms that delay finalising cases. This dissertation, focusing on South Africa, contributes to the body of empirical literature on collusion and cartel enforcement. It provides suggestions for further advances in the theory on collusion under imperfect information and on overcharge estimation when dealing with multi-product and multi-period collusion. The dissertation also makes policy contributions that could enhance the efficacy of cartel enforcement in South Africa and in other jurisdictions.
- ItemThe 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.
- ItemMethods for aggregating microeconomic data : applications to art prices, business sentiment and historical commodity prices(Stellenbosch : Stellenbosch University, 2018-03) Binge, Laurie H.; Boshoff, Willem H.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Economics.ENGLISH SUMMARY : In the modern world, large microeconomic datasets are becoming increasingly available due to technological developments. These datasets provide an opportunity to improve the measurement of a range of economic phenomena and to bolster economic research. One particular way in which these large datasets can aid economic analysis is to allow the creation of macroeconomic indicators from aggregated microeconomic data. Yet, there are often challenges in aggregating these large datasets and in identifying the underlying pattern in the data. The aim in this dissertation is to explore aggregation methods that overcome specific challenges in aggregating three relatively large microeconomic datasets to create time-series indicators. The first case explores aggregation methods for estimating South African art price indices (2000Q1-2015Q4), using a large database of art auction prices. The challenge in aggregating this dataset is that artworks are by and large unique and infrequently traded, which means that the composition of items sold is not constant over time. To address this challenge, central tendency, hedonic and hybrid repeat sales methods are used to estimate quality-adjusted South African art price indices. The second case explores aggregation methods for estimating indicators of business confidence and uncertainty for South Africa (1992Q1-2016Q3), using the Stellenbosch University Bureau for Economic Research’s (BER) business tendency surveys. The challenge in aggregating this dataset is to measure these concepts by identifying a pattern in the disparate views of individual agents. To address this challenge, aggregation methods for capturing the full distribution of the qualitative survey responses are explored. The cross-sectional weighted first and second moments of the distribution of responses are calculated to create new indicators of business confidence and uncertainty for South Africa. The third case explores aggregation methods for estimating monthly commodity price indices for the Cape Colony (September 1889 - July 1914), using two newly digitised datasets of commodity prices for various towns in the Colony. The challenge in aggregating these datasets is that both sets of records are incomplete, in terms of the coverage of both products and towns. The repeat sales method is used to aggregate the incomplete price series for various towns from both sources, to create more complete monthly commodity price indices for the Cape Colony. Testing specific hypotheses is useful, both in demonstrating the potential research applications for the aggregated indicators, and in assessing the validity of the proposed aggregation methods. The dissertation therefore uses the time-series indicators to test a specific hypothesis in each case. The first case examines the estimated South African art price indices for evidence of a bubble. The hypothesis that South African art prices exhibited mildly explosive behaviour between 2000 and 2015 is tested. The second case examines the relationship between business sentiment and real activity in South Africa, by testing the hypothesis that there was significant comovement between the sentiment indicators and real GDP growth. The third case examines the commodity price indices, as well as indicators of price dispersion, for evidence of increasing internal market integration in the Cape Colony. The hypotheses of price convergence between towns and cointegration of regional price indices are tested. This dissertation is a contribution to the literature in that it demonstrates suitable aggregation methods to overcome some of the challenges in aggregating relatively large microeconomic datasets. These aggregation challenges relate to (i) estimating quality-adjusted price indices for unique and infrequently traded items, (ii) developing aggregate measures of sentiment based on the disparate views of a large number of respondents, and (iii) estimating complete price indices from data that is incomplete. These aggregation methods may prove useful in a variety of settings where there are similar challenges. The estimated time series may prove useful for further research in each of the relevant fields and are reported in the chapter appendices.