Browsing Doctoral Degrees (Economics) by browse.metadata.advisor "Du Plessis, Stan A."
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- ItemThe South African business cycle and the application of dynamic stochastic general equilibrium models(Stellenbosch : Stellenbosch University, 2014-12) Kotze, Kevin Lawrence; Du Plessis, Stan A.; Smit, Ben W.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Economics.ENGLISH ABSTRACT: This dissertation considers the use of Dynamic Stochastic General Equilibrium (DSGE) models for the analysis of South African macroeconomic business cycle phenomena. It includes four separate, but interrelated parts, which follow a logical sequence. The rst part motivates the use of these models before establishing the theoretical foundations for these models. The theoretical foundations are accompanied by detailed derivations that are used to construct a model for a small open economy. The second part considers the properties of South African macroeconomic data that may be used to estimate the parameters in these models. It includes a discussion of the variables that may be included in such a model, as well as various methods that may be used to extract the business cycle. Thereafter, the sample size for the dataset is established, after investigating for possible structural breaks in the rst two moments of the data, using various univariate and multivariate techniques. The nal chapter of this part contains an investigation into the measures of core in ation, whereby a comparison of trimmed means, dynamic factor models and various wavelet decompositions are applied to data for South Africa. The third part considers the application of the dataset that was identi ed in part two, in a DSGE model that incorporates features that are typical of small open economies. It includes a discussion that relates to the role of the exchange rate in these models, which is found to contain key information. In addition, this part also includes a optimal policy investigation, which considers the reaction function of central bank. The nal part of this thesis considers more recent advances that have been applied to DSGE models for the South African economy. It includes an example of a nonlinear model that is estimated with the aid of a particle lter, which is then used for forecasting purposes. The forecasting results of both linear and nonlinear versions of the model are then compared with the results from various Vector Autoregression (VAR) and Bayesian VAR models.