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An empirical analysis of the adequacy of the infrastructure delivery rate to address poverty in South Africa

  • Authors: Bosch, Adél
  • Date: 2010-10-04T08:30:21Z
  • Subjects: Infrastructure (Economics) , Poverty in South Africa , Econometrics
  • Type: Thesis
  • Identifier: uj:6914 , http://hdl.handle.net/10210/3425
  • Description: M.Comm. , Each year, in an attempt to alleviate poverty, government invests large parts of the budget to provide infrastructure to poor households in South Africa. This not only necessitates an understanding of the effectiveness of government’s infrastructure delivery rate to address poverty in South Africa, but also raises important questions on how the poor can be identified. In recent years, countries have moved away from traditional broad poverty measures such as gross national income (GNI) per capita and Human Development Index (HDI). Information on poverty and other household information are more often collected through household surveys. From these surveys, monetary and non-monetary poverty measures can be used to identify the poor. By making use of a monetary poverty measure such as expenditure, per capita household expenditure can be calculated. Households are divided into quintiles based on their per capita household expenditure, and the bottom 20 and 40 per cent are usually the benchmark for households to be identified as being poor. This is analysed in terms of the poor’s access to services and other household characteristics. Qualitative regression models have gained more recognition in econometrics, especially in the social sciences field. Information collected from household surveys is often qualitative, or binary in nature. Due to the non-linear nature of binary-dependent variable models, logit and probit models were appropriate for this study. The maximum likelihood method, within the binary choice framework, was employed to determine the extent to which infrastructure delivery and other household characteristics have an impact on poverty. The results provided empirical evidence that infrastructure investment can significantly reduce the likelihood that a household will be poor, given a set of characteristics.
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Die ekonometriese verbetering van die stochastiese vergelykings van 'n ekonometriese model : met spesifieke vermelding van stasionariteit en ko-integrasie

  • Authors: Naude, Yolanda
  • Date: 2012-08-22
  • Subjects: Econometrics , Econometric models
  • Type: Thesis
  • Identifier: uj:3003 , http://hdl.handle.net/10210/6426
  • Description: M.Comm. , The aim of this study is the econometric improvement of the stochastic equations of an econometric model with specific reference made to the explanation and incorporation of stationarity and cointegration testing. The study is based on an existing macroeconometric forecasting model. The focus of the study is not on the improvement of the specification of individual equations per se, but rather on the econometric improvement thereof, therefore changes to the specification of individual equations have only been made in cases where test results strongly recommended it. The RAU-model had previously been exposed to neither structural stability-, stationarity-, nor cointegration testing and therefore both the explanation and implementation of these tests have been included in the study. It is, however, important to note that the main purpose of both stationarity and co-integration testing is not to substitute nonstationary data with data which is proven to be stationary, but rather to identify nonstationary and non-cointegrationary data for future improvement and enhancement of the RAU model. Following the completion of the abovementioned tests, parameters have been estimated for the individual equations of the three sectors of the RAU-model (i.e. the Real-, Balance of payments-, and the Monetary sectors). Thereafter the results have been evaluated on the basis of the economic-, statistic-, and econometric evaluation criteria. In cases where econometric inconsistencies arose from the violation of the assumptions underlying the econometric tests, appropriate transformation processes have been applied in an attempt to resolve the problem. Thereafter, tests have been carried out to determine the forecasting ability of the model as well as to compare the model results with the a priori results. In general, the aim of the study, to econometrically improve the stochastic equations of the RAU model, has been achieved on the basis of overall better regression- and evaluation results that have been obtained. Following the completion of the study, a new approach to econometric modelbuilding, which makes provision for the inclusion of both stationarity- and cointegration testing, is proposed.
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An econometric estimation of the demand for clothing in South Africa

  • Authors: Seseli, Mothobi
  • Date: 2012-09-11
  • Subjects: Econometrics , Clothing trade - South Africa - Statistical methods
  • Type: Thesis
  • Identifier: uj:9951 , http://hdl.handle.net/10210/7348
  • Description: M.A. , The purpose of this study is to document and build an econometric model of the demand in the South African Clothing industry. It is important to study the clothing industry because it is labour intensive and thus its growth and development could contribute positively toward eradicating the unemployment problem in South Africa. With globalization of world economies and South Africa being a signatory to the GATT/WTO, the implications for this industry are manifold. The opening chapter lists the problem statement, identifies the method of research utilised and the relevance of the study. Chapter two looks at demand theory, particularly with regard to the quantitative techniques involved in its estimation. It focusses on regression theory and the evaluation of results generated. The third chapter gives a background to the South African clothing industry, and touches on amongst others aspects of current importance such as trade reform, international best practice and the key issues the industry has to deal with. Chapter four looks at the econometrics aspects of the study. A near perfect forecast was obtained, which attests to the stability and superiority of the model which is presented. The main findings of this study are that it is supply considerations such as the wage bill, costs of inputs (eg textile materials) etc which play an important part in the survival and prosperity of the industry. It is also reveals the fact that low productivity levels could be easily and quickly rectified through the introduction of new organizational practices and human resource development, development of quick response relationships and training to support new organizational practices. The study further and finally asserts that, while trade reform could necessitate painful adjustments the industry could actually come out a stronger world player
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Die kombinering van vooruitskattings : 'n toepassing op die vernaamste makro-ekonomiese veranderlikes

  • Authors: Ruthven, Christelle
  • Date: 2014-02-18
  • Subjects: Econometrics , Econometric models , Economic forecasting - Econometric models
  • Type: Thesis
  • Identifier: uj:4091 , http://hdl.handle.net/10210/9439
  • Description: M.Com. (Econometrics) , The main purpose of this study is the combining of forecasts with special reference to major macroeconomic series of South Africa. The study is based on econometric principles and makes use of three macro-economic variables, forecasted with four forecasting techniques. The macroeconomic variables which have been selected are the consumer price index, consumer expenditure on durable and semi-durable products and real M3 money supply. Forecasts of these variables have been generated by applying the Box-Jenkins ARIMA technique, Holt's two parameter exponential smoothing, the regression approach and mUltiplicative decomposition. Subsequently, the results of each individual forecast are combined in order to determine if forecasting errors can be minimized. Traditionally, forecasting involves the identification and application of the best forecasting model. However, in the search for this unique model, it often happens that some important independent information contained in one of the other models, is discarded. To prevent this from happening, researchers have investigated the idea of combining forecasts. A number of researchers used the results from different techniques as inputs into the combination of forecasts. In spite of the differences in their conclusions, three basic principles have been identified in the combination of forecasts, namely: i The considered forecasts should represent the widest range of forecasting techniques possible. Inferior forecasts should be identified. Predictable errors should be modelled and incorporated into a new forecast series. Finally, a method of combining the selected forecasts needs to be chosen. The best way of selecting a m ethod is probably by experimenting to find the best fit over the historical data. Having generated individual forecasts, these are combined by considering the specifications of the three combination methods. The first combination method is the combination of forecasts via weighted averages. The use of weighted averages to combine forecasts allows consideration of the relative accuracy of the individual methods and of the covariances of forecast errors among the methods. Secondly, the combination of exponential smoothing and Box-Jenkins is considered. Past errors of each of the original forecasts are used to determine the weights to attach to the two original forecasts in forming the combined forecasts. Finally, the regression approach is used to combine individual forecasts. Granger en Ramanathan (1984) have shown that weights can be obtained by regressing actual values of the variables of interest on the individual forecasts, without including a constant and with the restriction that weights add up to one. The performance of combination relative to the individual forecasts have been tested, given that the efficiency criterion is the minimization of the mean square errors. The results of both the individual and the combined forecasting methods are acceptable. Although some of the methods prove to be more accurate than others, the conclusion can be made that reliable forecasts are generated by individual and combined forecasting methods. It is up to the researcher to decide whether he wants to use an individual or combined method since the difference, if any, in the root mean square percentage errors (RMSPE) are insignificantly small.
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Econometric modelling of the demand for small, medium and large cars in South Africa

Modelling the term structure of implied volatility stock options on the JSE Limited

  • Authors: Gina, Sikelela
  • Date: 2015
  • Subjects: JSE Limited , Econometrics , Stock options , Economic forecasting
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/70329 , uj:17989
  • Description: Abstract: This paper models the implied volatility skew of the JSE Top 40 options, with the aim of producing useful forecasts for option traders based on weekly historical data over a 388 week period. The comovements of implied volatility for 51 rates moneyness, ranging from out-of-the money to in-themoney are statistically investigated. The dissertation demonstrates that the 51 rates of moneyness can be reduced to fewer dimensions of three uncorrelated variables known as principal components. These variables account for the trend, slop and curvature of the implied volatility skew, which on average, explain more than 99% of the movements of the implied volatility skew across the study sample. Instead of forecasting the volatility skew using the 51 rates of moneyness, the three principal components are forecasted using ARMA models, and results of forecasts are transformed to forecasted implied volatility. The out-of-sample accuracy of these models is tested against actual observed figures, and was found to correctly predict both the sign and magnitude 57.5% of the time. To illustrate the applicability of this research, an example was used to show the benefit of such forecast. The approach used in the research is easily transferable to the term structure as well, which can potentially give a better understanding of the entire implied volatility surface. , M.Com. (Financial Economics in Economics and Econometrics)
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Die gebruik van Almonsloerings by die skat van ekonometriese vergelykings

  • Authors: Van Wyk, Hendrik Adriaan
  • Date: 2015-02-09
  • Subjects: Econometrics , Distributed lags (Economics) , Estimation theory
  • Type: Thesis
  • Identifier: uj:13164 , http://hdl.handle.net/10210/13195
  • Description: M.Com. (Economics) , In this study the use of distributed lags in the estimation of econometric equations is discussed with special reference to Shirley Almon's model of polinomically distributed lags. In chapter 2 of this study possible reasons for the existence of distributed lags as well as a number of distributed lag models are discussed. In chapter 3 the estimation of Almon lag models with and without the existence of end restrictions is discussed with special mention of the practical problems associated with such estimations. In chapter 4 the estimation of multi-variable Almon lags and the benefit of computer programs in the estimation thereof are discussed. In chapter 5 a procedure is given for the estimation of Almon lag models with examples of the estimation of two fuctions: Investment: Private: Non-Agriculture (IPNL) and Exports Excluding Gold (XSG).
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Monetary process in South Africa : an econometric model approach

The detection of tacit collusion using agent-based modelling

  • Authors: Govender, Roverndren
  • Date: 2016
  • Subjects: Price fixing , Econometrics
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/124198 , uj:20888
  • Description: Abstract: The main aim of this study was to create a model of tacit collusion that could be used to detect such collusion. The secondary aim was to provide suggestions on how to curb tacit collusion, given the different variables that affect it. The following variables were investigated to gauge the extent of their effect on tacit collusion: demand; firms’ costs; and, finally, the number of firms’ and buyers’ suspicions regarding collusion among firms. Given the complexity of the interactions between firms and buyers, resulting from firms and buyers attempting to follow their individual rules, an agent-based model was used in the study. Agent-based models are a relatively new way of modelling complex interactions while incorporating a multitude of variables. In this way, agent-based models have an advantage over econometric models or standard simulation models, which are incapable of handling such complexity. Results from the agent-based model were consistent with economic theory and suggested that the model was calibrated correctly. A key finding was that pricing leadership behaviour occurs between firms, but that this behaviour may differ, depending on the varying attributes of the different firms. We were able to derive patterns of each such behaviour. In doing so, it was proven, in principle, that tacit collusion can be detected, and, designing an automated system to identify it was indeed possible. , M.Com.
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Multi-period portfolio optimization : a differential evolution copula-based approach

Essays on inequality and total factor productivity

  • Authors: Espoir, Delphin Kamanda
  • Date: 2020
  • Subjects: Income distribution , Econometrics , Economic development , Human capital , Industrial productivity
  • Language: English
  • Type: Doctoral (Thesis)
  • Identifier: http://hdl.handle.net/10210/485164 , uj:44090
  • Description: Abstract: This thesis investigates the effects of income inequality on Total Factor Productivity (TFP). The thesis also aims at empirically exploring the specific channels through which those effects transit. To this end, two levels of empirical analysis are carried out with time series cross-sectional data. The first is a cross-country study, while the second is a country specific case, where South Africa has been selected. It is necessary to mention here that at both levels of analysis, the investigation of this relationship is done in an essay format of four self-contained essays. The first essay (Chapter 2) utilises panel data of a sample group of 88 countries from 1990 to 2014, selected from the developed and developing world. This study seeks to answer the questions about whether income inequality affects TFP, and if so, indicate whether the effect is short- or long-term, – and determine if the effect of income inequality on TFP is the same across regions (developed and developing regions). To this end, I use econometric techniques such as panel cointegration tests, the Fully Modified Ordinary Least Squares (FMOLS) technique and the rolling window OLS regression to study the long-run relationship. I also use Granger causality test in heterogeneous mixed panels for the short-run dynamics. Overall, the results suggest that there is a negative long-run effect of income inequality on TFP only in developing countries (developing regions). Similar evidence for the case of the developed countries (developed regions) is not supported by our estimations. Additionally, the results indicate that income inequality determines TFP in the short term only in 8 countries. Since these findings establish that inequality dulls TFP in developing countries, I recommend that efforts and resources to fight inequality should be focused in developing countries rather than developed countries... , Ph.D. (Economics)
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GARCH option pricing models in a South African

On the relation between government expenditure and revenue in South Africa : An empirical investigation in a nonlinear framework

Towards an effective fiscal stimulus : evidence from Botswana

Predicting the direction of returns using binary response models : evidence from South stock markets

  • Authors: Chakhumbira, Dumiso Paul
  • Date: 2021
  • Subjects: Econometrics , Economics - Statistical methods
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/485116 , uj:44084
  • Description: Abstract: The forecasting of stock returns is an area of interest that has attracted much attention, with many authors looking to find economic and financial variables that can forecast the mean of excess returns in stock markets across different countries. South Africa is not exempt to this, with authors attempting to unearth forecastability of stock returns; the experiment has produced mixed results as some works have found evidence that stock returns are forecastable while others have failed to find evidence of forecasting ability. Some reservations regarding the use of mean forecasts exist from a perspective of asset allocation decisions. The objective of this study is to assess the performance of binary probit models in South African stock market returns. The study will use variables from the literature to forecast stock market direction from February 2003 to January 2018. This study has two objectives, to use dynamic binary model to assess the in-sample forecastability of the direction of stock market returns in South Africa; and to analyse the performance of conditional country risk improving the accuracy of the binary probit models in the study. The variables employed in this study include the South Africa MSCI country index, US 3-month Treasury bill rates, US short-term and long-term government bond yields, as well as the dividend yield and earnings yield for South African stock returns. The data was obtained from Datastream, the South African reserve bank and the Federal Reserve. The in-sample results show that certain variables are significant in explain the direction of stock returns in South Africa. Dynamic extensions of the static probit model are shown to have improved performance in forecasting the direction of stock markets and produce superior returns in trading simulations. Out-of-sample results show risk measures based on conditional residual risk produce superior forecasting performance, and the risk measures produce portfolios that outperform the buy-and-hold strategy... , M.Com. (Financial Economics)
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Socioeconomic determinants of global COVID-19 mortalities : policy lessons for current and future pandemics

  • Authors: Ngepah, Nicholas
  • Date: 2021
  • Subjects: Social determinants , Quantitative , Econometrics
  • Language: English
  • Type: Article
  • Identifier: http://hdl.handle.net/10210/489718 , uj:44661 , Citation: Ngepah N. Socio-economic determinants of global COVID-19 mortalities: policy lessons for current and future pandemics. Health Policy Plan. 2021 May 17;36(4):418-434. doi: 10.1093/heapol/czaa161. PMID: 33439993; PMCID: PMC7928932.
  • Description: Abstract: This paper examines the different socio-economic determinants of the fatalities associated with the COVID-19 pandemic globally in social determinants of health frameworks. It adapts the Poisson pseudo-maximum-likelihood (PPML) and the quantile regression techniques to effectively exploit the non-linear estimates of the data in order to derive non-biased point estimates at each quantile and make interquantile comparisons. This is particularly useful in recommending which societal variables become most significant at catastrophic levels of a pandemic like COVID-19 when existing health systems become overwhelmed. These estimators are applied to panel data for 196 countries over days of infection from the first recorded case. The COVID-19-related data is from Our World in Data, and the socio-economic variables are from the World Bank's World Development Indicators. The results establish that an improved adequate health infrastructure for both testing and treatment is necessary, but not sufficient. Health systems ultimately become overwhelmed and ineffective in managing cases and reducing mortality in the face of the rising pandemic. Complementary social, economic, physical and environmental factors are necessary for curbing deaths. These factors relate to improving the health stock of the population through reductions in both communicable and non-communicable comorbidities; enhancing sanitation and hygiene; and improving the nutrition of the population. Socio-economic and environmental measures are the reduction of household and ambient air pollution; reduction of exposure to alcohol and cigarettes; reduction of poverty and ensuring economic inclusion; and learning from the past to fine-tune governments' control measures in order to minimize harm to the population while effectively curbing mortality.
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