Thesis (MBA)--Stellenbosch University, 2000. / ENGLISH ABSTRACT: In this paper the effectiveness of "transplanting" a particular methodology of a probabilistic approach is assessed in a South African economic context. The methodology makes use of leading indicators which are used in regression models, with a dichotomous response variable, assuming values of 0 or 1 to indicate expansion or contraction of economic activity. The backbone of the study closely replicates the work of Nazmi (1993) and his work on turning point prediction. The recorded results indicate an ability of the model to accurately forecast businesscycle turning points in the 1980s. In the period of the 1990s, the model displays a diminished capacity to forecast the turning points with acceptable accuracy. Leading indicators, in the South African experience, show a reliable leading relationship to the composite coincident index in the current study period between 1970 and 1980 and thereafter this relationship decreases, impacting negatively upon the forecasting ability of the model. / AFRIKAANSE OPSOMMING: In hierdie studie word die doeltreffende 'oorplanting' van 'n bepaalde metodologie van 'n waarskynlikheidsbenadering tot ekonomiese vooruitskatting in 'n Suid-Afrikaanse konteks assesseer. Die metodologie benut leidende aanwysers wat in regressiemodelle gebruik word, met 'n tweeledige responsveranderlike wat die waardes 0 of 1 aanneem om die uitbreiding of inkrimping van ekonomiese aktiwiteit aan te dui. Die kern van hierdie studie reflekteer tot 'n groot mate die werk van Nader Nazmi oor draaipunt voorspellings. Resultate toon aan dat Nazmi se model wel sakesiklusse se draaipunte akkuraat voorspel het gedurende die 1980's. Gedurende die 1990's het hierdie model se voorspeIlingsakkuraatheid egter afgeneem. In die Suid-Afrikaanse omstandighede dui leidende/rigtinggewende aanwysers op 'n betroubare verhouding wat betref die saamgestelde meelopende indeks vir die tydperk 1970 tot 1980 in die onderhawige studie. Daarna is daar 'n afname in die verhouding, wat 'n negatiewe impak het op die voorspellingsvermoe van die model. In hierdie studie word die doeltreffende 'oorplanting' van 'n bepaalde metodologie van 'n waarskynlikheidsbenadering tot ekonomiese vooruitskatting in 'n Suid-Afrikaanse konteks assesseer. Die metodologie benut leidende aanwysers wat in regressiemodelle gebruik word, met 'n tweeledige responsveranderlike wat die waardes 0 of 1 aanneem om die uitbreiding of inkrimping van ekonomiese aktiwiteit aan te dui. Die kern van hierdie studie reflekteer tot 'n groot mate die werk van Nader Nazmi oor draaipunt voorspellings. Resultate toon aan dat Nazmi se model wel sakesiklusse se draaipunte akkuraat voorspel het gedurende die 1980's. Gedurende die 1990's het hierdie model se voorspeIlingsakkuraatheid egter afgeneem. In die Suid-Afrikaanse omstandighede dui leidende/rigtinggewende aanwysers op 'n betroubare verhouding wat betref die saamgestelde meelopende indeks vir die tydperk 1970 tot 1980 in die onderhawige studie. Daarna is daar 'n afname in die verhouding, wat 'n negatiewe impak het op die voorspellingsvermoe van die model.

Thesis (PhD)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: In the first essay of this thesis, a medium scale DSGE model is developed and estimated for the South African economy. When used for forecasting, the model is found to outperform private sector economists when forecasting CPI inflation, GDP growth and the policy rate over certain horizons. In the second essay, the benchmark DSGE model is extended to include the yield on South African 10-year government bonds. The model is then used to decompose the 10-year yield spread into (1) the structural shocks that contributed to its evolution during the inflation targeting regime of the South African Reserve Bank, as well as (2) an expected yield and a term premium. In addition, it is found that changes in the South African term premium may predict future real economic activity. Finally, the need for DSGE models to take account of financial frictions became apparent during the recent global financial crisis. As a result, the final essay incorporates a stylised banking sector into the benchmark DSGE model described above. The optimal response of the South African Reserve Bank to financial shocks is then analysed within the context of this structural model.

Thesis (MComm (Economics)--University of Stellenbosch, 2006. / The goal of this thesis is twofold: it aims, firstly, at a description of cycles in South African financial variables and, secondly, at the evaluation of the relationship between cycles in financial variables and the South African business cycle. The study is based on the original business cycle framework of Arthur Burns and Wesley Mitchell, but incorporates recent contributions by Australian economists Don Harding and Adrian Pagan, as well as the work of the Economic Cycle Research Institute in New York. Part I of the thesis is concerned with the characteristics of cycles in financial variables within the South African context. The first chapter presents a taxonomy of the concepts of classical, deviation and growth rate cycles in order to establish a simple reference framework for cycle concepts. At this point the concept of a ‘turning point cycle’ is introduced, with particular focus on the non-parametric method of turning point identification, following Harding and Pagan’s recent translation of the original work of Burns and Mitchell into a modern version with a sound statistical basis. With the turning points identified the dissertation proceeds to an exposition of descriptive measures of expansion and contraction phases. The second chapter entails an empirical report on descriptive results for amplitude and duration characteristics of cycle phases in the different financial variables, with separate reports for classical cycles and growth rate cycles. Chapter two concludes with a series of tables in which the behaviour of cycle phases are compared for different financial variables. Part II considers financial variables as potential leading indicators of the business cycle in South Africa. Chapter 3 introduces the concept ‘leading indicator’ to this end and distinguishes the original concept from modern, econometric versions. The chapter then introduces a framework for evaluating potential leading indicators, which emphasises two requirements: firstly, broad co-movement between cycles in the proposed leading indicator and the business cycle and, secondly, stability in the number of months between turning points in cycles of the proposed indicator and business cycle turning points. The capacity of potential indicators to meet these criteria is measured via the concordance statistic and the ‘lead profile’ respectively. Chapter four provides the statistical basis for the concordance statistic, after which the empirical results (presented separately for classical and growth rate cycles) are presented. The fifth chapter presents the statistical test for the stability of the interval by which cyclical turning points in the potential indicator lead turning points in the business cycle. Empirical results are presented in both tabular form (the ‘lead profile’) and graphical form (the ‘lead profile chart’). As far as can be determined, this analysis represents the first application of the ‘lead profile’ evaluation to financial variables. Chapter six concludes by presenting a summary of the results and a brief comparison with findings from an econometric study of leading indicators for South Africa.

Thesis (Ph. D.)--University of California, San Diego, 2008. / Title from first page of PDF file (viewed June 19, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 124-127).

Univ., Diss.--Konstanz, 2003. / Literaturverz. S. [273] - 283.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 79-81). Also available on the Internet.

The study investigates the relationship between stock market performance and business cycles in South Africa for the period 2002-2009 using monthly data. This is done by constructing a Vector Error Correction Model (VECM). The study specifies a business cycle model with the business cycle coincident indicator (BC) regressed against, the All Share Price Index (ALSI), Real Effective Exchange Rate (REER), Money Supply (M1), Inflation (CPIX) and the Prime Overdraft Rate (POR). The ALSI represents stock market performance whilst the rest of the variables are to enhance model specification. The study found a positive relationship between stock market performance and business cycles in South Africa. The results also indicated that business cycles are positively related to the lagged variable of the coincident indicator and money supply. In addition, the findings also reveal that BC is negatively related to interest rates and the real effective exchange rate.

Tesis por compendio / [ES] En la Era Digital, el creciente uso de Internet y de dispositivos digitales está transformando completamente la forma de interactuar en el contexto económico y social. Miles de personas, empresas y organismos públicos utilizan Internet en sus actividades diarias, generando de este modo una enorme cantidad de datos actualizados ("Big Data") accesibles principalmente a través de la World Wide Web (WWW), que se ha convertido en el mayor repositorio de información del mundo. Estas huellas digitales se pueden rastrear y, si se procesan y analizan de manera apropiada, podrían ayudar a monitorizar en tiempo real una infinidad de variables económicas. En este contexto, el objetivo principal de esta tesis doctoral es generar indicadores económicos, basados en datos web, que sean capaces de proveer regularmente de predicciones a corto plazo ("nowcasting") sobre varias actividades empresariales que son fundamentales para el crecimiento y desarrollo de las economías. Concretamente, tres indicadores económicos basados en la web han sido diseñados y evaluados: en primer lugar, un indicador de orientación exportadora, basado en un modelo que predice si una empresa es exportadora; en segundo lugar, un indicador de adopción de comercio electrónico, basado en un modelo que predice si una empresa ofrece la posibilidad de venta online; y en tercer lugar, un indicador de supervivencia empresarial, basado en dos modelos que indican la probabilidad de supervivencia de una empresa y su tasa de riesgo. Para crear estos indicadores, se han descargado una diversidad de datos de sitios web corporativos de forma manual y automática, que posteriormente se han procesado y analizado con técnicas de análisis Big Data. Los resultados muestran que los datos web seleccionados están altamente relacionados con las variables económicas objeto de estudio, y que los indicadores basados en la web que se han diseñado en esta tesis capturan en un alto grado los valores reales de dichas variables económicas, siendo por tanto válidos para su uso por parte del mundo académico, de las empresas y de los decisores políticos. Además, la naturaleza online y digital de los indicadores basados en la web hace posible proveer regularmente y de forma barata de predicciones a corto plazo. Así, estos indicadores son ventajosos con respecto a los indicadores tradicionales. Esta tesis doctoral ha contribuido a generar conocimiento sobre la viabilidad de producir indicadores económicos con datos online procedentes de sitios web corporativos. Los indicadores que se han diseñado pretenden contribuir a la modernización en la producción de estadísticas oficiales, así como ayudar a los decisores políticos y los gerentes de empresas a tomar decisiones informadas más rápidamente. / [CA] A l'Era Digital, el creixent ús d'Internet i dels dispositius digitals està transformant completament la forma d'interactuar al context econòmic i social. Milers de persones, empreses i organismes públics utilitzen Internet a les seues activitats diàries, generant d'aquesta forma una enorme quantitat de dades actualitzades ("Big Data") accessibles principalment mitjançant la World Wide Web (WWW), que s'ha convertit en el major repositori d'informació del món. Aquestes empremtes digitals poden rastrejar-se i, si se processen i analitzen de forma apropiada, podrien ajudar a monitoritzar en temps real una infinitat de variables econòmiques. En aquest context, l'objectiu principal d'aquesta tesi doctoral és generar indicadors econòmics, basats en dades web, que siguen capaços de proveïr regularment de prediccions a curt termini ("nowcasting") sobre diverses activitats empresarials que són fonamentals per al creixement i desenvolupament de les economies. Concretament, tres indicadors econòmics basats en la web han sigut dissenyats i avaluats: en primer lloc, un indicador d'orientació exportadora, basat en un model que prediu si una empresa és exportadora; en segon lloc, un indicador d'adopció de comerç electrònic, basat en un model que prediu si una empresa ofereix la possibilitat de venda online; i en tercer lloc, un indicador de supervivència empresarial, basat en dos models que indiquen la probabilitat de supervivència d'una empresa i la seua tasa de risc. Per a crear aquestos indicadors, s'han descarregat una diversitat de dades de llocs web corporatius de forma manual i automàtica, que posteriorment s'han analitzat i processat amb tècniques d'anàlisi Big Data. Els resultats mostren que les dades web seleccionades estan altament relacionades amb les variables econòmiques objecte d'estudi, i que els indicadors basats en la web que s'han dissenyat en aquesta tesi capturen en un alt grau els valors reals d'aquestes variables econòmiques, sent per tant vàlids per al seu ús per part del món acadèmic, de les empreses i dels decisors polítics. A més, la naturalesa online i digital dels indicadors basats en la web fa possible proveïr regularment i de forma barata de prediccions a curt termini. D'aquesta forma, són avantatjosos en comparació als indicadors tradicionals. Aquesta tesi doctoral ha contribuït a generar coneixement sobre la viabilitat de produïr indicadors econòmics amb dades online procedents de llocs web corporatius. Els indicadors que s'han dissenyat pretenen contribuïr a la modernització en la producció d'estadístiques oficials, així com ajudar als decisors polítics i als gerents d'empreses a prendre decisions informades més ràpidament. / [EN] In the Digital Era, the increasing use of the Internet and digital devices is completely transforming the way of interacting in the economic and social framework. Myriad individuals, companies and public organizations use the Internet for their daily activities, generating a stream of fresh data ("Big Data") principally accessible through the World Wide Web (WWW), which has become the largest repository of information in the world. These digital footprints can be tracked and, if properly processed and analyzed, could help to monitor in real time a wide range of economic variables. In this context, the main goal of this PhD thesis is to generate economic indicators, based on web data, which are able to provide regular, short-term predictions ("nowcasting") about some business activities that are basic for the growth and development of an economy. Concretely, three web-based economic indicators have been designed and evaluated: first, an indicator of firms' export orientation, which is based on a model that predicts if a firm is an exporter; second, an indicator of firms' engagement in e-commerce, which is based on a model that predicts if a firm offers e-commerce facilities in its website; and third, an indicator of firms' survival, which is based on two models that indicate the probability of survival of a firm and its hazard rate. To build these indicators, a variety of data from corporate websites have been retrieved manually and automatically, and subsequently have been processed and analyzed with Big Data analysis techniques. Results show that the selected web data are highly related to the economic variables under study, and the web-based indicators designed in this thesis are capturing to a great extent their real values, thus being valid for their use by the academia, firms and policy-makers. Additionally, the digital and online nature of web-based indicators makes it possible to provide timely, inexpensive predictions about the economy. This way, they are advantageous with respect to traditional indicators. This PhD thesis has contributed to generating knowledge about the viability of producing economic indicators with data coming from corporate websites. The indicators that have been designed are expected to contribute to the modernization of official statistics and to help in making earlier, more informed decisions to policy-makers and business managers. / Blázquez Soriano, MD. (2019). Design and Evaluation of Web-Based Economic Indicators: A Big Data Analysis Approach [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/116836 / Compendio

Thesis (MBA)--Stellenbosch University, 2000. / ENGLISH ABSTRACT: The relationship between asset markets and economic growth is well documented in economic literature. Harvey (1989), conducted a study of the relationship between interest rate spreads, share market prices and real economic growth in the USA. He developed a model to forecast real economic growth using interest rate spreads and share market prices and concluded that interest rate spreads produced superior forecasts to those based on share market information. He further established that the forecasts obtained from his simple model, which made no provision for serial correlation, compared favourably with those of leading economic forecasters in the USA. Van der Mescht (1991) undertook a similar study based on interest rate spreads and share market prices in South Africa. He concluded that there were no significant differences between the capital market and share market as predictors of economic growth in South Africa when provision was made in Harvey's model for the effects of serial correlation. His results indicated that both the capital and share markets were able to explain more than 65 percent of the variation in economic growth over the period of his study and that the forecasts were able to accurately predict the turning points in the economy and compared favourably with other leading economic forecasters. A similar study to Van der Mescht's using updated South African data found that in general the conclusions reached by Van der Mescht remain valid. A difference which is evident, however, is that, whereas previously, there was little difference between the results of the interest rate spread and share market index model, the interest rate spread model produced better results over the period of this study (1981 - 1998). / AFRIKAANSE OPSOMMING: Die verwantskap tussen die kapitaal- en aandelemark en ekonomiese groei is deeglik in die ekonomiese literatuur ge-dokumenteer. Harvey (1989) het navorsing gedoen oor die verwantskap tussen die termynstruktuur van rentekoerse, aandelepryse en reële ekonomiese groei in die VSA. Hy het 'n vooruitskattingsmodel ontwikkel vir ekonomiese groei, gebaseer op die termynstruktuur van rentekoerse en aandelepryse en het tot die gevolgtrekking gekom dat die termynstruktuur van rentekoerse 'n beter vooruitskatter van ekonomiese groei is as die aandelemark, en dat sy model, wat geen voorsiening vir outokorrelasie maak nie, goed vergelyk met ander ekonometriese modelle wat ekonomiese groei in die VSA vooruitskat. Van der Mescht (1991) het 'n soortgelyke studie, gebaseer op die termynstruktuur van rentekoerse en aandelepyse in Suid Afrika, onderneem. Hy het tot die gevolgtrekking gekom dat daar geen betekenisvolle verskil is tussen die kapitaal en aandelemark as vooruitskatters van ekonomiese groei indien daar vir outokorrelasie in die modelle voorsiening gemaak word nie. Sy resultate dui aan dat die kapitaal- en aandelemark meer as 65 persent van die persentasieverandering in die ekonomiese groei kon verklaar oor die termyn van sy studie, dat dit akkurate vooruitskattings van die draaipunte in die Suid Afrikaanse ekonomie gelewer het, en dat dit gunstig vergelyk met ander ekonomiese vooruitskatters. 'n Soortgelyke studie as die van Van der Mescht is onderneem, met die jongste inligting omtrent termynstruktuur van rentekoerse en aandelepryse in Suid Afrika. In die algemeen is die gevolgtrekkings van Van der Mescht steeds van toepassing. Daar is egter aangetoon dat, waar daar voorheen geen betekenisvolle verskil tussen die kapitaal- en aandelemark as vooruitskatters van ekonomiese groei was nie, die termynstruktuur van rentekoerse beter resultate oor die termyn van hierdie studie gelewer het. (1981 -1998).

Mercado Preditivo (MP) é uma ferramenta que utiliza o mecanismo de preço de mercado para agregar informações dispersas em um grande grupo de pessoas, visando à geração de previsões sobre assuntos de interesse. Trata-se de um método de baixo custo, capaz de gerar previsões de forma contínua e que não exige amostras probabilísticas. Há diversas aplicações para esses mercados, sendo que uma das principais é o prognóstico de resultados eleitorais. Este estudo analisou evidências empíricas da eficácia de um Mercado Preditivo no Brasil, criado para fazer previsões sobre os resultados das eleições gerais do ano de 2014, sobre indicadores econômicos e sobre os resultados de jogos do Campeonato Brasileiro de futebol. A pesquisa teve dois grandes objetivos: i) desenvolver e avaliar o desempenho de um MP no contexto brasileiro, comparando suas previsões em relação a métodos alternativos; ii) explicar o que motiva as pessoas a participarem do MP, especialmente quando há pouca ou nenhuma interação entre os participantes e quando as transações são realizadas com uma moeda virtual. O estudo foi viabilizado por meio da criação da Bolsa de Previsões (BPrev), um MP online que funcionou por 61 dias, entre setembro e novembro de 2014, e que esteve aberto à participação de qualquer usuário da Internet no Brasil. Os 147 participantes registrados na BPrev efetuaram um total de 1.612 transações, sendo 760 no tema eleições, 270 em economia e 582 em futebol. Também foram utilizados dois questionários online para coletar dados demográficos e percepções dos usuários. O primeiro foi aplicado aos potenciais participantes antes do lançamento da BPrev (302 respostas válidas) e o segundo foi aplicado apenas aos usuários registrados, após dois meses de experiência de uso da ferramenta (71 respostas válidas). Com relação ao primeiro objetivo, os resultados sugerem que Mercados Preditivos são viáveis no contexto brasileiro. No tema eleições, o erro absoluto médio das previsões do MP na véspera do pleito foi de 3,33 pontos percentuais, enquanto o das pesquisas de opinião foi de 3,31. Considerando todo o período em que o MP esteve em operação, o desempenho dos dois métodos também foi parecido (erro absoluto médio de 4,20 pontos percentuais para o MP e de 4,09 para as pesquisas). Constatou-se também que os preços dos contratos não são um simples reflexo dos resultados das pesquisas, o que indica que o mercado é capaz de agregar informações de diferentes fontes. Há potencial para o uso de MPs em eleições brasileiras, principalmente como complemento às metodologias de previsão mais tradicionais. Todavia, algumas limitações da ferramenta e possíveis restrições legais podem dificultar sua adoção. No tema economia, os erros foram ligeiramente maiores do que os obtidos com métodos alternativos. Logo, um MP aberto ao público geral, como foi o caso da BPrev, mostrou-se mais indicado para previsões eleitorais do que para previsões econômicas. Já no tema futebol, as previsões do MP foram melhores do que o critério do acaso, mas não houve diferença significante em relação a outro método de previsão baseado na análise estatística de dados históricos. No que diz respeito ao segundo objetivo, a análise da participação no MP aponta que motivações intrínsecas são mais importantes para explicar o uso do que motivações extrínsecas. Em ordem decrescente de relevância, os principais fatores que influenciam a adoção inicial da ferramenta são: prazer percebido, aprendizado percebido, utilidade percebida, interesse pelo tema das previsões, facilidade de uso percebida, altruísmo percebido e recompensa percebida. Os indivíduos com melhor desempenho no mercado são mais propensos a continuar participando. Isso sugere que, com o passar do tempo, o nível médio de habilidade dos participantes tende a crescer, tornando as previsões do MP cada vez melhores. Os resultados também indicam que a prática de incluir questões de entretenimento para incentivar a participação em outros temas é pouco eficaz. Diante de todas as conclusões, o MP revelou-se como potencial técnica de previsão em variados campos de investigação. / Prediction Market (PM) is a tool which uses the market price mechanism to aggregate information scattered in a large group of people, aiming at generating predictions about matters of interest. It is a low cost method, able to generate forecasts continuously and it does not require random samples. There are several applications for these markets and one of the main ones is the prognosis of election outcomes. This study analyzed empirical evidences on the effectiveness of Prediction Markets in Brazil, regarding forecasts about the outcomes of the general elections in the year of 2014, about economic indicators and about the results of the Brazilian Championship soccer games. The research had two main purposes: i) to develop and evaluate the performance of PMs in the Brazilian context, comparing their predictions to the alternative methods; ii) to explain what motivates people´s participation in PMs, especially when there is little or no interaction among participants and when the trades are made with a virtual currency (play-money). The study was made feasible by means of the creation of a prediction exchange named Bolsa de Previsões (BPrev), an online marketplace which operated for 61 days, from September to November, 2014, being open to the participation of any Brazilian Internet user. The 147 participants enrolled in BPrev made a total of 1,612 trades, with 760 on the election markets, 270 on economy and 582 on soccer. Two online surveys were also used to collect demographic data and users´ perceptions. The first one was applied to potential participants before BPrev launching (302 valid answers) and the second was applied only to the registered users after two-month experience in tool using (71 valid answers). Regarding the first purpose, the results suggest Prediction Markets to be feasible in the Brazilian context. On the election markets, the mean absolute error of PM predictions on the eve of the elections was of 3.33 percentage points whereas the one of the polls was of 3.31. Considering the whole period in which BPrev was running, the performance of both methods was also similar (PM mean absolute error of 4.20 percentage points and poll´s 4.09). Contract prices were also found as not being a simple reflection of poll results, indicating that the market is capable to aggregate information from different sources. There is scope for the use of PMs in Brazilian elections, mainly as a complement of the most traditional forecasting methodologies. Nevertheless, some tool limitations and legal restrictions may hinder their adoption. On markets about economic indicators, the errors were slightly higher than those obtained by alternative methods. Therefore, a PM open to general public, as in the case of BPrev, showed as being more suitable to electoral predictions than to economic ones. Yet, on soccer markets, PM predictions were better than the criterion of chance although there had not been significant difference in relation to other forecasting method based on the statistical analysis of historical data. As far as the second purpose is concerned, the analysis of people´s participation in PMs points out intrinsic motivations being more important in explaining their use than extrinsic motivations. In relevance descending order, the principal factors that influenced tool´s initial adoption are: perceived enjoyment, perceived learning, perceived usefulness, interest in the theme of predictions, perceived ease of use, perceived altruism and perceived reward. Individuals with better performance in the market are more inclined to continue participating. This suggests that, over time, participants´ average skill level tends to increase, making PM forecasts better and better. Results also indicate that the practice of creating entertainment markets to encourage participation in other subjects is ineffective. Ratifying all the conclusions, PM showed as being a prediction potential technique in a variety of research fields.