Globally, the tourism industry is recognised as one of the fastest growing industries, generating high revenues and creating a vast number of job opportunities. In South Africa, this is no different and, in recent years, the tourism industry has outshone the country's gold exports therefore claiming its position as the fourth highest earner of foreign exchange to date. Yet the industry is still to receive the attention it deserves from conventional economics. This research aimed to fill this gap in South Africa by providing an understanding on the determinants of international tourism demand for South Africa. The first objective of the study was to provide a broad overview of the tourism industry of South Africa. The discussion focused on the supply and demand sides of tourism which, in turn, are divided into the domestic and international tourism markets. There has been a high growth, especially in the international market since 1994 and, while domestic and international markets continue to grow, seasonality remains an issue. Tourism has a significant impact on economic activity, employment, and the balance of payments and therefore the industry has great potential. The second objective was to create a theoretical understanding on the different factors that could determine the international demand for the tourism product. From this discussion it was found that there are various economic and non-economic factors that are believed to have an influence on tourism demand. Income, prices, transport cost, and the exchange rate are amongst the favourite economic variables with travel time, population, marketing expenditure, climate, and capacity being the more popular noneconomic factors. Among these, certain threats were also identified that could have harmful impacts on tourism growth. The third objective and main aim of the study was to determine which of the factors identified earlier determine the demand for international tourism to South Africa. This was done through an empirical investigation. Data from all the continents were used to attain an international perspective on tourist arrivals (tourism demand). The results indicated that capacity and climate factors determine tourism demand in the short term with income and transport cost influencing South Africa as a tourism destination in the long term. The last objective was to determine whether certain events or disasters that take place globally have a negative influence on tourism demand to South Africa. The event that was looked as was the terror attacks on the United States in September 2001. It was found that although the overall tourism activity of the world became stagnant during this period, the effect was not that considerable in South Africa's tourism arrivals. Tourism in countries such as the United Sates, on the other hand, has still not recovered fully after this event. / Thesis (M.Com. (International Commerce))--North-West University, Potchefstroom Campus, 2007.

Globally, the tourism industry is recognised as one of the fastest growing industries, generating high revenues and creating a vast number of job opportunities. In South Africa, this is no different and, in recent years, the tourism industry has outshone the country's gold exports therefore claiming its position as the fourth highest earner of foreign exchange to date. Yet the industry is still to receive the attention it deserves from conventional economics. This research aimed to fill this gap in South Africa by providing an understanding on the determinants of international tourism demand for South Africa. The first objective of the study was to provide a broad overview of the tourism industry of South Africa. The discussion focused on the supply and demand sides of tourism which, in turn, are divided into the domestic and international tourism markets. There has been a high growth, especially in the international market since 1994 and, while domestic and international markets continue to grow, seasonality remains an issue. Tourism has a significant impact on economic activity, employment, and the balance of payments and therefore the industry has great potential. The second objective was to create a theoretical understanding on the different factors that could determine the international demand for the tourism product. From this discussion it was found that there are various economic and non-economic factors that are believed to have an influence on tourism demand. Income, prices, transport cost, and the exchange rate are amongst the favourite economic variables with travel time, population, marketing expenditure, climate, and capacity being the more popular noneconomic factors. Among these, certain threats were also identified that could have harmful impacts on tourism growth. The third objective and main aim of the study was to determine which of the factors identified earlier determine the demand for international tourism to South Africa. This was done through an empirical investigation. Data from all the continents were used to attain an international perspective on tourist arrivals (tourism demand). The results indicated that capacity and climate factors determine tourism demand in the short term with income and transport cost influencing South Africa as a tourism destination in the long term. The last objective was to determine whether certain events or disasters that take place globally have a negative influence on tourism demand to South Africa. The event that was looked as was the terror attacks on the United States in September 2001. It was found that although the overall tourism activity of the world became stagnant during this period, the effect was not that considerable in South Africa's tourism arrivals. Tourism in countries such as the United Sates, on the other hand, has still not recovered fully after this event. / Thesis (M.Com. (International Commerce))--North-West University, Potchefstroom Campus, 2007.

In this paper, we study the parameter estimation of the multiple linear time series regression model with long memory stochastic regressors and innovations. Robinson and Hidalgo (1997) and Hidalgo and Robinson (2002) proposed a class of frequency-domain weighted least squares estimates. Their estimates are shown to achieve the Gauss-Markov bound with standard convergence rate. In this study, we proposed a time-domain generalized LSE approach, in which the inverse autocovariance matrix of the innovations is estimated via autoregressive coefficients. Simulation studies are performed to compare the proposed estimates with Robinson and Hidalgo (1997) and Hidalgo and Robinson (2002). The results show the time-domain generalized LSE is comparable to Robinson and Hidalgo (1997) and Hidalgo and Robinson (2002) and attains higher efficiencies when the autoregressive or moving average coefficients of the FARIMA models have larger values. A variance reduction estimator, called TF estimator, based on linear combination of the proposed estimator and Hidalgo and Robinson (2002)'s estimator is further proposed to improve the efficiency. Bootstrap method is applied to estimate the weights of the linear combination. Simulation results show the TF estimator outperforms the frequency-domain as well as the time-domain approaches.

Building cost indices are widely used in construction industry to measure the rate of change of building costs as a combination of labor and material costs. Cost index forecast is crucial for the two main parties of construction industry, contactor, and the client. Forecast information is used to increase the accuracy of estimate for the project cost to evaluate the bid price. The aim of this study is to develop time series models to forecast building cost indices in Turkey and United States. The models developed are compared with regression analysis and simple averaging models in terms of predictive accuracy. As a result of this study, time series models are selected as the most accurate models in predicting cost indices for both Turkey and United States. Future values of building cost indices can be predicted in adequate precision using time series models. This useful information can be used in tender process in estimation of project costs, which is one of the critical factors affecting the overall success of a construction project. Better cost estimates shall enable contractors to produce cash flow forecasts more acurately. Furthermore accurate prediction of future prices is very useful for owners in budget allocations / moreover can help investors to evaluate project alternatives adequately.

This thesis tests for seasonal anornalies and daily predictability on the UK stock market and investigates how mispricing caused by the bid-ask spread, known as the 'touch' and nonsynchronous trading in portfolio returns may explain these anomalies. By using constructed portfolios within a th-ne-series regression framework, I show that seasonality, in the first instance, is prominent in returns around the turn of the week and the turn of the year. However, this seasonal returns behaviour disappears when the touch is accounted for. Indeed, seasonality seerns to occur in the touch rather than returns. Despite this touch explanation, lagged returns remain significant, suggesting return predictability. In fact, when using a price adjustment model returns are predictable across portfolios. This predictability, while to some extent dependent upon firm size and the touch, may be accounted for by nonsynchronous trading. First-order autocorrelation and cross-autocorrelation found in returns proves more indicative of infrequent trading than return predictability. Thus, these results confirm that mismeasurernent in portfolio returns caused by market microstructure and nonsynchronous trading can create false inferences about the extent of stock market anornalies in the UK and subsequently, market efficiency.

A long record of daily data is used to study the lake levels of Lake Neusiedl, a large steppe lake at the eastern border of Austria. Daily lake level changes are modeled as functions of precipitation, temperature, and wind conditions. The occurrence and the amount of daily precipitation are modeled with logistic regressions and generalized linear models.

This thesis within Industrial Economics and Applied Mathematics investigates the relationship between economic development and subjective well-being. The Easterlin Paradox, originally stated by Richard Easterlin in 1974, is reassessed by utilizing cross-sectional and time series data. A simple regression model is applied, using average happiness within a country as dependent variable, and gross national product per capita as regressor. In addition, an extensive study of previous research is conducted, focusing on reliability of data and earlier methodologies. The Easterlin Paradox is confirmed to still be valid when analyzing the United States over the time period 1972{2016, and 140 of the countries across the world 2012. / Det här kandidatexamensarbetet inom Industriell Ekonomi och Tillämpad Matematik undersöker relationen mellan ekonomisk utveckling och subjektivt välmående. Easterlinparadoxen, ursprungligen fastställd av Richard Easterlin 1974, omprövas med hjälp av tvärsnitts- och tidsseriedata. En enkel linjär regressionsmodell appliceras med genomsnittlig lycka i ett land som beroende variabel och bruttonationalprodukt per capita som oberoende variabel. Dessutom utförs en omfattande studie av tidigare forskning med fokus på tillförlitlighet av data samt tidigare metodologier. Easterlinparadoxen bekräftas fortfarande gälla vid analys av USA over tidsperioden 1972-2016, och 140 av världens länder år 2012.

This study investigates if momentum effects can be found on the Swedish stock market by testing a cross-sectional momentum strategy on historical data. To explain the results mathematically, a second approach, involving time series regression for predicting future returns is introduced and thereby extends the cross-sectional theory. The result of the study shows that momentum effects through the cross-sectional strategy exist on the Swedish stock market. Although positive return is found, the time series regression do not give any significance for predicting future returns. Hence, there is a contradiction between the two approaches. / Denna studie undersöker om momentumeffekter föreligger på den svenska aktiemarknaden med hjälp av två olika tillvägagångssätt. Först testas momentumstrategin på historisk data och därefter genomförs tidseriesregression för att undersöka om resultaten har statistisk signifikans för att prediktera framtida avkastning. Resultatet visar att momentumeffekter existerar på den svenska aktiemarknaden. Trots att positiv avkastning erhålls ger tidserieregressionen ingen indikation på att prediktering av framtida avkastning är möjlig. Följaktligen finns det en motsägelse mellan de två tillvägagångssätten.

This thesis within Industrial Economics and Applied Mathematics examines the term commodity currency. The thesis delves into analysing the characteristics and consequences of such a currency through a macroeconomic perspective while discussing previous studies within the matter. The applied mathematical statistics section audits the correlation between the currency and the commodities of the exporting country through a time series regression. The regression is based on the currency as the dependent variable and the commodities represent the covariates. Furthermore, a trading strategy is developed to see if a profit can be made on the foreign exchange market when looking at the commodity price movements. / Det här kandidatexamensarbetet är skrivet inom industriell ekonomi och tillämpad matematik och granskar termen råvaruvaluta (commodity currency). Uppsatsen analyserar, utifrån ett makroekonomiskt perspektiv, karaktärsdragen och konsekvenserna av en sådan valuta, samtidigt som den diskuterar tidigare studier inom ämnet. Delen inom tillämpad matematik undersöker korrelationen mellan valutan och råvarorna som landet exporterar genom en tidsserieregression. Regressionen är baserad på valutan som responsvariabel samtidigt som råvarorna representerar kovariaterna. Den färdiga modellen används sedan i en handelsstrategi som försöker förutspå växelkursens rörelser genom att titta på råvarornas rörelser.

This study investigates fluctuations of construction output, and growth of the output in Kenya. Fluctuation and growth of construction activity are matters of concern in construction industries of many countries in the developing as well as in the developed world. The construction industry of Kenya is therefore an exemplifying case for this phenomenon. Construction activity in Kenya fluctuates excessively and grows very slowly. This remains a big challenge to policy makers, developers, consultants and contractors in their decision-making processes. In this study, systems thinking was applied to investigate the problem of excessive fluctuations and stunted growth of construction output in Kenya. The study developed a system dynamics model to simulate the construction output problem behaviour. The historical behaviour of the construction industry was described using construction output data of a 40-year period - from 1964 to 2003. Line graphs of the historical data exhibited profiles that helped to identify the system archetypes operating in the industry. From the profiles, it was deduced that the problem of fluctuations and slow growth of construction output in Kenya is encapsulated in two system archetypes, namely: balancing process with a delay, and limits to growth. The relationship between construction output and its determinant factors from the constru ction industry's environment was investigated using time series regression, which involved autoregressive integrated moving average (ARIMA) regression and multiple regression modelling of the output. On the basis of the historical data analysis and the system archetypes identified, a system dynamics (SD) model was developed to replicate the problem of fluctuations and slow growth in the construction output. The data used to develop the system dynamics model was annual construction output in Kenya from 1964 to 2003. The model was then used: to appraise policy changes suggested by construction industry participants in Kenya, and to project construction output in Kenya from year 2004 to year 2050, in order to establish the expected future fluctuations and growth trends of the construction output. It was observed that three fundamental changes are necessary in the system structure of the construction industry of Kenya, in order to minimize fluctuations and foster growth in construction output in the country, in the long run. The changes are: setting long-term targets of annual construction output in the industry as a whole, incorporating reserve capacity in the production process, and expanding the system st ructure to capture a larger construction market. The study recommends regulation of the response of the construction industry of Kenya to changes in construction demand in the market, and expansion of the construction industry's market into the African region and beyond.