Thesis (M.M. (Finance & Investment))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Graduate School of Business Administration, 2014. / Dornbusch’s exchange rate overshooting hypothesis has guided monetary policy conduct for many years though empirical evidence on its validity is mixed. This study re-examines the validity of the overshooting hypothesis by using the autoregressive distributed lag (ARDL) procedure. Specifically, the study investigates whether the overshooting hypothesis holds for the United States Dollar/Zambian Kwacha (USD-ZMK) exchange rate. In addition, the study tests if there is a long-run equilibrium relationship between the USD-ZMK exchange rate and the macroeconomic fundamentals (money supply, real Gross Domestic Product (GDP), interest rates and inflation rates). The study uses monthly nominal USD/ZMK exchange rates and monetary fundamentals data from January 2000 to December 2012. The study finds no evidence of exchange rate overshooting. The result also show that there is no long run equilibrium relationship between the exchange rate and the differentials of macroeconomic fundamentals. The implication is that macroeconomic fundamentals are insignificant in determining the exchange rate fluctuations in the long run. This finding is inconsistent with the monetary model of exchange rate determination, which asserts that there is a long-run relationship between the exchange rate and macroeconomic fundamentals.

This study empirically examines the relationship between financial development and economic growth in Nigeria. It employs statistical techniques such as the Autoregressive Distributed Lag approach as well as a short and long run Granger Causality test on time series data spanning from 1960-2016. Empirical results reveal that the financial development indicators have a long run relationship with economic growth in Nigeria and the existence of unidirectional and bidirectional Granger causality was also discovered. This study recommends that policy should be geared towards promoting financial development in the country as well as encouraging more financial depth and openness – in order to foster economic growth in Nigeria.

This study aims to identify the effects of oil income on economic growth in Iran over the period 1955-2014. The empirical literature indicates that countries with natural resources are growing more slowly than their counterparts. However, the results from this literature are far from conclusive, particularly in regard to the role played by oil-rich countries. Needless to say, this role depends on other factors as well, including the political situation in the country, the quality of institutions, and the efficacy of the financial system. Some empirical research has found that natural resources, particularly oil, can have a positive impact on the output of a country. although natural resources are not a factor of production in growth theories, studies have used different growth frameworks in order to discover whether having natural resources is a blessing or a curse. In line with recent studies, this work uses an augmented neoclassical growth model to develop a theoretical framework where oil enters the long-term output of the country through saving and investment. Overall, the results suggests that oil income has a positive impact on the level of output per capita in Iran. The findings of the econometric results are in line with the historical analysis of the study. Since different methods and proxies were used, a total of eight models were estimated. Interestingly, when PRIVY is used as an index of financial development, the result of the study changes and oil no longer has a significant impact on the economy. However, this can be translated to an inefficient allocation of credit to the private sector.

This thesis aims to investigate the impact of state fragility on capital inflows and economic growth in Nigeria over the period 1980-2015. In line with existing studies, it adopts an augmented neoclassical growth model where capital is divided into domestic and foreign capital inflows (FDI, ODA and Remittances). Using an autoregressive distributed lag (ARDL) bounds testing approach to co-integration, significant long-run relationship was confirmed between state fragility, capital flows and economic growth. The results reveal domestic capital to be very significant and contribute positively to economic growth. Similarly it was observed that remittances remain a very crucial form of capital flow to Nigeria and that the presence of state fragility makes it more significant. For ODA a positive contribution to economic growth was observed, however, the presence of state fragility renders it insignificant. In the case of FDI, the study found a negative relationship between FDI and economic growth albeit insignificant. However, the presence of state fragility makes it significant but still negative. A negative relationship was also observed between state fragility and economic growth. These findings, implies that while the issue of state fragility needs to be addressed and concerted efforts put into building state resilience, not just for the direct impact of state fragility on the economy, but also its impact on the economy through other channels such as capital flows.

The main purpose of the study is to examine the cointegration relationships among economic growth, foreign direct investment and financial sector development in 4 East Asian countries, namely Korea, Malaysia, the Philippines and Thailand between the years 1971-2008 by autoregressive distributed lag (ARDL) approach. In the existing literature, there is no study examining the causal relationships among economic growth, foreign direct investment and financial sector development by applying ARDL methodology for these East Asian countries. The contribution of this study to the literature, the cointegration relationships are constructed to observe the direct linkage among these variables by ARDL approach. If cointegration relationships exist among these variables, then the effect of each regressor on the dependent variable is also investigated. The results of the study indicate that foreign direct investment and financial sector development could be long run forcing variables of economic growth. Additionally, economic growth and financial sector development could be long run forcing variables of foreign direct investment. However, there is not sufficient evidence that economic growth and foreign direct investment together are long run key determinants of financial sector development in a country as obtained in this study.

This thesis employs the Autoregressive Distributed Lag model (ARDL), Toda-Yamamoto causality analysis, and ordinary least square (OLS for robust estimation) techniques to empirically investigate the impact of economic growth and energy consumption on the environment in Nigeria from 1980 to 2020. The results of cointegration demonstrate a long-term link between the model's input variables. The outcome of the first objective of the study shows that trade and economic development in Nigeria worsen the state of the environment. Environmental quality is accelerated by financial development; nevertheless, FDI is proven to be insignificant in predicting environmental quality. The result demonstrates that FDI and energy use both have the potential to significantly speed up the rate of environmental degradation. Nevertheless, trade has a negligible impact on the environment in the country, and financial development slows down environmental deterioration. The study also finds that the combination between energy and economic development improves Nigeria's environmental quality. The outcome of the fourth objective shows that economic expansion and energy consumption have a favorable impact on the environment. Additionally, environmental degradation, energy use, and economic growth are all causally related. Moreover, the outcome of the robust estimation reveals a positive and significant relationship between economic growth and energy consumption in the environment. Therefore, the study suggests economic policies with environmental control measures. This could be through an emphasis on the use of other alternatives of low-emission energy, that will mitigate the level of C02 and enhance energy utilization for a better environment in the nation.

Liberalisation of trade is deepening, and so have the incentive schemes put in place by a number of countries to promote it. International trade promotion agencies in developing countries are actively promoting their countries as the best, with which to trade. With international trade emerging as a favourite source of revenue and technology transfer for most countries, profound questions about the impact of trade liberalisation to economic growth are addressed in this study. The main purpose of this study is to empirically assess the relationship between trade liberalisation and economic growth in Zimbabwe using annual time series data from 1980 to 2017. Autoregressive distributed lag (ARDL) bounds testing approach to cointegration and Error Correction Mechanism (ECM) are applied in order to investigate the long run and short run impact of trade liberalisation on economic growth. The results proved the existence of a positive long-run relationship between trade liberalisation and economic growth. The study therefore concludes that policy makers and government negotiators in Zimbabwe should introduce policies that promote openness through the removal of barriers to trade and export promotion in order to promote overall growth of the economy. / Economics / M. Com (Economics)

Until very recently, most emerging market economies have achieved higher growth rates for the last decade. It is controversial whether this good economic environment is due to domestic reforms or due to favorable external factors. In this framework, the main aim of this study is to investigate the structure and sources of business cycles in emerging market economies and to determine how these cycles differ than those in developed countries. The role of external and domestic factors on business cycles are analyzed by applying not only the conventional panel data estimations but also common correlated effects panel mean group method which is introduced by Peseran (2006). Besides, the convergence of business cycles in emerging market economies to the business cycles in developed countries is discussed based on factor analysis. The major results indicate the common global factors are the leading source of the business cycles both in emerging market economies and developed countries. However, domestic determinants of fluctuations differ across two groups of countries. In addition, results show that in the last two decades fluctuations in emerging market economies have started to be more dependent on the fluctuations in developed countries.

In this study, the effects of CBRT monetary policy decisions on the consumer, automobile, housing and commercial loans of the banks during the period from the early of 2004 to the middle of 2011 are examined. In order to perform this study, it is benefited from weekly weighted average loan interest rate data of the banks, which is the data having the highest frequency that could be obtained from the electronic data distribution system of CBRT. Monetary policy instruments of Central Bank may change in the course of time or monetary policy could be executed by more than one instrument. Therefore, as the political interest rate would be insufficient in the calculation of the effect of monetary policy on loan interest rates of the banks, Government Dept Securities&rsquo / premiums are used instead of the political interest rates in this study to make it reflect the policies of central bank more clearly as a whole. Among the Government Dept Securities that have different maturity structure, benchmark bonds that are adapted to the expected political interest rate changes and that react to the unexpected interest rate changes at the high rate (reaction coefficient 0.983) are used. In order to weight the cointegration relation between interest rates, unrestricted error correction model is established and it is determined by Bound Test that there is a long-term relation between each interest rate and interest rate of benchmark bond. After a cointegration relation is determined among the serials, autoregressive distributed lag model is used to determine the level of transitivity and it is determined that monetary policy decisions affect the banking interest rate at 77% level and by 13 weeks delay on average.

Tourism is currently the third largest industry within South Africa. Many African countries, including South Africa, have the potential to achieve increased economic growth and development with the aid of the tourism sector. As tourism is a great earner of foreign exchange and also creates employment opportunities, especially low–skilled employment, it is identified as a sector that can aid developing countries to increase economic growth and development. Accurate forecasting of tourism demand is important due to the perishable nature of tourism products and services. Little research on forecasting tourism demand in South Africa can be found. The aim of this study is to forecast tourism demand (international tourist arrivals) to South Africa by making use of different causal models and to compare the forecasting accuracy of the causal models used. Accurate forecasts of tourism demand may assist policy–makers and business concerns with decisions regarding future investment and employment. An overview of South African tourism trends indicates that although domestic arrivals surpass foreign arrivals in terms of volume, foreign arrivals spend more in South Africa than domestic tourists. It was also established that tourist arrivals from Africa (including the Middle East), form the largest market of international tourist arrivals to South Africa. Africa is, however, not included in the empirical analysis mainly due to data limitations. All the other markets namely Asia, Australasia, Europe, North America, South America and the United Kingdom are included as origin markets for the empirical analysis and this study therefore focuses on intercontinental tourism demand for South Africa. A review of the literature identified several determinants of tourist arrivals, including income, relative prices, transport cost, climate, supply–side factors, health risks, political stability as well as terrorism and crime. Most researchers used tourist arrivals/departures or tourist spending/receipts as dependent variables in empirical tourism demand studies. The first approach used to forecast tourism demand is a single equation approach, more specifically an Autoregressive Distributed Lag Model. This relationship between the explanatory variables and the dependent variable was then used to ex post forecast tourism demand for South Africa from the six markets identified earlier. Secondly, a system of equation approach, more specifically a Vector Autoregressive Model and Vector Error Correction Model were estimated for each of the identified six markets. An impulse response analysis was undertaken to determine the effect of shocks in the explanatory variables on tourism demand using the Vector Error Correction Model. It was established that it takes on average three years for the effect on tourism demand to disappear. A variance decomposition analysis was also done using the Vector Error Correction Model to determine how each variable affects the percentage forecast variance of a certain variable. It was found that income plays an important role in explaining the percentage forecast variance of almost every variable. The Vector Autoregressive Model was used to estimate the short–run relationship between the variables and to ex post forecast tourism demand to South Africa from the six identified markets. The results showed that enhanced marketing can be done in origin markets with a growing GDP in order to attract more arrivals from those areas due to the high elasticity of the real GDP per capita in the long run and its positive impact on tourist arrivals. It is mainly up to the origin countries to increase their income per capita. Focussing on infrastructure development and maintenance could contribute to an increase in future tourist arrivals. It is evident that arrivals from Europe might have a negative relationship with the number of hotel rooms available since tourists from this region might prefer accommodation with a safari atmosphere such as bush lodges. Investment in such accommodation facilities and the marketing of such facilities to Europeans may contribute to an increase in arrivals from Europe. The real exchange rate also plays a role in the price competitiveness of the destination country. Therefore, in order for South Africa to be more price competitive, inflation rate control can be a way to increase price competitiveness rather than to have a fixed exchange rate. Forecasting accuracy was tested by estimating the Mean Absolute Percentage Error, Root Mean Square Error and Theil’s U of each model. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was estimated for each origin market as a benchmark model to determine forecasting accuracy against this univariate time series approach. The results showed that the Seasonal Autoregressive Integrated Moving Average model achieved more accurate predictions whereas the Vector Autoregressive model forecasts were more accurate than the Autoregressive Distributed Lag Model forecasts. Policy–makers can use both the SARIMA and VAR model, which may generate more accurate forecast results in order to provide better policy recommendations. / Thesis (M.Com. (Economics))--North-West University, Potchefstroom Campus, 2011.