This study attempts to ascertain the importance of foreign capital inflows (FCIs) in Pakistan. We do so by first finding the key determinants of FCIs in Pakistan. Secondly, we attempt to investigate the relationship of FCIs with economic growth and finally we study the impact of FCIs on unemployment, poverty and income inequality. FCIs in this study are combination of foreign direct investment, remittances, foreign aid and external debt. Using data from 1973-2008 for Pakistan we found that growth is key determinant of FCIs both in aggregated and disaggregated forms. Moreover, FCIs have positive impact on economic growth in Pakistan. We also found that FCIs do help in reducing unemployment. Impact on poverty and inequality, however, was found to be insignificant. Results suggest that though FCI is beneficial for growth, the spillovers of the growth are not reaching the poor segment of the society. Policy makers should therefore focus on utilizing these foreign resources, especially remittance inflows, to strengthen domestic financial sector, reduce poverty and inequality. JEL Classification F21, F24, F29 Keywords International Capital Flows, Economic growth, Foreign Direct Investment, Remittances, Foreign Debt, Foriegn Aid, ARDL, Poverty Author's e-mail alionline83@yahoo.com Supervisor's e-mail...

Approximately 60% of New Zealand's electricity is produced from hydro generation. The Waitaki River catchment is located in the centre of the South Island of New Zealand, and produces 35-40% of New Zealand's electricity. Low inflow years in 1992 and 2001 resulted in the threat of power blackouts, and a national demand for electricity that is currently growing at 2 to 5% a year gives strong justification for better management of the hydro resource. Improved seasonal rainfall and inflow forecasts will result in the better management of the water used in hydro generation on a seasonal basis. Seasonal rainfall forecasting has been the focus of much international research in recent years, but seasonal inflow forecasting is in its relative infancy. Researchers have stated that key directions for both fields are to decrease the spatial scale of forecast products, and to tailor forecast products to end user needs, so as to provide more relevant and targeted forecasts, which will hopefully decrease the enormous socio-economic costs of climate fluctuations. This study calibrated several season ahead lake inflow and rainfall forecast models for the Waitaki river catchment, using statistical techniques to quantify relationships between land-ocean-atmosphere state variables and seasonally lagged inflows and rainfall. Techniques included principal components analysis and multiple linear regression, with cross-validation techniques applied to estimate model error. Many of both the continuous and discrete format models calibrated in this study predict anomalously wet and dry seasons better than random chance, and better than the long term mean as a predictor. 95% confidence limits around most model predictions in this study offer significant skill when compared with the range of all probable inflows (based on the 80 year recording history in the catchment). Models predicting winter Lake Pukaki inflows are those with the strongest predictive relationships in this study. Spring and summer predictions were generally less skilful than those for winter and autumn. Inflows could be predicted with some skill in winter and summer, but not rainfall, and rainfall could be predicted with some skill in autumn and spring, but not inflows. Models predicting inflows and rainfall for different seasons in this study use very different sets of predictor variables to accomplish their seasonal predictability. This may be related to the significant seasonal snow storage in the catchment, so that other factors such as temperature and the number of north-westerly storms may have a large part to play in the magnitude of inflows. Similarly, predicting the same dependent variable but for different seasons led to different contributing variables, leading to the conclusion that different wider physical causative mechanisms are behind the predictability in different seasons, and that they too should be studied separately in any future research. SST5 (sea surface temperature to the north of New Zealand) was found to have more relevance than any other predictor in predicting Waitaki river inflows and rainfall in any season. The models calibrated with SOI and IPO included as predictor variables were almost invariably worse in their predictive skill than those without, and the list of the most important predictor variables in all models did not include equatorial sea surface temperatures, sea level pressures, or 700hpa geopotential height variables. The conclusion from these findings is that equatorial ocean-atmosphere state variables do not have significant relationships with season ahead inflows and rainfall in the South Island of New Zealand. Seasonal climate forecasting on single catchment scale, and focussed to end user needs, is possible with some skill, at least in the South Island of New Zealand.

Freshwater inflows are a crucial component for maintaining estuarine health, function and productivity. Streamflows, the primary source of freshwater inflows, have been modified and altered from their natural flow by population growth and anthropogenic impacts on the contributing watersheds. The Guadalupe Estuary is a primary habitat for many endangered species. The Guadalupe River Watershed, which supplies 70% of freshwater inflows, experiences rapid urbanization and agricultural development. This study proposed to characterize the impact of land use/cover change in the Guadalupe River Watershed on freshwater inflows to the Guadalupe Estuary. Pre-whitening, Mann-Kendall and bootstrap techniques were used to test for significant trends on streamflow and precipitation. Analyses suggested more trends in annual and seasonal minimum and mean streamflow than would be expected to occur by chance in the periods of 1930-2005 and 1950-2005. No significant trends were found in the period of 1970-2005. Significant trends were more prominent in the upper watershed and decreased as analysis moved downstream in the period of 1950-2005. Trend tests on precipitation data in the period of 1950-2005 revealed more significant trends than would be expected by chance in mean annual and winter precipitation. Analyses of Landsat images of the watershed using an unsupervised classification method showed an increase in forest, urban and irrigated land by 13, 42 and 7%, respectively, from 1987 to 2002. Urbanized areas were mostly found in the middle part of watershed surrounding the I-35 corridor. More than 80% of irrigated lands are distributed over the San Marcos and Middle Guadalupe River Watersheds. Soil and Water Assessment Tool (SWAT) model was applied for the Guadalupe River Watershed. Calibration and validation using data recorded at USGS 08176500 indicated the model performed well to simulate streamflow. The coefficient of Nash- Sutcliffe, determination and percent bias were 0.83, 0.96 and 3.81, respectively, for calibration and 0.68, 0.75 and 29.38 for validation period. SWAT predicted a 2% decrease in annual freshwater inflow rates from the effect of land use/cover change from 1987 to 2002. Reservoirs increased freshwater inflows during low flow months and decreased the inflows during high flow months. Precipitation variability changed characteristics of monthly freshwater inflows.

Harmful algal blooms' global amplification has driven research on growth characteristics and instigating mechanisms. These blooms prosper under diverse environmental conditions, creating challenges identifying bloom initiation. The haptophyte, Prymnesium parvum, plagues the southwestern United States with massive system disruptions and huge fish kills caused by its toxin. Despite many abiotic factors' association with P. parvum blooms, low nutrient levels stress the alga increasing toxin production, eliminating nutrient competition, and alleviating grazing pressures. This model examines the relationship between nutrient availability and P. parvum toxin production against another phytoplankton and a single grazing zooplankton, using a Monod function relating population growth rate with limiting nutrient concentrations. Sensitivity analyses emphasize plankton biological parameters most influential in accumulating biomass. The impact of toxin production on zooplankton grazing rates underscores P. parvum's need for top-down control suppression. The toxin production equation increases production when P. parvum experiences low specific growth rates from nutrient availability and low biomass. This equation is analyzed against previously published allelopathic relationships, comparing plankton reactions and bloom endurance. The model's toxin production equation proves more ecologically feasible, incorporating competing phytoplankton species' mortality and variables easily verified through laboratory experiments. Though not intended for management strategy development, the model explores and supports the proposed strategy of incorporating hydraulic flushing, pulsed and continuous inflows, to eliminate biomass accumulation. Inflows relieve stressful nutrient-limiting conditions, introducing resources affecting bloom stability and plankton community dynamics. The faster-growing competing phytoplankton gains survival advantages when inflow rates fall lower than its maximum specific growth rate, but greater than P. Parvum's, emphasizing the accurate measuring of competitors' maximum specific growth rates and identifying a dilution rate range where P. parvum loses at nutrient intake. Inflows with various nutrient levels representing different source waters from freshwater lakes were tested for impacts on plankton dynamics. Adding any hydrological effect reduced P. parvum biomass. Disruptions create disturbance, removing P. parvum's system-dominating position, allowing the phytoplankton to exceed P. parvum's density. The model highlights the importance of P. parvum's toxin's presence to maintain dominance and emphasizes flushing agitation as potential and feasible management schemes to deter bloom continuation and increase species diversity.

Please read the abstract in the 00front of this document. / Thesis (PhD)--University of Pretoria, 2011. / Economics / unrestricted

The Lake Kariba catchment area in southern Africa has one of the most variable climates of any major river basin, with an extreme range of conditions across the catchment and through time. The study characterized rainfall variability across the Lake Kariba catchment area, followed by describing prediction models for seasonal rainfall totals over the catchment and for inflows into Lake Kariba. The thesis therefore improved our understanding of rainfall variations over central southern Africa and provided evidence on how seasonal forecasts can be applied in order to potentially improve decision making in dam management. The prediction of the seasons in which floods or droughts are most likely to occur involves studying the characteristics of rainfall and inflows within these extreme seasons. The study started off by analyzing monthly rainfall data through statistical analysis. To determine the predictability of seasonal rainfall totals over the Lake Kariba catchment area, this study used low-level atmospheric circulation of a fully coupled ocean-atmosphere general circulation model over southern Africa, statistically downscaled to seasonal rainfall totals over the catchment. The verification of hindcasts showed that rainfall over the catchment is predictable at extended lead-times. Seasonal climate forecasts need to be integrated into application models in order to help with decision-making processes. The use of hydro-meteorological models may be proven effective for reservoir operations since accurate and reliable prediction of reservoir inflows can provide balanced solution to the problems faced by dam or reservoir managers. In order to reliably predict reservoir inflows for decision-making, the study investigated the use of a combination of physical and empirical models to predict seasonal inflows into the Lake. Two predictions systems were considered. First, antecedent seasonal rainfall totals over the upper Zambezi catchment were used as predictors in a statistical model for estimating seasonal inflows into Lake Kariba. The second and more sophisticated method used predicted low-level atmospheric circulation of a coupled ocean-atmosphere general circulation model downscaled to the inflows. Inflow hindcasts performed best during the austral mid-summer season of DJF (seasonal onset of inflows) and the autumn season of MAM (main inflow season). / Thesis (PhD)--University of Pretoria, 2015. / gm2015 / Geography, Geoinformatics and Meteorology / PhD / Unrestricted

Foreign direct investment is an important topic in economic research. FDI occurs when a firm invests in a foreign country. The purpose of this thesis is to empirically analyze the effects of FDI on the economic growth of the selected sample of twenty-one OECD countries. The thesis is based on a theoretical model of cross-country regressions and a panel data technique methodology was followed. The results of the time-period 1998-2017, show a direct positive impact of FDI on GDP per capita growth, namely economic growth. Moreover, it was found a lack of complementarity between FDI inflows and human capital, and a negative dependency between FDI inflows and institutions such as private sector credit.

Freshwater inflows are essential to the health of estuaries and minimum discharge levels must be maintained in order to sustain a healthy ecosystem. Due to the predicted 50% increase in urban population growth along the Texas coastline by the year 2050, water regulators and managers are faced with the challenge of meeting human needs, while maintaining essential freshwater inflows into estuarine ecosystems. Galveston Bay is of particular concern because 10 million people currently living within its watershed. Freshwater inflows into Galveston Bay during 2006 were determined by using daily discharge data from a United States Geological Survey (USGS) sampling gauge in the Trinity River. Changes in water quality parameters, primary productivity, and phytoplankton community structure in response to freshwater inflows, were monitored monthly to determine how the phytoplankton community responded to inflow events. Freshwater inflow into Galveston Bay during 2006 was indicative of a low-inflow year, with seven large (>7,000 ft.3 sec-1) inflow events occurring throughout the year. There were significant differences in phytoplankton biomass (Fm), photosynthetic efficiency (alpha), and photosynthetic potential (yield) of the phytoplankton community, between wet (January-April and October-December) and dry (May-September) months. Significant differences in the biomass of phytoplankton groups also occurred with cyanobacteria being present in higher concentrations during the dry months and diatoms & dinoflagellates during the wet months. Low flow periods favored cyanobacteria, which lead to decreased secondary productivity, while pulsed inflow events resulted in enhanced secondary productivity by favoring diatoms and dinoflagellates. Resource Limitation Assays (RLAs) indicated that nitrogen was a potential limiting nutrient in Galveston Bay during spring/summer, with light limitation of phytoplankton communities possibly occurring near the mouth of the Trinity River. This study demonstrates the role of freshwater inflows in determining the primary productivity and community composition of the phytoplankton in Galveston Bay over an annual cycle. Inter-annual studies are needed to elucidate the impact of freshwater inflows in years with higher inflows to Galveston Bay and determine which of these impacts need to be incorporated into water management decisions to maintain a healthy ecosystem.

This dissertation attempts in three essays to contribute to the growing body of research on the problems associated with sudden stops of capital inflows, known to have been at the heart of many recent emerging market crises. It does this by developing basic models that can incorporate sudden stops and hopefully make policy relevant recommendations. The first essay develops a simple three date representative agent model of a small open endowment economy without money. It allows sudden stops to occur at date two and asks whether individuals in such a shock-prone world are still better off borrowing than in autarky. Unambiguously, this chapter shows that individuals are better off borrowing than in autarky and provides a tractable core model on which the later chapters build. The second essay then includes a long-term borrowing option as well as country-specific risk premia based on an information asymmetry between domestic borrowers and international lenders. This allows analysis of optimal maturity choices in a meaningful way. The intent is to address questions in the literature concerning whether emerging economies could enhance welfare by imposing short-term capital controls to encourage the use of longer-maturing debt and thus avoid the sudden stop. The results imply that short-term capital controls would generally lower welfare, even when sudden stops are fully anticipated. Finally, the third essay extends the horizon of the model and includes a much wider range of maturities. This allows one to start making sense of maturity bunching (when a country's debt all matures around a given date) which is known to exacerbate sudden-stop related problems. The model shows that maturity bunching can occur endogenously when both risk premia and uncertainty over the duration of the sudden stop are present.

This article describes a method to analyse retail trade flows among competing retail centres. A case study of three nearby communities in the Southeastern United States is used to demonstrate the application of the technique. Results of the case study and their implications are discussed.