This dissertation investigates the determinants of China's exports and regional economic growth, the direction of causality between foreign direct investment (FDI) and exports; and convergence analysis among Chinese provinces. The study firstly discusses the evolutional process of China's foreign trade regime through comparing the strategies and policies before 1978 with those after 1978. It is emphasised that the export-promotion development policies result in the recent basic export patterns and characteristics. Furthermore, the study reviews the existing literature on exports, FDI, and convergence/growth determinants in the case of China. The empirical work comprises three parts. Firstly, fixed-effects ordinary least squares (OLS) and random-effects generalised least squares (GLS) panel data estimators are applied to test the determinants of provincial exports from 1994 to 2003. It is found that FDI, geographical location, investment in manufacturing innovation, and human capital have significant influences on regional export performance. Secondly, the augmented Dickey-Fuller (ADF) tests are carried out to test stationarity and the Granger causality tests are conducted to test the causal direction between FDI and exports, based on monthly national data from January, 2002 to June, 2006. The empirical results indicate that there is a one-way complementary causal link from FDI inflows to China's export flows. Thirdly, three methods, beta convergence, sigma convergence, and Markov Chain analysis, are used to do convergence debate among China's regions and the standard OLS cross-section and random-effects GLS panel data are applied to test the conditional convergence. The results suggest that the convergence hypothesis does not hold in China between 1994 and 2003 and there is a sign of conditional convergence, conditioning the explanatory variables such as exports, human capital, and population growth. / Thesis (Ph.D. (Economics))--North-West University, Potchefstroom Campus, 2007.

Research Question: This research adapted, tested, and evaluated a methodology to set priorities for systematic reviews topics within the Cochrane Collaboration that is sustainable and incorporates the social determinants of health and health equity into the analysis. Background: In 2008 a study was conducted to review, evaluate and compare the methods for prioritization used across the Cochrane Collaboration. Two key findings from that study were: 1) the methods were not sustainable and 2) health equity represented a gap in the process. To address these key findings, the objective of this research was to produce and test a method that is sustainable and incorporates the social determinants of health and health equity into the decision making process. As part of this research, the methods were evaluated to determine the level of success. Methodology: With assistance from experts in the field, a comparative analysis of existing priority setting methods was conducted. The Global Evidence Mapping (GEM) method was selected to be adapted to meet our research objectives. The adapted method was tested with assistance of the Cochrane Musculoskeletal Group in identifying priorities for Osteoarthritis. The results of the process and the outcomes were evaluated by applying the “Framework for Successful Priority Setting”. Results: This research found that the priority setting method developed is sustainable. Also, the methods succeeded in incorporating the social determinants of health and health equity into the analysis. A key strength of the study was the ability to incorporate the patients’ perspective in setting priorities for review topics. The lack of involvement of disadvantaged groups of the population was identified as a key limitation. Recommendations were put forward to incorporate the strengths of the study into future priority setting exercises within Cochrane and to address the limitations.

This dissertation investigates the determinants of China's exports and regional economic growth, the direction of causality between foreign direct investment (FDI) and exports; and convergence analysis among Chinese provinces. The study firstly discusses the evolutional process of China's foreign trade regime through comparing the strategies and policies before 1978 with those after 1978. It is emphasised that the export-promotion development policies result in the recent basic export patterns and characteristics. Furthermore, the study reviews the existing literature on exports, FDI, and convergence/growth determinants in the case of China. The empirical work comprises three parts. Firstly, fixed-effects ordinary least squares (OLS) and random-effects generalised least squares (GLS) panel data estimators are applied to test the determinants of provincial exports from 1994 to 2003. It is found that FDI, geographical location, investment in manufacturing innovation, and human capital have significant influences on regional export performance. Secondly, the augmented Dickey-Fuller (ADF) tests are carried out to test stationarity and the Granger causality tests are conducted to test the causal direction between FDI and exports, based on monthly national data from January, 2002 to June, 2006. The empirical results indicate that there is a one-way complementary causal link from FDI inflows to China's export flows. Thirdly, three methods, beta convergence, sigma convergence, and Markov Chain analysis, are used to do convergence debate among China's regions and the standard OLS cross-section and random-effects GLS panel data are applied to test the conditional convergence. The results suggest that the convergence hypothesis does not hold in China between 1994 and 2003 and there is a sign of conditional convergence, conditioning the explanatory variables such as exports, human capital, and population growth. / Thesis (Ph.D. (Economics))--North-West University, Potchefstroom Campus, 2007.

Background Hand-arm vibration (HAV) is an occupational hazard which, cumulatively, leads to hand-arm vibration syndrome (HAVS). Detection and reduction of HAV can help prevent the disease or slow down its progress. Unfortunately, assessment of HAV through direct measurement is difficult due to the high cost of measurement equipment, interruption of work performance, and long travel cost to worksites. An alternative assessment method is through development of an exposure prediction model to identify workplace, tool, and task characteristics which significantly predict HAV exposure. Purpose The purpose of this study is twofold: 1) to determine the extent and nature of previously published scientific journal articles on exposure prediction modeling of HAV through performing a systematic review; and 2) to develop a new exposure prediction model using administrative data to find significant HAV predictors. Methods A systematic review of relevant studies involved humans aged 18 or over, applicable to occupational setting, with vibration measured using tri-axial accelerometer and statistical modeling of the effects of occupational characteristics on measure HAV were identified. Five online bibliographic databases (Medline, CINAHL, Web of Science, Scopus, and EMBASE) were searched using a combined word list of terms under three categories: “occupational diseases”; “Hand-arm vibration”; and “Statistical Modelling”. Two multiple linear regression models predicting average hand-arm vibration exposure over 8 hour day, A(8), were built using enforcement data collected by Ministry of Labour Relations and Workplace Safety Saskatchewan using standard model building method. In addition, GEE was used to account for repeated data collection within workers and worksites. Results In the first manuscript, 7 articles found were deemed relevant. Four studies built regression models, while three used ANOVA to find significant HAV predictors. Examples of significant HAV predictors included: tool age, tool weight, participant, and operating power; the proportion of HAV variance explained varied from 46 to 90%. In the second manuscript, the models based on administrative data explained 16% to 27% of A(8) variance. The included variables were tool power source, vibration control, and job type for the parsimonious model; the comprehensive model has the same variables as parsimonious along with accelerometer attachment method and tool brand. Conclusion HAV prediction through exposure prediction modeling is a relatively new method for assessing occupational HAV. It is feasible to find HAV predictors using low-cost administrative data, and variables such as tool power source, job type, and vibration control make promising predictors. However, the variance explained will be lower than using data collected for research purposes. The significant predictors found in the systematic review can be considered when installing protective measures in the future. The significant predictors found and procedures used from the modeling study can be considered for future HAV exposure prediction modeling studies.

Mountain ecosystems are considered highly sensitive to the impacts of climate change, and are experiencing a magnitude of change that far exceeds global averages, particularly with respect to increases in average temperature and precipitation. As such, scientists are predicting a rapid habitat reduction or even the loss of the coolest climatic alpine zones, thus threatening the continued survival of high elevation specialists. However, many of these ‘doomsday’ predictions are based primarily on models with coarse-resolution changes to atmospheric climate parameters, and do not take into account the potential buffering effects of other environmental gradients known to structure alpine plant communities, related to topography and soils. To assess the accuracy of predictions regarding the state of vulnerability of alpine plant communities to climate change, this thesis examined the relative importance of climate, topography and soils as determinants of regional alpine plant diversity for all species, as well as for forbs, graminoids and woody species separately, in alpine meadows of southwestern British Columbia. Through redundancy analyses and variation partitioning, results show that topography and soils are more important than climate as determinants of regional alpine plant diversity. Within these groups, elevation, slope, soil moisture and mean summer temperature were most significant. Interestingly, precipitation played only a small role, even though the study area spanned a precipitation gradient of over 1200 mm/year. The stronger influence of temperature, especially for woody species beta diversity, supports findings of shrub expansion in arctic-alpine systems. The lower importance of climate as a determinant of regional alpine plant diversity, especially for forbs, the dominant life form in alpine meadow ecosystems, suggests that these productive environments may be more resilient to on-going changes in atmospheric climate conditions than previously believed. / Graduate

In Canada, accessible and culturally relevant population health data for urban First Nations, Métis and Inuit people are almost non-existent. There is a need for Aboriginal community centric research and data systems, specifically in the area of mental health and substance misuse. The goal of this research was to address these knowledge gaps. The three linked studies being presented were nested in the Our Health Counts (OHC) project, a multi-partnership study aimed at developing a baseline population health database for urban Aboriginal people living in Ontario. In the first study, concept mapping was used to engage urban Aboriginal stakeholders from three culturally diverse communities in identifying health priorities. After completing brainstorming, sorting and rating, and map interpretation sessions, three unique community specific maps emerged. Map clusters and their ratings reflected First Nations, Inuit, and Métis understandings of health. Concept mapping encouraged community participation and informed the development of three health assessment surveys. The second study generated a representative sample of First Nations adults and children living in Hamilton, Ontario by utilizing Respondent Driven Sampling (RDS), a modified chain-referral sampling approach. Population estimates were generated for household and personal income, mobility, over-crowding and food availability. Results revealed striking disparities in social determinants of health between First Nations and the general population. The third study used the RDS generated sample to examine mental health and substance misuse among First Nations adults living in Hamilton. Prevalence estimates were generated for diagnosis and treatment of a mental illness, depression, anxiety, post-traumatic stress disorder (PTSD), suicide, alcohol and substance misuse, and access to emotional supports. Findings indicated that First Nations adults living in Hamilton experience a disproportionate burden of mental health and substance misuse challenges. The three linked studies make innovative contributions to Aboriginal health research. Results clearly exemplify the effective application of community-based research methods that are grounded in local knowledge and built on existing community strengths and capacities. Representative population health data for urban First Nations will contribute to current deficiencies in health information; will shape policy and programming priorities as well as future research directions, particularly with respect to health and social disparities among this population.

Objectives: The overall aim was to investigate determinants and consequences of global non-comparative self-ratings of health (SRH). Concerning determinants, the aim was more specifically to investigate the association between age, year of investigation, stress-theory based psychobiological variables, and SRH. Materials and methods: Papers I and IV were based on eight ongoing population-based cohort studies, with sampling performed 1973-2003. The study-population consisted of 11,880 men and women, aged 25-99 years, providing 14,470 observations. Papers II and III were based on a longitudinal study of 212 adult, healthy, women and men. Results: In women, SRH declined linearly with age and year of investigation, after adjustment for influence of covariates, while in men the association was based on a third degree polynomial function. The most important covariates were complaint score, sick-leave or disability pension, and leisure time physical activity. The final model explained 76.2% of the variance in women and 74.5% in men. SRH was directly associated with psychological resources and inversely associated with psychological strain, in healthy, adult, women and men. In men with SRH which decreased to fair or poor, higher levels of prolactin and lower levels of testosterone were observed at follow-up as compared to baseline. There were no associations between endocrine variables and SRH in women. There was a significant inverse association between SRH and mortality, disability pension, and sick-leave during follow-up, in women and men, adjusted for covariates. Associations between SRH and mortality were robust during the follow-up period. Conclusions: Age and year of investigation were associated with SRH, but differently in women and men. Psychological resources and psychological strain were consistently associated with SRH, but there were no robust associations between endocrine measures and SRH. SRH was associated with mortality, disability pension, and sick-leave, during follow-up. The association between SRH and mortality was robust during the follow-up period

Most countries in the world are working hard to attract more foreign direct investment. Identifying the key determinants of foreign direct investment is therefore seen as a crucial task for policy makers. Compared to other parts of the world, the performance of Sub-Sahara African countries in attracting foreign direct investment is poor. This study deals with identifying the determinants of foreign direct investment inflow in Sub-Saharan Africa. The study employed panel data analysis: pooled ordinary least square method, fixed effects and Random Effect methods. Fourteen Sub-Saharan Africa countries were sampled for the study. Trade openness, gross domestic product, gross domestic product growth, gross domestic product per capita, telephone line (per 100 people), gross fixed capital formation, inflation and the lag of FDI are explanatory variables while the stock of FDI inflow is dependent variable. The analyzed data covered for the period 1986-2010.  The study finding shows that trade openness, gross domestic product, inflation, and lag of FDI are the most significant determinants of foreign direct investment inflows to sub-Saharan Africa.

Increased globalisation over the last two decades has led to strong growth of international business activity and FDI. Despite the considerable amount of research that has been undertaken to analyse the determinants and consequences of FDI, Australia represents a country with a substantial share of foreign ownership whose FDI experience has been largely overlooked in terms of a comprehensive economic analysis. Not only has Australia received a large amount of foreign investment so far, it is also competing for more FDI. Invest Australia, Australia’s national inward investment agency, is actively promoting Australia as a location for FDI, claiming that foreign investment has made a major contribution to Australia’s economic growth and living standards of all Australians. Instantly, two key issues arise. Firstly, assuming that FDI has positive effects, what causes the inflow of FDI, i.e. what are the determinants of FDI in Australia? Secondly, given the inflow of FDI, what is its actual effect on the Australian economy, i.e. what are the consequences of FDI in Australia? / In order to analyse those questions, new and previously unused data on FDI inflows in Australia were explored by applying time-series and panel-data analysis. The time period ranges from 1981 to 2002, with differing coverage for the individual samples. A further contribution of the thesis is the search for new FDI data, bringing together and analysing datasets provided by the ABS and other statistical agencies (from the US, the UK, Japan and Germany). A detailed description of Australian FDI data was given to gain a better understanding of the Australian FDI experience and because no such comprehensive summary has been available. / The first part of the analysis focused on the determinants of FDI. Determinants of FDI according to different theoretical models were discussed and tested using five types of datasets: aggregate quarterly data, country-specific annual data, industry-specific annual data, country- and industry-specific data (from the US, the UK, Japan and Germany and US) and US form-specific data. Australian FDI inflows were found to be driven by economic growth and market size, wages and labour supply (though the signs varied across models), trade and openness (though customs duties encouraged Japanese industry-specific FDI), interest rates, exchange rate appreciation, inflation rate (which had a unexpected positive effect) and the investing country’s overall FDI outflows. Corporate tax rates were only significant in the quarterly FDI model, but they had an unpredicted positive sign. Australian FDI was driven by longer term considerations and its determinants could not be fully explained by any single theory, but a variety of theoretical models. Furthermore investment decisions depend on factors such as investment origin, the industry in which the investment takes place and the form of the investment, making aggregation difficult. / The second part of the analysis focused on consequences of FDI. Consequences of FDI according to different theoretical models were discussed and tested using two types of datasets: aggregate quarterly data and industry-specific annual data. FDI inflows had positive effects on economic growth and domestic investment, supporting the Australian government’s view that FDI is a favourable source of capital. However, the claim that FDI is favourable for Australia’s balance of payments position could not be supported by this analysis. FDI led to a reduction in export growth and no direct effect on import growth, though the effect of FDI on GDP growth led to increased import growth. Furthermore, industry-specific FDI in Australia had significant effects on employment growth (negative) and labour productivity growth (positive), while FDI growth had significant effects on real wage growth (negative) and industry concentration (positive). However, effects may differ depending on the FDI form, and Australia should focus more on attracting beneficial FDI (such as export-oriented or import-substituting FDI) rather than FDI in general.

Thesis (Ph. D.)--University of Missouri--Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves : 128-138). Also available on the Internet.