Thesis (Ph. D.)--University of Missouri--Columbia, 1999. / "May 1999." Typescript. Vita. Includes bibliographical references (leaves 103-107). Also available on the Internet.

Thesis (M.A.)--York University, 2005. Graduate Programme in Psychology. / Typescript. Includes bibliographical references (leaves 45-49). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url%5Fver=Z39.88-2004&res%5Fdat=xri:pqdiss &rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR11745

Yes / This study investigates whether, how and why industry performance can drive long-term return reversals. Using data from the UK, we find that firms in losing industries significantly outperform those in winning industries over the subsequent five years. These industry reversals remain strong and persistent after controlling for stock momentum, industry momentum, seasonal effects and traditional risk factors. We find a strong influence of past industry performance on stock return reversals. Our results also show that past industry performance is the driving force behind long-term reversals. Specifically, we find that industry components drive stock reversals, while past stock performance does not explain industry reversals. Further analysis suggests that industry reversals are present in both good and bad states of the economy and are stronger in industries with high valuation uncertainty. This implies that industry reversals are more likely to be a result of mispricing.

Wind is a fluctuating source of energy and, therefore, it can cause several technical impacts. These can be tackled by forecasting wind speed and thus wind power. The introduction of several statistical models in this field of research has brought to light promising results for improving wind speed predictions. However, there is not converging evidence on which is the optimal method. Over the last three decades, significant research has been carried out in the field of short-term forecasting using statistical models though less work focuses on longer timescales. The first part of this work concentrated on long-term wind speed variability over the UK. Two subsets have been used for assessing the variability of wind speed in the UK on both temporal and spatial coverage over a period representative of the expected lifespan of a wind farm. Two wind indices are presented with a calculated standard deviation of 4% . This value reveals that such changes in the average UK wind power capacity factor is equal to 7%. A parallel line of the research reported herein aimed to develop a novel statistical forecasting model for generating monthly mean wind speed predictions. It utilised long-term historic wind speed records from surface stations as well as reanalysis data. The methodology employed a SARIMAX model that incorporated monthly autocorrelation of wind speed and seasonality, and also included exogenous inputs. Four different cases were examined, each of which incorporated different independent variables. The results disclosed a strong association between the independent variables and wind speed showing correlations up to 0.72. Depending on each case, this relationship occurred from 4- up to 12-month lags. The inter comparison revealed an improvement in the forecasting accuracy of the proposed model compared to a similar model that did not take into account exogenous variables. This finding demonstrates the indisputable potential of using a SARIMAX for long-term wind speed forecasting.

Macrodiversity system is a communication architecture where base stations (BS) act as distributed nodes of a multiple-input multiple-output (MIMO) antennas. It has many promising features that can improve system performance from a network perspective, such as improving the weak signals of users affected by shadow fading, or users at the cell-edge. They also allow multiple users to share the same resource in time and frequency, improving the overall user capacity. Traditionally, evaluating the link quality of resource-sharing users requires instantaneous channel state information (CSI). However, finding compatible users to share resource in macrodiversity systems is a challenging task. For macrodiversity systems, instantaneous CSI could be passed to the backhaul processing unit (BPU) through the network backhaul. This creates a delay in the signal, and makes instantaneous CSI a less accurate reflection of the channel environment at the time. Passing instantaneous CSI of all users also creates a significant amount of network overheads, reducing the overall efficiency of the network. Compared to MIMO systems with co-located antennas, macrodiversity systems cover a larger geographical area and more users. For this reason, the number of user selection combinations can become extremely large, making scheduling decisions in real time an even more challenging task. These problems limit the realisation of the user capacity potential of macrodiversity systems. This thesis presents a low complexity method of resource allocation for up-link macrodiversity systems. In particular, it uses long-term power to estimate the link quality of resource-sharing users. Using long-term power bypasses the issue of channel estimation error introduced by the network delay, and it also reduces the communication overhead on the network backhaul. In this thesis, we use Symbol-Error Rate (SER) as the measure for link quality. Using the method developed by Basnayaka [1], we are able to estimate SER of resource-sharing users using long-term power. Using the SER estimation method, we further proposed a user compatibility check (UCC), which evaluates the compatibility of users sharing the same resource. Users are only considered compatible with each other if all of them meet a pre-defined SER threshold. We attempt to reduce the complexity of user selection by using heuristic solution-finding methods. In our research, we found that greedy algorithms have the least complexity. We propose four low-complexity user selection algorithms based on a greedy algorithm. These algorithms are simulated under different environment parameters. We evaluate the system performance in terms of utilisation and complexity. Utilisation refers to the percentage of allocated users compared to the theoretical user capacity. Complexity refers to the number of SER calculations required to find a resource allocation solution. From the simulation results, we observed that with the proposed user selection algorithms, we can achieve moderately high utilisation with much lower complexity, compared to finding user selections via an exhaustive search method. Out of the proposed user selection algorithms, the Priority Order with Sequential Removal (PO+SR) and the First-Fit (FF) algorithm have the best overall performance, in terms of the trade-off between utilisation performance, and complexity performance. The final choice of the algorithm will depend on the processing power and the system performance requirement of the macrodiversity system.

One of the most controversial issues for long-term stock performance is whether the presence of anomalies is against the efficient market hypothesis. The methodologies to measure abnormal returns applied in the long-run event studies are questioned for their reliability and specification. This thesis compares three major methodologies via a simulation process based on the UK stock market over a period of 1982 to 2008 with investment horizons of one, three and five years. Specifically, the methodologies that are compared are the event-time methods based on models (Chapter 3), the event-time methods based on reference portfolios (Chapter 4), and the calendar-time methods (Chapter 5). Chapter 3 covers the event-time approach based on the following models which are used to estimate normal stock returns: the market-adjusted model, the market model, the capital asset pricing model, the Fama-French three-factor model and the Carhart four-factor model. The measurement of CARs yields misspecification with higher rejection rates of the null hypothesis of zero abnormal returns. Although the application of standard errors estimated from the test period improves the misspecification, CARs still yield misspecified test statistics. When using BHARs, well-specified results are achieved when applying the market-adjusted model, capital asset pricing model and Fama-French three-factor model over all investment horizons. It is important to note that the market model is severely misspecified with the highest rejection rates under both measurements. The empirical results from simulations of event-time methods based on reference portfolios in Chapter 4 indicate that the application of BHARs in conjunction with p-value from pseudoportfolios is appropriate for application in the context of long-run event studies. Furthermore, the control firm approach together with student t-test statistics is proved to yield well-specified test statistics in both random and non-random samples. Firms in reference portfolios and control firms are selected on the basis of size, BTM or both. However, in terms of power of test, these two approaches have the least power whereas the skewness-adjusted test and bootstrapped skewness-adjusted test have the highest power. It is worth noting that when the non-random samples are examined, the benchmark portfolio or control firm needs to share at least one characteristic with the event firm. The calendar-time approach is suggested in the literature to overcome potential issues with event-time approaches like overlapping returns and calendar month clustering. Chapter 5 suggests that both three-factor and four-factor models present significant overrejections of the null hypothesis of zero abnormal returns under an equally-weighted scheme. Even for stocks under a value-weighted scheme, the rejection rate for small firms shows overrejection. This indicates the small size effect is more prevalent in the UK stock market than in the US and the calendar-time approach cannot resolve this issue. Compared with the three-factor model, the four-factor model, despite its higher explanatory power, improves the results under a value-weighted scheme. The ordinary least squares technique in the regression produces the smallest rejection rates compared with weighted least squares, sandwich variance estimators and generalized weighted least squares. The mean monthly calendar time returns, combining the reference portfolios and calendar time, show similar results to the event-time approach based on reference portfolios. The weighting scheme plays an insignificant role in this approach. The empirical results suggest the following methods are appropriately applied to detect the long-term abnormal stock performance. When the event-time approach is applied based on models, although the measurement of BHARs together with the market-adjusted model, capital asset pricing model and Fama-French three-factor model generate well-specified results, the test statistics are not reliable because BHARs show severe positively skewed and leptokurtic distribution. Moreover, the reference portfolios in conjunction with p-value from pseudoportfolios and the control firm approach with student t test in the event-time approach are advocated although with lower power of test. When it comes to the calendar-time approach, the three-factor model under OLS together with sandwich variance estimators using the value-weighted scheme and the mean monthly calendar-time abnormal returns under equal weights are proved to be the most appropriate methods.

In this thesis, the overall purpose was to investigate the role of regulation in the care of older people with depression living in long-term care (LTC). The first manuscript in this thesis is a systematic scoping review protocol which was published in BMJ open, using Arksey and O'Malley's scoping review methodology as a guide. In the second manuscript which was submitted to BMC Geriatrics, a systematic scoping review was conducted, exploring the concepts of regulation, older people, depression, and long-term care. The search yielded 778 unique articles, of which 21 were included in the final analysis. The scoping review revealed that the highly regulated environment of LTC poses significant challenges which can influence the quality of care of residents with depression. Despite evidence of high prevalence and improved treatment, regulation appears to have failed to capture best practice and contemporary knowledge. The scoping review demonstrated a need for further empirical research to explore these issues. Findings from this study, which explored the role of regulation on the quality of care of older people living with depression in LTC are presented, and which were the basis of the third manuscript, to the Canadian Journal of Aging. Using instrumental case study methodology, I interviewed managers, staff, informal carers and residents, and reviewed documents and clinical charts. I found that Ministry of Health and Long-Term Care regulations influenced strategic planning, educational priorities, resourcing decisions and direct care. The findings from the study suggest an alternative approach to regulation is needed in this sector, which places accountability for standards of care at a provincial level and which has a more supportive and collaborative approach to regulations. The research findings showed that the staff working in the LTC home are committed to the care of residents with depression, but they had little time to implement additional quality initiatives outside of the identified mandated areas. The study concludes by suggesting that in its current state, the care of residents with depression in LTC homes is not reflected in Ministry of Health and Long-Term Care regulations and inspections, which make little difference to the care of older people living with depression living in LTC. In contributing to the existing knowledge and practice the study along with the findings from the scoping review, finds an alternative model of inspection could be implemented in partnership with the province. An alternative approach to inspection might adopt an extended approach to quality, along with an individualized approach to inspections to meet the requirements set out in regulation, but at the same time offering flexibility and a more collaborative approach to improving quality in the LTC sector.

I examine the market reaction to merger announcements and the long-term post-merger stock price performance of newly merged firms. For a sample of 484 acquiring firms completing mergers between 1993 and 2000, the average value-weighted abnormal announcement date return (market-adjusted) is a statistically significant -1.02%. On average, this reaction is more negative for firms with "good governance." Specifically, a governance index comprised of three governance variables is significantly negative in a multivariate regression of announcement date abnormal returns. Comp is the percentage of CEO salary consisting of equity incentives (including stock options and restricted stock grants), InsideOwn is the percentage of the firm owned by officers and directors, and InstOwn is the percentage of the firm owned by large outside block shareholders. Value-weighted calendar-time portfolios consisting of the full sample of acquirers exhibit significant abnormal returns of 9.12%, 33.84% and 55.8% for the 12, 36 and 60 months following the merger, respectively. This overperformance is limited to the value-weighted portfolios. There is calendar-time evidence of abnormal performance for some subsamples on a risk adjusted basis. However, when compared to a control group, abnormal performance is limited to large glamour acquirers on a 12-month horizon, large cash acquirers on a 36 and 60-month horizon, and small focusing acquirers on a 60-month horizon. Multivariate analysis of long-run returns reveals that use of equity and corporate diversification are associated with lower post-merger performance. With regard to governance and long-run stock returns, there is also evidence that suggests higher levels of incentive compensation for CEOs is associated with more successful merger transactions for long-term investors.

This thesis explores Korean-Chinese migrant workers’ local experiences of the global phenomenon of international migration of care labour, focusing on how the care labour of migrant workers is being constructed through the intertwined social and political processes in South Korea’s shifting long-term care sector for the elderly. The thesis uses a qualitative case study method and relies on data collected through participant observation, interviews, and textual analysis during field research between November 2009 and May 2010. The analysis is based on a global economy of care framework, which understands care work as being made of products that are socially and politically constructed in the global processes. My study findings illuminate the roles and relations of the state, the employers, and the workers in producing a huge migrant workforce in South Korea’s segregated elder care labour market. The policy analysis at the intersection of elder care, labour market, and immigration policies shows that, over the last decade, the South Korean government has significantly reconstructed the boundaries of elder care work through the expansion of publicly-funded programmes for the elderly and the institutionalisation of care work in those programmes. In the institutionalisation process, the government’s ignorance about the care work performed in the private care sector has resulted in different regulations and working conditions for care workers in the publicly-funded versus the private sector. My empirical findings highlight how employers’ search for ‘cheap’ and ‘flexible’ labour and older female migrants’ disadvantageous status in the labour market have placed these workers in the less regulated private sector and their pay and working conditions at the bottom of hierarchical elder care workforce. In advocating for migrant care workers’ labour rights, this thesis challenges the current discriminative employment practices and the government’s lack of protection and regulation of care work in the private sector.

This thesis explores Korean-Chinese migrant workers’ local experiences of the global phenomenon of international migration of care labour, focusing on how the care labour of migrant workers is being constructed through the intertwined social and political processes in South Korea’s shifting long-term care sector for the elderly. The thesis uses a qualitative case study method and relies on data collected through participant observation, interviews, and textual analysis during field research between November 2009 and May 2010. The analysis is based on a global economy of care framework, which understands care work as being made of products that are socially and politically constructed in the global processes. My study findings illuminate the roles and relations of the state, the employers, and the workers in producing a huge migrant workforce in South Korea’s segregated elder care labour market. The policy analysis at the intersection of elder care, labour market, and immigration policies shows that, over the last decade, the South Korean government has significantly reconstructed the boundaries of elder care work through the expansion of publicly-funded programmes for the elderly and the institutionalisation of care work in those programmes. In the institutionalisation process, the government’s ignorance about the care work performed in the private care sector has resulted in different regulations and working conditions for care workers in the publicly-funded versus the private sector. My empirical findings highlight how employers’ search for ‘cheap’ and ‘flexible’ labour and older female migrants’ disadvantageous status in the labour market have placed these workers in the less regulated private sector and their pay and working conditions at the bottom of hierarchical elder care workforce. In advocating for migrant care workers’ labour rights, this thesis challenges the current discriminative employment practices and the government’s lack of protection and regulation of care work in the private sector.