Youth crime has been increasing rapidly since the Economy Reform and Open-door Policy in 1979 and become a serious social problem in China. Researches on explanations of juvenile delinquency, however, are relatively limited, while a number of scholars in western countries have developed delicate theoretical models to explore this problem. General strain, differential association, and social bond theory are employed in the current study to test if western theories can be applied to a different social context and to empirically explain the causes of youth crime in China. An integrated model is addressed through a self-reported survey with 385 respondents. The respondents are high school students in the city of Shenyang, aged from 16 to 18. Data from the questionnaire survey suggests that these three theories could explain Chinese youth crime. Two separate Ordinary Least Squares (OLS) models are built for analyzing delinquency of males and females. Predictors related to strain and differential association theory are directly associated with youth crime, while weak social bonds have indirect impacts on juvenile delinquency. Males and females are influenced by different factors when they are involved in delinquency. The thesis concludes with a discussion of establishing a theoretical integrated model for Chinese adolescence and provides policy implications for protection programs.

Youth crime has been increasing rapidly since the Economy Reform and Open-door Policy in 1979 and become a serious social problem in China. Researches on explanations of juvenile delinquency, however, are relatively limited, while a number of scholars in western countries have developed delicate theoretical models to explore this problem. General strain, differential association, and social bond theory are employed in the current study to test if western theories can be applied to a different social context and to empirically explain the causes of youth crime in China. An integrated model is addressed through a self-reported survey with 385 respondents. The respondents are high school students in the city of Shenyang, aged from 16 to 18. Data from the questionnaire survey suggests that these three theories could explain Chinese youth crime. Two separate Ordinary Least Squares (OLS) models are built for analyzing delinquency of males and females. Predictors related to strain and differential association theory are directly associated with youth crime, while weak social bonds have indirect impacts on juvenile delinquency. Males and females are influenced by different factors when they are involved in delinquency. The thesis concludes with a discussion of establishing a theoretical integrated model for Chinese adolescence and provides policy implications for protection programs.

This work outlines several aspects of multiple time series analysis, which are then demonstrated on a large set of data. After introducing the general autoregressive integrated moving average model, discussion is restricted to a canonical form: the pure autoregressive process of order p (AR(p)). Methods for identifying and fitting the AR(p) process using quasi-partial correlation matrices and Akaike's AIC criterion are discussed. The AR model can then be used to make forecasts by taking conditional expectations at the origin time. Probability limits on the forecasts are also defined. A method for canonical analysis of AR processes is described which can indicate possible reductions in the dimensionality of the problem. Using computer programs developed for this project, the above methods are applied to an 11-dimensional set of Canadian economic data and the results are discussed. / Thesis / Master of Science (MSc)

Computerised integrated models from science contribute to better informed and holistic exante integrated assessments of multifaceted policies and technologies. This view has lead to considerable effort being devoted to developing integrated models to support decisionmaking under Integrated Water Resources Management (IWRM). Nevertheless, an appraisal of previous and ongoing efforts to develop such decision support systems shows that attempts to address the hydro-socio-economic effects on livelihoods have been deficient and fragmented. To date, no universal standard integration method or framework is in use. Existing integrated models application failures have pointed to the lack of stakeholder participation. In an endeavour to close this gap, this thesis focuses on an integrated model development with prediction capability, ICHSEA, developed in Avenues script language in ArcView 3.3, to take advantage of the mapping capability of ArcView. This model couples existing hydrology (SWAT), agronomy (PARCHED-THIRST) and socio-economic (OLYMPE) models to link livelihoods of resource-constrained smallholder farmers to water resources availability at catchment level in the semi-arid Olifants subbasin, South Africa. These three models were calibrated and validated using observed data and local stakeholder participation, prior to coupling in the integrated model. All the models performed well in representing the study conditions, as indicated by the statistical performance. The integrated model is generally applicable to any catchment. The study methodology was inspired by the need to enhance rural livelihoods and to close the gap of stakeholder involvement in building and applying integrated models to ensure acceptability and application in decision-making. Over 20 years, the predicted impacts of untied ridges and planting basins versus conventional rainfed tillage on surface runoff reduction were 14.3 % and 19.8 %, respectively, and about 41─46 % sediment yield reduction in the catchment. At 90 % confidence interval, family savings improved from US$ 4─US$ 270 under conventional rainfed to US$ 233─US$ 1 140 under supplemental irrigation. These results underscore the economic and environmental benefits that could be achieved by adopting the new crop management practices. A relationship between maize crop evapotranspiration and family savings under different crop management strategies was also derived for five farm typologies in the catchment.

Wetland, which contains about 20 - 30% of global soil carbon pool (Lal, 2008), is one of the world’s most important environmental resources for long-term carbon storage, and plays a vital role in global carbon cycling, especially in mitigating carbon concentration in the atmosphere. However, it is also the ecosystem that has been most seriously abused and suffering from continuous degradation and loss across the world. During the past few centuries, about 50% of the world’s wetland has been lost due to increasing anthropogenic disturbances and global warming (Mitsch & Gosselink, 2007; Gibbs, 2000; Dugan, 1993; Zedler and Kercher, 2005). One typical example is the wetland in Dongting Lake area of China, which was once China’s largest freshwater wetland and now has become the second one. During the past few decades, the Lake has experienced many significant changes causing the rapid degradation, shrinkage and fragmentation of its wetland. Therefore, monitoring the changes of the Lake wetland in spatial distribution and temporal trend and predicting its potential dynamics under climate change and human induced disturbances are becoming increasingly important for linking policy decision-making with regulatory actions and subsequent land-use activities. The overall objective of this project is to monitor the wetland changes in the Lake area and predict its dynamics in the future using proposed land use and land cover (LULC) classification, change detection and modelling approaches. To start with, this study examined the spatiotemporal dynamics of the Lake wetland patterns during the past half century through analyzing remotely sensed images acquired on six time points, including 1978, 1984, 1994, 2001, 2004, 2009, and 2013. A hybrid knowledge-based classification method which combines supervised and expert classification systems was first applied to conduct image classifications with special attention to the classification accuracy of the wetland categories including water, paddy field, reed and marsh categories. After that, a post-classification based change detection technique was carried out to monitor the dynamics of the Lake wetland. The error matrices and Kappa coefficients were than used to assess the classification accuracy. The classification results demonstrated that the proposed hybrid classification approach could discriminate the wetland categories from others with the high accuracy of 96.9%, 93.7%, 82.6%, and 82.4% for water, paddy field, reed, and marsh categories, respectively. The LULC analysis based on the classification showed that wetland area (reed and marsh) in the Lake area has decreased with a dramatic decrease trend after the Three Gorges Dam being fully operated in 2003. To predict future wetland changes and allocate the changes effectively, an integrated model incorporating the logistic, the Markov, and the Conversion of Land use and its Effects (CLUE-S) models has been developed and utilized to 1) produce the LULC probability surface maps; 2) to simulate the LULC change demand in 2013 and 2025 of which the demand for 2013 was then used for validating the results of this integrated model by comparing with the actual LULC maps of the same year; 3) to allocate the simulated changes of 2013 and 2025 based on the obtained LULC probability surface maps and some user-defined rules including land use conversion rules and conversion elasticity. The results from the model validation indicated that the integrated model performed very well with an overall modelling accuracy and Kappa statistic of 80.2% and 74.9%, respectively. The results also suggested that the wetland area is likely to undergo further decrease of another 256.3 km2 by 2025. In summary, this study focused on the development of a unique and integrated approach for the LULC image classification, change detection and prediction of the wetland area – Dongting Lake region in which the landscape was complex and experiencing fast and dramatic changes due to the construction of the TGD. The approach can be easily extended to other wetland associated studies. By providing the information of the long-term wetland dynamics and simulation of its future changes in the Lake area, this research will also enhance our understanding of wetland resources, their dynamics and relationships with human activity induced disturbances and thus promote our ability to make informed use and wise restoration regulations of wetlands.

This study constructs a cross-market risk model based upon local multi-factor risk models of Taiwan and China equity markets. We employ world, country, industry, and global risk factors to build a structural model which could explain the relationship between local factors across markets by further decomposing local factor returns. Under the structure, this model allows each local market to adopt different local factors rather than force all local markets to use one parsimonious set of factors. Therefore, this model could provide both in-depth and broad coverage analysis of international equity portfolios. The innovative methodology is first introduced by Barra as the Integrated Model. Moreover, we build a simple portfolio and its corresponding benchmark to illustrate the power of our model. Once the contents of a portfolio are decided, this model could provide not only the risk estimation and decomposition in advance but also the performance attribution compared with the benchmark after the portfolio is realized. The analytical viewpoint could also easily change with different numeraire perspectives. The result demonstrates that this model is practical and flexible for international equity portfolio analysis.

The Integrated Land Use, Transportation, Environment (ILUTE) modelling system simulates the activities of agents within the Greater Toronto and Hamilton Area (GTHA) as they evolve over time. However, in its currently implemented form, ILUTE lacks an endogenous treatment of the labour market and the associated wages. This is seen as the major weakness of the current model. This work describes a labour market framework to partially fill this gap and then develops the dynamic disaggregate model of year to year transitions of the labour force status of the people within the GTHA and the set of wage models components of this framework. The data used is a sample of individuals from the Toronto, Oshawa, and Hamilton Census Metropolitan Areas surveyed over twelve consecutive years between 1995 and 2007 in the Survey of Labour and Income Dynamics.

The Integrated Land Use, Transportation, Environment (ILUTE) modelling system simulates the activities of agents within the Greater Toronto and Hamilton Area (GTHA) as they evolve over time. However, in its currently implemented form, ILUTE lacks an endogenous treatment of the labour market and the associated wages. This is seen as the major weakness of the current model. This work describes a labour market framework to partially fill this gap and then develops the dynamic disaggregate model of year to year transitions of the labour force status of the people within the GTHA and the set of wage models components of this framework. The data used is a sample of individuals from the Toronto, Oshawa, and Hamilton Census Metropolitan Areas surveyed over twelve consecutive years between 1995 and 2007 in the Survey of Labour and Income Dynamics.

The Integrated Land Use, Transportation, Environment (ILUTE) modelling system simulates the activities of agents within the Greater Toronto and Hamilton Area (GTHA) as they evolve over time. However, in its currently implemented form, ILUTE lacks an endogenous treatment of the labour market and the associated wages. This is seen as the major weakness of the current model. This work describes a labour market framework to partially fill this gap and then develops the dynamic disaggregate model of year to year transitions of the labour force status of the people within the GTHA and the set of wage models components of this framework. The data used is a sample of individuals from the Toronto, Oshawa, and Hamilton Census Metropolitan Areas surveyed over twelve consecutive years between 1995 and 2007 in the Survey of Labour and Income Dynamics.

The Integrated Land Use, Transportation, Environment (ILUTE) modelling system simulates the activities of agents within the Greater Toronto and Hamilton Area (GTHA) as they evolve over time. However, in its currently implemented form, ILUTE lacks an endogenous treatment of the labour market and the associated wages. This is seen as the major weakness of the current model. This work describes a labour market framework to partially fill this gap and then develops the dynamic disaggregate model of year to year transitions of the labour force status of the people within the GTHA and the set of wage models components of this framework. The data used is a sample of individuals from the Toronto, Oshawa, and Hamilton Census Metropolitan Areas surveyed over twelve consecutive years between 1995 and 2007 in the Survey of Labour and Income Dynamics.