<p>As a mid-size industrial city in North America, the City of Hamilton has been increasingly experiencing urban sprawl in the past six decades coupled with population growth and economic development. The study of various interdependent processes driving the evolution of urban form requires the application of simulation models that offer urban planners and policy-makers an efficient means for evaluating urban development policies. This thesis focuses on the modeling efforts towards building a microsimulation residential housing market system for the City of Hamilton. To this end, two major tasks have been conducted in this research. First, a state-of-the-art agent-based microsimulation housing market framework has been designed. Second, two model components in the microsimulation framework, namely a real estate appraisal model and a new housing development model, have been estimated. The objective of the real estate appraisal model is to assess the market values of existing dwellings based on the housing transactions in the previous period. Thre e model forms, including a traditional hedonic model, a spatial regression model, and a regression Kriging model, have been employed in estimations for comparison purposes. A series of independent variables that describe the characteristics of dwelling, location, and neighborhood are specified in the explanatory model. The comparisons among estimation results demonstrate that the spatial regression model has achieved a higher goodness-of-fit than the traditional hedonic model. In addition, we verified that spatial autocorrelation is present in the residuals of the traditional hedonic model, which is explicitly captured by the spatial regression model. In terms of model prediction accuracy, spatial models (SAR and Kriging) both achieve a certain level of improvements over the traditional hedonic model. Overall, we end up recommending that the SAR model is more appropriate to be incorporated into the microsimulation framework, as it provides the best match between predicted and observed values. The new housing development model enables the development of a dynamic housing supply module in the simulation framework by modeling the location and type decisions during the housing development process for each year. A parcel -level two-tier nested-logit model has been estimated. The model is able to deal with not only the decision to develop a specific vacant residential land parcel, but also the development type choice. In terms of the factors influencing the decision to develop, the picture revealed from the model estimation results is that land developers are more likely to start a development project in greenfields than in brownfields. As for the type choice decision during the development process, a variety of variables describing transportation accessibility, residential amenities, the characteristics of the land parcel and neighborhood are included in the model specifications.</p> / Master of Arts (MA)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/11211 |
| Date | 10 1900 |
| Creators | Liu, Xudong |
| Contributors | Kanaroglou, Pavlos, Darren Scott; Antonio Paez, Darren Scott; Antonio Paez, Geography and Earth Sciences |
| Source Sets | McMaster University |
| Detected Language | English |
| Type | thesis |
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