Developing an Employment Location model for the Hamilton CMA

Abstract

<p>In this Thesis, the spatial distribution of employment is modeled for the Hamilton CMA. A behavioral employment location model is constructed, estimated, implemented and tested. Employment mobility is associated with the redistribution of firms in the region, thus, the spatial distribution of firms is modeled and employment location is inferred from that. Manufacturing, construction, wholesale trade, retail trade and services sectors are modeled. Sectors like the communication, transportation, government services and educational services are given exogenously to the model. Three models form the elements of the employment model. The first is an Input-Output Model, which captures the linkages between the different sectors of the economy and predicts the regional employment in each industry. The second is a destination choice model having in its elements a Multinomial Logit Model that predicts the choice probability of new and relocating firms. The third model is a regression model having in its elements both a spatial regression (SAR model) and non-spatial (classical) regression model. The model predicts the number of lost firms. The last two models predict firms at the census tract level. Estimation results indicate that firms in the different industries show a systematic behavior in choosing a site to locate at. Factors such as the CBD proximity, highway proximity, mall proximity, population size, household density, and agglomeration economies affect the locational decision of the different types of firms. Moreover, the analysis shows that loss of firms is linearly related to the total number of firms at the census tract level. The employment model is implemented using the GAUSS programming language. The model shows a significant goodness-of-fit when comparing the predicted values of employment with the observed with an r-square value of 0.91. Scenario simulation is also achieved using the implemented model. The model shows its capability of simulating certain types of scenarios.</p>