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UBC Theses and Dissertations

Economic determinants of interprovincial migration in British Columbia Trépanier, Marie


Given the fundamental importance of population base to the level of economic activity, an accurate population estimate is essential to most planners. Interprovincial migration is the major factor in differing regional population growth. Hence an understanding of the Canadian "footloose" behaviour of individuals is invaluable. The purpose of this thesis was twofold: first to find the economic determinants of interprovincial migration for two-age cohorts (the working and the retired), for the 1966-1981 (ex-post) and second to forecast the number of working migrants for 1982 (ex-ante). The case of British Columbia was used. The main sources of migration data were the number of account transfers for family allowance and old age security benefits. Structural and time-series models were investigated. The former were used for explaining and forecasting purposes and the latter for forecasting purposes only. The techniques applied were ordinary least squares for the structural models and unconditional non-linear least squares with back forecasting (Box and Jenkins) for the time-series models. The outcome was that income variables, labour variables, housing prices, personal taxes, cost of living variables and housing market variables were all significant determinants of interprovincial migration. One exception was the out-migration of the elderly group where only housing prices and cost of living variables had any significance. The results also indicated that first the elderly were more sensitive to housing prices, personal taxes and cost of living differentials between British Columbia and the rest of Canada and second the two-age cohorts had similar elasticities to migrate for labour and housing market variables. Finally, in combining ex-ante and ex-post results, it was shown that the optimum solution for determining net migration of the working was in-migration estimates minus out-migration estimates using the structural models.

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