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The determinants of rural and urban community population change over the period 1991-2001 are investigated at a very fine level of disaggregation for Canada. The study examines the influence of local amenities, economic factors, and agglomeration economies on population growth for age cohorts starting from the very young to the elderly. Motivated by the objective of assessing the overall jobs versus people question in economic development, the emphasis is on estimating the relative contribution of groupings of variables in explaining the variations in population change rather than the contribution of individual variables. Results indicate that rural and urban populations are influenced to differing degrees by amenity, economic, and urban scale groupings of variables and that there are variations among age cohorts in both urban and rural areas. While economic variables are the most influential in population change for all rural cohorts, their contribution somewhat diminishes with age. In urban areas, amenity, and economic variable groupings have approximately equal importance across all cohorts. For the key young adult cohort, the economic grouping is clearly the most influential in rural areas, while it is a close second to amenities in urban areas. Copyright 2007 Blackwell Publishing.

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Commuting ties between rural places of residence and urban places of employment are among the most visible forms of rural-urban integration. For some rural areas, access to urban employment is a key source of population retention and growth. However, this access varies considerably across rural areas, with distance representing a primary deterrent. In addition to distance, the size of the urban community will also influence rural-to-urban commuting opportunities. In this paper, using Canadian data, we empirically estimated the influence of local rural population and job growth on rural out-commuting within the urban hierarchy. We find consistent support for the deconcentration hypothesis where population moves to rural areas for lifestyle and quality of life reasons, while retaining urban employment. Further, we find some evidence that in addition to distance from the nearest urban center being a deterrent, increased remoteness from the top of the urban hierarchy exerts a "positive" influence on out-commuting. Recognition of these types of rural-urban linkages through commuting is essential in designing Canadian rural policy and targeted programs that may effectively support local rural populations. In particular, they point to the need to have reasonable transportation infrastructure for urban accessibility, which should be complemented by other "built" infrastructure to improve the livability of rural communities. Copyright (c) 2010 Copyright the Authors. Journal compilation (c) 2010 Wiley Periodicals, Inc..

Although the New Economic Geography (NEG) has been used extensively to formally explain the emergence of the American urban system, few studies investigate its success in explaining current population dynamics in a more established urban system. This study explores whether proximity to same-sized and higher-tiered urban centres affected the patterns of 1990-2006 US county population growth. Rather than casting NEG agglomeration shadows on nearby growth, larger urban centres generally appear to have positive growth effects for more proximate places of less than 250,000 people. However, there is some evidence the largest urban areas cast growth shadows on proximate medium-sized metropolitan areas and of spatial competition among small metropolitan areas. Copyright (c) 2009 the author(s). Journal compilation (c) 2009 RSAI.

Policy design in a regional context requires explicit recognition of spatial heterogeneity in community characteristics as well as in the heterogeneity of how these characteristics impact the target variables. By providing only a “global” measure for the entire space, standard approaches such as ordinary least squares or (most) spatial econometric models tend to compromise spatial heterogeneity in favor of average estimates and efficiency. More assessment is needed of whether the gains of simplicity and statistical efficiency offset the losses from ignoring spatial heterogeneity. Using data for about 1,900 rural Canadian communities as a backdrop, the authors address this issue using a geographically weighted regression approach. The authors find that for about two-thirds of the variables, standard approaches would have significantly understated the spatial differences in the impact of selected variables. Standard analysis would not have uncovered this information, suggesting that subsequent policy inferences would be poorly suited to many local settings.