Abstract
Regional disequilibrium adjustment frameworks, pioneered by Carlino and Mills (1987), have been widely employed for a broad range of regional and more disaggregated level research. In particular, the method has been more extensively used, after Boarnet (1994a) extended the original form of the adjustment model by introducing a spatial weight matrix into the equation system in order to explicitly consider the intrinsic spatial interdependence. So far, the applications include a variety of empirical analyses of growth dynamics, ranging from the examinations of the population-employment interaction (see e.g. Carlino and Mills 1987; Boarnet 1994b; Clark and Murphy 1996; Vias 1999) to the studies on spatial linkages (see e.g. Henry et al. 1997, 1999, 2001; Feser and Isserman 2005) and the investigations on development policy issues (see e.g. Bollinger and Ihlanfeldt. 1997; Edmiston 2004; Ke and Feser 2010).
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Notes
- 1.
By conducting a large number of experiments, Hoogstra et al. (2011) finds that the outcomes of the empirical studies on this population–employment interactions can differ by many other factors, such as measurements and spatial weight matrix specification.
- 2.
Given the methodological advantages, REIMs have long been widely used for regional socio-economic forecasting and various types of advanced policy and/or impact analyses (Kim and Hewings 2011).
- 3.
Cuaresma and Feldkircher (2010) has provided significant evidence that the choice of weight matrix is important, challenging the received assumption to the contrary.
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Kim, J.H., Hewings, G.J.D. (2012). An Application of the Disequilibrium Adjustment Framework to Small Area Forecasting and Impact Analysis. In: Fernández Vázquez, E., Rubiera Morollón, F. (eds) Defining the Spatial Scale in Modern Regional Analysis. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31994-5_7
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