The black box of regional growth

Abstract

Regional growth models leave a large share of variation unexplained. While we should continuously aim to improve these models, the unique combination of conditions and human agency in each region will also invariably lead to region-specific growth trajectories. Theoretically, we should thus expect systematic deviations from growth predictions. We propose an approach to explore these unexplained deviations and to detect regions that perform unexpectedly well or badly in certain periods. We illustrate the approach using data for Sweden from 1990 to 2016. We find systematic patterns of unexplained periodic regional growth deviations outweighing the effect of generic structural factors.

Path tracing in the study of agency and structures: Methodological considerations

“…Lagendijk (2007) maintains that structural analysis would examine how ecological, economic, political, and social trajectories and institutions privilege some regions but not others. It would approach path development as essentially an outcome of structures, production systems, state restructuring and globalisation, for example (Grillitsch et al, 2021). Conversely, an agency-oriented study would approach regions as constructed through myriad processes, each reflecting their logic and practices (Lagendijk, 2007: 1194).…”

“…The main purpose of taking inspiration from process studies is to gain analytical leverage by focussing on patterns of agency and relations (necessary and contingent) among objects in time. The main difference between path tracing and process tracing (or analysis of organisational change) is that path tracing expands process tracing to cover changes in material and social worlds (see Grillitsch et al, 2021). It is central to remember that path tracing operates in a multi-process context.…”

Advancing the treatment of human agency in the analysis of regional economic development: Illustrated with three Norwegian cases

“…In each year, we standardized the residuals from the growth regression so that the distribution of residuals had a mean of 0 and a standard deviation of 1. We then considered only those regions that exhibited periods (minimum three consecutive years) in which the residual was consistently larger or smaller than one standard deviation, plus or minus respectively (for details, see Grillitsch, Martynovich, et al., 2021). In a second step, we prepared regional profiles of the extreme cases using secondary data.…”

Heterogeneity of Research and Development Expenditure: A Convergence Analysis for the Spanish Regions

“…For Europe, they state that regions classified as innovation leaders were significantly more likely to have either resisted the Great Recession or recovered rapidly from it. However, it should be remarked that regional growth is a very complex phenomenon, and despite the great research efforts in recent decades, it still remains partially as a "black box" (Grillitsch et al 2021). Additionally, Audretsch et al (2022) argue the link between the literature on radical innovation 5 and regional growth, concluding that it is still an under-researched area.…”