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Consumer expenditures in the United Kingdom account for over 50% of Gross Domestic Product on the expenditure side, yet their impact on economic activity is often overshadowed by attention to technological change, value chain analysis and especially international trade. In this paper, a recently developed interregional model of the UK economy, SEIM (S ocio- E conomic I mpact M odel) will be used to provide some parallel perspectives to the role of interregional trade in goods and services by focusing on the interregional structure and impact of income and expenditures by households. Drawing on the original contributions of Miyazawa (1976) to highlight the contribution and structure of income interdependence complemented by interpretations offered by average propagation length, field of influence, and feedback loop analyses. The findings reveal the nature and strength of asymmetries in the structure of income formation and their impacts across the multiregional system. While there is only modest variation in aggregate income propagation by region, the accumulation of income is dominated by regions in the London area and secondarily by other metropolitan areas providing a source of explanation for the sustained income inequalities that have characterized the UK economy for almost a century. [ABSTRACT FROM AUTHOR]

The heterogeneous spatial and individual impacts of the Great Recession, Brexit and COVID-19 have generated an important challenge for macroeconomic and regional/spatial modellers to consider greater integration of their approaches. Focusing on agent heterogeneity at the ITL 1 level in the UK, we propose the National Institute Regional Modelling System (NiReMS) – a synthesis of dynamic microsimulation with a spatial regional macroeconometric model. The model gives regional macro projections while allowing for household level inference. To showcase the model, we explore the impact of discontinuing the uplift in Universal Credit (UC) before the end of the pandemic and show that it led to more households consuming less. Importantly, the proposed framework highlights the unequal distributional impact across regions of the UK. [ABSTRACT FROM AUTHOR]

Shift‐share analysis has been extensively used to investigate the different drivers of changes in socioeconomic variables in both spatial and non‐spatial contexts. This paper presents a comprehensive shift‐share formulation that, by considering all the possible interactions between the geographical and sectoral variables that interplay in a non‐spatial context, accounts for the intrinsic conditions of the regions that could affect the regional changes when spatial influences are not detected. The proposed technique is illustrated by analyzing the growth of industrial gross value added in the Spanish provinces between 2015 and 2019. Our results show the relevance of the intrinsic effects: the advantages (disadvantages) of the industrial sector within each province and the regional dynamism are important factors to explain the industrial changes in the Spanish regions. These findings provide evidence for the use of the comprehensive shift‐share as a tool that contribute to the regional analysis by identifying the characteristics of vulnerable regions that require further attention to avoid or lessen the effects of low economic growth. [ABSTRACT FROM AUTHOR]

Land use regulations often delay residential development processes and increase the development costs, although they contribute to addressing market failures and realizing a well-organized urban spatial structure. Raising barriers to development can prevent households from moving in response to either job relocations or job growth at certain locations in a timely manner through restrictions in the local housing supply. This situation may also result in longer commuting distances, times, and costs, as well as greater spatial mismatches. To examine the possible adverse effects of the regulations, this study analyzes how intraregional population-employment interactions vary across metropolitan areas that substantially differ in the restrictiveness of land use regulations. First, an exploratory correlation analysis of 40 large U.S. metropolitan areas reveals that highly regulated regions, particularly those with lengthy approval processes, are likely to show a lower correlation between census tract-level population and employment changes and an increase in mean commuting time between 1990 and 2000. Secondly, regression analysis suggests that the lower correlation in highly regulated metropolitan areas could be attributed to the limited responsiveness of the population to employment redistribution within the regions. © 2013 Springer-Verlag Berlin Heidelberg.