Urban Dynamics Lab research
The Urban Dynamics Lab addresses a number of research challenges that are key to tackling issues around regional and city economic growth and development in the UK. It brings together a number of research strands funded under the DET, EPSRC and ESRC portfolios over the last decade to tackle the vexed question of regional competitiveness and the imbalances of the UK economy.
The challenges faced by policy makers charged with improving economic performance and social wellbeing lie first in how to benchmark current performance and then in how best to achieve a desired set of changes. Policy measures and incentives can be considered as perturbing the trajectory of economic development on a 'fitness landscape', representing the structural context defining a region.
A policy intervention may nudge a trajectory from one path to another through the landscape, or it may prove insufficient to deliver lasting change. Infrastructure investments can be seen as changing the topography of the landscape. In order to forecast effectively, one thus needs to understand the shape of the fitness landscape, the way this may be affected by planned infrastructure, and the likely effects of policy nudges.
Datasets are increasingly available to inform this process, but without new analytics, researchers struggle with the size and complexity of the challenge, and decisions are based on projection of past trends, ideology and gut instinct. Issues of content, coverage, provenance and currency of Big Data from different domains are also salient.
Research themes/objectives
Based on UCL's EPSRC funded 'Space Syntax' model, we will build a unified analytic map of the network of UK infrastructure of all types, loaded with locational information on property stock. This will create a new generation of integrated regional modelling capability.
Currently regions used for economic statistics are defined by administrative boundaries. Functional regions based on analysis of travel to work patterns have been shown to give a much better account of UK economic geography. New city definitions from the Mechanicity project show how stocks and flows of materials, people, information and energy over infrastructure networks can be used to remap functional regions of any town or city. It will build upon UCL collaborative work with the Office for National Statistics in creating the 2011 Output Area Classification, and extend related work undertaken for the GLA for the Greater London area.
Our work on this project will focus on defining cities and measuring their performance on a range of social and economic attributes. This will be explored through graph theoretic partitions of cities and examine different kinds of interactions - adding flows to the networks and exploring different kinds of network decompositions, and integrated with new measures of income and related social, economic and physical attributes of the chosen urban systems.
Addressing current developments in devolution, city and regional policy around the 'Northern Powerhouse' and the 'Midlands Engine', we will also consider the notion of regions of cities as well as city regions.
Part of our aim is to produce a reasonably definitive measure of city performance and potentially extending this kind of analysis to temporal dynamics.
Our work will investigate the long-term and short-term interactions between UK regions, notably the origin and destination of both domestic and international migrants. The degree to which regional populations have remained stable over time or have become very heterogeneous may be compared to other economic and physical aspects of agglomeration, such as land values, transport networks and daily travel destinations. Our geo-temporal toolkit will constitute a resource in re-mapping the UK's regions based on various functional characteristics.
In order to pinpoint the negative consequences of agglomeration we will map inequalities of various kinds, and investigate the association between these and flows of capital, credit, investment, employment and social and physical infrastructure.
This will include a review of such measures of inequality, as well as revisiting our voting analysis of the partition of Britain which we explored during the last election, as this provides an interesting way of looking at the distribution of cities which is complementary to inequality analysis and city performance.
Our work will assess the ways in which populations in UK regions have evolved differentially over time and have attracted different groups of people in terms of skills, social milieus and geographic origin, both nationally and internationally.
We will model the evolution of different population groups in different regions over time and estimate their socio-economic success in terms of spatial mobility - as indication of actualised social mobility - as well as health and well-being. The work will highlight the socio-cultural undercurrents in shaping regional disparities in social outcomes, including economic performance and health, mainly reworked through dynamic individual and neighbourhood-level classifications.
Where is infrastructure investment best targeted to stimulate private sector investment and third sector action? We will create a new diagnostic tool based on analysis of residuals between different kinds of infrastructure capacity and configuration, and economic activity.
The indicators or classifications developed under 'Mapping Inequalities' will be used with a view to informing policy priorities.
With consideration of the broader policy and economic environment that contribute to inter and intra-regional inequalities, a broad framework for choosing and designing policy to attenuate or manage regional inequalities will be designed.
By drawing on other data sources pertaining to the physical environment and urban services, the framework may be extended to classify different kinds and levels of investment need at a range of spatial scales.
Recent theories which focus on demonstrating that, the more advanced and wealthy the economy, the more diverse the industrial and employment structure tends to be. These have been developed by Hidalgo and Hausmann and extended by Pietronero's group.
There are very promising proposals that these also apply to cities and could mean that the larger and more prosperous the city the more diverse it is. We will test these on UK cities and regions and in this way automate the UK fitness landscape, which is composed of functional regions defined by the project.