Application of Spatial Agent Based Modelling in Agricultural Economics

Lead Research Organisation: University of Nottingham
Department Name: Faculty of Engineering

Abstract

My research takes a look into developing agent based, demand side economic models of food intervention strategies across large areas of South Asia and Sub-Saharan Africa. The intervention strategies are characterized by novel and innovative agricultural methods for addressing the micronutrient deficiency amongst the population in those areas.

Strategies for deploying new methods to farming are non-trivial. Simply introducing newer, enriched farming products, such as fertilizers, into the market does not mean that local industries will adopt it overnight. Moreover, trust must be established in the local population through widespread dissemination of information regarding the safety and added benefits of the new variants of fertilizers. From the economic standpoint uptake of such interventional products can be monitored through the demand generated for the product in the local markets. As economies consist of heterogeneously mixing entities, interaction between them gives rise to emergent behaviours that might offer insights on the granular level economic activities in a population.

Current economic models try to find aggregate properties of the population as a whole and ignore individual attributes. Such macroscopic view of the economy overlooks the dynamic changes in behaviour of the individual entities that make up the entire population. Furthermore, these models are too static in nature to account for spatiotemporal changes in characteristics of entities over large geographical areas. Neglecting such crucial behaviour can potentially lead to incomplete assumptions about the local population and contribute to developing intervention strategies that may not fully serve the purpose of the intervention.

Therefore, my research will attempt to uncover the granular level characteristics of local economic activities across large geographical regions such that emergent behaviours in local population, in the event of intervention strategies, can be understood and effective measures be taken. Complexity sciences based methodologies, such as agent based modelling, lend ways to looking at economic models and geospatial research through an alternative lens and offer up ways to identifying and addressing the unique behaviour patterns amongst spatially interacting entities. Understanding such existing dynamic economic characteristic in a population would serve as a vital tool in developing effective local policies

Planned Impact

We have identified the potential impact of the CDT in consultation with 44 partner organisations, ensuring we are meeting the needs of potential beneficiaries. The impacts that we will develop robust pathways to achieve include:

Economic:
Our graduates will be a key pool of knowledge and skills to deliver the annual £11bn of economic benefit to the UK from 'opening-up' geospatial data. Their advanced skills in a rapidly changing technological field will help the UK geospatial industry realise the predicted global annual growth of 13.8% and transform the use of geospatial data and technology in smart cities, urban-infrastructure resilience, energy systems and structural monitoring.
Through continuous two-way engagement with our partners we will shape and deliver industry relevant PhD projects that apply students' unique training. Ongoing knowledge exchange with industry will be facilitated through regular interaction with the centre, the Industrial Advisory Board and partner participation at the Innovation Festival, CDT Assembly and Challenge Week events. We will work with the recently announced £80m Geospatial Commission to ensure the translation of new methods, techniques and technology to the broadest possible user base; using our partnerships with professional bodies to recognise the opportunities and challenges to realising the economic benefits of geospatial data.
SME and start-ups are will be major drivers of global geospatial industry growth. Innovation and entrepreneurial training will position our graduates to act as a catalyst of the growth needed in the UK to remain internationally competitive. Working with Satellite and Digital Catapults, and the £30million National Innovation Centre for Data, we will foster a 'full-circle' engagement with SME's and start-ups; to ensure our graduates understand the drivers for innovation, facilitate co-production and ensure the timely adoption of academic driven advances for economic growth.

Societal:
We have recognised the significant role geospatial data will play in providing the evidence for improved planning and response to significant global societal problems. The interdisciplinary PhD research conducted within the CDT will provide new insight and understanding in climate impacts and adaption, sustainable cities, and healthy living and aging. Our graduates will engage with key international and national organisations (e.g., Cities Resilience Programme of the World Bank, UK National Infrastructure Commission) to ensure the widest adoption of their research.

Academic:
Our graduates will form the next generation of geospatial scientists and engineers vital for interdisciplinary research at the engineering-societal-environment nexus. Their combined skills in geospatial technology and methods, along with advanced mathematical, statistical and computing skills, will provide the UK with a unique resource pool of academic leaders. The research produced by the centre, sustained and embedded by the skilled workforce it creates, will help address the Grand Challenges of the UK Industrial Strategy; AI and the Data Driven Economy, Future Mobility and an Aging Society.

To maximize academic outreach we will provide a Geospatial Systems Resource Portal that will allow researchers to access the new techniques and methods developed. Software and related methods will be open source, and tutorials and training guides will be developed as a matter of routine. We will organise CPD courses based on our unique integrated training in Geospatial Systems, open to cohorts from other CDTs within the digital economy space. We will foster cross-UKRI translation and learning by working with related CDTs; the ESRC CDT in Data Analytics and Society and NERC CDT in Data, Risks and Environmental Analytical Methods. Via our 9 international research partners our unique training approach and strong emphasis on interdisciplinary research will become internationally impactful.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023577/1 01/04/2019 30/09/2027
2299620 Studentship EP/S023577/1 01/10/2019 30/09/2024 Tahsinur Khan