Applying Big Data to Economics

Lucy Tallentire from the School of Business, Economics and Informatics at Birkbeck and CSIS PhD candidate Seongil Han report on a recent conference at the Birkbeck Centre for Data Analytics (BIDA).bidaWhat can we learn from Big Data, and how can Big Data analytics be applied to the field of Economics? These were just some of the questions answered by a one-day conference held by Birkbeck Institute for Data Analytics (BIDA) on Monday 5 June. The event was organised in collaboration with the Department of Economics, Mathematics and Statistics, to bring together researchers from statistics, applied mathematics, computer science, finance and economics to enhance the research environment and promote cross-disciplinary collaboration within the College, and with a wider external audience.

Birkbeck’s Professor Stephen Wright kicked off proceedings with an insightful presentation on the application of Big Data to large-scale surveys and maps. In his research project of residential land supply in 27 EU countries, he examines sources such as Google Maps, ONS/Ordnance Survey and Open Street maps to explain large differences across EU countries and identify whether there are restrictions on residential land. Professor Wright concluded that a large proportion of the regional variation in supply of residential land in the EU can be explained econometrically and is very strongly determined by regional geography and history.

Guest speaker Giovanni Mastrobuoni, Professor of Economics in Department of Economics, University of Essex, provided a unique insight into the role of Big Data analytics on police patrols and crime. Based on recent evidence that police deployment reduces crime, the project was designed to identify whether the elasticity of crime with regard to policing remains the same, and whether it is worth randomly increasing mobile police presence in an area. The results suggest, however, that big data is only useful with good prior identification; elasticity is negligible if identification is low, and random mobile patrolling cannot reduce crime significantly.

The second part of the conference focused on big data in business, economy and strategy. Professor Roger Maull, from the Department of Digital Economy in University of Surrey, discussed business models in relation to the digital economy, introducing 3 new approaches to the economy for big data – digitisation, datafication and digitalisation. He explained business models with industry dynamics and emphasised the following qualities:

  • value proposition, or what the customer pays for;
  • value creation, or how one delivers what the customer pays for;
  • value capture, or how the customer pays for it.

Big data has allowed significant advancements in personalisation and customisation, which also link to HAT (Hub of All Things): an IT business services to store and customise the personal data, as a real business model for personal data.

Final speaker Ernesto Damiani, from the Etisalat British Telecom Innovation Centre, Abu Dhabi, introduced the prospect of big data analytics as a service. He started by highlighting the 5 Vs of big data:

  • Variety in analytics model: static ways vs dynamic ways;
  • Volume;
  • Velocity;
  • Value;

He also compared traditional analytics with big data analytics and explained a change in paradigm for data analytics, which is supported by the example of Google.

The conference succeeded in providing a comprehensive introduction to the many ways in which big data analytics, such as text mining techniques, can be applied to Economics and business. Big data analytics continue to attract a great deal of attention in academia and industry, with an increasing amount of unstructured data available on web; it is vital to apply big data analytics to various problems to supplement qualitative information to conventional descriptive analytics and infer the predictive analytics.

BIDA would like to thank the presenters and all those who attended for their insightful comments and discussion. You can find out more about the Birkbeck Institute for Data Analytics on their website.

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