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Emergent Economic Engine - Emergent Alliance

Emergent Economic Engine

Breathe life into your local economy with E3

E3 gives you answers to your most critical “what if?” questions. Questions about what might happen to your local economy and what you should do to help business rebound.

Combining diverse data sources with a sophisticated economic model, E3  (the Emergent Economic Engine) reveals the potential effects of future COVID scenarios, from local lockdowns to restrictions on specific sectors.

E3 then helps you identify the best strategies for helping your local economy rebound from the effects of COVID.

Imagine you want to know whether sector subsidies will make a difference to the overall economy. E3 helps you predict the impact of different subsidy approaches, modelling the impact of each intervention across the whole system.

The E3 app, combined with Emergent Alliance’s expert support, places a set of sophisticated technologies comfortably in your hands – bringing new insights to your work, building trust in your decision making.

E3 – powered by data and proven models

We have published two blogs about the underlying model and the app, which can be read here and here. The underlying code is accessible in our Github repo.

The E3 app is the result of our work to assess the impact of Covid-19 on economic networks by modelling it as an exogenous shock. The effect of this shock is modelled following the approach investigated in Klimek et. al. (2019). In this context, the initial shock propagates across time (dynamic effect) and sectors (Input-Output table). As part of this work, an analytical strategy was developed which models the impact of counter-strategies such as subsidies against the economic depression caused by the shock. The approach is to represent a stimulus in the form of extra resources injected into the system by external actors such as governments or other public authorities. Here we keep our approach at a relatively high level of abstraction, in the sense that we do not provide any guidance on how to inject the resources into the system, but rather assume that the resources get to the system. 

The building block of our approach is Leontief’s Input-Output model. This model is based on the idea that sectors in an economy are interconnected through input-output linkages. In other words, part of what one sector produces is used as an input by other sectors. 

 The practical purpose of our work is to help policymakers and business leaders understand the likely macroeconomic consequences of lockdown measures, in particular the impact on specific sectors.

About the Authors

We are a team of data scientists from IBM’s Data Science & AI Elite Team, IBM’s Cloud Pak Acceleration Team, and Rolls-Royce’s R2 Data Labs working on Regional Risk-Pulse Index: forecasting and simulation within Emergent Alliance. Have a look at our challenge statement!

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