Late last month the United Kingdom filed Article 50, officially notifying Europe of its intent to leave the European Union. This will most certainly impact the global economy, but can we trust our current forecasting systems to prepare us for the economic impact of Brexit? They haven’t been wildly successful to date.
The forecasts for global trade in the wake of a “leave” vote from the UK was notably pessimistic last June. The Bank of England warned of a national recession. The International Monetary Fund cut global growth estimates, citing “a substantial increase in economic, political, and institutional uncertainty, which is projected to have negative macroeconomic consequences, especially in advanced European economies.” Sterling shed one tenth of its value in only two days, a real-time financial signal that currency holders considered the pound a risky store of value.
These dire predictions did not mirror reality. The UK has avoided a recession. Consumer spending remains strong, the employment rate continues to grow, and many economists have softened their forecasts. The IMF has amended their projected growth rates upward for developed economies. Though the full economic impact of Brexit remains to be seen, it appears the world was overly pessimistic.
Confidence is a major indicator of economic health. Though currency fluctuations provide real-time data on market and investor confidence, it says little about consumers and businesses. These confidence levels are arguable more important indications of future economic well-being.
Brexit predictions were based on a perceived hit to consumer and business confidence. They were, in part, well founded. In June 2016, consumer confidence plummeted in the UK. Business confidence was not far behind, hitting its lowest point since the 2009 recession in September of 2016. Our forecasts were correct about the initial reaction to Brexit, but they were incorrect about our rate of recovery. No sooner had confidence fallen, then it began to climb. We missed the shifting trend.
How did we get it so wrong? In an age of unprecedented data, we have yet to master the art of identifying, analyzing, and utilizing important trends. These trends are too important to be missing. We need to capture them in real time, adjusting our predictions and business strategies in response to quantified sentiment-driven data. Vector is a tool that can do this.
Vector is a real-time sentiment analysis system. Using algorithms that scan and assess news articles throughout the web, Vector delivers cutting-edge data that can then be used to guide investment and business decisions. It may be too late to assess tends from the 2016 referendum, but there is still the opportunity to stay abreast of popular sentiment as the Brexit process moves forward.
Uncoupling a 43-year relationship is no small task, especially when over 40,000 legal acts need to be revisited, sorted, and deciphered. Though many of the Union’s laws can be copied into UK law to be accepted or vetoed at a later date, there are some decisions that need to be finalized and agreed upon before Brexit can move forward. The next two years will require intense, non-stop negotiations as the UK paves its way towards an independent future. Chief among the issues requiring attention is trade, and the ramifications of Brexit trade negotiations will be felt far beyond Europe.
Article 50 will almost certainly impact consumer confidence in the UK and the Eurozone. In fact, the next two years are likely to see ebbs and flows in confidence as various pieces to the puzzle of exit are cemented in place. To obtain a deeper read on consumer confidence you need a tool like the Vector API, that can sample consumer and business sentiment across multiple social media channels in real-time.
Vector is a natural language processing application that performs information extraction on millions of news stories per day. It provides high value to any quantitative researcher, adding a collaborative-authoring workflow in perfect synergy with the most powerful and unique faceted search in the business. For more information, please visit www.indexer.meor firstname.lastname@example.org.