Who is smart at predicting short-term fluctuations in the economy?

The global financial crisis of 2007-2008 highlighted the need for better monitoring and forecasting of fluctuations in the economy in order to avoid similar economic recessions in the future. Since then, various institutions have been searching for new and more accurate prediction methods, which could reduce the uncertainties associated with economic fluctuations at a national level [1].

One of such studies was undertaken in 2017-2018 at the Collective Intelligence Unit, Copenhagen Business School. The study tested the comparative capability of distinct crowds of individuals to predict fluctuations in unemployment, credit, debt, and savings.

Questioning citizens about ongoing economic fluctuations for the improvement of economic models is not a new idea. Survey-based indexes, such as the Consumer Confidence Index and the University of Michigan Consumer Sentiment Index, have been in use for decades. However, surveying citizens for the forecasting of economic indicators has not been utilized fully and systematically, leaving room for the validation of citizens’ and experts’ deep insights about the economy.

Our study built upon the ‘wisdom of crowds’ principles, which has emerged as an essential part of management literature [2]. The essence of the ‘wisdom of crowds’ is derived from the empirical observation that groups’ predictions tend to be more accurate than individual judgments, even when some individuals may have a particular expertise in the field of prediction.

A key condition for the wisdom of crowds to emerge is that the participants’ opinions are diverse [3] [4]. This diversity of opinions may derive from differences in individual skill sets, variances in their perspectives, or access to different sources of information [4] [5]. Aggregating these diverse opinions is what sets groups apart from individuals in terms of accurate predictions.

Our study included aggregation of predictions from a random crowd of 1500 Copenhageners which was then compared to four minor crowds: 218 frontline employees ( ie. customer service personnel) from within the banking sector, 17 financial experts, 200 borrowers, and 200 savers (the two latter groups were both drawn from a random sample of citizens). The prediction accuracy of the groups were compared on the following five items: unemployment, credit, mortgage, bank deposits and bank debt.

These five groups of random citizens, bank employees, financial experts, savers and debtors were asked to make predictions at 1, 3, 6, and 9 month horizons on the aforementioned items. The results showed significant accuracy for both the bank employees and the financial experts across all variables. The study also revealed that there were no significant differences in accuracy between the financial experts and bank employees.

Additional findings revealed that the random sample of savers also showed tendency to perform accurate predictions over the months, but less accurate than experts and frontline employees, while the random sample of debtors were the least accurate of all crowds.

What is the impact of such prediction results for navigating the short-term economy? This is yet to be validated over time using the ‘wisdom of crowds’ principles in dynamic national forecasting models, but the current study provides some indications about the important insights that a sample of bank employees, financial experts and savers in the financial sector holds for future short-term economic fluctuations.

Authors

Julian Johannes Umbhau Jensen

 Carina Antonia Hallin

References

[1] Zabai, A. (2017). Household Debt: Recent Developments And Challenges. In BIS Quarterly Review. December 2017

[2]  Surowiecki, J. (2004). The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations. New York: Doubleday & Co.

[3] Hong L, Page S. E. (2001) Problem Solving by Heterogeneous Agents. Journal of Economic Theory 97(1):123-163.

[4] Hong L, Page S. (2004) Groups of diverse problem solvers can outperform groups of high-ability problem solvers. Proceedings of the National Academy of Sciences 101(46):16385-16389.

[5] Mannes, A. E., Soll, J. B., & Larrick, R. P. (2014). The wisdom of select crowds. Journal of Personality and Social Psychology, 107, 276-299

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