Working Paper

Information and Economics: A New Way to Think About Expectations and to Improve Economic Prediction.

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The largely unexpected arrival of the global economic crisis and the largely unpredicted slowness of the recovery from the Great Recession should be precipitating an intellectual crisis across economics and policy making. We require additional theories and additional methods to detect how an economy is evolving and to provide the basis for policy intervention (Haldane, 2014).

Our starting point is a new theory of decision-making (Conviction Narrative Theory, CNT) and a new methodology for economic prediction (Directed Algorithmic Text Analysis, DATA).

The theory, like Keynes’ theory of long-term expectations and Soros’ theory of reflexivity, on which we draw, starts from observation and evidence. The method makes use of data sources and computer methodologies that have only become available in the last few years. It is derived from the theory, which focuses on how agents recruit their emotions when working out what to expect from their decisions and those of the agents around them.

In this approach expectations are conceived to be created through the capacity of human agents to simulate and communicate mental pictures of future outcomes that they feel are accurate. In this way, agents become confident enough to act to create potential gain and so risk loss under conditions of uncertainty.