Even more than Wall Street, the Priesthood of the Economic PhDs champions greater levels of opacity in the global financial system.  Why?  One reason is they believe in the myth of information overload.

For example, the Europeans Systemic Risk Board’s Advisory Scientific Committee published a report on regulatory complexity and the quest for robust regulation.  In the concluding section, titled Towards a Better Regulatory Framework, the Committee cites this myth as a reason for not requiring greater disclosure.

Disclosing more information is not sufficient to address complexity. It could be argued that regulatory complexity is what a complex financial system calls for and that it should be accompanied by a reporting system that better allows regulators and market participants to understand such fundamental complexity (e.g. through the reporting of more granular information or even the live monitoring of institutions via direct access to their IT systems). However, the financial system today is very interconnected, and it is doubtful that access to even the richest data on individual institutions could meaningfully allow full control of the risk in the system. As Brunnermeier and Oehmke (2009) point out, always seeking to increase the information disclosed to supervisors or the market is not a valid response to complexity as it can lead to information overload. In summary, the availability of more granular information can create an illusion of control, while in reality the wood is not seen for the trees.

Of course, the myth of information overload is false.  But you could never expect a member of the Priesthood of the Economic PhDs to take the required nano-second to consider why it might be false.

What exactly constitutes information overload?  According to the Priesthood, the volume of data makes it impossible to focus on what is the important data.

Apparently the Priesthood has never heard of experts.  What distinguishes an expert from Joe Six-Pack is their ability to know what data is important and to ignore the irrelevant data.  So by definition, experts don’t ever suffer from information overload.

Also, we live in the Information Age.  We don’t need to rely on just human experts.  We can use Artificial Intelligence to create experts who are capable of looking at every piece of information disclosed and using this information to provide insights (think IBM’s Watson).