Follow GAUGECASH on Twitter, Reddit, and LinkedIn
Join the Telegram group to stay updated
Traditional financial systems rely on central authorities that dictate economic policy based on the fiduciary trust that society places in them. In a perfect world, central bank authorities act in good faith and design policies that factor in the complexities behind the economy to the best of their ability. But the reality is that these central authorities face several challenges during policy decision-making, such as the irrationality of economic agents, foreign and domestic government policies, and the trustworthiness of data required for policy decision-making. For this article’s purpose, we will concentrate on one factor: reliability and value of the data used for policy decision-making.
An important thing to consider is that most of the economic data from which central authorities derive policy are not provided to them in real-time; the data is always out of phase. The consequence of this is that they never have a “real picture” of the economy and make decisions based on outdated data. These decisions take a long time to make the desired impact on the economy. In the end, they can only make approximations, or one could argue almost educated guesses and with this data model the economy and dictate policy.
Factors behind the time rate of data collection and the time it takes for the policies to produce the desired results can be attributed to outdated technologies used by central trusted authorities and society, such as cash, traditional accounting methods & the numerous authorized agents that comprise the system. Most of these factors can be significantly mitigated or eradicated with a transition towards better technologies. Still, there is one factor that cannot be mitigated, the model’s reliance on trust. This factor will always be a flaw that can be exploited by corrupt, negligent, irresponsible, or, to put it bluntly: fallible agents.
