Reviewing “Modelling Bitcoin’s Value with Scarcity” — Part IV: The Theoretical Framework leading to the Error Correction Model

The next step after the shown cointegrating relation between stock-to-flow and market cap of bitcoin

Introduction

In my first review of the work of PlanB, I concluded that the relation between stock-to-flow and bitcoin price as pointed out by the author was invalid because the general assumptions of ordinary least squares regression were not met. When two variables are non-stationary and we estimate a regression model, there is a good chance we find highly autocorrelated residuals and a significant value for the coefficient. This phenomenon is well known as spurious regression. But, spurious regression isn’t always the case. Sometimes the variables might be cointegrated, which would imply that the estimated relation is super consistent. Nick pointed out that we could very well be dealing with the exceptional case of cointegration and showed that he wasn’t able to falsify the cointegrating relationship between stock-to-flow and bitcoin’s market cap. After Nick showed that the variables were cointegrated, I verified his findings. Since I still was skeptic, I chose to run the analysis on my own dataset and ran three different cointegration tests to make sure there was no doubt. Even though I expected I would be able to show that at least one of those tests would lead me to reject cointegration, I could…