Hello, my name is Javier
and I'm going to present the work
Effect of the gas price surges in user activity in the Ethereum blockchain.
First, what is a DAO?
DAO stands for decentralized autonomous organization.
And in short,
a DAO is a software deployed in the blockchain
that makes it possible for people to coordinate and self govern themselves.
DAOs are booming due to platforms that make possible to easily create them and use them.
And these platforms are Aragon, DAOstack and DAOhouse.
In real life DAOs are mostly used for investing,
or also to organize the development of a project, typically software projects,
but also to govern, for example, physical places, or organizations.
DAOs typically hold cryptocurrencies or other crypto-assets,
and decide where to allocate them through some kind of voting mechanism.
DAO interactions are usually recorded in the blockchain.
And it means a cost.
So, in Ethereum, the operation cost is known as gas,
and is a way to compensate the network nodes for computation.
The thing is that the cost of gas dramatically increased in 2020,
mostly due to the boom of decentralized finance applications
Our question is:
How this increase affects the activity in the DAOs.
We use quantitative data and econometric tools to try to determine it.
Regarding the data,
we use time series, from May to December 2020.
And the time series that we use were daily returns of the gas prices,
and the daily DAO activity rate of DAOstack and DAOhaus.
So we have two cases, one for each platform.
Regarding the methods,
we use vector autoregressive models
to represent the dependence between the gas price and the DAO activity
Using these VAR models in combination with three tools
that make possible to determine the causality,
Namely Granger causality test, impulse response function, and the decomposition of the forecast error variance.
So our results show that,
according to the Granger causality
We only found a statistical evidence for the case of DAO house
and only significant at 10%.
Regarding the decomposition of the variance of the forecast error in the activity rate,
we saw that most of that variance is due to shocks on the activity rate
And only the 3.5% is due to shocks on price returns.
Regarding the impulse response function
of gas on activity,
we can see that a shock on gas
causes a significant decrease from two days after the shock and up to two weeks after it.
We also can see
a permanent decrease in the activity rate,
but apparently it's not significant.
Well,
these results were unexpected for us.
We expected a great influence of the gas price on the DAO activity,
but we found a minor one.
This is probably due to
the fact that most DAO users need to cope, cope with the increases
and absorb the cost individually.
This kind of behavior is not what we can expect of a self-regulated market.
and it typically calls for intervention or regulation to benefit consumers.
Thank you very much.