Dual-Token Economic Model

Vechain's novel economic model.

What is a blockchain token economic model?

Public, open blockchains rely on an economic system to govern the behavior and distribution of tokens within a blockchain network. A blockchain economic model encompasses the design, issuance, distribution, and management of tokens, as well as the incentives and mechanisms that drive their value and utilization.

Why is the right economic model important?

Selecting the right economic model for a blockchain has far reaching implications. Incentivising appropriately increases network security, distributing ethically ensures trust, governing openly increases confidence and designing cleverly increases robustness. We have designed our economic model with all these values in mind.

What economic model did vechain choose?

We learned from our business partners, especially corporations and enterprise business owners, that one of major obstacles to adopting blockchain technologies is the unpredictability of the cost of using a blockchain, thanks to the volatility of cryptocurrencies. To tackle this problem, we designed a dual-token model that includes the vechain token (VET) and VeThor token (VTHO). VET serves as a value-transfer medium (utility token), whereas VTHO represents the underlying cost of using the VechainThor blockchain resources (transaction / gas token). The unique, two-token design significantly helps to separate the cost of using the blockchain from market speculation.

Why did vechain choose this model?

When crypto markets are in a bull run, token prices inflate and as a consequence, the cost of transacting on the network also increases. This, however, is only the case when the native token is used to pay for transacting on the network. The objective of the dual-token model is to prevent transaction fees from being directly exposed to price volatility. It is imperative for enterprises and individual users alike, to be able to predict the future costs of using the network, VTHO helps vechain to provide predictability.