> For the complete documentation index, see [llms.txt](https://seer-2.gitbook.io/seer/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://seer-2.gitbook.io/seer/seer-solution/token-incentives.md).

# Token Incentives

A common solution taken by other prediction markets has been for the operators to provide liquidity themselves.\
However, this has two main issues:

* The operator is likely less efficient than the open market.
* In the case of Seer, we don’t have such an operator.

To solve those, Seer will distribute the majority of its tokens through yield farming. Governance will determine the amount of tokens and the applicable time period for eligible markets.

This yield farming model has been shown to be extremely efficient at bringing initial liquidity. It allowed the exchanges curve \[11] and Balancer \[12] to build their liquidity. It even allowed Sushiswap, initially a simple clone of Uniswap, to at some point even have a higher liquidity than Uniswap \[13].

Yield farming may not be sustainable in the long term but can serve to start the flywheel (virtuous circle) while in the long term payments from information seekers and fun traders can keep the system .

<figure><img src="/files/vclUvls6sQEJnkw1X7JH" alt=""><figcaption></figcaption></figure>

Let's see the relation and impact of information seekers present in all prediction markets and token incentives.


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