> For the complete documentation index, see [llms.txt](https://serotolabs.gitbook.io/tradeclash/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://serotolabs.gitbook.io/tradeclash/legacy-documentation/economic-models.md). # Historical: Economic Models > **This is legacy documentation.** Trade Clash has pivoted from AI-driven economic simulation to a [sealed-lot auction game](/tradeclash/game-design/core-mechanics.md). These economic models are no longer part of the game. Preserved for historical reference. *** ## Overview The original Trade Clash used real economic models to calculate the cascading effects of AI leader decisions. When an AI leader made a policy decision (e.g., raise tariffs), the outcome flowed through these models to determine economic impacts. ## Gravity Trade Model Bilateral trade volume calculated from GDP, geographic distance, and political friction between nations. Based on the gravity model of international trade — larger, closer economies trade more, adjusted for political relationships. ## Melitz Model Export feasibility determined by firm productivity thresholds. When trade conditions changed, only firms above a certain productivity level could continue exporting. This created realistic asymmetric impacts across nations. ## Tit-for-Tat Retaliation AI leaders maintained a 5-round grudge memory. If Nation A imposed tariffs on Nation B, Nation B would retaliate within 1-2 rounds. Retaliation chains could cascade through the entire system for 5-6 rounds before decaying. ## Economic Indicators The simulation tracked per-nation: * GDP and growth rate * Trade balance * Resource reserves * Political stability index These indicators shifted based on AI decisions filtered through the economic models. ## Why They Were Retired The pivot to sealed-lot auctions removed the AI simulation layer entirely. The new game derives value directly from Polymarket positions rather than from simulated economic outcomes. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://serotolabs.gitbook.io/tradeclash/legacy-documentation/economic-models.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.