Price Determinants in the Counter-Strike 2 Skin Market: A Hedonic Pricing Approach

Sammanfattning

This thesis estimates the price premium associated with the StatTrak feature in the Counter-Strike 2 skin market, a non-functional attribute that records in-game kills but provides no gameplay advantage. Using 1,836,721 daily price observations from the Steam Community Market (2014–2024) and a hedonic pricing model with skin and time fixed effects, the analysis finds that StatTrak skins trade at an average premium of approximately 206% over otherwise identical non-StatTrak skins. A pooled interaction model reveals that this premium declines monotonically across rarity tiers, from 349% at Mil-Spec to 104% at Covert, consistent with the prediction from vertical product differentiation theory that the marginal value of a differentiating attribute diminishes as baseline quality increases (Mussa and Rosen, 1978; Shaked and Sutton, 1982). The premium is robust across all exterior conditions (214%–264%), indicating that rarity rather than visual condition is the primary moderator. These findings demonstrate that non-functional attributes can generate substantial price differentials in digital goods markets and provide a direct empirical test of IO predictions in a setting with negligible production costs and a fully engineered product-attribute space