Standard consumer search models typically assume a stationary environment wherein past experiences do not affect current search effectiveness. In contrast, this paper leverages unique data on individual-level repeated refueling transactions and variations in market familiarity to demonstrate the strongly experience-dependent nature of search behavior. Specifically, when drivers refuel in unfamiliar markets-while traveling or after relocating-they pay significantly higher prices than in familiar markets. As their market-specific experience accumulates, this penalty persists but reduces, highlighting its importance in repeat-purchase settings. Further, a decomposition analysis indicates that experience-driven gains arise primarily from learning about the store and its market.
We study the impact of cartels on productivity using a novel plant-level dataset from the Japanese ready-mixed concrete industry, where cartels are legally permitted. After estimating plant-level productivity, we adopt a difference-in-differences design to show that cartel collapse increases plant-level and market-level productivity, while cartel formation has no effect. Furthermore, a triple-difference analysis reveals that productivity gains are more pronounced for initially less productive plants and those in high-density markets. These results, combined with decomposition analyses showing that market-level improvements are driven by within-plant changes rather than reallocation or exit, suggest that the treatment effect of competition drives productivity gains.