Replication Data for: The Impact of Follower-Based Status Change on Influencer Content Creation: Evidence from a Regression Discontinuity Approach

This research relies on proprietary data covered by a Non-Disclosure Agreement with the collaborating firm. Therefore, we propose the following alternative disclosure plan that is in keeping with the spirit of replicability while respecting the specific situation: • Synthetic Data Generation: We generate synthetic data sets that capture the underlying distributions, relationships, and structures present in the original data. Specifically, we added independent Gaussian noise to all key continuous variables. This ensures that the synthetic data retains the essential characteristics of the actual data without revealing any confidential or sensitive information. • Evidence of Representativeness: The descriptive statistics and treatment effects generated from this dataset remain highly consistent with the original results reported in the manuscript. • Code Provision: We will supply the complete STATA code used in our research, which will include both the analysis and the synthetic data generation process. This will allow other researchers to replicate our analyses using the synthetic data sets. • Support and Clarifications: We are committed to assisting researchers who wish to work with our synthetic data. Should there be any questions or if further clarifications are needed regarding the data or our methodologies, we will provide timely support.