Replication Package for "Central Signal Premium and Purity-Amplified Reactions to Emerging Industry Initiatives: Evidence from China's Low-Altitude Economy"

This archive is the complete replication package for the manuscript "Central Signal Premium and Purity-Amplified Reactions to Emerging Industry Initiatives: Evidence from China's Low-Altitude Economy" by Hao Zhu (Shanghai Sanda University), prepared for submission to a peer-reviewed journal in the Pacific-Basin finance field. Contents. the hand-collected Low-Altitude-Economy Policy Event Database (LAE-PED v1.0), containing 47 policy events spanning January 2022 to September 2025, aggregated into 39 same-trading-day event clusters used as the main analysis sample; Python 3.11 code (with optional R 4.3 cross-checks) for: market-model event-study estimation, cross-sectional regression, wild-cluster bootstrap with six-point sub-cluster weights (Webb, 2023), Benjamini-Hochberg false-discovery-rate correction, cross-industry placebo (1,391 non-LAE firm-events), 200-iteration random-date placebo, Oster (2019) / Altonji-Elder-Taber coefficient-stability bounds, Cinelli-Hazlett (2020) partial-R² sensitivity, firm-fixed-effects panel identification, and TF-IDF announcement-novelty scoring; all main-text tables and figures as CSV and PDF/PNG, together with an online appendix replicable from the same inputs; intermediate CAR firm-event panels and diagnostic outputs; a pre-registration document dated 15 March 2025 that fixed the three hypotheses, the regression specification, and the two-day event window prior to the collection of stock-price data; a Dockerfile and reproduce.sh script for one-command containerised reproduction of the entire pipeline; a SHA-256 manifest enabling verification of every intermediate and output file referenced in the paper. Running bash reproduce.sh in the package root rebuilds the full output/ directory from the inputs in approximately 40 minutes on a standard laptop (tested on macOS 14 and Ubuntu 22.04, Python 3.11, R 4.3.2), reproducing the numerical results reported in the paper to the precision displayed. Data sources. Raw daily share-price and turnover panels are obtained from (i) the open-source akshare Python interface, which aggregates publicly reported daily prices from the Shanghai and Shenzhen Stock Exchanges, and (ii) the CSMAR academic-subscription database for the non-LAE placebo panel. Irreversibly-transformed residual/return panels used for estimation are bundled in this archive; these are derived outputs that do not re-disclose CSMAR raw records, so that all reported numerical results can be reproduced both with and without an independent CSMAR subscription. Licence and access. Access is restricted during peer review via a private access token issued to the editorial office of the journal handling the manuscript. Upon formal acceptance, this archive will be made publicly available under the Creative Commons Attribution 4.0 International (CC-BY-4.0) licence within ten working days.