The Magnificent Seven (Mag 7): Strategic Evolution and Distance-to-Frontier Dataset Suite (2010-2022)

This dataset provides the cleaned panel data and MATLAB replication code for evaluating the structural convergence and multi-market diversification of major technology conglomerates. The data map the technological footprint of the 'Magnificent Seven' cohorts relative to the broader IT sector baseline. Files Included 1. Readme.pdf 2. mag7_longitudinal_subclass_GH.csv: The base technological subclass panel dataset restricted to Cooperative Patent Classification (CPC) sections G (Physics) and H (Electricity). This file is utilized for the core Hill number calculations and the baseline distance-to-frontier analysis. 3. mag7_longitudinal_subclass_th66.csv: The threshold-filtered panel dataset incorporating patents across all CPC sections. It includes data for the Magnificent Seven firms and a baseline 'Rest of the IT sector' comprised of firms where sections G and H constitute at least 66% of their total patent portfolios within the analysis period. This dataset is used exclusively for the Jensen-Shannon Divergence (JSD) robustness checks. 4. Replication.m: The master MATLAB script that automatically loads the datasets, executes the analytical loops, and generates the output figures. Data Source & Temporal Windows The underlying raw data were obtained from PatentsView, last updated on December 9, 2025. While the raw data files span from 2010 through 2024 to capture absolute historical allocation distributions, the empirical analysis window is intentionally evaluated up to the year 2022 to control for standard right-truncation biases introduced by patent approval time lags.