Replication Data for the Paper "Is there a secular decline in disruptive patents? Correcting for measurement bias"

<p><strong>Working Paper Title: The Illusive Slump of Disruptive Patents</strong></p> <p>The repository contains replication data and scripts for the paper:&nbsp;</p> <p>Jeffrey T. Macher, Christian Rutzer, Rolf Weder,<br>Is there a secular decline in disruptive patents? Correcting for measurement bias,<br>Research Policy,<br>Volume 53, Issue 5,<br>2024,<br>104992,<br>ISSN 0048-7333,<br>https://doi.org/10.1016/j.respol.2024.104992</p> <p>The core component of the repository is the file `replication_file.R` which is an R script to replicate all figures and tables of the paper.</p> <p>The script relies on multiple data files. The datasets contain CD-values for granted USPTO utility patents for the years 1976-2016. All data is available in two formats, `.fst' (from the R package fst) and `.csv'.</p> <p>&nbsp;</p> <p><strong>Dataset Descriptions</strong></p> <p><strong>Main Datasets:</strong></p> <p>1. `dat_cd5_no_trunc`: This dataset contains the CD5 index of patents based on a method without truncation.&nbsp;</p> <p>2. `dat_cd5_trunc_1975`: This dataset contains the CD5 index of patents based on a truncation method as in Park et al. (Nature, 2023).</p> <p>3. `dat_cd5_no_trunc_app_adj`: This dataset contains the CD5 index of patents based on a method without truncation and including citations to patent applications granted by 2021.&nbsp;</p> <p>&nbsp;</p> <p><strong>Additional Datasets:</strong></p> <p>4. `dat_cd5_trunc_1985`: This dataset contains the CD5 index of patents based on a truncation of all backward citations to patents published before 1985.</p> <p>5. `dat_cd5_trunc_1995`: This dataset contains the CD5 index of patents based on a truncation of all backward citations to patents published before 1995.</p> <p>6. `dat_cd5_no_trunc_app`: This dataset contains the CD5 index of patents based on a method without truncation and including citations to patent applications granted by 2021, as well as those not yet granted.&nbsp;</p> <p>7. `age_bwc_untrunc`: This dataset contains the age of backward citations using untruncated data.</p> <p>8. age_bwc_trunc: This dataset contains the age of backward citations using truncated data as in Park et al. (Nature, 2023).</p> <p>9. `age_bwc_untrunc_app_adj`: This dataset contains the age of backward citations using untruncated data and considering citations of patent applications granted until 2021.</p> <p>10. `dat_cd10_trunc_1975`: This dataset contains the CD10 index of patents based on a truncation method as in Park et al. (Nature, 2023).&nbsp;</p> <p>11. `dat_cd10_no_trunc_app_adj`: This dataset contains the CD10 index of patents based on a method without truncation and including citations to patent applications granted by 2021.&nbsp;</p> <p>12. `dat_cd2021_trunc_1975`: This dataset contains the CD index as of 2021 of patents based on a truncation method as in Park et al. (Nature, 2023).&nbsp;</p> <p>13. `dat_cd2021_no_trunc_app_adj`: This dataset contains the CD index as of 2021 of patents based on a method without truncation and including citations to patent applications granted by 2021.&nbsp;</p> <p>&nbsp;</p> <p>To successfully run the `replication_file.R' script, make sure all data files are in the directory and the `mainDir1' variable at the beginning of the script is set to the correct path to where the data is stored. In addition, set the `mainDir2' variable to the folder where you want to store the figures created by the script.&nbsp;</p> <p>If you have any questions, please contact christian.rutzer@unibas.ch</p>