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on Intellectual Property Rights |
| By: | Alexander Cuntz; Alessio Muscarnera; Julio Raffo |
| Abstract: | "Rights of publicity†provide a degree of control over one's name, image, and likeness (NILs), and can have significant commercial value, especially with the advent of artificial intelligence and digital replicas. Although publicity rights have recently received substantial media and legislative attention, they have so far escaped the attention of economists. This article remedies that with the first empirical examination of publicity rights, using asynchronous changes in U.S. state laws to explore potentially welfare-improving economic incentives and the interaction of NIL protections with other intellectual property rights, thus laying the foundation for a new line of economic inquiry. |
| Keywords: | Publicity right, Likeness, Copyright, Trademark, Empirical, Difference-in-differences |
| JEL: | O34 O33 K42 L82 Z10 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:wip:wpaper:89 |
| By: | Saeid Mashhadi; Amirhossein Saghezchi; Vesal Ghassemzadeh Kashani |
| Abstract: | This study develops an interpretable machine learning framework to forecast startup outcomes, including funding, patenting, and exit. A firm-quarter panel for 2010-2023 is constructed from Crunchbase and matched to U.S. Patent and Trademark Office (USPTO) data. Three horizons are evaluated: next funding within 12 months, patent-stock growth within 24 months, and exit through an initial public offering (IPO) or acquisition within 36 months. Preprocessing is fit on a development window (2010-2019) and applied without change to later cohorts to avoid leakage. Class imbalance is addressed using inverse-prevalence weights and the Synthetic Minority Oversampling Technique for Nominal and Continuous features (SMOTE-NC). Logistic regression and tree ensembles, including Random Forest, XGBoost, LightGBM, and CatBoost, are compared using the area under the precision-recall curve (PR-AUC) and the area under the receiver operating characteristic curve (AUROC). Patent, funding, and exit predictions achieve AUROC values of 0.921, 0.817, and 0.872, providing transparent and reproducible rankings for innovation finance. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.09465 |
| By: | Konrad Adler (University of St. Gallen - School of Finance; Swiss Finance Institute); JaeBin Ahn (International Monetary Fund (IMF)); Mai Dao (International Monetary Fund (IMF)) |
| Abstract: | We study how trade liberalization affects financial and innovation decisions of large firms across major G7 countries. We document how firms increase their cash holdings when their country's trading partners lower their import tariffs, while we find no effect of a decrease in the country's own import tariffs. Specifically, we find that the increase in cash holdings occurs before tariff cuts by trading partners and is associated with higher R&D spending and patent filing after the cuts. Our results are consistent with the predictions of a model in which higher expected returns to innovation from enhanced export market access lead to higher cash buffers. |
| Keywords: | Trade, MFN tariff, Cash Holdings, R&D, Patents |
| JEL: | F12 G31 O32 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:chf:rpseri:rp2571 |