Essays on the Economics of Innovation: Digital Adoption, Blockchain, and Tokenomics

Digitalization is one of the most transformative phenomena of the 21st century, reshaping industries, economies, and labor markets. It drives innovation, increases efficiency, and alters workforce demands. This thesis explores these dynamics through empirical analysis, supported by theoretical and policy considerations. It comprises four studies, three focusing on blockchain technology, each offering unique insights into digitalization’s implications. The first chapter—co-authored with Francesco Carbonero, Aldo Geuna, and Luigi Riso—examines digital adoption’s impact on human capital in Piedmont’s manufacturing sector. Using survey data from Unioncamere Piemonte, we analyze how digital investment influences hiring by education level. Our findings indicate a positive effect on demand for highly educated workers, particularly those with post-secondary Technical Institute (ITS) diplomas, MSc, or PhDs in STEM fields. Conversely, demand for workers with only secondary education declines. We reveal a human capital upscaling dynamic, showing how technology reshapes workforce composition. While digitalization fosters demand for highly educated labor, a balanced human capital mix remains necessary for non-automatable roles. Policymakers should develop education and training initiatives to mitigate job polarization and support workforce adaptability. The second chapter—co-authored with Pierluigi Freni and Enrico Ferro—shifts the thesis’ focus from digitalization’s labor market effects to blockchain technology. It explores the transition from traditional economic models to tokenomics, introducing a morphological framework for blockchain token classification. Categorizing tokens by technological attributes, behavioral incentives, and coordination mechanisms, the study clarifies token ecosystems and their economic functions. As blockchain adoption grows, this work reduces cognitive barriers and helps public and private actors integrate tokenization into their operations. The third chapter—co-authored with Enrico Ferro, Maurizio Fiaschetti, and Francesca Medda—investigates blockchain token price volatility and user activity across 58 networks. First, we analyze the drivers of user activity and token volatility using a novel classification framework. Our results show that token usage influences engagement differently from market stability. Certain features, like earning potential and voting rights, drive holding strategies, while Ethereum ecosystem membership uniquely impacts volatility. Second, we examine the direct relationship between volatility and active users, finding that a 10% rise in volatility correlates with a 3.96–5.88% drop in active addresses. This suggests that volatility may incentivize token retention. Robustness checks, including winsorizing and trimming, confirm these insights into the interplay between economic incentives and behavioral patterns in token ecosystems. The fourth chapter examines daily transaction (TX) fees in Proof-of-Work (PoW) blockchains, analyzing key factors like TX difficulty, active addresses, and block size. Using historical data from eight PoW blockchains, we find that network activity and block size significantly influence fees, while TX difficulty has no measurable effect. A 1% rise in active addresses or block size increases daily fees by approximately 0.59% and 0.72%, respectively. Robustness checks validate these findings, and we observe fee elasticity shifts during peak periods, where early spikes reflect demand-driven sensitivity, while later peaks exhibit a mix of demand- and supply-side effects. Our results highlight user activity and block utilization as primary fee drivers, offering insights into the economic dynamics and scalability of PoW blockchains.