1. Introduction

The technology-employment nexus: competing views

Classical, neoclassical, Keynesian and Evolutionary approaches 

SBTC, RBTC model and beyond 

Robots and employment 

References

Calvino, F., & Virgillito, M. E. (2018). The innovation‐employment nexus: a critical survey of theory and empirics. Journal of Economic surveys, 32(1), 83-117.

Montobbio, F., Staccioli, J., Virgillito, M. E., & Vivarelli, M. (2023). The empirics of technology, employment and occupations: Lessons learned and challenges ahead. Journal of Economic Surveys.

Notes provided in class

2. Using meta-analysis to synthesize the empirical literature on the robot-employment nexus 

Why meta-analsis can be helpful to synthesize the empirical literature on critical research questions and how it works 

Assessing the literature focusing on the robot-employment nexus 

Identifying the 'pubblication bias'

Investigating the role of heterogeneity

References

Irsova, Z., Doucouliagos, H., Havranek, T., & Stanley, T. D. (2023). Meta‐analysis of social science research: A practitioner's guide. Journal of Economic Surveys, 1-20.

Guarascio, D., Piccirillo, A., & Reljic, J. (2024). Will Robots Replace Workers? Assessing the Impact of Robots on Employment and Wages with Meta-Analysis. Assessing the Impact of Robots on Employment and Wages with Meta-Analysis.

3. Digitalization, AI and labor markets

Digitalization and labour markets

The impact of AI on labor markets: theoretical foundations

Measuring the diffusion of AI in labour markets 

Estimating  the impact of AI on employment: measurement and identification strategies 

References

Cirillo, V., Evangelista, R., Guarascio, D., & Sostero, M. (2021). Digitalization, routineness and employment: An exploration on Italian task-based data. Research Policy, 50(7), 104079.

Guarascio, D., Reljic, (2024). Artificial intelligence and employment