Aging Population and Technology Adoption
Abstract:
Population aging affects the relative supply of labor, the age, and skill composition of workers, thereby altering technology adoption decisions. A dynamic general equilibrium task-based model of endogenous technology adoption and skill acquisition choice shows that the impact of population aging on technology adoption is contingent upon the age structure of the population. Specifically, if the population is relatively young, population aging increases the adoption of “new” – labor-saving and skill-intensive – technology while it reduces its adoption when the population is relatively old. This hump-shaped relationship is supported by empirical evidence. Calibrating the model to fit European data, we observe that population aging is a major driver of the increase in new technology adoption between 1990 and 2015, while it determines its slowdown between 2015 and 2040. Population aging is also a primary contributor to wage inequality, explaining a larger share of its increase than technological progress. Finally, the increase in the retirement age driven by the budgetary pressure imposed by population aging is identified as a key determinant of the reduction of new technology adoption and labor productivity growth in the next decades. Policies aimed at mitigating the retirement age increase can lead to Pareto improving outcomes.
About Daniele Angelini:
Daniele Angelini is an applied theorist who obtained his Ph.D. at the European University Institute; he is now a postdoc researcher at the Macroeconomic chair at Konstanz University and will be joining the Economic Department at the University of Vienna as an Assistant Professor in September 2024. He is interested in Macroeconomics, Labor Economics, Technological Change, and Demographic Transition. His research investigates the interaction between technological and demographic changes and their consequences on the labor market, market structure, economic growth, and inequality.
Language: English
This is a free seminar. Registration is mandatory.
Contact:
dem@uni.lu
Tel: +352 46 66 44 6283
Supported by the Luxembourg National Research Fund (FNR) 17931929