Technology becomes useful only when individuals adopt it for productive activity. The manner in which adoption occurs is therefore important for a complete understanding of the evolution of technological change. We study a model with exogenously occurring technological progress and endogenous adoption of it. Individuals with N-period lives optimally allocate their time between leisure, work and adoption of new technology. We show that optimal behavior is characterized by a sequence of four phases of life which, described in their order of occurrence, are: (1) adoption only (schooling); (2) work and adoption (career path); (3) work but no adoption (end-of-work-life easing); (4) no work or adoption (retirement). The presence of the third phase, a period in which older workers choose not to adopt new technology, has several implications for the effects of changes in aggregate exogenous technology. Among these is the implication that a wave of innovation will have a smaller effect when the number of workers in this phase is relatively large. This is tested using patent data as a proxy for innovation and the Solow residual as a measure of technological progress; some support for this proposition is found. The model also implies that older (third phase) workers will appear more productive because each hour of non-leisure time will be devoted entirely to productive work, rather than being divided between work and technology adoption time. The data provides some support for this proposition as well: measured productivity is positively correlated with the relative size of the oldest cohort of workers.
[1]
José-Víctor Ríos-Rull.
Working in the Market, Working at Home, and the Acquisition of Skills: A General-Equilibrium Approach
,
1993
.
[2]
A. Rustichini,et al.
Research and imitation in long-run growth
,
1991
.
[3]
Boyan Jovanovic,et al.
The Life Cycle of a Competitive Industry
,
1993,
Journal of Political Economy.
[4]
Manuel S. Santos,et al.
On Endogenous Growth with Physical and Human Capital
,
1993,
Journal of Political Economy.
[5]
James D. Adams,et al.
Fundamental Stocks of Knowledge and Productivity Growth
,
1990,
Journal of Political Economy.
[6]
Z. Griliches.
Patent Statistics as Economic Indicators: a Survey
,
1990
.
[7]
D. Commerce.
Statistical abstract of the United States
,
1978
.
[8]
Stephen L. Parente,et al.
Barriers to Technology Adoption and Development
,
1994,
Journal of Political Economy.
[9]
J. Mincer.
Schooling, Experience, and Earnings
,
1976
.
[10]
Robert E. Hall,et al.
The Relation between Price and Marginal Cost in U.S. Industry
,
1988,
Journal of Political Economy.
[11]
R. Lucas.
On the Mechanics of Economic Development
,
1988
.