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"Learning By Doing and the ...
This paper explores a one-agent Bayesian model of learning by doing and technological choice. To produce output, the agent can choose among various technologies. The beneficial effects of learning by doing are bounded on each technology, and so long-run growth in output can take place only if the agent repeatedly switches to better technologies. As the agent repeatedly uses a technology, he learns about its unknown parameters, and this accumulated expertise is a form of human capital. But when the agent switches technologies, part of this human capital is lost. It is this loss of human capital that may prevent the agent from moving up the quality ladder of technologies as quickly as he can, since the loss is greater the bigger is the technological leap. We analyze the global dynamics. We find that a human-capital- rich agent may find it optimal to avoid any switching of technologies, and therefore to experience no long-run growth. On the other hand, a human-capital-poor agent, who because of his lack of skill is not so attached to any particular technology, can find it optimal to switch technologies repeatedly, and therefore enjoy long-run growth in output. Thus the model can give rise to overtaking
Monografía
monografia Rebiun36674274 https://catalogo.rebiun.org/rebiun/record/Rebiun36674274 m o d cr ||||||||||| 120107s1994 mau o 000 0 eng d 72459224 1027369396 1119438489 1243125262 UAO ocn756569616 DKDLA eng pn DKDLA OCLCQ COO OCLCQ OCLCO OCLCQ KIJ WYU YOU NBERS OCLCQ OCLCO OCLCQ QGK OCLCL OCLCF OCLCQ 361.37 23 "Learning By Doing and the Choice of Technology." Boyan Jovanovic, Yaw Nyarko Cambridge, Mass. National Bureau of Economic Research 1994 Cambridge, Mass. Cambridge, Mass. National Bureau of Economic Research 1 online resource 1 online resource Text txt rdacontent computer c rdamedia online resource cr rdacarrier NBER working paper series no. w4739 This paper explores a one-agent Bayesian model of learning by doing and technological choice. To produce output, the agent can choose among various technologies. The beneficial effects of learning by doing are bounded on each technology, and so long-run growth in output can take place only if the agent repeatedly switches to better technologies. As the agent repeatedly uses a technology, he learns about its unknown parameters, and this accumulated expertise is a form of human capital. But when the agent switches technologies, part of this human capital is lost. It is this loss of human capital that may prevent the agent from moving up the quality ladder of technologies as quickly as he can, since the loss is greater the bigger is the technological leap. We analyze the global dynamics. We find that a human-capital- rich agent may find it optimal to avoid any switching of technologies, and therefore to experience no long-run growth. On the other hand, a human-capital-poor agent, who because of his lack of skill is not so attached to any particular technology, can find it optimal to switch technologies repeatedly, and therefore enjoy long-run growth in output. Thus the model can give rise to overtaking Service learning Bayesian statistical decision theory Technology- Mathematical models Bayesian statistical decision theory. Service learning. Technology- Mathematical models. Nyarko, Yaw Jovanovic, Boyan National Bureau of Economic Research Working paper series (National Bureau of Economic Research) no. w4739