Modelling Experience as Signal Accumulation
AbstractExperience gained in a workplace characterised by decision-making and learning-by-doing is modelled via a process of signal accumulation under several different frameworks. We initially look at the probability of success based on uninterrupted signal accumulation, then consider the impact of rapid labour turnover under two alternative regimes. The first allows new workers to gain some of their predecessor’s experience through Bayesian inference on reported earlier actions. The means of information transfer between workers is therefore similar to observational learning in herding or informational cascade models. The second regime considers all experience to be lost when a worker is replaced. We see that although with valuable experience the first regime appears a much better outcome for firms, transferring some knowledge to future workers carries with it the risk of excess inertia in decision-making.
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Bibliographic InfoPaper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0205.
Date of creation: Mar 2002
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herding; private information; experience; labour turnover; excess inertia;
Find related papers by JEL classification:
- D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-04-03 (All new papers)
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