Optimal learning through experimentation by microeconomic agents
This thesis concerns itself with optimal learning through experimentation by microeconomic agents. The first part presents a model of a search process for the best outcome of many multi-stage projects. The branching structure of the search environment is such that the pay-offs to various actions are correlated; nevertheless, it is shown that the optimal strategy is given by a simple reservation price rule. A simple model of R&D is provided as an example. These general results are then applied in a model of job search and occupational choice in which jobs are grouped into occupations in a natural way. Before getting a job, the agent must first become qualified in the chosen occupation, at which point his general aptitude for jobs in this occupation is revealed. The search environment is such that the returns of jobs are correlated within a given occupation, but the optimal strategy is given by the above reservation value rule. One implication of this is that young inexperienced workers prefer to try riskier jobs/occupations first. Issues of job turnover and expected returns are addressed. The second part studies optimal experimentation by a monopolist who faces an unknown demand curve subject to random changes, and who maximises profits over an infinite horizon in continuous time. Two qualitatively very different regimes emerge, determined by the discount rate and the intensities of demand curve switching, and the dependence of the optimal policy on these parameters is discontinuous. One regime is characterised by extreme experimentation and good tracking of the prevailing demand curve, the other by moderate experimentation and poor tracking. Moreover, in the latter regime the agent eventually becomes ‘trapped’ into taking actions in a strict subset of the feasible set.