References of "Santugini, Marc"
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See detailOptimal Growth and Uncertainty: Learning
Koulovatianos, Christos UL; Mirman, Leonard; Santugini, Marc

in Journal of Economic Theory (2009), 144

We introduce learning in a Brock-Mirman environment and study the effect of risk generated by the planner’s econometric activity on optimal consumption and investment. Here, learning introduces two ... [more ▼]

We introduce learning in a Brock-Mirman environment and study the effect of risk generated by the planner’s econometric activity on optimal consumption and investment. Here, learning introduces two sources of risk about future payoffs: structural uncertainty and uncertainty from the anticipation of learning. The latter renders control and learning nonseparable. We present two sets of results in a learning environment. First, conditions under which the introduction of learning increases or decreases optimal consumption are provided. The effect depends on the strengths and directions of the two sources of risk, which may pull in opposite directions. Second, the effects of changes in the mean and riskiness of the distribution of the signal and initial beliefs on optimal consumption are studied. [less ▲]

Detailed reference viewed: 55 (8 UL)
See detailInvestment in a Monopoly with Bayesian Learning
Koulovatianos, Christos UL; Mirman, Leonard J.; Santugini, Marc

Report (2006)

We study how learning affects an uninformed monopolist's supply and investment decisions under multiplicative uncertainty in demand. The monopolist is uninformed because it does not know one of the ... [more ▼]

We study how learning affects an uninformed monopolist's supply and investment decisions under multiplicative uncertainty in demand. The monopolist is uninformed because it does not know one of the parameters defining the distribution of the random demand. Observing prices reveals this information slowly. We first show how to incorporate Bayesian learning into dynamic programming by focusing on sufficient statistics and conjugate families of distributions. We show their necessity in dynamic programming to be able to solve dynamic programs either analytically or numerically. This is important since it is not true that a solution to the infinite-horizon program can be found either analytically or numerically for any kinds of distributions. We then use specific distributions to study the monopolist?s behavior. Specifically, we rely on the fact that the family of normal distributions with an unknown mean is a conjugate family for samples from a normal distribution to obtain closed- form solutions for the optimal supply and investment decisions. This enables us to study the effect of learning on supply and investment decisions, as well as the steady state level of capital. Our findings are as follows. Learning affects the monopolist's behavior. The higher the expected mean of the demand shock given its beliefs, the higher the supply and the lower the investment. Although learning does not affect the steady state level of capital since the uninformed monopolist becomes informed in the limit, it reduces the speed of convergence to the steady state. [less ▲]

Detailed reference viewed: 29 (2 UL)