This paper describes a method for solving a class of forward-looking Markov-switching Rational Expectations models under noisy measurement, by specifying the unobservable expectations component as a general-measurable function of the observable states of the system, to be determined optimally...

This paper offers several contributions to actual research and discussion on monetary policy. It clarifies the relationship between uncertainty of inflation persistence and optimal monetary policy and discusses the consequences of the recent Blanchard proposal to implement a higher inflation...

The paper deals with the analysis of a special dynamic production and inventory model. In this model logical restrictions to fulfill an accepted constant minimal level of the production lot size are incorporated, instead of keeping setup cost in the objective function, as it is common in many...

This paper continues the analysis of a special uncapacitated single item lot sizing problem where a minimum order quantity restriction, instead of the setup cost, guarantees a certain level of production lots. A detailed analysis of the model and an investigation of the particularities of the...

This paper explores a single-item capacitated lot sizing problem with minimum order quantity, which plays the role of minor set-up cost. We work out the necessary and suffcient solvability conditions and apply the general dynamic programming technique to develop an O(T³) exact algorithm that is...

We consider a model for a serial supply chain in which production, inventory, and transportation decisions are integrated, in the presence of production capacities and for different transportation cost functions. The model we study is a generalization of the traditional single-item economic...

In this paper we present a polynomial time dynamic programming algorithm for solving a scheduling problem with a (total) weighted completion time objective function where the weights are activity- and time-dependent. We highlight application areas for this type of problem to underscore the...

We propose a new methodology for structural estimation of dynamic discrete choice models. We combine the Dynamic Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the DP problem and estimates the parameters...

This paper develops dynamic structural models - an option value model and a dynamic programming model - of the Social Security Disability Insurance (SSDI) application timing decision. We estimate the time to application from the point at which a health condition first begins to affect the kind...

Using a structural dynamic programming model, we investigate the relative importance of family background variables and individual specific abilities in explaining cross-sectional differences in schooling attainments and wages. Given scholastic ability, household background variables (especially...