Continuous-time Dynamic Model Research Articles

The Estimation of Open Higher-Order Continuous Time Dynamic Models with Mixed Stock and Flow Data

This article extends recent work on the Gaussian or quasi-maximum likelihood estimation of the parameters of a closed higher-order continuous time dynamic model by introducing exogenous variables into the model The method presented yields exact maximum likelihood estimates when the innovations are Gaussian and the exogenous variables are polynomials in time of degree not exceeding two, and it can be expected to yield very good estimates under more general conditions. It is applicable, in principle, to a system of any order with mixed stock and iow data. The precise formulas for its implementation are derived, in this article, for a second-order system in which both the endog-enous and exogenous variables are a mixture of stock and flow variables.

The Estimation of Parameters in Nonstationary Higher Order Continuous-Time Dynamic Models

This paper is concerned with derivation of a new efficient algorithm for computing the exact Gaussian likelihood for structural parameters in nonstationary higher-order continuous-time dynamic models and with its application in the estimation of these parameters. The algorithm completely avoids the computation of the covariance matrix of the observations and is applicable to a system of any order with mixed stock and flow data. It is used as the basis for an iterative procedure in which the structural parameters and the initial state vector are estimated alternately.

Walsh Function Decoupled Parameter Estimation Equations for Dynamic Continuous-Time Models with Time-Delay

Abstract A new method is presented based on persistently exciting Walsh function input signals to resolve output signals of MIMO systems into a set of independent SISO output signals - Walsh function orthogonality is used to decouple the parameter estimation equations for the SISO system into an uncoupled set for a second-order subsystem and a second independent set for a first-order subsystem and a time-delay parameter. Numerical results are given to illustrate the method.

Gaussian Estimation of Structural Parameters in Higher Order Continuous Time Dynamic Models

This paper is concerned with the efficient estimation of structural parameters in closed linear systems of higher order stochastic differential equations when the data are in discrete form and the model generally includes both stock and flow variables. A general existence and uniqueness theorem for the solution of such a system is proved and used in the rigorous derivation of exact discrete models satisfied by the various types of data. It is shown how these models can be used in the computation of various asymptotically efficient estimates obtained by the maximization of the Gaussian likelihood or approximations to it.

Qualitative Analysis and Econometric Estimation of Continuous Time Dynamic Models.

Journal Article Qualitative Analysis and Econometric Estimation of Continuous Time Dynamic Models Get access Qualitative Analysis and Econometric Estimation of Continuous Time Dynamic Models. By Giancarlo Gandolfo. (Amsterdam: North-Holland, 1981. Pp. xiv + 253. $39.00, Dfl 80.00.) Kumaraswamy Velupillai Kumaraswamy Velupillai European University Institute, Florence Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 92, Issue 368, 1 December 1982, Pages 981–983, https://doi.org/10.2307/2232687 Published: 01 December 1982

The Specification of Adaptive Expectations in Continuous Time Dynamic Economic Models

The Specification of Adaptive Expectations in Continuous Time Dynamic Economic Models

Optimal Production, Investment, Advertising, and Price Controls for the Dynamic Monopoly Firm

In this paper, a dynamic continuous time model, encompassing operations, investments, output prices, informative advertising, and brand advertising, is formulated as an optimal control problem in an activity analysis context. In the model, the objective of the firm is to maximise, subject to various constraints, the discounted value of accumulated savings over the finite decision-making interval plus the discounted value of capacity at the end of the interval. The state variables are capacity, goodwill of type 1 reflecting informative advertising, goodwill of type 2 reflecting brand advertising, net debt, and the output price. The controls are the scale of operation, the purchase of new capacity, informative advertising, brand advertising, and the rate of change of the output price. Final capacity, goodwill of types 1 and 2, net debt, and price are control parameters. There are several inequality constraints. Using results in control theory, the optimal controls are completely characterized. These results are interpreted using the properties of the Value Equation. In addition, the control problem is transformed into an approximate programming problem.