Linear Quadratic Optimization for Models with Rational Expectations and Learning
نویسندگان
چکیده
In this paper we present a method for using rational expectations in a linearquadratic optimization framework with learning. We present a method that allows a policy maker to derive an optimal policy in the presence of rational expectations and the possibility of parameter drift. In this fashion the Lucas critique can be mitigated.
منابع مشابه
Stochastic Policy Design in a Learning Environment with Rational Expectations
In this paper we present a method for using rational expectations in a stochastic linear-quadratic optimization framework in which the unknown parameters are updated through a learning scheme. We use the QZ decomposition as suggested by Sims (1996) to solve the rational expectations part of the model. The parameter updating is done with the Kalman filter and the optimal control is calculated us...
متن کاملTesting for Stochastic Non- Linearity in the Rational Expectations Permanent Income Hypothesis
The Rational Expectations Permanent Income Hypothesis implies that consumption follows a martingale. However, most empirical tests have rejected the hypothesis. Those empirical tests are based on linear models. If the data generating process is non-linear, conventional tests may not assess some of the randomness properly. As a result, inference based on conventional tests of linear models can b...
متن کاملAbout One Sweep Algorithm for Solving Linear-Quadratic Optimization Problem with Unseparated Two-Point Boundary Conditions
In the paper a linear-quadratic optimization problem (LCTOR) with unseparated two-point boundary conditions is considered. To solve this problem is proposed a new sweep algorithm which increases doubles the dimension of the original system. In contrast to the well-known methods, here it refuses to solve linear matrix and nonlinear Riccati equations, since the solution of such multi-point optimi...
متن کاملOptimization of ammonia removal in an integrated fix-film activated sludge using response surface methodology
In this work, removal of ammonia from synthetic wastewater using integrated fixed-film activated sludge (IFAS) process was optimized using response surface methodology (RSM). The main operating parameters such as ammonia concentration rate (ALR) and hydraulic retention time (HRT) were optimized to acquire the maximum removal efficiency. The linear, 2FI, quadratic, mean, and cubic models were ut...
متن کاملComparison of Kullback-Leibler, Hellinger and LINEX with Quadratic Loss Function in Bayesian Dynamic Linear Models: Forecasting of Real Price of Oil
In this paper we intend to examine the application of Kullback-Leibler, Hellinger and LINEX loss function in Dynamic Linear Model using the real price of oil for 106 years of data from 1913 to 2018 concerning the asymmetric problem in filtering and forecasting. We use DLM form of the basic Hoteling Model under Quadratic loss function, Kullback-Leibler, Hellinger and LINEX trying to address the ...
متن کامل