Suchergebnisse

I: Expectations -- 1. Optimal Stabilisation Policies under Perfect Foresight -- 2. Towards the Resurrection of Macroeconomic Policies -- 3. Optimal Feedback and Feedforward Stabilisation of Exchange Rates, Money, Prices and Output -- II: Uncertainty -- 4. Adaptive Econometric Forecasting using an Approximate Filtering-Smoothing Algorithm: the Case of the Israeli Meat Sector -- 5. Controlling an Econometric Model using Different Coefficient Sets -- 6. The Uncertainty Frontier as a Global Approach to the Efficient Stabilisation of Economic Systems: Experiments with the MICRO-DMS Model -- III: Policy Analysis and Decision Models -- 7. Incomes Policy in a Political Business Cycle Environment: a Structural Model for the UK 1961–1980 -- 8. Multiperiod Prediction for Dynamic Models with Autocorrelated Errors Conditional on Feedback Rules for Future Policy Variables -- 9. The Evaluation of Historical Policy via Optimal Control Techniques -- IV: Market Management -- 10. Endogenous vs. Exogenous Targets for Commodity Market Stabilisation -- 11. Simple and Optimal Control Rules for Stabilising Speculative Commodity Markets -- V: Decentralisation and Multi-Sector Planning -- 12. Behavioural Assumptions in Decentralised Stabilisation Policies -- 13. Stability Analysis of Large Scale Economic Systems which have a Multi-time Scale -- 14. The Location of a Firm on a Network -- Epilogue -- 15. Style in Multisectoral Modelling.

ABSTRACTSeveral techniques for solving dynamic rational expectations models have been proposed. This paper puts forward an alternative method for discrete time models, which is significantly simpler to use in practice. That solution is used to derive and compute optimal policy selections (incorporating 'noncausal' effects) which, by exploiting the discrete time framework, are also time consistent when sequentially reoptimized. Those decisions are shown to contain an optimal open loop component plus an innovations dependent correction mechanism. A numerical example is used to verify these properties, and to demonstrate the superiority of this policy selection technique over recursive methods (e.g. dynamic programming).