Forecasting in Urban and Regional Planning Closed Loops: The Examples of Road and Air Traffic Forecasts
- 1 February 1978
- journal article
- research article
- Published by SAGE Publications in Environment and Planning A: Economy and Space
- Vol. 10 (2) , 145-162
- https://doi.org/10.1068/a100145
Abstract
Attempts to forecast in situations in which the leading indicators are also used as policy variables are beset by a number of statistical problems which affect the specification of the forecasting model, estimation of its parameters, and the design of policy itself. The main effects are that when there is perfect policy feedback the forecasting model cannot be identified at all; when there is partial or imperfect feedback the forecasting model is collinear, underidentified, and least-squares parameter estimates will be biased. Estimation procedures available in closed loops are reviewed, and the application of these methods to road and air traffic forecasting is discussed.Keywords
This publication has 11 references indexed in Scilit:
- Identification of processes in closed loop—identifiability and accuracy aspectsAutomatica, 1977
- Feedback between stationary stochastic processesIEEE Transactions on Automatic Control, 1975
- Identifiability conditions for linear systems operating in closed loop†International Journal of Control, 1975
- Survey of applications of identification in chemical and physical processesAutomatica, 1975
- Identification of linear, multivariable systems operating under linear feedback controlIEEE Transactions on Automatic Control, 1974
- Process identification for time series modelling in urban and regional planningRegional Studies, 1974
- Stochastic identification of computer-regulated linear plants in noisy environmentsInternational Journal of Control, 1973
- Stochastic modelling of computer-regulated linear plants in noisy environments †International Journal of Control, 1972
- Problems of identification and controlJournal of Mathematical Analysis and Applications, 1971
- On the problem of ambiguities in maximum likelihood identificationAutomatica, 1971