Application of Least Squares Regression to Relationships Containing Auto-Correlated Error Terms
- 1 March 1949
- journal article
- research article
- Published by Informa UK Limited in Journal of the American Statistical Association
- Vol. 44 (245), 32-61
- https://doi.org/10.1080/01621459.1949.10483290
Abstract
We point out that autocorrelated error terms require modification of the usual methods of estimation and prediction; and we present evidence showing that the error terms involved in most current formulations of economic relations are highly positively autocorrelated. In doing this we demonstrate that when estimates of autoregressive properties of error terms are based on calculated residuals there is a large bias towards randomness. We demonstrate how much efficiency may be lost by current methods of estimation and prediction; and we give a tentative method of procedure for regaining the lost efficiency.Keywords
This publication has 12 references indexed in Scilit:
- Statistical Analysis of the Demand for Food: Examples of Simultaneous Estimation of Structural EquationsEconometrica, 1947
- The Use of Econometric Models as a Guide to Economic PolicyEconometrica, 1947
- Some Applications of Multivariate Analysis to Economic DataJournal of the American Statistical Association, 1946
- Statistical Estimation of Simultaneous Economic RelationsJournal of the American Statistical Association, 1945
- The Analysis of Market DemandJournal of the Royal Statistical Society, 1945
- The Probability Approach in EconometricsEconometrica, 1944
- Distribution of the Ratio of the Mean Square Successive Difference to the VarianceThe Annals of Mathematical Statistics, 1941
- IV.—On Least Squares and Linear Combination of ObservationsProceedings of the Royal Society of Edinburgh, 1936
- XX.—On the Theory of Statistical RegressionProceedings of the Royal Society of Edinburgh, 1934
- Why do we Sometimes get Nonsense-Correlations between Time-Series?--A Study in Sampling and the Nature of Time-SeriesJournal of the Royal Statistical Society, 1926