Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-27T18:36:52.877Z Has data issue: false hasContentIssue false

A Simulation Study of Effects of Multicollinearity and Autocorrelation on Estimates of Parameters

Published online by Cambridge University Press:  19 October 2009

Extract

In attempting to analytically discover or test economic relationships, econometricians have available many computational techniques by which to estimate the parameters of their models. But different solution methods may give unbiased and consistent, biased and consistent, or biased and inconsistent estimates under varying assumptions. The model builder is vitally interested in how each of these procedures reacts under varying conditions that may impinge on his model, but which are conditions not assumed by the estimation technique.

Type
Research Article
Copyright
Copyright © School of Business Administration, University of Washington 1966

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1 Johnston, J., Econometric Methods (New York: McGraw-Hill Book Company, Inc., 1963), p. 275.Google Scholar

2 Ibid., pp. 275–77.

3 Ibid., pp. 276–77.

4 Ibid., p. 277

5 Neiswanger, W. A. and Yancey, T. A., “Parameter Estimates and Autonomous Growth,” Journal of American Statistical Association, Vol. 54, pp. 389402.CrossRefGoogle Scholar

6 Ladd, G. W., “Effects of Shocks and Errors in Estimation: An Empirical Comparison,” Journal of Farm Economics, Vol. XXXVIII, pp. 486495.Google Scholar

7 Wagner, H., “A Monte Carlo Study of Estimates of Simultaneous Linear Structural Equations,” Econometrica, Vol. XXVI, pp. 117133.Google Scholar

8 Summers, Robert, “A Capital Intensive Approach to the Small Sample Properties of Various Simultaneous Equation Estimators,” Econcmetrica, Vol. XXXIII, pp. 147.Google Scholar

9 Wagner, H., “A Monte Carlo Study of Estimates of Simultaneous Linear Structural Equations,” Econametrica, Vol. XXVI, pp. 117133.Google Scholar

10 Goldberger, Arthur S., Econometric Theory (New York: John Wiley & Sons, Inc., 1964), p. 316.Google Scholar

11 Ibid., p. 297–99

12 Cochrane, D. and Orcutt, G. H., “A Sampling Study of the Merits of Autoregressive and Reduced Form Transformations in Regression Analysis,” Journal of the American Statistical Association, Vol. XXXXIV, p. 358.Google Scholar

13 The two autoregressive series were developed independently of each other and any intercorrelation between the two series, U1 and U2, is purely accidental and not by design.

14 SirFisher, Ronald A., The Design of Experiments (London: Oliver and Boyd, 1960), pp. 95100.Google ScholarPubMed

15 Summers, Robert, “A Capital Intensive Approach to the Small Sample Properties of Various Simultaneous Equation Estimators,” Econametrica, Vol. XXXIII (January 1965), pp. 147.Google Scholar

16 Ibid, p. 25.