THIS IS THE DEV/TESTING WEBSITE IPv4: 13.58.156.237 IPv6: || Country by IP: GB
Journals
Resources
About Us
Open Access

Fehlende Beobachtungen in autoregressiven Verhaltensgleichungen

Year:    1984

Author:    Hasenkamp, Georg

Journal of Contextual Economics – Schmollers Jahrbuch, Vol. 104 (1984), Iss. 1 : pp. 21–28

Abstract

This paper illustrates a method to estimate autoregressive equations whenever some observations are missing. By substituting for the missing observation one obtains a combination of linear and non-linear equations. The common parameters in these equations are estimated by a two-step-method. An empirical illustration of this method is provided by using data on industrial demand for electricity

Journal Article Details

Publisher Name:    Global Science Press

Language:    Multiple languages

DOI:    https://doi.org/10.3790/schm.104.1.21

Journal of Contextual Economics – Schmollers Jahrbuch, Vol. 104 (1984), Iss. 1 : pp. 21–28

Published online:    1984-01

AMS Subject Headings:    Duncker & Humblot

Copyright:    COPYRIGHT: © Global Science Press

Pages:    8

Author Details

Hasenkamp, Georg

  1. Degenais, M. G. (1973), The use of incomplete observations in multiple regression analysis, a generalized least squares approach. Journal of Econometrics 1, 317 - 328.  Google Scholar
  2. Gourieroux, Ch. and A. Monfont (1981), On the problem of missing Data in linear models. Review of Economic Studies 48, 579 - 586.  Google Scholar
  3. Kmenta, J. (1981), On the problem of missing measurements in the estimation of economic relationship, in: E. G. Charatsis (ed.), Proceedings of the Econometric Society Meeting 1979, North-Holland, Arnsterdam.  Google Scholar
  4. Palm, F. C. and Th. E. Nijman (1982), Missing observations in the dynamic regression model, Paper presented at the Econometric Society European Meeting in Dublin. Sept. 1982.  Google Scholar
  5. Wansbeek, T. and A. Kapteyn (1981), Maximum likelihood estimation in a linear model with serially correlated errors when observations are missing, Central Bureau of Statistics, The Netherlands, manuscript.  Google Scholar
  6. White, H. and I. Domowitz (1981), Nonlinear regression with dependent observations, Dept. of Economics, University of California - San Diego, Discussion Paper 81 - 32.  Google Scholar
  7. Zellner, A. (1966), On the analysis of first order autoregressive models with incomplete data. International Economic Review 7, 72 - 76.  Google Scholar