Estimating Distributed Lag Models from Cross Section Data

The Case of Hospital Admissions and Discharges

Charles R. Nelson

University of Washington, Seattle, WA
and National Bureau of Economic Research

G. William Schwert

University of Rochester, Rochester, NY 14627
and National Bureau of Economic Research

Journal of the American Statistical Association, 69 (September 1974) 627-633

It is natural to think of estimating distributed lag models from time series data since it is time series contexts that such models arise. This article studies the estimation of rational distributed lags in the context of hospital admissions and discharges where a relevant body of cross-section data exists in the form of lengths-of-stay and appears to be more appropriate for this purpose than do the available time series data. The cross-section approach presumably has applications in many situations in which length-of-stay in the system or its counterpart can be observed.

Key words: Hospital, Length-of-stay, Distributed lag, Maximum likelihood

JEL Classifications: C22

Cited 3 times in the SSCI and SCOPUS through 2014
© Copyright 1974, American Statistical Association
A full-text version of this paper, including tables and figures, is available in Acrobat's portable data format (.pdf). The file is about 1,292K and can only be viewed (and printed) using a copy of Acrobat Reader.

If you want the current version of the Adobe Acrobat Reader for other platforms, visit Adobe's web page by clicking the image below.

Click here to download the reprint of the causality test paper.

Click here to download a lower quality (and smaller file size) reprint of the causality test paper.

Return to Publications Page

© Copyright 1998-2015, G. William Schwert

Last Updated on 2/26/2015