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Autoregressive Modeling of Earnings‐Investment Causality

Autoregressive Modeling of Earnings‐Investment Causality ABSTRACT The purpose of this paper is to empirically test the relationships between corporate earnings and investment. In particular, the study investigates whether knowledge of past investments improves the prediction of future earnings beyond predictions that are based on past earnings alone. Similarly, it investigates whether knowledge of past earnings improves the prediction of future investments beyond knowledge of past investments alone. This is the empirical definition of Granger causality. The empirical results show that the bivariate past series of earnings and investments is superior to the univariate series in predicting future investments but not in predicting future earnings. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journal of Finance Wiley

Autoregressive Modeling of Earnings‐Investment Causality

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References (34)

Publisher
Wiley
Copyright
1987 The American Finance Association
ISSN
0022-1082
eISSN
1540-6261
DOI
10.1111/j.1540-6261.1987.tb02547.x
Publisher site
See Article on Publisher Site

Abstract

ABSTRACT The purpose of this paper is to empirically test the relationships between corporate earnings and investment. In particular, the study investigates whether knowledge of past investments improves the prediction of future earnings beyond predictions that are based on past earnings alone. Similarly, it investigates whether knowledge of past earnings improves the prediction of future investments beyond knowledge of past investments alone. This is the empirical definition of Granger causality. The empirical results show that the bivariate past series of earnings and investments is superior to the univariate series in predicting future investments but not in predicting future earnings.

Journal

The Journal of FinanceWiley

Published: Mar 1, 1987

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