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This article demonstrates how a spurious regression problem caused by dividend persistence is compounded by a spurious correlation problem when the dependent and independent variables in dividend behaviour regressions are ratios composed of common component variables. This article utilises a simulation procedure to take account of these problems, with the findings implying that extreme care should be taken when using ratios as predictor or explanatory variables in time series regression. This article introduces a reformulated Lintner first difference dividend behaviour model that is not subject to spurious regression in which past prices predict subsequent changes in dividends.

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The present paper explores a class of jump-diffusion models for the Australian short-term interest rate. The proposed general model incorporates linear mean-reverting drift, time-varying volatility in the form of LEVELS (sensitivity of the volatility to the levels of the short-rates) and generalized autoregressive conditional heteroscedasticity (GARCH), as well as jumps, to match the salient features of the short-rate dynamics. Maximum likelihood estimation reveals that pure diffusion models that ignore the jump factor are mis-specified in the sense that they imply a spuriously high speed of mean-reversion in the level of short-rate changes as well as a spuriously high degree of persistence in volatility. Once the jump factor is incorporated, the jump models that can also capture the GARCH-induced volatility produce reasonable estimates of the speed of mean reversion. The introduction of the jump factor also yields reasonable estimates of the GARCH parameters. Overall, the LEVELS-GARCH-JUMP model fits the data best. Copyright 2005 Accounting and Finance Association of Australia and New Zealand..

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