We consider AR(q) models in time series with non-normal innovations represented by a member of a wide family of symmetric distributions (Student's t).Since the ML (maximum likelihood) estimators are intractable, we derive the MML (modi®ed maximum likelihood) estimators of the parameters and show that they are remarkably ef®cient. We use these estimators for hypothesis testing, and show that the resulting tests are robust and powerful.

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Regression models are used to show that interest rates, income growth rates and the supply of housing have not played a statistically significant role in the determination of private housing prices in Singapore between 1975 and 1994. Instead, private housing prices in Singapore were highly correlated with the prices for public-sector-built housing. Moreover, the timing of government policies relating to the use of compulsory savings for private housing finance purposes, the liberalisation of rules on public housing ownership criterion as well as for housing finance had a significant impact on private housing prices.

Extensive evidence on the prevalence of calendar effects suggests that there exists abnormal returns, but some recent studies have concluded that calendar effects have largely disappeared. In spite of the non-normal nature of stock returns, most previous studies have employed the meanvariance criterion or CAPM statistics, which rely on the normality assumption and depend only on the first two moments, to test for calendar effects. A limitation of these approaches is that they miss much important information contained in the data such as higher moments. In this paper, we use the Davidson and Duclos (2000) test, which is a powerful non-parametric stochastic dominance (SD) test, to test for the existence of day-of-the-week and January effects for several Asian markets using daily data for the period from 1988 to 2002. Our empirical results support the existence of weekday and monthly seasonality effects in some Asian markets but suggest that first order SD for the January effect has largely disappeared.

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