We develop a robust least squares estimator for autoregressions with possibly heavy tailed errors. Robustness to heavy tails is ensured by negligibly trimming the squared error according to extreme values of the error and regressor. Tail-trimming ensures asymptotic normality and...

Lai and Wang's (1996) work suggests that under most circumstances, property valuation based on Vandell's (1991) minimum-variance grid method is more accurate than the valuation based on a linear hedonic pricing model with its coefficients estimated using ordinary least squares technique. This...

We investigated the determinants of profitability in leasing companies of Pakistan over the period 2006 to 2008. This study has applied Ordinary Least Square (OLS) Model and Logistic (Logit) models for estimation of results. It is found that the size, net investments in leasing finance and...

Effectiveness, cost-efficiency and distribution issues are crucial for any form of future regulation. This results in the need for reliable instruments to assess regulations ex ante. Elasticities are key parameters for such instruments. We consistently estimate substitution elasticities for a...

The paper by Kiefer, Vogelsang and Bunzel (2000), KVB henceforth, provides an interesting unconventional application of functional limit theory to a conventional problem. In this note, we point out that the limiting distribution of the t^{∗} test proposed by KVB turns out to be equivalent to...

Effectiveness, cost-efficiency and distribution issues are crucial for any form of future regulation. This results in the need for reliable instruments to assess regulations ex ante. Elasticities are key parameters for such instruments. We consistently estimate substitution elasticities for a...