
Asad Zaman
I have taught at leading universities like Columbia, U. Penn., Johns Hopkins and Cal. Tech. My textbook Statistical Foundations of Econometric Techniques (Academic Press, NY, 1996) is widely used in advanced graduate courses. My research on Islamic economics is widely cited, and has been highly influential in shaping the field. I am deeply engaged in a project to create a revolutionary alternative to mainstream economics and econometrics. Both disciplines are based on flawed foundations of logical positivist ideas. My publications in top ranked journals like Annals of Statistics, Journal of Econometrics, Econometric Theory, Journal of Labor Economics, etc. have more than a thousand citations as per Google Scholar.
Phone: +92 334 5164905
Address: House 5A, Street 33, F8/1, Islamabad, Pakistan
Phone: +92 334 5164905
Address: House 5A, Street 33, F8/1, Islamabad, Pakistan
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estimate for a regression model. The validity of the usual variance estimate depends on
some assumptions, most critically the validity of the model being estimated. This is often
violated in model selection contexts, where model search takes place over invalid models.
A cross validated variance estimate is more robust to specification errors (see, for
example, Efron, 1983). We consider the effects of replacing the usual variance estimate
by a cross validated variance estimate, namely, the Prediction Sum of Squares (PRESS) in
the functions of several model selection criteria. Such replacements improve the
probability of finding the true model, at least in large samples.