SECOND ORDER LEAST SQUARE ESTIMATION ON ARCH(1) MODEL WITH BOX-COX TRANSFORMED DEPENDENT VARIABLE
Abstract
Box-Cox transformation is often used to reduce heterogeneity and to achieve a symmetric distribution of response variable. In this paper, we estimate the parameters of Box-Cox transformed ARCH(1) model using second-order leastsquare method and then we study the consistency and asymptotic normality for second-order least square (SLS) estimators. The SLS estimation was introduced byWang (2003, 2004) to estimate the parameters of nonlinear regression models with independent and identically distributed errors.
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Authors
Utami, H., & -, S. (2014). SECOND ORDER LEAST SQUARE ESTIMATION ON ARCH(1) MODEL WITH BOX-COX TRANSFORMED DEPENDENT VARIABLE. Journal of the Indonesian Mathematical Society, 19(2), 99–110. https://doi.org/10.22342/jims.19.2.166.99-110
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