标题：Regression Analysis of Collinear Data using r-k Class Estimator: Socio-Economic and Demographic Factors Affecting the Total Fertility Rate ( TFR ) in India
摘要：A basic assumption concerned with general linear regression model isthat there is no correlation (or no multicollinearity) between the explana-tory variables. When this assumption is not satis ed, the least squaresestimators have large variances and become unstable and may have a wrongsign. Therefore, we resort to biased regression methods, which stabilizethe parameter estimates. Ridge regression (RR) and principal componentregression (PCR) are two of the most popular biased regression methodswhich can be used in case of multicollinearity. But the r-k class estimator,which is composed by combining the RR estimator and the PCR estimatorinto a single estimator gives the better estimates of the regression coecientsthan the RR estimator and PCR estimator.This paper explores the multiple regression technique using r-k classestimator between TFR and other socio-economic and demographic variablesand the data has been taken from the National Family Health Survey-III(NFHS-III): 29 states of India. The analysis shows that use of contraceptivedevices shares the greatest impact on fertility rate followed by maternal care,use of improved water, female age at marriage and spacing between births.
关键词：Multicollinearity; principal component regression (PCR) esti-;mator; r-k class estimator; ridge regression (RR) estimator; total fertility;rate (TFR).
