The errors-in-variables model analyzed in the text results in $\hat { \beta } _ { 1 } \stackrel { p } { \longrightarrow } \frac { \sigma _ { X } ^ { 2 } } { \sigma _ { X } ^ { 2 } + \sigma _ { w } ^ { 2 } } \beta _ { 1 }$ so that the OLS estimator is inconsistent. Give a condition involving the variances of X and w, under which the bias towards zero becomes small.

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The Answer of The errors-in-variables model analyzed in the text results in $\hat { \beta } _ { 1 } \stackrel { p } { \longrightarrow } \frac { \sigma _ { X } ^ { 2 } } { \sigma _ { X } ^ { 2 } + \sigma _ { w } ^ { 2 } } \beta _ { 1 }$ so that the OLS estimator is inconsistent. Give a condition involving the variances of X and w, under which the bias towards zero becomes small.

The Errors-In-Variables Model Analyzed in the Text Results In So That the OLS Estimator Is Inconsistent