9.4 A variable Y is determined by the model Y = 1 + 2Z + v, where Z is a variable and v is a

9.4 A variable Y is determined by the model Y = β1 + β2Z + v,

where Z is a variable and v is a disturbance term that satisfies the Gauss–Markov conditions.
The explanatory variable is subject to measurement error and is measured as X where X = Z + w and w is the measurement error, distributed independently of v. Describe analytically the consequences of using OLS to fit this model if (1) The expected value of w is not equal to 0 (but w is distributed independently of Z), (2) w is not distributed independently of Z (but its expected value is 0).