Asked by Joy
Consider a linear model with unobserved beterogeneity (q) and measurement error in an explanatory variable:
y = B0 + B1x1 + ... + Bkx*k + q + v
where ek = xk - x*k is the measurement error and we set the coefficient on q equal to one without loss of generality. The variable q might be correlated with any of the explanatory variables, but an indicator, q1= 8o + 81q + a1, is available. The measurement error ek might be correlated with the observed measure, xk. In addition to q1, you also have variables z1,z2; ...zM, M > or equal to 2, that are uncorrelated with v, a1, and ek.
A.) Suggest an IV procedure for consistently estimating the Bj. Why is M > or equal to 2 required?
y = B0 + B1x1 + ... + Bkx*k + q + v
where ek = xk - x*k is the measurement error and we set the coefficient on q equal to one without loss of generality. The variable q might be correlated with any of the explanatory variables, but an indicator, q1= 8o + 81q + a1, is available. The measurement error ek might be correlated with the observed measure, xk. In addition to q1, you also have variables z1,z2; ...zM, M > or equal to 2, that are uncorrelated with v, a1, and ek.
A.) Suggest an IV procedure for consistently estimating the Bj. Why is M > or equal to 2 required?
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