Stambaugh bias on an Indian valuation predictor

You regress monthly Nifty excess returns on the lagged earnings yield over $T = 300$ months. The yield is AR(1) with $\hat\rho = 0.97$; $\hat\sigma_u = 6\%$, $\hat\sigma_v = 0.25\%$, $\widehat{\operatorname{corr}}(u,v) = -0.85$ (illustrative). OLS gives $\hat\beta = 0.9$ with standard error 0.45. (a) Compute $\gamma$ and the approximate bias of $\hat\beta$. (b) Give the bias-adjusted estimate and its $t$-statistic (keep the same standard error). (c) Why is the bias positive, and why does it matter more for valuation ratios than for, say, last month's return as a predictor?