In a dataset of $n = 15$ points, the response variable is completely constant: $y_i = 10.0$ for all observations, but the predictor variable $x$ varies. If you fit a simple linear regression model $\hat{y} = \beta_0 + \beta_1 x$ using ordinary least squares, what are the estimated values of $\hat{\beta}_1$ and $\hat{\beta}_0$?