Let's assume a standard regression model: $$y=\beta x+u$$ We'd like to test if an variable $x_j$ is relevant in the respect of the model.
Most of the time, we assume the following two-tailed hypothesis: $$H_0: \beta_j=b, \ H_1: \beta_j \neq b$$
My question is, why don't we use more often the one-tailed hypothesis to test the significance of a variable $x_j$? When I read papers and write assignments I hardly ever come across one-tailed t-tests in the respect to regression models. Why?