how to model relationship between two persistent AR(1) processes how to model a relationship between an ar(1) process and an independent variable why not model relationship between two persistent ar(1) processes? how to predict a relationship between two process ____ if y_t is different from zero what is the corresponding dependent variable called model correlation of the independent variable $y_t$ with the dependent variable $y_t$ why is it important to model the relationship between an independent and dependent variable in AR which variable is a persistent process? when the independent variable is different from zero what is the dependent variable if $tt$ is different from zero, would $y_t% end up as a process what is the relationship between the dependent variable $_t$ and the independent variable $_t$? how to model a relational process if $y_t = zero what is the relationship between the independent and dependent variables? model relationship between two r(1) processes how to determine whether $y_t is an AR(1) process how to model relationships between an independent and a dependent variable on a random walk if the dependency variable $x_t is stationary in empirical data, then the relationship between $x_t is _____. if beta is different from zero how to model if $y_t$ is stationary which dependent variable is likely to be a correlated error if the dependent variable is 0 then what is the relationship between the independent variable and the independent variable