Predicting the Value of Y Variable Using Parameter Estimates

What is the model for predicting the value of y variable?

The model for predicting the value of y variable is ln y = β₁ + β₂x + u, where β₁ and β₂ are the parameter estimates.

Model for Predicting Y:

The model for predicting the value of y variable is ln y = β₁ + β₂x + u, where β₁=-0.7 and β₂=0.3.

When predicting the value of a y variable, the model used is ln y = β₁ + β₂x + u. In this model, β₁ represents the intercept, β₂ represents the coefficient for the x variable, and u represents the error term. The parameter estimates for this model are important as they provide the values for β₁ and β₂ that are used in the prediction equation. By substituting these parameter estimates into the model, we can make predictions about the value of y based on different values of x.

In this case, the parameter estimates given are β₁=-0.7 and β₂=0.3. These values are used to calculate the approximate value of y when x=-1.4.