Regression Model with Gamma Disturbances Gauss file(s) prop_gamma.g Matlab file(s) prop_gamma.m Consider the linear regression model yt = 0 + 1xt + (ut ),

Regression Model with Gamma Disturbances Gauss file(s) prop_gamma.g Matlab file(s) prop_gamma.m Consider the linear regression model yt = β0 + β1xt + (ut − ρα), where yt is the dependent variable, xt is the explanatory variable and the disturbance term ut is an iid drawing from the gamma distribution f(u; ρ, α) = 1 Γ(ρ)  1 α ρ u ρ−1 exp h − u α i , with Γ(ρ) representing the gamma function. The term −ρα in the regression model is included to ensure that E[ut − ρα] = 0. For samples of size T = {50, 100, 250, 500}, compute the standardized sampling distributions of the least squares estimators z βb0 = βb 0 − β0 se(βb 0) , zβb1 = βb 1 − β1 se(βb 1) , based on 5000 draws, parameter values β0 = 1, β1 = 2, ρ = 0.25, α = 0.1 and xt is drawn from a standard normal distribution. Discuss the limiting properties of the sampling distributions.