Mixed estimation and OLS were each used to estimate an aggregate agricultural production function for Thailand for which data were highly multicollinear. The final mixed model obtained using minimax regret in the pretest appeared to significantly outperform OLS in terms of precision and overall reasonableness, mitigating a serious multicollinearity problem.