A Monte Carlo study of the effect of design characteristics on the inequality restricted maximum entropy estimator
In this paper, we conduct a set of Monte Carlo sampling experiments to examine the effect of design characteristics on the inequality restricted maximum entropy (RME) estimator. We generate data under varying design characteristics, and estimate the parameters using maximum entropy and least squares estimation, both with and without parameter inequality restrictions. As part of the experimental design we vary the sample size, the distribution of the regressors, the distribution of the errors, the degree of collinearity, the signal-to-noise ratio, and the specification error. We compare the alternative estimators on the basis of mean square error.
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- Shen, Edward Z. & Perloff, Jeffrey M., 2001. "Maximum entropy and Bayesian approaches to the ratio problem," Journal of Econometrics, Elsevier, vol. 104(2), pages 289-313, September.
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