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We propose a partially adaptive estimator based on information theoretic maximum entropy estimates of the error distribution. The maximum entropy (maxent) densities have simple yet flexible functional forms to nest most of the mathematical distributions. Unlike the nonparametric fully adaptive estimators, our parametric esti-mators do not involve choosing a(More)
A semi-parametric econometric model is used to study the relationship between malaria cases and climatic factors in 25 African countries. Results show that a marginal change in temperature and precipitation levels would lead to a significant change in the number of malaria cases for most countries by the end of the century. Consistent with the existing(More)
We use a new method to estimate China's income distributions using publicly available interval summary statistics from China's largest national household survey. We examine rural, urban, and overall income distributions for each year from 1985-2001. By estimating the entire distributions, we can show how the distributions change directly as well as examine(More)
Marginal tax rates have larger income redistribution and equilibrating welfare effects than do social insurance or direct transfer programs. The Earned Income Tax Credit has smaller but still statistically significant desirable effects. Social insurance programs have little effect except for Supplemental Security Income, which increases equality. The(More)
This study proposes an information-theoretic deconvolution method to approximate the entire distribution of individual treatment effect. This method uses higher-order information implied by the standard average treatment effect estimator to approximate the underlying distribution of individual treatment effect using the method of maximum entropy density.(More)
We derive general distribution tests based on the method of Maximum Entropy density. The proposed tests are derived from maximizing the differential entropy subject to moment constraints. By exploiting the equivalence between the Maximum Entropy and Maximum Likelihood estimates of the general exponential family, we can use the conventional Likelihood Ratio,(More)
We develop a GMM estimator for the distribution of a variable where summary statistics are available only for intervals of the random variable. Without individual data, one cannot calculate the weighting matrix for the GMM estimator. Instead, we propose a simulated weighting matrix based on a first-step consistent estimate. When the functional form of the(More)
BACKGROUND Biofilms affect >80% bacterial infections in human and are usually difficult to eradicate because of their inherent drug resistance. METHODS We investigated the effectiveness of antimicrobial blue light (aBL) (wavelength, 415 nm) for inactivating Acinetobacter baumannii or Pseudomonas aeruginosa biofilms in 96-well microplates or infected mouse(More)