Information-Theoretic Distribution Test with Application to Normality

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, Wald and Lagrange Multiplier testing principles in the maximum entropy framework. In particular, we use the Lagrange Multiplier method to derive tests for normality and their asymptotic properties. Monte Carlo evidence suggests that the proposed tests have desirable small sample properties and often outperform commonly used tests such as the Jarque-Bera test and the Komogorov-Smirnov-Lillie test for normality. We show that the proposed tests can be extended to tests based on regression residuals and non-iid data in a straightforward manner. We apply the proposed tests to the residuals from a stochastic production frontier model and reject the normality hypothesis.

Partially Adaptive Estimation via Maximum Entropy Densities

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 estimators do not involve choosing a bandwidth or trimming, and only require estimating a small number of nuisance parameters, which is desirable when the sample size is small. Monte Carlo simulations suggest that the proposed estimators fare well with non-normal error distributions. When the errors are normal, the efficiency loss due to redundant nuisance parameters is negligible as the proposed error densities nest the normal. The proposed partially adaptive estimator compares favorably with existing methods, especially when the sample size is small. We apply the estimator to a bio-pharmaceutical example and a stochastic frontier model.

China's Income Distribution and Inequality

We use a new method to estimate China’s income distributions based on 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 trends in traditional welfare indices such as the Gini. We find that inequality has increased substantially in both rural and urban areas. Using an inter-temporal decomposition of aggregate inequality, we determine that increases in inequality within the rural and urban sectors and the growing gap in rural and urban incomes have been equally responsible for the growth in overall inequality over the last two decades. However, the rural-urban income gap has played an increasingly important role in recent years. In contrast, only the growth of inequality within rural and urban areas is responsible for the increase in inequality in the United States, where the overall inequality is close to that of China. As a robustness check, we show that consumption inequality (which may be a proxy for permanent income inequality) in urban areas also rose considerablyincome distribution, inequality, maximum entropy

CHINA'S INCOME DISTRIBUTION OVER TIME: REASONS FOR RISING INEQUALITY

We estimate China's rural, urban and overall income distributions using grouped data from 1985-2001. We show how the distributions evolve as well as examine trends in welfare indices. We find the growing rural-urban income gap and increases in inequality within either sector have been equally responsible for overall inequality growth.Consumer/Household Economics,

The Global Joint Distribution of Income and Health

We investigate the evolution of global welfare in two dimensions: income per capita and life expectancy. First, we estimate the marginal distributions of income and life expectancy separately. More importantly, in contrast to previous univariate approaches, we consider income and life expectancy jointly and estimate their bivariate global distribution for 137 countries during 1970 - 2000. We reach several conclusions: the global joint distribution has evolved from a bimodal into a unimodal one, the evolution of the health distribution has preceded that of income, global inequality and poverty has decreased over time and the evolution of the global distribution has been welfare improving. Our decomposition of overall welfare indicates that global inequality would be underestimated if within-country inequality is not taken into account. Moreover, global inequality and poverty would be substantially underestimated if the dependence between the income and health distributions is ignored.income, health, global distribution, inequality, poverty

The Global Joint Distribution of Income and Health

We investigate the evolution of global welfare in two dimensions: income per capita and life expectancy. First, we estimate the marginal distributions of income and life expectancy separately. More importantly, in contrast to previous univariate approaches, we consider income and life expectancy jointly and estimate their bivariate global distribution for 137 countries during 1970 - 2000. We reach several conclusions: the global joint distribution has evolved from a bimodal into a unimodal one, the evolution of the health distribution has preceded that of income, global inequality and poverty has decreased over time and the evolution of the global distribution has been welfare improving. Our decomposition of overall welfare indicates that global inequality would be underestimated if within-country inequality is not taken into account. Moreover, global inequality and poverty would be substantially underestimated if the dependence between the income and health distributions is ignored.Income; Health; Global Distribution; Inequality; Poverty

Risk Perception and Altruistic Averting Behavior: Removing Arsenic in Drinking Water

Self protection and altruism are crucial behavioral factors in determining the effectiveness of public policies aimed to improve human health from environmental hazards. This paper examined people’s arsenic mortality risk perception in the drinking water for themselves and their children using the Bayesian learning framework. A two-stage structural model within the random utility framework was developed to model the household’s risk averting behavior with respect to arsenic-related mortality risk. The empirical results indicate that parents engage in a form of mixed altruism. Parents are willing to spend more to make a trade-off between their risk and their children’s risk.Resource /Energy Economics and Policy, Risk and Uncertainty,

Micro-Demand Systems Analysis of Non-Alcoholic Beverages in the United States: An Application of Econometric Techniques Dealing With Censoring

A censored Almost Ideal Demand System (AIDS) and a Quadratic Almost Ideal Demand System (QUAIDS) were estimated in modeling non-alcoholic beverages. Five estimation techniques were used, including the conventional Iterated Seemingly Unrelated Regression (ITSUR), two-stage methods such as the Heien and Wessells (1990) and the Shonkwiler and Yen (1999) approaches, the generalized maximum entropy method and the Amemiya-Tobin framework of Dong, Gould and Kaiser (2004). Our results based on various specifications and estimation techniques are quantitatively similar and indicate that price elasticity estimates have a greater variability in more highly censored non-alcoholic beverage items such as tea, coffee and bottled water as opposed to less censored non-alcoholic beverage items such as carbonated softdrinks, milk and fruit juices.Censored demand systems, AIDS, QUAIDS, Two-Step Methods, Generalized Maximum Entropy, Amemiya-Tobin Framework, Non-Alcoholic Beverages, Agribusiness, Consumer/Household Economics, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, C34, D12,

On the Use of Cheap Talk in New Product Valuation

This study reports on the potential use of “cheap talk†in hypothetical new product valuation research using a simple field experiment eliciting subjects' willingness to pay for a new product. While cheap talk has been used in the non-market valuation literature, its application in hypothetical new product valuation research is very limited.cheap talk