ESTIMATION OF A DISTRIBUTION FUNCTION DOMINATING STOCHASTICALLY A KNOWN DISTRIBUTION FUNCTION

This paper considers the problem of estimating a cumulative distribution function (cdf), when it is known a priori to dominate a known cdf. The estimator considered is obtained by adjusting the empirical cdf using the prior information. This adjusted estimator is shown to be consistent, its limiting distribution is found, and its mean squared error (MSE) is shown to be smaller than the MSE of the empirical cdf. Its asymptotic efficiency (compared to the empirical cdf) is also found.     

New Evidence on the Urbanization of Global Poverty

One‐quarter of the world's consumption poor live in urban areas, and that proportion has been rising over time. Over 1993–2002, the count of the “$1 a day” poor fell by 150 million in rural areas but rose by 50 million in urban areas. The poor have been urbanizing even more rapidly than the population as a whole. By fostering economic growth, urbanization helped reduce absolute poverty in the aggregate. There are marked regional differences: Latin America has the most urbanized poverty problem, East Asia has the least; there has been a “ruralization” of poverty in Eastern Europe and Central Asia; in marked contrast to other regions, Africa's urbanization process has not been associated with falling overall poverty.     

BAYESIAN MODELS FOR NEW PRODUCT PRICING

This paper develops an information decision system for new product pricing based on Bayesian updating of prior estimates of demand distribution parameter values and on optimization by dynamic programming. The model considers the interaction of production and pricing decisions and emphasizes the simultaneous making of both decisions. After presentation of the basic model, approximate techniques are introduced which obtain most of the benefit of the approach while requiring only a fraction of the computer cost and input data. Numerical examples using growing demand and price sensitivity are given to demonstrate the high computer cost of the first model and the relative performance (on a profit basis) of the approximate techniques.