Measuring Avoidable Health Inequality with Realization of Conditional Potential Life Years (RCPLY)

In a series of papers (Tang, Chin and Rao, 2008; and Tang, Petrie and Rao 2006 & 2007), we have tried to improve on a mortality-based health status indicator, namely age-at-death (AAD), and its associated health inequality indicators that measure the distribution of AAD. The main contribution of these papers is to propose a frontier method to separate avoidable and unavoidable mortality risks. This has facilitated the development of a new indicator of health status, namely the Realization of Potential Life Years (RePLY). The RePLY measure is based on the concept of a “frontier country” that, by construction, has the lowest mortality risks for each age-sex group amongst all countries. The mortality rates of the frontier country are used as a proxy for the unavoidable mortality rates, and the residual between the observed mortality rates and the unavoidable mortality rates are considered as avoidable morality rates. In this approach, however, countries at different levels of development are benchmarked against the same frontier country without considering their heterogeneity. The main objective of the current paper is to control for national resources in estimating (conditional) unavoidable and avoidable mortality risks for individual countries. This allows us to construct a new indicator of health status – Realization of Conditional Potential Life Years (RCPLY). The paper presents empirical results from a dataset of life tables for 167 countries from the year 2000, compiled and updated by the World Health Organization. Measures of national average health status and health inequality based on RePLY and RCPLY are presented and compared.

Self-Fulfilling Price Cycles

This paper presents a model of a self-fulfilling price cycle in an asset market. Price oscillates deterministically even though the underlying environment is stationary. The mechanism that we uncover is driven by endogenous variation in the investment horizons of the different market participants, informed and uninformed. On even days, the price is high; on odd days it is low. On even days, informed traders are willing to jettison their good assets, knowing that they can buy them back the next day, when the price is low. The anticipated drop in price more than offsets any potential loss in dividend. Because of these asset sales, the informed build up their cash holdings. Understanding that the market is flooded with good assets, the uninformed traders are willing to pay a high price. But their investment horizon is longer than that of the informed traders: their intention is to hold the assets they purchase, not to resell. On odd days, the price is low because the uninformed recognise that the informed are using their cash holdings to cherry-pick good assets from the market. Now the uninformed, like the informed, are investing short-term. Rather than buy-and-hold as they do with assets purchased on even days, on odd days the uninformed are buying to sell. Notice that, at the root of the model, there lies a credit constraint. Although the informed are flush with cash on odd days, they are not deep pockets. On each cherry that they pick out of the market, they earn a high return: buying cheap, selling dear. However they don't have enough cash to strip the market of cherries and thereby bid the price up.