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.

Accounting for the dead in the longitudinal analysis of income-related health inequalities

This paper develops an accounting framework to consider the effect of deaths on the longitudinal analysis of income-related health inequalities. Ignoring deaths or using inverse probability weights (IPWs) to re-weight the sample for mortality-related attrition can produce misleading results, since to do so would be to disregard the most extreme of all health outcomes. Incorporating deaths into the longitudinal analysis of income-related health inequalities provides a more complete picture in terms of the evaluation of health changes in respect to socioeconomic status. We illustrate our work by investigating health mobility in Quality Adjusted Life Years (QALYs) as measured by the SF6D from 1999 till 2004 using the British Household Panel Survey (BHPS). We show that for Scottish males explicitly accounting for the dead, rather than using IPWs to account for mortality-related attrition, changes the direction of the relationship between relative health changes and initial income position, while for other population groups it increases the strength of this relationship by up to 14 times. When deaths are explicitly incorporated into the analysis it is found that over this five year period for both Scotland and England & Wales the relative health changes were significantly regressive such that the poor experienced a larger share of the health losses relative to their initial share of health and a large amount of this was related to mortality.

On decomposing the causes of changes in income-related health inequality with longitudinal data

Regression-based decomposition procedures are used to both standardise the concentration index and to determine the contribution of inequalities in the individual health determinants to the overall value of the index. The main contribution of this paper is to develop analogous procedures to decompose the income-related health mobility and health-related income mobility indices first proposed in Allanson, Gerdtham and Petrie (2010) and subsequently extended in Petrie, Allanson and Gerdtham (2010) to account for deaths. The application of the procedures is illustrated by an empirical study that uses British Household Panel Survey (BHPS) data to analyse the performance of Scotland in tackling income-related health inequalities relative to England & Wales over the five year period 1999 to 2004.

Handling the endogeneity of income to health using a field experiment in Taiwan

This paper uses an exogenous increase in income for a specific sub-group in Taiwan to explore the extent to which higher income leads to higher levels of health and wellbeing. In 1995, the Taiwanese government implemented the Senior Farmer Welfare Benefit Interim Regulation (SFWBIR) which was a pure cash injection, approximately US$110 (£70) per month in 1996, to senior farmers. A Difference-in-differences (DiD) approach is used on survey data from the Taiwanese Health and Living Status of Elderly in 1989 and 1996 to evaluate the short term effect of the SFWBIR on self-assessed health, depression, and life satisfaction. Senior manufacturing workers are employed as a comparison group for the senior farmers in the natural experiment because their demographic backgrounds are similar. This paper provides evidence that the increase in income from the SFWBIR significantly improved the mental health of senior farmers by reducing the scale of depression (CES-D) by 1.718, however, it had no significant short term impact on self-assessed health or life satisfaction.

Understanding the vertical equity judgements underpinning health inequality measures

The choice of income-related health inequality measures in comparative studies is often determined by custom and analytical concerns, without much explicit consideration of the vertical equity judgements underlying alternative measures. This note employs an inequality map to illustrate how it these judgements that affect the ranking of populations by health inequality. In particular, it is shown that relative indices of inequality in health attainments and shortfalls embody distinct vertical equity judgments, where each may represent ethically defensible positions in specific contexts. Further research is needed to explore people’s preferences over distributions of income and health.

When to Quit Under Uncertainty? A real options approach to smoking cessation

This paper models the decision to quit smoking like an investment decision where the quitter incurs a sunk withdrawal cost today and forgoes their consumer surplus from cigarettes (invests) and hopes to reap an uncertain reward of better health and therefore higher utility in the future (return). We show that a risk-averse mature smoker who expects to benefit from quitting may still rationally choose to delay quitting until they are more confident that quitting is the right decision for them. Such a decision by the smoker is due to the value associated with keeping their option of whether or not to quit open as they learn more about the damage that smoking will have on their future utility. Policies which reduce a smoker’s uncertainty about the damage that smoking with have on their future utility is likely to make them quit earlier.

Expectations Traps and Coordination Failures with Discretionary Policymaking

Discretionary policymakers cannot manage private-sector expectations and cannot coordinate the actions of future policymakers. As a consequence, expectations traps and coordination failures can occur and multiple equilibria can arise. To utilize the explanatory power of models with multiple equilibria it is first necessary to understand how an economy arrives to a particular equilibrium. In this paper we employ notions of learnability and self-enforceability to motivate and identify equilibria of particular interest. Central among these criteria are whether the equilibrium is learnable by private agents and jointly learnable by private agents and the policymaker. We use two New Keynesian policy models to identify the strategic interactions that give rise to multiple equilibria and to illustrate our methods for identifying equilibria of interest. Importantly, unless the Pareto-preferred equilibrium is learnable by private agents, we find little reason to expect coordination on that equilibrium.

Imperfect Credibility and Robust Monetary Policy

This paper studies the behavior of a central bank that seeks to conduct policy optimally while having imperfect credibility and harboring doubts about its model. Taking the Smets-Wouters model as the central bank.s approximating model, the paper's main findings are as follows. First, a central bank.s credibility can have large consequences for how policy responds to shocks. Second, central banks that have low credibility can bene.t from a desire for robustness because this desire motivates the central bank to follow through on policy announcements that would otherwise not be time-consistent. Third, even relatively small departures from perfect credibility can produce important declines in policy performance. Finally, as a technical contribution, the paper develops a numerical procedure to solve the decision-problem facing an imperfectly credible policymaker that seeks robustness.

Asset Prices, Business Cycles, and Markov-Perfect Fiscal Policy when Agents are Risk-Sensitive

We study a business cycle model in which a benevolent fiscal authority must determine the optimal provision of government services, while lacking credibility, lump-sum taxes, and the ability to bond finance deficits. Households and the fiscal authority have risk sensitive preferences. We find that outcomes are affected importantly by the household's risk sensitivity, but not by the fiscal authority's. Further, while household risk-sensitivity induces a strong precautionary saving motive, which raises capital and lowers the return on assets, its effects on fluctuations and the business cycle are generally small, although more pronounced for negative shocks. Holding the stochastic steady state constant, increases in household risk-sensitivity lower the risk-free rate and raise the return on equity, increasing the equity premium. Finally, although risk-sensitivity has little effect on the provision of government services, it does cause the fiscal authority to lower the income tax rate. An additional contribution of this paper is to present a method for computing Markov-perfect equilibria in models where private agents and the government are risk-sensitive decisionmakers.

Computing Markov-Perfect Optimal Policies in Business-Cycle Models

Time-inconsistency is an essential feature of many policy problems (Kydland and Prescott, 1977). This paper presents and compares three methods for computing Markov-perfect optimal policies in stochastic nonlinear business cycle models. The methods considered include value function iteration, generalized Euler-equations, and parameterized shadow prices. In the context of a business cycle model in which a scal authority chooses government spending and income taxation optimally, while lacking the ability to commit, we show that the solutions obtained using value function iteration and generalized Euler equations are somewhat more accurate than that obtained using parameterized shadow prices. Among these three methods, we show that value function iteration can be applied easily, even to environments that include a risk-sensitive scal authority and/or inequality constraints on government spending. We show that the risk-sensitive scal authority lowers government spending and income-taxation, reducing the disincentive households face to accumulate wealth.

The Optimal Degree of Monetary-Discretion in a New Keynesian Model with Private Information

This paper considers the optimal degree of discretion in monetary policy when the central bank conducts policy based on its private information about the state of the economy and is unable to commit. Society seeks to maximize social welfare by imposing restrictions on the central bank's actions over time, and the central bank takes these restrictions and the New Keynesian Phillips curve as constraints. By solving a dynamic mechanism design problem we find that it is optimal to grant "constrained discretion" to the central bank by imposing both upper and lower bounds on permissible inflation, and that these bounds must be set in a history-dependent way. The optimal degree of discretion varies over time with the severity of the time-inconsistency problem, and, although no discretion is optimal when the time-inconsistency problem is very severe, our numerical experiment suggests that no-discretion is a transient phenomenon, and that some discretion is granted eventually.

Estimation of dynamic latent variable models using simulated nonparametric moments

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Because conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. It is shown that as the number of simulations diverges, the estimator is consistent and a higher-order expansion reveals the stochastic difference between the infeasible GMM estimator based on the same moment conditions and the simulated version. In particular, we show how to adjust standard errors to account for the simulations. Monte Carlo results show how the estimator may be applied to a range of dynamic latent variable (DLV) models, and that it performs well in comparison to several other estimators that have been proposed for DLV models.

SNM Guide

This is a guide that explains how to use software that implements the simulated nonparametric moments (SNM) estimator proposed by Creel and Kristensen (2009). The guide shows how results of that paper may easily be replicated, and explains how to install and use the software for estimation of simulable econometric models.

Aspects of immunity for the AMA-1 family of molecules in humans and non-human primates malarias

The apical membrane antigen (AMA-1) family of malaria merozoite proteins is characterised by a high degree of inter-species conservation. Evidence that the protein (PK66/AMA-1) from the simian parasite Plasmodium knowlesi was protective in rhesus monkeys suggested that the 83kDa P. falciparum equivalent (PF83/AMA-1) should be investigated for protective effects in humans. Here we briefly review pertinent comparative data, and describe the use of an eukaryotic full length recombinant PF83/AMA-1 molecule to develop a sensitive ELISA for the determination of serological responses in endemic populations. The assay has revealed surprisingly high levels of humoral response to this quantitatively minor antigen. We also show that PK66/AMA-1 inhibitory mAb's are active against merozoites subsequent to release from schizont-infected red cells, further implicating AMA-1 molecules in red cell invasion.

Indirect likelihood inference

Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Zn. We call this the maximum indirect likelihood (MIL) estimator. We also propose a computationally tractable Bayesian version of the estimator which we refer to as a Bayesian Indirect Likelihood (BIL) estimator. In most cases, the density of the statistic will be of unknown form, and we develop simulated versions of the MIL and BIL estimators. We show that the indirect likelihood estimators are consistent and asymptotically normally distributed, with the same asymptotic variance as that of the corresponding efficient two-step GMM estimator based on the same statistic. However, our likelihood-based estimators, by taking into account the full finite-sample distribution of the statistic, are higher order efficient relative to GMM-type estimators. Furthermore, in many cases they enjoy a bias reduction property similar to that of the indirect inference estimator. Monte Carlo results for a number of applications including dynamic and nonlinear panel data models, a structural auction model and two DSGE models show that the proposed estimators indeed have attractive finite sample properties.