Estimating the Percentage of the US Population without Health Insurance: An Ecological Approach

Article excerpt

Abstract This ecological study identifies factors that affect the percentage of a state's population without health insurance. Even with the Medicaid program, over 15% of the US population is without health insurance and understanding reasons why people are uninsured is an important first step in remedying this problem. Results presented here indicate an income policy or a piecemeal approach to the problem will probably be unsuccessful.

Keywords Health insurance . Poverty . Uninsured

JEL 100

Introduction

The issue of health insurance coverage has increasingly captured the interest of scholars and policy makers. As argued in Dushi and Honig (2003, p. 252), at least part of this increased attention can be attributed to a noticeable decline in health insurance coverage over the last two decades. A decade ago, Cutler (1994, p. 20) observed, "About 15% of the population ... [is] uninsured." For the year 2003, Bharmal and Thomas (2005, p. 643) observe the number of uninsured reached 43.6 million or 17.3% of persons under the age of 65. Indeed, every sign indicates a continuing stubborn problem and any increase in the medically uninsured is alarming. Consequently states such as Massachusetts are enacting special programs to provide more medical insurance coverage.

This study seeks to identify key factors that determine geographic differentials in the percentage of the population without health insurance coverage. After developing a rudimentary framework involving factors associated with affordability and access to health insurance, this study empirically investigates, using state-level data, the impact of factors, such as the following: poverty or some measure of family income, average household size, the cost of medical care, unionization rates, the relative presence of small-sized firms, the percentage of the population age 65 and above, smoking behavior, and health status, in terms of tuberculosis or AIDS. Evidence is provided that poverty plays a central role in this persistent social problem. Problems of adverse selection by the insured and cherry-picking by the insurer may also be present. Because of the number of factors contributing to the percentage of the population without insurance a comprehensive, rather than a piecemeal, approach should be used to examine this problem.

Review of Recent Literature and Framework of Analysis

Rice (2002, p. 238) lists various characteristics associated with the insured and the uninsured in the U.S. Swartz (2003), Dushi and Honig (2003), Newhouse (1994), Frick and Bopp (2005), and Cebula (2006), among others, have used some of those characteristics to measure the impact of various attributes on the percentage without insurance. Each one of those analysis details some of the complexity in explaining why people are medically uninsured.

The framework adopted in this study focuses on the affordability and the access to health insurance as the context to explain the percentage of the population without any kind of health insurance (PCTWOUT), including health maintenance organization (HMO) coverage. The household is treated as a utility-maximizing decision making unit, with maximum utility pursued subject to real world constraints, including a broadly interpreted budget constraint. Utility-maximization for the household naturally reflects economic, demographic, health, and institutional dimensions and considerations.

Perhaps, the most fundamental economic consideration in obtaining health insurance is purchasing power. Many of the independent variables that follow relate to the affordability or availability of health insurance at work. Secondary reasons for not purchasing health insurance include adverse selection (health persons opting out) or cherry-picking (insurers marketing insurance to only healthy persons).

An economist might approach the number without health insurance by estimating the supply of and demand for health insurance and then subtracting the equilibrium quantity from the total population. …