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Notes for Appendix D
1. Prepared by John Sheils, Lewin/ICF, Inc.
2. A detailed description of the model is provided
in: Lewin/ICF, "The Health Benefits Simulation Model (HBSM), Technical Documentation," submitted to the Office of Research, Health Care Financing Administration, April 13, 1990.
-J.F. Long and F.A. Scott, "The Income Tax and Nonwage Compensation,” Review of Economics and Statistics, 64(2) 1982:211-219. -A. Taylor and G. Wilensky, “The Effect of Tax Policies on Expenditures for Private Insurance,” in Jack Meyer (ed.) Market Reforms in Health Care (Washington, D.C., American Enterprise Institute, 1983), 163-184. -M. Holmer, "Tax Policy and the Demand for Health Insurance,” Journal of Health Economics, 3 (3) 1984:203-221. -F. Sloan and K. Adamche, “Taxation and the Growth of Nonwage Compensation,” Public Finance Quarterly, 14 (2) April 1986:115-137.
3. Net actuarial value refers to the actuarial value
of the plan's benefits multiplied by the proportion of the plan premium cost paid by the employer.
4. Articles on this topic include:
-Charles E. Phelps, Demand for Health Insurance: A Theoretical and Empirical Investigation (Santa Monica, Calif.: RAND, 1973).
5. Estimates provided by Kenneth Thorpe of the
Harvard School of Public Health. See Thorpe et al., “Including the Poor: The Fiscal Impacts of Medicaid Expansion.” Journal of the American Medical Association 261 (1989): 1003-1007.
Assumptions Used to Estimate Costs for Long-Term Care Recommendations
Estimates of the costs of the long-term care program proposed by the Pepper Commission were made using the Brookings/ICF Long-Term Care Financing Model." This appendix discusses the methodology used in estimating the costs of the proposed program. The first section presents an overview of the model structure, the databases used in the model, and the model's underlying logic. The key relationships and behavioral parameters of the model are then discussed. The final section explains the implementation of the Commission's proposal within the model's framework.
on future public and private expenditures for nursing home and home care. The model can be used to simulate long-term care financing assuming changes in pri
methods (such as increased purchase of private long-term care insurance) or new public financing programs. These simulations are greatly affected by the choice of assumptions about the economy (such as the rate of growth of the overall economy and nursing home prices) and individual behavior (such as rates of nursing home utilization and insurance purchase). Because of the uncertainty surrounding some of these events, the model is designed to facilitate use of alternative assumptions to show how sensitive the results are to the assumptions chosen.
OVERVIEW OF THE MODEL
The Brookings/ICF Long-Term Care Financing Model simulates the utilization and financing of both institutional and noninstitutional long-term care services for elderly families over the period 1986 to 2020. Institutional services include nursing home care provided by skilled nursing facilities (SNFs) and intermediate care facilities (ICFs). Noninstitutional services include home health, homemaker, personal care, and meal preparation services. The model simulates the number of individuals receiving these services and the costs of these services as financed by various public and private sources.
The key advantage of this model over actuarial models is its ability to simulate the effects of various policy options on the distribution of benefits for different economic and demographic groups. For example, the model can be used to generate estimates of the effects of proposals on demographic groups, such as low-income unmarried women age 85 and over, who have few assets.
The model was jointly developed by The Brookings Institution and Lewin/ICF in 1986. Significant funding for the components of the model was received from the U.S. Department of Labor, the President's Commission on Pension Policy, the American Council of Life Insurance, the Employee Benefits Research Institute, the Congressional Budget Office, and the assistant secretary for planning and evaluation of the U.S. Department of Health and Human Services. Lewin/ICF and The Brookings Institution staff made major revisions to the model in 1989 with the support and guidance of the assistant secretary for planning and evaluation, U.S. Department of Health and Human Services, and the Robert Wood Johnson Foundation,
The model begins with a nationally representative sample of the adult population with a record for each person's age, sex, income, and other characteristics assembled from the sources described below. The model simulates life events for each individual in the sample population from 1986 to 2020, using a Monte Carlo simulation methodology. The model first simulates future demographic characteristics, labor force participation, and income and assets of the elderly. It then simulates disability, admission to and use of nursing home and home care, and methods of financing long-term care services. The model uses national data and does not take into account regional, state, or local variations.
The current version of the model is a major revision of the model that was developed jointly by Lewin/ICF and The Brookings Institution in 1986. The model was revised in 1988-89 to incorporate data from a number of newly available data sources, including the 1982-84 National Long-Term Care Survey (NLTCS), the 1985 National Nursing Home
The objective of the model is to simulate the effects of various financing and organizational reform options
Simulate Utilization of LTC Services o Institutional services o Noninstitutional services
Simulate Sources and Levels of Payment
o Eligibility for public programs o Program rules o Eligibility for private programs
The model then simulates demographic events such as mortality, marital status, labor force activity, income, and assets for each individual. The probabilities of the likelihood of marriage, work, and so forth for different demographic groups were estimated from matched CPS files and other sources. The aggregate probabilities of mortality are taken from Social Security Administration estimates. The macroeconomic assumptions underlying the simulations are generally those used in Alternative II-B of the 1989 Social Security Trustee's Report. These assumptions about future economic growth, inflation, unemployment, and wages greatly influence the model's results. These economic assumptions were selected in part because they are consistent with the demographic probabilities used in the model. Based on these assumptions, the model estimates retirement income from private sector defined benefit pension plans, public pension plans, social security, private sector defined contribution plans, Individual Retirement Accounts (IRAs), and Keoghs. The model also simulates the assets of elderly individuals, including the value of home equity, from the 1984 Panel of the Survey of Income and Program Participation (SIPP).
Analysis Tabulations o Public, private expenditures for LTC o Nursing home, home care utilization
Utilization of Long-Term Care Services
Disability of the Elderly
Using probabilities estimated from the 1982-84 NLTCS and the 1985 NNHS, this part of the model simulates the level of disability for persons age 65 and over. The model simulates the onset of disability, the level of disability, changes in disability, and recovery from disability.
This part of the model uses probabilities estimated from the 1982-84 NLTCS and the 1985 NNHS to simulate admission to and length of stay in a nursing home. For noninstitutionalized persons, the model also simulates the use and length of receipt of paid home care services using probabilities derived primarily from the 1982-84 NLTCS and Medicare program data. Many policy changes can affect the utilization of services. Changes in the utilization of services resulting from changes in delivery or financing of longterm care are implemented in this module.
Sources and Levels of Payment
The fifth component of the model simulates the sources of payment and the level of expenditures for each individual receiving institutional or noninstitutional long-term care services. The model incorporates current Medicare eligibility and coverage provisions (post-Medicare Catastrophic Coverage Act provisions) and a set of uniform assumptions about the Medicaid program, including spousal impoverishment protection. State Medicaid program variations are not modeled. Altering the characteristics of existing programs or adding new programs to this component of the model permits analysis of the impact of policy options on the financing of care and the economic impact of policy changes on various demographic groups.
uals use nursing homes less in the future, it may result in declines in aggregate long-term care
expenditures. • Nursing home and home care prices, which affect
not only expenditures but also utilization. Whether prices will continue to increase faster than the consumer price index (CPI) as they have in recent years will have a large effect on the ability of individuals to pay privately for longterm care.
This section discusses how these key factors and relationships were modeled and how these analyses have been incorporated into the model.
Future Retirement Income and Assets
Aggregate Expenditures and Utilization
The sixth part of the model accumulates Medicare, Medicaid, private expenditures, and utilization for each simulated individual for each year. The final output file from the model provides detailed information for individuals age 65 and older, for each year from 1986 to 2020, on individuals' age, sex, marital status, disability, sources and amounts of income, assets, and use of and payment sources for nursing home and home care services. This file is tabulated to show aggregate long-term care expenditures for various demographic groups and sources of financing.
Approximately one-half of all long-term care expenditures for the elderly are accounted for by out-ofpocket payments made by the elderly. Because of the heavy reliance on out-of-pocket payments, understanding the level and distribution of the income and assets of the elderly is extremely important to understanding the ability of the elderly to pay for long-term care and the degree to which they must rely on public programs.
Retirement Income-In recent years the average income of the elderly has increased, and poverty rates for the elderly have declined. Much of these increases in income have stemmed from higher social security payments and the expanded role of employer pensions. In the future, the level of retirement income will depend on a number of key factors, including preretirement earnings histories of workers, the age of retirement, and the level of pension coverage.
SPECIFICATION OF KEY MODEL RELATIONSHIPS
Under current policy, four key factors and relationships have the largest influence on the level and distribution of long-term care expenditures over the 1986 to 2020 period. These four factors are:
• Income and assets of the elderly, which in
fluence whether individuals are able to pay privately for long-term care or must rely on Medicaid. In general, if income and assets increase faster than prices, the ability of the elderly
to pay privately will increase. • The level and severity of disability, which
determines the size of the disabled population and the average number of years of disability prior to death. Whether disability rates will decrease as mortality rates decline will have a large impact
on future long-term care expenditures. • The likelihood of nursing home entry, which in
fluences long-term care expenditures. If individ
The model simulates benefits from social security, private and public employee retirement plans, IRAs, earnings, asset income, and Supplemental Security Income (SSI) program benefits. Pension and social security benefits are simulated based on the simulated work history of an individual. Each time a worker is simulated to enter a pension-covered job, he or she is assigned to an actual pension plan sponsor selected from a representative sample of private and public retirement plan sponsors. If the individual becomes eligible for a pension benefit, the model then calculates the individual's benefit using the plan's actual benefit provisions.
The individual labor supply probabilities in the model are linked to aggregate estimates of employment levels and industry composition. The aggregate levels are based on Bureau of Labor Statistics fore