The Balance Sheets of Low-Income Households: What We Know about Their Assets and Liabilities. Data Sources Used in the Literature


Researchers have used the following major household surveys to examine the distribution and accumulation of wealth across the population. The Survey of Consumer Finances (SCF) examines a cross-section of the population in each year (or similar time frame) they are fielded  meaning that one cannot match up households between one year of the survey and another. The Survey of Income and Program Participation (SIPP), Panel Study on Income Dynamics (PSID), and the National Longitudinal Surveys (NLS) are longitudinal in nature, tracking a set of households over time. The SCF is the most widely used survey in the general literature on asset holdings, although the literature that focuses on old-age and retirement and specific cohorts  groups born or retiring in a certain range of years  often relies on the Health and Retirement Survey (HRS). Additionally, sources like the National Income and Product Accounts (NIPA), maintained by the Bureau of Economic Analysis, and the Federal Reserves Flow of Funds data provide economy-wide totals for broad classes of assets and debts  a balance sheet by economic sector.

The SCF, PSID, SIPP and HRS have varying definitions of the units that are interviewed for each survey. While the words household and family can be used relatively interchangeably, each survey (and the research based on the surveys) has a different set of rules that defines a household or family. These definitions are clarified below.

Survey of Consumer Finances. In the SCF, a household unit is divided into a primary economic unit (PEU)  the family  and everyone else in the household. The PEU is intended to be the economically dominant single individual or couple (whether married or living together as partners) and all other persons in the household who are financially interdependent with that person or those persons (Bucks et al. 2006).

Panel Study of Income Dynamics. In the PSID, the main observational unit is the family unit. The family unit is defined as a group of people living together, who are usually related by blood, marriage or adoption. Unrelated persons can be part of a family unit if they are permanently living together and share both income and expenses. The PSID also creates a household unit, defined as the physical boundary, such as a house or apartment, where members of the PSID family unit reside. Not everyone living in a household unit is automatically part of the family unit (University of Michigan 2005). The PSID studies (such as Caner and Wolff 2004) in this report base their data on the family unit, although they often describe the family unit as a household.

Survey of Income and Program Participation. In the SIPP, a housing unit is defined as a living quarters with its own entrance and cooking facilities. The people living in a housing unit constitute a household. However, SIPP does not treat the household as a continuous unit to be followed in the panel. SIPP is a person-based survey; SIPP follows original sample members regardless of household composition. A house, an apartment or other group of rooms, or a single room is regarded as a housing unit if it is occupied or intended for occupancy as separate living quarters. That is, the occupants do not live and eat with any other persons in the structure and there is direct access from the outside or through a common hall. A group of friends sharing an apartment constitutes a household. Noninstitutional group quarters, such as rooming and boarding houses, college dormitories, convents, and monasteries, are classified as group quarters rather than households (U.S. Census Bureau 2001).

Health and Retirement Study. The HRS observational unit is an eligible household financial unit. The HRS household financial unit must include at least one age-eligible member from the 19311941 birth year cohorts: (1) a single unmarried age-eligible person; (2) a married couple in which both persons are age eligible; or (3) a married couple in which only one spouse is age eligible. For most HRS-eligible units, the term household can be used interchangeably with the more precise household financial unit. However, some households may contain multiple household financial units. If a sample housing unit contains more than one unrelated age-eligible person (i.e., financial unit), one of these persons is randomly selected as the financial unit to be observed. If an age-eligible person has a spouse, the spouse is automatically selected for the HRS even if he or she is not age-eligible (Heeringa and Connor 1995).

While household or family surveys tend to be the major source of empirical evidence on holdings of assets, liabilities, and net worth in the population, a variety of other empirical data sources do exist. These sources include demonstration projects, such as the American Dream Demonstration (ADD), or administrative data sets, such as the Home Mortgage Disclosure Act Data (HMDA). Researchers also rely on microsimulation models as secondary data sources. These models draw on one or more surveys to amalgamate data on assets, debts, and income, impute assets and debts to households for which these data are missing, and calculate additional sources of wealth such as defined-benefit pensions or government benefits like Social Security. Microsimulation examples include the Urban Institutes DYNASIM model or the Social Security Administrations POLISIM model.

Some assets, such as Social Security and Medicare wealth, defined-benefit pension wealth, life and health insurance, are difficult to measure for estimation reasons, but tend to dominate the other assets held by a household, along with housing. How these additional forms of wealth are measured, or in regard to Social Security, even whether they are measured, varies across surveys and studies. Estimates of the value of Social Security or pension wealth at a particular age depend on forecasts of life expectancy, labor force tenure, tenure at a particular job (for pensions), the career pattern of earnings, a spouses average career earnings (for Social Security), marital status, future economic assumptions (e.g., wage growth, inflation, and interest rates), and unforeseen changes in pension plan rules or the Social Security benefit formula. Estimates of life insurance and health insurance are also complicated by assumptions about health status, heredity, and lifestyle choices.

An equally important concern, addressed more rigorously in the first report in the Poor Finances series, Assets, Poverty, and Public Policy: Challenges in Definition and Measurement is what constitutes an asset. By nature of having little or sporadic income, poorer families tend to own less in the way of typical assets (financial assets or homes) and depend more on durables like vehicles, furniture, appliances, or equipment. While vehicles are often identified as an asset on national surveys, few data sources capture ownership of other durables  aside from antiques, jewelry, collections, and artwork. Moreover, as with Social Security and pensions, these assets may be difficult to value, although for different reasons. Durables such as cars depreciate, can be superseded by better products, and often cannot be sold (wholesale) for the price that they were purchased (retail). Yet without durables, no household could function, and for low-income households, acquiring a car or a computer with internet services may be crucial for economic advancement and a necessary pre-cursor to acquiring additional assets like bank accounts, pensions, or homes. As this report depends in large part on national household surveys for the portraits of assets and debt holdings, we can say little about holdings of durable goods other than vehicles.

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