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Tables:
This appendix provides a discussion of the data sources used in the assets and liabilities literature,[12] a detailed discussion of the methods and measures used in the assets and liabilities literature, and a summary of the approaches 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 Reserve’s 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 1931–1941 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 Institute’s DYNASIM model or the Social Security Administration’s 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 spouse’s 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.
This appendix reports in some detail on the different methods the current literature uses to measure assets, debts, and net worth, such as means and medians.
Means. If we are looking at the asset holdings of 100 households, then the mean is the average asset holding for all 100. If there were $1,000 in total assets spread across all 100 households, then $10 would be the mean asset holding.
Per capita assets, debts, or net worth. Per capita is just like the mean, but for individuals rather than households. In our sample of 100 households with $1,000 in assets total, if we knew that each household had four persons, then the amount of assets per capita would be $2.50.
Medians. For the same group of 100, we sort them in ascending (or descending) order of asset values. Since there is an even number of households, the median is the value midway between households 50 and 51 — meaning that fifty percent of the sample has assets holdings worth less than this median household and fifty percent has assets holdings worth more. When the total number is odd (for example, 99 households), the median is the middle value (household 50 of the 99). Note that the median value does not change even if we replace one of the households above the median with an extremely wealthy household, although the mean would change substantially.
Quintiles. Following the same principle as locating the median, here we divide the sample into equal fifths (20 households a piece), known as quintiles. The first or bottom quintile contains those households that have the least in asset holdings and the fifth or top quintile contains those that have the most. The median would fall in the middle of the third quintile. If we instead divided the sample into deciles or tenths, than each decile would contain ten households and the median would fall right between the fifth and the sixth decile. Alternatively, quartiles divide the distribution into fourths or 25 persons each in our example. The literature often uses quintiles of income or quintiles of net worth, but may refer to these quintiles as “income percentiles.”
Percentage of households holding an asset. This measure refers to the percentage of households within a defined group that hold a given asset with a positive value. Bank accounts are an exception, in that accounts with zero balances are included, the rationale being that while a respondent’s account may have been zero at the time of the survey, it was probably not at (or below) zero the entire month. Accounts that have negative balances are treated as drawing on a line of bank credit, which counts as a debt when the SCF totals up net worth.
Distribution of total assets, debts, or net worth. This measure is used when we want to know how much of an asset is concentrated in, say, each quintile of household income. In our example of 100 households, we might find that $1,000 in total assets is distributed as follows: $50 in the bottom quintile, $100 in the second quintile, $150 in the third quintile, $250 in the fourth quintile, and $450 in the top quintile.
Shares of assets, debts, or net worth. Based on the distribution in the preceding entry, suppose we then wanted to know what fraction or share of total assets was held by each quintile. We would simply divide the total asset amount of each quintile’s holdings by the total asset amount for the sample ($1,000) and arrive at the following shares: 5 percent for the first quintile, 10 percent for the second quintile, 15 percent for the third quintile, 25 percent for the fourth quintile, and 45 percent for the top quintile, summing to 100 percent.
Gini coefficients. The gini coefficient is a number between zero and one that is a measure of inequality. A gini of 0 indicates that an item like total assets, total debt, or total net worth is totally equally distributed — for example, in our sample 100 households, if total assets were $1,000, each household would have $10. A gini of 1 indicates that an item is maximally unequally distributed — for our example, the 100th household has all $1,000 of assets and the other 99 households have nothing. Wolff (2004) examines the concentration of national wealth in the 2001 SCF and calculates a gini of 0.826.
Asset poverty measures. In this report, we rely on the definition in Caner and Wolff (2004), though they calculate asset poverty in several different ways. A household is asset poor if its access to wealth is insufficient to allow the household to meet basic needs over a certain period of time. Caner and Wolff, acknowledging that these specifications are somewhat arbitrary, consider three measures of wealth — net worth, net worth minus home equity, and liquid wealth (the value of cash and other assets that can be easily converted to cash). They rely on poverty thresholds (which increase with family size) for their definition of basic needs.[13] And they define a “certain period of time” as three months. Therefore, for this report, the asset poverty line is defined as the amount of assets a household would need to have available to liquidate in order to live at the designated poverty line for three months.
Asset poverty gap ratio. This ratio measures the per-household amount of wealth that would be required to raise all asset poor households to the asset poverty line, calculated as a share of the asset poverty line. In other words, a household at 40 percent of the asset poverty line would have an asset poverty gap ratio of “60.00” which would mean that an additional 60 percent of the asset poverty line would be required to bring this household up to the line.
Debt ratios. These ratios can be expressed in many ways. One way is to simply divide a household’s debts by its assets — this debt-to-asset ratio is sometimes called the leverage ratio and shows how extended (or over-extended) a household may be. Another ratio, which we call the debt service ratio or debt-to-income ratio, divides the payments necessary to service household debt by household income.
Bankruptcy filings. This measure of household financial distress can be expressed in several ways, one of which is simply the number of bankruptcy filings per 1 million persons.
That income and wealth are tightly concentrated in a relatively few, high-income households argues for the use of medians over means, as medians are much less sensitive to outliers (Aizcorbe et al. 2003). Still, medians by themselves only reveal conditions for typical households and, for our purposes, would miss shining a spotlight on the possible distress felt by the bottom 50 percent. That is why it is important to combine medians (as well as means) with income classifiers like quintiles and deciles.
A related point is that means and medians must also be weighed against holding rates (the likelihood that a household would hold a particular asset or debt). Some calculations of means and medians include zeros — that is, households that do not hold an asset or debt — while other calculations do not. If means and medians exclude zeros, then a statement that “median business equity is $200,000” refers only to the sample of households that have business equity — if the vast majority of households, who do not hold any business equity, were included, the $200,000 figure would be much lower.
The gini coefficient is a relative measure of inequality. To give an extreme example, a gini coefficient calculated for the wealth holdings of the top 0.1 percent wealthiest individuals would show a lot of “inequality” as there are households with $1 million mixed in with households with $50 million or $100 million, even though none of these households are poor. Similarly, a gini coefficient calculated for a sample of households on welfare for some portion of the year where those earning $0 are mixed in with those earning $5,000 to $7,000, would indicate tremendous inequality, even though all the households are below the poverty level. Caner and Wolff (2004), as mentioned, present asset poverty measures, instead. Unlike gini coefficients, asset poverty is an absolute measure.
With regard to debt, higher debt-to-asset ratios may be more common for younger households that have just begun acquiring assets and have not had the time to build up sufficient equity. The clearest example of this would be a household that has just purchased a $150,000 home with a $5,000 down payment. While their $5,000 down payment represents their equity or asset value, they have $145,000 remaining in their mortgage, or debt. The debt service ratio may be more indicative of a household’s indebtedness. Also, the type of debt is important — debt that directly accompanies an asset (e.g., mortgage debt) is considered “secure” and is better to have than “unsecured” debt that is mainly used to finance current consumption rather than current savings (e.g., consumer credit card debt).
Some studies, such as Sullivan (2004), Carasso, Bell, Olsen, and Steuerle (2005), Bell, Carasso, and Steuerle (2005), and McKernan and Chen (2005), focus strictly on assets or a particular asset class such as vehicles, owner-occupied housing, pensions, or small businesses, respectively. The goal of these studies is to chart ownership: who in the population owns the asset, what is the average asset holding, what are the financial and demographic characteristics that correlate with ownership, and what are the barriers to owning or continuing to own. While assets are generally measured in dollar terms, the dominating criterion is an implicit asset holding triage — this type of study identifies a population of concern and offers an argument as to why a certain asset is vital (or not) for this population’s economic advancement. For example, Sullivan (2004) examines vehicle ownership among families receiving Temporary Assistance for Needy Families (TANF) cash benefits (welfare) — benefits that come with an asset test and may be curtailed or cut-off if recipients own assets above a certain value. He concludes that the asset test does empirically limit ownership of a vehicle.
Other studies do not consider an asset or debt category in isolation, but assemble an overall balance sheet for a survey sample, usually culminating in a calculation of net worth (assets minus debts). Aizcorbe, Kennickell and Moore (2003) and Bucks, Kennickell, and Moore (2006) present an array of tables that show net worth, assets by type, and debts by type, using the SCF. Badu, Daniels, and Salandro (1999), Caner and Wolff (2004), Lerman (2002), Lupton and Smith (1999), and Smith (1995) concentrate on net worth, but describe certain key asset and debt holdings like Social Security, homes, or mortgages by way of comparison, using a variety of surveys including the SCF, PSID, and HRS. Caner and Wolff go a step further and define their own measure, asset poverty, as an analog to income poverty and chart the numbers, frequency, and associated characteristics of households that are asset impoverished. These studies always provide mean and median measures of assets, debts, and net worth and the means and medians typically exclude zeroes (i.e., those households who do not hold a particular asset or debt or who have a zero balance).
Bucks et al. (2006), Smith (1995), and Lerman (2005), among others, also emphasize the percentage of households holding an asset or debt — although Bucks et al. (2006) are the most comprehensive in that they provide these “holding rates” for every asset class, by classifier. While Bucks et al. (2006) use a wide range of classifiers in their SCF wealth tables — income, age, education (in some cases), work status, race, and the like — they do not break out assets, debt, and net worth by marital status, although the data are readily available. Lupton and Smith (1999), Smith (1995), and Lerman (2005), however, do break out by marital status and find pronounced effects.
Kennickell (2003) and Wolff (2004) use gini coefficients, among other measures, to trace changes in the concentration of wealth over time. Wolff also includes tables showing the percentage of wealth by income class, which portrays the unequal distribution of wealth in a simpler way.
| Family characteristic | Any financial asset | Transaction accounts | Certificates of deposit | Savings bonds | Bonds | Stocks | Pooled investment funds | Retirement accounts | Cash value life insurance | Other managed assets | Other | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | |
| $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | ||||||||||||
| All Families | 93.8% | 23.0 | 91.3% | 3.8 | 12.7% | 15.0 | 17.6% | 1.0 | 1.8% | 65.0 | 20.7% | 15.0 | 15.0% | 40.4 | 49.7% | 35.2 | 45.0% | 6.0 | 7.3% | 45.0 | 10.0% | 4.0 |
| Age of head (years) | ||||||||||||||||||||||
| Less than 35 | 90.1% | 5.2 | 86.4% | 1.8 | 5.6% | 4.0 | 15.3% | 0.5 | * | * | 13.3% | 4.4 | 8.3% | 8.0 | 40.2% | 11.0 | 11.0% | 3.0 | 2.9% | 5.0 | 11.6% | 1.0 |
| 35-44 | 93.6% | 19.0 | 90.8% | 3.0 | 6.7% | 10.0 | 23.3% | 0.5 | 0.6% | 10.0 | 18.5% | 10.0 | 12.3% | 15.9 | 55.9% | 27.9 | 20.1% | 5.0 | 3.7% | 18.3 | 10.0% | 3.5 |
| 45-54 | 93.6% | 38.6 | 91.8% | 4.8 | 11.9% | 11.0 | 21.0% | 1.0 | 1.8% | 30.0 | 23.2% | 14.5 | 18.2% | 50.0 | 57.7% | 55.5 | 23.0% | 8.0 | 6.2% | 43.0 | 12.1% | 5.0 |
| 55-64 | 95.2% | 78.0 | 93.2% | 6.7 | 18.1% | 29.0 | 15.2% | 2.5 | 3.3% | 80.0 | 29.1% | 25.0 | 20.6% | 75.0 | 62.9% | 83.0 | 32.1% | 10.0 | 9.4% | 65.0 | 7.2% | 7.0 |
| 65-74 | 96.5% | 36.1 | 93.9% | 5.5 | 19.9% | 20.0 | 14.9% | 3.0 | 4.3% | 40.0 | 25.4% | 42.0 | 18.6% | 60.0 | 43.2% | 80.0 | 34.8% | 8.0 | 12.8% | 60.0 | 8.1% | 10.0 |
| 75 or more | 97.6% | 38.8 | 96.4% | 6.5 | 25.7% | 22.0 | 11.0% | 5.0 | 3.0% | 295.0 | 18.4% | 50.0 | 16.6% | 60.0 | 29.2% | 30.0 | 34.0% | 5.0 | 16.7% | 50.0 | 8.1% | 22.0 |
| Income percentile | ||||||||||||||||||||||
| Bottom quintile | 80.1% | 1.3 | 75.5% | 0.6 | 5.0% | 10.0 | 6.2% | 0.4 | * | * | 5.1% | 6.0 | 3.6% | 15.3 | 10.1% | 5.0 | 14.0% | 2.8 | 3.1% | 22.0 | 7.1% | 2.5 |
| Second quintile | 91.5% | 4.9 | 87.3% | 1.5 | 12.7% | 14.0 | 8.8% | 0.6 | * | * | 8.2% | 8.0 | 7.6% | 25.0 | 30.0% | 10.0 | 19.2% | 3.9 | 4.9% | 50.0 | 9.9% | 2.0 |
| Third quintile | 98.5% | 15.5 | 95.9% | 3.0 | 11.8% | 10.0 | 15.4% | 0.8 | * | * | 16.3% | 12.0 | 12.7% | 23.0 | 53.4% | 17.2 | 24.2% | 5.0 | 7.9% | 36.0 | 9.3% | 2.5 |
| Fourth quintile | 99.1% | 48.5 | 98.4% | 6.6 | 14.9% | 18.0 | 26.6% | 1.0 | 2.2% | 80.0 | 28.2% | 10.0 | 18.6% | 25.5 | 69.7% | 32.0 | 29.8% | 7.0 | 7.8% | 35.0 | 11.2% | 4.0 |
| Fifth quintile | 99.9% | 236.7 | 99.6% | 19.5 | 18.9% | 26.5 | 31.1% | 1.4 | 5.8% | 93.4 | 45.4% | 36.0 | 32.7% | 79.3 | 85.2% | 126.4 | 33.8% | 15.0 | 12.6% | 75.0 | 12.4% | 12.5 |
| 80-89.9% | 99.8% | 108.2 | 99.1% | 11.0 | 16.3% | 20.0 | 32.3% | 0.8 | 2.8% | 26.7 | 35.8% | 15.0 | 26.2% | 33.5 | 81.9% | 70.0 | 29.5% | 10.0 | 12.1% | 50.0 | 11.4% | 5.0 |
| 90-100% | 100.0% | 365.1 | 100.0% | 28.0 | 21.5% | 33.0 | 29.9% | 2.0 | 8.8% | 160.0 | 55.0% | 57.0 | 39.1% | 125.0 | 88.5% | 182.7 | 38.1% | 20.0 | 13.0% | 100.0 | 13.4% | 20.0 |
| Net worth percentile | ||||||||||||||||||||||
| Less than 25% | 79.8% | 1.0 | 75.4% | 0.5 | 2.2% | 2.0 | 6.2% | 0.3 | * | * | 3.6% | 1.9 | 2.0% | 2.0 | 14.3% | 2.9 | 7.7% | 0.8 | * | * | 6.9% | 0.7 |
| 25-49.9% | 96.1% | 9.9 | 92.0% | 2.0 | 6.5% | 5.8 | 13.2% | 0.5 | * | * | 9.3% | 3.5 | 7.2% | 7.4 | 43.1% | 11.8 | 19.3% | 4.0 | 2.3% | 9.4 | 9.5% | 2.0 |
| 50-74.9% | 99.4% | 47.2 | 98.0% | 5.8 | 16.0% | 10.4 | 22.7% | 1.0 | * | * | 21.0% | 8.0 | 12.5% | 16.0 | 61.8% | 33.5 | 30.1% | 5.0 | 8.8% | 22.0 | 10.2% | 5.0 |
| 75-89.9% | 100.0% | 203.0 | 99.7% | 15.8 | 24.2% | 31.0 | 28.5% | 2.0 | 3.2% | 25.0 | 39.1% | 20.0 | 32.4% | 50.0 | 77.6% | 95.7 | 36.7% | 10.0 | 15.6% | 50.0 | 11.2% | 7.0 |
| 90-100% | 100.0% | 728.8 | 100.0% | 43.0 | 28.8% | 46.0 | 28.1% | 2.5 | 12.7% | 111.1 | 62.9% | 110.0 | 47.3% | 160.0 | 82.5% | 264.0 | 43.8% | 20.0 | 21.0% | 135.0 | 16.4% | 40.0 |
| Family Structure | ||||||||||||||||||||||
| Single-Headed | 91.2% | 8.6 | 87.8% | 2.0 | 11.0% | 15.0 | 10.5% | 1.0 | 1.2% | 40.0 | 13.9% | 15.0 | 11.8% | 39.0 | 35.2% | 19.0 | 20.3% | 3.5 | 6.9% | 43.0 | 12.1% | 3.0 |
| Married or Cohabiting | 95.7% | 39.5 | 93.9% | 5.9 | 13.9% | 15.0 | 22.8% | 1.0 | 2.3% | 80.0 | 25.6% | 15.0 | 17.4% | 45.0 | 60.2% | 49.0 | 27.0% | 9.5 | 7.5% | 45.0 | 8.9% | 5.0 |
| Education | ||||||||||||||||||||||
| No high school diploma | 77.4% | 2.2 | 72.4% | 1.1 | 5.6% | 15.0 | 4.2% | 0.5 | 0.4% | 20.0 | 4.7% | 7.5 | 2.3% | 7.2 | 16.2% | 12.4 | 13.7% | 3.2 | 3.0% | 15.0 | 5.1% | 2.0 |
| High school diploma | 92.9% | 12.0 | 89.1% | 2.5 | 9.4% | 17.5 | 14.2% | 0.6 | 0.4% | 62.0 | 12.4% | 7.5 | 9.2% | 24.9 | 43.6% | 20.5 | 23.0% | 5.0 | 5.4% | 29.0 | 8.4% | 2.8 |
| Some college | 96.6% | 16.0 | 94.3% | 2.6 | 12.9% | 10.0 | 19.3% | 0.8 | 0.6% | 80.0 | 17.7% | 12.0 | 12.6% | 40.0 | 47.7% | 21.0 | 23.8% | 5.4 | 6.2% | 50.0 | 10.9% | 4.0 |
| College graduate | 99.6% | 78.2 | 99.1% | 9.2 | 17.0% | 19.0 | 24.9% | 1.0 | 4.1% | 153.5 | 35.3% | 20.0 | 26.1% | 53.0 | 68.9% | 64.3 | 29.5% | 10.0 | 10.9% | 50.0 | 14.4% | 7.0 |
| Race or ethnicity of respondent | ||||||||||||||||||||||
| Non white or Hispanic | 85.0% | 5.0 | 80.6% | 1.5 | 6.0% | 12.0 | 8.5% | 0.6 | * | * | 8.0% | 5.3 | 5.0% | 18.0 | 32.9% | 16.0 | 17.4% | 5.0 | 2.1% | 40.0 | 9.4% | 2.5 |
| White non-Hispanic | 97.2% | 36.0 | 95.5% | 5.0 | 15.3% | 16.0 | 21.1% | 1.0 | 2.5% | 80.0 | 25.5% | 18.0 | 18.9% | 45.0 | 56.1% | 41.0 | 26.8% | 7.0 | 9.2% | 45.0 | 10.2% | 5.0 |
| Current work status of head | ||||||||||||||||||||||
| Working for someone else | 94.5% | 20.5 | 92.2% | 3.1 | 9.8% | 10.0 | 20.1% | 0.7 | 0.8% | 25.0 | 19.6% | 10.0 | 13.5% | 25.0 | 57.1% | 30.0 | 21.8% | 5.4 | 5.4% | 50.0 | 9.5% | 3.0 |
| Self-employed | 96.1% | 53.2 | 94.4% | 10.0 | 14.2% | 20.0 | 18.7% | 1.9 | 4.3% | 130.0 | 31.6% | 25.0 | 22.3% | 60.0 | 54.6% | 60.0 | 29.8% | 10.5 | 7.6% | 42.0 | 15.1% | 6.0 |
| Retired | 93.6% | 26.5 | 90.4% | 4.2 | 20.2% | 25.0 | 11.4% | 3.0 | 3.5% | 90.0 | 19.0% | 45.0 | 16.2% | 75.0 | 32.9% | 47.0 | 29.7% | 5.0 | 12.8% | 45.0 | 8.4% | 10.0 |
| Other not working | 79.6% | 5.0 | 76.2% | 2.0 | 7.9% | 8.0 | 14.5% | 2.0 | * | * | 14.3% | 5.0 | 10.2% | 15.9 | 24.9% | 31.0 | 10.7% | 8.4 | * | * | 11.5% | 3.0 |
| Housing status | ||||||||||||||||||||||
| Renter or other | 85.5% | 3.0 | 80.9% | 1.1 | 5.6% | 7.0 | 9.5% | 0.7 | 0.2% | 130.0 | 9.1% | 4.5 | 5.7% | 10.0 | 26.2% | 11.0 | 11.0% | 3.0 | 2.0% | 42.0 | 10.9% | 2.0 |
| Owner | 97.5% | 47.9 | 96.0% | 6.0 | 15.9% | 20.0 | 21.2% | 1.0 | 2.6% | 65.0 | 25.8% | 20.0 | 19.2% | 50.0 | 60.2% | 46.0 | 30.1% | 7.0 | 9.6% | 45.0 | 9.6% | 6.0 |
| * Ten or fewer observations. Note: For questions on income, respondents were asked to base their answers on the calendar year preceding the interview. For questions on saving, respondents were asked to base their answers on the year (that is, not specifically the calendar year) preceding the interview. Percentage distributions may not sum to 100 because of rounding. Source: Bucks et al. (2006) and Urban Institute tabulations using the 2004 Survey of Consumer Finances. |
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| Family characteristic | Any nonfinancial asset | Vehicles | Primary residence | Other residential property | Equity in nonresidential property | Business Equity | Other | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | |
| $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | ||||||||
| All families | 92.5% | 147.8 | 86.3% | 14.2 | 69.1% | 160.0 | 12.5% | 100.0 | 8.3% | 60.0 | 11.5% | 100.0 | 7.8% | 15.0 |
| Age of head (years) | ||||||||||||||
| Less than 35 | 88.6% | 32.2 | 82.9% | 11.3 | 41.6% | 135.0 | 5.1% | 82.5 | 3.3% | 55.0 | 6.9% | 50.0 | 5.5% | 5.0 |
| 35-44 | 93.0% | 151.3 | 89.4% | 15.6 | 68.3% | 160.0 | 9.4% | 80.0 | 6.4% | 42.2 | 13.9% | 100.0 | 6.0% | 10.0 |
| 45-54 | 94.7% | 184.5 | 88.8% | 18.8 | 77.3% | 170.0 | 16.3% | 90.0 | 11.4% | 43.0 | 15.7% | 144.0 | 9.7% | 20.0 |
| 55-64 | 92.6% | 226.3 | 88.6% | 18.6 | 79.1% | 200.0 | 19.5% | 135.0 | 12.8% | 75.0 | 15.8% | 190.9 | 9.2% | 25.0 |
| 65-74 | 95.6% | 161.1 | 89.1% | 12.4 | 81.3% | 150.0 | 19.9% | 80.0 | 10.6% | 78.0 | 8.0% | 100.0 | 9.0% | 30.0 |
| 75 or more | 92.5% | 137.1 | 76.9% | 8.4 | 85.2% | 125.0 | 9.7% | 150.0 | 7.7% | 58.8 | 5.3% | 80.3 | 8.5% | 11.0 |
| Income percentile | ||||||||||||||
| Bottom quintile | 76.4% | 22.4 | 65.0% | 4.5 | 40.3% | 70.0 | 3.6% | 33.0 | 2.7% | 11.0 | 3.7% | 30.0 | 3.9% | 4.5 |
| Second quintile | 92.0% | 71.1 | 85.3% | 7.9 | 57.0% | 100.0 | 6.9% | 65.0 | 3.8% | 30.0 | 6.7% | 30.0 | 4.4% | 7.5 |
| Third quintile | 96.7% | 131.2 | 91.6% | 13.1 | 71.5% | 135.0 | 10.0% | 55.0 | 7.6% | 36.0 | 9.5% | 62.5 | 7.5% | 10.0 |
| Fourth quintile | 98.4% | 197.2 | 95.3% | 19.8 | 83.1% | 175.0 | 14.0% | 100.0 | 10.6% | 47.0 | 12.0% | 150.0 | 10.4% | 10.0 |
| Fifth quintile | 99.2% | 466.5 | 94.5% | 29.4 | 93.3% | 337.5 | 28.3% | 183.2 | 16.8% | 124.5 | 25.4% | 225.0 | 12.5% | 33.8 |
| 80-89.9% | 99.1% | 281.8 | 95.9% | 25.8 | 91.8% | 225.0 | 19.3% | 98.0 | 12.8% | 60.0 | 16.0% | 100.0 | 8.3% | 17.5 |
| 90-100% | 99.3% | 651.2 | 93.1% | 33.0 | 94.7% | 450.0 | 37.2% | 268.3 | 20.8% | 189.0 | 34.7% | 350.0 | 16.7% | 50.0 |
| Net worth percentile | ||||||||||||||
| Less than 25% | 73.7% | 7.4 | 69.8% | 5.6 | 15.2% | 65.0 | * | * | * | * | * | * | 2.9% | 3.0 |
| 25-49.9% | 97.5% | 72.4 | 89.2% | 11.9 | 71.2% | 85.0 | 4.9% | 25.6 | 4.1% | 14.9 | 5.6% | 17.5 | 5.4% | 6.0 |
| 50-74.9% | 99.0% | 188.1 | 92.0% | 17.4 | 93.4% | 159.3 | 12.7% | 65.0 | 8.3% | 25.0 | 11.2% | 55.0 | 7.8% | 10.0 |
| 75-89.9% | 99.8% | 360.8 | 95.2% | 22.6 | 96.2% | 250.0 | 23.1% | 100.0 | 15.1% | 73.9 | 19.9% | 150.0 | 12.3% | 25.0 |
| 90-100% | 99.9% | 907.7 | 93.1% | 30.6 | 96.9% | 450.0 | 45.6% | 325.0 | 28.8% | 250.0 | 40.8% | 527.4 | 18.8% | 80.0 |
| Family Structure | ||||||||||||||
| Single-Headed | 86.3% | 83.5 | 77.0% | 7.6 | 55.1% | 120.0 | 8.5% | 65.0 | 5.1% | 45.0 | 6.0% | 75.0 | 6.6% | 10.0 |
| Married or Cohabiting | 97.1% | 195.3 | 93.1% | 19.6 | 79.2% | 185.0 | 15.6% | 115.0 | 10.5% | 65.0 | 15.4% | 135.0 | 8.2% | 20.0 |
| Education | ||||||||||||||
| No high school diploma | 81.9% | 54.6 | 70.1% | 7.4 | 56.3% | 75.0 | 5.6% | 70.0 | 4.0% | 16.0 | 4.2% | 55.0 | 2.0% | 5.0 |
| High school diploma | 92.4% | 109.2 | 87.6% | 12.4 | 64.5% | 125.0 | 8.3% | 80.0 | 6.1% | 25.0 | 10.4% | 80.6 | 5.4% | 10.0 |
| Some college | 93.3% | 137.4 | 88.2% | 13.2 | 65.8% | 154.0 | 12.2% | 86.0 | 8.1% | 80.0 | 10.7% | 150.0 | 9.4% | 10.0 |
| College graduate | 96.5% | 241.2 | 90.7% | 18.9 | 79.1% | 240.0 | 19.0% | 145.0 | 11.9% | 92.0 | 15.6% | 150.0 | 11.3% | 20.0 |
| Race or ethnicity of respondent | ||||||||||||||
| Non white or Hispanic | 84.0% | 64.1 | 76.1% | 9.8 | 50.8% | 130.0 | 8.9% | 80.0 | 5.8% | 30.0 | 5.9% | 66.7 | 3.8% | 10.0 |
| White non-Hispanic | 95.8% | 164.8 | 90.3% | 15.7 | 76.1% | 165.0 | 14.0% | 105.0 | 9.2% | 66.0 | 13.6% | 135.0 | 9.3% | 16.5 |
| Current work status of head | ||||||||||||||
| Working for someone else | 93.8% | 141.9 | 89.7% | 14.9 | 66.5% | 160.0 | 10.4% | 88.0 | 6.8% | 40.0 | 5.8% | 50.0 | 7.1% | 10.0 |
| Self-employed | 97.5% | 335.4 | 91.2% | 21.9 | 79.1% | 248.0 | 25.8% | 141.5 | 18.7% | 125.0 | 58.1% | 174.0 | 12.9% | 30.0 |
| Retired | 89.8% | 131.7 | 79.0% | 10.1 | 75.8% | 130.0 | 12.8% | 100.0 | 7.9% | 60.0 | 3.5% | 120.0 | 7.1% | 25.0 |
| Other not working | 76.3% | 60.0 | 66.9% | 10.7 | 40.0% | 130.0 | 5.4% | 86.0 | * | * | 6.9% | 25.0 | 6.4% | 20.0 |
| Housing status | ||||||||||||||
| Renter or other | 75.9% | 8.4 | 73.0% | 7.2 | . . . | . . . | 5.4% | 80.0 | 2.4% | 56.0 | 4.3% | 50.0 | 4.6% | 8.0 |
| Owner | 100.0% | 201.6 | 92.3% | 17.5 | 100.0% | 160.0 | 15.7% | 100.0 | 11.0% | 62.0 | 14.7% | 112.8 | 9.2% | 17.5 |
| * Ten or fewer observations. . . . Not applicable. Note: For questions on income, respondents were asked to base their answers on the calendar year preceding the interview. For questions on saving, respondents were asked to base their answers on the year (that is, not specifically the calendar year) preceding the interview. Percentage distributions may not sum to 100 because of rounding. Source: Bucks et al. (2006) and Urban Institute tabulations using the 2004 Survey of Consumer Finances. |
||||||||||||||
| Family characteristic | Any debt | Home-secured | Other residential property | Installment loans | Credit card balances | Other lines of credit | Other | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | Percent | Median | |
| $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | $1000s | ||||||||
| All Families | 76.4% | 55.3 | 47.9% | 95.0 | 4.0% | 87.0 | 46.0% | 11.5 | 46.2% | 2.2 | 1.6% | 3.0 | 7.6% | 4.0 |
| Age of head (years) | ||||||||||||||
| Less than 35 | 79.8% | 33.6 | 37.7% | 107.0 | 2.1% | 62.5 | 59.4% | 11.9 | 47.5% | 1.5 | 2.2% | 1.0 | 6.2% | 3.0 |
| 35-44 | 88.6% | 87.2 | 62.8% | 110.0 | 4.0% | 75.0 | 55.7% | 12.0 | 58.8% | 2.5 | 1.5% | 1.9 | 11.3% | 4.0 |
| 45-54 | 88.4% | 83.2 | 64.6% | 97.0 | 6.3% | 87.0 | 50.2% | 12.0 | 54.0% | 2.9 | 2.9% | 7.0 | 9.4% | 4.0 |
| 55-64 | 76.3% | 48.0 | 51.0% | 83.0 | 5.9% | 108.8 | 42.8% | 12.9 | 42.1% | 2.2 | 0.7% | 14.0 | 8.4% | 5.5 |
| 65-74 | 58.8% | 25.0 | 32.1% | 51.0 | 3.2% | 100.0 | 27.5% | 8.3 | 31.9% | 2.2 | 0.4% | 4.0 | 4.0% | 5.0 |
| 75 or more | 40.3% | 15.4 | 18.7% | 31.0 | 1.5% | 39.0 | 13.9% | 6.7 | 23.6% | 1.0 | * | * | 2.5% | 2.0 |
| Income percentile | ||||||||||||||
| Bottom quintile | 52.6% | 7.0 | 15.9% | 37.0 | * | * | 26.9% | 5.6 | 28.8% | 1.0 | * | * | 4.6% | 2.0 |
| Second quintile | 69.8% | 16.1 | 29.5% | 53.3 | 1.5% | 32.5 | 39.9% | 8.0 | 42.9% | 1.9 | 1.5% | 32.5 | 5.8% | 2.7 |
| Third quintile | 84.0% | 44.7 | 51.7% | 78.0 | 2.6% | 66.0 | 52.4% | 10.8 | 55.1% | 2.2 | 1.8% | 66.0 | 8.0% | 2.3 |
| Fourth quintile | 56.6% | 93.4 | 65.8% | 97.0 | 4.1% | 62.0 | 57.8% | 13.9 | 56.0% | 3.0 | 1.8% | 62.0 | 8.3% | 3.5 |
| Fifth quintile | 89.2% | 172.5 | 76.5% | 159.0 | 11.5% | 118.5 | 52.9% | 16.6 | 48.1% | 3.4 | 2.6% | 118.5 | 11.5% | 7.2 |
| 80-89.9% | 92.0% | 136.0 | 76.8% | 133.0 | 7.5% | 78.0 | 60.0% | 15.1 | 57.6% | 2.7 | 2.6% | 78.0 | 12.3% | 5.0 |
| 90-100% | 86.3% | 209.0 | 76.2% | 185.0 | 15.4% | 159.0 | 45.7% | 18.0 | 38.5% | 4.0 | 2.5% | 159.0 | 10.6% | 9.4 |
| Net worth percentile | ||||||||||||||
| Less than 25% | 64.9% | 11.4 | 12.4% | 71.0 | * | * | 47.5% | 10.5 | 40.3% | 1.8 | 1.3% | 0.3 | 6.2% | 4.0 |
| 25-49.9% | 83.8% | 44.2 | 52.8% | 75.0 | 1.4% | 26.3 | 52.4% | 9.3 | 57.9% | 2.0 | 1.7% | 1.0 | 9.4% | 2.0 |
| 50-74.9% | 83.2% | 90.1 | 66.1% | 97.0 | 4.5% | 47.0 | 49.1% | 13.3 | 52.8% | 2.5 | 1.9% | 8.0 | 7.0% | 4.0 |
| 75-89.9% | 74.6% | 110.7 | 61.6% | 115.0 | 5.7% | 99.0 | 40.2% | 12.9 | 40.5% | 3.0 | 1.3% | 22.0 | 7.1% | 5.0 |
| 90-100% | 72.7% | 190.8 | 58.4% | 186.1 | 16.6% | 148.0 | 27.2% | 17.5 | 23.5% | 3.0 | 1.4% | 50.0 | 9.1% | 20.0 |
| Family Structure | ||||||||||||||
| Single-Headed | 67.4% | 24.0 | 32.2% | 75.0 | 2.5% | 76.0 | 36.5% | 8.6 | 41.0% | 1.0 | 1.0% | 1.9 | 6.6% | 2.4 |
| Married or Cohabiting | 82.3% | 86.0 | 59.2% | 105.0 | 5.1% | 99.0 | 52.9% | 13.6 | 49.9% | 7.0 | 2.0% | 2.4 | 8.4% | 5.0 |
| Education | ||||||||||||||
| No high school diploma | 53.4% | 12.0 | 24.8% | 44.0 | 0.3% | 80.0 | 28.0% | 7.0 | 29.5% | 1.2 | 0.3% | 105.0 | 5.7% | 4.0 |
| High school diploma | 73.2% | 31.0 | 42.2% | 70.0 | 2.2% | 47.0 | 44.3% | 9.0 | 48.2% | 1.9 | 1.8% | 1.5 | 59.0% | 3.0 |
| Some college | 84.2% | 45.0 | 48.7% | 86.0 | 4.7% | 75.0 | 49.9% | 11.8 | 54.4% | 2.2 | 1.8% | 3.0 | 10.3% | 3.4 |
| College graduate | 84.3% | 107.2 | 61.3% | 125.0 | 6.7% | 105.0 | 55.3% | 15.4 | 47.0% | 2.7 | 1.7% | 4.0 | 8.5% | 5.0 |
| Race or ethnicity of respondent | ||||||||||||||
| Non white or Hispanic | 72.5% | 30.5 | 37.4% | 83.0 | 3.0% | 66.0 | 43.2% | 9.6 | 46.7% | 1.6 | 1.1% | 0.4 | 7.3% | 3.0 |
| White non-Hispanic | 78.0% | 69.5 | 51.9% | 98.0 | 4.4% | 87.0 | 47.0% | 12.4 | 46.0% | 2.5 | 1.7% | 4.0 | 7.8% | 4.0 |
| Current work status of head | ||||||||||||||
| Working for someone else | 86.1% | 71.8 | 56.1% | 100.0 | 4.1% | 83.0 | 55.7% | 12.0 | 54.9% | 2.3 | 1.9% | 4.0 | 9.8% | 3.5 |
| Self-employed | 81.5% | 93.4 | 59.5% | 119.8 | 10.2% | 100.0 | 43.5% | 15.4 | 44.3% | 2.7 | 3.0% | 2.2 | 5.8% | 7.0 |
| Retired | 50.7% | 15.4 | 24.6% | 42.0 | 1.2% | 79.0 | 22.8% | 7.3 | 25.9% | 1.4 | * | * | 3.9% | 3.0 |
| Other not working | 70.4% | 21.1 | 30.3% | 78.0 | * | * | 45.6% | 7.5 | 41.0% | 2.5 | * | * | * | * |
| Housing status | ||||||||||||||
| Renter or other | 63.4% | 7.8 | . . . | . . . | 1.7% | 83.0 | 44.6% | 8.7 | 40.4% | 1.5 | 1.7% | 0.5 | 7.3% | 3.0 |
| Owner | 82.3% | 95.8 | 69.4% | 95.0 | 5.1% | 90.0 | 46.6% | 12.9 | 48.8% | 2.5 | 5.1% | 8.0 | 7.7% | 4.0 |
| *Ten or fewer observations. . . . Not
applicable Note: For questions on income, respondents were asked to base their answers on the calendar year preceding the interview. For questions on saving, respondents were asked to base their answers on the year (that is, not specifically the calendar year) preceding the interview. Percentage distributions may not sum to 100 because of rounding. Source: Bucks et al. (2006) and Urban Institute tabulations using the 2004 Survey of Consumer Finances. |
||||||||||||||
| Family Characteristic | Aggregate | Median of Family Ratios | ||||||
|---|---|---|---|---|---|---|---|---|
| 1995 | 1998 | 2001 | 2004 | 1995 | 1998 | 2001 | 2004 | |
| All Families | 14.1% | 14.9% | 12.9% | 14.4% | 16.2% | 17.9% | 16.7% | 18.0% |
| Income Percentile | ||||||||
| Bottom quintile | 19.1% | 18.7% | 16.1% | 18.2% | 13.3% | 18.8% | 19.2% | 19.7% |
| Second quintile | 17.0% | 16.5% | 15.8% | 16.7% | 17.5% | 17.5% | 16.7% | 17.4% |
| Third quintile | 15.6% | 18.6% | 17.1% | 19.4% | 15.7% | 19.4% | 17.6% | 19.5% |
| Fourth quintile | 17.9% | 19.1% | 16.8% | 18.5% | 18.9% | 19.5% | 18.1% | 20.6% |
| Fifth quintile | 13.1% | 13.6% | 12.6% | 13.3% | 14.7% | 15.8% | 14.3% | 15.4% |
| 80-89.9% | 16.6% | 16.8% | 17.0% | 17.3% | 16.8% | 17.8% | 17.3% | 18.1% |
| 90-100% | 9.5% | 10.3% | 8.1% | 9.3% | 12.6% | 13.7% | 11.2% | 12.7% |
| Age of Family Head | ||||||||
| Less than 35 | 17.8% | 17.2% | 17.2% | 17.8% | 16.8% | 16.9% | 17.7% | 18.0% |
| 35-44 | 17.2% | 17.7% | 15.1% | 18.2% | 18.3% | 20.0% | 17.8% | 20.6% |
| 45-54 | 15.1% | 16.3% | 12.8% | 15.3% | 16.6% | 17.9% | 17.4% | 18.4% |
| 55-64 | 11.8% | 13.4% | 10.9% | 11.5% | 14.2% | 17.6% | 14.3% | 15.8% |
| 65-74 | 7.2% | 8.8% | 9.2% | 8.7% | 12.3% | 13.2% | 16.0% | 15.6% |
| 75 or more | 2.5% | 4.1% | 3.9% | 7.1% | 2.9% | 8.1% | 8.0% | 12.8% |
| Net Worth Percentile | ||||||||
| Less than 25% | 13.4% | 15.0% | 13.4% | 13.0% | 11.7% | 13.6% | 11.5% | 13.0% |
| 25-49.9% | 18.5% | 20.1% | 18.0% | 19.5% | 19.0% | 20.0% | 20.1% | 21.2% |
| 50-74.9% | 18.0% | 18.3% | 16.8% | 20.6% | 19.3% | 20.2% | 18.3% | 21.4% |
| 75-89.9% | 14.0% | 14.8% | 15.4% | 15.1% | 15.3% | 17.8% | 16.8% | 17.9% |
| 90-100% | 9.0% | 10.2% | 7.5% | 8.5% | 12.7% | 14.0% | 11.2% | 12.6% |
| Housing Status | ||||||||
| Renter or other | 7.9% | 8.2% | 7.4% | 7.2% | 8.1% | 8.5% | 8.3% | 8.2% |
| Owner | 15.6% | 16.2% | 13.9% | 15.6% | 20.1% | 21.2% | 20.0% | 21.5% |
| Family Characteristic | Families with debt ratios greater than 40 percent | Families with any payment past due sixty days or more | ||||||
| 1995 | 1998 | 2001 | 2004 | 1995 | 1998 | 2001 | 2004 | |
| All Families | 11.7% | 13.6% | 11.8% | 12.2% | 7.1% | 8.1% | 7.0% | 8.9% |
| Income Percentile | ||||||||
| Bottom quintile | 27.5% | 29.9% | 29.3% | 27.0% | 10.2% | 12.9% | 13.4% | 15.9% |
| Second quintile | 18.0% | 18.3% | 16.6% | 18.6% | 10.1% | 12.3% | 11.7% | 13.8% |
| Third quintile | 9.9% | 15.8% | 12.3% | 13.7% | 8.7% | 10.0% | 7.9% | 10.4% |
| Fourth quintile | 7.7% | 9.8% | 6.5% | 7.1% | 6.6% | 5.9% | 4.0% | 7.1% |
| Fifth quintile | 3.5% | 3.2% | 2.8% | 2.1% | 1.9% | 2.8% | 2.0% | 1.3% |
| 80-89.9 | 4.7% | 3.5% | 3.5% | 2.4% | 2.8% | 3.9% | 2.6% | 2.3% |
| 90-100 | 2.3% | 2.8% | 2.0% | 1.8% | 1.0% | 1.6% | 1.3% | 0.3% |
| Age of Family Head | ||||||||
| Less than 35 | 12.1% | 12.8% | 12.0% | 12.8% | 8.7% | 11.1% | 11.9% | 13.7% |
| 35-44 | 9.9% | 12.5% | 10.1% | 12.6% | 7.7% | 8.4% | 5.9% | 11.7% |
| 45-54 | 12.3% | 12.9% | 11.6% | 13.1% | 7.4% | 7.4% | 6.2% | 7.6% |
| 55-64 | 15.1% | 14.0% | 12.3% | 10.2% | 3.2% | 7.5% | 7.1% | 4.2% |
| 65-74 | 11.3% | 18.1% | 14.7% | 11.6% | 5.3% | 3.1% | 1.5% | 3.4% |
| 75 or more | 7.4% | 21.4% | 14.6% | 10.7% | 5.4% | 1.1% | 0.8% | 3.9% |
| Net Worth Percentile | ||||||||
| Less than 25 | 10.1% | 13.0% | 11.6% | 10.6% | 14.5% | 16.1% | 17.7% | 22.9% |
| 25-49.9 | 12.9% | 15.9% | 14.1% | 15.8% | 8.2% | 9.8% | 7.2% | 11.0% |
| 50-74.9 | 12.7% | 13.0% | 11.3% | 12.8% | 4.4% | 5.5% | 3.6% | 3.2% |
| 75-89.9 | 9.9% | 12.2% | 10.7% | 9.6% | 2.4% | 1.0% | 0.7% | 1.1% |
| 90-100 | 11.6% | 12.4% | 8.5% | 7.6% | 0.7% | 2.4% | 0.3% | 0.1% |
| Housing Status | ||||||||
| Renter or other | 5.8% | 6.4% | 4.2% | 4.4% | 11.5% | 12.8% | 14.0% | 18.6% |
| Owner | 14.3% | 16.5% | 14.7% | 14.9% | 5.1% | 6.1% | 4.3% | 5.6% |
| Note: The aggregate measure is the ratio
of total debt payments to total income for all families. The median
of family ratios is the median of the distribution of ratios calculated for
individual families. Source: Bucks et al. (2006) using the 2004 Survey of Consumer Finances. |
||||||||
| Family Characteristic | Any financial asset | Any nonfinancial asset | Any asset | Any debt | Leverage Ratio Assets over Debts |
||||
|---|---|---|---|---|---|---|---|---|---|
| Percent | Median | Percent | Median | Percent | Median | Percent | Median | ||
| $1000s | $1000s | $1000s | $1000s | ||||||
| All Families | 93.8% | 23.0 | 92.5% | 147.8 | 97.9% | 172.9 | 76.4% | 55.3 | 3.1 |
| Age of Family Head | |||||||||
| Less than 35 | 90.1% | 5.2 | 88.6% | 32.2 | 96.5% | 39.2 | 79.8% | 33.6 | 1.2 |
| 35-44 | 93.6% | 19.0 | 93.0% | 151.3 | 97.7% | 173.4 | 88.6% | 87.2 | 2.0 |
| 45-54 | 93.6% | 38.6 | 94.7% | 184.5 | 98.3% | 234.9 | 88.4% | 83.2 | 2.8 |
| 55-64 | 95.2% | 78.0 | 92.6% | 226.3 | 97.5% | 351.2 | 76.3% | 48.0 | 7.3 |
| 65-74 | 96.5% | 36.1 | 95.6% | 161.1 | 99.5% | 233.2 | 58.8% | 25.0 | 9.3 |
| 75 or more | 97.6% | 38.8 | 92.5% | 137.1 | 99.6% | 185.2 | 40.3% | 15.4 | 12.0 |
| Income Percentile | |||||||||
| Bottom quintile | 80.1% | 1.3 | 76.4% | 22.4 | 92.2% | 17.0 | 52.6% | 7.0 | 2.4 |
| Second quintile | 91.5% | 4.9 | 92.0% | 71.1 | 97.8% | 78.3 | 69.8% | 16.1 | 4.9 |
| Third quintile | 98.5% | 15.5 | 96.7% | 131.2 | 99.8% | 154.4 | 84.0% | 44.7 | 3.5 |
| Fourth quintile | 99.1% | 48.5 | 98.4% | 197.2 | 100.0% | 289.4 | 56.6% | 93.4 | 3.1 |
| Fifth quintile | 99.9% | 236.7 | 99.2% | 466.5 | 99.9% | 808.1 | 89.2% | 172.5 | 4.5 |
| 80-89.9% | 99.8% | 108.2 | 99.1% | 281.8 | 99.8% | 458.5 | 92.0% | 136.0 | 3.4 |
| 90-100% | 100.0% | 365.1 | 99.3% | 651.2 | 100.0% | 1157.7 | 86.3% | 209.0 | 5.5 |
| Net Worth Percentile | |||||||||
| Less than 25% | 79.8% | 1.0 | 73.7% | 7.4 | 91.7% | 7.7 | 64.9% | 11.4 | 0.7 |
| 25-49.9% | 96.1% | 9.9 | 97.5% | 72.4 | 100.0% | 84.5 | 83.8% | 44.2 | 1.9 |
| 50-74.9% | 99.4% | 47.2 | 99.0% | 188.1 | 100.0% | 257.3 | 83.2% | 90.1 | 2.9 |
| 75-89.9% | 100.0% | 203.0 | 99.8% | 360.8 | 100.0% | 600.2 | 74.6% | 110.7 | 5.4 |
| 90-100% | 100.0% | 728.8 | 99.9% | 907.7 | 100.0% | 1572.6 | 72.7% | 190.8 | 8.2 |
| Family Structure | |||||||||
| Single-Headed | 91.2% | 8.6 | 86.3% | 83.5 | 96.5% | 83.4 | 67.4% | 24.0 | 3.5 |
| Married or Cohabiting | 95.7% | 39.5 | 97.1% | 195.3 | 99.0% | 265.8 | 82.3% | 86.0 | 3.1 |
| Education | |||||||||
| No high school diploma | 77.4% | 2.2 | 81.9% | 54.6 | 91.1% | 49.9 | 53.4% | 12.0 | 4.2 |
| High school diploma | 92.9% | 12.0 | 92.4% | 109.2 | 98.1% | 133.4 | 73.2% | 31.0 | 4.3 |
| Some college | 96.6% | 16.0 | 93.3% | 137.4 | 99.1% | 150.5 | 84.2% | 45.0 | 3.3 |
| College graduate | 99.6% | 78.2 | 96.5% | 241.2 | 99.9% | 357.0 | 84.3% | 107.2 | 3.3 |
| Race and Ethnicity | |||||||||
| Non-white or Hispanic | 85.0% | 5.0 | 84.0% | 64.1 | 94.4% | 59.6 | 72.5% | 30.5 | 2.0 |
| White, Non-Hispanic | 97.2% | 36.0 | 95.8% | 164.8 | 99.3% | 224.5 | 78.0% | 69.5 | 3.2 |
| Housing Status | |||||||||
| Renter or other | 85.5% | 3.0 | 80.9% | 1.1 | 93.3% | 12.2 | 63.4% | 7.8 | 1.6 |
| Owner | 97.5% | 47.9 | 96.0% | 6.0 | 100.0% | 289.9 | 82.3% | 95.8 | 3.0 |
| Source: Bucks et al. (2006) and Urban Institute tabulations using the 2004 Survey of Consumer Finances. | |||||||||
| Family Characteristic | 1992 | 1995 | 1998 | 2001 | 2004 | % Change, '92-'04 | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Median | Mean | Median | Mean | Median | Mean | Median | Mean | Median | Mean | Median | Mean | |
| All Families | 65.4 | 246.3 | 70.8 | 260.8 | 83.1 | 327.5 | 91.7 | 421.5 | 93.1 | 448.2 | 31.5% | 71.9% |
| Income Percentile | ||||||||||||
| Bottom quintile | 5.2 | 43.9 | 7.4 | 54.7 | 6.8 | 55.4 | 8.4 | 56.1 | 7.5 | 72.6 | 44.4% | 65.3% |
| Second quintile | 36.6 | 85.4 | 41.3 | 97.4 | 38.4 | 111.5 | 39.6 | 121.8 | 34.3 | 122.0 | -6.2% | 42.9% |
| Third quintile | 52.1 | 133.6 | 57.1 | 126.0 | 61.9 | 146.6 | 66.5 | 171.4 | 71.6 | 193.8 | 37.4% | 45.0% |
| Fourth quintile | 98.2 | 183.9 | 93.6 | 198.5 | 130.2 | 238.3 | 150.7 | 311.3 | 160.0 | 342.8 | 63.0% | 86.4% |
| Fifth quintile | 319.1 | 784.3 | 297.3 | 827.4 | 371.5 | 1085.5 | 584.1 | 1446.7 | 617.6 | 1509.7 | 93.6% | 80.9% |
| 80-89.9% | 157.4 | 299.1 | 157.7 | 316.8 | 218.5 | 377.1 | 280.3 | 486.6 | 311.1 | 485.0 | 97.7% | 62.1% |
| 90-100% | 480.8 | 1269.6 | 436.9 | 1338.0 | 524.4 | 1793.9 | 887.9 | 2406.7 | 924.1 | 2534.4 | 92.2% | 99.6% |
| Age of Family Head | ||||||||||||
| Less than 35 | 12.0 | 59.8 | 14.8 | 53.2 | 10.6 | 74.0 | 12.3 | 96.6 | 14.2 | 73.5 | 18.1% | 23.0% |
| 35-44 | 58.8 | 175.6 | 64.2 | 176.8 | 73.5 | 227.6 | 82.6 | 276.4 | 69.4 | 299.2 | 18.1% | 70.4% |
| 45-54 | 103.2 | 353.5 | 116.8 | 364.8 | 122.3 | 420.2 | 141.6 | 517.6 | 144.7 | 542.7 | 40.2% | 53.5% |
| 55-64 | 150.0 | 447.2 | 141.9 | 471.1 | 148.2 | 617.0 | 193.3 | 775.4 | 248.7 | 843.8 | 65.8% | 88.7% |
| 65-74 | 130.1 | 379.7 | 136.6 | 429.3 | 169.8 | 541.1 | 187.8 | 717.9 | 190.1 | 690.9 | 46.1% | 82.0% |
| 75 or more | 114.5 | 282.4 | 114.5 | 317.9 | 145.6 | 360.3 | 161.2 | 496.2 | 163.1 | 528.1 | 42.4% | 87.0% |
| Education of Family Head | ||||||||||||
| No high school diploma | 24.6 | 92.4 | 27.9 | 103.7 | 24.5 | 91.4 | 27.2 | 109.7 | 20.6 | 136.5 | -16.4% | 47.8% |
| High school diploma | 50.6 | 147.2 | 63.9 | 163.7 | 62.7 | 182.9 | 61.8 | 192.5 | 68.7 | 196.8 | 35.7% | 33.7% |
| Some college | 76.2 | 227.0 | 57.6 | 232.3 | 85.6 | 275.5 | 76.3 | 303.8 | 69.3 | 308.6 | -9.1% | 35.9% |
| College graduate | 129.8 | 448.6 | 128.6 | 473.7 | 169.7 | 612.3 | 227.2 | 845.7 | 226.1 | 851.3 | 74.2% | 89.8% |
| Race and Ethnicity | ||||||||||||
| Non-white or Hispanic | 15.8 | 102.1 | 19.5 | 94.9 | 19.3 | 116.5 | 19.1 | 123.8 | 24.8 | 153.1 | 56.8% | 50.0% |
| White, Non-Hispanic | 91.9 | 293.7 | 94.3 | 308.7 | 111.0 | 391.1 | 129.6 | 518.7 | 140.7 | 561.8 | 53.2% | 91.3% |
| Current Work Status of Head | ||||||||||||
| Working for someone else | 51.8 | 161.5 | 60.3 | 168.4 | 61.2 | 194.8 | 69.3 | 240.1 | 67.2 | 268.5 | 29.7% | 66.2% |
| Self-employed | 193.7 | 792.5 | 191.8 | 862.8 | 288.0 | 1071.3 | 375.2 | 1340.6 | 335.6 | 1423.2 | 73.2% | 79.6% |
| Retired | 92.9 | 250.0 | 99.9 | 277.2 | 131.0 | 356.5 | 120.4 | 479.2 | 139.8 | 469.0 | 50.5% | 87.6% |
| Other not working | 4.3 | 70.0 | 4.5 | 70.1 | 4.1 | 85.8 | 9.5 | 191.7 | 11.8 | 162.3 | 171.3% | 131.9% |
| Region | ||||||||||||
| Northeast | 84.5 | 277.2 | 102.0 | 308.9 | 109.3 | 351.3 | 98.3 | 480.0 | 161.7 | 569.1 | 91.4% | 105.3% |
| North Central | 75.1 | 228.1 | 80.8 | 244.7 | 93.1 | 288.5 | 111.3 | 361.6 | 115.0 | 436.1 | 53.1% | 91.2% |
| South | 45.5 | 185.5 | 54.2 | 229.5 | 71.0 | 309.6 | 78.6 | 400.4 | 63.8 | 348.0 | 40.2% | 87.6% |
| West | 94.2 | 335.4 | 67.4 | 286.1 | 71.1 | 379.1 | 93.3 | 468.8 | 94.8 | 523.7 | 0.6% | 56.1% |
| Housing Status | ||||||||||||
| Renter | 4.2 | 50.9 | 6.0 | 53.8 | 4.9 | 50.4 | 5.1 | 58.5 | 4.0 | 54.1 | -5.2% | 6.2% |
| Owner | 130.3 | 356.6 | 128.1 | 373.7 | 153.2 | 468.7 | 182.9 | 594.8 | 184.4 | 624.9 | 41.5% | 75.3% |
| Net Worth Percentile | ||||||||||||
| Less than 25% | 0.7 | -0.8 | 1.2 | -0.2 | 0.6 | -2.1 | 1.2 | 0.0 | 1.7 | -1.4 | 158.0% | -79.5% |
| 25-49.9% | 31.0 | 33.4 | 34.7 | 37.6 | 37.9 | 41.6 | 43.4 | 47.0 | 43.6 | 47.1 | 40.8% | 40.8% |
| 50-74.9% | 115.7 | 119.4 | 117.1 | 122.6 | 139.7 | 149.1 | 166.8 | 176.6 | 170.7 | 185.4 | 47.5% | 55.2% |
| 75-89.9% | 268.9 | 288.1 | 272.3 | 293.6 | 357.7 | 372.6 | 458.2 | 478.6 | 506.8 | 526.7 | 88.5% | 82.8% |
| 90-100% | 880.4 | 1650.4 | 836.7 | 1766.7 | 1039.1 | 2244.2 | 1386.6 | 2936.1 | 1430.1 | 3114.2 | 62.4% | 88.7% |
| Note: For questions on income, respondents were
asked to base their answers on the calendar year preceding the interview.
For questions on saving, respondents were asked to base their answers on
the year (that is, not specifically the calendar year) preceding the interview.
Percentage distributions may not sum to 100 because of rounding. Source: Bucks et al. (2006) using the 2004 Survey of Consumer Finances. |
||||||||||||
[12] A more thorough analysis of data sources is available in the Poor Finances report “Assessing Asset Data on Low-Income Households: Current Availability and Options for Improvement” (Ratcliffe et al. 2007).
[13] They use an alternative version of family-sized poverty thresholds devised by a National Academy of Sciences panel, rather than the official U.S. poverty threshold.
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