Federal Reserve

BULLETIN

Income

Median and mean inflation-adjusted before-tax family incomes moved in different directions between 2010 and 2013.⁷ Overall, median income fell 5 percent between 2010 and 2013, from $49,000 to $46,700 (table 1). Mean income increased 4 percent, from $84,100 to $87,200. The decline in median income coupled with the rise in mean income is consistent with a widening income distribution during this period.⁸

Table 1. Before-tax median and mean family income, by selected characteristics of families,
2010 and 2013 surveys
Thousands of 2013 dollars except as noted

Family characteristic	Median income			Mean income
	2010	2013	Percent change 2010-13	2010	2013	Percent change 2010-13
All families	49.0	46.7	-5	84.1	87.2	4
	(.6)	(.6)		(1.2)	(1.5)
Percentile of usual income
Less than 20	15.8	15.2	-4	16.5	15.2	-8
20-39.9	32.7	30.4	-7	32.4	30.5	-6
40-59.9	51.8	48.7	-6	49.9	49.6	-1
60-79.9	79.5	77.9	-2	78.9	80.0	1
80-89.9	125.3	121.7	-3	124.3	123.5	-1
90-100	217.9	223.2	2	361.5	397.5	10
Age of head (years)
Less than 35	37.6	35.3	-6	51.1	48.7	-5
35-44	57.7	60.9	6	86.8	102.0	18
45-54	65.4	60.9	-7	109.5	103.8	-5
55-64	59.0	55.1	-7	113.4	110.1	-3
65-74	45.8	45.9	0	81.2	98.8	22
75 or more	31.2	28.5	-9	49.4	53.1	7
Education of head
No high school diploma	24.6	22.3	-9	36.1	30.0	-17
High school diploma	39.2	37.0	-6	51.6	50.7	-2
Some college	46.0	40.9	-11	63.0	61.3	-3
College degree	79.1	80.0	1	138.1	145.4	5
Race or ethnicity of respondent
White non-Hispanic	56.6	55.8	-1	96.6	104.5	8
Nonwhite or Hispanic	37.1	33.6	-9	58.3	51.6	-11
Housing status
Owner	63.8	63.4	-1	105.3	112.4	7
Renter or other	28.0	27.8	-1	40.6	40.1	-1
Percentile of net worth
Less than 25	25.4	23.7	-7	35.0	31.4	-10
25-49.9	40.6	38.6	-5	48.8	46.9	-4
50-74.9	58.8	55.8	-5	67.8	65.8	-3
75-89.9	79.9	87.5	10	95.4	100.0	5
90-100	174.9	183.4	5	319.2	361.2	13

Note: Income is measured for the year prior to the survey. See the appendix for details on standard errors (shown in parentheses below the first row of data for the means and medians).

Over the preceding three-year period, 2007-10, median and mean income both fell sharply (8 percent and 11 percent, respectively). The changes for both the 2007-10 and 2010-13 periods stand in stark contrast to a pattern of substantial increases in both the median and the mean dating back to the early 1990s.⁹

Some predictable patterns in income levels across demographic groups are observed in the 2013 SCF, and those patterns are largely consistent with prior surveys.¹⁰ Across age groups, median and mean incomes show a life-cycle pattern, rising to a peak in the middle age groups and then declining for groups that are older and increasingly more likely to be retired. Income also shows a strong positive association with education; in particular, incomes for families headed by a person who has a college degree tend to be substantially higher than for those with lower levels of schooling. Incomes of white non-Hispanic families are substantially higher than those of other families.¹¹ Income is also higher for homeowners than for other families, and income is systematically higher for groups with greater net worth.¹²

Changes in Income by Family Characteristics

Changes in median and mean incomes between 2010 and 2013 varied substantially across different types of families, whether grouped by economic characteristics such as income, wealth, and homeowner status, or by purely demographic variables such as age, education, or race and ethnicity. Patterns are generally consistent with the overall widening of the income distribution, as reflected in the differential growth of overall median and mean family income.

For a given family, income at a particular time may not be indicative of its "usual" income. Unemployment, a bonus, a capital loss or gain, or other factors may cause income to deviate temporarily from the usual amount.¹³ Across the distribution of families grouped by usual income, all but the highest quintile saw declines in median income between 2010 and 2013, with second and third quintiles seeing the largest declines (7 percent and 6 percent, respectively).¹⁴ Median income increased 2 percent for the top income decile. Mean income declined strongly for the bottom two quintiles and barely budged for those between the 40th and 90th percentiles, whereas the mean income of the top decile increased 10 percent between 2010 and 2013.

Nearly all age groups experienced declines in median income, with the exception of families headed by those age 35 to 44 (6 percent increase) and age 65 to 74 (no change). Mean incomes increased 18 percent for ages 35 to 44 and 22 percent for ages 65 to 74. Unlike for median incomes, the mean income of the oldest households increased about 7 percent. For every age group, mean incomes declined by less than median incomes or rose by more than median incomes.

Between 2010 and 2013, both median and mean income changes were positively associated with educational attainment. The median income of households with a high school diploma or less fell between 6 and 9 percent, whereas the mean income of those without a high school diploma fell much more than that of those who graduated from high school (a 17 percent decline versus a 2 percent decline). The median income of those with some college decreased 11 percent, whereas the median income of those with a college degree increased 1 percent. Mean income for those with a college degree increased 5 percent.

Over the 2010-13 period, median income for white non-Hispanic families decreased modestly, 1 percent, whereas their mean income increased 8 percent. Their incomes in both years were much higher than non-white or Hispanic families, who saw declines in median income of 9 percent and declines in mean income of 11 percent.

For homeowners, median income fell 1 percent between 2010 and 2013, while mean income increased 7 percent during this period. Median and mean incomes for renters and other families declined very modestly, 1 percent for both measures.

By percentile of net worth measured concurrently in the SCF, both mean and median income fell for those in the bottom three quartiles, while both measures rose for the top quartile. For households in the lowest quartile of net worth, median income declined 7 percent and mean income fell 10 percent. Households in the second and third quartile saw smaller declines in income (5 percent for both groups for median income, and 3 to 4 percent for mean income, for both groups). However, both mean and median income increased for the top quartile. For those households in the 75th to 90th percentile of net worth, median income rose 10 percent, while it rose 5 percent for the top decile. The largest increase was in mean income for the top decile of net worth, an increase of 13 percent.

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Net Worth

Median and mean inflation-adjusted net worth--the difference between families' gross assets and their liabilities--were both little changed between 2010 and 2013 (table 2). Overall, the median net worth of all families fell a modest 2 percent to $81,200, while mean net worth was effectively unchanged at $534,600. In contrast, the 2010 SCF showed dramatic decreases in median and mean net worth in the 2007-10 period, while the 2007 survey showed substantial increases relative to 2004.¹⁵ These patterns in net worth over the past decade were largely driven by the boom and bust in house and other asset prices. The bust, in particular, had a disproportionate effect on families in the middle of the net worth distribution, whose wealth portfolio is dominated by housing. Divergent trends in median and mean net worth over the past few surveys suggest substantial heterogeneity in wealth changes across families.¹⁶

Table 2. Family median and mean net worth, by selected characteristics of families,
2010 and 2013 surveys
Thousands of 2013 dollars except as noted

Family characteristic	Median net worth			Mean net worth
	2010	2013	Percent change 2010-13	2010	2013	Percent change 2010-13
All families	82.8	81.2	-2	534.5	534.6	0
	(2.6)	(2.8)		(10.0)	(9.3)
Percentile of usual income
Less than 20	7.3	6.4	-12	81.8	64.6	-21
20-39.9	31.0	27.9	-10	134.7	113.1	-16
40-59.9	66.6	55.4	-17	189.5	164.8	-13
60-79.9	138.6	161.3	16	306.8	350.9	14
80-89.9	321.7	287.9	-11	645.0	631.4	-2
90-100	1,275.7	1,125.9	-12	3,274.6	3,327.3	2
Age of head (years)
Less than 35	10.0	10.4	4	70.0	75.5	8
35-44	45.2	46.7	3	233.0	347.2	49
45-54	126.3	105.3	-17	614.1	530.1	-14
55-64	192.3	165.9	-14	943.6	798.4	-15
65-74	221.5	232.1	5	909.2	1,057.0	16
75 or more	232.3	194.8	-16	726.5	645.2	-11
Education of head
No high school diploma	17.2	17.2	0	118.6	108.3	-9
High school diploma	60.7	52.5	-14	233.8	199.6	-15
Some college	54.5	46.9	-14	291.7	317.9	9
College degree	209.2	219.4	5	1,047.8	1,031.6	-2
Race or ethnicity of respondent
White non-Hispanic	139.9	142.0	2	701.4	705.9	1
Nonwhite or Hispanic	21.9	18.1	-17	188.5	183.9	-2
Housing status
Owner	187.0	195.4	4	764.6	783.0	2
Renter or other	5.4	5.4	0	61.3	70.3	15
Percentile of net worth
Less than 25	†	†	...	-13.7	-13.4	2
25-49.9	34.5	31.3	-9	38.2	35.9	-6
50-74.9	168.5	168.1	0	181.0	177.7	-2
75-89.9	517.3	505.8	-2	565.7	546.2	-3
90-100	1,997.8	1,871.8	-6	3,982.8	4,024.8	1

† Less than 0.05 ($50).

... Not applicable.

Note: Net worth is the difference between families' gross assets and their liabilities. See the appendix for definitions of asset and liability categories used in the SCF, as well as details on standard errors (shown in parentheses below the first row of data for the means and medians).

The median and mean values of wealth rise systematically with usual income, a relationship reflecting a higher level of saving among higher-income families, and the feedback effect of higher incomes from the accumulated assets.¹⁷ Median and mean family net worth generally increase with age, with a plateau or modest decreases for the oldest age groups relative to the near-retirement age groups. This pattern reflects both life-cycle saving behavior and a historical pattern of long-run growth in inflation-adjusted wages, as younger cohorts have generally had higher lifetime earnings than preceding cohorts. Wealth shows strong differentials across groups defined in terms of education, racial or ethnic background, and housing status; these differentials generally mirror those for income, but the wealth differences are larger.

Changes in Net Worth by Family Characteristics

Families with higher levels of usual income reported greater levels of net worth, but changes in net worth varied substantially across the usual income distribution. Median net worth decreased between 2010 and 2013 for most usual income groups, falling between 10 and 17 percent, with the exception of the fourth quintile. Those in the lowest usual income quintile saw small decreases in median net worth (12 percent, from $7,300 to $6,400), but they also saw the largest proportional decrease in mean net worth (21 percent, from $81,800 to $64,600). Households in the second and third quintile of usual income saw large declines in median net worth (10 percent and 17 percent, respectively), as well as mean net worth (16 percent and 13 percent). The fourth income quintile was the only group that experienced increases in both median and mean net worth: 16 percent for median net worth and 14 percent for mean net worth. Those at the top of the income distribution experienced decreases in median net worth, while mean net worth was little changed.

Different age groups experienced very different trends in net worth between 2010 and 2013. Both mean and median net worth increased for those under age 45, decreased for those between age 45 and 64, increased for those between age 65 and 74, and decreased for the oldest group. Increases were generally larger for mean net worth than for median net worth, while declines were similar in magnitude for the two measures. Gains in median net worth ranged between 3 and 5 percent, while declines ranged between 14 and 17 percent.

From 2010 to 2013, net worth followed different patterns for different education groups. Those without a high school diploma saw no change in median net worth between 2010 and 2013, but their mean net worth fell 9 percent. Those with high school diplomas or some college both saw 14 percent declines in median net worth; the former saw a 15 percent decline in mean net worth, while those with some college had 9 percent higher mean net worth in 2013. Median net worth increased 5 percent for those with college degrees, while their mean net worth declined 2 percent.

Mean and median net worth of non-Hispanic white families changed similarly, a 1 percent mean increase and 2 percent median increase, with median net worth reaching $142,000 and mean net worth reaching $705,900 in 2013. However, the median net worth of non-white or Hispanic families fell 17 percent to $18,100, and mean net worth fell 2 percent to $183,900.

The median net worth of homeowners increased 4 percent between 2010 and 2013, whereas that of renters or other non-homeowners did not change. The mean net worth of homeowners increased 2 percent compared with the 15 percent increase for renters.

Median net worth fell for all percentile groups of the distribution of net worth, with the largest decreases in proportional terms being for the second quartile (9 percent decline) and the top decile (6 percent) of the net worth distribution. For the lowest quartile, median net worth was less than $50 in both 2010 and 2013, while mean net worth increased 2 percent from negative $13,700 to negative $13,400. While the second quartile experienced the largest declines in mean and median net worth, median net worth of the third quartile was virtually unchanged between 2010 and 2013 at approximately $168,100 and mean net worth declined 2 percent to $177,700. Families between the 75th and 90th percentile of net worth saw a 2 percent decline in median net worth, reaching $505,800 in 2013, and a 3 percent decline in mean net worth. While the median net worth of the top decile dropped 6 percent to $1,871,800 in 2013, the group's mean net worth rose slightly and exceeded $4 million in 2013.

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Assets

Between 2010 and 2013, ownership of any type of asset changed little, rising slightly from 97.4 percent to 97.9 percent in 2013 (table 3). At the same time, ownership rates of nearly every type of individual asset fell between 2010 and 2013. This finding indicates that while most families continue to hold some type of asset, many more families now hold fewer different types of assets.

Table 3. Holding and values of assets, 2010 and 2013 surveys
Thousands of 2013 dollars except as noted

Balance sheet item	Percent holding		Conditional median value			Conditional mean value
	2010	2013	2010	2013	Percent change 2010-13	2010	2013	Percent change 2010-13
Any Asset	97.4	97.9	200.6	177.9	-11	656.2	638.9	-3
Types of financial asset
Any financial asset	94.0	94.5	23.0	21.2	-8	257.8	270.1	5
Transaction accounts	92.5	93.2	3.8	4.1	9	34.8	36.3	4
Certificates of deposit	12.2	7.8	21.4	16.0	-25	77.8	64.5	-17
Savings bonds	12.0	10.0	1.1	1.0	-7	6.6	6.4	-3
Bonds	1.6	1.4	146.8	94.5	-36	659.1	581.7	-12
Stocks	15.1	13.8	21.4	27.0	26	224.8	294.3	31
Pooled investment funds	8.7	8.2	85.7	80.0	-7	416.4	462.9	11
Retirement accounts	50.4	49.2	47.2	59.0	25	183.4	201.3	10
Cash value life insurance	19.7	19.2	7.8	8.0	2	30.4	35.3	16
Other managed assets	5.7	5.2	75.0	100.0	33	265.7	370.6	39
Other	8.0	6.9	5.4	4.0	-25	68.5	55.1	-20
Types of nonfinancial asset
Any nonfinancial asset	91.3	91.0	165.6	148.4	-10	434.6	407.2	-6
Vehicles	86.7	86.3	16.3	15.8	-4	23.7	22.6	-5
Primary residence	67.3	65.2	182.2	170.0	-7	280.1	262.6	-6
Other residential property	14.3	13.2	128.6	123.8	-4	309.7	316.3	2
Equity in nonresidential property	7.7	7.2	69.7	60.0	-14	344.6	268.0	-22
Business equity	13.3	11.7	84.4	67.5	-20	844.8	973.9	15
Other	7.0	7.3	16.1	13.0	-19	71.3	72.2	1

Note: See the appendix for definitions of asset categories used in the SCF.

Conditional on holding any assets, the median family's total asset holdings fell 11 percent, from $200,600 in 2010 to $177,900 in 2013. The conditional mean value of total assets also fell, although the drop was more modest, at 3 percent. Much of this decline in the conditional median and mean value of total assets held can be explained by declines in homeownership and stagnant real home prices between 2010 and 2013. The larger drop in median--versus mean--asset holdings indicates that losses in asset values were spread unequally across families and asset types.

Financial Assets

Overall, ownership of any financial assets--which includes transaction accounts, certificates of deposit, savings bonds, other bonds, stocks, pooled investment funds, retirement accounts, cash value life insurance, and other managed assets--remained high in 2013, at 94.5 percent.¹⁸ This finding represented almost no change from the level seen in 2010 (94.0 percent). However, the conditional median value of all financial assets held by families fell 8 percent, from $23,000 in 2010 to $21,200 in 2013. Conditional mean values, by contrast, rose 5 percent, from $257,800 to $270,100. This increase indicates that some families experienced large gains in the values of their financial assets, but the median family experienced a loss in financial asset values.

Although overall ownership rates of any financial asset remained unchanged, ownership rates of almost every specific type of financial asset fell (with the exception of transaction accounts), suggesting families now hold fewer different types of financial assets.

Transaction accounts--which include checking, savings, money market, and call accounts--remained the most commonly held type of financial asset in 2013, with an ownership rate of 93.2 percent, a slight increase from the 92.5 percent of families that held a transaction account in 2010. The conditional median and mean values of those accounts also rose between 2010 and 2013, 9 percent and 4 percent, respectively. In 2013, median transaction account holdings were $4,100, and mean holdings were $36,300.

Rates of ownership of certificates of deposits fell markedly between 2010 and 2013, from 12.2 percent to 7.8 percent. The amount held in those accounts also fell, with the median declining 25 percent and the mean declining 17 percent. These declines are, at least in part, attributable to low interest rates over this period, which reduced the advantage of certificates of deposit over transaction accounts.

Ownership of savings bonds, other bonds, directly held stocks, and pooled investment funds sustained sizable drops in ownership rates between 2010 and 2013, although none of the four types of assets are commonly held, with ownership rates in 2013 varying between 1.4 percent (other bonds) and 13.8 percent (directly held stocks). The conditional median and mean value of most of these assets also fell between 2010 and 2013, with the exception of pooled investment funds and stocks. The median value of stocks rose 26 percent, from $21,400 in 2010 to $27,000 in 2013. The growth in median and mean holdings of stocks is largely explained by the widespread increase in stock market indexes between 2010 and 2013.¹⁹ However, some of the increase in conditional holdings might be due to exits from ownership, if those who exited tended to have stock holdings of lower value.²⁰

Ownership of retirement accounts--including individual retirement accounts (IRAs), Keogh accounts, and certain employer-sponsored accounts, such as 401(k), 403(b), and thrift savings accounts--fell below 50 percent in 2013, continuing the downward trend also observed between the 2007 and 2010 surveys. Median and mean values of retirement accounts, however, rose substantially. The conditional median value of retirement accounts rose 25 percent from $47,200 in 2010 to $59,000 in 2013; and the mean value rose 10 percent, from $183,400 in 2010 to $201,300 in 2013. This growth is likely explained by a combination of resurgent stock markets and increased contributions by those who participated in retirement plans.²¹

The percent of families owning the remaining financial asset categories--cash value of life insurance, other managed assets, and the catch-all "other" category--declined between 2010 and 2013. The median and mean values of other managed assets moved in line with stocks and retirement accounts, and they reflected the positive effect of the stock market on the value of assets in these portfolios.

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Nonfinancial Assets

Ownership of nonfinancial assets--including vehicles, residential and nonresidential property, and business equity--remained high in 2013 at 91.0 percent, falling only slightly from 2010. For every separate category of nonfinancial assets except "other," however, ownership rates fell. These patterns indicate that most families still hold a nonfinancial asset, but they hold fewer types than were held in 2010.

The most commonly held type of nonfinancial asset in 2013 was vehicles, a very broad category that includes cars, vans, sport utility vehicles, trucks, motor homes, recreational vehicles, motorcycles, boats, airplanes, and helicopters. Between 2010 and 2013, the fraction of families owning a vehicle declined slightly from 86.7 percent to 86.3 percent. The median and mean value of vehicles owned by families also fell between 2010 and 2013. The median value decreased from $16,300 to $15,800, and the mean declined from $23,700 to $22,600 between 2010 and 2013.²²

Housing ownership also fell, both for primary residences and for other residential property. Ownership declined from 67.3 percent of families owning a primary residence in 2010 to 65.2 percent owning a primary residence in 2013. This decrease represented a continued decline since the 2004 SCF was conducted, when the homeownership rate was 69.1 percent.²³

The conditional median and mean value of primary residences also fell in real terms, 7 percent and 6 percent, respectively. Among families who are homeowners, the median family's home was worth $170,000 in 2013, down from $182,200 in 2010. The decline in respondent-reported home values between the two most recent surveys is a little surprising, given the widespread perception that house values have stabilized and partially recovered in most areas. However, inflation-adjusted national home price indexes showed slight declines over the period between the onsets of field work for the two most recent surveys.²⁴ In addition, the divergence in house price trends is well within empirical estimates of homeowner reporting bias in house values, and it may reflect a correction in perceived values following the housing boom period, during which houses may have been overvalued by respondents.²⁵ It is also worth noting that since the 2013 survey was administered, house price indexes have increased substantially.

Ownership and median values of other residential property, which includes residences such as second homes and time shares, also fell between 2010 and 2013. Mean values of other residences increased slightly.

The largest relative drop in ownership rates of any type of nonfinancial asset was in the category of business equity, where ownership rates fell from 13.3 percent to 11.7 percent. The median family with business equity also experienced a decline of 20 percent in value, with median business equity falling from $84,400 to $67,500 between 2010 and 2013. The mean value of business equity rose 15 percent. This change indicates that losses in business equity were not equally distributed, and many business-owning families experienced large gains, while the median business-owning family experienced a loss.²⁶

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Debt, Debt Burden, and Credit Market Experiences

The fractions of families holding any type of debt fell slightly between 2010 and 2013, from 74.9 percent to 74.5 percent, representing a continued decline in debt holding since 2007 (table 4).²⁷ The conditional median and mean value of debt held also fell between 2010 and 2013. The conditional median fell 20 percent, from $75,800 in 2010 to $60,400 in 2013. The conditional mean also fell, from $140,000 in 2010 to $122,300 in 2013, a decline of 13 percent.

Table 4. Holding and values of debt items, 2010 and 2013 surveys
Thousands of 2013 dollars except as noted

Types of debts	Percent holding		Conditional median value			Conditional mean value
	2010	2013	2010	2013	Percent change 2010-13	2010	2013	Percent change 2010-13
Any debt	74.9	74.5	75.8	60.4	-20	140.0	122.3	-13
Secured by residential property
Primary residence	47.0	42.9	117.5	115.0	-2	165.4	156.7	-5
Other	5.3	5.2	105.0	90.0	-14	192.4	156.1	-19
Lines of credit not secured by residential property	2.1	1.9	6.4	4.4	-32	52.7	35.2	-33
Installment loans
Education loans	19.2	20.0	13.9	16.0	15	27.5	28.9	5
Vehicle loans	30.2	30.9	10.7	11.9	11	15.2	14.6	-4
Other installment loans	11.5	10.1	3.6	3.3	-9	15.9	15.9	0
Credit card balances	39.4	38.1	2.8	2.3	-18	7.6	5.7	-25
Other	6.4	6.6	4.8	4.0	-17	18.0	14.6	-19

Note: See the appendix for definitions of liability categories used in the SCF.

Debt Holdings by Type

Between 2010 and 2013, the mix of debt held by families also changed. Fewer families held debt secured by a primary residence, and those that did have such types of debt owed smaller amounts. However, more families held education loans in 2013 than in 2010, and those with education loans owed larger amounts on the loans.

Paralleling the drop in homeownership, rates of holding of debt secured by a primary residence (hereafter, home-secured debt) fell between 2010 and 2013. The fraction of families with mortgages and other home-secured debt fell from 47.0 percent in 2010 to 42.9 percent in 2013. This decline was much larger than the 3.3 percent decrease in homeownership noted previously.

However, home-secured debt continued to be the most common type of debt held by families. The conditional median and mean values of home-secured debt also fell between 2010 and 2013. The conditional median value of home-secured debt fell 2 percent, from $117,500 to $115,000. The conditional mean value of home-secured debt fell 5 percent, from $165,400 to $156,700. The declines in holding and the conditional mean and median values of home-secured debt represented a continuation of declines seen between 2007 and 2010.²⁸ These declines also parallel the declines in home values seen between 2010 and 2013 (table 3), although the declines in the value of debt are much smaller than the declines in home values (2 percent versus 7 percent).

Lines of credit not secured by residential property were not widely held by families in either the 2010 or 2013 surveys, at around 2 percent of families. The decline in conditional debt outstanding among those with such debts are quite substantial, with both the median and mean values falling by about one-third between 2010 and 2013.

The fraction of families with education loans, and the conditional median and mean value of education loans, increased between 2010 and 2013, representing a continuation of the long-term trend of rising education debt. In 2010, 19.2 percent of families had an education loan. This share rose to 20.0 percent of families in 2013. The conditional median value of education loans rose 15 percent, from $13,900 in 2010 to $16,000 in 2013. The mean rose 5 percent, from $27,500 to $28,900.²⁹

As discussed earlier, the fraction of families owning a vehicle fell slightly between 2010 and 2013, to 86.3 percent. At the same time, the fraction of families with vehicle loans increased slightly, and in 2013, 30.9 percent of families had vehicle loans. This finding represented a reversal of the trend between 2007 and 2010, when the fraction of families with a vehicle loan fell. Between 2010 and 2013, the conditional median value of vehicle loans rose 11 percent and the conditional mean fell 4 percent. This movement indicates that although fewer families have vehicles overall, families are beginning to take out more loans on vehicles.

Other installment loans, often associated with purchases of furniture, appliances, and other durable goods, were held by 11.5 percent of families in 2010, falling to 10.1 percent of families in 2013. The median balances on such loans decreased 9 percent between the two surveys, and the mean was effectively unchanged.

The fraction of families with outstanding balances on their credit cards fell between 2010 and 2013, representing a continuation of declines seen between 2007 and 2010. In 2010, 39.4 percent of families held credit card debt, while in 2013, 38.1 percent of families held credit card debt.** The median family with a credit card balance carried $2,300 in 2013, down 18 percent from $2,800 in 2010. The mean balance fell from $7,600 in 2010 to $5,700 in 2013, a 25 percent drop.

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Debt Burden

The ability of individual families to service their loans is a function of two factors: the level of their loan payments and the income and assets they have available to meet those payments. In planning their borrowing, families make assumptions about their future ability to repay their loans. Problems may occur when events turn out to be contrary to those assumptions. If such misjudgments are sufficiently large and prevalent, a broad pattern of default, restraint in spending, and financial distress in the wider economy might ensue (such as was seen in the period after the 2007 survey).

The SCF data can be used to construct three measures of debt burdens: leverage ratios, debt-to-income ratios, and payment-to-income ratios. Leverage ratios compare debts to assets, debt-to-income ratios compare total debt to income, and payment-to-income ratios compare total payments made on debt to income. All three ratios can be constructed either in aggregate or as a median for debtors.³⁰

Leverage ratios, debt-to-income ratios, and payment-to-income ratios all rose between 2001 and 2010 and then fell between 2010 and 2013 (table 5).³¹ Leverage ratios and debt-to-income ratios have not fallen back to levels seen in 2001, but payment-to-income ratios are lower than levels seen in 2001.

Table 5. Debt burdens and credit market experiences, 2001-13 surveys
Percent or thousands of 2013 dollars

Measure of debt burden/interaction with credit markets	2001	2004	2007	2010	2013
Debt burden
Leverage ratio
Aggregate	12.0	15.0	14.8	16.4	14.6
Median for debtors	29.4	34.7	34.8	41.3	38.6
Debt to income ratio
Aggregate	80.1	111.6	115.2	124.7	104.6
Median for debtors	76.7	107.0	111.1	118.8	107.4
Payment to income ratio
Aggregate	12.9	14.4	14.6	14.7	12.0
Median for debtors	16.7	18.1	18.7	18.1	15.9
Fraction with payment to income ratio greater than 40%	8.8	9.4	11.4	10.4	8.2
Credit market experiences
Credit constrained
Turned down for credit	17.0	17.5	16.7	17.4	16.4
Did not apply for credit for fear of being turned down	15.5	15.8	15.3	18.5	19.0
Either turned down for credit or feared denial	24.9	25.6	24.5	28.3	27.6
Late on payments
Late on payments	14.0	16.3	20.8	17.3	14.9
Late on payments 60 days or more	5.3	6.9	5.5	8.1	6.9
Took out a payday loan in past year	n.a.	n.a.	2.4	3.9	4.2
Declared bankruptcy in past 5 years	4.3	4.4	3.8	3.6	4.1
Use credit cards for convenience only/do not carry a balance	57.9	56.6	56.2	63.0	64.0

n.a. Not available (relevant data not collected).

Note: See the appendix for a description of measures of debt burden and credit market experiences.

In 2013, the median leverage ratio for debtors was 38.6 percent, down from 41.3 percent in 2010 but still higher than the medians of 29.4 percent in 2001 or 34.8 percent in 2007. In aggregate, the leverage ratio in 2013 was 14.6 percent, higher than 2001 but lower than the 2004-10 period.

In 2013, the median debt-to-income ratio for debtors was 107.4 percent, down from the level seen in 2010 (118.8 percent). The level in 2013 is similar to that witnessed in 2004, and similar trends can be seen for the aggregate.

Payment-to-income ratios for the median debtor fell from 18.1 percent to 15.9 percent between 2010 and 2013.³² The 2013 level is lower than what was observed in any of the survey years between 2001 and 2010. Similar trends held in the aggregate payment-to-income ratios.

A limitation of using measures of debt burdens for the median debtor is that they may not be indicative of distress because they reflect the situation of a typical family. Unless errors of judgment by both families and lenders are pervasive, one would not expect to see signs of financial distress at the median. Thus, a more compelling indicator of distress is the proportion of families with unusually large debt burdens. In 2013, 8.2 percent of debtors had payment-to-income ratios greater than 40 percent. This value represents a decrease from 2010, when 10.4 percent of debtors had payment-to-income ratios of over 40 percent. The levels in 2013 are lower than those witnessed at any time between 2001 and 2010.

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Credit Market Experiences

The SCF also collects various measures of respondents' recent experiences with credit markets, such as information on credit applications and payment behavior. Overall, SCF respondents' experiences with credit markets display a mixed picture. The fraction of respondents who were late on payments fell, while the fraction who took out a payday loan rose, and credit constraints eased slightly.

The SCF asks two questions intended to capture whether or not families are likely credit constrained: first, if the family was turned down for credit, and, second, if the family did not apply for credit for fear of being turned down. Overall, between 2010 and 2013, the fraction of families that responded "yes" to one or both of these questions fell from 28.3 percent in 2010 to 27.6 percent in 2013. This decrease indicates that, by this measure, fewer families were credit constrained in 2013 than in 2010. There was also a change in composition within this category between 2010 and 2013: More families reported not applying for fear of being turned down in 2013 than in 2010, while fewer families reported being turned down for credit in 2013 than in 2010. In fact, 2010 and 2013 were the first survey years that more families reported not applying for fear of being turned down (19 percent in 2013) than reported being turned down (16.4 percent in 2013).

The SCF also asks respondents if they have taken out a payday loan in the past year. Payday loans are unsecured loans that are typically small and short-term. Because these loans generally carry interest rates that far exceed those for conventional forms of credit, usage of payday loans is often a signal that an individual cannot obtain credit by other means. In 2013, 4.2 percent of families reported taking out a payday loan, up from 3.9 percent in 2010 and 2.4 percent in 2004, the first year the SCF asked respondents about usage of payday loans.

The SCF also collects information on families' debt payment behavior. Families that have any debt at the time of their interview are asked whether they were behind on any of their loan payments in the preceding year. In 2013, 14.9 percent of families reported being late on payments at all, down from 17.3 percent in 2010. The percent of families who reported being late on payments 60 or more days declined from 8.1 percent in 2010 to 6.9 percent. Compared with 2001, more families reported being late on payments at all in 2013, and more reported being late 60 or more days.

An additional measure of financial distress and problems managing debt is bankruptcy. The SCF asks respondents if they have declared bankruptcy in the past five years. In 2013, 4.1 percent of families reported having declared bankruptcy in the past five years, up from 3.6 percent in 2010 but down from 4.3 percent in 2001.

A final measure of debt payment behavior covered in the SCF is whether a family uses credit cards for convenience only, or carries a balance month to month. In 2013, 64 percent of families reported using credit cards for convenience only (not carrying a balance), up from 57.9 percent in 2001 and 63 percent in 2010.

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Appendix: Survey Procedures and Statistical Measures

The 2013 data used here are derived from the final internal version of the survey information. Data from this survey, suitably altered to protect the privacy of respondents, along with additional tabulations of data from the surveys beginning with 1989, are expected to be available in September 2014 on the Federal Reserve Board's website.³³

As part of the general reconciliations required for this article, the survey data were compared with many external estimates. One particularly important comparison is between the Survey of Consumer Finances (SCF) and the Federal Reserve's Statistical Release Z.1, Financial Accounts of the United States, for the household sector.³⁴ This comparison suggests that when the definitions of the variables in the two sources are adjusted to a common conceptual basis, the estimates of totals in the two systems tend to be close. The data series in the SCF and in Statistical Release Z.1 usually show very similar growth rates.³⁵ In general, the income and net worth data from the SCF can be compared with those of other surveys only in terms of the medians because of the special design of the SCF sample.³⁶

Adjustment for Inflation

In this article, all dollar amounts from the SCF are adjusted to 2013 dollars using the "current methods" version of the CPI for all urban consumers. In an ongoing effort to improve accuracy, the Bureau of Labor Statistics has introduced several revisions to its CPI methodology. The current-methods index attempts to extend these changes to earlier years to obtain a series as consistent as possible with current practices in the official CPI.³⁷ To adjust assets and liabilities to 2013 dollars and to adjust family income for the preceding calendar year to 2013, the figures given in the following table were applied:

Survey year	Adjustment factor for assets and debts in the survey year	Adjustment factor for income in the calendar year before the survey year
2001	1.3132	1.3501
2004	1.2331	1.2665
2007	1.1228	1.1546
2010	1.0717	1.0894
2013	1.0000	1.0145

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Definition of "Family" in the Survey of Consumer Finances

The definition of "family" used throughout this article differs from that typically used in other government studies. 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 person or couple (whether married or living together as partners) and all other persons in the household who are financially interdependent with that economically dominant person or couple.

This report also designates a head of the PEU, not to convey a judgment about how an individual family is structured but as a means of organizing the data consistently. If a couple is economically dominant in the PEU, the head is the male in a mixed-sex couple or the older person in a same-sex couple. If a single person is economically dominant, that person is designated as the family head in this report.

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Asset and Liability Categories in the Survey of Consumer Finances

The specific concepts of asset and liability categories in the SCF are necessarily tied to the survey question wording and associated field interviewer instructions, both of which can be found in the SCF codebook for the year(s) in question.³⁸ What follows is a general exposition of the asset and liability categories reported in the tables.

Transaction accounts include checking, savings, and money market deposit accounts; money market funds; and call or cash accounts at brokerages. Call accounts include those that hold money received from the sale of securities until the money is reinvested. The savings account category includes a relatively small number of tax-preferred accounts such as medical or health savings accounts and Coverdell or 529 education accounts.

Certificate of deposits are accounts that are held for a set period of time that must be cashed or renewed at the maturity date. Savings bonds include only U.S. government issues; recent series include EE, HH, and I, and older bonds may be series E and H. Other bonds include only those held directly (not part of a managed investment account or bond fund) and include corporate and mortgage-backed bonds; federal, state, and local government bonds; and foreign bonds. Stocks include publicly traded stocks that are directly held--that is, corporate equities not held as part of a managed investment account or mutual fund.

Pooled investment funds include stock funds, tax-free bond funds, government bond funds, other bond funds, and any combinations thereof, but exclude money market funds and indirectly held mutual funds. These funds include all other types of directly held pooled investments, such as traditional open-end and closed-end mutual funds, real estate investment trusts, and hedge funds.

Retirement accounts include IRAs, Keogh accounts, and certain employer-sponsored accounts, such as 401(k), 403(b), and thrift savings accounts from current or past jobs; other current job plans from which loans or withdrawals can be made; and accounts from past jobs from which the family expects to receive the account balance in the future. This definition of employer-sponsored plans is intended to confine the analysis to accounts that are portable across jobs and for which families will ultimately have the option to withdraw the balance. Usually, such accounts may be invested in virtually any asset, including stocks, bonds, pooled investment funds, options, and real estate. In principle, employer-sponsored plans may be invested in a similarly broad way, but, in practice, a person's choices for investment are sometimes limited to a narrower set of assets.³⁹

Cash value life insurance is the current (nonzero) value of any life insurance policies with a cash value that can be withdrawn. The survey measures the value of such policies according to their current cash value, not their death benefit. In this article, the cash value is included as an asset only when the cash value at the time of the interview was nonzero. This designation excludes term life insurance policies, which only provide a death benefit.

Other managed assets include personal annuities and trusts with an equity interest and managed investment accounts. Annuities may be those in which the family has an equity interest in the asset or in which the family possesses an entitlement only to a stream of income. The wealth figures in this article include only the annuities in which the family has an equity interest.⁴⁰ The trusts or managed investment accounts included in other managed assets are those in which families have an equity interest and for which components were not separately reported. Typically, such accounts are those in which the ownership is complicated or the management is undertaken by a professional.⁴¹

Other financial assets include oil and gas leases, futures contracts, royalties, proceeds from lawsuits or estates in settlement, and loans made to others. One specific financial asset excluded from this category and any other is employment-related stock options. Because such options are typically not publicly traded, or their execution is otherwise constrained, their value is uncertain until the exercise date; until then, meaningful valuation would require complex assumptions about the future behavior of stock prices.

Vehicles include cars, vans, sport utility vehicles, trucks, motor homes, recreational vehicles, motorcycles, boats, airplanes, and helicopters.⁴² Primary residences include mobile homes and their sites, the parts of farms and ranches not used for farming or ranching business, condominiums, cooperatives, townhouses, other single-family homes, and other permanent dwellings. Other residential property includes second homes, time-shares, one- to four-family rental properties, and other types of residential properties. It also includes outstanding balances on loans that the family may have made to finance the sale of properties they previously owned and which are still owed to the family.

Nonresidential real estate includes the following types of properties unless they are owned through a business: commercial property, rental property with five or more units, farm and ranch land, undeveloped land, and all other types of nonresidential real estate. Most often, nonresidential real estate properties are functionally more like a business than a residential property. They may have several owners, they are typically worth a considerable amount, and they often carry large mortgages, which appear to be paid using the revenues from the property, not the family's other income. As in the case of privately owned businesses, the value of the property in this analysis is taken to be the net value.

Business equity includes net worth in the following forms of business: sole proprietorships, limited partnerships, other types of partnerships, S corporations and other types of corporations that are not publicly traded, limited liability companies, and other types of private businesses. If the family lived on a farm or ranch that was used at least in part for agricultural business, the value of that part, net of the corresponding share of associated debts, is included with other business assets. In the survey, self-employment status and business ownership are independently determined.⁴³

Debt secured by residential property consists of first-lien and junior-lien mortgages and home equity lines of credit (HELOCs) secured by the primary residence. For purposes of this article, first- and junior-lien mortgages consist only of closed-end loans--that is, loans typically with a one-time extension of credit, a set frequency of repayments, and a required repayment size that may be fixed or vary over time in accordance with a pre-specified agreement or with changes in a given market interest rate.⁴⁴ As a type of open-ended credit, HELOCs typically allow credit extensions at the borrower's discretion subject to a prearranged limit and allow repayments at the borrower's discretion subject to a prearranged minimum size and frequency.

Lines of credit not secured by residential property are any lines of credit except HELOCs and borrowing on credit cards.

The term "installment loan" describes closed-end consumer loans--that is, loans that typically have fixed payments and a fixed term. The most common examples are education loans; automobile loans; and loans for furniture, appliances, and other durable goods. Other installment loans include all closed-end consumer loans that are not for education or a vehicle--that is, loans that typically have fixed payments and a fixed term. Examples include loans for furniture, appliances, and other durable goods.

Credit card balances consist of balances on bank-type cards (such as Visa, MasterCard, and Discover as well as Optima and other American Express cards that routinely allow holders to carry a balance), store cards or charge accounts, gasoline company cards, so-called travel and entertainment cards (such as American Express cards that do not routinely allow holders to carry a balance and Diners Club), other credit cards, and revolving store accounts that are not tied to a credit card. Balances exclude purchases made after the most recent bill was paid.

The "other" debt category comprises loans on cash value life insurance policies, loans against pension accounts, borrowing on margin accounts, and a miscellaneous category largely comprising personal loans not explicitly categorized elsewhere.

Finally, the SCF measure of liabilities excludes debt owed by family-owned businesses and debt owed on nonresidential real estate; in this article, such debt is netted against the corresponding assets.

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Measures of Debt Burden and Credit Market Experiences in the Survey of Consumer Finances

The SCF includes several questions designed to capture information about respondents' debt burdens and interactions with credit markets. The specific concepts addressed in the SCF are necessarily tied to the survey question wording and associated field interviewer instructions, which can be found in the SCF codebook for the year(s) in question.⁴⁵ What follows is a general exposition of the debt burden and credit market experience measures reported in the tables.

Leverage ratios compare the total of all debts to the total of all assets. The aggregate version of this measure is the sum of all debts for all SCF respondents, divided by the sum of all assets for SCF respondents. The median for debtors is the median of each individual family's leverage ratio and is calculated for those with positive values of total debt only.

The aggregate debt-to-income ratio is the sum of liabilities for all SCF respondents, divided by the total income for all SCF respondents. The median for debtors is the 50th percentile of an individual family's debt-to-income ratios and is calculated for those with positive values of total debt only.

Payment-to-income ratios measure total debt payments relative to total income.⁴⁶ The aggregate version of this measure is the sum of all debt payments for all SCF respondents, divided by total income for all SCF respondents. The median for debtors is the 50th percentile of an individual family's payment-to-income ratios and is calculated for those with positive values of total debt only.

It should be recognized that the aggregate measure of payment-to-income ratios that is referenced in this article can differ from aggregate measures constructed from other sources such as the debt service ratio.⁴⁷ The survey measure of payments relative to income can differ from the aggregate-level measure for several reasons. First, the debt payments included in each measure are different. The aggregate-level measure includes only debts originated by depositories, finance companies, and other financial institutions, whereas the survey includes, in principle, debts from all sources. Second, the aggregate-level measure uses an estimate of disposable personal income from the national income and product accounts for the period concurrent with the estimated payments as the denominator of the ratio, whereas the survey measure uses total before-tax income reported by survey families for the preceding year; the differences in these two income measures are complex. Third, the payments in the aggregate-level measure are estimated using a formula that entails many assumptions about minimum payments and the distribution of loan terms at any given time; the survey measure of payments is directly asked of the survey respondents but may also include payments of taxes and insurance on real estate loans. Fourth, because the survey measures of payments and income are based on the responses of a sample of respondents, they may be affected both by sampling error and by various types of response errors. As mentioned earlier in this article, the survey income measure tracks the most comparable measure of income in the Census Bureau's Current Population Survey (CPS).

The SCF asks two questions that are intended to capture whether or not families are credit constrained, which is broadly defined as having difficulty accessing credit. The first question asks the respondent if the family was turned down for credit at any point in the past year. The second asks if, within the past year, the family did not apply for credit for fear of being turned down. A combination of these two questions is used to measure overall credit constraints.

Delinquency on debt obligations is captured by asking families that have any debt at the time of their interview whether or not they have been behind in any of their loan payments in the preceding year. The survey asks if respondents have been behind at all and if they have been behind in payments for 60 or more days.

Payday loans are defined as loans that are meant to be repaid in full out of the respondent's next paycheck; they are unsecured loans that are typically small, short-term, and carry above-average interest rates.

Bankruptcy behavior is a retrospective question in which the respondent reports whether or not he had declared bankruptcy at any time in the past five years.

Finally, convenience use of credit cards is determined using questions on whether or not a respondent had positive balances after the most recent payment for bank-type cards (such as Visa, MasterCard, and Discover as well as Optima and other American Express cards that routinely allow holders to carry a balance), store cards, gasoline company cards, so-called travel and entertainment cards (such as American Express cards that do not routinely allow holders to carry a balance and Diners Club), and other credit cards.

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Percentiles of the Distributions of Income and Net Worth

Throughout this article, references are made to various percentile groups of the distributions of income or net worth. For a given characteristic, a percentile can be used to define a family's rank relative to other families. For example, the 10th percentile of the distribution of usual income is the amount of income received by a family for whom less than 10 percent of other families have lower incomes and 90 percent have higher incomes. The percentiles of the distributions of income and net worth used to define the income and net worth groups in table 1 and table 2 in the article are given in the following table:

Item	Survey year
	2001	2004	2007	2010	2013
Percentile of usual income
20	24,300	25,800	25,200	26,200	23,300
40	43,200	44,300	43,300	43,600	40,500
60	67,500	69,700	69,300	67,500	63,100
80	108,000	112,700	110,200	108,900	104,500
90	155,300	164,600	155,900	163,400	154,600
Percentile of net worth
25	16,800	16,400	15,900	8,900	8,800
50	113,700	114,800	135,400	82,800	81,200
75	377,000	405,900	418,600	323,300	317,300
90	972,000	1,028,400	1,022,100	1,020,800	941,700

The groups that are created when a distribution is divided at every 10th percentile are commonly referred to as deciles. Similarly, when a distribution is divided at every 20th (25th) percentile, the groups are known as quintiles (quartiles). Families in the first income decile, for example, are those with income below the 10th percentile.

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Racial and Ethnic Identification

In this article, the race and ethnicity of a family in the SCF are classified according to the self-identification of that family's original respondent to the SCF interview. The questions underlying the method of classification used in the survey were changed in both 1998 and 2004. Starting in 1998, SCF respondents were allowed to report more than one racial identification; in surveys before then, only one response was recorded. For maximum comparability with earlier data, respondents reporting multiple racial identifications were asked to report their strongest racial identification first. In the 2013 SCF, 6.1 percent of respondents reported more than one racial identification, up from 5.4 percent in 2007 and 2.3 percent in 2004.

Beginning with the 2004 survey, the question on racial identification is preceded by a question on whether respondents consider themselves to be Hispanic or Latino in culture or origin; previously, such ethnic identification was captured only to the extent that it was reported as a response to the question on racial identification. The sequence of these two questions in the 2004 SCF is similar to that in the CPS. When families in the March 2004 CPS are classified in a way that is most compatible with the SCF, the proportion of Hispanic families is 10.5 percent; the 2004 SCF estimate is 11.2 percent. Differences in these proportions are attributable to sampling error and possibly to differences in the wording and context of the questions.

For greater comparability with earlier SCF data, the data reported in this article ignore the information on ethnic identification available in the surveys since 2004, but respondents reporting multiple racial identifications in the surveys starting with 1998 are classified as "non-white or Hispanic." Of those who responded affirmatively to the question on Hispanic or Latino identification in 2013, 88.1 percent also reported "Hispanic or Latino" as one of their racial identifications, and 80.1 percent reported it as their primary racial identification. Because the question on Hispanic or Latino ethnicity precedes the one on racial identification in the surveys from 2004 through 2013, the answer to the second of these two questions may have been influenced by the answer to the first.⁴⁸

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The Sampling Techniques

The survey is expected to provide a core set of data on family income, assets, and liabilities. The major aspects of the sample design that address this requirement have been constant since 1989. The SCF combines two techniques for random sampling. First, a standard multistage area-probability sample (a geographically based random sample) is selected to provide good coverage of characteristics, such as homeownership, that are broadly distributed in the population.

Second, a supplemental sample is selected to disproportionately include wealthy families, which hold a relatively large share of such thinly held assets as noncorporate businesses and tax-exempt bonds. Called the "list sample," this group is drawn from a list of statistical records derived from tax returns. These records are used under strict rules governing confidentiality, the rights of potential respondents to refuse participation in the survey, and the types of information that can be made available. Persons listed by Forbes magazine as being among the wealthiest 400 people in the United States are excluded from sampling.

Of the 6,026 interviews completed for the 2013 SCF, 4,568 were from the area-probability sample, and 1,458 were from the list sample; for 2010, 5,012 were from the area-probability sample, and 1,480 were from the list sample. The number of families represented in the surveys considered in this article is given by the following table:

Year	Number of families represented (millions)
2001	106.5
2004	112.1
2007	116.1
2010	117.6
2013	122.5

Overall population growth between 2010 and 2013 was 2.4 percent, according to figures from the Census Bureau, down slightly from the 2.5 percent growth rate between 2007 and 2010. Also according to Census Bureau estimates, the number of households increased 4.2 percent between 2010 and 2013--well above the greatly diminished rate of household formation between 2007 and 2010, which was 1.3 percent. With the population growing more slowly than household formation, the average number of persons per household fell slightly, from 2.63 people in 2010 to 2.58 in 2013.

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The Interviews

Aside from the addition of new questions in the 2010 survey to address the financial relationships of businesses that are not publicly traded, the survey questionnaire has changed in only minor ways since 1989, except in a small number of instances in which the structure was altered to accommodate changes in financial behaviors, in types of financial arrangements available to families, and in regulations covering data collection. In these cases and in all earlier ones, every effort has been made to ensure the maximum degree of comparability of the data over time. Except where noted in the article, the data are highly comparable over time.

The generosity of families in giving their time for interviews has been crucial to the ongoing success of the SCF. In the 2010 SCF, the median interview length was about 85 minutes. However, in some particularly complicated cases, the amount of time needed was substantially more than three hours. The role of the interviewers in this effort is also critical. Without their dedication and perseverance, the survey would not be possible.

The SCF interviews were conducted largely between the months of May and December in each survey year by NORC, a social science and survey research organization at the University of Chicago. The majority of interviews were obtained in person, although interviewers were allowed to conduct telephone interviews if that was more convenient for the respondent. Each interviewer used a program running on a laptop computer to administer the survey and collect the data.

The use of computer-assisted personal interviewing has the great advantage of enforcing systematic collection of data across all cases. The computer program developed to collect the data for the SCF was tailored to allow the collection of partial information in the form of ranges whenever a respondent either did not know or did not want to reveal an exact dollar figure.

The response rate in the area-probability sample is more than double that in the list sample. In both 2010 and 2013, about 70 percent of households selected for the area-probability sample actually completed interviews. The overall response rate in the list sample was about one-third; in the part of the list sample likely containing the wealthiest families, the response rate was only about one-half that level.

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Weighting

To provide a measure of the frequency with which families similar to the sample families could be expected to be found in the population of all families, an analysis weight is computed for each case, accounting both for the systematic properties of the sample design and for differential patterns of nonresponse. The SCF response rates are low by the standards of some other major government surveys, and analysis of the data confirms that the tendency to refuse participation is highly correlated with net worth. However, unlike other surveys, which almost certainly also have differential nonresponse by wealthy households, the SCF has the means to adjust for such nonresponse. A major part of SCF research is devoted to the evaluation of nonresponse and adjustments for nonresponse in the analysis weights of the survey.⁴⁹

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Sources of Error

Errors may be introduced into survey results at many stages. Sampling error--the variability expected in estimates based on a sample instead of a census--is a particularly important source of error. Such error can be reduced either by increasing the size of a sample or, as is done in the SCF, by designing the sample to reduce important sources of variability. Sampling error can be estimated, and for this article we use replication methods to do so.

Replication methods draw samples, called replicates, from the set of actual respondents in a way that incorporates the important dimensions of the original sample design. In the SCF, weights were computed for all of the cases in each of the replicates.⁵⁰ Every value for which standard errors are reported in this article is a weighted statistic estimated using the replicate samples. To estimate the overall standard error, a measure of the variability of these estimates is combined with a measure of the variability because of imputation for missing data.

Other errors include those that interviewers may introduce by failing to follow the survey protocol or misunderstanding a respondent's answers. SCF interviewers are given lengthy, project-specific training and ongoing coaching to minimize such problems. Respondents may introduce error by interpreting a question in a sense different from that intended by the survey. For the SCF, extensive pretesting of questions and thorough review of the data tend to reduce this source of error.

Nonresponse--either complete nonresponse to the survey or nonresponse to selected items within the survey--may be another important source of error. As noted in more detail previously, the SCF uses weighting to adjust for differential nonresponse to the survey. To address missing information on individual questions within the interview, the SCF uses statistical methods to impute missing data; the technique makes multiple estimates of missing data to allow for an estimate of the uncertainty attributable to this type of nonresponse.

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