Created Variables

NET_WORTH: These variables contain the total net worth amount (assets - debts) for each survey year in which assets information was collected (1985-1990, 1992-2000, 2004, 2008, and 2012).


Important Information About Using Assets Data

The NLSY79 cohort is a unique source of wealth information. Because the original NLSY79 panel contains a supplemental sample of 5,295 blacks, Hispanics or Latinos, and economically disadvantaged nonblack/non-Hispanics, researchers are able to precisely measure wealth for low-income and minority households. For more information, see Zagorsky (1997).

The Assets, Debts & Expenditures section is divided into the following subsections:

General Information about Assets Questions

From the first survey year, NLSY79 respondents have been asked about their savings, home, and vehicle ownership. Over the course of the survey, these questions provide information on when saving begins, how savings habits are formed, and how persistent savings habits are.

Each of the first four surveys (1979-1982) contain identical sets of questions asking if the respondent or their spouse had any money set aside for savings, owned a vehicle, or owned their own home. In those early years however, the respondent was not asked how much savings were held, the value or number of vehicles, or the value of, and mortgage on, their home. Additionally, respondents were only asked questions on assets if they met one of following five criteria:

  • 18 years old or greater
  • Had a child
  • Enrolled in college
  • Married
  • Living outside their parents' home

This selection process eliminated many respondents from these questions. Early NLSY79 data show that few individuals answered the questions until they turned 18 years old. For example, in 1979 only five percent of those interviewed under age 18 answered the asset questions. Except for the question on home ownership, asset questions were dropped during 1983 and 1984. Beginning in 1985, when all respondents had turned 18, NLSY79 respondents were administered a much larger wealth section. As Table 1 shows, respondents were given the opportunity to answer approximately 20 questions about a variety of asset and debt holdings. In most years respondents estimated how much their home, cash savings, stock and bond portfolio, estate, business, and automobile were worth. Additionally, respondents estimated how much mortgage debt, property debt, and other debt they had accumulated. Together these variables provide a rough overview of the net worth of each respondent. As the cohort has aged, the wealth section has grown in length and detail.

Table 1. NLSY79 Asset Questions 1985 to 20141

Question 85 86 87 88 89 90 92 93 94 96 98 00 04 08 12 14
Own Home/Apartment; Market Value * * * * * * * * * * * * * * *  
Amount Owed on Property * * * * * * * * * * * * * * *  
Amount Other Home Debt * * * * * * * * * * * * * * *  
Have Money Assets; Amount * * * * * * * * * * * * * * *  
Did Savings Change; Amount       *                        
Have Common Stock, Bonds; Value       * * * * * * * * * * * *  
Hold Money in IRA/Keogh; Amount                 * * * * * * *  
Hold Money in 401k/403b; Amount                 * * * * * * *  
Hold Money in CDs; Amount                 * * * * * * *  
Rights to Estate/Trust; Value       * * * * * * * * * * * *  
Own Farm/Bus/Real Estate; Market Value * * * * * * * * * * * * * * *  
Amount Debts Farm/Bus/Real Estate * * * * * * * * * * * * * * *  
Own Vehicles for Own Use; Market Value * * * * * * * * * * * * * * *  
Owe Any Money on Vehicles; Amount * * * * * * * * * * * * * * *  
Make/Model/Year of Car *                              
Own Items over $1000; Value * * * * * * * * * * * * * * *  
Owe over $1000; Amount owed * * * * * * * * * * * * * * * *
Amount R would have left if paid off debts           * * * * * * * * * * *
1 Assets module was not included in the 1991, 2002, 2006, 2010, and 2014 surveys.

Top Coding

Because the NLSY79 is a public use data set that is distributed widely throughout the research and public policy communities, the survey takes extensive measures to protect the confidentiality of respondents. One method of ensuring confidentiality is to "top code" unusually high values.

The NLSY79 has used three top coding algorithms for assets. From 1979 to 1988, every NLSY79 asset question that elicited a response above a specified cutoff value, such as $100,000 for some income variables, was recoded to the truncation value plus one dollar, such as $100,001. Unfortunately this algorithm results in a sharp downward bias in the mean value of NLSY79 asset holdings since the entire right hand tail is truncated. To address this problem, beginning in 1989, a new algorithm was implemented. The new top code algorithm replaces all values above the cutoff with the average of all outlying values.

Beginning in 1996, the top two percent of respondents with valid values were identified. Values within that top range were averaged and that averaged value replaced all values in the top range.

The extent of top coding for NLSY79 asset questions varies greatly. For example, in 1993 there were only two individuals whose money assets exceeded the cut-off value of $500,000, while 581 individuals gave a market value for their residence above the cut-off value of $150,001. While top-coding presents problems in analysis of individual observations and alters some statistical properties, the new algorithm does not affect the estimates of mean and median holdings. Table 2 shows the number of people shielded by top codes in both 1985 and 1993.

Table 2. Number and Percentage of Respondents Whose Assets Were Top Coded in 1985 and 1993

  1985 Percentage 1985 Number 1993 Percentage 1993 Number Cut-off Value
Market Value of Property 0.3 18 8.5 581 $150,000
Property Mortgage 0.1 7 2.3 159 $150,000
Other Property Debts 0.0 0 0.0 1 $150,000
Money Assets 0.0 3 0.0 2 $500,000
Value Farm/Bus/Other Property 0.2 12 0.5 34 $500,000
Debts Farm/Bus/Other Property 0.0 1 0.1 9 $500,000
Vehicle Debt 0.0 0 0.4 23 $30,000
Vehicle Value 0.0 0 2.3 156 $30,000
Assets Over $500 0.1 10 0.2 10 $150,000
Debts Over $500 0.0 1 0.0 2 $150,000

Respondents Living Abroad

A second out-of-range issue with NLSY79 data concerns individuals living outside the United States. Residing outside the United States does not preclude a respondent from being interviewed. For example, in 1992, 125 respondents lived abroad. Between 1989 and 1992, for people who hold assets denominated in foreign currency, little effort was made to transform these assets into dollar figures. Instead, such values are classified as "invalid skips" in the data. Beginning in 1993, an effort was made to convert these currencies whenever the unit of the response could be determined. While researchers are warned that this occurs, relatively few respondents live outside the United States and only a small number of individuals in this group cannot report their wealth in U.S. dollars.


As more respondents reach their 50s it is important to augment information on health, asset accumulation and retirement plans with information on NLSY79 respondents' estate planning. Beginning in 2012 a new set of questions on wills was administered. These questions were drawn from the 2006 wave of the Health and Retirement Study and also have overlap with questions asked in the final rounds of the NLS Women. 

The new questions identify whether respondents have a will, a trust, or both, when it was established, when and why it was last modified, whether it provides for children and for grandchildren and, if so, whether it provides for them equally, and whether it provides for charities or nonprofit organizations. Respondents who report no will or trust are asked whether they intend to establish one.

This section ends by asking whether respondents have long-term care (LTC) insurance. While relatively few respondents are expected to have LTC insurance at this stage in the life-cycle, planning for costly health care expenses is intrinsically linked to bequest planning. 


An extensive set of questions were added in 2010 on Philantrophy and were on both volunteer activity and monetary donations to charitable causes. In 2012 only respondents who had not answered the set of questions in 2010 viewed the module.

Financial Literacy and Practices

In 2012 eight new questions on financial literacy and practices were asked of all respondents. These questions ask respondents about their preparedness for financial emergencies, their ability to monitor financial matters, and their knowledge of core financial concepts. These questions were originally asked in the Health and Retirement Study in 2004 and the Financial Capability Study. This short module complements the new questions on wills and estates, and is consistent with ongoing plans to learn more about respondents' financial literacy, practices, and preparedness as they enter their 50s and begin planning in earnest for retirement. This series of questions was repeated in 2014 for those who were not interviewed in 2012.

Debt and Personal Finance

Beginning in 2004, respondents have answered more detailed questions about their debt and personal finance histories. Respondents report total amounts owed on all credit card accounts, in student loans for which they or their spouse or partner are responsible, to other businesses or to other people/institutions/companies over $1000. Respondents are also asked if they have missed bill payments or been at least two months late in the last five years and the number of credit cards on which they owe the maximum amount (if any). Respondents reporting any bankruptcies within a specified reference period are asked how many bankruptcies they have declared. Information is then collected for the most recent bankruptcy, including whether the bankruptcy was related to the failure of a business and the date and type of bankruptcy declaration. Finally, respondents are asked if in the last five years they or their spouse or partner have applied for credit or a loan and been turned down or have chosen not to apply assuming they would be turned down. These variables can be found in the DEBT Area of Interest in survey years 2004-2014.


In 2010, a short module was added to capture more specific information on respondents affected by or possibly threatened with foreclosure. Respondents reporting property ownership within a specified time frame (both residential or other real estate) were asked if they had fallen more than two months behind on mortgage payments, whether they had received notice of foreclosure, if they had lost their property or were under threat of foreclosure, and how likely it was that they would fall behind on payments in the next six months.

Revisions to Resolve Asset and Debt Issues

In the spring of 2008 a revised set of asset and debt variables were released to the public. These revised asset and debt variables fixed a number of problems with the NLSY79 data by eliminating some implausible outliers, generating uniform topcodes for all rounds, and constructing a total net worth variable. The following provides details on revision process.

What Users See: Prior to the spring 2008 release users saw a single asset or debt question for each item in the wealth section of the questionnaire. For example in 1987 the questionnaire asked each respondent who owned a home or apartment the market value of their residential property. The questionnaire asked respondents "About how much do you think this property would sell for on today's market?" Until the spring of 2008 the respondent answers were found in a single 1987 variable that had the following R and Q numbers:

R23627.00    [Q1947] (TRUNC)

After the revision was done, two more asset variables were added to the data set based on the same underlying property responses. The two new variables are:

R23627.01    [*Created] (TRUNC) (REVISED)
R23627.02    [*Created] (TRUNC) (IMPUTED)

The variable that ends in (.00) R23627.00 is the original variable in the dataset and is left so that researchers can reproduce previous results. The variables that ends in (.01) R23627.01 is a new variable which uses a revised topcoding algorithm. By revising the variable researchers are now provided with some extra information that was not available before. The variable that ends in (.02) R23627.02 is a new variable which imputes missing and unknown responses if possible as well as using the revised topcoding algorithm.

There are two new variables because some users will not want to use imputed data. The (.01) variables are cleaned and re-topcoded but do not have any imputed values. The (.02) variables have as many missing or unknown values imputed as possible. In general the survey staff recommends that users without a strong preference should use the (.02) asset or debt value that ends in the label "(TRUNC) (IMPUTED)."

A more detailed explanation is available in Appendix 23.

Details about Computed Net Worth Variables

Previously, information was available on both low-level asset and debt questions and on the high-level approach to calculating net worth. Additional documentation is now available to describe the intermediate sets of variables that were used to create the high-level net worth figures and are currently the only NLSY79 variables that are imputed, which fills in missing information. The intermediate sets of variables are useful for researchers who want to probe a particular aspect of a respondent’s financial life, such as their debts or ownership of vehicles. Appendix 23 has been updated to include this additional information.

Household Expenditures

In 2006, respondents answered a series of questions about regular (monthly or weekly) household expenses, including grocery/non-grocery purchases, telephone, internet, electricity, and other utility bills. These variables can be found by searching Area of Interest=Consumption in NLS Investigator.

Educational Expenditures

Respondents who were parents answered a new series of questions in 2014 regarding the costs of their children's education for high school (for children attending private school grades 9-12) and post-secondary institutions (two-year or four-year college). They were first asked the total expense incurred (amount borrowed or paid) by respondent, student, family, and friends. Respondents then reported the percentage of the total they and their spouse/partner had paid, another parent had paid, grandparents had paid, child had paid, and other relatives/friends had paid. In addition, respondents answered the following speculative questions about their children and college:

  • Do you believe [name of child] would have attended a more expensive college or attended college for a longer time if you and other family members had been able to contribute more...?
  • Do you believe [name of child]'s decision not to attend college was influenced by concerns about the cost of college?
  • If [name of child] had attended college, do you believe you and other family members would have contributed [to the expenses]?
  • Given that [name of child] did not attend college, did you give him/her money that might otherwise have been used for college-related expenses?

Comparison to Other NLS Cohorts: Information on assets has been regularly collected from each cohort (except for NLSY79 children under age 15). Users should note, however, that the assets included have varied widely over time and among cohorts. Data on the respondent's debts have been collected from each cohort on a less regular basis. A set of questions on financial literacy appeared in Round 11 of the NLSY97. For more precise details about the content of each survey, consult the appropriate cohort's User's Guide using the tabs above for more information.


Zagorsky, Jay L. "The NLSY79 Wealth Data Evaluation." Columbus, OH: CHRR, The Ohio State University, 1997.

Survey Instruments and Documentation Questions pertaining to assets are found in the "Income and Assets" section of the NLSY79 questionnaire beginning with 1985.  Specifically, Section 11 (1993), Section 12 (1987, 1989, 1990, 1992), Section 13 (1986, 1994-2000, 2004, 2008, and 2012-2014), Section 14 (1985), and Section 15 (1988) contain these questions.
Areas of Interest Data are found primarily within the "Asset" area of interest in the NLSY79 data set.