Transportation Cost Burden:

Cost Burden Concepts 

Transportation cost burden measures the percentage of income that a household spends on transportation. The cost of transportation, the modes available, and the modes used affect the total households spend on transportation.

This page highlights cost burden concepts related to the price of transportation and equity.

What does cost burden mean?

The cost burden measures the percentage of income that a household spends on transportation. The cost of transportation, the modes available, and the modes used affect the total households spend on transportation. Transportation cost is a measure of transportation affordability and depends on household income. Cost burden is calculated as the amount a household spends on public and private transportation as a share of the household’s income. Income can be measured in a variety of ways, such as before-tax income or after-tax income. These pages (Overview of Household Spending on Transportation by Income Quintile, Transportation Spending by Income Quintile and Vehicles Available, and Transportation Expenditures by Selected Household Characteristics and Income Quintile) show transportation cost burden as a share of before- and after-tax income. 
Transportation cost burden measured from national level data, as in these pages (Total National Household Spending and Average Household Spending on Transportation), lacks geographic detail, so it does not capture the reasons for the burden such as modes available to households and the locations of jobs, food, and medical care. It also does not capture nuances that may further increase the burden face by low-income households such as the reliability of the mode they’re using and how safe they feel using it. Finally, it captures only trips made and not the trips forgone due to their high cost or lack of transportation.

The data

The data comes from the Bureau of Labor Statistics’ (BLS’) Consumer Expenditure Survey (CE) and the Federal Highway Administration’s (FHWA’s) National Household Travel Survey (NHTS). The CE provides detailed, national level data on the amount different types of households spend, including but not limited to transportation. The NHTS provides context for understanding household spending on transportation, as it provides data on daily personal travel.
The CE consists of estimates derived from two separate surveys, the Interview Survey and the Diary Survey. The Quarterly Interview Survey is designed to collect data on large and recurring expenditures that consumers can be expected to recall for a period of three months or longer, such as rent and utilities, and the Diary Survey is designed to collect data on small, frequently purchased items, including most food and clothing. Both surveys include people living in houses, condominiums, apartments, and group quarters such as college dormitories. They exclude military personnel living overseas or on base, nursing home residents, and people in prisons. BLS uses address-based sampling for both surveys, as selected by the U.S. Census Bureau on behalf of BLS. The Census Bureau selects a sample of approximately 12,000 addresses per year to participate in the Diary Survey and obtains usable diaries (two 1-week diaries per household) from approximately 6,900 households. The Interview Survey is a rotating panel survey of approximately 12,000 addresses each calendar quarter of the year. One-fourth of the contacted addresses each quarter are new to the survey. Approximately 6,900 households at the contacted addresses provide usable responses each quarter of the year.
The NHTS is a national survey that provides data on daily personal travel, including information on household and demographic characteristics, employment status, vehicle ownership, trips taken, modal choice, and other related transportation data. The survey — conducted in 2001, 2009, 2017, and 2022 — is a continuation of the Nationwide Personal Transportation Survey (NPTS). This analysis utilizes data from the 2022 NHTS. The 2022 NHTS collected travel data from a national sample of civilian, non-institutionalized population of the United States - 7,893 households, as collected from January 2022 to January 2023. Data collection in 2017 and 2022 differed from that in earlier years, because it used address-based sampling rather than random digit-dialing (as was the case in the 1990, 1995, 2001, and 2009 surveys) to obtain survey responses. The change to address-based sampling enabled the inclusion of cellphone-only households – a group excluded in previous years. The 2017 NHTS utilized both online data and phone data collection instead of phone only as in previous years, while the 2022 NHTS relied on online data collection with the option of requesting a paper survey by mail (after receipt of the initial recruitment letter). Address-based sampling also allows for better geographic controls to ensure the geographic distribution of the sample since phone numbers are no longer tied to a geographical area like they once were.

Consumer units versus households

The Consumer Expenditure Survey reports data for consumer units. A consumer unit comprises either: (1) all members of a particular household who are related by blood, marriage, adoption, or other legal arrangements; (2) a person living alone or sharing a household with others or living as a roomer in a private home or lodging house or in permanent living quarters in a hotel or motel, but who is financially independent; or (3) two or more persons living together who use their income to make joint expenditure decisions. To be considered financially independent, at least two of the three major expense categories (housing, food, and other living expenses) have to be provided entirely, or in part, by the respondent.
The National Household Travel Survey (NHTS) reports data for households. A household consists of a group of persons whose reside together in a housing unit (usual place of residence). These persons may or may not be related to each other. Households in the NHTS do not include group quarters (e.g., 10 or more persons living together, none of whom are related).

Income

The BLS CE defines income as the combined income of all consumer unit members 14 years of age or over, during the 12 months preceding the interview. Income before taxes is the total money earnings and selected money receipts during the 12 months prior to the interview date. Money includes wages and salaries, self-employment income, Social Security, private, and government retirement, interest, dividends, rental income, and other property income, unemployment and workers’ compensation and veterans’ benefits, public assistance, supplemental security income, and food stamps, regular contributions for support, and other income. For more detail on what is included in the CE income definition, visit the BLS CEX glossary. For consumer units that do not report income, BLS began imputing their income in 2004.
The FHWA NHTS defines household income as the money earned by all family members in a household, including those temporarily absent, 12 months preceding the interview. Income includes wages and salary, commissions, tips, cash bonuses, income from a business or farm, pension, dividends, interest, unemployment or workers’ compensation, social security, veterans’ payments, rent received from owned property, public assistance payments, regular gifts of money from friends or relatives not living in the household, alimony, child support, and other types of periodic money income other than earnings. Household income excludes in-kind income such as room and board, insurance payments, lump-sum inheritances, occasional gifts of money from persons not living in the same household, withdrawal of savings from banks, tax refunds, and the proceeds of the sale of one’s house, car, or other personal property. For more details about what is included in the NHTS, visit the NHTS glossary. The NHTS includes only reported income.

Income quintiles

Income quintiles are a representation of income groups that consider the distribution of household income. It looks at the range of household income and divides households into five equal groups. The bottom group contains the households with the lowest income and the top group contains the households with the highest income.
To construct income quintiles, this analysis uses before-tax income, while after-tax income — what a household has available to spend — is used to look at the share of income spent on transportation. The Bureau of Labor Statistics publishes the before-tax income quintiles for the CE. This analysis uses the published values when dealing with CE data. The income range for a quintile is specific to a year and therefore varies across years.
Below and above the poverty threshold or a percent of the poverty threshold is a second way to create income groups. Unlike income quintiles, the poverty threshold takes into account the size of the household and the minimum income needed, as set by the federal government, for a household of that size to meet basic needs. This analysis currently does not report data by poverty level.
Both of these representations require survey data that report income as a continuous variable for researchers to analyze. Data on transportation expenditures, from the CE, include household income as a continuous variable whereas data from the NHTS present household income as a categorical variable. Categorical income data from the NHTS are grouped together as best as possible to create income quintiles, i.e., five equal groups of households based on income. The categorical data is not detailed enough to designate households by poverty status.
The CE imputes income whereas the NHTS does not.

Effects of work status on the composition of income quintiles

This analysis breaks households into income quintiles. The lowest income quintile includes a large number of persons who are not working because they are disabled or going to school or retired. A chart displaying the composition of characteristics making up income quintiles can be found on this cost burden page

Before-tax and after-tax income measures

The BLS CE include both before- and after-tax income, while the FHWA NHTS include only before-tax income. Before-tax income measures gross income the household has earned, in total, before taxes are applied. After-tax income represents the amount the household has after federal, state, and withholding taxes have been applied and includes any refunds or tax credits the household received. After-tax income is a better representation of what a household has to spend, invest, or save.
Note, the BLS CE before-tax income includes Supplementary Nutrition Assistance Program (SNAP).  Before-tax income used by the Census Bureau to set the official poverty thresholds does not include SNAP. 
Beginning in 2015, BLS imputes all state and federal income taxes for all consumer units in the CE. Prior to 2015, tax data included collected and imputed values.
In 2020 and 2021, BLS CE after-tax income includes economic stimulus payments. The first economic payment in 2020 — issued starting April 10, 2020 — was part of the Coronavirus Aid, Relief, and Economic Security (CARES) Act, which distributed $1,200 to qualifying adults and an additional $500 to qualifying adults for each child under age 17. The second economic payment in 2020 was part of the COVID-related Tax Relief Act, which authorized additional payments (starting December 29, 2020) of up to $600 to eligible adults and an additional $600 to eligible adults for each child under age 17.  In 2021, the American Rescue Plan Act provided economic payments up to $1,400 for eligible individuals, plus $1,400 for each qualifying dependent, including adult dependents — starting March 17, 2021.  

Standard error

Standard error (SE) is the approximate standard deviation of a statistical sample. It is a measure of how accurately a sample population represents the real population. Because the data are from a survey, and that survey is from a sample rather than an entire population, there is a SE associated with the results.
The SE is the square root of the variance which is a measure of how far each number within the data set is from the mean of that dataset. To calculate a margin of error at 90%, multiply 1.645*SE or 1.645*√variance.
SEs provide a general measure of the precision of a survey’s estimates. The SE of a sample can be interpreted that if the survey was conducted again and again, the mean would likely vary by approximately the mean plus-or-minus the SE. The SE can be used to determine whether differences between estimates are statistically significant.
Standard error in a sample is impacted by sample size and the variation within the population being sampled. The larger the sample size the smaller the error, because the larger sample is more representative of the population and less likely to portray randomness. A population that has relatively little variation, meaning they are all relatively similar in their behaviors, would mean if you pick a sample at random, that sample is more likely to be close to the population average.
For more information on the standard errors in the Consumer Expenditure Survey, visit their CE SE paper. In the CE, standard errors for income are calculated differently than standard errors for expenditures, because of income imputation. See the CE Users Guide on Income Imputation for more information. 

Recommended citation
U.S. Department of Transportation, Bureau of Transportation Statistics, Transportation Economic Trends, available at www.bts.gov/product/transportation-economic-trends.

Bureau of Transportation Statistics
The Bureau of Transportation Statistics, part of the U.S. Department of Transportation, is the preeminent source of statistics on commercial aviation, multimodal freight activity, and transportation economics, and provides context to decision makers and the public for understanding statistics on transportation.
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