CFED Assets & Opportunity Scorecard
Asset Poverty by Gender
Definition
Ratio of the asset poverty rate of single male-headed households to single female-headed households, 2010.
Calculated by dividing the higher value by the lower value, i.e., single female-headed households divided by single male-headed households, except in Colorado, Florida, Iowa, Maryland, Missouri, New Jersey, North Carolina and Virginia where single male-headed households have higher rates of asset poverty.
A ratio of 1 indicates perfect equality; the higher the ratio, the greater the inequality. For example, the asset poverty rate for single female-headed households in Oregon is 1.7 times higher than for single male-headed households.
Data are point estimates produced from a national survey with relatively small samples for some states, which can result in imprecise estimates and ranks. States are not ranked on this measure due to insufficient data at the state level. For more information on how we measured precision and to download margin of error data for each state, see here.
Description
This measure describes the disparity in asset poverty between single male- and single female-headed households. Historically, women have faced barriers to or been prevented from acquiring assets, especially property and capital. However, when comparing single women to single men, asset poverty is only 1.14 (or 14%) higher for single women than it is for single men. In fact, asset poverty is higher for men in eight of the 29 states for which data is available.
The Scorecard compares single households in gender comparisons rather than all male- and female-headed households to disentangle issues of gender from marital status. For more information on wealth disparities by gender, see the work of Mariko Lin Chang.
Asset Poverty by Gender
| State | Asset Poverty, Single Male-Headed Households (%) | Asset Poverty, Single Female-Headed Households (%) | Ratio |
|---|---|---|---|
| United States | 31.8% | 36.3% | 1.14 |
| Alabama | 25.9% * | 29.6% | 1.14 |
| Alaska | — | — | — |
| Arizona | 27.5% | 41.4% | 1.50 |
| Arkansas | — | 38.9% | — |
| California | 31.8% | 39.1% | 1.23 |
| Colorado | 35.1% | 28.7% | 1.22 |
| Connecticut | — | 33.8% | — |
| Delaware | — | — | — |
| District of Columbia | — | — | — |
| Florida | 37.5% | 35.1% | 1.07 |
| Georgia | 38.2% | 41.2% | 1.08 |
| Hawaii | — | — | — |
| Idaho | — | — | — |
| Illinois | 33.4% | 36.1% | 1.08 |
| Indiana | 24.9% | 36.7% | 1.47 |
| Iowa | 39.1% | 26.8% | 1.46 |
| Kansas | — | 31.6% | — |
| Kentucky | 28.4% | 33.5% * | 1.18 |
| Louisiana | — | 38.5% | — |
| Maine | — | — | — |
| Maryland | 31.9% | 31.2% | 1.02 |
| Massachusetts | 31.7% | 40.1% | 1.27 |
| Michigan | 34.3% * | 38.8% | 1.13 |
| Minnesota | 21.5% * | 30.1% | 1.40 |
| Mississippi | 30.7% | 41.2% | 1.34 |
| Missouri | 32.0% | 31.1% | 1.03 |
| Montana | — | — | — |
| Nebraska | — | — | — |
| Nevada | — | — | — |
| New Hampshire | — | — | — |
| New Jersey | 37.1% | 35.3% | 1.05 |
| New Mexico | — | 32.9% * | — |
| New York | 39.4% | 44.8% | 1.14 |
| North Carolina | 38.7% | 38.5% | 1.01 |
| North Dakota | — | — | — |
| Ohio | 31.8% | 37.6% | 1.18 |
| Oklahoma | 27.0% * | 33.9% | 1.26 |
| Oregon | 24.0% | 40.2% | 1.67 |
| Pennsylvania | 27.3% | 29.2% | 1.07 |
| Rhode Island | — | — | — |
| South Carolina | 24.7% | 40.1% | 1.62 |
| South Dakota | — | — | — |
| Tennessee | 31.0% | 33.3% | 1.07 |
| Texas | 30.5% | 35.5% | 1.16 |
| Utah | — | — | — |
| Vermont | — | — | — |
| Virginia | 28.3% | 26.6% | 1.07 |
| Washington | 29.5% | 30.8% | 1.04 |
| West Virginia | — | 24.4% * | — |
| Wisconsin | 29.7% | 33.8% | 1.14 |
| Wyoming | — | — | — |
Source
Survey of Income and Program Participation, 2008 Panel, Wave 7. Washington, DC: U.S. Department of Commerce, Census Bureau, 2012. Data calculated by the Bay Area Council Economic Institute.
"—" indicates that no data is available, or data is suppressed due to a margin of error that is greater than 50% of the estimate.
Footnotes
* Indicates that the margin of error is greater than 25% of the estimate, and as such, this estimate is too imprecise to rank. Caution should be used when using this data.
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