Educational Needs Index Model 2.0 (Using Public Use Microdata Areas)
Until recently, much of the data for geographic areas smaller than states were only available every ten years from the decennial census. Beginning in 2005, the Census Bureau began to provide a variety of data at the sub-state level for areas called Public Use Microdata Areas (PUMAs). The variables that make up the ENI change from year-to-year and we wanted to provide the most current picture of the education, economic, and population challenges facing regions throughout the U.S.
The ENI model evaluates the educational needs and demands of the 2,071 Public Use Microdata Areas across the nation. It combines thirteen variables that measure educational attainment levels, economic and employment strength, and population growth and diversity. Through standardization of the data (described below), the model combines these measures and allows for comparison across all of the PUMAs in a given region and the nation as a whole. PUMAs are designated “most critical” when relatively poor conditions of under-education and economic challenges are compounded by population growth and shifting demographics toward youth or at-risk minority groups.
The three factors drive the ENI model and the variables that make up each factor are:
- Educational Factor – Indicators assess the educational capacity of a region’s adult population. Indicators measure the percent of the population with a high school degree, associate’s degree, and bachelor’s degree, and a measure of the educational attainment gap between younger and older members of the workforce.
- Economic Factor - Indicators in this category assess the degree of economic challenges facing counties. Indicators measure the percent of population in poverty, unemployment rates, the existing earnings capacity of residents, and dependence upon manufacturing and extraction jobs.
- Population Factor – Indicators assess the present population growth issues facing the county and potential need for increased emphasis on human capital development to address changing demographics. Indicators measure recent and project population growth, population aged 19 and younger as a percent of the total population, population aged 20-44, and the relative size of an area’s at-risk minority population (African-Americans, Hispanics, and Native Americans).
ENI Factor Categories and Associated Indicators
Educational Factor (33.3% of ENI)
Percent 18-64 Year Olds with a High School Diploma (2005)
Percent 25-64 Year Olds with an Associates Degree (2005)
Percent 25-64 Year Olds with a Bachelor's Degree or Higher (2005)
Difference in College Attainment Between Young (25-35) and Older (45-64)
Economic Factor (33.3% of ENI)
Unemployment Rate (2005)
Percent of Population Under 65 In Poverty (2005)
Median Family Income (2005)
Per Capita Income (2005)
Percent Employment in Manufacturing and Extraction Industries (2005)
Population Factor (33.3% of ENI)
Percent of Population Ages 0 to 19 (2005)
Percent of Population Ages 20 to 44 (2005)
Rate of Population Growth 64 and Under (2000 to 2005)
Percent At-Risk Minority (%) (2005)
The Educational Needs Index places an emphasis on the transition between K-12 policy concerns and postsecondary opportunities. The data assists policymakers at state, regional, and local levels as they work to reach informed decisions on issues of adult education and postsecondary education access and attainment. Particular emphasis is placed on the role that training, certificate programs, two-year degrees, and adult literacy initiatives play in forming foundations for more promising futures and stronger economies built upon a more versatile workforce. By identifying and offering intervention strategies for the most pressing issues facing critical regions, this research promotes a more informed and long-term conversation about postsecondary access. The project focuses on the most disadvantaged rural and urban areas of the U.S. and promotes regional partnerships between education, business, and government.
About the Needs Index Scores
The index is derived from averaging the individual measures within each of the three factors above. Prior to averaging, the values for each of the measures are converted to Z scores. This technique forces the mean for each measure to “0” – where high educational need is typically above “0” and low need below “0”. The reason for using this procedure is to standardize the varying scales associated with each measure – since there are a mixture of percentages and dollars. An average of the three categories is used to derive the overall ENI index scores. The overall results at the state level are shown below.
State Scores on the Overall Educational Needs Index
Texas, Mississippi, Louisiana, and New Mexico have the most critical overall scores on the Educational Needs Index and North Dakota, New Hampshire, Massachusetts, and Connecticut are the least critical. The same methodology is used to determine the index scores for each of the Public Use Microdata Areas within each state. The scores for the overall needs index and each of the three factors are shown in the table below.
| State |
ENI Score |
Factor Summary |
| Education Factor |
Economic Factor |
Population Factor |
| Alabama |
0.496 |
0.696 |
0.925 |
-0.134 |
| Alaska |
0.156 |
0.218 |
-0.494 |
0.745 |
| Arizona |
0.672 |
0.683 |
0.049 |
1.284 |
| Arkansas |
0.638 |
0.955 |
1.074 |
-0.116 |
| California |
0.560 |
0.733 |
-0.139 |
1.087 |
| Colorado |
-0.035 |
-0.277 |
-0.624 |
0.797 |
| Connecticut |
-0.685 |
-0.336 |
-1.256 |
-0.464 |
| Delaware |
-0.062 |
0.219 |
-0.591 |
0.185 |
| District of Columbia |
-0.276 |
-0.813 |
-0.284 |
0.269 |
| Florida |
0.025 |
0.106 |
-0.175 |
0.144 |
| Georgia |
0.698 |
0.496 |
0.278 |
1.320 |
| Hawaii |
-0.618 |
-0.234 |
-1.188 |
-0.433 |
| Idaho |
0.389 |
0.458 |
0.237 |
0.472 |
| Illinois |
0.052 |
-0.240 |
0.057 |
0.339 |
| Indiana |
0.229 |
0.191 |
0.636 |
-0.140 |
| Iowa |
-0.606 |
-0.990 |
-0.009 |
-0.818 |
| Kansas |
-0.134 |
-0.220 |
-0.050 |
-0.131 |
| Kentucky |
0.457 |
0.715 |
1.016 |
-0.358 |
| Louisiana |
0.793 |
1.014 |
1.106 |
0.260 |
| Maine |
-0.572 |
-0.302 |
-0.165 |
-1.249 |
| Maryland |
-0.445 |
-0.204 |
-1.475 |
0.345 |
| Massachusetts |
-0.725 |
-0.826 |
-0.957 |
-0.391 |
| Michigan |
0.125 |
-0.142 |
0.765 |
-0.249 |
| Minnesota |
-0.650 |
-1.247 |
-0.619 |
-0.085 |
| Mississippi |
0.921 |
0.583 |
1.799 |
0.380 |
| Missouri |
0.117 |
0.306 |
0.291 |
-0.246 |
| Montana |
-0.460 |
-0.233 |
-0.053 |
-1.095 |
| Nebraska |
-0.475 |
-0.882 |
-0.292 |
-0.252 |
| Nevada |
0.713 |
1.152 |
-0.535 |
1.522 |
| New Hampshire |
-0.852 |
-0.908 |
-1.029 |
-0.619 |
| New Jersey |
-0.471 |
-0.261 |
-1.186 |
0.033 |
| New Mexico |
0.775 |
0.998 |
0.706 |
0.622 |
| New York |
-0.311 |
-0.562 |
-0.321 |
-0.048 |
| North Carolina |
0.460 |
0.247 |
0.656 |
0.477 |
| North Dakota |
-0.913 |
-1.321 |
-0.630 |
-0.790 |
| Ohio |
-0.008 |
-0.033 |
0.525 |
-0.517 |
| Oklahoma |
0.328 |
0.549 |
0.672 |
-0.237 |
| Oregon |
0.126 |
0.179 |
0.391 |
-0.192 |
| Pennsylvania |
-0.419 |
-0.417 |
0.053 |
-0.892 |
| Rhode Island |
-0.394 |
-0.299 |
-0.453 |
-0.431 |
| South Carolina |
0.528 |
0.504 |
0.876 |
0.202 |
| South Dakota |
-0.524 |
-1.072 |
-0.165 |
-0.334 |
| Tennessee |
0.500 |
0.753 |
0.795 |
-0.048 |
| Texas |
1.123 |
1.206 |
0.696 |
1.468 |
| Utah |
0.419 |
-0.363 |
-0.144 |
1.764 |
| Vermont |
-0.596 |
-0.283 |
-0.309 |
-1.196 |
| Virginia |
-0.300 |
-0.049 |
-1.023 |
0.172 |
| Washington |
-0.157 |
-0.365 |
-0.246 |
0.140 |
| West Virginia |
0.171 |
0.767 |
1.120 |
-1.374 |
| Wisconsin |
-0.320 |
-0.695 |
0.054 |
-0.318 |
| Wyoming |
-0.463 |
-0.151 |
-0.367 |
-0.871 |
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