Methodology

The Distressed Communities Index (DCI) is designed to provide a single, holistic, and comparative measure of economic well-being across communities throughout the United States. It combines seven complementary economic indicators into a single summary statistic that conveys each community’s standing relative to its peers. The 2020 edition of the DCI is built from the U.S. Census Bureau’s American Community Survey (ACS) 5-Year Estimates covering the years 2014-2018 and the Census Bureau’s Business Patterns datasets for the same years.

The seven components of the index are:

Each community’s score on the index is equivalent to its percentile rank across all seven measures combined. To calculate the index, each community is ranked on each measure. Then each community’s seven rankings are averaged and weighted equally to create a preliminary score, which is then normalized into a final score that ranges from approaching 0 (most prosperous) to 100 (most distressed). Communities are then sorted into five even quintiles, or tiers, of economic well being: prosperous, comfortable, mid-tier, at risk, and distressed

The 2000 DCI was calculated in much the same manner using data from that year’s Decennial Census, as well as Business Patterns data for the years 1996 and 2000 to calculate change in employment and business establishments over that time period. The 2000 DCI was calculated against the country’s zip code map as it stood that year, and boundaries may have changed since then. There are 955 zip codes that appeared in the 2020 vintage that lacked a score in the 2000 edition of the DCI, and there are 1,268 that appeared in the 2000 version but not in 2020. Such entries and exits into the sample can happen due to the creation of new zip codes, consolidation of old ones, or population fluctuations around the 500-person minimum.

The same methodology is applied at every level of geography reported in the DCI and its related products. In all, the zip code-level DCI captures 99 percent of the U.S. population and all 25,400-plus zip codes with at least 500 residents not in dormitories, group quarters, the armed forces, or other similar arrangements. At higher levels of geography, it captures 3,133 counties with at least 500 residents; 828 cities that contain at least 50,000 people; and 383 metro areas.

Source notes

The 5-year ACS estimates are constructed from five years’ worth of data collection, reflecting the length of time required to compile enough data to provide meaningful and accurate estimates at fine geographic scales (such as zip codes) by the U.S. Census Bureau. The ACS supplies the first five variables that enter into the DCI, and Business Patterns supplies the two growth metrics. ACS variables can be interpreted as showing what share of housing units were vacant when surveyed sometime between 2014 and 2018 in a zip code, for example. 

All of the auxiliary data presented in the DCI suite of materials (e.g. racial and demographic information) come from ACS 5-year estimates.

Data notes

In instances where employment estimates from Business Patterns were suppressed by the Census Bureau in order to preserve privacy, the DCI defaulted to the next-highest level geography to produce a growth estimate that could enter into the index. This affected approximately 3,700 zip codes in the 2014-2018 DCI and 2 counties. For example, the statewide job growth rate of 9.3 percent entered into the index as the job growth rate for Calhoun County, Michigan, for which employment figures were suppressed.

Beginning in 2017, the Census Bureau completely excluded zip codes with fewer than three establishments from Business Patterns. The majority of these excluded zip codes did not meet the population threshold for the DCI; however, 196 zip codes did and were removed from the DCI due to the consequent lack of both employment and establishment data for 2018.

Defining urban and rural

This report uses the 2010 U.S. Census urban and rural classification and urban area criteria to classify a zip code as urban, suburban, small town, or rural. 

  • Urban: More than 50 percent of the zip code’s population lives in an urbanized area, defined by the U.S. Census Bureau as an area of 50,000 or more people, and the zip code is located in a city with a population of 100,000 or higher.
  • Suburban: More than 50 percent of the zip code’s population lives in an urbanized area and the zip code is located in a city with a population less than 100,000. zip codes where 1 percent or more of the population was rural, but were still assigned to a city with a population above 100,000, were designated suburban. This captures zip codes on the edges of large urban areas.
  • Small town: More than 50 percent of the zip code’s population lives in an urban cluster, defined by the U.S. Census Bureau as an area of less than 50,000 people.
  • Rural: More than 50 percent of the zip code’s population lives in an area classified as rural by the U.S. Census Bureau.

Based on these criteria, just over one-fifth of the country’s zip codes are suburban, but they contain a plurality of the country’s population. Similarly, only 11 percent of zip codes are urban, but nearly one-third of the country’s population lives in them. Rural zip codes are the most numerous but contain only one in seven Americans, while small towns’ share of the map and the population are proportional. 

Geographical notes

Zip codes as presented and discussed here should be considered approximations of geographies and communities. Official zip codes represent postal routes defined by the U.S. Postal Service (USPS), not the U.S. Census Bureau, and their boundaries can and do change. The U.S. Census Bureau builds its own proprietary approximations of zip codes called Zip Code Tabulation Areas (ZCTAs) from census blocks once after each Decennial Census. The DCI joins data tabulated by both zip code and ZCTA based on matching codes, not necessarily coterminous boundaries. Two of the underlying variables (those from Business Patterns) are defined by zip code, and five (those from the American Community Survey) are defined by ZCTA. As such, it is important to interpret zip code-level findings in the DCI as general trends for an approximate area. In addition, Business Patterns data are subject to suppressions and other methodological precautions to avoid disclosure of individual employers as well as errors that the Census Bureau does not go back to correct. Zip code boundary changes, suppressions, and errors may affect change over time calculations.

Similarly, in instances where the research tracks the evolution of a particular zip code over time (either by following its subsequent employment trends or by comparing its distress score in the years 2000 and 2018), matches are made based on codes alone; underlying and unobserved changes may have been made to boundaries.

Zip code-level data was used to create city-level estimates for change in employment and change in establishments. Zip code values were aggregated up to the city level using ZCTA-to-place relationship files provided by the Census Bureau. In instances where zip code boundaries cut across city lines, zip code portions were attributed to cities according to the share of the associated ZCTA’s population falling within the boundaries of the larger geography using relationship files provided by the Census Bureau. Relationship and mapping files were also used to report the share of a city’s, county’s, state’s, or congressional district’s population residing in distressed and prosperous zip codes.

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