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The 2000 Census: Counting Under Adversity (2004)

Chapter: 2 Census Goals and Uses

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Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
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CHAPTER 2
Census Goals and Uses

THE RESULT OF A DECENNIAL CENSUS is a collection of data of various types. One such type is basic population counts, which are used in reapportionment and redistricting, as input to federal funding formulas, and in many other ways. The other prominent type of data product from the census characterizes local areas or population groups from tabulations and analyses of the demographic and socioeconomic variables on the census long form.

These census data are provided to users in a wide variety of data products (see Box 2.1). Such products include aggregate or summary tables for geographic areas ranging from the nation as a whole to individual blocks or groups of blocks. Another data product comprises public use microdata sample (PUMS) files, which are subsamples of individual person records from the census long-form sample, which have been carefully reprocessed to minimize the risk of reidentification of respondents. Both summary and microdata products serve federal, state, and local governments, private-sector organizations, researchers, the media, and, ultimately, the public. Collectively, these data are the only available source of detailed information for small geographic areas and population groups. They are also the only source of information about the entire U.S. population, including not only residents of conventional housing units but also residents of special places and group quarters like military bases, dormitories, nursing homes, and prisons.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Box 2.1
Selected 2000 Census Data Products

  1. TABULATIONS OF BASIC (COMPLETE-COUNT) DATA ITEMS (age, sex, race, ethnicity, relationship, housing tenure)

  • Census 2000 Redistricting Data Summary File (P.L. 94-171 File) Population counts, total and aged 18 and over, by 63 race categories; by Hispanic origin; and by geography (county, place, minor civil division, census tract, block group, block)

  • Demographic Profile; Congressional District Demographic Profile Selected complete-count characteristics, by state, county, place, minor civil division, census tract; congressional district (106th, 108th Congresses)

  • Summary File 1 (SF1, 286 tables in all)

  1. Population counts for 63 race categories and Hispanic, not Hispanic—down to the block level (file for each state)

  2. Population counts for many detailed race and Hispanic categories and American Indian and Alaska Native tribes—down to the census tract level (file for each state)

  3. Selected complete-count characteristics—down to the block level (file for each state)

  4. National-level file—tabulations for states, counties, and places; urban-rural tabulations

  • Summary File 2 (SF2, 47 tables in all)

  1. Complete-count characteristics iterated for many detailed race and Hispanic categories and American Indian and Alaska Native tribes—down to the census tract level (file for each state)

  2. National-level file—tabulations for states, counties, and places; urban-rural tabulations

  1. TABULATIONS OF LONG-FORM (SAMPLE) DATA ITEMS

  • Demographic Profile; Congressional District Demographic Profile Demographic, social, economic, and housing characteristics (three separate tables), by state, county, place, minor civil division, census tract; congressional district (106th, 108th Congresses)

  • Summary File 3 (SF3, 813 tables in all)

  1. Population counts for ancestry groups—down to the census tract level (file for each state)

  2. Selected sample population and housing characteristics—down to the census tract and block group levels (file for each state)

  3. National-level file—tabulations for states, counties, places

  • Summary File 4 (SF4)

  1. Sample population and housing characteristics iterated for many detailed race and Hispanic categories, American Indian and Alaska Native tribes, and ancestry groups—down to the census tract level (file for each state)

  2. National-level file—detailed tabulations for states, counties, places

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×
  1. PUBLIC USE MICRODATA SAMPLE (PUMS) FILES (all items for households and persons selected from the census long-form sample)

  • 1-Percent Sample Files, containing about 1 million household and 3 million person records

    Geographic identification: state, large areas of 400,000 or more population

  • 5-Percent Sample Files, containing about 5 million household and 15 million person records

    Geographic identification: state, areas of 100,000 or more population

NOTES: All files available on the Internet and CD-ROM/DVD, profiles also available on paper; all files have been processed to protect confidentiality.

SOURCE: http://www.census.gov/population/www/censusdata/c2kproducts.html [12/1/03].

The sheer scope and variety of census data and products complicates the task of evaluating a census. This difficulty is compounded by two basic truths. First, census results can only be meaningfully assessed in the context in which those data are actually used. For example, a census could provide outstanding population count data but subpar characteristics data: this could happen if serious problems occurred with the census long form. The data from such a census would be perfectly adequate for some uses but would fail to satisfy others. Similarly, whether the data were to be used as counts or shares, or the level of geographic aggregation, might lead to different judgments about the quality of the data. For instance, a hypothetical census that—for some reason—did an excellent job of collecting information from people living in Western states but not elsewhere would provide good counts for the population living in the West but overestimate the West’s share of the total U.S. population. Furthermore, changes in census processes could improve the precision of counts while hurting the use of the same data to represent changes in counts over time. For example, the change to allow multiple responses to race and ethnicity questions in the 2000 census may make it possible to capture data on more focused demographic groups, but it may complicate inferences about the relative sizes of minority groups relative to past censuses. A comprehensive evaluation of a census must therefore strive to interpret census results in the context of all of their possible uses.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

The second basic truth—and major complication for evaluating a census—is that there is no single, dominant use of census data. While the use of census data to reapportion the U.S. House of Representatives is arguably the primary role of the American census due to the constitutional mandate to do so, it is hardly the exclusive or most demanding use of those data. Hence, there is no single, dominant metric against which census results can be compared in order to unequivocably determine how good they are.

As context for our assessments and recommendations in subsequent chapters, this chapter summarizes the goals of the 2000 census and major uses of the data under four headings: (2-A) use for congressional reapportionment; (2-B) use for congressional and state and local redistricting; (2-C) other uses of the basic demographic data—age, sex, race, and ethnicity—collected from everyone enumerated in the census, including use of updated population estimates in federal funding formulae; and (2-D) uses of the additional data that are obtained on a wide range of topics from questions on the census long form.

2–A CONGRESSIONAL APPORTIONMENT

Censuses play a fundamental role in the U.S. political system by providing counts of the population for each state once a decade for reallocation of seats in the U.S. House of Representatives. This primary role for census-taking is mandated in Article 1 of the U.S. Constitution and elaborated in Title 13 of the U.S. Code (specifically, 13 USC §141b), which stipulates that the Census Bureau must provide state-level population counts to the president by 9 months after Census Day (i.e., December 31 of the census year under the current schedule). Within 1 week of the opening of the next session of Congress, the president must report to the clerk of the House of Representatives the apportionment population counts for each state and the number of representatives to which each state is entitled according to the prescribed formula (2 USC §2a).1 In turn, the clerk of the

1  

The current reapportionment formula, which uses the method of “equal proportions,” was written into law at the time of the 1940 census (Anderson, 1988:189). Apportionment is subject to the constitutional constraint that each state have at least one representative in the House.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

House must inform each state governor of the number of representatives to which each state is entitled (2 USC §2a). This schedule was legislated by Congress in 1929 so that reapportionment would occur automatically each decade, thereby precluding what happened after the 1920 census: beset by rural concerns over sharp population growth in urban areas—largely immigration-driven—Congress could not agree on a bill to reapportion seats on the basis of the census results (see Magnuson, 2000b).

Concern over the possible effect of census coverage error on congressional reapportionment—and, more specifically, the effect of competing statistical adjustments to try to correct for said error—has fueled debate over census methodology for years. Although the use of sampling-based census estimates for reapportionment is now prohibited pursuant to a U.S. Supreme Court ruling (see Chapter 3), the potential effects of error and adjustment on apportionment are still viable concerns given the prominence of reapportionment as a use of census data. In studies related to the 1990 census, census data that were adjusted to reflect estimated net undercount shifted one or two House seats between states when input into the “method of equal proportions” formula used for reapportionment compared to results using unadjusted counts. The sensitivity of the apportionment formula to small shifts in population counts was cited by then Commerce Secretary Robert Mosbacher in his decision not to adjust the 1990 census.

The major issue with regard to census data for reapportionment is the definition of who is included in the state counts. Historically, major controversies have involved the treatment of three groups: (2-A.1) noncitizens, (2-A.2) Americans overseas, and (2-A.3) people who are not counted in the census itself but who are estimated to be part of the U.S. population through a coverage estimation program, such as the Accuracy and Coverage Evaluation (A.C.E.) Program implemented for 2000.

2–A.1 Treatment of Noncitizens

Since 1790 the census has had a goal to count all U.S. residents, including people who are not citizens of the United States (except for tourists and other temporary visitors from abroad and people

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

who represent a foreign government). With the rise in the numbers of illegal immigrants in the 1970s and 1980s, lawsuits were filed to exclude them from the apportionment counts (Federation for American Immigration Reform (FAIR) v. Klutznick for the 1980 census and Ridge v. Verity for 1990; see Passel, 2000). The plaintiffs argued that including illegal immigrants unfairly benefited states with larger numbers of them at the expense of states with fewer of them. The defendants countered that the Constitution did not limit the apportionment counts to citizens or potential voters but included the entire population (originally counting slaves as three-fifths of a person). Defendants also argued that it was impractical to identify and exclude illegal immigrants in the census.

Federal district courts decided both the FAIR and Ridge cases on the legal grounds of standing. Specifically, the courts ruled that the plaintiffs had not demonstrated injury or harm resulting from the inclusion of illegal immigrants in apportionment counts. The U.S. Supreme Court declined to hear appeals in both cases, upholding the lower court rulings. Although the district court opinions offer some commentary on the constitutional intent to provide representation to everyone and not just to potential voters, this language was not the basis for the decisions. Hence, the issue of including illegal immigrants in the apportionment counts has never been fully resolved.

The 2000 census followed historical practice by striving to include all U.S. residents in the apportionment count. Indeed, the results indicated that the census counted many more illegal immigrants than had been estimated to reside in the country, based on survey and administrative records data (see Section 5-D).

2–A.2 Treatment of Americans Overseas

Rules about counting Americans who live overseas have varied from census to census. Typically, when counted at all, Americans living abroad have been included in an “overseas” population category and not included in the population of specific states for apportionment or other purposes.

Two recent exceptions occurred in 1970 and 1990, when federal military and civilian employees who lived abroad and could be assigned to a “home” state from administrative records were included

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

in the state counts for reapportionment, but not in any other data releases. According to McMillen (2000:33):

In both cases, the Census Bureau yielded to pressure from Congress to change its procedures to forestall the passage of undesirable legislation. In 1970 the Census Bureau sought to avoid being embroiled in the debate over the Vietnam War. In 1990 the Census Bureau did not want to link the counting of Americans overseas with excluding undocumented aliens from the census.

Since 1995, groups representing Americans abroad have lobbied the Census Bureau to enumerate not only federal government employees who live overseas, but also private citizens who live abroad. The Bureau has resisted such pleas on grounds of the difficulties of finding such people and evaluating the completeness of their coverage. It would also be hard to determine how to allocate them to a home state of residence for inclusion in state apportionment counts. The 2000 census did not attempt to count private citizens who lived abroad but, instead, followed the 1990 practice by enumerating federal military and civilian employees (and their dependents), including them in the state apportionment counts (using the home residence listed for them in administrative records), and tabulating them as “Americans overseas” for other purposes. This population totaled 576,000 people in 2000, or about two-tenths of 1 percent of the total U.S. population.

After narrowly losing the 435th and final seat in the U.S. House of Representatives to North Carolina, the state of Utah filed the first of two challenges against the apportionment totals on the grounds that the Census Bureau had not treated Americans living overseas equally in the count. Specifically, the case held that Mormon missionaries stationed abroad should be treated in the same manner as military and other federal employees stationed oversees (see Box 2.2). The case ultimately failed but—in the wake of the Utah suit and in response to congressional directives for planning for the 2010 census—the Census Bureau in 2004 will test the feasibility of counting private citizens living abroad, using France, Kuwait, and Mexico as test sites. The Census Bureau also plans a second Overseas Census Test in 2006.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Box 2.2
Utah v. Evans: Legal Challenges to 2000 Census

Under the reapportionment counts issued by the Census Bureau in December 2000, Utah fell short of the 435th (and final) seat in the U.S. House of Representatives by fewer than 1,000 people; the seat was awarded to North Carolina. As a consequence, Utah filed two legal challenges, one of which was decided by the U.S. Supreme Court and both of which raise issues likely to be revisited as the 2010 census approaches.

Many of the documents filed by the state of Utah in the two cases remain available on the Internet at http://attorneygeneral.utah.gov/highprofileissues.htm [12/1/03].

Utah v. Evans I: Overseas Enumeration

In its first legal filing, Utah challenged the reapportionment counts on the basis that Americans living overseas were treated unequally in the census count. Specifically, the case cited the failure to count missionaries of the Church of Jesus Christ of Latter-day Saints (who temporarily live abroad), even though military personnel and other federal employees stationed overseas are counted. To apply a uniform standard, the case argued that federal employees stationed overseas should be dropped from the apportionment counts.

In April 2001, a three-judge panel of the U.S. District Court for the District of Utah ruled against the state. In a November 26, 2001, order, the U.S. Supreme Court affirmed the ruling without comment and declined to take the case on appeal (Nov. 26, 2001, order list, No. 01-283).

Utah v. Evans II: Whole-Person Imputation

As litigation in the overseas enumeration case proceeded, Utah’s legal team developed another challenge to the apportionment count, this time examining imputation of whole persons to the census when even household size is not known (imputation types 3–5, as in Box 4.2 in Chapter 4). Utah argued that whole-person imputation using hot-deck methods (see Appendix G) constituted sampling, which was prohibited for use in apportionment totals by the U.S. Supreme Court in 1999. If those imputations were dropped from apportionment tallies, Utah would win the 435th seat rather than North Carolina, but no other state’s apportionment total would be affected.

Utah initially sought to add its case against imputation to the existing litigation on overseas enumeration, but the U.S. District Court for the District of Utah denied amendment to the case. However, it did so not on the merits of the case but rather on the grounds that it would fundamentally affect the character of the lawsuit. Consequently, the imputation challenge was filed in its own right.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

In November 2001, a three-judge panel of the U.S. District Court for the District of Utah sided with the Census Bureau and ruled that imputation did not constitute sampling. Utah appealed to the U.S. Supreme Court, which announced in late January 2002 that it would hear arguments on March 27, 2002, on both the court’s jurisdiction in the case (i.e., whether Utah had legal standing to bring the case) and on the merits of the case.

On June 20, 2002, Justice Stephen Breyer delivered the opinion of a 5–4 court majority in favor of the Census Bureau. The court found that “imputation differs from sampling in respect to the nature of the enterprise, the methodology used, and the immediate objective sought. [These] differences are of both kind and degree.” Consistent with the “actual enumeration” clause in the Constitution, the opinion notes that “in this instance, where all efforts have been made to reach every household, where the methods used consist not of statistical sampling but of inference, where that inference involves a tiny percent of the population, where the alternative is to make a far less accurate assessment of the population, and where consequently manipulation of the method is highly unlikely, [methodological limits under the “actual enumeration” clause] are not exceeded” (Utah v. Evans, 536 U.S. 452, 2002).

Justice Sandra Day O’Connor dissented, concluding that imputation is a form of sampling and is, therefore, prohibited under Title 13 of the U.S. Code (see Box 3.1). Accordingly, she declined to comment on the constitutionality of imputation. Justice Clarence Thomas, joined by Justice Anthony Kennedy, also dissented; they agreed with the majority opinion that imputation is not a form of sampling but disagreed on the question of constitutionality, finding imputation and “estimation techniques” inconsistent with their reading of the Constitution’s “actual Enumeration” clause and the historical record of the debate surrounding it. Justice Antonin Scalia dissented in full, arguing that Utah lacked standing to bring the case. Even if Utah succeeded in its challenge and the census totals were recalculated, the president could not and would not be compelled to issue a new apportionment slate to Congress. As a result, Scalia concluded, the federal courts are powerless to “redress the injury” claimed by Utah, and the state is ineligible to bring the case. Scalia would dismiss the case on that basis and did not comment on either the legality or constitutionality of imputation in the census process.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

2–A.3 Treatment of Uncounted People

The goal of the census is to count each U.S. resident once and only once. However, research on census coverage, which began with analyses of undercounts of draft-age men and young children in the 1940 census, estimated a net undercount of the population in every census from 1950 to 1990. (The net undercount is the difference between the number of missed people who should have been included in the census—omissions—and the number of people who were included in the census in error, such as duplicates and other erroneous enumerations.) Research also estimated higher net undercount rates for some population groups than others, such as higher rates for blacks compared with nonblacks and children compared with adults (see Chapter 5).

Beginning with the 1970 census, the Census Bureau made special efforts to improve coverage of hard-to-count population groups, although research showed that such efforts were only partly effective (see Citro, 2000c). Beginning with the 1980 census, the Bureau worked to develop a dual-systems estimation (DSE) methodology, based on data from a postenumeration survey and a sample of census records, that could be used to statistically adjust census counts for measured net undercount. The Bureau originally planned to use DSE methods to adjust 2000 census state population totals for congressional reapportionment, but a January 1999 decision by the U.S. Supreme Court precluded the use of adjusted totals for this purpose. The Bureau then planned to adjust census counts for other purposes, but that was not done.

The latest Bureau DSE estimates are that the 2000 census overcounted the population by about 1.3 million people or about one-half of 1 percent of the population. This small overcount masked not only large numbers of duplicates and other erroneous enumerations, but also large numbers of omissions. In Chapters 5 and 6 we review the long controversy over census adjustment and assess what is known about population coverage in 2000.

On a related note, the second lawsuit filed by the state of Utah challenged the inclusion of certain kinds of census imputations—persons who were not directly enumerated but whose characteristics were imputed instead—in apportionment totals. In June 2002, the U.S. Supreme Court ruled in favor of the Census Bureau’s inclusion

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

of imputations (see Box 2.2; we discuss imputation in greater detail in Section 4-D and in Appendixes F, G, and H).

2–B LEGISLATIVE REDISTRICTING

A second major function of the U.S. census, which flows from its constitutional mandate to provide state apportionment counts, is to provide small-area population counts for redrawing congressional and state legislative district boundaries. Census small-area data by age, race, and ethnicity (Hispanic origin) are used to ensure that districts satisfy standards for equal population and the requirements of the Voting Rights Act for equitable representation of population groups. In this section, we review the history of redistricting with regard to population size for three time periods: through 1960, from 1960 to 1990, and since 1990. Although the historical discussion may seem to be a lengthy digression, the various battles over standards for redistricting are crucial to understanding data needs served by the census and have important ramifications for the level of geographic detail needed in census tallies.

It is important to note that, in the following discussion of equality of district size, we speak principally about comparison of district populations within states and not equality of population across states, among all 435 districts of the U.S. House of Representatives. The latter issue was resolved by the U.S. Supreme Court following the 1990 census; the state of Montana challenged the “equal proportions” method used to allocate seats in the House after it lost its second House seat and Montana’s at-large district became the most populous in the nation. The Court ruled that Congress has discretion to allocate House seats as it sees fit so long as good-faith efforts are made to achieve mathematical equality in representation based on state population, even though inequities in district population (necessarily) arise when compared across states (United States Department of Commerce v. Montana, 503 U.S. 442, 1992).2

2  

Following the 2000 census, Montana remained a single-district state; with a 2000 census apportionment population of 905,316, its single at-large district remains the most populous in the nation.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

2–B.1 History of Redistricting Standards

Through 1960

The needs for census data for redistricting have evolved over time. In the 19th century, Congress typically passed a statute at the occasion of each census that required all states, whether or not they gained or lost seats, to redistrict and to establish single-member districts that were contiguous, compact, and as nearly equal in population as practicable (Durbin and Whitaker, 1991:4–8). During this period, the smallest areas for which census counts were published were incorporated towns and villages, which could be quite small in population. Until 1911, with one exception, Congress increased the size of the House of Representatives at each reapportionment, so that no state lost congressional seats. (The exception occurred when the size of the House was decreased from 240 to 223 members following the 1840 census.) In 1911, the size of the House was fixed at 435 seats, at which level it has remained except for a brief two-seat enlargement when Alaska and Hawaii achieved statehood in 1959.

In 1929, Congress required automatic reapportionment of the House of Representatives upon delivery of new census counts, but it set no standards for redistricting. The U.S. Supreme Court held that the omission of such standards was intentional (Wood v. Broom, 287 U.S. 1, 1932) and that it was up to the states to develop their own standards until and unless the courts decided to intervene (Durbin and Whitaker, 1991:4–5; see also Anderson, 1988:Ch.6).

From the 1920s through the 1950s, the courts generally declined to intervene in redistricting issues, and congressional and state legislative districts became increasingly unequal in population size. Many states chose not to redistrict after a census unless they gained or lost seats, and those that did often paid little attention to achieving population equality across districts.

1960 to 1990

The landmark “one-person, one-vote” Supreme Court decisions, beginning in the early 1960s, drastically changed the requirements for redistricting. In the first of these cases, Baker v. Carr (369 U.S. 186, 1962, which involved Tennessee state legislative districts), the Court held that reapportionment and redistricting matters were subject to judicial review under the equal protection clause of the Fourteenth

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Amendment. In Wesberry v. Sanders (376 U.S. 1, 1964), the Court held, under Article 1 of the Constitution, that congressional districts must be as nearly equal in population as practicable. In Karcher v. Daggett (462 U.S. 725, 1983), by a 5–4 margin, the Court rejected a New Jersey congressional redistricting plan in which the smallest district was only seven-tenths of one percent smaller in population than the largest district. The New Jersey legislature argued that the 0.7 percent difference (about 3,700 people) was the functional equivalent of zero because it was less than the predictable undercount in the census. The majority decision rebutted that argument: “Even assuming that the extent to which the census system systematically undercounts actual population can be precisely determined, it would not be relevant. The census count provides the only reliable—albeit less than perfect—indication of the districts’ ‘real’ relative population levels, and furnishes the only basis for good-faith attempts to achieve population equality” (Parker, 1989:61; see also Durbin and Whitaker, 1991:12; Ehrenhalt, 1983:56–57).

In Reynolds v. Sims (377 U.S. 533, 1964), the Supreme Court held that, under the Fourteenth Amendment, both houses of a state legislature must be apportioned on a population basis. Moreover, states should strive for population equality. Generally, however, the courts allowed more deviation among state legislative seats than among congressional districts—deviations below 10 percent in the size of state districts were accepted, and sometimes deviations between 10 and 16 percent, but not deviations greater than 16 percent (Parker, 1989:57–58; see also O’Rourke, 1980:22).

The courts held that the states could use other data sources than the census for redistricting purposes. Over time, however, the states—on their own initiative and prodded by the courts—came to rely almost exclusively on census data to prepare redistricting plans. Thus, when states used other data for redistricting, such as rolls of registered voters, they generally had to obtain census data to demonstrate to the courts that their data would not give a substantially different result from census data (see National Research Council, 1995b:246–247).3

3  

Massachusetts until 1990 had a requirement in its constitution to conduct a state census every 10 years in years ending in 5; the state census results were used for local redistricting. Beginning in 1992 results from the U.S. census were used.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

From the 1970 census the states could obtain population counts for geographic areas as small as city blocks (which were then defined in urbanized areas and in other localities that contracted with the Census Bureau) and for enumeration districts in unblocked areas. However, no special data files or reports were provided specifically to meet redistricting needs, and the boundaries of blocks and enumeration districts often did not match state voting precinct boundaries.

In 1975 Congress required the Census Bureau to provide census population tabulations to state officials for purposes of redistricting within a year after the census date (i.e., under the current schedule, by April 1 of the census year plus one) (Public Law 94-171; codified in 13 USC §141c). States could suggest block boundaries and specify the geographic areas for which they required tabulations, provided that their requirements satisfied Census Bureau criteria and were transmitted to the Bureau on the specified time schedule; if no special areas were identified, the Census Bureau was to provide “basic tabulations of population.” In practice, basic tabulations came to mean tabulations for blocks (about 10 million in all), which were identified nationwide beginning with the 1990 census and are the smallest area of geography identified in census data products.

Since 1990

Court cases in the 1990s continued to uphold strict standards of population equality for congressional redistricting, in no instance approving a plan with more than a 0.09 percent deviation in population size from the largest to the smallest district and generally approving plans with 0.01 percent or smaller deviations. Relevant cases are listed in Box 2.3. One commentator (Baker, 1986:275–276) claimed that a majority of the Supreme Court no longer truly supported the ideal of strict mathematical equality for congressional districts but has felt constrained by precedent. He argued that Congress should pass legislation that would permit a reasonable degree of population variance among districts and require other desirable criteria, such as compactness and contiguity. To date, however, the courts have observed precedent on population equality for congressional redistricting, and Congress has not intervened.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Following the 2000 census, courts continued to uphold strict population equality standards for congressional districts. However, they did not reject plans simply for having slightly more variance than alternative plans. Relevant cases are listed in Box 2.4 (note that not all redistricting challenges have played out by the time of this writing).

As in previous decades, courts in the 1990s and 2000s allowed greater population deviation in drawing state legislative districts. Generally, as before, deviations of less than 10 percent did not have to be justified; deviations of between 10 and 16 percent had to have justification to be upheld, and deviations of more than 16 percent were struck down. Relevant cases in the 1990s are listed in Box 2.5. Relevant cases following the 2000 census are listed in Box 2.6.

2–B.2 Voting Rights Act of 1965 and Amendments

The above discussion of data needs for redistricting has focused on total population figures. The civil rights movement of the 1950s and 1960s led to legislation, court decisions, and administrative practices that moved another requirement front and center—namely, the need for data on race and ethnic origin for purposes of legislative redistricting. The Voting Rights Act, originally passed in 1965 (P.L. 89-110) and extended and amended in 1970, 1975, 1982, and 1992, is the primary piece of legislation in this regard (see Laney, 1992, for a history of the act). The act nowhere stipulates the use of census data, but interpretations of the act by the courts and the Justice Department have virtually mandated the use of census data on race and ethnicity for redistricting.

The original intention of the Voting Rights Act was to make it possible for blacks in the South to participate in elections, an opportunity that was often denied them by unreasonable literacy tests and other barriers to registration and voting. The 1965 act prohibited (in §2) under the authority of the Fifteenth Amendment the enactment of any election law to deny or abridge voting rights on account of race or color. It further specified (in §4) that any state or county that had any test or device as a condition for voter registration on November 1, 1964, and in which the number of registered or actual voters fell below 50 percent of the total voting-age population in the 1964 presidential election could not use a literacy test or any other

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Box 2.3
Congressional Redistricting Cases on Population Equality, 1990s

  • Hastert v. Board of Elections (1991) A three-judge panel of the Northern Illinois federal district court approved the Republican congressional redistricting plan partly on the basis that it had a more precisely equal distribution of population (two districts had 1 more person than the ideal of 571,530 people, or 0.0002 percent deviation) compared with the Democratic plan (deviation of 17 people, or 0.003 percent).

  • State ex rel. Stephan v. Graves (1992) The Kansas federal district court ruled that a congressional district plan with a population deviation of 0.94 percent was unconstitutional because it failed to achieve population equality, citing Karcher v. Daggett (1983). The court rejected maintenance of whole counties in each congressional district as justification for the higher population deviation; it approved an alternative plan with an overall deviation of 0.01 percent (69 people).

  • Anne Arundel County Republican Central Committee v. State Administrative Board of Election Laws (1992) The Maryland federal district court ruled that the General Assembly’s congressional redistricting plan was constitutional despite small mathematical population deviations among districts. The overall variance of the plan was 10 people, or 0.00167 percent. The justifications offered by the state (keeping three major regions intact, creating a minority voting district, and recognizing incumbent representation with its attendant seniority in the House of Representatives) were found sufficient to meet the tests under Karcher.

  • Puerto Rican Legal Defense and Education Fund v. Gantt (1992) The New York Eastern District federal court held that a special master’s plan met the criteria of a population deviation of less than 0.001 percent (2 people separated the largest and smallest district, or less than 0.0004 percent).

  • Mellow v. Mitchell (1992) The Pennsylvania Supreme court upheld a plan selected by a court master that had a total variance of 0.0111 percent of the population (57 people), higher than the variance in some other plans. The court ruled that the deviation was “fully justified by the policy of preserving the boundaries of municipalities and precincts;” its decision was upheld in federal district court.

  • Stone v. Hechler (1992) A three-judge federal district court held that the legislature’s plans for West Virginia’s three congressional districts were acceptable, even though the population deviation was 556 people, or 0.09 percent, because the plan better preserved the cores of prior districts and made the districts more compact than other plans.

SOURCE: Web site for the Minnesota State Senate:

http://www.senate.leg.state.mn.us/departments/scr/redist/redsum [9/1/03].

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Box 2.4
Congressional Redistricting Cases on Population Equality, 2000s

  • Graham v. Thornburgh (2002) A federal 3-judge panel upheld the Illinois legislature’s plan, which had a variance of 33 people (0.0049 percent). An alternative plan would have reduced the variance to 29 people, but the court found that the legislature’s plan had sufficient justification for a marginally higher variance.

  • Jepsen v. Vigil-Giron (2002) A New Mexico state district court upheld a plan with a variance of 166 people (0.027 percent) because it made the least change to the previous districts.

  • Vieth v. Commonwealth (2002) A federal district court rejected the congressional redistricting plan of the Pennsylvania General Assembly because it had a deviation of 19 people (0.0039 percent), split voting precincts, and other problems, and because an alternate plan was available that had a deviation of only 1 person and split no voting precincts. The Assembly thereupon devised a plan with a 1-person deviation.

SOURCE: See Box 2.3.

test or device to screen potential voters. Finally, it provided (in §5) that any covered jurisdiction (i.e., any jurisdiction required to drop voting tests under §4) had to submit “any voting qualification or prerequisite to voting, or standard, practice, or procedure with respect to voting” adopted after November 1, 1964, for “preclearance” to the U.S. Department of Justice or the U.S. District Court for the District of Columbia to determine that there was no abridgement of the right to vote on the basis of race or color.

The 1970 amendments to the Voting Rights Act outlawed literacy tests and other devices in all jurisdictions and extended coverage to jurisdictions that had such tests in November 1, 1968, and in which there was less than 50 percent registration or turnout in the 1968 presidential election. The effect of this provision was to cover subdivisions in northern and western as well as southern states.

The 1975 amendments to the act included a major new provision that extended coverage under the act to protect the voting rights of language minorities on the basis of the equal protection clause of the Fourteenth Amendment. These language minorities were defined to be people of Spanish heritage, American Indians, Asian Americans, and Alaska Natives. The preclearance provisions of the act (i.e., the requirement to submit proposed changes in voting procedures to the Justice Department for approval) were applied to any county,

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Box 2.5
State Legislative Redistricting Cases on Population Equality, 1990s

  • Sinkfield v. Bennett (1997) An Alabama Circuit Court upheld a plan in which one legislative district had a deviation of 10.2 percent because it was a whole county and no other district had more than a 5 percent deviation.

  • Fischer v. State of Board of Elections (1994) The Kentucky Supreme Court affirmed that maintaining the integrity of counties was as important as population equality for legislative districts, so long as the deviation did not exceed 5 percent.

  • Legislative Redistricting Cases (1993) The Maryland Supreme Court affirmed that Maryland’s constitutional language requiring “substantially equal population” did not impose a stricter standard than the 10 percent rule imposed by the Fourteenth Amendment.

  • Hlava v. Nelson (1992) A Nebraska district court held that the Nebraska legislature’s self-imposed statistical guideline allowing no more than a 2 percent deviation in population size of legislative districts was constitutional.

  • Fund for Accurate and Informed Representation, Inc. v. Weprin (1992) The Northern District of New York federal court ruled that the legislature’s plans for assembly districts met the required standard of less than 10 percent deviation (the deviation was 9.43 percent).

  • Voinovich v. Ferguson (1992) The Ohio Supreme Court in 1992 held that a senate district was constitutional even though it deviated by 6 percent from the ideal population size because the Ohio constitution allows districts to deviate from the ideal by up to 10 percent when the district constitutes an entire county; the deviation must be less than 5 percent otherwise. The redistricting plan was challenged on other grounds; finally, in Quilter v. Voinovich (1994), the Ohio Northern District federal court held that a deviation of 13.81 percent for house districts and 10.54 percent for senate districts fell within constitutional limits because of the desire to respect county boundaries.

  • Ater v. Keisling (1991) The Oregon Supreme Court held that the secretary of state’s decision to adopt a plus-or-minus 1 percent deviation standard was not irrational or contrary to the redistricting provisions of the Oregon constitution.

  • Langsdon v. Millsaps (1993) A three-judge district court panel held that a 13.9 percent variance for Tennessee house districts was not justifiable to protect county boundaries when an alternate plan had less than a 10 percent variance and split fewer counties.

  • Holloway v. Hechler (1992) A three-judge federal district court held that a redistricting plan for the West Virginia House of Delegates, with a 9.97 percent deviation, did not violate the Fourteenth Amendment.

  • Gorin v. Karpa (1991) The Wyoming federal district court struck down a legislative plan that had a deviation of 83 percent for house seats and 58 percent for senate seats in order to protect county boundaries, requiring the legislature to come up with a plan with less than 10 percent deviation, which was done.

SOURCE: See Box 2.3.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Box 2.6
State Legislative Redistricting Cases on Population Equality, 2000s

  • In re 2001 Redistricting Cases (2002) The Alaska Supreme Court rejected the Redistricting Board’s plan that had a deviation for 16 house seats of 9.5 percent because the Alaska constitution had been amended in 1998 to make the state standard “as near as practicable” and thus more exacting than the federal standard.

  • Smith v. Idaho Commission on Redistricting (2001) The Idaho Supreme Court rejected a legislative redistricting plan with a deviation of 10.69 percent, given that the state had offered no evidence that the disparity resulted from the advancement of a rational state policy. In a later case, the court rejected a revised plan with an 11.79 percent deviation because policies to preserve county and neighborhood boundaries were not consistently followed statewide.

  • Burling v. Chandler (1992) The New Hampshire Supreme Court adopted a legislative redistricting plan with a deviation of 9.26 percent.

  • Allen v. Pataki (2002) A New York court upheld a state senate redistricting plan with a deviation of 9.78 percent even though previous deviations had been smaller (1.83 percent in 1972, 5.3 percent in 1982, and 4.29 percent in 1992).

  • Deem v. Manchin (2001) A state court upheld a plan for West Virginia senate districts with a deviation of 10.92 percent because the plan recognized the legislature’s goals to maintain county lines as nearly as possible.

  • Arrington v. Elections Board (2002) A three-judge federal court rejected all 16 legislative district plans for Wisconsin and adopted one of its own, which had an overall deviation of 1.48 percent.

SOURCE: See Box 2.3.

city, or township for which the Census Bureau determined that more than 5 percent of the voting-age citizens were of a single-language minority, election materials had been printed only in English for the November 1972 elections, and less than 50 percent of all voting-age citizens in the jurisdiction had registered or voted in the 1972 presidential election. This provision covered the states of Alaska, Arizona, and Texas and political subdivisions in eight other states.

The 1982 amendments to the act kept the basic provisions intact but made some changes. The amendments extended the preclearance requirements of the act until 2007 but provided that Congress reexamine them in 1997. Another provision stated that the standard of proof for judging an election law to be discriminatory was no longer discriminatory intent, but rather discriminatory result. As

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

somewhat of a counterbalance, still another provision stated that minorities had no right to proportional representation, but courts could consider the lack of representation as part of the totality of circumstances in cases brought under the Voting Rights Act.

With regard to data needs for redistricting, §5 of the Voting Rights Act led to the practical necessity for census data on race and ethnicity for redistricting. A key case that supported the use of §5 to review many aspects of state and local electoral systems was Allan v. Board of Education (1969), in which the Supreme Court held that such changes as moving from single-member to multimember districts were “practices or procedures” that were subject to review under §5 because they had the potential of “diluting” the black vote. The Justice Department quickly moved to instruct legal officers in covered jurisdictions to clear every change in voting procedure. Whereas only 323 voting changes were received by the Department for preclearance between 1965 and 1969, almost 5,000 were submitted between 1969 and 1975 (Thernstrom, 1979:59). Parker (1989:59–63) notes that challenges to redistricting plans on the grounds that they are racially discriminatory can be brought under §2 of the act as well as the more frequently invoked §5. Hence, although the preclearance provisions of §5 currently apply to fewer than half the states (in some cases, just to selected jurisdictions in the state; see Laney, 1992), all states must worry about the racial composition of legislative districts if they are to avoid challenges under the Voting Rights Act.

From 1965 to 1988, the Justice Department objected most often to municipal annexations that diluted the voting power of blacks, Hispanics, or other protected minority voters; it objected next most often to changes from single-member districts to at-large voting. The third most common objection (made 248 times) was to redistricting plans that lessened the effectiveness of minority votes, for example, such schemes as dividing concentrations of minority voters into adjoining majority-white areas or minimizing the number of minority districts by placing minority voters in as few districts as possible.

Many court challenges to redistricting plans in the 1990s and after the 2000 census invoked the Voting Rights Act. Pursuant to the language in the 1982 amendments denying a right to proportional representation for minorities but allowing representation to be considered, the courts issued a variety of opinions. Yet whether the

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

courts upheld greater or lesser minority representation, the issue of race and ethnic origin of voters played an important role in Voting Rights Act cases. Relevant cases following the 2000 census are listed in Box 2.7.

2–B.3 Implications of Redistricting for Census Data Requirements

To meet court mandates for equal population size congressional districts with a typical standard of less than 0.01 percent deviation, states almost necessarily rely on the block-level data in the P.L. 94-171 file. The average size of a congressional district in 2000 was about 646,000 people, so that 0.01 percent was about 65 people, which compares to the average block size of about 30 people. Many states try to preserve voting precinct and even county boundaries when delineating congressional districts, but block data are needed to meet strict population size standards.

For state legislative districts, block data are also sometimes needed to meet the looser standard of 10 percent deviation because of the smaller size of such districts. As of 2000, the median population size of state house districts was about 40,000 people, with a range from about 423,000 (California) to about 3,000 (New Hampshire) (see Table 2.1). A 10 percent deviation for the median state means that the smallest district must have no fewer than 38,000 people and the largest district no more than 42,000 people, for a difference of 4,000 people—close to the size of an average census tract. For New Hampshire, a 10 percent deviation would require the use of block group or block data to obtain equal population size within a 10 percent range from 2,850 to 3,150 people.

The data files provided by the Census Bureau to the states for redistricting carry not only population counts but also counts of voting-age population by race and ethnicity, which most states use in drawing district boundaries (see National Conference of State Legislatures, 1992:8). The 2000 census P.L. 94-171 data provided to the states by April 1, 2001, included an unprecedented array of race and ethnic origin data for the total population and people age 18 and over for states, counties, minor civil divisions, places, voting districts (when specified by the state), census tracts, block groups, and blocks. In all, the file provided 63 race categories by Hispanic

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Box 2.7
Voting Rights Act Redistricting Cases, 2000s

  • Page v. Bartels (2001) The New Jersey federal district court upheld a legislative redistricting plan that reduced the concentration of blacks to less than a majority of the voting age population in three districts and increased the concentration in a fourth district, arguing that the result was likely to increase by one the number of blacks elected to the legislature because of white and Hispanic support for black candidates. The same court also upheld a senate district in which the black voting age population was raised from 3.9 to 35.3 percent. (The challenger had argued that minority incumbents had been protected but not white incumbents.)

  • Stevenson v. Bartlett (2001) The North Carolina Supreme Court held that creation of minority state senate and house districts to satisfy the Voting Rights Act and devising a plan that did not cause the opportunities for minorities to regress took precedence over the state constitution’s requirement to preserve county boundaries to the extent possible.

  • Bone Shirt v. Hazeltine (2002) A three-judge federal district court prevented South Dakota from implementing its legislative redistricting plan because Native Americans were packed into a single senate district in which they constituted 86 percent of the voting-age population and because the plan had not been precleared with the Justice Department.

  • Balderas v. State (2002) The Texas Eastern District federal court found that the legislature could not have created additional Latino majority districts without risking retrogression (dilution) in existing Latino majority districts. It declined to find any necessity to create minority “influence districts.”

  • West v. Gilmore (2002) A Virginia circuit court ruled against the legislature’s house and senate redistricting plan for reasons that include that black voters were packed into as few districts as possible in order to minimize their political influence. In some districts, blacks were more than 55 percent of the voting-age population, a percentage that in past elections had enabled minority candidates to win by landslide proportions. The Supreme Court of Virginia reversed the decision, upholding the original plan.

SOURCE: See Box 2.3.

and not Hispanic for each geographic area in order to reflect all of the possible race combinations afforded by the new option of checking more than one race on the 2000 questionnaire.

A difficulty is that the accuracy of total population counts for individual blocks is not high, whether the data are from the enumeration or are adjusted for measured net undercount. Errors in the population counts for blocks can occur because of such factors as misgeocoding—that is, assigning addresses to the wrong block—as well as omissions and duplications or other erroneous enumera-

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

tions. Errors in adjusted data include sampling error and biases in the adjustment procedure. Inaccuracy in block-level counts may also arise from imputation for nonresponse, proxy response, and other measurement issues. Users must be aware that block data are simply building blocks for larger areas for which relative accuracy can be better ensured.

The potential effect of census error on legislative redistricting is particularly hard to assess, given the intensely political nature of the process. The shrewdness of a mapmaker in piecing together blocks into districts arguably has more effect on any perceived bias in the district than do block-level census errors. However, it is certainly possible that high levels of error in the census could have major effects on districts within states. For instance, errors in the census might affect the urban-rural balance within a state, and any resulting district map could dilute the vote of urban residents at the expense of rural residents—or vice versa. Such outcomes would depend on the average size of the districts, the differential undercoverage rates of major population groups, the proportionate distribution among areas of these population groups, and the number of districts with high rates of census undercoverage.

2–C OTHER USES OF BASIC CENSUS DATA

Census data on age, race, ethnicity, and sex, which are asked of the entire population, have many uses, particularly as they form the basis of small-area population estimates that the Census Bureau develops for years following each census. Currently, the Bureau produces estimates of total population by single years of age, sex, race, and Hispanic origin on a monthly basis for the United States and annually for states and counties as of July 1 of each year. The Bureau also produces estimates of the total population every 2 years for incorporated places and minor civil divisions of counties (in states that have such divisions). Recently, the Bureau began producing biennial estimates of total population and children ages 5 through 17 for school districts. The estimates are produced by updating the census year figures with data from such sources as birth and death records (see Citro, 2000e).

Census-derived population estimates serve a variety of needs of federal, state, and local government agencies and academic and

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Table 2.1 Number and Approximate Average Population Size of State Senate and House Districts, by State, 2000

 

Senate Districts

House (Assembly) Districts

State

Number

Average Size

Number

Average Size

Alabama

35

127,000

105

42,000

Alaska

20

31,000

40

16,000

Arizona*

30

171,000

60

86,000

Arkansas

35

76,000

100

27,000

California

40

847,000

80

424,000

Colorado

35

123,000

65

66,000

Connecticut

36

95,000

151

23,000

Delaware

21

37,000

41

19,000

Florida

40

400,000

120

133,000

Georgia

56

146,000

180

45,000

Hawaii

25

48,000

51

24,000

Idaho*

35

37,000

70

18,000

Illinois

59

210,000

118

105,000

Indiana

50

122,000

100

61,000

Iowa

50

59,000

100

29,000

Kansas

40

67,000

125

22,000

Kentucky

38

106,000

100

40,000

Louisiana

39

115,000

105

43,000

Maine

35

36,000

151

8,000

Maryland

47

113,000

141

38,000

Massachusetts

40

159,000

160

40,000

Michigan

38

262,000

110

90,000

Minnesota

67

73,000

134

37,000

Mississippi

52

55,000

122

23,000

Missouri

34

165,000

163

34,000

Montana

50

18,000

100

9,000

Nebraska

49

35,000

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

 

Senate Districts

House (Assembly) Districts

State

Number

Average Size

Number

Average Size

Nevada

21

95,000

42

48,000

New Hampshire

24

51,000

400

3,000

New Jersey*

40

210,000

80

105,000

New Mexico

42

43,000

70

26,000

New York

61

311,000

150

127,000

North Carolina

50

161,000

120

67,000

North Dakota*

49

13,000

98

7,000

Ohio

33

344,000

99

115,000

Oklahoma

48

72,000

101

34,000

Oregon

30

114,000

60

57,000

Pennsylvania

50

246,000

203

60,000

Rhode Island

50

21,000

100

10,000

South Carolina

46

87,000

124

32,000

South Dakota*

35

22,000

70

11,000

Tennessee

33

172,000

99

57,000

Texas

31

673,000

150

139,000

Utah

29

77,000

75

30,000

Vermont

30

20,000

150

4,000

Virginia

40

177,000

100

71,000

Washington*

49

120,000

98

60,000

West Virginia

34

53,000

100

18,000

Wisconsin

33

163,000

99

54,000

Wyoming

30

16,000

60

8,000

NOTES: For a 10 percent deviation or less, the smallest district must be 95 to 100 percent of the average district size, and the largest district must be 100 to 105 percent of the average district size. Nebraska has a unicameral legislature.

* Voters elect one senator and two assembly members from a set of legislative districts.

SOURCE: Adapted from National Council of State Legislatures:

http://www.ncsl.org/programs/legman/elect/cnstprst.htm [9/1/03]. In states with mixed multi-member districts, district population is for single-member districts.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

private-sector users. The estimates are used by the National Center for Health Statistics as denominators for important national and subnational statistics, such as birth and death rates (by age, sex, and race) for the United States, states, and local areas. Currently, federal agencies allocate more than $200 billion of federal dollars to states and other areas by formulas, many of which include population estimates as one of the factors in the formula. For example, the Prevention and Treatment of Substance Abuse Block Grants Program allocates funds to states (estimated $1.6 billion obligated in fiscal 2002) with a formula that includes two equally weighted factors: each state’s share of the population ages 18 to 24 (double counting urban residents ages 18 to 24) and each state’s share of the population ages 25 to 64 (see U.S. General Accounting Office, 1999b; National Research Council, 2003b; see also Section 2-D.1).

Major federal household surveys, such as the Current Population Survey (source of official employment and poverty statistics) and the Survey of Income and Program Participation, use census-based population estimates as survey controls—that is, the survey estimates are adjusted to agree with national population estimates by age, sex, race, and Hispanic origin. Without reweighting to national estimates, the surveys would underestimate many demographic groups because coverage of the population is typically less complete in household surveys than in the decennial census (see National Research Council, 1995a:App.B). Beginning in 1994 the population controls for weighting survey results included an adjustment for the undercount in the 1990 census, although such an adjustment was not part of the official estimates that were publicly available. Population estimates beginning in 2001 are based on the 2000 census results, not adjusted for estimated net undercount or overcount.

At the local level, census-derived population estimates are used by planning agencies for the development, implementation, and evaluation of programs in a host of areas, such as day care, job training, elderly assistance, and transportation planning. Governments compare administrative records counts of service users (e.g., services for the elderly) to census counts for the relevant populations to document need and to evaluate the reach and effectiveness of programs.

The private sector makes extensive use of census-derived population estimates and year-to-year change in business planning (see

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

Naymark and Hodges, 2000). For example, growth in the number of teenagers may support a decision to launch a new product aimed at that market; the distribution of the Hispanic population may help guide the placement of Spanish-language advertising, signs, and merchandise; and determining when the population of a growing suburb will reach a threshold for opening a new store can help in site planning and development.

Research uses of basic census data include analyses of residential segregation by race and ethnicity among neighborhoods within and across cities and metropolitan areas and over time by comparison with previous censuses. Another research use of basic census data is to analyze changing age composition and the implications for state and local government finance.

The major issues of concern to our panel with regard to the basic census data (which also include household relationship and housing tenure) concern the quality of the estimates. Specific quality issues that we address (see Chapter 7) include response rates for individual items and the effects of imputation procedures to compensate for nonresponse; consistency of reporting for the same people in the census and other sources (an indicator of reliability); and reporting errors (e.g., reporting age as younger or older than actual age) and the net biases from reporting errors (e.g., the extent to which underreports and overreports of age fail to balance out). Given that people attach different meanings to race and ethnicity, consistency and reporting errors may be particularly problematic for those items.

For census-derived population estimates, an added concern is the quality of the administrative records data that are used to update the census figures to account for births, deaths, and net migration. Specific issues include compatibility of reporting of race and ethnicity among the different data sets and the accuracy of estimates of net illegal immigration. For small-area population estimates, an added issue (which we do not discuss) is the accuracy of the data and methods used to estimate migration flows among areas.

2–D USES OF ADDITIONAL DATA FROM THE LONG FORM

Beginning in 1820, when enumerators were asked to tally the number of noncitizens in each household and the number engaged in agriculture, manufacturing, and commerce, the decennial census

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

has been a vehicle to obtain additional information beyond the basic head count by age, race, and sex. By 1910 the census questionnaire had grown to include 34 questions for household residents, including items on age, race, sex, household relationship, marital status, citizenship, education, health, home ownership, language, occupation, place of birth, service in the Civil War, and—in a last-minute addition by the Congress—language of mother and father (Magnuson, 2000a). The 1910 census also included special questions for American Indians, Alaska Natives, and blind and deaf people.

Beginning in 1940 statistical sampling was used to accommodate additional questions without burdening the entire population: six new questions on socioeconomic status and housing adequacy were asked of a 5 percent sample of the population in 1940 (6.5 million people). The 1960 census, which first used the U.S. Postal Service for questionnaire delivery, introduced the concept of separate “short” and “long” forms. Since then, the short form has included basic items asked of all U.S. residents, and the long form has included the short-form items together with additional items asked of a sample (about one-sixth of the population in 2000, or 45 million people). The added questions on the 2000 census long form (see Appendix B) included 36 population items, covering such topics as marital status, educational attainment, place of birth, citizenship, language spoken at home, English proficiency, ancestry, military service, year moved into residence, various types of disability, responsibility for grandchildren in the home (new item in 2000), current and prior-year employment status, occupation and industry, transportation to work, and income by type. The 2000 census long form also included 26 housing items, covering such topics as market value of owned home, rent, cost of utilities, characteristics of house or apartment (e.g., number of bedrooms, heating fuel), year structure built, ownership finances (mortgage payment, taxes, home insurance), and number of vehicles (including autos, vans, and trucks).4

The census long-form-sample data have extensive uses in the public and private sectors. At present the long-form sample is generally the only source of nationwide small-area data (for counties, cities, towns, neighborhoods) on the topics it covers, and the size of

4  

Numbers of questions or items should be taken as approximate: one question may have several parts that refer to distinct items.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

the long-form sample also makes it a unique resource for analysis of small population groups, such as elderly minorities. Below we briefly describe uses of long-form data by: (2-D.1) the federal government (see Citro, 2000d; National Research Council, 1995b:Apps. C, G, H, M); (2-D.2) state and local governments (see Gaines et al., 2000; National Research Council, 1995b:Apps. E, G, H); (2-D.3) the private sector (see Naymark and Hodges, 2000; National Research Council, 1995b:App. F; Spar, 2000); and (2-D.4) academia (see National Research Council, 1995b:App. D).

2–D.1 Federal Government Uses of Long-Form-Sample Data

Many federal agency uses of census long-form data are mandated in law, either directly or indirectly in that the census is the only feasible data source to satisfy a mandate. Indeed, no item was included in the 2000 census if it was not deemed to serve an important federal purpose (see Section 3-B.2). Such purposes include implementation of sections of the Voting Rights Act, allocation of federal funds to states and localities, assessment of charges of employment discrimination, and planning, monitoring, and evaluation of federal programs.

  • Since §203 was added to the Voting Rights Act in 1975, census long-form data have played a key role in ensuring that localities assist voters who have trouble reading English.

    • §203 required counties, cities, and townships to provide election materials and oral assistance in another language as well as in English in areas for which the Census Bureau determined that 5 percent of the voting-age citizens were of a single-language minority and had an illiteracy rate in English (defined as failure to complete fifth grade) higher than the illiteracy rate in English of the entire nation.

    • The 1982 amendments asked the Census Bureau to investigate the usefulness of 1980 census long-form questions on mother tongue and English-speaking ability for determining coverage under the bilingual assistance provision. On the basis of the Bureau’s research, the definition of a covered area became one in which 5 percent of the citizens of voting age spoke a single minority language, said

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

they did not speak English very well, and had a higher illiteracy rate than the nation as a whole. The result of this change was to reduce the number of covered areas from about 500 following the 1970 census to about 200 following the 1980 census; about 300 covered areas were identified after the 1990 census.

  • The 1992 amendments extended the bilingual voting assistance provision to 2007 and made some additional minor changes to the definition (see Bureau of the Census, 1976; Kominski, 1985, 1992). About 300 areas were identified as covered under the bilingual assistance provision after the 2000 census (Federal Register, 67[144, July 26, 2002]:48871–48877).

  • Over $200 billion of federal funds are allocated each year to states and localities by means of formulas, many of which directly or indirectly make use of census long-form data (see National Research Council, 2001b, 2003b). Examples include:

    • Medicaid (estimated $145 billion obligated in fiscal year 2002): Reimburses a percentage of each state’s expenditures for medical care services for low-income elderly and disabled people and families with dependent children by a formula that uses per capita income estimates from the U.S. Bureau of Economic Analysis (BEA). BEA develops these estimates by using data from a wide range of administrative records, the decennial census long-form sample and other censuses and surveys, and census-based population estimates (as denominators). The Medicaid formula is also used to allocate funds under other programs (e.g., Foster Care-Title IV-E, with estimated obligations of $5.1 billion in fiscal 2002).

    • Title 1 of the Elementary and Secondary Education Act (estimated $9.5 billion obligated in fiscal 2002): Allocates funds to school districts to meet the needs of educationally disadvantaged children on the basis of a formula that includes estimates of poor school-age children. The estimates were previously derived from the most recent

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

census long-form sample; currently, the estimates are obtained from statistical models developed by the Census Bureau, which include census poverty data as one input.

  • Special Education Grants to States (estimated $7.5 billion obligated in fiscal 2000): Allocates funds to states for the education of handicapped children in part on the basis of a formula that includes the number of children in the age ranges mandated by the state’s program and the number of children in poverty in those age ranges. Census long-form-sample data are the source for the estimates.

  • Community Development Block Grants, Entitlement Grants Program ($3 billion authorized in fiscal 2002): Allocates 30 percent of funds to states and 70 percent of funds to localities (metropolitan cities and urban counties) on the basis of the larger amount computed under two formulas. Both formulas use census complete-count and long-form-sample data—total population, poverty population, and overcrowded housing units in the first formula and total population, poverty population, and housing units built before 1940 in the second formula.

  • Home Investment Partnership Program (estimated $1.8 billion obligated in fiscal 2002): Allocates funds to states, cities, urban counties, and consortia of local governments on the basis of a formula that uses census long-form-sample data, such as estimates of rental units built before 1950 occupied by poor families.

  • Workforce Investment Act Adult Program and Youth Activities (estimated $1 billion obligated in fiscal 2002): These programs allocate funds to service delivery areas (one or more counties or cities of 200,000 or more population) by use of formulas that include census long-form-sample data for specified age groups (people ages 22–72 and people ages 16–21, respectively) in families with income not more than the higher of the official poverty line or 70 percent of the Department of Labor lower living standard income level.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×
  • Many federal agencies use census long-form-sample data for program planning, monitoring, evaluation, enforcement, and development of special statistics and surveys. For example:

    • The U.S. Equal Employment Opportunity Commission regularly uses census long-form-sample labor force data on occupation and industry for ZIP codes and other geographic areas to analyze statistical evidence in class action charges of employment discrimination by age, sex, race, or ethnicity. In addition, federal agencies, as employers, use such data to evaluate their own recruitment and promotion systems.

    • The U.S. Department of Transportation uses census long-form-sample data on disability for traffic analysis zones to monitor compliance with the Federal Transit Act and the Americans with Disabilities Act. The Department has helped develop for every census since 1960 a transportation planning package, which provides local governments with detailed information on commuting flows in their areas (cross-tabulating place of residence by place of work for traffic analysis zones made up of groups of census blocks).

    • The U.S. Department of Housing and Urban Development uses census long-form-sample data on rental housing condition to construct fair market rents for non-metropolitan counties and all but the largest metropolitan areas (for which it uses the American Housing Survey). Fair market rents are used to determine rent subsidies to eligible families under the Section 8 Housing Assistance Payments Program; for areas for which census data are used, fair market rates are set at a percentile of the distribution of gross rents (including utility costs) for two-bedroom apartments with electricity and complete kitchen and plumbing facilities and into which the occupant moved within the last 5 years.

    • Since 1950, the U.S. Office of Management and Budget has used census long-form-sample data on commuting patterns to help define metropolitan statistical areas (MSAs).

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

In turn, there are many federal agency applications of MSAs, such as determining eligibility for fund allocations.

  • Following every census since 1960, the Science Resources Statistics Division of the National Science Foundation has commissioned a survey by the Census Bureau of a sample of college graduates drawn from the census long-form records, with oversampling of people who reported a science or engineering occupation. People identified as scientists and engineers in the survey are followed up every 2 years to track changes in their training and employment.

2–D.2 State and Local Government Uses of Long-Form-Sample Data

State and local governments use small-area census data extensively for such purposes as fund allocation, program planning and evaluation, facility planning, disaster planning, and economic development and marketing.

  • Examples of formula allocation by states include: allocation of over $200 million in Colorado child welfare block grants to counties with a formula that includes census estimates of the county’s number of children below 200 percent of the poverty line; allocation of $5 million in Florida Intensive Crisis Counseling funds to counties with a formula that includes census estimates of the number of poor female-headed households with dependent children (see Butcher and Dunton, 1999).

  • Examples of state and local government program planning and evaluation include: using census long-form-sample data on English language proficiency, language spoken at home, and years of school completed to identify neighborhoods in which residents may require special assistance in using local government services; developing socioeconomic profiles of census tracts to use in applications for funds from federal housing and other grant programs.

  • Examples of facility planning include: using census long-form-sample data on commuting patterns to help redesign

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

bus routes and plan new roads; comparing distributions of census small-area characteristics with corresponding distributions of service users (e.g., people visiting health clinics) to determine where new service facilities are most needed (such studies are often done by geocoding administrative records addresses of service users to census geographic areas).

  • Examples of disaster planning include: using census long-form-sample data on vehicle ownership and disability together with basic population data to estimate numbers of people who might need to be evacuated in the case of a disaster (e.g., from an area prone to flooding) and how many of them might need transportation assistance; using census place of work and place of residence data to estimate daytime populations for use in developing disaster planning for employment centers.

  • Examples of economic development and marketing include: using census long-form-sample data on educational attainment, occupation, and labor force participation of the adult population to attract prospective businesses by informing them of the availability of an appropriately skilled labor force; using census long-form-sample data on ancestry and language to inform businesses of opportunities for serving particular markets.

2–D.3 Private-Sector Uses of Long-Form-Sample Data

Retail establishments and restaurants, banks and other financial institutions, media and advertising firms, insurance companies, utility companies, health care providers, and many other segments of the business world use census long-form-sample data, as do nonprofit organizations. An entire industry developed after the 1970 census to repackage census data, use the data to develop lifestyle cluster systems (neighborhood types that correlate with consumer behavior and provide a convenient way of condensing and applying census data), and supply address coding and computer mapping services to make the data more useful. Typical private-sector uses of census data include site location, targeting of advertising and services, workforce development, and assessment of compliance with government requirements, such as equal employment opportunity.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×
  • Many retail and service businesses use census population, poverty, income, and labor force data for specific locations to study the possibilities for retail outlets.

  • Some radio stations relate callers’ ZIP codes to census tract profiles to determine areas with residents who are partial to the station’s format, using the information to develop a marketing plan to target those areas.

  • Some churches compare members’ characteristics from a survey to census characteristics for the surrounding community to determine ways in which members are similar to and distinct from the community and use the information to develop an outreach program.

  • All banks are required to use median household income and income distributions by census tract to ensure compliance with federal mortgage lending guidelines regarding race, as well as for meeting other regulatory requirements.

  • Most employers are required to use local-area data on occupation by sex, age, race, and ethnicity to assess compliance with federal equal opportunity employment and anti-discrimination laws.

2–D.4 Research Uses of Long-Form-Sample Data

Research studies using long-form-sample data have developed basic understanding of key social processes, such as migration flows and the social and economic effects of the aging of the population. They have also contributed important information to policy makers and the public on such topics as demographic changes, trends in educational attainment, concentrations of people in poverty, and local exposure to environmental hazards. Some research applications use tabular data for small areas. Others use public use microdata sample (PUMS) files, which are available for most censuses back to 1850—the first census to obtain data about individuals rather than summary data for whole households (see Box 2.1; Ruggles, 2000).

  • The aging of the population has led to heightened research attention on the characteristics of older people and how they are

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

changing over time. Census small-area tabulations support analyses of migration flows and concentrations of the elderly by geographic area in total and for subgroups defined by such characteristics as income, living arrangements, labor force attachment, and extent of disabilities. Microdata sample files support detailed analyses of different groups of the elderly, such as those with different disabilities and the relationship of disability to education, labor force attachment, and income. Such analyses are not often possible with other data sources, which have much smaller sample sizes than the microdata sample files. The availability of these files for previous censuses permits rich historical analyses of the aging of the U.S. population and the different experiences of the elderly over time.

  • Census data support research on the process of education and the consequences of education on individuals’ life chances. Education researchers use small-area census data on median years of school completed, average income, and employment patterns to understand the challenges facing different school districts. They use microdata sample files to study how age and race groups differ on such factors as educational attainment, income, and housing quality.

  • Path-breaking analyses of 1970 and 1980 census small-area tabulations revealed a large increase during the 1970s in the number of urban neighborhoods in which more than 40 percent of the families had incomes below the official poverty line. The number of people living in such areas also increased dramatically, and a large proportion of them were blacks living in a handful of the nation’s largest cities. These tabulations stimulated research with census and other data on the correlates and consequences of concentrated urban poverty. For example, detailed longitudinal data for families in the ongoing Panel Survey of Income Dynamics were augmented by census characteristics of the neighborhoods in which the sample families lived, permitting rich contextual analyses of family outcomes.

  • Census socioeconomic profiles for small areas, when related to environmental data, permit analyses of the distribution of

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
×

environmental risks for different population groups and are an essential basis for studies of health effects of such local hazards as toxic waste dumps.

  • Census small-area data are an unparalleled resource for analysis of migration flows over time among regions, states, counties, and places and the consequences for changing demographic and economic conditions among different parts of the country. Microdata sample files permit detailed analysis of the characteristics of long-distance migrants versus those who migrate shorter distances or not at all.

Suggested Citation:"2 Census Goals and Uses." National Research Council. 2004. The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press. doi: 10.17226/10907.
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The decennial census was the federal government’s largest and most complex peacetime operation. This report of a panel of the National Research Council’s Committee on National Statistics comprehensively reviews the conduct of the 2000 census and the quality of the resulting data. The panel’s findings cover the planning process for 2000, which was marked by an atmosphere of intense controversy about the proposed role of statistical techniques in the census enumeration and possible adjustment for errors in counting the population. The report addresses the success and problems of major innovations in census operations, the completeness of population coverage in 2000, and the quality of both the basic demographic data collected from all census respondents and the detailed socioeconomic data collected from the census long-form sample (about one-sixth of the population). The panel draws comparisons with the 1990 experience and recommends improvements in the planning process and design for 2010. The 2000 Census: Counting Under Adversity will be an invaluable resource for users of the 2000 data and for policymakers and census planners. It provides a trove of information about the issues that have fueled debate about the census process and about the operations and quality of the nation’s twenty-second decennial enumeration.

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