California and the 2000 Census |
Introduction |
As the U.S. Census Bureau prepares to conduct the nation's next decennial census on April 1, 2000, controversy exists concerning plans to supplement the traditional population headcount with estimates derived from statistical sampling techniques. | |
LAO Findings |
In 1990, the nation's population was undercounted by roughly 1.6 percent.
California's undercount, however, was much higher--2.7 percent. This higher
undercount likely cost California one seat in the U.S. House of Representatives
and at least $2 billion in federal funds during the 1990s.
Different subgroups of the population have been undercounted at different rates. For example, undercount rates were highest for minorities, renters, and those persons living in nontraditional households. As a result, the undercount rates varied significantly among counties. For instance, in 1990 Los Angeles County and most counties in the San Joaquin Valley had rates much higher than the statewide average. The bureau currently plans to release two sets of population figures--one using traditional counting techniques and a second set which uses sampling to correct for the undercount. Congress, however, has not as yet provided funding for the sampling process. If sampling-adjusted numbers are provided, state policymakers will have to decide which set of data to use for redistricting in California and for allocating state funds to localities. |
In about a year, the first decennial census of the new millennium--Census 2000will be conducted. The decennial census is the single most important source of information about the people of the United States, and the forthcoming census will be the twenty-second that has taken place over the past 200 years, beginning in 1790.
Since that first census, each decennial census has attempted to count each and every person in the country via direct contact. With recent censuses, each household receives a questionnaire to answer and return via the U.S. mail. Households that do not respond to the questionnaire are subsequently visited by census staff. This self-enumeration approach is rooted in the concept of relying on a minimally intrusive process and respect for individual privacy.
In contrast to this method, some governments use more invasive approaches. In Turkey, for example, its latest census involved counting the entire population manually in one day over a 14-hour period, with people being required to stay home and be counted under threat of punishment if found in public without special permission during this time interval.
The decennial census is important because it provides the only true statistical "snapshot" of the entire U.S. population--both in terms of its size and characteristics. It is used for a wide variety of purposes--by economists and the business community in documenting demographic trends and their implications, by policymakers to understand the characteristics of the population and its needs, by governments to allocate spending to different governmental entities, and by federal authorities to determine the allocation/apportionment of electoral districts and how many representatives each state will have in the Congress. Given these uses, the census is an extremely important undertaking, and its integrity and accuracy are of paramount importance.
Conducting the census is inherently an extremely challenging undertaking involving thousands of census workers, a budget in the billions of dollars, and requiring the voluntary cooperation of hundreds of millions of people. The challenge is complicated by the sheer physical size of the country, its geographic diversity, the mobility of its population, its high rates of foreign in-migration, and its nonhomogeneous population reflecting its great ethnic diversity and wide mix of urban, suburban, and rural communities. It also appears that Americans are becoming a bit less responsive to the census questionnaire process. Given this, conducting the census today is a truly massive and difficult undertaking, and inherently open to debate and disagreement about how it can best be carried out and/or improved.
History indicates that problems with obtaining accurate census counts are not new. Even when Thomas Jefferson--who headed-up the first censusreported the results, he noted that there was evidence that some persons had been missed. Over the years, as the country has continued to expand and society has undergone changes, there always have been new challenges to obtaining accurate census counts.
As the U.S. Census Bureau approaches the 2000 census, however, an unusual degree of controversy exists. The key issue is: Should a traditional headcount be relied on as in past years, or should this headcount be supplemented with statistical estimates to account for persons missed by the enumerators? This has been referred to as the statistical sampling debate, and has filled the newspaper headlines on-and-off, been the topic of conferences and symposiums for economists and demographers, resulted in Congressional hearings, and been the subject of litigation.
The interest in statistical sampling evolved in response to documented problems experienced in previous decennial censuses in accurately measuring the population. The U.S. Census Bureau had previously determined that its decennial censuses were resulting in population undercounts, and the idea of sampling was proposed in part to deal with them. The fact that particularly significant undercounts occurred in the 1990 census has been especially well documented and publicized in recent years.
Of particular concern has been the fact that states experiencing larger-than-average undercounts have been "shorted" federal funds, given that many federal funding formulas use population as a factor in determining the share of funds going to individual states. As discussed below, California is significantly affected by undercounting.
Census undercounts can occur for two basic reasons: (1) the "master list" of households used to identify people is not completely accurate, and (2) difficulties are encountered in tracking down and collecting information on individuals who live in households. Figure 1 (see page 4) provides the Census Bureau's own estimates of the census undercount since 1940. While the accuracy of the census improved steadily (that is, the undercount declined) between 1940 and 1980, the 1990 census took a step backward on the fundamental issue of accuracy. Indeed, the 1990 count missed 4 million people, an error margin of 1.6 percent. More troubling, the 1990 census was the first to be less accurate than its predecessor.
Compounding the undercounting problem is that different subgroups of the population are undercounted to different degrees. For instance, African Americans tend to be undercounted to a greater degree than the population generally. After the 1940 census, for example, the Census Bureau gave the Selective Service an estimate of how many young men it could expect to answer its call for the war effort. In total, 3 percent more men registered for the draft than had been counted by enumerators. Among the African-American community, however, 13 percent more men showed up for registration than had been expected based on 1940 census data. Similarly, in the 1990 census, it has been estimated that African Americans had a net undercount of 4.4 percent, compared to only 1.2 percent for non-African Americans. The latter included 0.9 percent for whites and 2.3 percent for Asian Americans.
Undercounting is caused by many factors:
The 1990 census was the most expensive in history, costing $25 per housing unit. In contrast, on an inflation-adjusted basis, the 1970 census cost only $11 per housing unit, and the 1980 census cost $20 per housing unit. Therefore, even after accounting for inflation and increases to population, the 1990 census cost twice as much as the 1970 census.
Much of this cost increase can be explained by the decline in the percentage of households that returned the census questionnaire by mail, and the resulting need of more expensive, labor-intensive follow-up procedures using hundreds of census takers going door-to-door. When census questionnaires were mailed in 1970, 78 percent of housing units mailed back their questionnaires. By 1990, that percentage had fallen to 65 percent.
Thus, it has been argued that the 1990 census failed on two fronts: (1) it was too expensive and (2) it counted too few people. It is because of this experience of the 1990 census that many economic and demographic experts hold the view that is has become both physically impossible and cost-prohibitive to even attempt to directly count every person in the United States.
The 1990 census undercount varied significantly by state. In large part this reflected the fact discussed above that undercount rates tend to differ for different population characteristics and living situations, and these are not the same in all states. In addition, the extent to which a state's population lives in urban versus suburban versus rural settings is a factor.
As noted above, the net 1990 national undercount was estimated to be 4 million people, or 1.6 percent of the population. As shown in Figure 2, California's undercount was disproportionately worsean estimated 835,000, or 2.7 percent, of the state's population, was missed. In terms of the number of people undercounted, its 835,000 undercount was almost double that of Texas, the state with the second-highest numerical undercount. In percentage terms, the state's undercount rate was fourth highesttrailing only the District of Columbia, New Mexico, and Texas. The geographic distribution of the state's undercount is discussed later.
Figure 2 | ||||
1990 Census Undercount, by Region and State | ||||
Region/State | 1990 Population Total | |||
Reported | Adjusted for Estimated Undercount | Estimated Undercount | ||
Amount | Percent | |||
Northeast: | ||||
Connecticut | 3,287,116 | 3,308,343 | 21,227 | 0.6% |
Maine | 1,227,928 | 1,237,130 | 9,202 | 0.7 |
Massachusetts | 6,016,425 | 6,045,224 | 28,799 | 0.5 |
New Hampshire | 1,109,252 | 1,118,632 | 9,380 | 0.8 |
New Jersey | 7,730,188 | 7,774,461 | 44,273 | 0.6 |
New York | 17,990,455 | 18,262,491 | 272,036 | 1.5 |
Rhode Island | 1,003,464 | 1,004,815 | 1,351 | 0.1 |
Pennsylvania | 11,881,643 | 11,916,783 | 35,140 | 0.3 |
Vermont | 562,758 | 569,100 | 6,342 | 1.1 |
Midwest: | ||||
Illinois | 11,430,602 | 11,544,319 | 113,717 | 1.0% |
Indiana | 5,544,159 | 5,572,057 | 27,898 | 0.5 |
Iowa | 2,776,755 | 2,788,332 | 11,577 | 0.4 |
Kansas | 2,477,574 | 2,495,014 | 17,440 | 0.7 |
Michigan | 9,295,297 | 9,361,308 | 66,011 | 0.7 |
Minnesota | 4,375,099 | 4,394,610 | 19,511 | 0.4 |
Missouri | 5,117,073 | 5,148,974 | 31,901 | 0.6 |
Nebraska | 1,578,385 | 1,588,712 | 10,327 | 0.7 |
North Dakota | 638,800 | 643,033 | 4,233 | 0.7 |
Ohio | 10,847,115 | 10,921,741 | 74,626 | 0.7 |
South Dakota | 696,004 | 702,864 | 6,860 | 1.0 |
Wisconsin | 4,891,769 | 4,921,871 | 30,102 | 0.6 |
South: | ||||
Alabama | 4,040,587 | 4,113,810 | 73,223 | 1.8% |
Arkansas | 2,350,725 | 2,392,596 | 41,871 | 1.8 |
Delaware | 666,168 | 678,385 | 12,217 | 1.8 |
District of Columbia | 606,900 | 628,309 | 21,409 | 3.4 |
Florida | 12,937,926 | 13,197,755 | 259,829 | 2.0 |
Georgia | 6,478,216 | 6,620,641 | 142,425 | 2.2 |
Kentucky | 3,685,296 | 3,746,044 | 60,748 | 1.6 |
Louisiana | 4,219,973 | 4,314,085 | 94,112 | 2.2 |
Maryland | 4,781,468 | 4,882,452 | 100,984 | 2.1 |
Mississippi | 2,573,216 | 2,629,548 | 56,332 | 2.1 |
North Carolina | 6,628,637 | 6,754,567 | 125,930 | 1.9 |
Oklahoma | 3,145,585 | 3,202,963 | 57,378 | 1.8 |
South Carolina | 3,486,703 | 3,559,547 | 72,844 | 2.0 |
Tennessee | 4,877,185 | 4,964,261 | 87,076 | 1.8 |
Texas | 16,986,510 | 17,472,538 | 486,028 | 2.8 |
Virginia | 6,187,358 | 6,313,836 | 126,478 | 2.0 |
West Virginia | 1,793,477 | 1,819,363 | 25,886 | 1.4 |
West: | ||||
Alaska | 550,043 | 561,276 | 11,233 | 2.0% |
Arizona | 3,665,228 | 3,754,666 | 89,438 | 2.4 |
California | 29,760,021 | 30,597,578 | 837,557 | 2.7 |
Colorado | 3,294,394 | 3,363,637 | 69,243 | 2.1 |
Idaho | 1,006,749 | 1,029,283 | 22,534 | 2.2 |
Hawaii | 1,108,229 | 1,129,170 | 20,941 | 1.9 |
Montana | 799,065 | 818,348 | 19,283 | 2.4 |
Nevada | 1,201,833 | 1,230,709 | 28,876 | 2.3 |
New Mexico | 1,515,069 | 1,563,579 | 48,510 | 3.1 |
Oregon | 2,842,321 | 2,896,472 | 54,151 | 1.9 |
Utah | 1,722,850 | 1,753,188 | 30,338 | 1.7 |
Washington | 4,866,692 | 4,958,320 | 91,628 | 1.8 |
Wyoming | 453,588 | 463,629 | 10,041 | 2.2 |
U.S. Totals | 248,709,873 | 252,730,369 | 4,020,496 | 1.6% |
Source: U.S. Census Bureau, based on 1990 Post Enumeraton Survey. | ||||
Estimating the 1990 Census UndercountPrior to 1990, the Census Bureau primarily relied on "demographic analysis" to estimate the level of the undercount. This analysis relies on such factors as administrative records of births, deaths, immigration, and emigration to provide estimates of the true population total. In 1990, the Census Bureau used an additional technique to generate estimates of the undercount--the Post Enumeration Survey (PES). Essentially, once the 1990 census was conducted, the bureau drew a sample of census blocks from around the country. Then, census staff knocked on the door of each housing unit in the sample census blocks--regardless of whether it was on the master address list. For each of the blocks, the Census Bureau compared the information from both sources--that is, the official census and the PES. Based on the results of the PES survey, an estimate was made of people missed in the original census count. Then, using a statistical model, these PES estimates of undercount were used to develop undercount figures for all geographic areas. Census research indicates that the majority of the undercount is associated with incorrect reporting during the initial census. The PES relies on an intensive effort (much more so than the initial census) to count all the residents in the sample blocks. This "saturation coverage" is the key to the survey's ability to identify the undercount. |
As noted previously, two of the more direct effects of census undercounts are that (1) they can affect the regional distribution of representatives from different states in Congress and (2) they can affect the interstate distribution of federal funds.
Article 1, Section 2, of the U.S. Constitution requires that the census be used to apportion seats in the U.S. House of Representatives (House). The effect of the 1990 undercount on the allocation of House seats to the 50 states is discussed below.
How Seats Are Allocated Among States. The U.S. Constitution provides that each state will have a minimum of one member in the House, and the current size of the House (435 seats) has not changed since the apportionment made following the 1910 census. Thus, the current apportionment calculation divides 385 seats (435 seats, minus the 50 seats automatically given) among the 50 states.
The method currently used for apportioning these 385 seats is called the "method of equal proportions." It was adopted in 1941 following the 1940 census, and involves establishing a listing of the states according to "priority values." These priority values are calculated using a formula which incorporates each state's population growth relative to the size of each state. Seats 51 through 435 are assigned to the 50 states on the basis of this listing of priority values.
For example, following the 1990 census, each of the 50 states was given one seat out of the current total of 435. The next, or 51st seat, went to the state with the highest priority value (California) and thus became that state's second seat. The state that had the next-highest priority value (New York) captured the 52nd seat, while the state with the third-highest priority value (California again) captured the 53rd seat. This process continued until all 435 seats had been assigned to a state.
California Would Have Gained an Additional Seat Absent the 1990 Undercount. Using the official 1990 census figures, California was allocated 52 seats in the House, with its 52nd seat being the 427th allocated under the priority ranking. Washington received the final 435th seat according to the priority ranking, and the next five states in priority order were Massachusetts, New Jersey, New York, Kentucky, and California (in that order). Thus, California qualified for the 440th seat, but because the total number of seats is fixed at 435, could not receive that 53rd seat.
Had the 1990 census undercount not occurred, the priority-order ranking would have been jumbled around. This is because the extent of the undercount differed by state. Adjusting for the undercount would have improved California's priority ordering for its 53rd seat from number 440 to number 434, or inside the 435 House limit. Thus, California would have picked up a seat (its 53rd), due to its large relative undercount. As it turns out, this additional seat would have been at the expense of Wisconsin, whose 9th seat would have slipped from priority-order ranking 429 using the official census data to 436 using the adjusted data. It should be noted that California is the only state in the nation to lose a seat because of the 1990 undercount. Moreover, the National Conference of State Legislators cited in a recent report an estimate by a demographic research firm that an adjusted 2000 census count would shift at least one seat to California as well.
Population helps determine the amount of federal funds states receive for a wide variety of public programs. Because of this, California's large relative census undercount caused it to receive less than it should have under a wide range of federal formula grant programs throughout the 1990s. Precise dollar figures regarding federal funding effects are difficult to pinpoint, partly because some of the formulas which are used to distribute federal funds are very complex. Figure 3 lists California's 15 largest federal grant programs, and summarizes the eight that have been shortchanged because of the undercount. Note that these figures are for a single fiscal year only, and are for only a fraction of the grant programs under which California receives federal funds. Extrapolating these figures for the entire decade suggests that the 1990 census undercount has likely cost California an estimated $2.2 billion during the 1990s.
Figure 3 | |
California's Estimated Loss in Federal Funding
Due to 1990 Census Undercount Fifteen Largest Grant Programs | |
(In Thousands) | |
Federal Program | Amounta |
Adoption Assistance | $995b |
Prevention and Treatment of Substance Abuse | 3,632c |
Child Care and Development | 1,883c |
Employment and Training Assistance | --d |
Employment Services | --d |
Foster Care | 9,353b |
Highway Planning and Construction | --d |
Low Income Home Energy | --d |
Medicaid | 197,912b |
Rehabilitation Services | 4,719 |
Social Services | 3,213 |
Special Education | --d |
Women Infants and Children Program (WIC)--Food | --d |
WIC--Nutritional Services and Administration | --d |
Vocational Education | 1,128c |
Total | $222,835 |
a Federal fiscal year 1998 unless otherwise indicated. | |
b Federal fiscal year 1997. | |
c Federal fiscal year 1999. | |
d These programs do not use population data to allocate funding. | |
Source: United States General Accounting Office. | |
Just like individual states experienced different relative 1990 census undercounts, so did California's different geographic regions. This reflects such factors as regionally different population characteristics, different living styles and arrangements, and different degrees of urbanization, suburbanization, and rural living.
Figure 4 (see page 12) shows the percentage undercounts which characterized the state's broad geographic regions in 1990. For this purpose, California's counties were grouped into five regions, each of which has somewhat different and distinct economic and geographic characteristics. These regions include:
Figure 5 (see page 13) and Figure 6 (see page 15) report the undercount figures for California's counties and larger cities, respectively. Note that all but two counties (Marin and Placer) and three cities (Santa Clarita, Thousand Oaks, and Torrance) had undercount rates higher than the nation as a whole (1.6 percent).
Figure 5 | ||||
1990 California Census Undercount | ||||
1990 Population Total | ||||
Region/County | Reported | Adjusted for Estimated Undercount | Estimated Undercount | |
Amount | Percent | |||
Southern California: | ||||
Los Angeles | 8,863,164 | 9,168,936 | 305,772 | 3.3% |
Orange | 2,410,556 | 2,461,397 | 50,841 | 2.1 |
Riverside | 1,170,413 | 1,199,176 | 28,763 | 2.4 |
San Bernardino | 1,418,380 | 1,455,650 | 37,270 | 2.6 |
San Diego | 2,498,016 | 2,560,552 | 62,536 | 2.4 |
Ventura | 669,016 | 683,743 | 14,727 | 2.2 |
Subtotals | 17,029,545 | 17,529,454 | 499,909 | 2.9% |
San Francisco Bay Area: | ||||
Alameda | 1,279,182 | 1,317,262 | 38,080 | 2.9% |
Contra Costa | 803,732 | 817,986 | 14,254 | 1.7 |
Marin | 230,096 | 232,969 | 2,873 | 1.2 |
Napa | 110,765 | 113,321 | 2,556 | 2.3 |
San Francisco | 723,959 | 745,580 | 21,621 | 2.9 |
San Mateo | 649,623 | 661,717 | 12,094 | 1.8 |
Santa Clara | 1,497,577 | 1,531,401 | 33,824 | 2.2 |
Solano | 340,421 | 348,548 | 8,127 | 2.3 |
Sonoma | 388,222 | 397,508 | 9,286 | 2.3 |
Subtotals | 6,023,577 | 6,166,292 | 142,715 | 2.3% |
Central Valley: | ||||
Butte | 182,120 | 186,843 | 4,723 | 2.5% |
Colusa | 16,275 | 16,992 | 717 | 4.2 |
El Dorado | 125,995 | 128,454 | 2,459 | 1.9 |
Fresno | 667,490 | 692,182 | 24,692 | 3.6 |
Kern | 543,477 | 558,924 | 15,447 | 2.8 |
Kings | 101,469 | 105,195 | 3,726 | 3.5 |
Madera | 88,090 | 91,267 | 3,177 | 3.5 |
Merced | 178,403 | 185,469 | 7,066 | 3.8 |
Placer | 172,796 | 175,290 | 2,494 | 1.4 |
Sacramento | 1,041,219 | 1,065,246 | 24,027 | 2.3 |
San Joaquin | 480,628 | 495,277 | 14,649 | 3.0 |
Shasta | 147,036 | 150,146 | 3,110 | 2.1 |
Stanislaus | 370,522 | 380,819 | 10,297 | 2.7 |
Sutter | 64,415 | 66,163 | 1,748 | 2.6 |
Tulare | 311,921 | 323,772 | 11,851 | 3.7 |
Yolo | 141,092 | 145,974 | 4,882 | 3.3 |
Yuba | 58,228 | 60,102 | 1,874 | 3.1 |
Subtotals | 4,691,176 | 4,828,115 | 136,939 | 2.8% |
Central Coast: | ||||
Monterey | 355,660 | 367,820 | 12,160 | 3.3% |
San Benito | 36,697 | 38,192 | 1,495 | 3.9 |
San Luis Obispo | 217,162 | 222,870 | 5,708 | 2.6 |
Santa Barbara | 369,608 | 381,099 | 11,491 | 3.0 |
Santa Cruz | 229,734 | 236,015 | 6,281 | 2.7 |
Subtotals | 1,208,861 | 1,245,996 | 37,135 | 3.0% |
Rest of State: | ||||
Alpine | 1,113 | 1,148 | 35 | 3.0% |
Amador | 30,039 | 30,482 | 443 | 1.5 |
Calaveras | 31,998 | 32,606 | 608 | 1.9 |
Del Norte | 23,460 | 24,035 | 575 | 2.4 |
Glenn | 24,798 | 25,686 | 888 | 3.5 |
Humboldt | 119,118 | 122,441 | 3,323 | 2.7 |
Imperial | 109,303 | 113,271 | 3,968 | 3.5 |
Inyo | 18,281 | 18,876 | 595 | 3.2 |
Lake | 50,631 | 51,774 | 1,143 | 2.2 |
Lassen | 27,598 | 28,162 | 564 | 2.0 |
Mariposa | 14,302 | 14,673 | 371 | 2.5 |
Mendocino | 80,345 | 82,788 | 2,443 | 3.0 |
Modoc | 9,678 | 9,921 | 243 | 2.4 |
Mono | 9,956 | 10,328 | 372 | 3.6 |
Nevada | 78,510 | 79,826 | 1,316 | 1.6 |
Plumas | 19,739 | 20,195 | 456 | 2.3 |
Sierra | 3,318 | 3,401 | 83 | 2.4 |
Siskiyou | 43,531 | 44,578 | 1,047 | 2.3 |
Tehama | 49,625 | 50,823 | 1,198 | 2.4 |
Trinity | 13,063 | 13,317 | 254 | 1.9 |
Tuolumne | 48,456 | 49,390 | 934 | 1.9 |
Subtotals | 806,862 | 827,721 | 20,859 | 2.5% |
California Totals | 29,760,021 | 30,597,578 | 837,557 | 2.7% |
Figure 6 | ||||
1990 California Census Undercount for Larger Citiesa | ||||
1990 Census Total | ||||
Region/City | Reported | Adjusted for Estimated Undercount | Estimated Undercount | |
Amount | Percent | |||
Southern California: | ||||
Anaheim | 266,406 | 273,740 | 7,334 | 2.7% |
Chula Vista | 135,163 | 138,715 | 3,552 | 2.6 |
El Monte | 106,209 | 110,792 | 4,583 | 4.1 |
Escondido | 108,635 | 111,040 | 2,405 | 2.2 |
Fullerton | 114,144 | 116,725 | 2,581 | 2.2 |
Garden Grove | 143,050 | 146,412 | 3,362 | 2.3 |
Glendale | 180,038 | 184,515 | 4,477 | 2.4 |
Huntington Beach | 181,519 | 184,639 | 3,120 | 1.7 |
Inglewood | 109,602 | 116,991 | 7,389 | 6.3 |
Irvine | 110,330 | 112,191 | 1,861 | 1.7 |
Long Beach | 429,433 | 445,925 | 16,492 | 3.7 |
Los Angeles | 3,485,398 | 3,624,206 | 138,808 | 3.8 |
Moreno Valley | 118,779 | 121,925 | 3,146 | 2.6 |
Oceanside | 128,398 | 131,711 | 3,313 | 2.5 |
Ontario | 133,179 | 137,458 | 4,279 | 3.1 |
Orange | 110,658 | 112,738 | 2,080 | 1.8 |
Oxnard | 142,216 | 147,164 | 4,948 | 3.4 |
Pasadena | 131,591 | 136,431 | 4,840 | 3.5 |
Pomona | 131,723 | 137,116 | 5,393 | 3.9 |
Rancho Cucamonga | 101,409 | 103,309 | 1,900 | 1.8 |
Riverside | 226,505 | 232,608 | 6,103 | 2.6 |
San Bernardino | 164,164 | 170,249 | 6,085 | 3.6 |
San Diego | 1,110,549 | 1,143,032 | 32,483 | 2.8 |
Santa Ana | 293,742 | 305,815 | 12,073 | 3.9 |
Santa Clarita | 110,642 | 111,997 | 1,355 | 1.2 |
Simi Valley | 100,217 | 102,006 | 1,789 | 1.8 |
Thousand Oaks | 104,352 | 105,407 | 1,055 | 1.0 |
Torrance | 133,107 | 135,125 | 2,018 | 1.5 |
San Francisco Bay Area: | ||||
Berkeley | 102,724 | 106,630 | 3,906 | 3.7% |
Concord | 111,348 | 113,137 | 1,789 | 1.6 |
Fremont | 173,339 | 176,094 | 2,755 | 1.6 |
Hayward | 111,498 | 114,720 | 3,222 | 2.8 |
Oakland | 372,242 | 391,553 | 19,311 | 4.9 |
Salinas | 108,777 | 112,703 | 3,926 | 3.5 |
San Francisco | 723,959 | 745,573 | 21,614 | 2.9 |
San Jose | 782,248 | 801,296 | 19,048 | 2.4 |
Santa Rosa | 113,313 | 115,898 | 2,585 | 2.2 |
Sunnyvale | 117,229 | 119,999 | 2,770 | 2.3 |
Vallejo | 109,199 | 112,178 | 2,979 | 2.7 |
Central Valley: | ||||
Bakersfield | 174,820 | 179,398 | 4,578 | 2.6% |
Fresno | 354,202 | 366,527 | 12,325 | 3.4 |
Modesto | 164,730 | 168,849 | 4,119 | 2.4 |
Sacramento | 369,365 | 380,736 | 11,371 | 3.0 |
Stockton | 210,943 | 218,358 | 7,415 | 3.4 |
a Defined as cities with populations in excess of 100,000 as of 1990. | ||||
The 1990 census undercount experience in the state's five broad geographic regions was as follows:
Southern California. In 1990, this region contained 57 percent of the state's population, and slightly more than 60 percent of the census undercount occurred in it. The experience for this region, however, is completely explained by Los Angeles County, which itself had an extremely high undercount. In fact, Los Angeles was the only county in this region which experienced a higher undercount than the state in its entirety. It accounted for 30 percent of the state's population but was home to almost 37 percent (about 306,000) of the statewide's undercounted individuals.
San Francisco Bay Area. In contrast to Southern California, the nine-county San Francisco Bay Area accounted for less of the undercount than its population share17 percent of the undercount, three percentage points below its share of 1990 official state population. Three counties--Marin, San Mateo, and Contra Costa--all posted undercount figures considerably lower than the state (rates of 1.2 percent, 1.7 percent, and 1.8 percent, respectively). These three rates rank among the six lowest of all the counties, and offset higher undercount rates in such Bay Area counties as San Francisco and Alameda.
Central Valley. The Central Valley posted undercount figures which generally mirrored that of the state as a whole. That is, the region comprised 16 percent of the statewide population and accounted for 16 percent of the statewide undercount. However, like Southern California, the Central Valley also exhibited considerable intercounty variation. The Central Valley is essentially comprised of two subregions--the San Joaquin Valley (extending from Kern County to San Joaquin County) and the Sacramento Valley (including Sacramento County up to Shasta County). The census data reveal that the entire San Joaquin Valley (all eight counties) suffered a collective undercount of 3.2 percent, significantly higher than the statewide average of 2.7 percent, and easily the highest of any subregion in the state. Conversely, the Sacramento Valley counties posted the lowest undercount rate of any subregion2.3 percent. This was despite the fact that it contains Colusa County, which had the highest undercount rate of all the counties in the state.
Central Coast and Rest-of-the-State. The final two broad geographic regions of California--the Central Coast and the Rest-of-the-State region--together posted undercount rates proportional to their shares of population. That is, the two regions collectively accounted for about 7 percent of the state's official population count in 1990, as well as about 7 percent of the estimated statewide census undercount. However, the Central Coast taken alone experienced the largest undercount rate of all five geographic regions (3 percent), driven by large undercount rates in San Benito and Monterey Counties. These above-average rates were offset by generally lower undercount rates for the 21 remaining, mostly rural counties.
In response to the undercounting problem associated with past censuses--especially in 1990the Census Bureau, as noted above, advocates the use of statistical sampling methods to increase accuracy. "Sampling" occurs whenever the information on a portion of the population is used to infer information on the population at large. This approach is intended to deal with both the component of the undercount problem associated with inaccuracies in the master list of households, as well as the component associated with imperfect information about the population residing in known households.
Actually, statistical sampling has been used since 1940 to obtain detailed demographic information about the population. In 1990, for example, about one-in-six residents were sent a special long-form questionnaire to fill out, the results of which were used to draw inferences about various attributes of the general population. (This same process with respect to the long-form questionnaire will be repeated in 2000.) Through 1990, however, the population totals themselves have reflected only the actual population head count. The Census Bureau is proposing to change this traditional practice in 2000, and augment the head count itself by incorporating the results of sampling.
The Original Proposal. The Census Bureau's original objective with respect to the upcoming 2000 census was to physically count the population in 90 percent of the households it was aware of in every census tract (each of which contains roughly 4,000 people). It would then account for the remainder of the population through scientific sampling techniques.
In addition to the above process, the Census Bureau wanted to conduct a second sample of 750,000 households nationwide drawn from all ethnic groups and geographic locations, as a sort of "quality assurance" check. This sample would allow the bureau's statisticians to gauge whether some particular demographic groups were miscounted in the first-round census calculations, in which case the preliminary results would then be adjusted accordingly.
According to the Census Bureau, if such a sampling method had been used, there was a 90 percent chance that its estimate of the nation's population would be within 0.1 percent of the true number. On the other hand, if no sampling methods were used, it estimated that the likely undercount would be about 1.9 percent, even higher than the 1.6 percent undercount in 1990.
The Current Plan. As discussed below, recent court decisions provide that congressional seats may not be apportioned using sample-adjusted data. This means that the Census Bureau cannot rely on a 90 percent coverage plan. Rather, it must try to make its coverage as close to 100 percent as possible. As a result, the bureau recently modified its original plan for sampling. It now plans to attempt to physically count everyone and then adjust this count using an Accuracy and Coverage Evaluation (ACE) survey involving approximately 300,000 households--twice as large as the one used in 1990 but less than half of the one originally proposed. The bureau believes that this modified plan, like the original plan, will significantly improve census accuracy--both in terms of identifying missed households and obtaining more accurate data on counted households. However, the unadjusted data will be used to apportion congressional seats, and the survey-adjusted data will be available for other purposes. The bureau estimates that the cost of conducting the 2000 census will be $4.5 billion, $1.7 billion higher than its original estimate, due to the need to try to count everyone.
The initial phases of the Census 2000 project would be similar to those of previous census counts which did not use sampling. The first step calls for developing a list of every housing unit in the nation (the so-called master list). To contact all addresses, the Census Bureau plans to merge its 1990 Census Address List with a current address list from the U.S. Postal Service. Local governments would then be given the opportunity to review and update the list. The result will be a national listing consisting of about 120 million addresses. In April 2000, a series of mailings will be sent to each address on the list. Specifically, each address will be mailed a prenotice letter, followed by the official questionnaire, followed by a "reminder" or "thank you" postcard, as appropriate. To achieve as large a response rate as possible, census questionnaire forms also will be available in different languages at public places, such as libraries and post offices. Thus, the starting point for both the 1990 and 2000 censuses is in principle the samea listing of the nation's households and other places of residences (such as nursing homes and dormitories).
As previously, the Census Bureau will focus on those households not responding to the census forms and/or other correspondence sent to them. Interviewers will go door-to-door to collect information from all the nonresponders they can locate, along with collecting information when possible about them from third-party sources such as neighbors and postal carriers.
There will still be persons who are missed or incorrectly enumerated in this process. For example, people in the responding housing units may make errors in filling out the census questionnaire. Likewise, some households may not even be included on the master-address list for the questionnaire. To address these problems, the bureau will undertake the post-census ACE survey. A similar survey was conducted in 1990, but the results were not incorporated into the final population figures. The ACE survey will be twice as big as the previous one and, hence, be more useful for adjusting the data.
In summary, the key difference between the 1990 census and the planned 2000 version is that in 2000 a population series will be available which incorporates the undercount identified by the post-census survey, if policymakers wish to use it.
What About the Homeless? In 2000, the Census Bureau will enumerate people at service locations (such as shelters, soup kitchens, and regularly scheduled food vans) that primarily serve people without housing. Efforts are also planned to enumerate persons without housing at targeted nonsheltered outdoor locations. In this way, the Census Bureau will seek to include people without housing in the census who might be missed in the traditional enumeration of housing units and group quarters.
In preparation for the upcoming census, the bureau conducted "dress rehearsals" at three sites around the country in the spring of 1998. The three dress rehearsal sites were Sacramento; the 11 rural counties surrounding Columbia, South Carolina; and the Menominee Reservation in Wisconsin. The three trial run sites were chosen because they have attributes reflective of the various challenges that Census 2000 will confront. Specifically, Sacramento was chosen to represent urban conditions; the multicounty area surrounding Columbia was selected because it provided an opportunity to test procedures in suburban and rural areas; and the final test site was chosen to demonstrate the special procedures planned for use on Native American Indian reservations.
The results from these three dress rehearsals will allow the bureau to evaluate the new procedures being considered for Census 2000. These include user-friendly forms and digital capture of forms. In addition, the Census Bureau tested the statistical sampling techniques it intends to use in the 2000 census. The site selection criteria for the dress rehearsal allowed populations to be assessed with certain attributes associated with the 1990 census undercount.
The Case of Sacramento. Sacramento was specifically selected because its population variations are felt to be reflective of those characterizing California generally, and it was felt that Sacramento provides a good "testing ground" to evaluate efforts to capture the classifications of persons generally missed in 1990. Figure 7 (see page 20) shows the results from the Sacramento trial run. These results suggest a continuation of two trends identified in the 1990 census.
Figure 7 | ||||
Summary Results of 1998 Census Dress Rehearsal
(Sacramento) | ||||
Ethnic Group | Population Totals | |||
Unadjusted for Undercount | Adjusted for Undercount | Undercount | ||
Amount | Percent | |||
White | 185,478 | 195,046 | 9,568 | 4.9% |
Black/African American | 58,443 | 63,826 | 5,383 | 8.4 |
Asian/Pacific Islander | 59,265 | 63,125 | 3,860 | 6.1 |
American Indian, Alaskan Native | 11,270 | 12,327 | 1,057 | 8.6 |
Other | 63,285 | 68,988 | 5,703 | 8.3 |
Totals | 377,741 | 403,312 | 25,571 | 6.3% |
Thus, many experts believe that the results of the Sacramento rehearsal suggest that, absent statistical sampling as a corrective remedy, the census undercount resulting from the 2000 census may be even larger and the population totals more problematic than for the 1990 experience.
In 1998, in response to suits challenging the use of sampling for census purposes, it was ruled at the federal district court level that sampling methods may not be used to produce the population counts used to reapportion seats in Congress.
These rulings were upheld by the Supreme Court in January 1999, when it found that the census law directly prohibits use of statistical sampling to adjust population figures used to allocate House of Representative members among the states. The court drew a distinction, however, between using sampling to adjust the head-count figures used to apportion seats in the House among the 50 states, and statistical adjustment of those figures for other purposes (such as the distribution of federal funds to the states). While federal law bars sampling for apportionment, the court said it permits and perhaps even may require statistical adjustments for other purposes. Thus, the court's interpretation of the Census Act suggests that population counts adjusted by sampling could or even should be used for these other purposes. Both Clinton Administration officials and Census Bureau officials have signaled their intention to do so.
Given the court decision, the Census Bureau plans to produce two sets of population figures--a traditional head-count version for the purpose of congressional apportionment, and then a second set of numbers which corrects for the undercount. The latter, more complete figures would be made available in a form that allows them to be used, if so desired by policymakers, for intrastate redistricting, determining the allocation of federal funds, and various other purposes. However, this would be contingent on Congress agreeing to appropriate the money for the Census Bureau to produce sample-adjusted figures following the regular head-count enumeration.
At this point, the 2000 census and the sampling controversy surrounding it remains an unfinished story. Several key issues remain to be resolved.
Federal Issues. At the federal level, there are two key decision points. The first involves whether Congress will fund the ACE survey. If it does not, that will be the end of the story, as only one set of population figures will be produced--reflecting an actual census headcount that is unadjusted for the undercount through sampling. If the ACE survey is funded, however, a second key decision will then have to be made--namely, what set of population data should be used to distribute federal funds amongst the states, the unadjusted or sample-adjusted census results?
California Issues. Should sample-adjusted census data be made available through the ACE survey, the state will have to face several important issues. The first involves redistricting--specifically, which set of population data (adjusted versus unadjusted) should be used to re-draw the boundaries of the state's Congressional districts, as well as the Legislature's Senate and Assembly districts?
The second key California issue facing the Legislature will involve the geographic dispersion of certain state funds to localities. Under current law, for example, population influences how vehicle license fee revenues, certain gasoline tax proceeds, and funds under the Citizens' Option for Public Safety (COPS) program are geographically allocated. Thus, the amounts of dollars going to different localities under these programs will depend, in part, on whether adjusted versus unadjusted population figures are used.
Thus, depending on actions at the federal level, the state may soon have to deal with the impact of sampling on the census data.
Acknowledgments This report was prepared by Robert Ingenito, under the supervision of David Vasché. The Legislative Analyst's Office (LAO) is a nonpartisan office which provides fiscal and policy information and advice to the Legislature. | LAO Publications
To request publications call (916) 445-2375. This report and others, as well as an E-mail subscription service, are available on the LAO's internet site at www.lao.ca.gov. The LAO is located at 925 L Street, Suite 1000, Sacramento, CA 95814. |