1 

Household Estimates Conundrum: Effort to Develop More 

Consistent Household Estimates Across Surveys 

Arthur R Cresce, Yang Cheng, and Christopher Grieves* 

U.S. Census Bureau 

Washington, D.C. 20233 

Proceedings of the 2013 Federal Committee on Statistical Methodology (FCSM) Research Conference 

Introduction 

One of the most basic demographic concepts is that of households. If one were to look at the technical 

documentation for the decennial census and our current surveys (see attachment A), one would find that we 

consistently define households as including all the people who occupy a housing unit. Thus, by definition, the 

number of households (householders) should be equal to the number of occupied housing units. However, despite 

the consistency of definition of households (occupied housing units), the Census Bureau has had to deal with the 

issue of different estimates of households in the United States among its various data collection efforts. Table 1 

shows these differences among 4 surveys: the Current Population Survey/Annual Social and Economic Survey 

(CPS/ASEC), the Housing Vacancy Survey (HVS - part of the CPS), the American Community Survey (ACS), and 

the American Housing Survey (AHS). 

*The views expressed in this paper are solely attributable to the authors and do not necessarily reflect the 

position of the United States Census Bureau. 

(Numbers in thousands)

2003 2004 2005 2006 2007 2008 2009 2010[1] 2011 2012

CPS Basic 112,312 113,291 114,475 115,942 117,474 118,033 118,518 118,636 119,571 121,804

CPS/ASEC [2] 111,278 112,000 113,343 114,384 116,011 116,783 117,181 117,538 118,682 121,084

CPS/HVS 106,111 107,606 109,484 110,693 111,258 111,672 112,295 112,899 113,533 114,513

ACS 108,420 109,902 111,091 111,617 112,378 113,101 113,616 114,567 114,992 115,970

AHS 105,842 NA 108,871 NA 110,692 NA 111,806 NA 114,907 NA

[1] Further complicating the situation is the fact that the2010 Census provided yet another total for 

 households that was different from the other estimates show below:

2010 Census 116,716

CPS Basic 118,636

CPS/ASEC 117,538

CPS/HVS 112,899

ACS 114,567

We have attempted to explain the differences between the 2010 Census and the 2010 1-year ACS, Griffin (2011)

and Cresce (2012) provided a preliminary analysis of possible souces of differences, including comparison of 

field procedures; evaluatons of 2010 Census methods; assessment of ACS methods, frame, sampling and

estimation; analysis of results from a match of 2010 Census and 2010 1-year ACS records; and analysis of 

aggregate data from both sources. It is clear at this stage that there are factors associated with each data source

that can help explain at least a portion of the differences noted.

[2] Although the Housing Vacancy Survey is part of the Current Population Survey and is conducted by the 

same field representatives, the results for vacant and occupied housing units from the Housing Vacancy Survey

are based on independent housing unit controls while the results for the occupied housing units (households) 

in the CPS/ASEC are based on independent population controls. The CPS/HVS estimates are based on vintage

2011 housing unit controls provided by the Population Division.

Table 1 Estimate of Households and Occupied Housing Units in the Current Population Survey, the 

Housing Vacancy Survey, and the American Housing Survey, and the American Community Survey
2 

It is clear from an initial reading of Table 1 that, with a few exceptions, none of these sources of data on households 

agree. Across all years, there is a consistent pattern with the CPS/ASEC providing the highest estimate, the ACS 

providing the second highest estimate, and the CPS/HVS providing the lowest estimate. In odd-numbered years 

when the AHS is conducted, the AHS estimate is not different from the CPS/HVS in 2003 and 2005 and the estimate 

for the 2011 is not statistically different from the ACS es timate for that year. It is not surprising, then, that data 

users are confused and unsure what estimate to use for their programs/analyses. 

If the concept underlying these estimates is the same across the three surveys, why should there be such large 

differences? The answer to this question is largely due to: 1) differences in estimation methods, 2) differences in 

sample design, and 3) differences in operational procedures. The focus for this paper will be on: 1) understanding 

the reasons for the differences among the current surveys, including the American Community Survey and 2) 

developing a methodology for calculating consistent household estimates among the various CPS-based surveys 

(“basic” CPS, CPS/ASEC and the CPS/HVS). The decennial census, as noted in Griffin (2011) and Cresce (2012), 

poses unique challenges in trying to understand these differences but will not be the focus of this paper. We expect 

that the same (or similar) approach for obtaining consistent household estimates for the CPS would be employed at 

some point for the American Housing Survey and the Survey of Income and Program Participation (SIPP), with 

some possible revisiting of the ACS methodology to make sure the approaches are as similar as possible. 

Furthermore, although we state that the differences in household estimates are a function of both estimation issues, 

design issues, and operational issues, we believe that most of the differences are due to estimation and will only 

mention possible design and operational issues while focusing primarily on estimation issues. 

Differences in Estimation 

In the early 2000’s, an interdivisional team of statisticians at the Census Bureau examined the use of housing unit 

controls versus population controls as it applied to Housing Vacancy Survey (see Love, 2003). They concluded that 

the use of the weight adjustment for within household undercoverage when using population controls by age, sex 

and race tended to be higher than the adjustment to the weights for housing unit coverage when using housing unit 

controls, which focus on coverage of housing units (including whole households). Thus, when population controlbased weights are applied to characteristics such as household relationship, the estimate of householders (family 

plus nonfamily) will almost always be higher than the corresponding housing unit control-based weights that are 

applied to obtain the estimate of occupied housing units. 

This apparent discrepancy had been an issue when results for estimates of occupied housing units were compared 

between: 1) the Housing Vacancy Survey (before 2002), which is part of the Current Population Survey and had 

been based on population control-based weights and 2) the American Housing Survey1, which was based only on 

housing unit control-based weights, and the New York City Housing and Vacancy Survey2, which was based on a 

combination of housing unit control- and population control-based weights. Ultimately, discussions about this 

difference led to the Housing Vacancy Survey applying housing unit control-based weighting that not only resulted 

in consistent estimates between the HVS and the AHS, but also resulted in a precipitous drop in the estimate total 

housing units and occupied units in 2003 from the old method to the new method (See Table 2 below).3 

 

1

 Since the American Housing Survey primarily focuses on housing characteristics, no population weights are used 

and any population characteristics shown are those of the householder or the household. In addition, we should note 

that AHS estimates are controlled to selected CPS/HVS estimates for householders and for vacancy status. 

2

 In fact, the New York City Housing Vacancy also had this problem (of inconsistent occupied units vs. households) 

until the sponsors insisted that the estimates be brought into agreement and the Statistical Methods Division devised 

a method to achieve this goal. 

3

 The CPS/HVS estimation methodology essentially takes the base population weight that has been adjusted for 

differential undercoverage using population controls and controls those weights to add up to the independent 

housing controls and apportions the remaining weight to other household members. See “Memorandum for Chester 

E. Bowie from Alan R. Tupek, ‘Weighting Specifications for the Housing Vacancy Survey (HVS2000-1), June 1, 

2004. This approach appears to be similar to the approach used for ACS estimation after 2000, but this observation 

needs to be verified. 
3 

*The estimates for 2003 in this table are based on 2001-vintage housing unit controls. Thus, the estimate of 

households (occupied housing units) in this table will differ from that in Table 1. 

The American Community Survey (ACS) also dealt with this issue. Since the ACS produced both population and 

housing estimates, it had to address some troublesome internal inconsistencies between estimates of occupied 

housing units and households. This issue was partially addressed by using housing unit controlled weights for 

housing unit tables and tables where households were the universe. However, from the inception of the ACS 

through 2005 there still remained the problem that estimates of households obtained by adding family and nonfamily 

householders from the relationship question (based on population controlled weights) were still much higher (as 

expected) than the estimates for occupied housing units and households. For example, in the 2005 ACS, the 

estimate for occupied housing units was 111.1 million while the corresponding estimate for householders was 114.8 

million. This problem was addressed in 2006 with the application of a new estimation methodology (for a full 

explanation, see: 

http://www.census.gov/acs/www/Downloads/survey_methodology/acs_design_methodology_ch11.pdf) that 

essentially guaranteed consistency between estimates of occupied housing units and householders in housing unit 

tables and estimates of householders in population tables by creating a householder weight that could be used both 

for housing and population tabulations. One of the distinctive features of this new methodology was the fact that 

estimates for both the vacant and occupied housing units were to be obtained directly from the survey, meaning: 1) 

that their sum would not necessarily add to the housing control total and 2) the housing unit total would now have 

sampling error attached to it. 

However, despite the progress made in harmonizing occupied housing unit/householder estimates for internal 

consistency within the ACS and the New York City Housing and Vacancy Survey, we must address the following 

questions: 

1 Should we apply a similar type of methodology to the base CPS, the CPS/ASEC, and the CPS/HVS to

ensure reasonably consistent household estimates and what are the consequences of implementing such a 

methodology for some of the key statistics produced by these surveys ? 

2 Will the resulting methodology used in 1 above be comparable with those employed in the ACS and the 

New York City and Housing Vacancy Survey? 

3 If they are different, can that partially account for the differences among them and can they all be 

reconciled into one methodology that can be applied for all these surveys ? 

This paper will not address the second and third questions, which, however, ultimately must be answered after we 

address the first question regarding the potential application of the same housing-unit based estimate of households 

(occupied housing units) across the base CPS, the CPS/ASEC, and the CPS/HVS. 

Differences in Sampling Frame 

Related to the issue of estimation is the fact that the ACS, CPS and the AHS are based on somewhat different 

sampling frames. The ACS is solely based on the master address file (MAF), which was significantly updated using 

results of the 2010 census. The current CPS sample is based on a sampling frame originally designed using 

addresses from the 2000 Census and updated during the decade for new construction. The new CPS sample design, 

which will be implemented starting in April 2014, will be based on the MAF. The AHS is based on a sample that 

was originally designed from an address file resulting from the 1980 census with updates for new construction ever 

since. Starting in 2015, the AHS will also be based on an entirely new sample drawn from the MAF. It is not clear 

what impact differing sample frames for each of these surveys has had on differences among these surveys for 

Table 2. Comparison of HVS Estimates Based on Population-Based vs Housing-Based Weights

 2003 - Housing Based* 2002 - Housing Based 2002 – Pop Based

Total Housing 120,834 119,297 123,318

 Occupied 105,560 104,965 108,539

 Vacant 15,274 14,332 14,779
4 

characteristics or concepts that presumably the same for all three surveys4. However, to the extent that differing 

sample frames might explain differences observed in estimates for households (occupied housing units), this 

potential source of differences could be substantially mitigated. 

Differences in Operational Procedures 

While we believe that the impact of estimation differences probably explains the largest portion of the differences 

among the surveys in estimates of households (occupied housing units), operational differences also help explain 

differences in household estimates. Although we have noted above that the ACS has been able to achieve internal 

consistency among the estimates of occupied housing units, households and the sum of family and non-family 

householders, this survey regularly produces estimates of vacant units that are lower than those produced by the 

HVS and the AHS. Conversely, the estimate of occupied housing units (households) is almost always higher in the 

ACS than in the HVS or the AHS. This phenomenon is well known and was documented in a repo rt by Schwartz 

(2009) comparing results of the American Housing Survey with those from the ACS.5 In this report, the gross 

vacancy rate for the ACS was 12.1 percent – 1.6 percentage points lower than the AHS gross vacancy rate of 13.7 

percent. The tendency for the ACS to produce lower estimates of vacant units (and higher estimates of occupied 

units) than the HVS or the AHS can be attributed, in part, to the fact that in the ACS, vacant units are mostly 

identified in the personal visit stage of enumeration, which occurs up to three months after the initial mail out. This 

procedure, coupled with a “current residence” rule of 2 months, could result in classifying housing units that were 

vacant at the initial mail out being occupied by the time of the personal visit interview. This phenomenon is much 

more likely to occur in rental units than in owned units.6 Thus, the estimate of households (occupied housing units) 

from the ACS will almost always be higher for the ACS than for the AHS or the HVS. In addition, it is also 

possible that the ACS sampling and estimation procedures for vacant units may also contribute to these differences 

since vacant units are mostly included in the nonresponse universe, which is subsampled at a given rate and results 

are weighted at a much higher rate than results from the mail form. 

There appears to be no really significant differences in operational procedures between the CPS/HVS and the AHS. 

In fact, they have in common something that is not done in the ACS (nor in the decennial census) in that they both 

determine for vacant units whether the unit is intended for year-round use. If the housing unit is intended for yearround use, the Field Representative (FR) then asks the vacancy status questions (that is, is the housing unit for sale, 

for rent, or some other reason). If the vacant housing unit is not intended for year –round use (even if it is capable of 

being occupied at any time of the year), the unit is automatically classified as “seasonal” and no attempt is made to 

determine if it is for sale or rent. ACS FRs and decennial census enumerators, on the other hand, do not ask this 

question and determine vacancy status for all vacant housing units. We need to determine if we should make the 

ACS and the decennial census conform to the HVS and the AHS or vice versa, even though we believe the 

differences do not affect differences in occupancy status. 

One other possible source of differences that we need to explore is the possible use of different rules or procedures 

for determining occupancy status in current surveys. We know from discussions with FRs that determining 

occupancy status can be one of the most difficult tasks that FRs must accomplish, especially if they are having 

difficulty finding a respondent or a “knowledgeable source”. The FRs success in obtaining this information for a 

particular housing unit will help determine whether the unit is vacant or a refusal (Type A). The consequences of 

designating a housing unit as vacant or Type A are significant since Type A noninterviews are accounted for by a 

noninterview adjustment in the very early stages of the estimation process while an erroneous designation of a 

housing unit as being vacant results in a whole household miss with no adjustment for loss of cov erage of the 

household. We need to review practices across surveys to ensure that consistent rules are being applied across 

surveys. 

 

4

 We have some evidence from Hefter and Anderson (2012) of the possible impact of differing frames between the 

2010 American Community Survey 1-year data and the 2010 census. However, this paper did not assess how that 

impact might explain differences between the 2010 Census and the 2010 1-year ACS in gross vacancy rates. 

5

 Ironically, the gross vacancy rate from the 2005 New York City Housing Vacancy Survey (NYCHVS) was lower 

than the 2005 ACS estimate for New York City. However, the authors note that there are various reasons why the 

NYCHVS estimate would be lower than the ACS estimate (see Callis and Fronczek, 2008). 

6

 For example, in 2007 the ACS rental vacancy rate was 7.9 percent, compared with 9.8 percent for the AHS, while 

the ACS homeowner vacancy rate was 2.5 percent, compared with 2.6 percent for the AHS (Schwartz, 2008, Table 

2a). 
5 

We will continue to research these issues to see what impact they might have on differences among the surveys. 

The remainder of this paper, however, will focus on efforts to address estimation methodology for households 

(occupied housing units) in the CPS. 

Developing a Housing-Unit Based Methodology for Estimating Households in the CPS 

The intentions of our research is to try a modification to the current base CPS weighting scheme by introducing 

house unit controls. We hope that this will produce consistent estimates of the number of occupied households and 

their characteristics among CPS related surveys. At the same time, we will monitor the impact of these 

methodologies on a wide range of characteristics, most particularly labor force, income and poverty statistics. 

Beyond just the immediate effect on labor force statistics, we have to account for the fact that other su rveys are 

stakeholders in the results of base CPS. For example, three immediate stakeholders would be: 1) the CPS/HVS, 

which uses the Base CPS “Family Weight” in its estimation procedure, 2) the CPS supplements (especially the 

CPS/ASEC), and 3) the AHS which, in turn, controls to proportions of demographics created using CPS/HVS and 

base CPS data over the same time period during which AHS field enumeration is being conducted . These are all 

things we must take care to acknowledge while conducting our research and take care not to introduce any bias into 

our estimates. 

One way we may introduce the total housing unit control to estimate occupied housing units is as follows. After the 

State Coverage Adjustment in the CPS, we create an estimate of total housing units from the survey using the 

householder’s weight and the base weights for the vacant homes. Then using the ratio of the housing unit control 

over the estimate of total housing units we have created, we can ratio adjust the weights of all the household ers. We 

can obtain a new estimate as follows 

 ̂ 

 ̂

 ̂ ̂

 ̂ ∑ 

 

 

 {

 

 

Where ̂  is our new estimate of occupied households, ̂, ̂ are estimates of occupied and vacant housing units, 

 is the total housing unit control, and is the weight of the reference person in the above summation. is 

the selected sample from the non-institutionalized labor force. 

We then create an estimate of the Non-Householders, or “Residual” population by 

 ̂ ̂ ̂ 

 ̂ 

 ̂

 ̂ ∑ 

 

 

Where 

 ̂ ∑ 

 

 

and 

 {

 

 

 

 ̂  is our new estimate of the non-householder population, ̂ is the current estimate of the non-household 

population, is the total population control for the civilian non-institutional labor force, and are the state 

coverage weights summed over non-householders. 
6 

However, in order for these estimates to hold through second stage, we would need to constrain our householder and 

non-householder population estimates to ̂  and ̂ , respectively. To accomplish this, we include a new 

dimension in the second stage raking matrix with margins containing ̂  and ̂  for the householders and nonhouseholders respectively. All other margins remain as they currently are. 

The above method needs some refinement for the CPS. Some other considerations are: 

1. What level of geography should we apply the adjustment at? National, Regional, State? 

2. CPS does weighting by month-in-sample pairs (1,5), (2,6), (3,7), (4,8). Should we give each pair an equal 

proportion of our developed control? 

3. Our Occupied Housing Unit “control” in the Second Stage Raking procedure has variance. What affect 

does this variance have on point estimates and variance estimates? 

4. The above method gives estimates closer to those from other surveys, especially the CPS/HVS. However, 

the main concern is inference on the population’s labor force characteristics and coverage of the different 

demographics. As base CPS is only concerned about the civilian non-institutionalized labor force, does this 

give us correct inference of the population and make sense? Are there actual coverage issues with 

householders vs non-householders? 

We performed the above method by performing the above adjustment at the state level, including the District of 

Columbia, for July 2012. We gave each month-in-sample pair an equal proportion of the control for occupied 

housing units. The table below provides the results of applying this approach. 

Table 3. July 2012 Estimates of Occupied Housing Units New Method\Current Weighting 

Housing and Population Controls Population Controls Only 

113,778,859 121,854,557

We see that performing the above procedure gave an estimate of occupied housing units (households) that was 

considerably lower than the estimate obtained from using only population controls but was slightly lower estimate of 

the number of households than those from other surveys. However, more analysis needs to be done to address its 

impact on coverage and employment characteristics. We also need to address the level of aggregation. 

We also note that this is not the only approach one can take. Creating a separate weight for households and persons 

can make more sense in the context of doing inference on characteristics of households. We plan to do future 

research on this topic. 

Recommendations and Conclusion 

This discussion and the decisions we make are very important for the estimate of households and vacant housing 

units. We know that the housing industry is very interested in the number of households and in the growth of 

households for the purposes of residential construction. In addition, there are certainly many other uses for accurate 

data on household, both by private industry and by federal, state and local governments. The fact remains, however, 

that somehow our estimates of households (occupied housing units) and, by definition, our estimates of vacant 

housing units are not in sync. 

We recommend that the following actions be taken: 

1. Develop alternative estimation methodologies for the base CPS and determine the impact of these 

methodologies: a) on various key statistics produced by the base CPS and b) on the resulting estimate of 

households (occupied housing units). 

2. Take the preferred methodology developed in 1 above, implement that methodology for the CPS 

supplements and the CPS/HVS and assess the impact of this methodology: a) on various key statistics 

produced by these CPS surveys and b) on the resulting estimate of households (occupied housing units) 

3. Review systematically the procedures for determining the occupancy status of housing units across current 

surveys and from one Regional Office (RO) to another. “Best practices” should be learned and applied 

across all surveys in each RO. We are already working to make sure that more detailed categories for the

“Other Vacancy” status category are being applied across our housing surveys. 
7 

4. Determine whether the “year-round use” concept for housing units should be used not only for the HVS 

and the AHS but also for all our other surveys where FRs need to determine occupancy status or whether it 

should be dropped altogether. 

5. Investigate differences between household estimates obtained from our newly developed household 

estimation methodology for the CPS with those from the ACS and those from the New York City Housing 

and Vacancy Survey (NYCHVS). If necessary, adjust the methodologies where necessary to ensure that all

methodologies are employing the same (or similar) approach. 

6. Apply this same methodology to the Survey of Income and Program Participation and assess the impact of

using this methodology on key statistics produced by the survey. 

Conclusion 

We have an obligation to our data users to provide clear, unambiguous explanations and guidance about the 

estimates we provide on households (occupied housing units). In our role as the “leading source of quality data 

about the Nation’s people and economy,” we ultimately should be able to: 

1. Develop a common methodology that produces reasonably consistent estimates of households (and, 

therefore, vacant housing units) across our current surveys , 

2. Develop a common methodology that may still produce noticeable differences but still be able to explain 

differences and recommend a preferred estimate, or 

3. Be able to explain why we cannot develop a common methodology and be able to explain the differences 

and provide guidance about the agency’s preferred estimate of households (occupied housing units) for the 

United States. 

References 

Cresce, Arthur. R. 2012. Evaluation of Gross Vacancy Rates From the 2010 Census Versus Current Surveys: Early 

Findings from Comparisons with the 2010 Census and the 2010 ACS 1-Year Estimates. Paper presented at the 

January 2012 meeting of the Federal Committee on Statistical Methodology in Washington, DC. Available at: 

http://www.census.gov/housing/files/FCSM%20paper.pdf. 

Griffin, Deborah. 2011. Comparing 2010 American Community Survey 1-Year Estimates of Occupancy Status,

Vacancy Status, and Household Size with the 2010 Census - Preliminary Results. Available at: 

http://www.census.gov/acs/www/Downloads/library/2011/2011_Griffin_03.pdf. 

Schwartz, Mary B. 2009. 2007 American Community Survey: A Comparison to Selected Housing and Financial

Characteristic for the United States from the 2007 American Housing Survey. ACS evaluation report available 

at: http://www.census.gov/acs/www/Downloads/library/2009/2009_Schwartz_01.pdf. 
8 

Attachment A – Definitions of Households 

Decennial Census 

A household includes all of the people who occupy a housing unit. A housing unit is a house, 

an apartment, a mobile home, a group of rooms, or a single room occupied (or if vacant, intended for occupancy) as 

separate living quarters. Separate living quarters are those in which the occupants live separately from any other 

people in the building and that have direct access from the outside of the building or through a common hall. The 

occupants may be a single family, one person living alone, two or more families living together, or any oth er group 

of related or unrelated people who share living quarters. 

ACS

A household includes all the people who occupy a housing unit. (People not living in households are classified as 

living in group quarters.) A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single 

room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters 

are those in which the occupants live separately from any other people in the building and which have direct access 

from the outside of the building or through a common hall. The occupants may be a single family, one person living 

alone, two or more families living together, or any other group of related or unrelated people who share living 

arrangements. 

CPS/ASEC 

A household consists of all the people who occupy a housing unit. A house, an apartment or other group of rooms, 

or a single room, is regarded as a housing unit when it is occupied or intended for occupancy as separate living 

quarters; that is, when the occupants do not live and eat with any other persons in the structure and there is direct 

access from the outside or through a common hall. 

A household includes the related family members and all the unrelated people, if any, such as lodg ers, foster 

children, wards, or employees who share the housing unit. A person living alone in a housing unit, or a group of 

unrelated people sharing a housing unit such as partners or roomers, is also counted as a household. The count of 

households excludes group quarters. There are two major categories of households, "family" and "nonfamily". (See 

definitions of Family household and Nonfamily household).

HVS 

Occupied Housing Units. A housing unit is occupied if a person or group of persons is living in it at the time of the 

interview or if the occupants are only temporarily absent, as for example, on vacation. The persons living in the unit 

must consider it their usual place of residence or have no usual place of residence elsewhere. The count of occupied 

housing units is the same as the count of households.