DOE/EIA-0555(94)71

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DOE/EIA-OS55(94)/1 

Distribution Category UC-950

Energy Consumption Series

Sample Design for the 

Residential Energy Consumption Survey

August 1994

Energy Information Administration

Office of Energy Markets and End Use

U. S. Department of Energy

Washington, DC 20585

This report was prepared by the Energy Information Administration, the independent statistical and 

analytical agency within the Department of Energy. The information contained herein should not be 

construed as advocating or reflecting any policy position of the Department of Energy or any other 

organization.
Contacts

This report was prepared under the general direction of W. Calvin Kilgore, Director of the Office of Energy 

Markets and End Use (202/586-1617). The project was directed by Lynda T. Carlson, Director of the Energy 

End Use and Integrated Statistics Division (EEUISD) (202/586-1112) and Nancy L. Leach, Chief of the 

Residential and Commercial Branch (202/586-1114). Specific information regarding the contents 01 

preparation of this publication can be obtained from the principal author, Robert B Latta (202/586-1385). 

Organization and production of this report was done by Ivy Harrison and Hattie Ramseur. Questions. 

regarding the Residential Energy Consumption Survey (RECS) may be referred to Wendel Thompson, RECS 

Survey Manager (202/586-1119). The FAX number for all EEUISD personnel is 202/586-0018.

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
Contents

1. Introduction ................................................................... 1

Overview of the Residential Energy Consumption Survey .............................. 1

History ................................................................... 2

Organization of this Report.................................................... 3

2. Multistage Area-Probability Design .................................................. 5

Design Considerations ........................................................ 6

3. Objectives and Constraints to the RECS Sample Design .................................. 9

1980 Sample Design ......................................................... 9

1984 Sample Design ........................................................ 10

1993 Sample Design ........................................................ 10

4. Optimization Analysis ........................................................... 11

5. Primary Stage of the RECS Sample Design ........................................... 17

Number of Primary Sampling Units per Stratum ................................... 17

Census Divisions and Federal Regions ........................................... 18

Number of Strata to Use in the Primary Stage ..................................... 21

Criteria for Forming Primary Sampling Units ..................................... 23

Criteria for Grouping Primary Sampling Units Into Strata ............................ 24

Number of Strata by Type and Census Division .................................... 27

Primary Sampling Unit Selection Procedures ...................................... 29

Summary of Primary Stage .................................................... 31

6. Secondary Stage of the RECS Sample Design .......................................... 33

1993 New Construction Supplement ............................................ 33

Number of Secondary Sampling Units ........................................... 34

Criteria for Forming Secondary Sampling Units .................................... 36

Secondary Sampling Unit Selection Procedures .................................... 37

Additional Details of Secondary Stage for Each RECS ............................... 40

Summary of Secondary Stage .................................................. 42

7. Elementary-Unit Stage .......................................................... 43

Basic Elementary-Unit Stage .................................................. 43

Longitudinal and Incoming Panels .............................................. 46

New Construction Update Procedures ........................................... 47

New Construction Supplement for the 1993 RECS ................................. 48

Low-Income Supplement ..................................................... 49

Summary of Features for the Elementary-Unit Stage ................................ 49

8. Reasons for Revising RECS Sample Design .......................................... 51

Outdated Survey Materials and Definitions ....................................... 51

Uneven Population Growth ................................................... 52

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey jjj
IJ.J

Appendices

A U.S. Census Regions and Divisions and Federal Regions Maps ......................

B Detailed Instructions to Field Workers on Housing Unit Definition ..................... (5

C Strata Listings by Census Division .............................................. 67

Tables

1. Optimum Multistage Allocation-Solution Estimates for 1990 REGS Ratio Statistics ......... 14

2. Optimum Multistage Sample Allocation Based on Average Values of

Estimates of d x and 6 2 ....................................................... 14

3a. Number of Primary Stage Strata, Population, and Average Population per Strata

by Census Division for 1980, 1984, and 1993 RECS Sample Designs .................... 2.2

3b. Average Population and Number of Households per Stratum by Census Division for

1980, 1984, and 1993 RECS Sample Designs ..................................... '12

4. Number of Strata for PSU's by Census Division and Type of Strata for the 1980 Design ..... 28

5. Number of Strata for PSU's by Census Division and Type of Strata for the 1984 Design ..... 29

6. Number of Strata for PSU's by Census Division and Type of Strata for the 1993 Design ..... 29

7. Comparison of RECS Sample Designs at the PSU Level .............................. 31

8a. Number of Secondary Sampling Units and, Population by Census Division for 1980, 1984,

and 1993 RECS Sample Designs ............................................... 35

8b. Average Population per Secondary Sampling Units and Number of Households

by Census Division for 1980, 1984, and 1993 RECS Sample Designs .................... 35

9. Number of Secondary Sampling Units, Primary Sampling Units, and SSU's per

PSU by Census Division for 1980, 1984, and 1993 RECS Sample Designs ................ 36

10. Comparison of RECS Sample Designs at the SSU Level ............................. 42

11. Overview of Longitudinal Sample Design for the 1982, 1984, 1987, and 1990 RECS ......... 47

12. Features of RECS Surreys .................................................... 50

13. New Construction Updates ................................................... 50

14. Population and Percent Increase in Population by State, Census Division,

and National Total ........................................................ 53

15. Number of Counties Losing or Gaining Population by State, Census Division,

and National Total ......................................................... 55

16. Percent Increase in Population, Smallest Percent Increase in Population for 

a County and Largest Percent Increase in Population for a County by State, 

Census Division, and National Total ............................................ ::7

Illustrations

1. Description of Ratio Statistics Used in the 1990 RECS Components of Variance Analysis .... 13

2. List of the States Within Census Divisions and Federal Regions ....................... 19

3. State Intersections of Census Divisions and Federal Regions .......................... 20

4. Self-Representing PSU's for 1980, 1984, and 1993 RECS Sample Designs

by Census Division ......................................................... 25

Energy Information Administration/Energy Consumption Series 

JV Sample Design for the Residential Energy Consumption Survey
	Acronym Listing

1. CBECS Commercial Buildings Energy Consumption Survey

2. CPS Current Population Survey

3. EIA Energy Information Administration

4. EPACT Energy Policy Act (P.L. 102-486)

5. HHS U.S. Department of Health and Human Services

6. MCD Minor Civil Division

7. MOS Measure of Size

8. MSA Metropolitan Statistical Area

9. NIECS National Interim Energy Consumption Survey

10. NSR Non-self Representing

11. PPS Probability-Proportional-to-Size

12. PSU Primary Sampling Unit

13. RECS Residential Energy Consumption Survey

14. RSE Relative Standard Error

15. RTECS Residential Transportation Energy Consumption Survey

16. SSU Secondary Sampling Unit

17. TIGER Topologically Integrated Geographic Encoding and Referencing

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
The purpose of this report is to provide detailed information about the multistage area-probability sample 

design used for the Residential Energy Consumption Survey (RECS). It is intended as a technical report, for 

use by statisticians, to better understand the theory and procedures followed in the creation of the RECS 

sample frame. For a more cursory overview of the RECS sample design, refer to the appendix entitled "How 

the Survey was Conducted," which is included in the statistical reports produced for each RECS survey year. 

The most recent reports in the RECS series include:

« Housing Characteristics 1990, DOE/EJA-Q314(90), May 1992 (GPO Stock No. 061-003-00754-6)

 Household Energy Consumption and Expenditures 1990, DOE/EIA-0321/1(90), February 1993 (GPO 

Stock No. 061-003-00795-3).

Overview of the Survey

The Energy Information Administration (EIA) is mandated by Congress to be the agency that collects, 

analyzes, and disseminates impartial, comprehensive data about energy; its users, and the purposes for which 

it is used. To comply with that congressional mandate, EIA collects energy data from the following sectors: 

residential, commercial, manufacturing, and transportation. The RECS is used to collect data from the 

residential sector. The Energy Policy Act (EPACT) of 1992 directs EIA to conduct a residential survey at least 

once every 3 years.

The RECS provides information on the use of energy in residential housing units in the United States. This 

information includes the physical characteristics of the units, the appliances utilized, the occupants, the types 

of fuels being used, the amount of energy used, and other energy use characteristics.

Because the RECS cannot survey every household in the Nation, a statistical sample representing all U.S. 

households is chosen. The RECS sample design was initially developed during 1979 and 1980, and was used 

in the 1980,1981, and 1982 RECS. The sample design was updated in 1984 and 1993 using the results of the 

1980 and 1990 Censuses, respectively. This report, therefore, distinguishes between the three basic sample 

designs (1980, 1984, and 1993), and the nine RECS fieldings (1978, 1979, 1980,1981, 1982,1984, 1987, 1990, 

and 1993).

The RECS sample design has always been a national multistage area-probability cluster-sample design. The 

basic sampling principles followed are in accord with recommendations in standard sampling texts, which 

evolved from sampling theory. 1 Many of the national surveys of households or housing units that are 

conducted by the Federal government use the same type of design as used for RECS. In particular, the design 

for RECS and the design for the Current Population Survey (CPS) are based on the same sampling 

principles.2

1Cochran, W.G.: Sampling Techniques, 3rd Ed. New York, NY, John Wiiey & Sons, 1977; Hansen, M.H., Hurwitz, W.N. and Madow, 

W.G.: Sample Survey Methods and Theory, Vols. I and I!, New York, NY, John Wiiey & Sons, 1953; Kish. L.: Survey Sampling, New York, 

NY, John Wiiey & Sons, 1965.

2 The Technical Paper 40, "The Current Population Survey Design and Methodology," Department of Commerce, Bureau of the 

Census, January 1978.

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
With this type of multistage area-probability cluster-sample design every occupied housing unit in the country 

has a known chance of being selected for RECS, yet the design does not require the use of a comprehensive 

up-to-date list of all housing units in the country. Such a list would be very costly to develop and maintain. 

(According to the 1990 Census, there were 91,947,410 occupied housing units in the country.) The Bureau 

of the Census and the U.S. Postal Service are currently developing such a list as part of the planning for the 

2000 Decennial Census. The Bureau of the Census plans to maintain and update the list. Consequently, the 

list will be available for use in the development of the sample design for post-2000 household surveys 

conducted by the Bureau of the Census. ETA is hopeful that the next major revision of the RECS sample 

design (following the 2000 'Census) can utilize this valuable resource.

With a multistage area-probability cluster-sample design, the interviews are geographically clustered. The 

clustering reduces both design artel interviewing costs, though designs with less clustering would result in more 

precise estimates. For each stage of the design, the procedures for (1) defining the sampling units, (2) 

stratifying the sampling units, and (3) selecting the sampling units, are chosen in an attempt to balance 

between reducing survey costs and meeting the precision requirements for national, regional, and Census;, 

division data.

The dual objectives of reducing survey costs and minimizing the variance of survey estimates (maximizing the 

accuracy of the estimates), pull in opposite directions. The more the interviews are clustered, the lower the 

survey costs. On the other hand, for a fixed sample size, the more the interviews are clustered, the larger the 

variance of the survey estimates. Procedures for optimizing a survey design to balance the two objectives wen; 

used in the development of the RECS sample design3.

History

The RECS has had four different sample designs since the survey began in 1978. This report will focus, on 

the four designs, and the individual surveys will be grouped by their sample design year, as presented in the 

following sections.

National Interim Energy Consumption Survey and the Household Screener Surveys

Interim versions of RECS were conducted in 1978 and 1979. The 1978 survey was called the National Interim 

Energy Consumption Survey (NIECS), and the 1979 survey was called Household Screener Survey (Screener), 

The sample design for the NIECS and the Screener was the same, a multistage area-probability cluster-sample, 

which was the property of the survey contractor. The NIECS used a multi-purpose sample design, one not 

specifically developed to collect energy-related data, and which had been used in non-energy-related surveys. 

It covered the 48 contiguous States and the District of Columbia, but did not cover Hawaii and Alaska. The 

NIECS supported estimates at the Census region level, but not at the Census division level.

The 1980 Sample Design (1980, 1981, and 1982 RECS)

The sample design for the RECS was expressly developed to collect energy-related data in the residential 

sector. The RECS design is the property of EIA and is used only for RECS or other EIA energy-related 

surveys. This design covered all 50 States and the District of Columbia, and supported estimates at the Census 

division level. Other EIA surveys based on the RECS design include Residential Transportation Energy 

Consumption Survey (RTECS) and Commercial Buildings Energy Consumption Survey (CBECS). A brief 

description of these designs will follow later in this section on the history of RECS.

Hansen, Hurwitz, and Madow, Sample Survey Methods and Theory Volume I Methods and Applications, John Wiiey & Sons, 1953.

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
The 1984 Sample Design and 1990

In addition to the 1980 Census results, the 1984 design incorporated changes in the definitions of Metropolitan 

Statistical Areas (MSA's), and changes in the priorities of the survey. The sample design for the 1984 REGS 

also contained a longitudinal panel and an incoming panel. The longitudinal panel was taken from the 1980 

sample design, and the incoming panel of sample households was taken from the 1984 design. (See Chapter 

7 for more details on longitudinal and incoming panels.) The 1987 RECS was the first to employ the 1984 

sample design for all observations. This design was also used in the 1990 RECS.

The 1993 Sample Design and

The 1993 revision of the RECS sample design incorporated changes in the definitions of MSA's, and 

improvements in the stratification of the sampling units in all stages. In developing this sample design, 

additional energy-related characteristics of the population (such as estimated energy expenditures) were used 

in the stratification and selection procedures. The primary stage for the 1993 RECS used the new design. 

However, while the initial plan was to completely redevelop all three stages of the sample design for the 1993 

RECS, in order to lower costs for some primary-stage units, their respective secondary stages were carried over 

from the 1984 design. (See Chapter 6 for more details.)

Current plans call for the 1996 RECS to use the full 1993 sample design. Ail secondary-stage units to be used 

for the 1996 RECS will have been selected during the 1993 design effort. No secondary-stage units will be 

carried over from the 1984 design to the 1996 RECS. The 1993 design will also be the basis for the 1999 

RECS.

Residential Transportation Energy Consumption Survey (RTECS)

The sample design for the RTECS involves selecting a subsample of the respondents from the RECS of the 

previous year. Therefore, any change in the sample design for RECS automatically applies to the RTECS.

Commercial Buildings Energy Consumption Survey (CBECS)

The primary stage for the 1984 RECS sample design was also used as the primary stage in the 1986 CBECS 

sample design. However, the secondary stage and the elementary-unit stage in the 1986 CBECS sample design 

were totally different than those used in the 1984 RECS. The CBECS sample design will be updated prior 

to its use in 1995. During this redesign effort, the decision on the feasibility of using the same first-stage 

design for both RECS and CBECS will be reviewed.

Organization of this Report

The RECS design is not static, it changes as priorities change. The following chapters present summaries of 

the details and changes in the sample design throughout the development of the RECS.

Chapter 1 gives a brief overview of the RECS. Chapter 2 gives a summary of the multistage area-probability 

design that is used for the RECS. Chapter 3 discusses the objectives of the RECS sample design, and the 

constraints under which it was developed. Chapter 4 discusses the optimization analyses that were performed 

prior to the 1980, 1984, and 1993 RECS. Chapters 5 and 6 present details on the primary and secondary

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
stages of the sample, respectively. Chapter 7 presents details on the elementaiy-unit stage, and discusses 

additional features of the RECS design, including the longitudinal component, the low-income supplement:, 

the new construction supplement, and the new construction update procedures. Chapter 8 presents; a 

discussion of the reasons for periodically revising the RECS sample design. Appendix A shows the nine 

Census divisions and the ten Federal regions and maps. Appendix B presents detailed instructions to :ield 

workers on the housing unit definition. Appendix C presents the strata listings by Census division.

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
2.

It is necessary to select a sample of households for the RECS because the cost and burden of interviewing 

every household in the United States would be prohibitive. The RECS sample design has always been a 

national multistage area-probability cluster-sample design. This type of design is used for many of the national 

surveys of households or housing units that are conducted by the Federal government. The following is a 

description of the multistage area-probability design with specific details about the RECS design.

In each RECS cycle, the sample design is divided into a primary stage, a secondary stage, and an elementaryunit stage. These three stages are briefly outlined in the box below.

Of.

 !::P|l|ipp(;p^|ggp.^Iri this stage, Pnm^.S^^'lmg Unite. (PSU*s),f re -defined, grouped into 

Tstr||i|||i|Si|i|l;i>f the design. TTieJpiiiSliiEres in this stage' cartis divided into three

Procedures: -C^ipes^mdependent eities»'and other county-like 

lil^p||||ipji|i;: areas are used to

Procedures: Tle;:PSt*s are grouped intp: strata.

Procedures: One^SlJW' selected from eacM-stratura.

 In this stage,.. ttt|/.t||Fs::lhat were selectediii the primary stage are

Sampling K^;;^SS|||p;;;pultiple SSU*s artfelected from each PSU, 

divided into IMi^S^ieias, with one lisring: :segment selected per 

in this stage into five groups:

m Procedures: Censos ^geographic units sucjbijas Census tracts, enumer- 

, block groups, aitd^;iiii|vMual blocks are used.; to form SSU's.

Procedures: The-SStJ's; are ordered or stratifled. The selection procethat these san|plis;.!SSlJ'& reflect the distribution of the values of the 

in the ordering or stratifieation. :;

;; r; : ;;^^ Fbrthe.larger SSU's selected/to the secondary stage, field

iiyass the SSU by autoiripbile or on foot, recording gross estimates of the 

of housing units on eacrt-:61ock face. : :

Procedures'.:;. Jh$ SSU's selected in the secondary stage are 

.mjp listing se}pnent$ using the rough counts of housing units. Smaller SSU's 

single listing segrnents* : " :;

io« Procedures: A single listing segment is selected for each SSU 

secondary stage.

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
Stages of RECS Sample Design (Continued)

Elementary-Unit Stage: Housing units make up the most elementary units in the 

RECS. In this stage, housing units are selected from their respective listing segments and 

given to the field workers for their interviewing assignments. The elementary-unit stage can 

be subdivided into three groups of procedures:

1. Field-Listing Procedures: For each listing segment selected, field workers canvassed the 

segment on foot, identifying and listing the address of all housing units. The lists 

prepared by the field worker are used by central office workers to develop a 

comprehensive list of housing units in the segment.

2. Penultimate Cluster Selection Procedures: From each listing segment a single

penultimate cluster is selected. If the listing segment is not too large, the penultimate 

cluster will equal the listing segment. If the listing segment contains too many 

housing units, the penultimate cluster will be made up of a subset of these units.

3. Interviewer Assignment Procedures: An ultimate cluster of approximately five housing 

units is selected from each penultimate cluster. The housing units in the ultimate 

clusters make up the sample in which the field workers conduct their occupant 

interviews.

It may be argued that the penultimate clusters are the actual secondary-stage units. If this is true, then it 

follows that the field-listing procedures and the penultimate cluster selection procedures are really part of t.h; 

secondary stage. However, EIA has chosen to place the field-listing procedures and the penultimate cluster 

selection procedures in the elementary-unit stage, because these procedures deal with the elementary units.

Design Considerations

The number of PSU's selected in the primary stage, the number of SSU's (or listing segments) per PSU, and 

the number of observations in the ultimate cluster, are chosen according to survey design principles. Taess 

decisions are made with the two-fold goal of reducing survey costs, and minimizing the variance of survey 

estimates.

The first two stages in the design (primary and secondary), are used to select a sample of listing segments, 

The size of the listing segments is determined by two goals:

1. The approximate number of housing units in a listing segment should be small enough so that ,a 

comprehensive list of these units can be developed by field workers at a reasonable cost

2. A listing segment needs to contain a sufficient number of housing units to cover the needs of several 

cycles of the RECS surrey.

During the initial RECS design effort, as well as during the 1984 design update, the minimum size of a listing 

segment was 25 housing units. For the 1993 design, the minimum size was expanded to 50 housing units, for 

the core sample, and 96 housing units for SSU's in a new construction supplement. The minimum size for 

the core sample SSU's was increased to give more flexibility in the elementary-unit stage not only for the 1993

Energy Information Administration/Energy Consumption Series 

6 Sample Design for the Residential Energy Consumption Survey
RECS, but also for the 1996 and 1999 REGS. The 1980 and 1984 designs called for the listing segments and 

penultimate clusters to be periodically replaced. If a 1993 RECS SSU does not experience substantial new 

residential construction, current plans call for using the corresponding 1993 penultimate cluster in the 1996, 

the 1999, and perhaps in the 2002 RECS. The expanded minimum size for the penultimate clusters ensures 

that they will contain enough housing units for four RECS cycles, as well as provide for an oversampling of 

low-income areas and new housing units. The expanded minimum size also allows for an increase in the core 

sample size for future RECS. The minimum size for SSU's in the new construction supplement is larger than 

that of core sample SSU's, due to the higher sampling rate for new housing units.

The penultimate cluster selection procedures are incorporated into the design as a cost-saving feature. Only 

the housing units in the penultimate cluster are keyed into the data base used to select the ultimate cluster. 

In addition, apart from major design revisions, or the occurrence of significant new construction (see 

Chapter 7), the list of housing units is updated only for the compact area covered by the penultimate cluster.

The most expensive parts of the design effort are the rough-counting procedures of the secondary-unit stage, 

and the field-listing procedures of the elementary-unit stage. Both of these procedures require the use of field 

workers in order to obtain data, and central office staff to edit, clean, and process the data. In the roughcounting procedures, field workers are used to obtain an approximate number of housing units by block face 

in the selected SSU's. In the field-listing procedures, field workers are used to prepare the comprehensive lists 

of housing units in the selected listing segments. The entire primary stage, and the SSU formulation and 

selection procedures of the secondary stage, can be done in a central office using maps, computer software, 

and data bases obtained from vendors and from the Bureau of the Census. Similarly, the segment formulation 

and selection procedures, the penultimate cluster selection procedures, and the interviewer assignment 

procedures, can be done in a central office using the rough counts and comprehensive lists prepared by the 

field workers.

If a SSU is small enough to economically list all of its housing units, then the rough-counting procedures, the 

segment formulation procedures, and the segment selection procedures are not needed. In this case, the SSU 

is not divided into listing segments. The entire SSU is defined as a single listing segment and is automatically 

selected.

The target number of housing units in a SSU for the 1980 and 1984 designs was 400. All of the SSU's for 

these designs, therefore, were much larger than the minimum size. Consequently, the rough-counting 

procedures, the segment formulation procedures, and the segment selection procedures were necessary for all 

of the 1980 and 1984 SSU's.

In the 1993 design, the target number of housing units was reduced to a quantity that was much closer to the 

minimum size. In the 1993 RECS, the core SSU's were defined so that their projected minimum number of 

housing units was 50, and the new construction supplement SSU's were defined so that their projected 

minimum number of housing units was 96. As a result, the proportion of SSU's in which the rough-counting 

procedures, the segment formulation procedures, and the segment selection procedures were necessary, was 

much smaller. This resulted in a cost savings for the design phase.

In summary, the number of cases where rough counting was necessary was substantially reduced in the 1993 

design. This was possible because the minimum size for a listing segment was increased for the 1993 design 

effort, while the size of the SSU's was reduced. Prior to the 1990 Census, the Bureau of the Census divided 

the entire country into Census tracts and divided all Census tracts into blocks. This enabled the 1993 survey 

design team to use smaller Census units to define SSU's in rural areas. In the 1980 Census, the smallest 

Census unit in many rural areas was an enumeration district.

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
to the

The REGS was designed to collect data on energy-related characteristics, both of housing units and the 

households living in these units. Consequently, the RECS elementary-sampling units were occupied housing 

units. The RECS was further restricted to housing units that are the primary residence of the occupants. As 

a result, there is a one-to-one correspondence between households and occupied primary-housing units. Since 

the elementary-sampling units for the CPS are households, its design was used as a model for the development 

of the sample design for REGS.

The CPS is mainly concerned with demographic and labor-force statistics, while the RECS is concerned with 

energy characteristics. Also, while the sample SITS, for the CPS is approximately 60,000 observations, the 

sample size for RECS is approximately 5,000 observations. Because of these variations, there are differences 

between the sample designs for RECS, and the design for the CPS. For example, the number of PSU's and 

SSU's used for RECS will be smaller than the number used for the CPS. In addition, the variables used to 

stratify or order the sampling units for the three stages of the sample design will not be the same for RECS 

as for the CPS.

The 1980 REGS sample design was limited by the following constraints'1 :

 Data are to be statistically reliable for nine Census divisions and ten Federal regions. (These are 

discussed in Chapter 5.)

 A self-weighting national sample should be included as the core of the total design; the balance of the 

sample is to be allocated so that, as a minimum, a specified level of precision is achieved for each 

Census division and Federal region

 Sample households are to be selected from as many States as possible; inclusion of some sample units 

in Alaska and Hawaii is to be assured

 In addition to regional geographic factors, stratification modes should be based, to the extent possible, 

on principal home heating fuel and climatological factors

 As a quality control factor, a minimum of two interviewers should be available for data-collection 

activity within reasonable travel distance of each cluster of sample households.

These additional constraints also affected the design:

 The design must provide for the contingency that RECS may have to be fielded every 6 months 

 The design must provide for the contingency of including a longitudinal component in future RECS

 The 1980 Census population data, and data on the number of households, were not available during 

the design phase. The 1970 Census data were available, but were outdated for some localities

4 Residential Energy Consumption Survey, Sample Desist and Methodology National Household Surveys: 1980, 1981, and 1982, 

Response Analysis Corporation, Princeton, New Jersey, August 1983.

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey g
 The most recent definitions of Metropolitan Statistical Areas--issued by the Office of Management 

and Budget formerly known as Standard Metropolitan Statistical Areas were those as of 1980, and 

developed prior to the completion of the 1980 Census

 The 1980 RECS was designed to produce 5,000 completed observations

 The design must provi.de for the contingency that would extend the survey to produce State-level dala.

1984 Sample Design

In the 1984 RECS redesign effort, the following changes were made in the design constraints:

 The mandate requiring the 1984 RECS to provide statistically reliable estimates for each of the ten 

Federal regions was eliminated. As a result, the number of strata used in the first stage of the design 

was reduced. The mandate requiring the 1984 RECS to provide statistically reliable estimates for each 

of the 9 Census divisions was observed

 The 1980 Census data would be available for the design effort

« The June 1983 definitions of MSA's (developed following the 1980 Census) would be available for the 

design effort.

1993 Sample Design

In the 1993 RECS redesign effort, the following changes were made in the design constraints:

 The 1990 Census data would be available for the design effort

 The June 1990 definitions of MSA's would be available for the design effort (developed prior to tie 

completion of the 1990 Census)

 The design was required to have the capability to oversample newly constructed housing units. 

The following changes were made to the RECS sample design as a result of the 1993 redesign effort:

 The number of strata of PSU's was reduced primarily because of larger increases in the PSU-leveC 

survey costs (for example, administrative costs, and the cost of recruiting and training interviewer?), 

in contrast to SSU-level survey costs and the elementary-unit level costs, which showed smaller 

increases

 The stratification procedures used in the primary stage were changed in order to use more energyrelated characteristics;

 The SSU's for metropolitan PSU's were stratified by energy-related characteristics and geography, 

For nonmetropolitan PSU's, the SSU's were stratified by geography alone

 A new construction supplement was incorporated into the sample design. Part of the supplement was 

the selection of 150 SSU's, which were expected to include high percentages of new homes

 The number of PSU's and SSU's assigned to each Census division was altered to more closely reflect 

the relative 1990 Census population of each Census division.

Energy Information Administration/Energy Consumption Series 

10 Sample Design for the Residential Energy Consumption Survey
4. Optimization Analysis

Prior to each major revision in the RECS sample design, an optimization analysis is conducted to determine 

the optimum number of PSU's, SSU's per PSU, and observations per SSU. The results of this analysis are 

used to guide decisions concerning the number of strata in the primary stage, the number of SSU's per PSU 

in the secondary stage, and the size of the ultimate clusters in the elementary-unit stage.

In each case, the optimization analysis only considered the effect of the sample design on the precision of 

national level statistics. It would be possible to expand the optimization analysis to cover the effect for 

subnational level statistics, but the vast number of subnational level statistics that are of interest implies that 

it would be very difficult and time consuming to conduct an optimization analysis that covers the effect on all 

statistics of interest. Consequently, each optimization analysis was restricted to covering the effect on the 

precision of national level statistics. Hence; the results of the optimization analysis are not completely 

followed in determining the sample design parameters. The results are used as a guide for determining the 

design parameters.

In a multi-stage sample design, the level of precision is affected not only by the total number of sample 

households, but also by the interaction of all the design features: the number of PSU's, the number of SSU's, 

the average size of an ultimate cluster, the "within" versus the "between" PSU variance, and the effectiveness 

of stratification, etc. The interaction between the level of precision and the design factors is approximated 

by the following formula5 :

Vr2 * V2 [1/mnql^-fiq + 1 + 8 2(q - 1)] (I)

where: Vr2 is the relvariance of an estimated mean or percentage derived from the survey results

V2 is the unit relvariance in the universe

m is the number of sample PSU's

n" is the expected value of the average number of SSU's per sample PSU

q" is the expected value of the average number of elementary units in an ultimate 

cluster that result in completed interviews

8 t is the "within" PSU measure of homogeneity 

8 2 is the "within" SSU measure of homogeneity. 

Note that the product of m, if, and q" is the total sample size.

The values of V2, o^, and 8 2 are estimated using survey data. For the optimization conducted prior to the 

development of the 1993 design, 1990 RECS data were used to estimate the values for these parameters.

Hansen, Hurwitz, and Madow, Sample Survey Methods and Theory Volume I Methods and Applications, p 403, John Wiley & Sons, 

1953.

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 11
In order to determine the optimum set of values for m, n, and q, where the total sample size is held fixed, 

it is necessary to approximate the survey costs (i.e., design, data collection, and data processing costs) as a 

function of m, if, and q". The following simple cost function was used to approximate the relationship6 :

C = Qm + QmTr + Q,mn q (2)

where: C is the portion of the total survey cost associated with "volume related" activities 

Ct is the cost per selected PSU 

C, is the cost per SSU 

C4 is the cost per completed interview.

If the sole purpose of RECS was to produce a national estimate of a single statistic, such as the number of 

housing units in the country using electricity as a primary heating source, or the average electricity 

consumption per housing unit, then the design should agree closely with the results of the optimization 

analysis. However, since RECS is a multi-purpose survey, the data obtained through it will be used to product: 

estimates for many housing-unit characteristics. In addition, EIA is interested in producing not only national 

estimates, but also estimates by Census division, by housing-unit type, by household income, as well as many 

other categories of residential energy use. As a consequence of the multipurpose nature of RECS, the value 

of its design varies depending on the characteristic of interest. This particular design will produce moieprecise estimates for some characteristics and less for others.

The optimization analysis in the 1993 design is conducted on 1990 RECS data, as this represents the latest 

data available. Figure 1 defines the parameters used in the optimization analysis, and Table 1 lists these 

parameters along with their resulting optimal values. The cost per primary stage unit (Q) is $3,095.50, the 

secondary stage cost per unit (C,) is S368.50, and the cost per observational unit (C4) is $184.00. The opti 

mization analysis was based on the assumption that the core sample size would be 5,095 observations. If the 

optimization analysis had been done with a fixed cost (that varied from the final effective cost) instead of a 

fixed sample-size, it would have called for a different value of m.

In an attempt to generalize the specific results contained in Table 1, the twenty-three ratio estimates - grouped into four classes: (1) consumption and expenditure variables; (2) housing unit characteristic variable;; 

(3) variables relating to appliance ownership; and (4) demographic characteristics of home owners. Within 

each of these four classes, average values of intraclass correlations were computed. The class averages for the 

intra-class correlation statistics were then used to compute optimal allocation solutions for each general class 

of variables. Table 2 provides the optimal allocation results for the resulting grouped computations.

The values that were used for the 1993 RECS sample design were m - 116, n' = 12.6, q~ = 4.11, and the core 

sample size was equal to 6,000 observations. Chapters 5 and 6 will discuss in detail, the number of PSU's, and 

the number of SSU's that were actually used in the 1993 RECS sample design.

The number of PSU's (m) used in the 1993 RECS sample design does fall within the range indicated by the 

optimization analysis. However, the average number of SSU's per PSU (n) used, and the average number of 

observations per ultimate cluster (q"), differ substantially from that indicated by the optimization analysi:;. In 

particular, the average number of SSU's per PSU is smaller than that indicated by the optimization analysis, 

while the average number of observations per ultimate cluster is larger.

6 Hansen, Hurwitz, and Madow, Sample Survey Methods and Theory Volume I Methods and Applications, p 408, John Wiley & Son . 

1953.

Energy Information Administration/Energy Consumption Series 

12 Sample Design for the Residential Energy Consumption Survey
Figure 1. Description of Ratio Statistics Used in the 1990 REGS Components of Variance Analysis

Ratio Statistic Name

HomeArea

Description

Mean Electricity Consumption per Household in Btu

Mean Natural Qas Consumption per Household in Btu

Mean Annual Household Expenditure For Electricity in Dollars

Mean Annuat Household Expenditure For Natural Gas in Dollars

Mean Toft! isnefgy Consumption per Household in Btu

Mean Total Energy Expenditure per Household in Dollars

Proportion of Housing Units with Window Awnings

Mean Number of Bedrooms per Household

Proportion of Housing Units with Window Blinds or Drapes

Proportion of Households with a Clothes Washer

Proportion of Households with a Dishwasher

Mean Number of Licensed Drivers per Household

Proportion of Households with an Electric Clothes Dryer

Proportion-of Households with a Male Head

Mean Number of Square Feet of Space per Household

Proportion of Households with Annual Income Over $35,000

Proportion of Households Owned by the Current Resident

Mean Number of Bathrooms per Housing Unit

Mean Cubic Feet of Refrigerator Storage Space

Mean Number of Stories per Housing Unit

Mean Number of Color Televisions per Household

Mean Nurribfcf of Cars and Trucks per Household

Mean Square Feet of Window Space per Household

Source: Energy Information Administration, Analysis of Components of Variance for the Residential Energy Consumption Survey 

(Draft), Survey Research Center, Institute for Social Research, University of Michigan (Ann Arbor, Michigan), December 16, 1993.

If the 1993 RECS sample design closely followed the optimization analysis, the average number of observations 

per ultimate cluster for the core sample would have equaled approximately 1.5. In order to have 6,000 

observations, the total number of SSU's (m x if) would equal approximately 4,000. To use such a large 

number of SSU's would have substantially increased the design and survey costs. In order to stay within 

budget, fewer than 4,000 SSU's were used.

If q" and ¥ are within the optimal range, and m is smaller than 116, then the total number of sample SSU's 

would be reduced, while the total core sample size would also be reduced. A design using such values for q",

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 13
n, and m would result in more precise national estimates of energy statistics than the design that was actual!', 

used, but the precision for the corresponding estimates for many subsections of the population would havr 

been lowered.

Table 1. Optimum Multistage Allocation-Solution Estimates for 1990 

RECS Ratio Statistics

Variable

Btu Electricity

Btu Natural Gas

Dollars Electricity

Dollars Natural Gas

Total Btu

Total Dollars

Awnings

Bedrooms

Blinds/Drapes

Clothes Washer

Dishwasher

Drivers in HH

Electric Dryer

HH Sex

Homearea

Income $35,000+

HU Tenure

No. Complete Baths

Refrigerator Size

Stories

Color TV

Vehicles

Windows

£L

.01 241

.02278

.01308

.01968

.01271

.00287

.00036

.01141

.00075

.00342

.00153

.00320

.00660

.00132

.01418

.0001 1

.00899

.00650

.00394

.01403

.00098

.00445

.00675

S2

.37094

.56636

.33392

.56296

.56358

.41881

.10751

.69468

.07600

.7361 1

.25621

.27615

.44753

.06892

.68448

.47697

.65739

.55433

.34716

.69230

.26064

.36352

.62120

Optimal Allocation

q"

1.84

1.24

2.00

1.25

1.25

1.67

4.08

0.94

4.93

0.85

2.41

2.29

1.57

5.20

0.96

1.48

1.02

1.27

1.94

0.94

2.38

1.87

1.11

n

15.84

14.45

14.64

15.50

19.30

35.02

50.10

22.62

29.08

42.52

37.45

26.93

23.86

20.97

20.13

18.64

24.78

26.78

27.22

20.36

47.38

26.20

27.80

m

174.5

284.7

174.1

263.6

212.0

87.3

24.9

240.1

35.5

141.4

56.4

82.6

135.8

46.7

263.4

1 38.9

201.3

150.0

96.5

265.2

45.1

103.8

165.9

Source: Analysis of Components of Variance for the Residential Energy Consumption Survey, 

Sampling Section, Survey Research Center, Institute for Social Research, University of Michigan 

(Ann Arbor, Michigan), December 16, 1993.

Table 2. Optimum Multistage Sample Allocation Based on Average Values of 

Estimates of A,, and <5 2

Variable

Optimal Allocation

Consumption and Expenditure Variables .013922 .469427

Housing-Unit Characteristic Variables .007711 .490072

Appliance Variables .003444 .383903

Demographic Variables .003474 .401091

1.50

1.44

1.79

1.73

n

16.83

23

30

31

10

60

14

m

201.2

152.8

92.9

94.6

Source: Analysis of Components of Variance for the Residential Energy Consumption Survey, Sampling Section, 

Survey Research Center, Institute for Social Research, University of Michigan (Ann Arbor, Michigan), December 16, 1993.

14

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
Even though the values of q, n, and m that were used in the 1993 RECS design differ from those called for 

by the optimization analysis, the precision of the national estimates remains near the optimum (due to the 

breadth of the optimum), and the precision of most subnational estimates of interest remains greater than 

would those yielded by a design following the results of the optimization analysis.

If the population of households is divided into three income categories (such as low, middle, and high), then 

the effective size of q^ for these categories would be approximately one-third of their original value; hence the 

value of q^ used for the 1993 design would fall in the range called for by the optimization analysis.

The 1980 RECS sample design used 131 PSU's, and an average of 11.6 SSU's per PSU. The 1984 RECS 

sample design used 129 PSU's, and an average of 11.8 SSU's per PSU. The number of observations per SSU 

averaged 3.3 for the 1980 through 1990 RECS.

The 1993 RECS sample design resulted in similar values. The number of PSU's was reduced from 129 in 1984 

to 116 in 1993, while the number of SSU's in the core sample was reduced from 1,516 in 1984 to 1,460 in 

1993. The number of observations per SSU was increased from an average of 3.3 to 4.1 for the core sample 

of the 1993 RECS. The reduction in the number of PSU's was due to cost increases at the PSU-level which 

outpaced those at the SSU and the elementary-unit levels. The number of observations per SSU was increased 

in order to provide a larger sample size, at the most cost-effective level.

There would have been a greater reduction in the number of PSU's if the 1993 RECS design had not required 

the survey to support Census division-level estimates with a specified maximum Relative Standard Error 

(RSE), as is discussed below. For this reason, the minimum number of PSU's in a Census division was set 

at 8.

One of the constraints in the 1993 RECS sample design was that the RSE of the estimate for the average 

energy expenditures per household would be less than or equal to the predetermined levels. The RSE for the 

National level estimates would be a maximum of 1.25 percent. The estimates for each Census region would 

have an RSE of no more than 2.75 percent, while the estimates for each Census division would have an RSE 

of 4.5 percent, or less. These constraints were determined by examining the results of the 1980 through 1990 

RECS. Simulations projected that the sample design with the above values for q", "n, and m would result in 

RSE estimates below the constrained maximum RSE values listed above.

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 15
5B Primary sff "^s? of the m ^^F

During the primary stage, the PSU's are defined, grouped into strata, and selected for the design. The 

following decisions are made during the design and implementation of the primary stage:

 Whether to select just one PSU per stratum, or to select two or more PSU's per stratum

» How will Census division boundaries and Federal region boundaries constrain the sample design

 The total number of strata to use in the primary stage

 Which criteria to use when forming PSU's

 Which criteria to use when grouping PSU's into strata

 How to select PSU's from strata?

Each of these decisions can be divided into one of the following three procedures: (1) PSU formulation 

procedures, (2) strata formulation procedures, and (3) PSU selection procedures. These decisions will be 

discussed in detail in the following sections.

Number of per

There are two basic competing strategies for the primary stage of a multistage area-probability sample design:

1. One PSU per stratum strategy: Stratify the sampling units as much as possible, then select only one 

sampling unit per stratum

2. Two or more PSU's per stratum strategy: Restrict the amount of stratification and if a stratum 

contains more than one sampling unit, select at least two of them.

For either strategy, an optimization analysis is used to determine the approximate number of sampling units 

that will be selected during each stage of the design.

The main advantage of the one-PSU per stratum strategy is the use of stratification to the fullest extent in 

order to improve the accuracy of the survey estimates. Its main disadvantage to survey estimates is the 

inability to obtain a pure estimate of the sampling errors. Stratifying to the fullest extent may improve the 

estimate, but as a result, it is necessary to use a variance estimation technique that does not utilize a pure 

estimate of the between sampling unit variance.

The main advantage of the two-PSU's per stratum strategy is that it is possible to obtain a pure estimate of 

the variance using a two-sampling unit per stratum design. Its main disadvantage is that fewer strata are used, 

and as a result, the precision of the estimate is lowered.

An early decision was made to use the one-PSU per stratum strategy for the primary stage. The sample design 

for all cycles of RECS have used the one-PSU per stratum strategy, and the 1993 sample design will continue 

to use this strategy. The only exception, in the 1993 sample design, was that the Fort Worth, Texas MSA; the

Residential Energy Consumption Survey Primary Stage Sample Design Plan (Third Draft), Sampling Section, Survey Research Center, 

Institute for Social Research, University of Michigan (Ann Arbor, Michigan), February 1, 1993.

Energy Information Administration/Energy Consumption

Sample Design for the Residential Energy Consumption Survey 17
San Antonio, Texas MSA; arid the Austin, Texas MSA were placed in the same stratum and two MSA's were 

selected from it. The reasons for using a double strata in this case are discussed in detail in the section titled! 

"Number of Strata by Type and Census Division" in this chapter.

Census Divisions and Federal Regions

As mentioned earlier, the 1980 RECS was designed in such a way that its data could be used to estimate 

energy characteristics for each of the nine Census divisions and each of the ten Federal regions, This 

prevented PSU's, and the strata used in the primary stage, from crossing the Census division or Federal region. 

boundaries. However, because the 1984 and 1993 RECS designs were no longer required to produce estimates. 

for the ten Federal regions, the PSU and strata boundaries could now cross Federal region boundaries (but 

they were still unable to cross Census division boundaries). Figure 2 lists the nine Census divisions and ten. 

Federal regions. They are also illustrated in map form in Appendix A.

Energy Information Administration/Energy Consumption Series 

18 Sample Design for the Residential Energy Consumption Survey
Figure 2. List of the States Within Census Divisions and Federal Regions

The nine Census divisions are defined as follows:

1, New England; Connecticut, Maine, Massachusetts, New Hampshi(-8,"fthode Island, and Vermont

Z. Middle Atlantic: New Jersey, New York, and Pennsylvania

3. East North;,Central: Illinois, Indiana, Michigan, Ohio, and Wisconsin

4. West North::6eritra(: Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota

5. South Atlantic: Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South

= -s Carolina, Virginia, and West Virginia

6. East South Centra!: Alabama, Kentucky, Mississippi, and Tennessee

7. We8tS^utH;<50rrtral: Arkansas, Louisiana, Oklahoma, and Texas

8. Mountain: Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming

9. Pacific: : Alaska, California, Hawaii, Oregon, and Washington.

The 10 Federal Regions are defined as follows:

Federal -Regtoipj -'8 ;';- Connecticut, Maine, Mlssachusetts, New Hampshire, Rhode Island, and Vermont 

Federal :)te|[||li21 ': S; ,' ; ..._v. . New Jersey and New York ^ 

Federal Flel|(|^|S; ; Delaware, District olXSpJunfibia, Maryland, Pennsylvania, Virginia, and West Virginia

v 5 : Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina,

' : "i'v- "^."' .' : and Tennessee h; ' -'- "-.-'

Federal Rs||J5|i!)5;; M ?: } Illinois, Indiana^ Mjcjjiggni Minnesota, Ohio, and Wisconsin

Federal He^|i|6f/^i=! ^ Arkansas, Louisiana^ l|8«r Mexico, Oklahoma, and/Texas

Federal Regj<i(iK0 ;=; ; Iowa, Kansas, Missouri, sand Nebraska ;

Federal-Re^t|n1|(: : v >; Colorado, Montana, t46rth Dakota, South Dakota, Utah, and Wyoming

Federal Reg^;!&l^:; y Arizona, California, Hawaii, and Nevada

Federal Region 10: % ; _.- Alaska, Idaho, Oregonjiand Washington

Energy information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 19
The New England Census division and the 1st Federal region are identical. For all other Census divisions, 

there does not exist an identical Federal region. Similarly, for all other Federal regions, there does not exis/: 

an identical Census division. The combined boundaries of the nine Census divisions and the ten Federal 

regions produce 17 intersections. These intersections are listed in Figure 3. The strata boundaries for the 

1980 REGS design could not cross the boundaries of the 17 intersections.

Figure 3. State Intersections of Census Divisions and Federal Regions

Federal 

Region

1

2

3

4

5

6

7

8

9

10

Census Division

New England

Middle Atlantic

Middle Atlantic

South Atlantic

South Atlantic

East South Central

East North Central

West North Central

West South Central

Mountain

West North Central

West North Central

Mountain

Mountain

Pacific

Mountain

Pacific

Intersection

1-

2-

3-

4-

5-

6-

7-

8-

9-

10-

11-

12-

13-

14-

15-

16-

17-

of Federal Region and Census Division

Connecticut, Maine, Massachusetts, New Hampshire, Rhode 

Island, and Vermont

New Jersey and New Yort

Pennsylvania

Delaware, District of Columbia, Maryland, Virginia, and 

West Virginia

Florida, Georgia, North Carolina, and South Carolina

Alabama, Kentucky, Mississippi, and Tennessee

Illinois, Indiana, Michigan, Ohio, and Wisconsin \

Minnesota

Arkansas, Louisiana, Oklahoma, and Texas

Mew Mexico

Iowa, Kansas, Missouri, and Nebraska

North Dakota and South Dakota

Colorado, Montana, Utah, and Wyoming

Arizona and Nevada

California and Hawaii

Idaho

Alaska, Oregon, and Washington

Source: Energy Information Administration. Residential Energy Consumption Survey, Sample Design and Methodology Natioi'a 1 

Household Surveys: 1980 - 1981, and 1982, Response Analysis Corporation (Princeton, NJ), August 1983.

20

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
Number of Strata to Use in the Primary Stage

The approximate total number of primary stage strata that will be used is determined during the optimization 

analysis. The final number of strata reflects decisions made concerning the number of strata per Census 

division, and within Census divisions, per strata type (e.g., large metropolitan areas, small metropolitan areas, 

non-metropolitan areas, and mixed areas). For each Census division, including the national total, Table 3 is 

divided into two parts (a and b), which provides the following data:

« The number of primary stage strata for the 1980, 1984, and 1993 sample designs

 The population: the 1980 design employs the 1978 population estimates, the 1984 design employs the 

1980 Census results, and the 1993 design employs the 1990 Census results

 The average population per primary stage stratum: the average population given in the 1980 design 

is the average 1978 population, in the 1984 design it is the average 1980 population, and in the 1993 

design it is the average 1990 population

 The 1990 Census number of households

 The average number of households per stratum for the 1993 sample design.

The reason for determining the number of households and the average number of households per stratum, is 

because the Measure of Size (MOS) used to select the PSU's changed from PSU population in the 1980 and 

1984 designs, to PSU number of households in the 1993 design. (The MOS is discussed later in this chapter.) 

From a practical perspective, each of the two variables used for the MOS is equally acceptable in devising a 

multipurpose probability-sampling design.

Because the RECS sample design has always used a one-PSU per stratum approach, there is a one-to-one 

correspondence between the strata and the PSU's selected. Therefore, when discussing the design, there is 

a tendency to interchange the terms stratum and PSU. To illustrate this, the 1980 sample design used 131 

PSU's; this means that the sample design for the 1980 RECS grouped the PSU's into 131 strata and selected 

one PSU per stratum, which yielded 131 PSU's.

The 1980, 1984, and 1993 sample designs each determined the set of self-representing PSU's by a standard 

sampling approach; the PSU's that exceeded in MOS a substantial fraction of the average MOS per stratum 

were identified as the self-representing set. Therefore, in each of the three sample designs, the New York 

counties of the New York Primary Metropolitan Statistical Area were grouped into two PSU's. New York 

City (Bronx, Kings, New York, Queens, and Richmond counties), and its northern suburbs (Putnam, Rocldand, 

and Westchester Counties), formed one PSU, which was placed into a stratum by itself. This PSU contained 

3,252,000 households in 1990, larger than any other PSU. The Long Island counties (Nassau and Suffolk) 

formed another PSU that was placed in a stratum by itself. The Illinois region of the Chicago PMSA, as well 

as Los Angeles county, were also single PSU's. These three largest self-representing PSU's significantly 

increased the average number of households per PSU in their respective Census divisions.

For variance estimation purposes, each self-representing PSU has, within its Census divisions, the approximate 

effect of two non-self-representing PSU's. Moreover, because of their large populations, the New York City, 

Chicago, and Los Angeles PSU's have the effect of three or four non-self-representing PSU's.

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 21
In general, the convention of treating the very large MSA's as self-representing PSU's, and the restriction 

treating Alaska and Hawaii as separate strata, means that the 116 strata used in the 1993 sample design were, 

for variance estimation purposes, more like a design with approximately 150 strata.8

Table 3a. Number of Primary Stage Strata and Population by Census Division for 1980, 

1984, and 1993 REGS Sample Designs

Census 

Division

Total

New England . Middle Atlantic

East North Central . West North Central .

South Atlantic .... 

East South Central 

West South Central

Mountain 

Pacific . .

Number of Primary 

Stage Strata

1980 

Design

1984 

Design

1993 

Design

Population 

(millions)

1980 

Estimates

1980 

Census

1990 

Census

131 129 116 218.1 226.5

10

14

16

17

17

13

12

13

19

10

15

17

17

19

12

12

11

16

8

13

17

9

20

8

14

10

17

248.7

12.3

35.8

41.2

r.'.o

34.6

14.0

22.0

10.3

29.8

12.3

36.8

41.7

17.2

37.0

14.7

23.7

11.4

31.8

13.2

37.6

42.0

17.7

43.6

15.2

26.7

13.7

39.1

Table 3b. Average Population and Number of Households per Stratum by Census Division for 

1984, and 1993 REGS Sample Designs

Census 

Division

Total ....

New Engla 

Middle Atla

East North 

West North

South Atlan 

East South 

West South

id .........

Central .....

tic .........

Central .....

Central .....

Average Population per 

Primary Stage Stratum 

(millions)

1980

Design

1.7

1.2

2.6

2.6 

1.0

2.0 

1.1 

1.8

0.8 

1.6

1984 

Design

1.8

1.2

2.5

2.5 

1.0

1.9 

1.2

2.0

1.0 

2.0

1993 

Design

2.1

1.7 

2.9

2.5 

2.0

2.2 

1.9 

1.9

1.4 

2.3

Number of Households for 1993

Design (1990 Census Data)

(millions)

Total

91.9

4.9

13.9

15.6

6.7

16.5

5.7

9.7

5.0

13.9

Average 

per Stratum

0.8

0

1

0

0

0

0

0

0

0

6

1

9

7

a

7

7

5

8

Source: Residential Energy Consumption Survey Primary Stage Sample Design Plan (Third Draft), Sampling Section, Survey Research 

Center, Institute for Social Research, University of Michigan (Ann Arbor, Michigan), February 1, 1993.

Residential Energy Consumption Survey Second Stage Sample Design Plan, Sampling Section, Survey Research Center, Institute: lot 

Social Research, page 7, University of Michigan (Ann Arbor, Michigan), June 1, 1993.

22

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
Note that the number of strata for the West North Central Census Division dropped from 17 in the 1980 and 

1984 designs, to 9 in the 1993 design. The large number of strata (relative to its population), in this Census 

division in the 1980 design, was a result of the stipulation preventing the strata from crossing Census divisions 

or Federal region boundaries, as well as the need for the statistical reliability of data for each of these 

geographic domains.

The preliminary finding (based on energy data collected prior to 1978) showing the variance of household 

energy expenditures to be higher in this Census division than in other Census divisions, also contributed to 

this large number. The relatively high number of PSU's assigned to this division in the 1980 design was 

carried over to the 1984 design. In the 1993 design, the decision on the number of PSU's to assign to each 

division was made independently of previous designs. A study of the 1990 RECS results indicated that there 

was no significant difference in the variance of household energy expenditures for the different Census 

divisions. Consequently, the number of PSU's assigned to the West North Central Census Division was 

reduced in the 1993 design.

If the RECS sample design was optimized to produce the lowest possible variance for the estimated energy 

consumption per household in the entire Nation, and if the optimization analysis was developed under the 

assumptions that: (1) the sample size was fixed, (2) the standard deviation of household energy consumption 

was the same for all Census divisions, and (3) costs was the same for all Census divisions, then the number 

of strata in a Census division should be roughly proportional to its number of households. Inequalities 

occurred for the following reasons: (1) upper boundaries were placed on the variances for the per household 

estimates of energy expenditures in each of the Census divisions; and, (2) the convention of treating large 

MSA's as single PSU's was used. The upper boundaries resulted in the use of extra PSU's for those Census 

divisions with the smallest population. The convention of treating very large metropolitan areas as selfrepresenting PSU's meant that their population was much larger than that of other PSU's.

Table 3 also shows that the average population per stratum for the nine Census divisions is closer in the 1993 

sample design than in the 1980 or 1984 sample designs. This improvement followed the elimination of the 

ten Federal region estimates, as well as the assumption that the variance of household energy expenditures 

is approximately equal for all Census divisions.

Criteria for Forming Primary Sampling Units

The RECS sample designs all used the same overall strategy for defining PSU's. In metropolitan areas, the 

PSU's are usually defined by the boundaries of MSA's. In non-metropolitan areas, the PSU's are usually 

individual counties or groups of contiguous counties. This is the same convention that is used for many 

national surveys conducted by the Federal government.

In the 1980 and 1984 sample designs, PSU boundaries did not cross State lines, with the exception of the 

Washington, DC metropolitan area. The design included this restriction in order to provide for its possible 

future expansion to a State-level survey. In the 1993 sample design, this restriction was relaxed to allow PSU's 

to cross State lines in more situations. These exceptions always involved PSU's in those metropolitan areas 

that included counties in two or more States.

In order to provide for the contingency that EIA forecasting models may require energy consumption estimates 

for the larger States, PSU boundaries were not allowed to cross State lines in California, New York, Texas, 

and Florida.

In all RECS sample designs, the restriction that prevented PSU boundaries from crossing Census division lines 

was observed. This restriction reflected the desire to control the effect on the variance in using the RECS data 

to make Census division-level estimates. Moreover, in the 1980 design, PSU boundaries did not cross Federal 

region boundaries.

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 23
In the 1980 sample design, the 3,141 counties and independent cities in the Unites States were formed into 

1,782 PSU's.* For the 1984 sample design, 1,799 PSU's were formed. For the 1993 sample design, 1,73* 

PSU's were formed. The following areas indicate where the PSU definitions were affected:

 Changes in the definitions of MSA's

« Changes in the treatment of MSA's that cross State lines

« Changes in the number of cases where large contiguous MSA's are combined to form a single PS7J

Criteria for Grouping Primary Sampling Units Into Strata

The PSU's are grouped into strata. Within the Census divisions, there are four types of strata:

1. Self-Representing Strata: Each of these strata contains only one PSU, and is the geographic are.fr 

corresponding to a MSA that has a large population. These PSU's are designated as self-representb:;: 

or "certainty" PSU's because they are included in the sample with certainty.

2. Non-Self-Representing MSA Strata: Each of these strata contains two or more PSU's. Each PSU

contained in these strata is defined as the geographic area covered by a MSA with a relatively smali 

or medium-size population.

3. Non-Self-Representing Non-MSA Strata: Each stratum in this category contains two or more PSU's 

Each PSU in these strata is comprised of a single non-metropolitan county (or similar jurisdiction), 

or a group of contiguous non-metropolitan counties.

4. Non-Self-RepresentLngMixed Strata: Each stratum in this category contains two or more PSU's. Oae 

or more of the PSU's is defined as the geographic area covered by a MSA with a relatively small or 

medium-size population,. One or more of the PSU's is comprised of a single non-metropolitan count,1 

(or similar jurisdiction), or a group of contiguous non-metropolitan counties.

Self-Representing Strata

Large MSA's are designated as self-representing or "certainty" PSU's because their MOS constitutes a 

substantial fraction of the MOS for their Census Division or "intersection" in the 1980 design. The minimum 

size for self-representing PSU's varies by Census division or by intersection.

The set of self-representing PSU's has changed with each major revision in the RECS sample design. In 

addition, the definition of individual self-representing PSU's has changed in relation to changes in MSA, 

definitions. The 1980 design used the 1980 MSA definitions, the 1984 design used the June 1983 MSA, 

definitions, and the 1993 design used the June 1990 MSA definitions. Figure 4 lists the self-representi:n (!i 

PSU's used for the 1980, 1984, arid 1993 RECS sample designs.

Residential Energy Consumption Survey, Sample Design and Methodology National Household Surveys: 1980, 1981, and 19K2, p 

Response Analysis Corporation (Prineslon, New Jersey), August 1983

Energy Information Administration/Energy Consumption Series 

24 Sample Design for the Residential Energy Consumption Survey
Figure 4. Self-Representing for 1980, 1984f and 1 i93 

by Census

Self-Representing PSU's

Census Division

New England

1980 Design

Boston 

Hartford

1984 Design

Boston 

Hartford

19S3 Design

Boston 

Hartford

Middle Atlantic

East North Central

West North Central

South Atlantic

East South Central 

West South Central

Mountain 

Pacific

Providence 

Fairfield County, CT 

New Haven

New York

Philadelphia

Nassau-Suffolk (Long Island)

Prttsburgh 

Newark

Chicago

Detroit

Cleveland

Minneapolis 

St Louis 

Kansas City

Washington, D.C.

Atlanta

Baltimore

None

Houston

Dallas

Phoenix

Denver

Salt Lake City

Los Angeles 

San Diego 

Orange County, CA 

Seattle

San Francisco-Oakland

Portland 

Tacoma

Providence 

Fairfield County, CT 

New Haven

New York

Philadelphia

Nassau-Suffolk (Long island)

Pittsburgh 

Newark

Chicago

Detroit

Cleveland

Minneapolis 

St Louis 

Kansas City

Washington, D.C.

Atlanta

Baltimore

Tampa

Miami

None

Houston 

Dallas

Phoenix

Denver

Salt Lake City

Los Angeles

San Diego

Orange County, CA

Seattle

Riverside-San Bernardino

San Francisco-Oakland

New York 

Philadelphia 

Nassau-Suffolk 

(Long island) 

Pittsburgh 

Newark

Chicago

Detroit

Cleveland

Minneapolis 

St Louis 

Kansas City

Washington, D.C.

Atlanta

Baltimore

Tampa

Miami

None

Houston 

Dallas

Phoenix 

Denver

Los Angeles 

San Diego 

Orange County, CA 

Seattle

Riverside-San 

Bernardino 

San Francisco 

Oakland 

Sacramento 

San Jose

Sources: * Energy Information Administration, Residential Energy Consumption Survey Primary Stage Sample Design Plan (Third 

Draft), Sampling Section, Survey Research Center, Institute for Social Research, University of Michigan (Ann Arbor, 

Michigan), February 1, 1993. The 1984 Residential Energy Consumption Survey Sample Design Procedures Manual, Orkand 

Corporation (Silver Spring, MD), March 1986. -» The Residential Energy Consumption Survey, Sample Design and Methodology 1980 

- 1981 National Household Survey (Draft Report), Response Analysis Corporation (Princeton, NJ), June 1981.

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 25
Non-Self-Representing MSA Strata

For each RECS design, the non-self-representing MSA PSU's were grouped into strata. Where possible, each 

stratum consisted of MSA's of similar size, from the same State (or at least contiguous States), and with ;i 

common dominate main space-heating fuel. Examples of non-self-representing strata in the 1993 RECS 

sample design are as follows:

Example 1: (Medium-Size MSA's ia New York) 

Buffalo 

Rochester 

Syracuse

Example 2: (Smaller MSA's in the northern half of the West North Central Census Division) 

Des Moines, Iowa 

Duluth, (Minnesota portion) 

Cedar Rapids, Iowa 

St Cloud, Minnesota

Fargo-Moorhead (Both North Dakota and Minnesota portions) 

Davenport-Rock Island-Moline (Iowa portion) 

Waterloo-Cedar Falls, Iowa 

Sioux Falls, South Dakota 

Rochester, Minnesota 

Iowa City, Iowa 

Bismarck, North Dakota 

Dubuque, Iowa 

Rapid City, South Dakota 

Grand Forte, North Dakota

In Example 2, the Wisconsin portion of the Duluth MSA is not in the West North Central Census Division; 

hence, it was placed in a non -self-representing MSA stratum in the East North Central Census Division, 

Similarly, the Illinois portion of the Davenport-Rock Island-Moline MSA was placed in a non-self-representi 11 a 

MSA stratum in the East North Central Census Division. However, the entire Fargo-Moorhead MSA is in 

the West North Central Census Division; hence, this PSU was allowed to cross State lines.

Non-Self-Representing Non-MSA Strata

The non-self-representing, rion-MSA PSU's were also grouped into strata. The strata for these PSU's in I lie 

1980 and 1984 sample designs were based heavily on the strata for the Current Population Survey, with some 

adjustments made for climate. As a result, the PSU's were grouped according to socioeconomic more than 

energy-related variables. However, the more important factor observed in devising each design was the need 

to have strata of smallest variation in aggregate measure of size for each Census division or each 'intersection: 

in the 1980 design. For example, the Monroe County, Florida PSU (The Everglades National Park and (lie 

Florida Keys) was placed in the same stratum as the PSU for Cherokee, Clay, Graham, and Swain counties 

in North Carolina (The Great Smoky Mountains National Park and surrounding areas). In the 1993 design. 

the PSU's were grouped into strata using energy-related variables, In particular, climate and main spaa; 

heating fuel where used in forming the strata.

Non-Self-Representing Mixed Strata

All RECS sample designs used some primary stage strata that contained metropolitan PSU's as well as nonmetropolitan PSU's. These strata are called mixed strata. The use of mixed strata does cause problems in Lbe

Energy Information Administration/Energy Consumption Series 

26 Sample Design for the Residential Energy Consumption Survey
weighting and variance estimation procedures. For this reason, the number of mixed strata was kept at a 

minimum.

Because of the unique climates of Hawaii and Alaska, all REGS sample designs were constructed such that 

one PSU from Alaska and one PSU from Hawaii would be selected during the primary stage. This was 

accomplished by forming a mixed stratum composed only of PSU's in Hawaii, both metropolitan and nonmetropolitan, and selecting a PSU from the stratum. Similarly, another PSU was selected from a mixed 

stratum composed only of PSU's in Alaska, both metropolitan and non-metropolitan.

In the 1980 RECS sample design, there were four additional mixed strata. These resulted from the mandate 

preventing strata boundaries from crossing any of the 17 intersections defined earlier. The four mixed strata 

were formed using (1) all PSU's in New Mexico, (2) all PSU's in Idaho, (3) all PSU's in Minnesota (with the 

exception of the Minneapolis-St Paul MSA), and (4) all MSA PSU's in North Dakota and South Dakota plus, 

some non-MSA PSU's in these two States.

Number of Strata by Type and Census DSv!s§on

The total number of strata for the RECS sample design reflects decisions made in the following areas:

 The optimization analysis

 The number of large metropolitan areas that are designated as certainty PSU's 

» The minimum number of PSU's for the Census divisions

 How well noncertainty PSU's can be grouped into strata of similar type, size, and energy 

characterization.

An additional feature of the 1993 design was the stipulation requiring, for each Census division, the use of 

an even number of strata for both the set of noncertainty metropolitan PSU's, and the set of noncertainty 

nonmetropolitan PSU's. The only exception to this was noncertainty metropolitan PSU's in the South Atlantic 

Census Division. This exception was due to budgetary restrictions.

The reason for adding this feature to the 1993 RECS sample design was to improve the variance estimation 

procedures. In particular, the variance procedure used for RECS, the Balanced Repeated Replication (BRR), 

requires the noncertainty strata to be paired and treated, for variance estimation purposes, as if the PSU's 

selected from the two strata were a sample size of two from a single large stratum.10 Using an even number 

of strata for each noncertainty type facilitates their pairing.

In the 1980,1981, and 1982 RECS, a total of 131 primary stage strata were used. Since the sample design for 

the 1984 RECS combined the 1980 and 1984 designs, it contained 153 PSU's. This breaks down to 107 PSU's 

that were used in both the 1980 and 1984 designs, 24 PSU's that were used in the 1980 design and the 1984 

data collection, but not in the 1984 design, and 22 PSU's that were used only in the 1984 design. The 1987 

and 1990 RECS each used a total of 129 strata. In the 1993 RECS, a total of 116 strata were used.

As mentioned earlier, a double strata were created in the West South Central Census Division in the 1993 

RECS primary stage design. The double strata consisted of the Fort Worth, Texas MSA; the San Antonio,

10 Kalton, G., "Practical Methods for Estimating Survey Sampling Errors," Bulletin of the International Statistical Institute: 47,3:495-524, 

1977.

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 27
Texas MSA; and the Austin, Texas MSA Two PSU's were selected from these strata. The double strata wein;; 

created in this situation for the following reasons:

 The stipulation preventing the primary stage strata from crossing Texas State boundaries

 The desire to have an even number of non-self-representing MSA strata in each Census division

 The desire to place non-self-representing MSA's into strata with MSA's of approximately the sanw: 

size ?

• The desire to use fewer strata for the 1993 RECS design than were used for the 1984 RECS design,

One alternative would have been to define the Fort Worth MSA, the San Antonio MSA, and the Austin MSA. 

each as a self-representing PSU. This would have increased the number of strata for the 1993 RECS design 

by one. Another alternative would have been to pair each of these three large MSA's with one or :mc:re 

smaller MSA's, to form non-self-representing strata; but this would run counter to the goal of forming strata 

with PSU's of roughly comparable size.

Tables 4, 5, and 6 give the number of primary stage strata by Census division and type of PSU, for the 1980, 

1984, and 1993 designs. Appendix C contains the strata listings by Census Division for the 1980, 1984 and 

1993 sample designs.

Table 4. Number of Strata for PSU's by Census Division and Type of Strata for the 1980 Design

Total

New Englar 

Middle Atla

East North 

West North

South Allan 

East South 

West South

Pacific . . .

Census S 

Division Total Repret

................ 131 3

id .............. 10

Central .......... 16

Central .......... 17

tic .............. 17

Central .......... 13 C

Central .......... 12 «

................ 13 ;

................ 19

Non-Self Representing (NSR)

1 14 IIBWOBI inn ,.,.. «-.,..'. mi III.I.MI

renting MSA Won MSA Mixed

1 53 41 6

532 0 

5 7 Z 0

357 

394 0 

2

380 0 

) 6 7 0 

> 6 '•• 0

J 3 5 2

r 6 4 2

Source: Energy Information Administration, Residential Energy Consumption Survey, "Sample Design and Methodology 1&BD 

1981 National Household Survey' (Draft Report), Response Analysis Corporation (Princeton, NJ), June 1981.

28

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
Table 5. Number of Strata for PSU's by Census Division and Type of Strata for the 1984 Design

Total . . .

New Engla 

Middle Atla

East North 

West North

South Attar 

East South 

West South

Mountain 

Pacific . .

Census 

Division Total F

................. 129

nd ............... 10

ntic .............. 15

Central ........... 17

Central ........... 17 

rtie ............... 19

Central ........... 12

Central ........... 12

................. 11

................. 16

Non-Self Representing (NSR)

Self 

Representing MSA Non-MSA

32 54 41

533 

582

395 

359

066 

586 

264

335 

663

Mixed

2

0 

0

0 

0

0 

0 

0

0 

2

Source: Energy Information Administration, "1984 Residential Energy Consumption Survey Sample Design Procedures Manual, 1 

The Orkand Corporation (Silver Spring, MD), March 1986.

Table 6. Number of Strata for PSU's by Census Division and Type of Strata for the 1993 Design

Total

New Engla 

Middle Atla

East North 

West North

South Atlar 

East South 

West South

Mountain 

Pacific . . .

Census 

Division Total Rep

................ 116

nd .............. 8

ntic ............. 13

Central .......... 17

Central .......... 9

tic .............. 20

Central .......... 8

Central .......... 14

................ 10

................ 17

Non-Self Representing

resenting MSA Non-MSA j

31 51 32

242

562

3 

324

10 4 

044 

596 

284

244 

942

(NSR)

Mixed

2

0 

0

0 

0

0 

0 

0

0 

2

Source: Energy Information Administration, 1993 Residential Energy Consumption Survey, Primary Stage Sample Design Plan" 

{Final Draft), Survey Research Center, Institute for Social Research, University of Michigan (Ann Arbor, Michigan), June 1993.

Primary Sampling Unit Selection Procedures

For each REGS sample design, a single PSU in each non-self representing stratum was selected using 

probability-proportional-to-size (PPS) sampling; a procedure used in many other surveys conducted by the 

Federal Government. In PPS sampling, each PSU was assigned a MOS. In the 1980 design, the MOS of a 

PSU was equal to 1978 PSU population estimates [CPS, Series P-26, No.783, issued February 1980], in the 

1984 design, the MOS was equal to the 1980 Census population counts, and in the 1993 design, the MOS was 

equal to the 1990 Census count of occupied housing units. Because there is a one-to-one correspondence 

between occupied housing units and households, the number of occupied housing units in a PSU is equal to 

the number of households.

However, this change from population to number of households for the MOS of a PSU in the 1993 design, 

was instituted because the elemental-sampling unit for all RECS sample designs was a housing unit and not

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 29
a person. While RECS has always used the housing unit as its elementary-sampling unit, previous designs; us,&i:l 

population as the MOS for PSU's. There is a strong relationship between the population of a PSU and I bi;: 

number of occupied housing unite in a PSU. As a result, this change has had only a minor effect.

The probability of selecting a particular PSU is proportional to its MOS, more specifically, its MOS divided 

by the MOS total for all PSU's in the stratum.

In the 1980 design, the PSU's were newly selected. Controlled selection was used to increase the assurance 

of a reasonably close match between the distribution of the sample, and actual population by State. 11

As a cost-saving feature in the 1984 design, a Keyfitz-type procedure, developed at the Bureau of file 

Census,12 was used to ensure that a large percentage of the PSU's selected for the 1980 design would ise 

carried over to the 1984 design. In fact, of the 129 PSU's selected for the 1984 design, 107 of these had been:. 

used for the 1980 design, leaving only 22 PSU's which were not used in the 1980 design. In particular, the 9 i 

non-self-representing PSU's selected for the 1984 design were chosen in such a way that 76 of these had a!.so 

been selected for the 1980 design, with 21 having been selected for the first time. Of the self-representing 

PSU's selected for the 1984 design, only one was not used in the 1980 design. The remaining self-representing 

PSU's were used in the 1980 design either as self-representing or non-self-representing PSU's. Controller. 

selection was also used in the 1984 design to ensure that the PSU's would be distributed among the Slates.

The original plans for the 1993 RECS sample design called for the selection of PSU's to be independent oi: 

the 1980 and 1984 selections. However, due to budget reductions, the plans were changed and again a Keyfil:! 

type procedure13 was used to ensure that a large proportion of the PSU's chosen for the 1984 design were: 

carried over to the 1993 design. In fact, of the 116 PSU's selected for the 1993 design, 94 of these were iiswi. 

in the 1984 design, with only 22 having been selected for the first time.

Of the 116 strata used for the 1993 design, 31 contained single self-representing PSU's, while 85 contained 

multiple PSU's. Of the 31 self-representing PSU's in this design, 27 were self-representing PSU's, and 2 were. 

non-self-representing PSU's in the 1984 design. The remaining 2 self-representing PSU's in the 1993 design 

(San Francisco and Oakland) were used in the 1984 design as a single self-representing PSU. The 85 non-self 

representing PSU's selected for the 1993 design were chosen in such a way that 63 of these had also been 

selected for the 1984 design; the other 22 non-self-representing PSU's were first time selections.

Goodman, Roe, and Kish, Leslie. "Controlled Selection: A Technique in Probability Sampling." Journal of the American Statistical 

Association Vol. 45, September 1950, pp. 350-372.

121970 Current Population Survey Redesign: Jllustration of Computation of PSU Probabilities Within a Given 1970 Stream. 

Memorandum from W.M. Perkins to 3. Waksberg, February 19,1971. The 1970 Cut-rent Population Survey Redesign: Proposed Method 

for Deriving Sample PSU Selection Probabilities Within 1970 Non-Self-Representing Strata, Memorandum from W.M. Perkins to J. Wal;s:3s::-g, 

August 5, 1970.

TCish, Leslie, and Scott, Alastair, "Retaining Units After Changing Strata and Probabilities." Journal of the American Statistical 

Association, Vol. 66, Number 335, Applications Section, September 1971.

Energy Information Administration/Energy Consumption Series 

30 Sample Design for the Residential Energy Consumption Survey
Summary of

For each RECS design, Table 7 summarizes the universe, the number of PSU's, the MOS used in selecting 

the PSU's, and the basis for the MSA definitions.

Table 7, Comparison of RECS Sample Designs at the PSU

Survey Design 

Year Universe Number of Strata

Measure-of-Si»

for PSU's

Definition of

NIECS (1978) and 48 contiguous States 103 1970 Census 197G Census 

Screener (1979) and District of Columbia definitions

1980

1984

50 States and District of 

Columbia

50 State* and District of 

Columbia

1993 50 States and District of 

Columbia

131

129 total

107 retained from 

1980 RECS Design

22 selected for the 

first time for 1984 

design

116 total

94 retained from 

1984 design

22 selected for the 

first time for 1993 

design

1978 population 

estimates from 

the Bureau of the

Census

Population: 1S80 

Census

1980 definitions

June 1983 

definitions

Number of 

households: 1990 

Census

June 1990 

definitions

Sources: Energy Information Administration, Residential Energy Consumption Survey, "Sample Design and Methodology 1980 - 

1981 National Household Survey" {Draft Report), Response Analysis Corporation (Princeton, NJ), June 1981, The National Interim 

Energy Consumption Survey, Part !: Methodology on Household and Utility Company Surveya, Response Analysis Corporation 

(Princeton, NJ), June 30,1981. The 1984 Residential Energy Consumption Survey Sample Design Procedures Manual, Orkand 

Corporation (Silver Spring, MD), March 1986. The 1993 Residential Energy Consumption Survey, Primary Stage Sample Design 

Plan* (Final Draft), Survey Research Center, Institute for Social Research, University of Michigan (Ann Arbor, Michigan), June 1993.

Energy Information Administration/Energy Consumption 

Sample Design for the Residential Energy Consumption Survey 31
6. Secondary of the

This chapter discusses the secondary stage of the RECS sample In this stage, each PSU that was 

selected during the primary stage is divided into SSU's, a of SSU's is from the PSU's, the 

selected SSU's are divided into listing segments, and a segment is from each SSU. As 

part of the secondary stage the following decisions are made:

 How to integrate the new construction supplement the secondary

 The number of SSU's

 Which criteria are to be used to form the SSU's

 How to select the SSU's? 

Each of these decisions will be discussed in detail in the

The 1993 RECS sample design includes a supplemental sample of SSU's that contain a high proportion of new 

housing units. For sampling purposes, a new housing unit is defined as units that were first occupied within 

6 years of the data collection period. From the start of construction to occupancy is typically 6 to 9 months; 

hence, for the 1993 REGS, housing units will be defined as if construction began on or after 

January 1, 1987. Because respondents may report the date the housing units was first occupied instead 

of the date construction began, new housing units should closely correspond to those where the respondent 

classified the units as being constructed during the January to December 1993 period. The object of 

including a new construction supplement in the 1993 RECS is to the number of 

interviews for new housing units.

For the 1990 RECS, new housing units were defined as those where the respondent reported that the 

housing units were constructed during the January 1985 to December 1990 period. Because the sampling was 

finalized during the summer of 1990 and most interviews were conducted during the fall of 1990, the units that 

were first occupied during the latter part of 1990 would be underrepresented in the 1990 RECS.

The 1990 RECS revealed that there were approximately 400 new housing units in its sample of 5,095 housing 

units. The 1993 core sample of 5,000 housing units is also expected to have approximately 400 new housing 

units. The new construction supplement is designed to increase the sample of new housing units to 

approximately 1,200 units.

This supplement will address new construction that is interspersed throughout existing residential areas, as 

well as very recent, large-scale construction projects (i.e., subdivisions, apartment complexes, mobile home 

parks, etc.). The approach EIA has taken is one that combines an oversampling of new housing units in the 

core 1993 SSU's, with a supplemental sampling of SSU's from geographic areas showing a high density of new 

housing units.

Based on experience with the 1990 RECS, the core sample of 1,460 SSU's is expected to include about 200 

SSU's that are located in areas with a high density of new housing units. The supplemental sample of 150 new 

construction SSU's will bring the total number of 1993 SSU's having significant new construction to about 350.

Energy information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 33
To reduce SSU listing costs, El A used existing SSU listings in 30 of the 116 PSU's. In addition, the complex;: 

sample of 1,610 new SSU selections would not be fully implemented until just prior to the 1996 data 

collection. Consequently, a total of 149 supplemental new construction SSU selections were listed for the 1993 

sample. Of this total, 105 were supplemental new housing unit selections from PSU's where all SSU's, core 

and new construction, were newly listed. The remaining 44 SSU's were selected from 30 PSU's where existing 

SSU listings were used. The complete 1993 RECS sample includes 348 SSU's from areas with a high deiisi.1:v 

of new housing units.

Number of Secondary Sampling Units

The total number of PSU's and SSU's is determined by an optimization analysis, by budget constraints, and 

by other factors; determinations are usually made prior to a major revision in the sample design. Also, these 

decisions on the number of PSU's, the average number of SSU's per PSU, and the average number of housinfi 

units in an ultimate cluster, usually occur simultaneously.

While the total number of SSU's used in the RECS sample design has remained relatively constant, the: 

number of SSU's assigned to some Census divisions has changed. Table 8 is divided into two parts (a ar.d b), 

which lists, by each Census division, the population, the number of SSU's, and the average population per 

SSU. These data are given for the 1980,1984, and 1993 designs. For the 1993 design, Table 8 also lists ite 

number of households, and the average number of households per SSU for each Census division.

While Table 3 deals with PSU's and Table 8 deals with SSU's, they show similar trends. For example, the 1993 

sample design resulted in fewer PSU's and SSU's in the West North Central Census Division. Also, the 

differences in the average population per SSU between the nine Census divisions, are smaller in the 1993 

sample design than in earlier designs.

The average number of SSU's per PSU has remained relatively constant from the 1980 sample design through 

the 1984 and 1993 sample designs; this especially applies to those SSU's in the core sample. Table 9 lists the 

number of core SSU's, the number of PSU's, and the average number of core SSU's per PSU by Census; 

division, for each major revision of the RECS sample design.

Once the number of SSU's for a Census division has been determined, they are assigned to PSU's in a manner 

that is approximately proportionate to the MOS for the corresponding stratum. For example, if Stratum A 

contains 12 percent of the households in the Census division, then approximately 12 percent of the SSU's 

assigned to that Census division are assigned to the PSU that is selected from Stratum A In the 1993 design, 

the number of SSU's for each stratum was rounded to an even number to make variance calculations easier,

Energy Information Administration/Energy Consumption Series 

34 Sarnplo Design for the Residential Energy Consumption Survey
Table 8a. Number of Secondary Sampling Units and Population by Census Division for 1980,1984, 

and 1993 RECS Sample Designs

Census 

Division

Number of Secondary 

Sampling Unite

1980 

Design*

1984 

Design

1993 

Design8

Population 

{millions}

1980 

Estimates

1980 

Census

1930 

Census

218.1 226.5 248.7

New England .........

Middle Atlantic ........

East North Central .....

West North Central .....

South Atlantic .........

East South Central .....

West South Central .....

Mountain ............

Pacific ..............

. . . . . 128

. . . . . 191

. . . . . 195

. . . . . 172

. . . . . 178

. . . . . 128

. . . . . 128

. . . . . 153

..... 242

122

202

202

202

202

122

122

122

220

116

202

202

118

204

118

152

126

222

12.3

36.8

41.2

17.0

34.6

14.0

22.0

10.3

29.8

12.3

36.8

41.7

17.2

37.0

14.7

23.7

11.4

31.8

13.2

37.6

42.0

17.7

43.6

15.2

26.7

13.7

39.2

Table 8b. Average Population per Secondary Sampling Units and Number of Households by Census 

Division for 1980,1984, and 1993 RECS Sample Designs

Census 

Division

Average Population per 

Secondary Sampling Unit 

(millions)

1980 

Design8

1984 

Design

1993 

Design"

Number of Households for 1 993 

Design8 (1 990 Census Data) 

(millions)

Total

Average 

per SSU

Total 0.17 91.9

New England .........

Middle Atlantic ........

East North Central .....

West North Central ,

South Atlantic .........

East South Central .....

West South Central

Mountain ............

Pacific ..............

0.10

0.19

0.21

0.10

0.19

0.11

0.17

0.07

0.12

0.10

0.18

0.21

0.09

0,18

0.12

0.19

0.09

0.14

0.11

0.19

0.21

0.15

0.21

0.13

0.18

0.11

0.18

4.9

13.9

15.6

6.7

16.5

5.7

9.7

5.0

13.9

0.043

0.069

0.077

0.057

0.081

0.047

0.064

0.040

0.063

aCore sample only.

Sources: "Energy Information Administration, Residential Energy Consumption Survey, Sample Design and Methodology 1980 - 

1981 National Household Survey (Draft Report), Response Analysis Corporation (Princeton, NJ), June 1981. » The 1993 Residential 

Energy Consumption survey, Second Stage Sample Design Plan (Final Draft), Survey Research Center, Institute for Social Research, 

University of Michigan (Ann Arbor, Michigan), June 1993.

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 35
Table 9. Number of Secondary Sampling Units, Primary Sampling Units, and SSU's per PSU by 

Census Division for 1980, 1984, and 1993 RECS Sample Designs

Census 

Division

Number of Secondary

Sampling Units

1980 1984 

Design9 Design

1993 

Design9

Number of Primary 

Sampling Unite

1980 

Design

1984 

Design

1i 993

Design

Number of Secondary 

Sampling Units 

per Primary Sampling llnil

1980 

Design"

1984 

Design

1 9H3 

Design"

131

Middle Atlantic ......

East North Central . . . West North Central . . .

South Atlantic .......

East South Central . . . West South Central . . .

128

191

195 

172

178

128 

128

153

242

122

202

202 

202

202

122 

122

122

220

116

202

202 

118

204

118 

152

126

?y>

10

14

16 

17

17

13 

12

13

19

10

15

17 

17

19

12 

12

11

16

8

13

17 

8

5>C

8 

14

10

IS

12.8

13.6

12.2 

10.1

10.5

9.8

10.7

11.8

12.7

12.2

13.5

11.9 

11.9

10.6

10.2 

10.2

11.1

13.8

1 4 5

1 '•• i;

 1 1 !!

IS. 1

 1C'.}!

H7 

ICO

1R:fi

a Core sample only.

Sources: »Energy Information Administration, Residential Energy Consumption Survey, Sample Design and Methodology 1SSO - 

1S81 National Household Survey (Draft Report), Response Analysis Corporation (Princeton, NJ), June 1981. The 1984 Residential 

Energy Consumption Survey Sample Design Procedures Manual, The Orkand Corporation (Silver Spring, MD), March 1986. <> The 

1993 Residential Energy Consumption Survey, Primary Stage Sample Design Plan (Final Draft), Survey Research Center, Institute! 

for Social Research, University of Michigan (Ann Arbor, Michigan), June 1993. The 1993 Residential Energy Consumption Survey, 

Second Stage Sample Design Plan (Final Draft), Survey Research Center, Institute for Social Research, University of Michigan (Ann 

Arbor), Michigan, June 1993.

Criteria for Forming Secondary Sampling Units

For each RECS design, the SSU's are well-defined geographic areas whose boundaries correspond to i:ht: 

boundaries of small geographic units that were defined by the Bureau of the Census. The 1980 and 19S4 

sample designs used Census tracts, enumeration districts, individual blocks and block groups. In the 1993 

RECS sample design, the SSU's are usually Census blocks or a set of contiguous Census blocks. A Census 

block is "An area bounded on all sides by visible features such as streets, roads, streams, and railroad tracks;. 

and occasionally by nonvisible boundaries such as city, town, or county limits, property lines, and shcal 

imaginary extensions of streets. Blocks do not cross Census tract or block numbering area boundaries. A. 

block is the smallest geographic tabulation area from the 1990 Census."1"

There are several major advantages for using Census units to define SSU's:

 Census data can be used to define a MOS for the SSU's

 Small area Census units exist for the entire country

 Census unit boundaries are well-defined and easy to locate

14 U.S. Department of Commerce. Bureau of the Census, 1990 Census of Population and Housing Tabulation and Publication Proff-ai? 

July 1989, p. 49.

36

Energy Information Administration/Energy Consumption Series 

Sample Design lor the Residential Energy Consumption Survey
 Maps of the Census units can be obtained from the Bureau of the Census, or created, using the 

Topologically Integrated Geographic Encoding and Referencing (TIGER) System data files obtained 

from the Bureau of the Census.

For the first time in the 199) Census, the Bureau of the Census defined blocks for the entire country. In the 

1980 Census, the smallest Census unit in many sparsely populated parts of the country was an enumeration 

district. (Census tracts and blocks were not defined for sparsely populated rural areas.) Consequently, some 

rural SSU's were enumeration districts in the 1980 and 1984 sample designs.

Number of Housing Units In SSU's

The target number of households in a SSU was different for the 1993 RECS design than for the 1980 and 1984 

RECS designs. For the 1993 RECS, the core SSU's were defined so that their projected minimum number 

of housing units was 50, and the New Construction Supplement SSU's were defined so that their projected 

minimum number of housing units was 96. For the 1980 and 1984 RECS sample designs, the SSU's were 

defined so that the target number of housing units was 400.

The 1980 and 1984 RECS used the larger minimum number of housing units in a SSU, in order to facilitate 

the new construction update procedures used in RECS cycles between major redesign efforts. For the 19% 

and subsequent RECS, the new construction update procedures will cover not only the selected SSU's, but 

may also cover neighboring SSU's.

The smaller size of the 1993 RECS sample design was used to reduce the number of SSU's in which roughcounting procedures, segment formulation procedures, and segment selection procedures were necessary. In 

fact, for the majority of the SSU's selected in the 1993 design, these three sets of procedures were not 

necessary. Consequently, the majority of the SSU's in this design were equal to their listing segment.

Secondary Sampling Unit Selection Procedures

The following steps summarize the procedures used in selecting the SSU's: 

« Assigning a MOS to the SSU's

 Stratify or order the SSU's prior to selection

 Randomly selecting the SSU's.

MOS for SSU's

During the secondary stage, the SSU's are selected using probability-proportionate-to-size sampling (PPS). 

In order to use PPS sampling, each SSU is assigned a MOS. The MOS used for the NIECS and Screener was 

the 1970 Census population of the SSU. Since the 1980 Census data were not available, the MOS used for 

the 1980 RECS sample design was the estimated number of households per SSU. These estimates were 

derived by combining information from a number of sources: The 1970 Census results, National Planning 

Data Corporation, Reuben H. Donnelly Company's marketing data on the number of households, and contacts 

with local officials.

The SSU's in the core sample for the 1980 design, along with their selection probabilities, were also used for 

the 1981 and 1982 RECS. Similarly, those SSU's that were carried over from the 1980 design to the 1984 

design also carried over with them their original selection probabilities. This differs from the Keyfitz

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 37
procedure used for selecting PSU's; a procedure which usually altered selection probabilities even when 

original PSU's were reselected. In those PSU's that were retained, the SSU stage, including its probability D 

selection, was frequently carried over intact from the earlier design. In those PSU's that were either altered 

to reflect changes in their definition, or were affected when the SSU structure was totally revised, the MOS 

used to select the SSU was based on the 1980 Census. In the 1993 RECS redesign effort, the 1990 Cens --K 

number of housing units was used to obtain the MOS for SSU's.

SSU Stratification or Ordering Procedures

In all three designs, the SSU's were ordered or stratified prior to selection. The 1980 and 1984 designs used 

the intermediate step of selecting a Minor Civil Division as an mechanism for guaranteeing that SSU's are: 

distributed across the PSU's. The 1993 RECS design also stratified the SSU's prior to selection. In non-MSA 

PSU's, the SSU's were stratified by geographic location. In MSA PSU's. the SSU's were first stratified bv 

predicted energy expenditures, and within these strata, by geographic location. The SSU's for non-MSA PSU's 

were not stratified by predicted energy expenditures, because in most of these areas there is too little housing 

unit clustering, by variables related to energy expenditures, to justify these procedures.

SSU Selection Procedure!! for the 1980 and 1984 RECS Sample Designs

The SSU's for the 1980 and 1984 designs were selected in a two-step procedure:

1. Minor Civil Divisions (MCD) such as cities, towns, and other Census units were selected from each 

RECS PSU

2. Secondary-Sampling Units (SSU's), which are Census tracts, block groups, and enumeration districts, 

were selected from each MCD chosen in the first step. Usually only one SSU was selected, but in some: 

cases multiple SSU's were selected. The SSU's were selected using PPS sampling, in which Census, 

counts or estimates of the number of households were used as a MOS.

The MCD's were selected by using a systematic sample, and were intended to stratify the SSU's into categories 

reflecting the size and characteristics of the MCD, For each PSU, this v/as accomplished in the followinji 

manner:

« Calculating the sum of the MOS for all MCD's in the PSU. (For notational purposes, denote the suin 

as £ MOS.)

« Setting the PSU "zone" interval equal to £ MOS, divided by the number of SSU's to be selected from 

the PSU. (For notational purposes, denote the "zone" interval as W.)

« Ordering the MCD's; first order the MCD by type, then by size (MOS) or by geographic location

 Using the ordered MCD's and their MOS to create "paper" rones for the PSU. Each "paper" zone; 

contains W households. The first zone extended from the "first" household in the PSU to the W-tla 

household. The second zone extended from household W + 1 to household 2W. Any MCD might 

lie entirely in a single zone, overlap a "paper" zone boundary and be partly included in two zones, e>: 

extend through all or part of three or more zones

« For each zone, select a random number between 1 and W. For zone i denote the random number si: 

K,. The MCD corresponding to the Kj-th household in the i-th zone is thereby selected.

Energy Information Administration/Energy Consumption Series 

38 Sample Design for tha Residential Energy Consumption Survey
The definitions for types of MCD's, and the procedures for ordering the MCD's within type classes, are given 

below:

 The MCD's for central cities are first. Within this group, MCD's are ordered by their MOS (largest 

to smallest)

» Other MCD's in urbanized areas follow. Within this group MCD's are ordered by geographic location

 Those MCD's, the majority of whose population lies in urban areas, form the next class. Within this 

group, the MCD's are ordered by their MOS (largest to smallest)

 All other MCD's follow. These MCD's are ordered by geographic location. 

This ordering also guarantees that those selected represent the different types of MCD's.

Any MCD that is placed in two or more "paper" zones could be selected from each zone. This is most likely 

to happen to MCD's that have a large MOS, in particular, to MCD's that are central cities in MSA's.

SSU Selection Procedures for the 1993 REGS Sample Design

Beginning with the 1993 RECS sample design, a substantial change was made in the SSU selection procedures. 

A decision was made to stratify and/or order the SSU's according to their energy-related characteristics and 

geographic location. (The 1980 and 1984 designs used urban/rural status as well as geographic location.) Using 

predicted energy expenditures to stratify the SSU's prior to selection will increase the precision of energy 

expenditure estimates, as well other energy-related estimates.

Within the PSU's selected for MSA strata (including certainty PSU's), the SSU's are first stratified by 

predicted energy expenditures. Within the strata determined by predicted energy expenditures, the SSU's are 

ordered geographically by county, Census tract, or block group. Within the PSU's selected for non-MSA 

strata, the SSU's are ordered geographically, as they are not first stratified by energy-related characteristics.

Respondents' estimates of energy expenditures were collected in the 1990 Census long form, but this 

information was not used to stratify the SSU's. The Census energy expenditure data only covered expenses 

incurred by the household; it did not take into account expenses that were included in the rent. In order to 

make full use of the Census data on expenditures, it would be necessary to estimate the energy expenditures 

in those households where utilities are included as part of the rent. An additional problem arises in cases 

where the rent includes only part of the utilities. It would be difficult to accurately detect these cases using 

Census data, or to calculate the energy expenditures included in the rent. Finally, Census expenditure data 

are known to be upwardly biased.

The predicted energy expenditures were determined by an equation that was developed using data from the 

1990 RECS. The independent variables used in the equation were available from both the 1990 RECS data 

base and the 1990 Census. Census data was used to determine the values for the predictor variables. This 

equation was applied at the Census tract level and, consequently, all SSU's (usually blocks) in the same tract 

were placed in the same stratum, having the same predicted average energy expenditures.

The energy expenditures model used the following four variables:

AVEHI = Average Household Income for Households in the Census Tract (in thousands of dollars) 

AVENHM = Average Number of Household Members for Households in the Census Tract

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 39
PSFDHU = Proportion of Single-Family Detached, Housing Units among all Housing Units in 1 i:w 

Census Trad.

AVENR = Average Number of Rooms for Occupied Housing Units in the Census Tract.

A regression procedure was used to develop the following equation, which predicts a log of the energy 

expenditures (LNEXP) based cm the above four variables:

LNEXP = 6.1384 + (.09179 x AVENR)

+ (.06765 x AVENHM) 

+ (.00678 x PSFDHU)' 

+ (.00485 x AVEHI)

This equation was used to predict the average energy expenditures for each Census tract in the MSA-PSU":; 

selected for the 1993 REGS redesign effort. The predicted energy expenditures that resulted were used tc 

divide the SSU's into strata. These strata correspond to the upper, middle, and lower third percentiles Ib 

energy expenditures in each Census division.

The low-expenditure stratum contained those SSU's in Census tracts where the regression estimate of the 

average predicted energy expenditures for households fell below the 33.33rd percentile. The middle-expend! tw« 

stratum contained those SSU's in Census tracts where the estimate fell between the 33.33rd and 66.67ti 

percentiles. The high-expenditure stratum contained those SSU's in Census tracts where the estimate let 

above the 66.67th percentile.

Within the low, middle, and high-expenditure strata, the SSU's were ordered by geographic characteristics 

(county, tract, and block group). This ordering is used in the same way that stratification is used to distribute 

the selected SSU's geographically.

The geographic ordering of SSU's occurs first by county, within counties they are ordered by tract, and finally 

within tracts they are ordered by block. For MSA PSU's, the counties are ordered from the center of the MSA 

to the peripheries, keeping adjacent counties together. Most non-MSA. PSU's consist of a single count/, or 

very few counties. Hence, the ordering for non-MSA PSU's may be purely arbitrary. The tract and bloc'-t; 

numbering systems assigned by the Bureau of the Census orders the tracts geographically within a count/, an: 

orders the blocks geographically within the tracts.

A systematic selection procedure (similar to the procedures used to select SSU's for the 1980 design) ij; usei: 

to select the SSU's in the non-MSA PSU's and in each energy expenditure stratum in the MSA PSU's. (i 

particular, the total MOS for each PSU or stratum is calculated (denote the total MOS by EMOS), the 'zone 1 ' 

interval is calculated (denote the "zone" interval by W), and a random start is chosen. The total MOS is ar 

estimate of the total number of households in the PSU or stratum, W equals EMOS divided by the num'ber 

of SSU's that are to be selected from the PSU or stratum. Assume that for each SSU we have a list a: 

households, these lists are combined, to form a list for the PSU or stratum using the ordering of the SSU':;, 

The PSU or stratum is divided into paper "zones" where the first "zone" contains the first W households; i.::i 

the list, the second "zone" contains the second W households in the list and, so forth. If K is the random star 1 :, 

then the SSU corresponding to the K-th household in each "zone" is selected. (For the 1980 design, a sepaiaii: 

random value (Kj) was selected for each "zone." This was a minor change, which made processing easier,)

Additional Details of Secondary Stage for Each RECS

The 1980 RECS sample design used a total of 1,667 SSU's. 1,515 SSU':; were in the core sample, and. 1J 

SSU's were selected to be used in a reliability study. Initial planning called for the housing units selected fxo;

Energy Information Administration/Energy Consumption Series 

40 Sample Design for the Residential Energy Consumption Survey
these 152 SSU's to be interviewed twice for the 1980 RECS. This would have enabled EIA to analyze the 

reliability of the data collected for RECS. However, the plans for the second interview were eliminated for 

budgetary reasons. These 152 SSU's were used only for the 1980 RECS.

The sample design for the secondary stage to the 1981 RECS was the same as the sample design for the 1980 

RECS, except that 152 SSU's originally incorporated into the 1980 RECS design for use in a reliability study, 

which were eliminated.

The secondary stage for the 1982 RECS was the same as that for the 1981 RECS.

As a result of the overlap in PSU's for the 1980 design and the 1984 RECS design, 1,249 of the 1,516 SSU's 

selected for the 1980 design were also used for the 1984 design. The SSU's in those PSU's that were selected 

for the first time in the 1984 sample design, were newly developed. However, these SSU's were not necessarily 

used in the 1984 RECS. Because a longitudinal design was incorporated in the RECS design (see Chapter 

7), the SSU's assigned to the returning panel were not used until the 1987 RECS. The returning panel used 

SSU's from the 1982 RECS, even when those SSU's were in PSU's that were eliminated from the 1984 RECS 

design.

The secondary stage developed during the 1984 RECS design effort was used in its entirety for the first time 

in the 1987 RECS.

The secondary stage for the 1990 RECS is the same as that used for the 1987 RECS.

In some PSU's that were used in both the 1984 and the 1993 designs, the corresponding SSU's that were 

selected for the 1984 design were also used in the 1993 RECS. This was done for economic and expediential 

reasons. In fact, of the 1,460 SSU's in the core sample for the 1993 design, 281 were first selected for the 1980 

design, 78 were first selected for the 1984 design, and 1,101 SSU's were initially selected for the 1993 design.

The SSU's that were selected during the 1993 design effort will be used for the 1996 RECS. All of the SSU's 

that were selected for the 1984 design will be eliminated.

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 41
Summary of Secondary Stag 

Table 10 lists the number of SSU's and the MOS for the SSU's. 

Table 10. Comparison of REGS Sample Designs at the SSU Level

Survey

NIECS (1978) and 

Screener (1979)

Number of SSU'a

456

Number of SSU's 

per PSU

4.4

Mea»ure-of-Slze for SSLl'o

1970 Census population for 400 SS 

and amount of new 

construction for 56 SSU's

1980 REGS Sample 

Design

1,667 total: 

1,515 SSU's in core sample

152 SSU':} in supplemental 

sample solected for 

reliability study

Total sample: 12.7 

Core sample: 11.3

Estimated number of households ir Ifa 

Derived from a combination of 197(9 

Census data, National Planning Corp;:r;i 

lion estimates, and other sources.

1984 REGS Sample 

Design

1,516 total:

1,249 retained from 1980 

design core sample

267 selected for the first 

time for 1984 Design

11.8

1984 SSU's retained from the 1'ffiO 

sample: estimated number of houssin 1980 (same MOS used in 19JIO)

SSU's selected for the first in 

estimated number of households in 1 ?B4 

Derived from a combination of 1 980 

Census data, National Planning Dale 

Corporation estimates, and other so-ur ::;'!;

1993 RECS Sample

Design

1,610 Total: 

1,460 for core sample

150 for New Construction 

Supplement

Total sample:! 3.8 

Core sample: 12.5

Number of housing units from 1930 

Census

Sources: »Energy Information Administration, Residential Energy Consumption Survey, Sample Design and Methodology 1980-

1981 National Household Survey (Draft Report), Response Analysis Corporation (Princeton, NJ), June 1981. »The National Interin

Energy Consumption Survey, Part I: Methodology on Household and Utility Company Surveys, Response Analysis Corporation

(Princeton, NJ), June 30, 1981. » The 1993 Residential Energy Consumption survey, Second Stage Sample Design Plan (Final Draff:],

Survey Research Center, Institute for Social Research, University of Michigan (Ann Arbor Michigan), June 1993.

42

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
7» Elementary-Unit

During the elementary-unit stage of the RECS sample design, field workers compile lists of all housing units 

in the listing segments selected during the secondary stage. From these lists, a penultimate cluster of housing 

units is selected for each listing segment, and the ultimate cluster is selected from the penultimate cluster.

When an SSU is selected for the first time, the elementary-unit stage must be developed from the beginning. 

This includes the field-listing procedures, the penultimate cluster selection procedures, and the interviewer 

assignment procedures. For RECS cycles between major revisions, the elementary-unit stage may or may not 

be redeveloped, and in fact, with the majority of SSU's, it is not. Instead, the listing of housing units in the 

penultimate cluster is updated to account for new construction, demolitions, and other changes in the housing 

stock. If properly implemented, these new construction update procedures should hot produce biased results, 

but rather, may yield a high variance for new home statistics. In addition, the provision of a longitudinal panel 

ensures that the ultimate clusters from one-half of the SSU's will be carried over from one RECS to the next. 

In the 1980 through 1990 RECS, these new construction update procedures were coordinated with the design 

of the longitudinal panel in order to keep the sample current, as well as to maintain continuity between RECS 

cycles.

The 1993 RECS included a new construction supplement, the effect of which, was to sample recently built 

housing units at a higher rate than older housing units. The sample design for this supplement involved both 

the secondary stage and the elementary-unit stage.

The elementary-unit stage is also designed to accommodate a low-income oversample, as well as to handle the 

existence of additional housing units discovered during the interviews.

Basic Elementary-Unit Stage

The following decisions are made at the elementary-unit stage:

 The instructions to the field workers for the field-listing procedures

 The maximum size for penultimate clusters

« How to select the penultimate clusters from the housing units found during the field-listing procedures

 The number of housing units to select from each penultimate cluster to form the ultimate clusters

 How to sample the housing units from the penultimate clusters for the ultimate clusters

« How to handle housing units in the penultimate clusters that were not listed during the field-listing 

procedures.

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 43
Instructions for Field Workers (Definition of Housing

The field workers are provided a map of the listing segment and are instructed to list all housing units fh& 

discover. These instructions define a housing unit15 as follows:

A house, an apartment, a group of rooms, or a single room if it is 

either occupied, or intended for occupancy, as separate living quarters 

by a family, an individual, or a group up to nine unrelated persons. 

Separate living quarters means the occupant(s): (1) live and eat 

separately from other persons in the house or apartment and (2) have 

direct access from the outside of the building or through a common 

hall -- that is, entry or exit can be made without entering someone 

else's living quarters. Housing units do not include group quarters 

such as prisons or nursing homes where ten or more unrelated persons 

live. A common, dining area used by residents is an indication of 

group quarters. Hotel and motel rooms are considered housing units 

if occupied as the usual or permanent place of residence.

Appendix B contains the detailed instructions given to field workers to help them determine what constitute!: 

a housing unit.

Maximum Size of Penultimate Clusters

The SSU's are typically larger in size than is desired for the penultimate clusters. The larger size of the SSU": 

makes the new construction update procedures used between major design years more effective, but using tin 

full SSU adds costs in other areas. However, since the penultimate clusters are subsets of the SSU's, their me. 

for example, in computerizing and later rechecking the housing lists, reduce costs.

In the 1984 design, the maximum size for a penultimate cluster was 25 housing units. For the 1993 design 1M;: 

was increased to 50 housing units for the core SSU's, and 96 units for the new construction supplement o

SSU's.

Selection of Penultimate Clusters

The penultimate clusters represent a compact geographic area within the SSU's, which are defined by the 

addresses of the housing units they contain. This means that a set of 25,50, or 96 consecutive addresses define 

a compact geographic area or penultimate cluster. The penultimate clusters are established by selecting a, 

single housing unit from the complete list of SSU housing units, and then defining this cluster as the next 25, 

50, or 96 housing units which follow the single unit selected. The housing unit list is created in a circular 

manner. This refers to the process of returning to the beginning of the list, when its end is reached, in order 

to obtain the remaining units for the penultimate cluster.

Number of Observation*, in an Ultimate Cluster

The approximate number of housing units per ultimate cluster has consistently been close to four or five a: i' 

each RECS. This corresponds to the results of the optimization analysis, which has called for a smaller 

number of observations in the ultimate clusters. The divergence between the actual number used aid the.

This definition is taken from the 1993 RECS instructions for Interviewers' Manual Glossary, p. 8.

Energy Information Administration/Energy Consumption Series 

44 Sample Design for the Residential Energy Consumption Survey
number specified by the optimization analysis is discussed in Chapter 4. The average number of observations 

in the ultimate clusters for each cycle of RECS, is increased or decreased to reflect the target number of 

completed observations.

Selection of Housing Units for the Ultimate Clusters

The housing units in the ultimate clusters are selected from those in the penultimate clusters using simple 

random sampling without replacement. In the 1980 through 1990 RECS, the housing units in the penultimate 

clusters were not divided into strata prior to the selection of the ultimate clusters. Consequently, within 

SSU's, the selection probabilities were not dependent on housing-unit characteristics, but did vary between 

SSU's according to the number of available housing units in the penultimate cluster, and the target number 

of housing units in the ultimate cluster. This target number was higher when the SSU's were designated as 

part of a low-income oversample. In the 1993 RECS, the housing units in the penultimate clusters were 

divided into two strata using the estimated age of the housing units prior to the selection of the ultimate 

clusters. The housing units in the stratum composed of units judged by the field workers to be newly 

constructed were sampled at a higher rate than those in the stratum composed of older units.

The number of housing units in the penultimate cluster that are available for selection to the ultimate cluster, 

varies according to the status of the corresponding SSU and listing segment. If the listing segment is to be 

used for the first time, all housing units in the penultimate cluster are available. If the SSU is part of the 

longitudinal panel (see discussion below), the available housing units are from an ultimate cluster chosen in 

a previous RECS. (An ultimate cluster used in a longitudinal panel is generally the equivalent of one used in 

a previous RECS.) If a SSU (or listing segment) is designated as part of the incoming panel, only those 

housing units in the penultimate cluster that have not been selected for a previous RECS are available.

In previous RECS cycles, there have been listing segments where the target size of an ultimate cluster exceeds 

the number of available housing units. This has occurred in two situations. In the first situation, when a SSU 

is part of the incoming panel (see below), and its corresponding penultimate cluster has been used in several 

previous RECS samples, it is possible that previous RECS cycles have used up almost all of the housing units 

in the penultimate cluster. In this case, those housing units that have not been used earlier are placed in the 

ultimate cluster, and the remaining housing units needed to complete the ultimate cluster are selected from 

those used in previous surveys.

A second situation occurs when a SSU is part of a longitudinal panel, and the target number of housing units 

for the ultimate cluster exceeds the number used earlier when the SSU was part of the incoming panel. In 

this case, the additional housing units needed for the ultimate cluster are selected from those in the 

penultimate cluster, which have not been used in a previous RECS.

Treatment of Housing Units Discovered During the Interviews

Even with the use of field workers, the list of housing units in the listing segments is incomplete. Some 

housing units are missed. Many missed units are separate living quarters within structures that contain other 

housing units (e.g., a basement apartment rented to an unrelated individual), or houses that are hidden from 

view.

Housing units that are missed during the listing phase are sometimes discovered during the RECS interviews. 

If a housing unit is discovered during these interviews, there are rules to follow for determining if it should 

be included in the ultimate cluster. For example, if a housing unit that is selected for the ultimate cluster 

happens to be two units, then both units are included. Also, if an unlisted single-family home is found and 

its listing would immediately follow a housing unit in the ultimate cluster, it too is added to the ultimate 

cluster. On the other hand, if the unlisted home follows a housing unit that is not in the ultimate cluster, then

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 45
this home is not added to the ultimate cluster. Additional rules handle more complicated situations, sucti M 

cases where a set of four or more units have been left off the housing-unit list.

Longitudinal and Incoming Panels

The provision for a longitudinal panel was incorporated into the sample design for the 1980 RECS. k 

particular, the 1980 RECS sample design divided the SSU's selected during the secondary stage into four 

panels. Each of the four panels could be used as a national sample by itself. This feature was incorporated 

into the RECS sample design for the following reasons:

 The RECS could be fielded every 6 months, by interviewing a sample of housing units from two of ttw; 

panels

 With the 6-month rotation, each housing unit would be interviewed twice. The original plans calksd 

for each 6-month cycle of RECS to consist of two panels: one panel where the housing units are 

interviewed for the first time, and another panel in which the housing units were interviewed 2 yean 

earlier.

The RECS was never fielded even/ 6 months. Therefore, the 1980 RECS included all four panels and all of 

the housing units were interviewed for the first time. This was repeated in the 1981 RECS. Beginning wit:Jn. 

the 1982 RECS, the panels were divided into incoming panels and longitudinal panels. The housing units ji 

the incoming panel were selected for the first time, while the housing units i;i the longitudinal panel had either 

been selected for the 1980 RECS, or added to the sample as part of the new construction update. Hence, 

slightly less than one-half of the housing units for the 1982 RECS had also been selected for the 1980 RECS. 

This longitudinal rotation of the sample was made a part of the 1984, 1987, and the 1990 RECS.

In the 1984 RECS, it was necessary to use the longitudinal panel from the 1980 design. The incoming pane);. 

however, was developed in the 1984 design. This complication added higher costs to the 1984 RECS became 

it meant working in both new arid old PSU's.

The 1993 RECS did not include a longitudinal panel. One reason for its elimination was to avoid the extra 

costs like those incurred in the 1984 RECS.

In the 1982 RECS, the longitudinal panel included housing units that were selected for the 1980 RECS, In 

the 1984,1987 and 1990 RECS, the longitudinal panel included housing units that were initially chosen ra tine. 

previous RECS (i.e., in the 1982, 1984, and 1987 RECS, respectively).

The primary objective of the longitudinal rotation plan (or longitudinal sample design), was to provide a 

subsample where changes occurring in the same group of housing units during the period between two RECS 

data-collection cycles could be analyzed. The period was 2 years for the 1982 and 1984 RECS and 3 years for 

the 1987 and 1990 RECS. This objective was accomplished using rotation groups. Systematic random 

procedures were used to divide the total set of SSU's into four subsamples, designated in Table 11 as C, I). 

E, and F.

Energy information Administration/Energy Consumption Series 

46 Sample Design for the Residential Energy Consumption Survey
Table 11. Overview of Longitudinal Sample Design for the 1982, 1984,1987, and 1990 REGS

Rotation Group 1982 1984 1987 1990

c

D

E

F

R

R

S

N

sa

Na

Rb

Rb

R

R

Na

Sa

N

S

R

R

a PSU's selected during the primary stage for the 1984 redesign were used for the first time. 

b PSU's selected during the primary stage for the initial 1980 design war used for the returning panels for the 1984 REGS. 

R = Housing units return from preceding survey.

S = Selected housing units from the same penultimate clusters that had been used in the preceding survey. 

N = Selected new listing segments from the SSU's used in the preceding survey.

Source: Energy Information Administration, Office of Energy Markets and End use, the 1982,1984, 1987, and 1990 Residential 

Energy Consumption Surveys.

In the 1990 RECS, for example, Rotation Groups E and F were designated as those returning groups, 

originally sampled in the previous RECS, which were to be interviewed again. Groups C and D on the other 

hand, made up the incoming or new groups, which were included for the first time in the 1990 RECS sample. 

Procedures for updating the sample for new construction and for other changes in the housing unit stock, were 

incorporated so that each rotation group, as well as the total RECS sample, represented a probability sample 

of the survey population.

The sample design for the 1993 RECS did not include a longitudinal panel, though one may be incorporated 

into the sample design for the 1996 and/or 1999 RECS. It would be possible to divide each of the ultimate 

clusters used for the 1993 RECS into two panels, and institute the longitudinal design at the elementary-unit 

level. Alternatively, the SSU's could be divided into two panels. (Each PSU for the 1993 design contains an 

even number of SSU's.) The longitudinal design could then be instituted at the SSU level, as was done for 

the 1980 through 1990 RECS. The exact form of a longitudinal sample design for the 1996 and/or 1999 RECS 

will be decided in the future. One complicating factor in developing a longitudinal panel for the 1996 RECS, 

is that the 1993 RECS obtained its SSU's from the second stages of both the 1984 and 1993 designs. Hence, 

some PSU's in the 1996 RECS would use the returning panel from 1984 SSU's, and the incoming panel from 

1993 SSU's. The need to work with two sets of SSU's in some PSU's will add higher costs to any proposal 

to incorporate a longitudinal panel into the 1996 RECS sample design.

New Construction Update Procedures

The new construction procedures for the 1982 through 1990 RECS vary by rotation group. The procedures 

for the returning rotation groups were different than those for the incoming rotation groups. In addition, the 

procedures differed between the two incoming rotation groups. The new construction procedures for the 1990 

RECS will be used to describe the procedures in general.

New Construction Updates for Returning Rotation Groups

Groups E and F made up the returning rotation groups for the 1990 RECS. The general plan for the SSU's 

in the returning groups, was to attempt to conduct interviews in the housing units taken from the ultimate 

clusters in the 1987 RECS, as well as in a sample of newly constructed units. It should be noted that these 

ultimate clusters in the 1987 RECS also included housing units that had been vacant when the interviews were 

first attempted, as well as housing units where interviews were attempted unsuccessfully (refusals, not-at-home, 

etc.).

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 47
In mid-1990, before the 1990 REGS interview phase was started in Rotation Groups E and F, field workers 

made visits to their respective penultimate clusters. During these visits, the 1987 housing units listings were 

checked and updated for missed units, new construction, demolition, and structure conversion (i.e., conversion 

from one use to another).

A sample of newly constructed units, units converted from nonresidential uses to residential units, and unite 

missed during the 1987 RECS field- listing procedures, were added to the ultimate clusters for Rotation Groups 

E and F. These units were sampled from the updated field listings at the 1990 RECS sampling rate.

New Construction Updates for New Rotation Groups

Groups C and D formed the new rotation groups for the 1990 RECS. Prior to selecting the ultimate clusters 

for the 758 SSU's in these groups, a new construction update procedure was utilized. The update procedure 

started with a canvass (primarily by telephone) of local information sources, such as building-permit-issuing 

agencies, zoning boards, and tax offices. The objective was to determine whether significant new construction 

defined as groups of 25 or more new housing units-had occurred within the SSU since 1984. In this canvass, 

significant new construction was found in 197 of the 758 SSU's. The rough-counting procedures, segment 

formulation procedures, and segment selection procedures of the secondary stage, as well as the entire primary 

stage, were repeated for these 197 SSU's.

In the SSU's where no significant new construction was found, procedures differed in Rotations Groups C and 

D. In mid-1990, field workers also made visits to the penultimate clusters in the SSU's in Rotation Grou ;> 

D. Like the listings checks, carried out for Rotation Groups E and F, in these visits, workers checked and 

updated the 1987 housing unite listings for missed units, new construction, demolitions, and stractiiin; 

conversions. In the SSU's in Rotation Group D, housing units for the 1990 RECS sample were selected Iron 

among those not selected in the earlier RECS.

For SSU's in Rotation Group C, a new listing segment was selected for the 1990 RECS using the existin e 

RECS rough counts. The elementary-unit stage was redeveloped for these new listing segments.

New Construction Update for 1993 RECS

Initial plans for the 1993 design included the complete revision of the secondary stage and, subsequently, the 

development of the elementary-unit stage for those SSU's selected in the secondary stage. While initially, the 

new construction update procedures were not needed, the budget restrictions required some PSU's to take 

their secondary stages from the 1984 design. For these PSU's, the new construction update procedures we:;e 

used and were the same as those used in prior RECS for the new rotation groups.

New Construction Update for 1996 RECS

New construction update procedures are included in the plans for the 1996 RECS. The exact form of these, 

procedures has not been completely specified. It is anticipated that the updates will cover not only the 

sampled SSU's but, also additional Census Blocks that adjoin the sampled SSU's.

New Construction Supplement for the 1993 RECS

An additional feature of the 1993 RECS design, is an oversample of newly built housing units. The design 

of the secondary stage for the 1993 RECS calls for 1,460 SSU's in the core sample, and 150 supplemental 

SSU's from those Census tracts or block groups with a high percentage of new housing units (i.e., constructed

Energy Information Administration/Energy Consumption Series 

48 Sample Design for the Residential Energy Consumption Survey
in the 6-year period prior to the 1990 Census). In addition, housing units judged to be new by field workers 

during the field-listing procedures will be sampled at a higher than those judged to be older. The 

oversample was included as part of the 1993 RECS sample design because of the importance of obtaining 

accurate data on the energy characteristics of new housing units.

One of the reasons for the major revisions in the sample design prior to the 1984 and 1993 RECS, was to 

update the sample design for population changes measured by the 1980 and 1990 Censuses. Areas with a large 

population increase should have a much higher incidence of new residential construction, than areas with a 

smaller population increase, or a decrease in population.

Low-Income

An additional feature of the 1981, 1984, 1987, and 1993 RECS designs, is an oversample of housing 

units in SSU's determined by the interviewers to be low-income Because of the low number of lowincome housing units in the core sample whose main space-heating fuel is electricity, fuel oil, liquefied 

petroleum gas, or kerosene, housing units in low-income SSU's where the main space-heating fuel was 

something other than natural gas were sampled at even an higher rate. This low-income supplement was 

funded by the Administration for Children and Families of the U.S. Department of Health and Human 

Services (HHS). Data collected during the RECS on low-income households are by HHS to administer 

the Low-Income Home Energy Assistance Program,

Summary of for the

Table 12 lists the sample size, the presence of a longitudinal component, the of a low-income 

supplement, and the presence of a new construction supplement.

Table 13 summarizes the new construction update/oversaraple procedures for the various cycles of RECS.

Energy Information Administration/Energy Consumption

Sample Design for the Residential Energy Consumption Survey 49
Table 12. Features of RECS Surveys

Survey

Number of 

Observations

1978 NIECS

Screener 

(1979)

1980RECS 

1981 RECS

1982 REGS

1984 REGS

1987 REGS

1990 REGS

1993 REGS

3,842

3,064

5,804

6,269

4,724

5,682

6,229

5,095

Approximately 

7,050

Longitudinal 

Component

None

None

None

None

Low-Income 

Supplement

None

None

None

Approximately 

percent of 

observations

18.4

2. of 4 panels 

carried over from 

1980 RECS

2 of 4 panels 

carried over from 

1982 RECS

2 of 4 panels 

carried over from 

1984 RECS

2 of 4 panels 

carried over from 

1987 RECS

None

None

Approximately 19.3 

percent of 

observations

Approximately 17.E5 

percent of 

observations

None

Approximately 850 

observations out of 

7,050 observations

New Construction 

Supplement

None

None

None 

None

None

None

None

None

Approximately 1,200 

observations out of 

7,050 observations

Source: Energy Information Administration, 1978, 1979, 1980, 1981, 1982, 1984, 1887, 1990, and 1993 Residential En»fi:y 

Consumption Surveys.

Table 13. New Construction Updates

Survey

Half-Open Interval 

Procedures Used

Local Officials Contacted and SSU's Rijllsted 

If Large Amount of New Construction !in SSU

Other New Construe'!! an: 

Update Procedures!

NIECS (1978) and 

Screener (1979)

1980 REGS

1981 REGS

1982 REGS 

1984 REGS 

1987 REGS 

1990 REGS 

1993 REGS

Yes

Yes 

Yes 

Yas 

Yas 

Yes 

Yes 

Yes

No

No

Yes

Yes

Yes, for SSU's retained from 1980 design

Yes

Yes

Yes, for SSU's retained from 1984 design

Selected 56 additional 

SSU's

Source: Energy Information Administration, 1978, 1979, 1980, 1981, 1982, 1984, 1987, 1990, and 1993 Residential Energy 

Consumption Surveys.

50

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
8, for

The RECS sample design will need to be updated/revised/redesigned periodically. The next major revision 

is scheduled to take place when the data for the 2000 Census become available. If major additional 

demands are placed on the RECS design, such as the capacity to produce State-level estimates, then it 

may need to be substantially revised in order to meet these demands prior to the post-2000 Census 

redesign. Even if the primary stage is not revised, the secondary and elementary-unit stages will need to 

be periodically revised.

Data from the Decennial Censuses are extremely useful in the development and revision of the sample 

design for household surveys. Traditionally, the sample design for household surveys is updated every 10 

years when the Census data becomes available. The Census data are used to develop improved definitions 

of PSU's and improved groupings of the PSU's into strata (both in greater MOS equality and in greater 

homogeneity of energy characteristics within strata). Similar measures also are possible in the secondary 

stage by improving the definition and stratification of SSU's. The use of new Census data to determine 

the MOS for PSU's and SSU's will reduce the variance of estimates derived from housing-unit surveys, 

particularly for estimates concerning new construction.

There are two major reasons for a regular decennial redesign of the RECS sample design:

 Outdated survey materials and definitions

 Uneven population growth.

Definitions

The following survey materials and definitions may become outdated: 

 Definitions of PSU's, SSU's, and listing segments

 Maps of SSU's and listing segments

« Lists of housing units in listing segments.

The definitions of metropolitan PSU's make use of MS A boundaries. These definitions are periodically revised 

by the Office of Management and Budget. The boundaries of MSA PSU's are brought up to date during the 

decennial revisions of the RECS sample design.

The SSU definitions make use of Census blocks and block groups. The listing segment for an SSU is either 

equal to the full SSU or only part of the SSU. Maps of the listing segment are used by the field workers to 

define the area in which housing units are to be listed, and are also used by interviewers to locate the housing 

units in the ultimate cluster. The construction of new roads, new landmarks, and new housing units entails 

that these maps will become outdated over time.

The minimum size of the listing segments was chosen, in part, to ensure that the segment will contain enough 

housing unite so that each unit will be selected for no more than two cycles of the RECS. If new listing 

segments are not periodically chosen, the housing-unit lists will be exhausted.

Some listing segments will be contained in a single apartment complex. Housing units in this complex will 

be sampled for each RECS as long as the listing segment is used.

Energy information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 51
Uneven Population Growth

While the national population grew by 9.8 percent from 1980 to 1990, there has been much variation in the 

rates of population change within and between Census divisions, States, and counties. This percentage of 

population change between geographic locations, can be illustrated by using the 1980 and 1990 Censuses.

Uneven population growth implies that both the primary stage and secondary stage of the design need to be 

periodically revised or updated, The extent and effect of uneven population growth will be briefly discussed 

below.

Population Trends by Census Division and State

The U.S. population is regularly enumerated in a Decennial Census. Table 14 shows the national population 

and the population by State and by Census division for the 1990 and 1980 'Censuses. It also indicates the 

percentage change during these years.

All nine of the Census divisions showed a growth in population. This population increase ranges from 0.8 

percent for the East North Central Census Division, to 23.0 percent for the Pacific Census Division. The two 

fastest growing divisions between 1980 and 1990 were the Pacific and the Mountain Census Divisions, both 

of which are in the West Census Region. The slowest growing divisions include the Middle Atlantic, the ]3ast 

North Central, and the West North Central Census Divisions.

Within Census divisions, the percentage of population increase varies by State. To illustrate an extreme, 

within the Mountain Census Division, Wyoming's population decreased by 3.4 percent, while Nevada1 :! 

population increased by 50.1 percent in the same 1980 to 1990 period, Similarly, within the South Atlantic 

Census Division, West Virginia's population decreased by 8.0 percent, while Florida's population increased 

by 32.7 percent. The range in population growth was smallest in the East North Central Census Division. Itn 

this division, Illinois' population increased by less than 0.05 percent, while Wisconsin's population incre;ised 

by 4.0 percent.

Nevada had the largest percentage of population increase (50.1 percent) of any State in the Union. While the, 

populations of West Virginia and the District of Columbia decreased by the largest percentage: 8.0 percent 

and 4.9 percent, respectively.

Population Trends by Couinty

Within States, some counties lost, while other counties gained in population. Table 15 indicates by State and 

by Census division, the number of counties or equivalent areas, which lost or gained in population during the 

1980's. Table 16 shows the minimum and maximum percentage change within counties, State, Census division 

and, national total.

Of the 3,141 counties or equivalent areas nationwide, 1,431 or 46 percent of these experienced a decrease in 

population from 1980 to 1990. The populations of Platte County in Wyoming, and Lake County in Colorado 

decreased by the largest percentage (32 percent). Flagler County in Florida showed the largest percentage of 

population increase (163 percent),

Energy Information Administration/Energy Consumption Series 

52 Sample Design for the Residential Energy Consumption Survey
Table 14. Population and Percent Increase In Population by State, Census Division, and 

National Total

Census Regions 

and Divisions

Population (thousands)

1990 1980

Percent 

increase in 

Population

National Total .....

New England ......

Maine ..........

Now Hampshire . . . 

Vermont .........

Massachusetts ....

Rhode Island .....

Connecticut ......

Middle Atlantic .....

New York ........

New Jersey ......

Pennsylvania .....

East North Central .. 

Ohio ...........

Indiana .........

Illinois ..........

Michigan ........

Wisconsin .......

West North Central .. 

Minnesota .......

Iowa ...........

Missouri .........

North Dakota .....

South Dakota .....

Nebraska ........

Kansas .........

South Atlantic ......

Delaware ........

Maryland ........

District of Columbia 

Virginia .........

West Virginia .....

North Carolina ....

South Carolina ....

Georgia .........

Florida ..........

East South Central .. 

Kentucky ........

Tennessee .......

Alabama ........

Mississippi .......

West South Central.. 

Arkansas ........

Louisiana ........

Oklahoma .......

Texas ...........

248,710

13,207

1,228

1,109

563

6,016

I,003 

3,287

37,602

17,990

7,730

II,882

42,009

10,847

5,544

11,431

9,295

4,892

17,660

4,375

2,777

8,117

639

696

1,578

2,478

43,567

66S

4,781

607

6,187

1,793

6,829

3,487

6,478

12,938

15,176

3,685

4,877

4,041

2,573

26,703

2,351

4,220

3,146

16,987

226,546

12,348

I,125 

921 

511

5,737 

947

3,108

36,787

17,558

7,365

II,864

41,682

10,798

5,490

11,427

9,262

4,706

17,183

4,076

2,914

4,917

653

691

1,570

2,364

36,959

594

4,217

638

5,347

1,950

5,882

3,122

5,463

9,746

14,666

3,661

4,591

3,894

2,521

23,747

2,286

4,206

3,025

14,229

9.8

7.0 

9.2

20.5

10.0

4.9

5.9 

5.8

2.2 

2.5 

5.0 

0.1

0.8 

0.5 

1.0 

0.0 

0.4 

4.0

2.8 

7.3

-4.7 

4.1

-2.1 

0.8 

0.5 

4.8

17.9

12.1

13.4

-4.9 

15.7

-8.0 

12.7 

11.7 

18.6 

32.7

3.5 

0.7 

6.2 

3.8

2.1

12.4

2.8

0.3

4.0

19.4

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 53
Table 14. Population and Percent Increase In Population by State, Census Division, and 

National Total (Continued)

Census Regions 

and Divisions

Population (thousands)

1990

Mountain ... 

Montana .. 

Idaho ..... 

Wyoming . . 

Colorado . . 

New Mexico 

Arizona .. . 

Utah ..... 

Nevada . . .

Pacific ..... 

Washington 

Oregon . .. 

California .. 

Alaska .... 

Hawaii ....

13,659

799

1,007

454

3,294

1,515

3,665

1,723

1,202

39,127

4,867

2,842

29,760

550

1,108

1980

 11,373

787

944

470

2,890

1,303

2,718

1,461

800

31,800

4,132

2,633

23,668

402

96,'i

Percent 

Increase In 

Population

20.1

1.6

6.7

-3.4

14.0

16.3

34.8

17.9

50.1

23.0

17.8

7.9

25.7

36.9

14.9

Source: Statistical Abstract of the United States 1993, U.S. Department of Commerce, Elureau of the Census. 

(Table No. 31, Page 28.)

54

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
Table 15. Number of Counties Losing or Gaining Population by State, Census Division, and 

_____National Total (Continued)______________________ _______

Number of Counties

Losing Population Gaining Population or No Change

Census Regions

and Divisions Total

More

than

10% Loss

0%Loss

to

10% Loss

No Change

to

10 % Gain

11 %Galn

to

20 % Gain

21 % Gain

to

40 % Gain

More

Than

40 % Gain

952 376 262 120

New England ........

Maine ...,...,,...

New Hampshire ....

Vermont .,...,....

Massachusetts .....

Rhode Island ......

Connecticut .......

Middle Atlantic .......

New York .........

New Jersey ........

Pennsylvania ......

East North Central ....

Ohio .............

Indiana ...........

Illinois ............

Michigan .........

Wisconsin .........

West North Central ....

Minnesota .........

Iowa .............

Missouri .,..,,..,.

North Dakota ......

South Dakota ......

Nebraska .........

Kansas ...........

South Atlantic ........

Delaware .........

Maryland .........

District of Columbia . .

Virginia ...........

West Virginia .......

North Carolina .....

South Carolina .....

Georgia ..........

Florida ...........

East South Central ....

Kentucky .........

Tennessee ........

Alabama ..........

Mississippi ........

West South Central ....

Arkansas ..........

Louisiana .........

Oklahoma .........

Texas ............

67

16

10

14

14

5

8

150

62

21

67

437

88

92

102

83

72

618

87

99

115

53

66

93

105

591

3

24

1

136

55

100

46

159

67

364

120

95

67

82

470

75

64

77

254

"»o>f

0

0

1

0

0

0

0

5

0

0

5

25

4

0

18

3

0

238

23

50

21

34

30

43

37

40

0

0

0

9

21

0

5

5

0

121

9

1

3

8

69

10

6

15

38

sri -T

3

1

1

0

1

0

0

52

16

4

32

193

35

50

63

26

19

215

26

41

31

13

22

40

42

140

0

3

1

46

23

20

7

38

2

147

57

26

32

32

148

25

31

32

60

<u>W^

33

7

3

7

10

4

4

73

43

9

21

170

40

36

14

35

45

110

26

7

36

5

9

8

19

165

0

5

0

34

6

42

23

49

6

156

45

54

24

33

140

29

21

23

67

V>/ \f

24

8

5

7

1

1

4

15

2

6

7

42

8

5

6

15

8

36

6

1

17

1

5

2

4

107

3

e

0

21

4

26

6

30

9

22

8

6

4

4

55

8

3

5

39

&.WK.

7

0

0

0

z

0

0

4

1

2

1

7

1

1

1

4

0

15

4

0

8

0

0

0

3

84

0

8

0

17

1

7

3

22

26

16

1

?

3

5

42

3

3

2

34

t K.W

0

0

0

0

0

0

0

1

0

0

1

0

0

0

0

0

0

4

2

0

2

0

0

0

0

55

0

2

0

9

0

3

2

15

24

2

0

1

1

0

16

0

0

0

16

Energy Information Administration/Energy Consumption Ssrtess 

Sample Design for the Residential Energy Consumption Survey 55
Table 15. Number of Counties Losing or Gaining Population by Stale, Census Division, and 

National Total (Continued)

Number of Counties

Lotting Population Gaining Population or No Change

Census Regions 

and Divisions

Montana ......

Idaho ........

Colorado .....

New Mexico . . .

Arizona .......

Utah .........

Nevada .......

Pacific .........

Washington . . .

Oregon .......

California .....

Alaska .......

Hawaii .......

Total

281

57

44

23

63

33

15

29

117

163

39

36

58

25

5

More

 than

i % Loss

0% Loss

to

10% Loss

No Change

to

10 % Gain

11 % Gain

l;e»

20 % Gain

21 % Gain

to

40 % Gain

More

Than

40 %G

55

21

7

9

11

2

1

4

0

4

1

3

0

0

0

60

19

11

5

16

6

0

3

0

16

5

10

0

0

1

62

8

17

6

9

9

1

10

2

43

18

14

7

3

1

50

9

6

1

12

11

5

5

1

25

5

7

11

2

0

30

0

3

1

9

2

4

5

6

57

10

2

30

13

2

24

0

0

Source: U.S. Bureau of the Census, County Populations, 1990 and 1980 Censuses R&nkad By 1990 Population Within State; 

U.S. Government Printing Office (Washington, DC), 1991.

56

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
Table 16. Percent Increase In Population, Smallest Percent Increase In Population for a County 

and Largest Percent Increase In Population for a County by State. Census Division, 

and National

Percent Increase in

Census Regions Population for State,

and Divisions Census Division, or Nation

National Total ........ 9.8

New England ......... 7.0

Maine ............. 9.2

New Hampshire ...... 20.5

Vermont ............ 10.0

Massachusetts ....... 4.9

Rhode Island ........ 5.9

Connecticut ......... 5.8

Middle Atlantic ........ 2.2

New York ........... 2.5

New Jersey ......... 5.0

Pennsylvania ........ 0.1

East North Central ..... 0.8

Ohio .............. 0.5

Indiana ............ 1 .0

Illinois ............. 0.0

Michigan ........... 0.4

Wisconsin .......... 4.0

West North Central ..... 2.8

Minnesota .......... 7.3

Iowa .............. -4.7

Missouri ............ 4.1

North Dakota ........ -2.1

South Dakota ........ 0.8

Nebraska ........... 0.5

Kansas ............ 4.8

South Atlantic ......... 17.9

Delaware ........... 12.1

Maryland ........... 13.4

District of Columbia . . . -4.9

Virginia ............ 15.7

West Virginia ........ -6.0

North Carolina ....... 12.7

South Carolina ....... 11.7

Georgia ............ 18.6

Florida ............. 32.7

East South Central ..... 3.5

Kentucky ........... 0.7

Tennessee .......... 6.2

Alabama ........... 3.8

Mississippi .......... 2.1

West South Central ..... 12.4

Arkansas ........... 2.8

Louisiana ........... 0.3

Oklahoma .......... 4.0

Texas .............. 19.4

Smallest Percent Largest Percent

increase in Population Increase in Population

for a County for a County

-32.0 163.0

-4.8 30.2

-4.8 18.2

-0.9 29.2

1.5 17.7

-4.0 30.2

4.1 17.9

2.5 12.1

-11.4 53.1

-4.6 25.9

-8.6 25.2

-11.4 53.1

-16.5 32.8

-13.9 24.3

-10.0 32.8

-16.5 23.9

-13.5 29.5

-8.6 16.5

-23.8 47.7

-20.1 41 .7

-17.1 17.6

-20.5 47.7

-23.8 16.6

-20.2 15.6

-22.1 19.3

-18.9 38.8

-29.4 163.0

11.0 15.5

-7.0 58.0

-4.9 -4.9

-22.9 80.3

-29.4 26.7

-8.5 70.0

-7.2 42.0

-22.1 125.6

-4.2 163.0

-24.0 49.9

-12.7 25.6

-10.5 41.1

-15.0 49.9

-24.0 29.7

-30.2 91.1

-19.3 9.9

-20.5 30.3

-19.6 31.8

-30.2 91.1

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 57
Table 16. Percent Increase in Population, Smallest Percent Increase! In Population for a County 

and Largest Percent Increase In Population for a County by State, Census Division, 

and National (Continued)

Mountain . . . 

Montana . . 

Idaho ..... 

Wyoming . . 

Colorado . . 

New Mexico 

Arizona . . . 

Utah ..... 

Nevada , . .

Pacific ..... 

Washington 

Oregon . . . 

California . . 

Alaska .... 

Hawaii ....

Increase In Smallest Pei 

n for State, Increase In 1 

Ivtsilon, or Nation for a County

20.1

1.6

6.7

-3.4

14.0

16.3

34.8

17.9

50.1

23.0

17.8

7.9

25.7

36.9

14.9

cent Largest Percent 

'opulatlon Increase In Population 

for a County

-32.0 140.1

124.7

••27.5

••32.0

17.7

37.7

43.7

•32.0 140.1

-21.6

-29.8

•19.7

1.2

84.1

67.4

86.3

96.5

•16.5 122.7

•13.2

•16.5

1.5

37.9

26.7

58.5

4.2: 122.7

-9.7 41.7

Negative number indicates a decreetse In population.

Source: U.S. Bureau of the Census, County Populations, 1990 and 1980 Censuses Ranked by 1890 Population Within Safe, 

U.S. Government Printing Office (Washington, DC), 1991.

The West North Central Census Division had the highest percentage of counties that lost population (73 

percent). The New England Census Division showed the lowest percentage (4 percent).

Among States, Iowa had the highest proportion of counties losing population (92 percent), followed by 

Nebraska (89 percent). Outside the Midwest, West Virginia showed 80 percent of its counties losinji 

population. The District of Columbia, which can be treated as a single county-like area, experienced a 4S 

decrease in its population.

Conversely, all of the counties in Vermont, Rhode Island, Connecticut, Delaware, Nevada, Alaska, and 

California experienced an increase in population from 1980 to 1990. However, except for California, all of 

these States had a relatively small number of counties.

Tables 15 and 16 indicate that even within States, there is a wide range in the percentage of population change 

among counties. For example, of the 159 counties in Georgia, five of these experienced a 10 percent or moire 

decrease, and 38 showed a 0 to 10 percent decrease. Yet, for 22 counties the population increased from T\ 

to 40 percent, and for 15 counties it increased by more than 40 percent.

When proceeding from larger to smaller segments of the population, the variability in percentage change 

between the segments increases. For example, the population change percentage between divisions ranged 

from a low of 0.8 percent increase (East North Central), to a high of 23.0 percent increase (Pacific). Between 

States the range was from an 8.0 percent decrease (West Virginia) to a 50.1 percent increase (Nevada), and 

between counties the range was from a 32 percent decrease to a 163 percent increase. At the Census ire.c;; 

level, a geographic location can experience a 100 percent decrease in population over a 10-year period if all 

of the housing units in it are demolished for commercial development (such as in the expansion of an airpor 

or the demolition of a large apartment complex). Conversely, an agricultural area can experience a growth 

in population ranging from very few to hundred's, if over a 10-year period a major housing project is built

58

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
The periodic redesign of the RECS is essential if accurate data on new housing units are to be obtained. As 

a design becomes older and, therefore, more out-of-date, its ability to support new construction estimates 

declines. The periodic redesign of all RECS stages is needed to account for the uneven nature of population 

growth. If the secondary stage and elementary-unit stage are not revised, only those new housing units in the 

existing sampled SSlfs and listing segments will have a chance of being selected. The selection probabilities 

for PSU's and SSU's are based on either the population or the number of households at a set point in time. 

A nonuniform population increase will not produce biased results from keeping these PSU's and SSU's. 

However, it will imply that the variance of statistics will be larger than would be the case if the survey was 

redesigned. This will be particularly true for new housing units.

Energy information Admlnlctratton/Enmrgy

Sample Design for the Residential 59
Appendix A

Census Divisions and Federal Regions Maps

U.S. Census Regions and Divisions

Region 1 

Northeast

Division 1 

(New England) 

Connecticut (CT) 

Maine (ME) 

Massachusetts (MA) 

New Hampshire (NH) 

Rhode Island (RI) 

Vermont (VT)

Division 2 

(Middle Atlantic)

New Jersey (NJ) 

New York (NY) 

Pennsylvania (PA)

Region 2 

Midwest

Division 3

(East North Central) 

Illinois (IL) 

Indiana (IN) 

Michigan (MI) 

Ohio (OH) 

Wisconsin (WI)

Division 4

(West North Central) 

Iowa (IA) 

Kansas (KS) 

Minnesota (MN) 

Missouri (MO) 

Nebraska (NE) 

North Dakota (ND) 

South Dakota (SD)

Region 3 

South

Division 5 

(South Atlantic)

Delaware (DE) 

District of Columbia (DC) 

Florida (FL) 

Georgia (GA) 

Maryland (MD) 

North Carol ina(NC) 

South Carolina (SC) 

Virginia (VA) 

West Virginia (WV)

Division 6

(East South Central)

Alabama (AL) 

Kentucky (KY) 

Mississippi (MS) 

Tennessee (TN)

Division 7

(West South Central) 

Arkansas (AR) 

Louisiana (LA) 

Oklahoma (OK) 

Texas (TX)

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey

Region 4 

West

Division 8 

(Mountain) 

Arizona (AZ) 

Colorado (CO) 

Idaho (ID) 

Montana (MT) 

Nevada (NV) 

New Mexico (NM) 

Utah (UT) 

Wyoming (WY)

Division 9 

(Pacific)

Alaska (AK) 

California (CA) 

Hawaii (HI) 

Oregon (OR) 

Washington (WA)

61
Federal Regions

Region 1 

New England 

Connecticut (CT) 

Maine (ME) 

Massachusetts (MA) 

New Hampshire (NH) 

Rhode Island (RI) 

Vermont (VT)

Region 2

New York/New Jersey 

New Jersey (NJ) 

New York (NY)

Region 3 

Mid Atlantic

Delaware (DE) 

District of Columbia (DC) 

Maryland (MD) 

Pennsylvania (PA) 

Virginia (VA) 

West Virginia (WV)

Region 4

South Atlantic 

Alabama (AL) 

Florida (FL) 

Georgia (GA) 

Kentucky (KY) 

Mississippi (MS) 

North Carolina (NC) 

South Carolina (SC) 

Tennessee (TN)

Region S 

Midwest

Illinois (IL) 

Indiana (IN) 

Michigan (MI) 

Minnesota (MN) 

Ohio (OH) 

Wisconsin (WI)

Region 6 

Southwest

Arkansas (AR) 

Louisiana (LA) 

New Mexico (NM) 

Oklahoma (OK) 

Texas (TX)

Region 7 

Central

Iowa (IA) 

Kansas (KS) 

Missouri (MO) 

Nebraska (NE)

Region 8 

North Central

Colorado (CO) 

Montana (MT) 

North Dakota (ND) 

South Dakota (SD) 

Utah (UT) 

Wyoming (WY)

Region 9 

West

Arizona (AZ) 

California (CA) 

Hawaii (HI) 

Nevada (NV)

Region 10 

Northwest

Alaska (AK) 

Idaho (ID) 

Oregon (OR) 

Washington (WA)

62

Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
Appendix B

Detailed to on

,16

A housing unit is a. house, an apartment, a group of rooms, or a single room if it is occupied, or intended for 

occupancy, as separate living quarters by a family, an individuals or a group of up to unrelated persons. 

In general:

 a "one-family house" is one housing unit.

« a "two-family house" is two housing units

 each apartment in an apartment building is a housing unit

 a vacant house or apartment is a housing unit (because someone live there in 

the future), and

« a store or business is not a housing unit, but... an apartment over or a store or business 

is a housing unit.

Rules about separate living quarters may be needed to determine the number of housing units to be listed. 

Separate living quarters are those where:

 the occupant(s) live and eat separately from other persons in the building; and

 the occupant(s) have direct access from the outside of the building or a common hall (that 

is, entry and exit can be made without entering someone living quarters).

Kitchen facilities are not required in order for separate living quarters to be as a housing unit.

Group Quarters - Living arrangements for institutional or inmates or for other groups of ten or 

more unrelated persons. Group quarters are not housing units, and you are not to conduct interviews in them. 

There are two general types:

« Group quarters are most frequently found in institutions. are hospitals, nursing homes, 

military barracks, college dormitories, fraternity and sorority houses, convents, monasteries, and 

penal institutions.

 A house or apartment is considered to be group quarters if it is by the person in charge 

and nine or more nonrdatives (a total of ten or more persons). If there is no head of household 

or person in charge, the household or apartment is considered group quarters if it is shared by ten 

or more unrelated persons.

However, rooms or apartments within a institution that serve as the permanent of staff members are 

housing units if they satisfy the requirements of separate living quarters.

16 This section is takea from the 1987 RECS Sample Desiffi Procedures Manual, pages F-10 to F-14.

Energy Information Administraflon/Ensrfly Consumption

Sample Design for the Residential Consumption 63
Be alert for places that appear to be group quarters but do not contain enough people. For example, suppose 

that a convent turns out to have five nuns living in it. This convent would not be considered group quarter.'.; 

it would be a housing unit.

Rooming and Boarding Houses - The rules apply here as applied to housing units/group quarters. The key 

items of information needed to determine whether these are housing units are (1) the number of residents ami 

(2) whether some rooms, or groups of rooms, meet the requirements for separate living quarters.

Example 1: Fewer than nine residents unrelated to the person in charge, and

separate rooms (or groups of rooms) do not meet conditions for separate living quarters.

This house would be treated as a single-housing unit.

Example 2: Nine or more residents unrelated to the person in charge (or a total of ten or more unrelated 

persons), and separate rooms (or groups of rooms) do not meet conditions listed for separate 

living quarters.

This house is considered a group quarters. No interview is to be conducted. 

Example 3: Some rooms (or groups of rooms) meet the conditions for separate living quarters.

Consider each room (or group of rooms) that is separate living quarters as a separate housing 

unit.

Housing Units in Special Cases

Below are some examples of special situations that should be listed as housing units: 

Basement or attic apartments which may occur in any type of structure. 

Vacant houses or apartments (because they could be occupied in the future.)

Houses and apartments that are tinder construction - if they are likely to be completed and ready :Ebr 

occupancy by the time the interviews are started.

Hotel or motel rooms which are (1) occupied by permanent guests, or (2) occupied by employees who have 

no permanent residence elsewhere.

Rooms within group quarters or institutions (such as a fraternity house or dormitory) which serve as the 

permanent residence of a staff member or person in charge, and which satisfy the requirements of the housingunit definition.

A room in a nonresidential structure - if there is one room in a warehouse which the caretaker uses for ibis 

living quarters, such a room qualifies as a housing unit.

A mobile home trailer that is used as the permanent residence of occupants and not just as their vacation 

residence.

Work camps occupied by seasonal workers.

Seasonal dwellings, such as summer homes, resort cottages, or other part-time, homes, are considered housing 

units.

Energy information Administration/Energy Consumption Series 

64 Sample Design for the Residential Energy Consumption Survey
Boats, tents, ete. Any such quarters that are occupied as someone's permanent residence are housing units, 

If they are used for vacation only, they are not housing units.

Not as in

Below are some examples of situations when housing units should not be listed as such:

Group quarters-However, you cannot completely ignore such buildings, since some of them may contain the 

dwelling unit of a manager, janitor, etc. You should determine whether there are "hidden" housing units in 

the building.

Unoccupied buildings that have been condemned or that are being demolished.

Places of business, such as stores, factories, etc.-but be sure to look for iiard-to-fmd living quarters behind or 

above or inside business places.

Energy Information Administration/Energy Consumption Series

Sample Design for the Residential Energy Consumption Survey 65
Appendix C

by

En«r§y information Administration/Energy Consumption Series

Sample Design for th Residential Energy Consumption Survey 67
RECS 1980

Intersection 1: Connecticut, Maine, Massachusetts, Rhode Island, and Vermont

(10 Strata)

MSA'S 

(8 Strata)

Self Representing 

(5 Strata)

Non-self 

Representing 

(3 Strata)

Boston

Hartford

Providence

Bridgeport (Connecticut Suburbs of NYC)

New Haven

Small and Medium-Size MSA's in ME, NH, and 

New London, CT and Worcester, MA 

Springfield and New Bedford, MA

Non MSA's 

{2 Strata)

Non-self 

Representing 

(2 Strata)

Non-MSA Counties in NH, ME, and VT

Non-MSA Counties in NH, ME, VT, CT, RI, and l-'.i\

68

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
REGS 1980

Intersection 2: New York and New Jersey 

(9 Strata)

MSA'S 

(8 Strata)

Self Representing 

(3 Strata)

Non-self

Representing 

(5 Strata)

New York City

Long Island (Suburbs of NYC)

Newark, NJ (Suburbs of NYC)

Buffalo, Binghamton, Elmira, 

and Utica, NY

Rochester and Syracuse, NY

Paterson, Jersey City, and 

Phillipsburg, NJ

MSA's in South and Central NJ

Albany and Poughkeepsie, NY; 

and Camden, NJ

Non MSA's 

(1 Strata)

Non-self 

Representing 

(1 Strata)

Non-MSA Counties in NY and NJ

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 69
RECS 1980

Intersection 3: Pennsylvania 

(5 Strata)

MSA'S

(4 Strata)

Self Representing 

(2 Strata)

Non-self

Representing 

(2 Strata)

Phi Ic.delphla 

Pittsburgh

Johnstown, York, Harrisburg, 

and Scranton, PA

Small and Medium-Size MSA's in P,i

Non MSA's 

(1 Strata)

Non-self 

Representing 

(1 Strata)

Non-MSA Counties in PA

70

Energy Information Administration/Energy Consumption Series 

Sample) Design for the Residential Energy Consumption Survey
REGS 1980

Intersection 4: Delaware, District of Columbia, Maryland, Virginia, and West Virginia

(6 Strata)

MSA'S

(4 Strata)

Non MSA's 

(2 Strata)

Self Representing 

(2 Strata)

Non-self 

Representing 

{2 Strata)

Non-self 

Representing 

(2 Strata)

Baltimore 

Washington, D.C.

Richmond and Virginia Beach, VA

Small and Medium-Size MSA's in WV, 

DE, MD, and VA

Non-MSA Counties in West Virginia, 

VA, and Maryland

Non-MSA Counties in Virginia, 

Maryland, and Delaware

Energy Information Administration/Energy Consumption 

Sample Design for the Residential Energy Consumption Survey 71
RECS 1980

Intersection 5; Florida, Georgia, North Carolina, and South Carolina

(11 Strata)

MSA'S 

(7 Strata)

Self Representing 

(1 Strata)

Non-self 

Representing 

(6 Strata)

Atlanta

Miami, Fort Lauderdale, and 

Wast Palm Beach, FL

Small and Medium-Size MSA's 

in GA and SC,

Orlando, Lakeland, and Tampa, i'L

Sma.'.l and Medium-Size MSA's in XT 

and SC

Small and Medium-Size MSA's in NC

Small and Medium-Size MSA's ir. ! 7 " 

and GA

Non MSA's 

(4 Strata)

Non-self 

Represent ing 

\4 Strata)

Nor.-MSA Counties in NC and SC

Non-MSA Counties in NC, SC, GA, 

and FL

Non-MSA Counties in NC, SC, GA. 

and FL

Non-MSA Counties in GA and SC

72

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
RECS 1980

Intersection 6: Alabama, Kentucky, Mississippi, and Tennessee

(13 Strata)

MSA'S 

(7 Strata)

Self Representing 

(None)

Non-self 

Representing 

(7 Strata)

Louisville and Lexington, KY 

Birmingham and Montgomery, AL 

Covington, Kentucky and Memphis, TN 

Mobile, AL; Biloxi and Jackson, MS 

Knoxville and Nashville, TN

Small and Medium-Size MSA's in AL, 

KY, and MS

Small and Medium-Size MSA's in AL 

and TN

Non MSA's 

(6, Strata!

Non-self 

Representing 

(6 Strata)

Small and Medium-Size MSA's in KY, 

TN, AL, and MS

Small and Medium-Size MSA's in KY, 

TN, AL, and MS

Small and Medium-Size MSA's in AL 

and MS

Small and Medium-Size MSA's in AL 

and MS

Small and Medium-Size MSA's in KY, 

TN, AL, and MS

Small and Medium-Size MSA's in KY 

and TN

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 73
RECS 1980

Intersection 7: Illinois, Indiana, Michigan, Ohio, and Wisconsin

(16 Strata)

Self Representing 

{3 Strata)

Cleveland

Chicago

Detroit

MSA's

{12 Strata)

Non-self 

Representing 

(9 Strata)

Milwaukee, Madison, and Appleton, WI

Small and Medium-Size MSA's in WI, MI,

and II-,

Fort Wayne, Gary, and Indianapolis, IN 

Canton, voungstown, and Columbus, OH 

Small and! Medium Size MSA's in MI 

Small and Medium-Size MSA's in OH

Small and Medium-Size MSA's in MI, IN, and 01- 

Day ton and Cincinnati, OH; and Indiana.

Suburb of CN

Small and. Medium-Size MSA's in IN and I

Non MSA's 

(4 Strata)

Non-self 

Representing 

(4 Strata)

Non-MSA Counties in OH, IN, MI, and U,

Non-MSA Counties in OH, IL, and IN

Non-MSA Counties in IN and IL

Non-MSA Counties in IN, MI, and WI

74

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
RECS 1§8§

Intersection 8: Arkansas, Louisiana, Oklahoma, and Texas

(12 Strata)

MSA'S 

(8 Strata)

Self Representing 

(2 strata)

Non-self 

Representing 

(6 Strata)

Houston 

Dallas

Non MSA's 

(4 Strata)

Non-self 

Representing 

(4 Strata)

Tulsa and Oklahoma City, OK; Lubbock 

and Midland, TX

Small and Medium-Size MSA's in AR 

and TX

New Orleans and Baton Rouge, LA

San Antonio, Austin, Waco, and 

Wichita Falls, TX

Small and Medium-Size MSA's in LA, 

OK, and TX

Small and Medium-Size MSA's in LA, 

and TX

Non-MSA Counties in AR, OK, and TX

Non-MSA Counties in AR, LA, OK,

and TX 

Non-MSA Counties in AR, LA, OK,

and TX

Non-MSA Counties in AR, LA, OK, 

and TX

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 75
RECS 1980

Intersection 9: New Mexico 

(1 Strata)

USA's

(None)

Non MSA's 

(None)

Mixed MSA

and non-M3A 

(1 Strata)

Non-self 

Representing 

(1 Strata)

MSA' and Non-MSA Counties 

New Mexico

in

76

Energy Information Administration/Energy Consumption Series 

Sarnpli: Dasign for the Residential Energy Consumption Survey
P.ECS 1980

intersection 10: Minnesota 

(2 Strata)

MSA's

{1 Strata)

Self Representing 

(1 Strata)

Non-self

Representing

(None)

Minneapolis, MN

Non-MSA's 

(None)

Mixed MSA 

and non-MSA 

(1 Strata)

Non-self 

Representing 

(1 Strata)

Small and Medium-Size MSA and Non-MSA Counties 

in MN

Energy Information Administration/Energy Consumption Series 

Sample Design for tha Residential Energy Consumption Survey 77
RECS 1980

Intersection 11: Iowa, Kansas, Missouri, and Nebraska 

(12 Strata)

MSA'S 

(6 Strata)

Self Representing 

(2 Strata)

Non-self 

Representing 

(4 Strata)

Kansas City, MO

Si Umis, MO

Des Moines, IA and Omaha, NE 

Small and Medium-Size MSA's :m t;':,

Small and Medium-Size MSA's in EC 

KS, and NE

Kansas City and Wichita, KS

Non MSA's

(6 Strata)

Non-self 

Representing 

(6 Strata)

Non-MSA Counties in IA and Nl!

Non-MSA counties in IA, ME, us, 

and MO

Non-MSA Counties in MO and K!J 

Non-MSA Counties in MO, KS, and H!i: 

Non-MSA Counties in IA and MO 

Non-MSA Counties in MO, KS, ana MS

78

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
RECS 1980

Intersection 12: North Dakota and South Dakota 

(3 Strata)

MSA'S

(None)

Non MSA's 

(2 Strata)

Non-self 

Representing 

(1 Strata)

Non-MSA Counties in ND and SD 

Non-MSA Counties in ND and SD

Mixed MSA's 

(1 Strata)

Non-self 

Representing 

(1 Strata)

MSA's in ND and SD

Non-MSA Counties in ND, and SD

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 79
RECS1980

Intersection 13: Colorado, Montana, Utah, and Wyoming

(8 Strata)

MSA'S

(4 Strata)

Self Representing 

(2 Strata)

Non-self 

Representing

(2 Strata)

Denver

Salt Lake City

Small and Medium-Size USA's in CO 

and MT

Small and Medium-Size MSA's in MT, 

CO, and UT

Non MSA's 

(4 Strata)

Non-self 

Representing 

(4 Strata)

Non-KSA Counties in MT, CO, WY, 

and UT

Non-KSA Counties in MT, CO, WY, 

and UT

Non-USA Counties in MT, CO, WY, 

and UT

Non-MSA Counties in MT, CO, WY, 

and UT

80

Energy Information Administration/Energy Consumption Series 

l'Si Design for the Residential Energy Consumption Survey
1880

14: Arizona and Sfevada 

(3

MSA's 

(2 Strata)

Self Representing 

(1 Strata)

Non-self 

Representing 

(1 Strata)

Phoenix

Tucson, AZ and Las Vegas, NV

Son MSA's 

(1 Strata!

Non-self 

Representing 

(1 Strata!

Non-MSA Counties in AZ and NV

Energy information Administration/Energy Consumption Series 

SampEe Design for the Residential Energy Consumption Survey 81
RECS 1980

Intersection 15: Idaho

(1 Strata)

MSA'S

(None)

Non-MSA's 

(None)

Mixed MSA 

and Non-MSA 

(1 Strata)

Non-self 

Representing 

[1 strata)

MSA's and Non-MSA Counties in ID

82

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
RECS 1980

intersection 16: California and Hawaii 

{10 Strata)

HSA's 

(Excluding 

Hawaii) 

{8 Strata)

Non MSA's

{Excluding

Hawaii

(1 Strata)

Self Representing 

(4 Strata)

Non-self 

Representing 

(4 Strata)

Non-self 

Representing 

(1 Strata!

Los Angles 

San Francisco 

Orange County 

San Diego

Riverside and San Bernardino, CA 

San Jose and Stockton, CA 

Small and Medium-Size MSA's in CA 

Small and Medium-Size MSA's in CA

Non-MSA Counties in CA

Hawaii 

(MSA's and 

Non MSA's) 

(1 Strata)

Non-self 

Representing 

{1 Strata)

Honolulu Hawaii and Non-MSA Counties

Energy Information Administration/Energy Consumption Saris 

Sample Design for the Residential Energy Consumption Survey 83
RECS 1980

Intersection 17: Alaska, Oregon, and Washington 

(9 Strata)

MSA's

(Excluding 

Alaska)

(5 Strata)

Self Representing 

(3 Strata)

Non-self 

Representing 

[2 Strata)

Seattle, WA 

Portland, OR 

Tacoma, WA

Small and Medium-Size MSA's in VIA

Small arid Medium-Size MSA's in OR 

and WA

Non MSA's 

(Excluding 

Alaska 

(3 Strata)

Non-self 

Representing 

(3 Strata)

Non-MSA Counties in WA and OR 

Non-MSA Counties in WA and OR 

Hon-MSA Counties in WA and OR

Alaska 

(MSA's and 

Non MSA's) 

(1 Strata)

Non-self 

Representing 

(1 Strata)

Anchorage Alaska and Non-MSA Counties

84

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
1984

England 

(10

MSA'S

(8 Strata)

Self Representing 

{5 Strata)

Non-self 

Representing 

(3 Strata

Boston

Hartford

Providence

Bridgeport (Connecticut Suburbs 

of NYC)

New Haven

Small and Medium-Size MSA's in ME, 

HH, and MA

New London, CT; Worcester, MA; and 

Burlington, vr

Springfield and New Bedford, MA

Nan MSA's 

{2 Strata)

Non-self 

Represent ing 

(2 Strata)

Uon-MS& Counties in HH, ME, and VT

Non-MSA Counties in NH, ME, VT, CT, 

RI, and MA

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 85
RECS 1984

Middle Atlantic Census Division 

(15 Strata)

MSA'S 

(13 Strata)

Self Representing 

(5 Strata)

Non-self 

Representing 

{8 Strata)

New York City

Long Island (Suburbs of NYC)

Newark, NJ (Suburbs of NYC}

Philadelphia

Pittsburgh

Buffalo, Binghamton, and Utica, :y 

Rochester, Syracuse, and Elmira, s

Paterson, Jersey City, and 

Phillipsburg, NJ

MSA's in South and Central NJ 

MSA's in NJ (Suburbs of NY City;

Johnstown, York, Harrisburg, and 

Scranton, PA

Small and Medium-Size MSA's in PA

Albany, Poughkeepsie, Glen Falls, 

and Orange County, NY

Non MSA's 

(2 Strata)

Non-self 

Representing 

(2 Strata)

Non-MSA Counties in NY 

Non-MSA Counties in PA

86

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consurnpliera Survey
1SS4

tforth Centra! Cerssus Division 

(17 Strata)

Self Representing 

(3 strata)

Cleveland

Chicago

Detroit

MSA's 

(12 Strata)

Non-self 

Representing 

(9 strata)

Milwaukee, Madison, and 

Appleton, WI

Small and Medium-Size MSA's 

in WI and IL

Fort Wayne, Gary/ and 

Indianapolis, IN

Canton, Youngstown, and 

Columbus, OH

Small and Medium-Size MSA's in MI 

Small and Medium-Size MSA's in OH

Small and Medium-Size MSA's in MI, 

IN, and OH

Dayton and Cincinnati, OH; and IN 

Suburb of Cincinnati

Small and Medium-Size MSA's in IN 

and IL

Non MSA's 

{5 Strata)

Non-self 

Representing 

(5 Strata)

Non-MSA Counties in OH, IN, MI, 

and IL

Non-MSA Counties in OH 

Non-MSA Counties in IN and IL 

Non-MSA Counties in MI and WI 

Non-MSA Counties in IN, IL, and MI

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 87
RECS 1984

West North Central Census Division 

(17 Strata)

MSA'S 

(8 Strata)

Self Representing 

(3 Strata)

Non-self 

Representing 

(5 Strata)

Minneapolis, MN 

Kansas City, MO 

St :L,c\j.is, MO

Des Moines, IA and Omaha, NE 

Small and Medium-Size MSA's in '.'.A

Small and Medium-Size MSA's in >IC , 

KS, and NE

Kansas City and Wichita, KS

Small and Medium-Size MSA's in :MK . 

ND, and 3D

Non MSA's 

(9 Strata)

Non-self 

Representing 

(9 Strata)

Non-MSA Counties in MN 

Non-MSA Counties in IA and NE

Non-MSA Counties in IA, NE, K!3, 

and NE

Non-MSA Counties in MO and KS 

Non-MSA Counties in MO, KS, and KK 

Non-MSA Counties in IA and MO 

Non-MSA Counties in MO, KS, and KE 

Non-MSA Counties in ND and SD 

Non-MSA Counties in MN, ND, and SD

88

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
RECS 11984 

South Atlantic Census Division

(19 Strata)

MSA's 

(13 Strata)

Self Representing 

(5 strata)

Non-self 

Representing 

(8 strata)

Baltimore

Washington, DC

Atlanta

Miami

Tampa

Richmond and Virginia Beach, VA

Small and Medium-Size MSA's in WV, 

DE, ME, and VA

Fort Lauderdale and

West Palm Beach, FL

Small and Medium-size MSA's in GA 

and sc

Orlando, Lakeland, Ocala, and 

Jacksonville, FL

Small and Medium-Size MSA's in GA, 

NC, and SC

Small and Medium-Size MSA's in NC 

and SC

Small and Medium-Size MSA's in FL

Non MSA's 

(6 Strata)

Non-self 

Representing 

(6 Strata)

Non-MSA Counties in WV, VA, and MD 

Non-MSA Counties in VA, MD, and DE 

Non-MSA Counties in NC and SC

Non-MSA Counties in NC, SC, GA, 

and FL

Non-MSA Counties in NC, SC, GA, 

and FL

Non-MSA Counties in GA and SC

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 89
RECS 1984

East South Central Census Division 

(12 Strata)

MSA'S 

(6 Strata)

Self Representing 

(None)

Non-self

Representing 

(6 strata)

Small and Medium-Size MSA's in KY 

Small and Medium-Size MSA's in M.

small and Medium-Size MSA's in KY. 

TN, and MS

Small and Medium-Size MSA's in i\l, 

and MS

Knoxville and Nashville, TN

Small and Medium-Size MSA's in ,<>L 

and TN

Non MSA's 

{6,Strata)

Non-self 

Representing 

(6 Strata)

Non-MSA Counties in KY, TN, AL, 

and MS

Non-MSA Counties in KY, TN, AL, 

and MS

Non-MSA Counties in AL and MS 

Non-MSA Counties in AL and MS

Non-MSA Counties in KY, TN, AL, 

and MS

Non-MSA Counties in KY and TN

90

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
REGS 1984

West South Central Census Division 

(12 Strata)

MSA's

(8 Strata)

Self Representing 

(2 Strata)

Houston 

Dallas

Non-self 

Representing 

(6 Strata)

Tulsa and Oklahoma City, OK; Lubbock 

and Midland, TX

Small and Medium-Size MSA's in AR 

and TX

New Orleans, Baton Rouge, and 

Houma, LA

San Antonio, Austin, Waco, and 

Victoria, TX

Small and Medium-Size MSA's in LA, 

OK, and TX

Small and Medium-Size MSA's in LA, 

and TX

Non MSA's 

(4 Strata)

Non-self 

Representing 

(4 Strata)

Non-MSA Counties in AR, OK, and TX

Non-MSA Counties in AR, LA, OK, 

and TX

Non-MSA Counties in AR, LA, OK, 

and TX

Non-MSA Counties in AR, LA, OK, 

and TX

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 91
RECS 1984

Mountain Census Division 

(11 Strata)

MSA'S 

(6 Strata)

Self Representing 

(3 Strata)

Non-self 

Representing 

(3 Strata)

Denver

Sal': Lake City

Phoenix

Small and Medium-Size MSA's in CO 

NM, and NV

Small and Medium-Size MSA's in KT 

CO.. UT, WY, and ID

TucKon, AZ and Las Vegas, NV

Non MSA's 

(5 Strata)

Non-self 

Representing 

(5 Strata)

Non-MSA Counties in NM and CO

Nor.-MSA Counties in MT, CO, WY, 

and UT

Ncn-MSA Counties in MT, CO, WY, 

and UT

Ncn-MSA Counties in AZ and NV 

Non-MSA Counties in ID, MT, and V.

92

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
RECS 1984

Pacific Census Division 

(16 Strata)

MSA'S

(Excluding 

Hawaii and 

Alaska)

(12 Strata)

Self Representing 

(6 Strata)

Non-self 

Representing

(6 Strata)

Los Angles

San Francisco

Orange County

San Diego

Riverside-San Bernardino

Seattle

San Jose and Stockton, CA

Napa, Redding, and Sacramento, CA

Ventura, Santa Barbara, Salinas, 

and Bakersfield, CA

Portland, OR; Tacoma and 

Bremerton, WA

Small and Medium-Size MSA's in OR 

and WA

Small and Medium-Size MSA's in CA

Non MSA's 

(Excluding

Hawaii and

Alaska) 

(2 Strata)

Non-self 

Representing 

(2 Strata)

Non-MSA Counties in CA and OR 

Non-MSA Counties in WA and OR

Hawaii and 

Alaska 

(MSA's and 

Non MSA's) 

(2 Strata)

Non-self 

Representing 

(2 strata)

Honolulu Hawaii and Non-MSA Counties 

Anchorage Alaska and Non-MSA Counties

Energy information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 93
RECS 1993

New England Census Division 

(8 Strata - 4,942,714)

MSA'S 

(6 Strata)

Self Representing 

(2 Strata)

Non-self 

Representing 

(4 Strata)

Boston, MA 

Hartford, CT

Providence, RI and New Bedford, MA 

New Haven and Bridgeport, CT

Worcester and Springfield, MA; New 

London, CT

Smaller NECMA's in MA, ME, NH, 

and VT

Non MSA's 

(2 Strata)

Non-self 

Representing 

(2 Strata)

Non-NECMA Counties in ME, Northern 

NH, and VT

Non-NECMA Counties in CT, MA, Rl, 

Southern NH, and VT

94

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
1993

Middle Atlantic Census Division 

(13

MSA's 

(11 Strata)

Self Representing 

(5 strata)

Non-self 

Representing 

(6 strata)

Hew York, NY

Philadelphia, PA and NJ

Nassau and Suffolk Counties in NY

Pittsburgh, PA

Newark, NJ

Buffalo, Rochester, and Syracuse, NY 

Medium and Small MSA's in NY

Monmouth-Ocean and MiddlesexSomerset-Hunterdon, NJ

Bergen-Passaic, NJ and ScrantonWilkes-Barre, PA

Medium and Small MSA's in PA 

Medium and Small MSA's in NJ and PA

Non MSA's 

(2 Strata)

Non-self

Representing

(2 strata)

Non-MSA Counties in NY 

Non-MSA Counties in PA

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 95
RECS 1993

East North Central Census Division 

(17 Strata)

MSA'S 

(13 Strata)

Self Representing 

(3 Strata)

Non-self 

Representing 

(10 Strata)

Non MSA's 

(4 Strata)

Non-self

Representing

{4 Strata)

Chicago, IL 

Detroit, MI 

Cleveland, OH

Milwaukee, Madison, and 

Appleton, WI

Columbus and Arkon, OH

Indianapolis, Gary, and 

Fort Wayne, IN

Cincinnati and Dayton, OH

Grand Rapids, Flint, Lansing,

Saginaw, and Ann Arbor, MI

Toledo, Youngstown, Canton,

Hamilton, and Lorain, OH

East St. Louis, Lake County,

Peoria, Joliet, and Aurora, V

Small MSA's in IL

Small MSA's in IN and OH

Small MSA's in MI and WI

Non-MSA Counties in WI and 

Northern MI

Non-MSA Counties in Northern OH s.nd 

Southern MI

Non-MSA Counties in Southern OH, 

II, and IN

Non-MSA Counties in Northern 

IL and IN

96

Energy Information Administration/Energy Consumption Series 

Sample; Design for the Residential Energy Consumption Survey
RECS 1993

West North Central Census Division 

(9 Strata)

MSA'S 

(5 Strata)

Self Representing 

(3 Strata)

Minneapolis, MN 

St Louis, MO 

Kansas City, MO-KS

Non-self 

Representing 

(2 Strata)

Medium and Small MSA's in NE, KS, 

and MO

Medium and Small MSA's in IA, MN, 

ND, and SD

Non MSA's 

(4 Strata)

Non-self

Representing

(4 Strata)

Non-MSA Counties in KS and 

Southern IA

Non-MSA Counties in MN and 

Northern IA

Non-MSA Counties in MO

Non-MSA Counties in NE, ND, and SD

Energy Information Administration/Energy Consumption Sarte* 

Sample Design for the Residential Energy Consumption Survey 97
REGS 1993

South Atlantic Census Division 

(20 Strata)

MSA's 

(14 Strata)

Self Representing 

(5 Strata)

Non-self 

Representing 

(9 Strata)

Non MSA's 

(6 Strata)

Non-self

Representing

(6 Strata)

Washington, DC, MD, and VA 

Atlanta, GA 

Baltimore, MD 

Tampa, FL 

Miami, FL,

Norfolk and Richmond, VA 

Charlotte, NC-SC and Greensboro, NC 

Medium and Small MSA's in NC anci SC

Medium, and Small-MSA's in DE, MO, 

VA, WV, and NC

Medium and Small MSA's in SC and Gh

Fort Lauderdale and West Palm 

Beach, Fl

Crlando, Melbourne, and 

Lakeland, FL

Jacksonville, Fort Meyers,

Sarasota, Fort Pierce, and 

Naples, FL

Medium and Small MSA's in Northern 

and Middle FL

Non-WSA Counties in DE, MD, and WV 

Non-MSA Counties in VA

Nca-WSA Counties in Eastern 

Carolinas

Non-MSA Counties in Western 

Carolinas

Non-MSA Counties in GA 

Non-KSA Counties in FL

98

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey
1993

South Central Division 

(8

USA'S

(4 Strata)

Non-self 

Representing 

(4 Strata)

MSA's in TN and AL

MSA's in TN and Northern AL and MS

MSA's in KY and TN

MSA's in Southern AL and MS

Non MSA's 

{4 Strata!

Non-self

Representing

{4 Strata)

Non-MSA Counties in KY

Non-MSA Counties in Southern TN, 

Northern AL, and MS

Non-MSA Counties in KY and TN

Non-MSA Counties in Southern AL 

and MS

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 99
RECS 1993

West South Central Census Division 

(14 Strata)

MSA'S 

(10 Strata)

Self Representing 

(2 Strata)

Non-self 

Representing 

(8 Strata)

Houston, TX 

Dallas, TX

DOUBLE STRATA:

Fort Worth, San Antonio, 

and Austin, TX

New Orleans and Baton Rouge, LA 

Oklahoma City and Tulsa, OK 

Medium and Small MSA's in AR and ot: 

Medium and Small MSA's in LA

Medium and Small MSA's in 

Northern TX

Medium and Small MSA's in 

Southern TX

Non MSA's 

(4 Strata)

Non-self 

Representing 

(4 Strata)

Non-MSA Counties in OK and 

Northern AR

Non-MSA Counties in LA and 

Southern AR

Non-MSA Counties in Eastern TX 

Non-MSA Counties in Western TX

100

Energy Information Administration/Energy Consumption Series 

Samplo Dasign for the Residential Energy Consumption Survey
RECS 1993

Mountain Census Division 

(10 Strata)

MSA'S 

(6 Strata)

Self Representing 

(2 Strata)

Non-self 

Representing 

(4 Strata)

Phoenix, AZ 

Denver, CO

Salt Lake City, UT and Colorado 

Springs, CO

Las Vegas, NV and Tucson, AZ

Medium and Small MSA's Southern half 

of the Division

Medium and Small MSA's Northern half 

of the Division

Non MSA's 

(4 Strata)

Non-self 

Representing 

(4 Strata)

Non-MSA Counties in CO, WY and UT

Non-MSA Counties in NM, NV, ID, UT 

and AZ

Non-MSA Counties in ID and MT 

Non-MSA Counties in AZ, NM, and UT

Energy Information Administration/Energy Consumption Series 

Sample Design for the Residential Energy Consumption Survey 101
RECS 1993

Pacific Census Division 

(17 Strata)

MSA'S

(13 Strata)

Self Representing 

(9 Strata)

Non-self 

Representing 

(4 Strata)

Los Angles, CA

San Diego, CA

Riverside-San Bernardino, CA

Anaheim-Santa Ana, CA

Seattle, WA

Oakland, CA

San Francisco, CA

Sacramento, CA

San Jose, CA

MSA's in the Central Valley of. CA 

Medium and Small MSA's in CA 

Medium and Small MSA's in WA

MSA's in OR

Non MSA's Non-self 

Representing 

(2 Strata)

Non-MSA Counties in WA and OR 

Non-MSA Counties in CA

Mixed

Non MSA and MSA

Non-self 

Representing 

(2 Strata)

Honolulu Hawaii and Non-MSA Count.ie: 

Anchorage Alaska and Non-MSA Count.ie:

102

Energy Information Administration/Energy Consumption Series 

Sampla Design for the Residential Energy Connumption Survey
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