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Residential Energy Consumption Survey (RECS)

1993 RECS Survey Data 2020 | 2015 |2009 | 2005 | 2001 | 1997 | 1993 |

1993 Public Use Data Files (ASCII Format)

WHAT IS RECS?

The Residential Energy Consumption Survey (RECS) is a national sample survey of housing units. The survey collects statistical information on the consumption of and expenditures for energy in housing units along with data on energy-related characteristics of the housing units and occupants. The survey is restricted to housing units that are the primary residence of the occupants; the RECS does not cover vacant housing units, second homes, or vacation units. RECS is conducted by the Energy Information Administration of the U.S. Department of Energy. The RECS was conducted in 1978, 1979, 1980, 1981, 1982, 1984, 1987, 1990, and 1993. For the 1993 RECS, data were obtained for 7,111 housing units. Energy-related characteristics of the housing units and occupants are obtained in an on-site personal interview with the occupants. Energy consumption and expenditures information are obtained from the energy suppliers to the responding households during the Energy Suppliers Survey that follows the household personal interview.


WHAT ARE THE RECS PUBLIC USE FILES?

The 1993 RECS Public Use Files are microdata files that contain 7,111 records, representing housing units from the 50 States and the District of Columbia. Each record corresponds to a single responding, in-scope sampled housing unit and contains information for that unit about the size, year constructed, types of energy used, energy-using equipment, conservation features, energy consumption and expenditures (electricity, natural gas, fuel oil, kerosene, and LPG), and the amount of energy used for five end uses: space heating, air-conditioning, water heating, refrigeration, and other.


WHAT IS THE GEOGRAPHIC LEVEL OF DATA AVAILABLE?

RECS data are available for the four Census regions and nine Census divisions. State-level data are available for the four most populated States (California, Texas New York, and Florida).


WHAT IS THE FORMAT OF THE PUBLIC USE FILES?

The Public Use Files are comma-delimited ASCII files.


HOW ARE THE PUBLIC USE FILES ORGANIZED?

Because of the size of the RECS database, the variables were grouped into 9 files by section of Household Questionnaire:

  1. Section A: Preinterview Observation
    Section B: Housing Type
  2. Section C: Home Heating
  3. Section D: Air Conditioning
    Section E: Water heating
    Section F: Lights
  4. Section G: Appliances
  5. Section H: Conservation Measures and Usage
    Section I: Demand Side Management
  6. Section J: Fuel Used
  7. Section K: Fuel Bills
  8. Section L: Background Information
    Section N: Vehicles
  9. Section M: Program Participation
  10. Characteristics of Energy Supplier Data
  11. Energy Consumption
  12. Energy Expenditures


VARIABLES ON EVERY FILE

Several variables are frequently used in the analysis of residential energy data. These include the type of housing unit, the geographic location of the unit, and weather data for the location of the unit. The nine variables on all 9 files are:

  1. HHID (unique housing unit identifier)
  2. NWEIGHT (household weight)
  3. QMAIL (mail questionnaire identifier)
  4. TYPEHUQ (type of housing unit)
  5. REGIONC (Census region)
  6. DIVISION (Census division)
  7. LRGSTATE (indicator for California, Texas, New York, and Florida)
  8. HDD65 (heating degree-days to 65 degrees for 1993)
  9. CDD65 (cooling degree-days to 65 degrees for 1993)


HOW TO MERGE FILES

Each of these 9 files can be used by itself or be merged with other files. By merging files together, a new file can be created that contains, for each respondent, variables from two or more files. The variable HHID can be used to link the files.


HOW TO USE WEIGHTS

The RECS sample was designed so that survey responses could be used to estimate characteristics of the national stock of occupied housing units. In order to arrive at national estimates from the RECS sample, base sampling weights for each housing unit, which were the reciprocal of the probability of that building being selected into the sample, were calculated. Therefore, a housing unit with a base weight of 10,000 represents itself and 9,999 similar, but unsampled housing units in the total stock of occupied residential housing units. The base weight is further adjusted to account for nonresponse bias. Finally, ratio adjustments were used to ensure that the RECS weights add up to Current Population Survey estimates of the number of households. The variable NWEIGHT in the data file is the final weight.

EXAMPLE 1: SINGLE RESPONSE

The respondent with HHID = 5198 has NWEIGHT = 13,292. Hence this respondent represents a total of 13,292 households. The site of the respondent home was 1,600 square feet. Hence, the respondent contributed 1,600 times 13,292 = 21,267,200 square feet to the estimated national total square footage.

EXAMPLE 2: USING NWEIGHT TO ESTIMATE NUMBER OF HOUSEHOLDS

There were 865, out of the 7,111 RECS respondents, that used fuel oil in their homes (USEFO = 1). Most, but not all, of these households use fuel oil for space heating. The sum of NWEIGHT over these 865 cases is 10,791,313. Hence, the estimated number of households that use fuel oil is 10,800,000.

EXAMPLE 3: USING NWEIGHT TO ESTIMATE PERCENTAGE OF HOUSEHOLDS

The sum of NWEIGHT over all 7,111 cases is 96,631,492. This is also an estimate of the total number of households as of July 1993. Hence, the estimated percent of households that use fuel oil (for any use in the home) is (10,791,313/96,631,492) times 100 equals 11.2 percent.

EXAMPLE 4: USING NWEIGHT TO ESTIMATE TOTAL SQUARE FEET

To estimate total square feet, multiply NWEIGHT times HOMEAREA for the 865 cases where fuel oil is used in the home (USEFO = 1), then sum the product over the cases where USEFO = 1. The resulting estimate is 24,413,335,370 square feet. This should be rounded to 24.4 billion square feet or 24,413 million square feet.

EXAMPLE 5: USING NWEIGHT TO ESTIMATE AVERAGE SQUARE FEET

The sum of NWEIGHT over cases where USEFO =1 is 10,791,313. Hence the estimated average square feet in homes that use fuel oil, is 24,413,335,370/10,791,313 = 2,262 square feet.


MAIL RESPONSES

If the field interviewers were not successful in obtaining a personal interview, a short mail questionnaire was mailed to the housing unit. Variables not on the mail questionnaire were then imputed for the housing unit using a hot deck procedure. There were 115 observations obtained via a mail questionnaire. These 115 records can be identified using the variable QMAIL.


FUEL USAGE INDICATORS

The variables USEEL, USEFO, USEKERO, USELP, and USENG are indicator variables for the use electricity, fuel oil, kerosene, LPG, and natural gas in the housing unit. They are on three files. They were obtained using section J of the questionnaire and they are indicator variables that equal 1 if the households uses the corresponding fuel and 0 otherwise.


HOW ARE THE VARIABLES THAT BEGIN WITH A Z DIFFERENT FROM THE NON-Z VARIABLES?

The "Z variables" are also referred to as "imputation flags." Imputation is a statistical procedure used to fill in missing values for respondents that are otherwise considered to be complete. Missing values for many, but not all, of the variables were imputed in 1997. The imputation flag indicates whether the corresponding non-Z variable was based upon reported data (Z variable = 0) or was imputed (Z variable = 1). There are no corresponding "Z variables" for variables from the RECS questionnaire that were not imputed, variables where there was no missing data, and variables that are not from the questionnaire.


HOW IS THE SURVEY RESPONDENT'S CONFIDENTIALITY PROTECTED?

There are no respondent names and address on these files. EIA does not receive nor take possession of the names or addresses of individual respondents or any other individually identifiable energy data that could be specifically linked with a housing unit. Local geographic identifiers and National Oceanic and Atmospheric Administration Weather Division identifiers are not included on these data files.

In addition, values for HDD65, CDD65, ELECRATE, and UGASRATE were altered slightly to mask the exact geographic location of the housing unit.


LlNKS TO EACH DATA FILE AND SUPPORTING DOCUMENTATION

For each data file, a codebook is provided (both files are in ASCII format). For files based upon the Household Questionnaire, the corresponding section of the questionnaire is provided (PDF format).To view and/or print PDF files (requires Adobe Acrobat Reader) Download Adobe Acrobat Reader .

Note: To DOWNLOAD one of the Text or PDF files below, click on the file of your choice to open it, then select FILE and SAVE AS, save file to your hard drive or a disk.

Microdata Files
by Topic Data Files Codebooks Questionnaire Release Date
File 1: Preinterview Observation and Housing Type TXT TXT Section A and B 07/08/03
File 2: Home Heating TXT TXT Section C 07/08/03
File 3: Air Conditioning, Water Heating, and Lights TXT TXT Section D, E, and F 07/08/03
File 4: Appliances TXT TXT Section G 07/08/03
File 5: Conservaton Measures and Usage and Demand Side Management TXT TXT Sections H and I 07/08/03
File 6: Fuels Used TXT TXT Section J 07/08/03
File 7: Fuel Bills TXT TXT Section K 07/08/03
File 8: Background Information and Vehicles TXT TXT Section L and N 07/08/03
File 9: Program Participation TXT TXT Section M 07/08/03
File 10: Characteristics of Energy Supplier Data TXT TXT 03/13/07
File11: Energy Consumption TXT TXT 03/13/07
File12: Energy Expenditures TXT TXT 03/13/07

Specific questions on this product may be directed to:

Consumption and efficiency data