Environmental Economic Survey, 2008
West Bank and Gaza, 2008
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Reference ID
PSE-PCBS-EES-2008-V1.0
Producer(s)
Palestinian Central Bureau of Statistics
Collections
Created on
Sep 14, 2020
Last modified
Sep 14, 2020
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Solid waste collection mean inside the Establishment (ES17)
Data file: Environmental Economic Survey, 2008 Main File
Overview
Valid:
2887
Valid (weighted):
91914.845
Invalid:
0
Invalid (weighted):
0
Questions and instructions
Literal question
Solid waste collection mean inside the Establishment
Categories
| Value | Category | Cases | Weighted | |
|---|---|---|---|---|
| 1 | Municipality open container | 2015 | 65554 |
71.3%
|
| 2 | Municipality closed container | 246 | 5447 |
5.9%
|
| 3 | Establishment open container | 229 | 7912 |
8.6%
|
| 4 | Establishment closed container | 116 | 3475 |
3.8%
|
| 5 | Without container | 281 | 9527 |
10.4%
|
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
Interviewer instructions
Without container (Go to ES20)
Question post text
Where did the solid waste collect before its final disposal?
Description
Universe
All the Palestinian economic establishments, which included in the Economic Series Survey sample in the Palestinian Territory.
Source of information
Palestinian economic establishments
Imputation and derivation
Imputation
Field operations started on 20/04/2008 and lasted until 03/08/2008, the reference period during the data collection process was the last week of the fieldworker existence in the establishment.
Others
Security
Several measures were adopted to minimize the effects of these errors. The interviewers, editors and coders underwent intensive training and were provided with fieldwork manuals to consult when facing any problem.
The data entry program was designed in a way that allows error detection and correction. This applies particularly to logical errors that might not be discovered before data entry operations. A consistency check was also performed to assure accuracy after data entry.
These errors are due to non-response cases as well as the implementation of surveys. In this survey, these errors emerged because of (a) the special situation of the questionnaire itself which depends on type of estimation; (b) diversity of sources (e.g. the interviewers, respondent, editors, coders, data entry operator, etc).
It is important to mention that 5% from the sample of this survey was re-interviewed, and the results of this re-interview were reported by the supervisors. The re-interview shows the variance in estimation by interviewers for quantities of water consumed and solid waste produced, when the interviewer who answers for the main survey questionnaire is different from the one who answers the re-interview questionnaire.
None response rate = Sum of none response cases x 100%
Net sample
= 567 x 100% = 16.4%
3,458
Response rate = 100% - none response rate
= 100% - 16.4% = 83.6%
The none response cases were treated using adjustment groups (strata) and the following equation shows this
Where
Total weights in g group
Total weights over coverage
Total weights responding in the survey
Each unit is given fg value for the interval lies in and finally we get using the following equation
Comparability
The data of the environmental economic survey is comparable geographically and against time; the results when comparing the data between different geographical areas and when comparing the data of this survey with the data of previous rounds were typical and there were no significant differences.
Data Quality Assurance Procedures
Several measures were made to ensure quality control in the survey, such as the training of the fieldworkers on main skills before the start of data collection, and conducting field visits to field researchers to ensure the integrity of data collection, in addition to conducting a re-interview for 5% of the establishments. Audit of questionnaires was carried out before data entry, and then a program was used that does not allow any mistakes during the process of data entry. Data was examined to ensure that they were free from errors not previously discovered. After the receipt of the raw data file, cleaning and inspection of the anomalous values was made, and also inspection of the consistency between the different questions on the questionnaire.
The data entry program was designed in a way that allows error detection and correction. This applies particularly to logical errors that might not be discovered before data entry operations. A consistency check was also performed to assure accuracy after data entry.
These errors are due to non-response cases as well as the implementation of surveys. In this survey, these errors emerged because of (a) the special situation of the questionnaire itself which depends on type of estimation; (b) diversity of sources (e.g. the interviewers, respondent, editors, coders, data entry operator, etc).
It is important to mention that 5% from the sample of this survey was re-interviewed, and the results of this re-interview were reported by the supervisors. The re-interview shows the variance in estimation by interviewers for quantities of water consumed and solid waste produced, when the interviewer who answers for the main survey questionnaire is different from the one who answers the re-interview questionnaire.
None response rate = Sum of none response cases x 100%
Net sample
= 567 x 100% = 16.4%
3,458
Response rate = 100% - none response rate
= 100% - 16.4% = 83.6%
The none response cases were treated using adjustment groups (strata) and the following equation shows this
Where
Total weights in g group
Total weights over coverage
Total weights responding in the survey
Each unit is given fg value for the interval lies in and finally we get using the following equation
Comparability
The data of the environmental economic survey is comparable geographically and against time; the results when comparing the data between different geographical areas and when comparing the data of this survey with the data of previous rounds were typical and there were no significant differences.
Data Quality Assurance Procedures
Several measures were made to ensure quality control in the survey, such as the training of the fieldworkers on main skills before the start of data collection, and conducting field visits to field researchers to ensure the integrity of data collection, in addition to conducting a re-interview for 5% of the establishments. Audit of questionnaires was carried out before data entry, and then a program was used that does not allow any mistakes during the process of data entry. Data was examined to ensure that they were free from errors not previously discovered. After the receipt of the raw data file, cleaning and inspection of the anomalous values was made, and also inspection of the consistency between the different questions on the questionnaire.