1. Editing and Imputing Income Data in the Integrated Census prepared by Yael Klejman Israel Central Bureau of Statistics
UNITED NATIONS
ECONOMIC COMMISSION FOR EUROPE
CONFERENCE OF EUROPEAN STATISTICIANS
Work Session on Statistical Data Editing
Hague, April 2017

2. The 2008 Population Census Integrated Census:
Use of administrative files for demographic data, mainly the Central Population Registry
Large sample survey (17% of households)
Statistical correction of the addresses provided by the CPR
Collecting socio-economic information

3. Income Data Administrative sources: Advantages:
Income Tax Authority for work income
National Insurance Institute for allowances
Advantages:
Reduced burden on population
Improved accuracy of data

4. Census scheme
Group A
Group B

5. Group A: reported in census as being in annual workforce but not found in Tax File
Missing employers
Missing occupations (caretakers, military personnel)
Rest of population

6. Imputation for Missing Employer
condition
Employer is completely missing from 2008 Tax File
Employee was employed by same employer in 2007
process
Find employee in 2007 Tax file
Adjust salary from 2007 to 2008 by industry
result
Insert into Socio Economic File

7. Missing occupations: caretakers and military personnel
Alternatives dismissed for caretakers:
Cold-deck from Income Survey: absent;
Nearest neighbor from Tax File: socio-economic characteristics not suitable.
Alternative chosen for both:
statistical imputation based on the Income Survey

8. Statistical imputation for caretakers and military personnel
Job extent, occupation
Job extent, occupation, (industry)
Job extent, occupation, (industry), age group

9. Rest of Population
“Nearest neighbor” method using Canceis program developed in Canada
At individual level
Socio-economic variables: job extent, occupation, industry, highest education degree, gender, age group, residence locality, number of children in household, marital status
Separate imputation for institution residents

10. Donor population Donor population: individuals in yearly workforce.
NOT included:
kibbutz members, caretakers, military personnel
Individuals earning highest income percentile of each occupation (2 digits)

11. Group B: reported as not in annual workforce but found in Tax File
73% income from salary
23% non-work related income
Reason: Irregular employment pattern or response by proxy
Decision: include work income
Status added: “has income from work but reported as not in annual workforce”

12. Topcoding procedure Calculate interquartile range at locality level
Define threshold
Calculate interquartile range at locality level
Multiply by factor (urban=4, rural=3)
ID records
Identify records above threshold
Minimum 3 records per locality
Edit
Calculate average of all top earners
Replace income for those records

13. Allowances
Based on Personal Identification Number, allowances were received from National Insurance Institute
Eight types of allowances
Number of months received
Side file used to calculate variables in SEF at individual and household level

14. Results Records in workforce with income in income file 84.9%
Percent
Imputation Type
84.9%
Records in workforce with income in income file
5.3%
Records with income in 2007 Income File
1.1%
Imputation based on Income Survey for military personnel
1.6%
Imputation based on Income Survey for caretakers
1.0%
Nearest neighbor imputation for institution residents- Canseis
6.2%
Nearest neighbor imputation – Canseis
100.0%
Records in workforce

15. Evaluation Difference
Average income of records from Tax Authority (NIS)
Average income of imputed records (NIS)
Age group
29%
2167
2785
Under 20
11%
4870
5400
20-29
2%-
9185
8962
30-39
-2%
10493
10312
40-49
-5%
11164
10623
50-59
-8%
10529
9636
60 +

16. Maintain distribution Maintain statistics
Difference
Average income of Records from Tax Authority (NIS)
Average income of Imputed records (NIS)
Occupation
-7%
14416
13457
Academic professionals
-2%
8280
8077
Associate professionals and technicians 1%
18927
19051
Managers 7%
7255
7755
Clerical workers
19%
5478
6531
Agents, sale workers and services workers 5%
7541
7945
Skilled agricultural workers
-4%
7913
7561
Mechanics, electricians
6404
6257
Painters, tailors, printing workers, workers in food processing
-10%
6864
6171
Drivers, ship deck crews, packaging machine operators, potters and glass makers
4703
4745
Unskilled workers
Maintain distribution
Maintain statistics

17. Evaluation (cont.) Maintain distribution Maintain statistics
Records from Tax Authority
Imputed records
Statistic
8696
8845
Mean
6031
6185
Median
4000
Mode 99 97 CV
8626
8618
Standard deviation
3.3
3.2
Skewness
Maintain distribution
Maintain statistics

18. Future Plans
Examination of Multiple Imputation Method (MI): simultaneous imputation on several variables. The method maintains distribution.
Foreigners living in Israel: inquiring administrative sources and develop models for income data.

19. Thank you!