1. The effects of rotational design and attrition
Abstract:
Rotational design in the Czech EU-SILC has impact on a stability of survey results because these could be biased by replacement of one quarter of the sample, what should be taken into account. This rotational design faces among others a problem of a loss of households in subsequent waves of panel sub-sample. The reason is additional non-response and movement out of the surveyed population (due to movement to collective household, institution or foreign country). This fact could influence some surveyed variables, subsequently some indicators could be biased by attrition. It is necessary to know, which variables are significantly affected by this effect. This potential impact on results requires control of structure of people who do not respond anymore or move out of survey. If this group has not completely random features and shows some specific characteristics in comparison to those continuing in the survey, this finding would be helpful for correction of attrition.
Michaela Brázdilová
EU-SILC workshop on best practices, London
16h September 2015

2. Challenges of rotational design
New independent survey sample:
Challenges of non-response in 1. wave (in 2014: 62,2 %)
Effect on cross-sectional measurements
Long-term panel survey:
Challenges of inter-waves behaviour of households
Out of survey = left the population (O): Death, Migration out of the country, Movement to collective institution
Attrition = total non-response (N): Refusal, No contact, Unable to trace a unit, Information not available
Effect on longitudinal measurements

3. Out of survey population
Inter-waves behaviour of households, 2014
2. wave 2014
3. wave 2014
4.wave 2014
Type
Number of households
Share
Response
Total (R)
1898
93,90%
1758
94,82%
2119
98,15%
Household on the same address
1865
98,30%
1723
98,01%
2080
98,16%
Household on new address 23
1,20% 26
1,48% 25
1,18%
Split-off household 10
0,50% 9
0,51% 14
0,66%
Non-response
Total (N)
105
5,20% 78
4,21%
1,16%
Refusal 58
55,20% 40
51,28% 8
32,00%
No contact (+ administrative reasons)
7,60%
11,54% 1
4,00%
Unable to trace a unit 18
17,10% 12
15,38% 4
16,00%
Unable to response, other reasons 21
20,00% 17
21,79%
48,00%
Out of survey population
Total (O)
0,90%
0,97% 15
0,69%
Moved to collective household or instituion 3
16,70%
16,67% 7
46,67%
All members of household died 11
61,10% 13
72,22%
53,33%
Moved outside the country
22,20% 2
11,11%
0,00%
attrition rate

4. Attrition rate Inter-waves behaviour of households:
Non-response especially between 1. and 2. wave (in 2014: 5,2 %)
Challenges of attrition in 2. wave
Monitoring of development of attrition rate of 2. wave in time

5. Out of survey population
Development of attrition between 1. and 2. wave
Type
Number of households
Share
Response
Total (R)
2237
92,10%
1840
92,56%
1898
93,90%
Household on the same address
2175
97,23%
1805
98,10%
1865
98,30%
Household on new address 54
2,41% 30
1,63% 23
1,20%
Split-off household 8
0,36% 5
0,27% 10
0,50%
Non-response
Total (N)
163
6,71%
127
6,39%
105
5,20%
Refusal
101
61,96% 84
66,14% 58
55,20%
No contact (+ administrative reasons) 1
0,61%
0,79%
7,60%
Unable to trace a unit 32
19,63% 16
12,60% 18
17,10%
Unable to response, other reasons 29
17,79% 26
20,47% 21
20,00%
Out of survey population
Total (O)
1,19%
1,06%
0,90%
Moved to collective household or instituion 3
10,34% 4
19,05%
16,70%
All members of household died 19
65,52%
76,19% 11
61,10%
Moved outside the country 7
24,14%
4,76%
22,20%
Attrition rate decreases slightly in time in the last period, what should have a positive impact on survey results.
Also the number of people, who are out of the survey population, is slightly declining in time.
Response rate is fast 94%, while non-response rate 5,2%.

6. Distribution of people by status in employment
93,6%
92,1%
95,8%
92,3%
75,0%
93,5%
5,8%
7,9%
2,5%
7,7%
25,0%
6,5%
0,6%
1,7%
Response
Non-response
Out of survey
Behaviour of households
Source: SPSS_own calculations

7. Distribution of people by degree of urbanisation
94,8%
92,4%
94,5%
4,6%
6,3%
4,7%
0,5%
1,3%
0,8%
Response
Non-response
Out of survey
Behaviour of households
Source: SPSS_own calculations

8. Distribution of people by income deciles
Response
Non-response
Out of survey
Behaviour of households
Source: SPSS_own calculations

9. Income distribution by household behaviour
Source: SAS_own calculations

10. Effect of rotational design on poverty rates in 1. and 2
Effect of rotational design on poverty rates in 1. and 2. wave of rotational group
Source: MS Excel_own calculations

11. Effect of attrition and weights on Poverty rate of 1. wave in 2013
Rotational group 2013
respondents
all 2013
without N 2013
without N, O 2013
income data
2013
2014
poverty line
weighted by
Effects
effect of attrition
effect of attrition (incl. out of scope)
effect of weights
effect of reported income
effect of poverty line
Poverty rate of 1. wave 2013
9,50%
9,43%
9,38%
9,92%
11,01%
11,08%

12. Effects on development of Poverty rate between 1. wave 2013 and 2
Effects on development of Poverty rate between 1. wave 2013 and 2. wave 2014
Source: MS Excel_own calculations

13. Development of effects on poverty rate in 1. wave in time
Attrition rate
Above poverty line
6,4%
5,9%
5,3%
Below poverty line
9,6%
9,8%
4,7%
Total
6,7%
5,2%
Source: MS Excel_own calculations

14. CONCLUSION
Attrition is one of challenges of survey with rotational design, which should be monitored
Attrition rate tends to slight decrease in time in the last period
Attrition occurs especially in the groups of students, employees, people from intermediate densely populated area and people in higher income deciles
Effect of attrition causes slight decrease of at-risk-of-poverty indicator → monitoring of attrition by people bellow poverty line
Effect of weights and reported income compensate the fluctuations

15. Thank you for your attention!
Michaela Brázdilová