The Italian LFS sampling design: recent and future developments

1. 9th Workshop on Labour Force Survey Methodology The Italian LFS sampling design: recent and future developments Loredana Di Consiglio Silvia Loriga Alessandro Martini Rita Ranaldi Rome, 15-16 May 2014

2. Two-stages with stratification of the PSUs (municipalities) in the first stage rotation of the FSUs (households) in the last stage IT-LFS sampling design /1

3. At the first stage… Municipalities are stratified at NUTS III level according to resident population and they are divided into two groups: SR (self-representative) municipalities: have larger demographic size (over a given threshold) each represents one stratum always selected in the sample NSR (non self-representative) municipalities: have smaller demographic size are stratified in groups (strata) having almost the same total population only one municipality for each stratum is selected in the sample, with probabilities proportional to its demographic size IT-LFS sampling design /2

4. At the second stage … Households are randomly selected from the population registers of municipalities drawn at the first stage FSUs are rotated according to a 2-(2)-2 rotation scheme. Households are interviewed during two consecutive quarters. After a two-quarters break, they are again interviewed twice in the corresponding two quarters of the following year IT-LFS sampling design /3

5. Sampling design: household rotation scheme

6. Leaving unchanged the general structure of the sample, in 2012 sampling design has been revised for the following main reasons: the previous sample was designed in 2001-2002, considering the target variables estimated at that time by the quarterly LFS and the frame information for stratification referred to 2002 several changes occurred in the boundaries of the administrative units such as municipalities and provinces to further improve the monthly representativeness of the sample, considering the high relevance of monthly LFS estimates budget constraints forced to reduce the sample size Sampling design revision /1

7. Sample size after revision Every quarter 71,536 theoretical sample households (average sampling rate: 1/350) allocatedin more than 1,000 sample municipalities (about 1 out of 7)

8. The following methodological and operational constraints have been taken into account: Eurostat precision requirements (Reg.577/98), but also additional constraints for national purposes have been considered the unemployment figures considered as target variables for the evaluation of precision requirements are referred to the pre-crisis period the information on non responses has been considered when distributing the sample units among the territorial units the monthly distribution of the sample guarantees that each month is representative of the whole national territory the new selected PSUs have to overlap as more as possible with the previous PSUs in order to minimize the impact on the fieldwork (and on the final estimates) a random rotation of the PSUs has to be applied every year to maintain the sample updated over time Sampling design revision /2

9. Distribution of the sample over space Because of the national precision requirement about unemployment estimates in NUTS 3 domains, the distribution of the sample is not proportional to the demographic size of the domains Minimum, mean value and maximum of resident population, unemployment rate, quarterly sample size and inclusion probabilities in NUTS 3 domains The sample deviates from the optimal sample we should have obtained considering just Eurostat NUTS 2 constraints. In any case, Eurostat constraints are satisfied.

10. The quarterly sample size is uniformly distributed among the 13 weeks, each stratum is observed at least in 3 weeks per quarter and the monthly representativeness of the sample is guaranteed The largest PSUs are in the sample all the 13 weeks of the quarter Other PSUs (among them also some chief towns at NUTS3 level) are in the sample just 3 weeks per quarter, assigning them reference weeks that are triplet of weeks in which the distance between them is 4 weeks: 1-5-9 or 2-6-10 or 5-9-13 and so on Distribution of the sample over time /1

11. The months are not fixed, but they are composed by a number of weeks that is variable (4 or 5) and depends on the number of Thursdays falling in each solar month Distribution of the sample over time /2 Week 5 may be included into months 1 or 2 and week 9 may be included into months 2 or 3 Some PSUs, to which the weeks 5 or 9 have been assigned, may fall into different months In the sample revision we guaranteed that the chief towns in NUTS 3 domain, observed just 3 weeks per quarter, are not to be observed neither in week 5 neither in week 9

12. Aim: to minimize the impact on the fieldwork (changing all the municipalities, or the majority of them, would have meant to recruit and to train a lot of new interviewers, with evident effects on the fieldwork and risks on the quality of the final estimates) Method: use of Permanent Random Numbers (PRN) applying the method suggested by Ernst (2004) Results: 831 municipalities, about 75% of the PSUs selected according to the new design, overlapped with the previous PSUs Maximum overlapping of old and new PSUs

13. Aim: to maintain the sample updated over time and to reduce the statistical burden, in particular for the households living in municipalities with a small number of residents Method: Probabilistic rotation by applying permanent random numbers (PRN) and constant shift method (Brewer et al. 1972, Ohlsson 1995) Results: in 2014, 143 municipalities have been rotated, about 13% of the PSUs that were sample in 2013, almost all the municipalities with less than 1,000 inhabitants and nearly three out of four municipalities of 1,001-2,000 inhabitants Rotation of PSUs of small demographic size

14. The new sample has been gradually introduced starting from the first wave of 2012Q3. For 5 quarters, until 2013Q3, old and new sampling designs were overlapped The estimation and analysis of variance procedures have been reviewed assuming that the two different sub-samples are independent The comparability of the accuracy between the two designs is not simple for the wide variations in the estimates due to the current economic situation and to usual seasonal effects as well observed in this period of 15 months The analysis was conducted using regression models that fit sampling errors, in order to obtain estimates of sampling errors independently by the observed phenomena, even with an approximate evaluations of the errors Accuracy evaluation of the two sample designs /1

15. Accuracy evaluation of the two sample designs /2 Graph 1 - Comparison of regression model of sampling errors for the new and old sample design of IT-LFS

16. Accuracy evaluation of the two sample designs /3 Graph 2 - Difference of coefficient of variation between old and new IT-LFS sample design by Nuts II level

17. Future perspectives • Istat has undertaken its process of renewal with the: • transition to CAPI mode of several PAPI surveys • integration of the Trips and Holidays Survey as module into HBS • introduction of web in the surveys on PHD and on high school graduates Carrying out several CAPI sample households surveys together with the new Population Rolling Census makes necessary to develop a coordinated approach to obtain harmonized sampling designs and to optimize the distribution of the sample over space and time

18. Thank you for your attention