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2006 August 24-28 Labour statistics The usage of administrative data sources for Lithuanian data of earnings Milda Šličkutė-Šeštokienė Statistics Lithuania.

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Presentation on theme: "2006 August 24-28 Labour statistics The usage of administrative data sources for Lithuanian data of earnings Milda Šličkutė-Šeštokienė Statistics Lithuania."— Presentation transcript:

1 2006 August 24-28 Labour statistics The usage of administrative data sources for Lithuanian data of earnings Milda Šličkutė-Šeštokienė Statistics Lithuania

2 2006 August 24-28 Labour statistics Annual data calculated:  Until 2003 on the basis of complete enumeration of enterprises;  From 2004 on the basis of sample Quarterly Survey of Earnings (QSE) and data of Social Insurance. The main reasons why two surveys with the same definitions used to be performed are the following:  Quarterly data is very important at national level;  Too detailed breakdown of annual data requires census of enterprises.

3 2006 August 24-28 Labour statistics Distribution of coefficients of correlation, in percent Variables in SI Bands of coeff. of corr. Variables in QSE Average number of employees Average number of full-time units Gross remune- ration Hours worked Hours paid Number insured persons < 0.80.0 3.10.0 0.8 – 0.90.01.629.71.6 0.9 – 1.0100.098.467.298.4 Taxable income < 0.82.31.60.00.83.9 0.8 – 0.926.619.50.021.919.5 0.9 – 1.071.178.9100.077.376.6 Days worked < 0.80.0 2.30.0 0.8 – 0.90.0 28.10.00.8 0.9 – 1.0100.0 69.5100.099.2

4 2006 August 24-28 Labour statistics GREG estimator chosen for calculation of annual results 2004 are expressed by the formula: where i – sample; – calibrated weight of k-th enterprise; – variable of interest in k-th enterprise; – sample design weights of k-th element. i s expressed by the formula: where: – vector of auxiliary information; ;

5 2006 August 24-28 Labour statistics Auxiliary variables analyzed:  Number of insured persons;  Gross remuneration;  Days worked. Levels of auxiliary information analyzed:  NACE at section level;  NACE at section level & county. Total 14 GREG estimators were calculated (7 combinations of 3 auxiliary variables multiplied by 2 levels of auxiliary information).

6 2006 August 24-28 Labour statistics Breakdowns required for Annual Survey of Earnings:  NACE (two digits or sometimes even more detailed) & economic sector (total 49 economic activities and 2 economic sectors), it is also the breakdown of QSE;  NACE (section level) & size of enterprise & economic sector (total 15 economic activities, 6 sizes of enterprise and 2 economic sectors);  NACE (section level) & county (total 15 economic activities and 10 counties);  Municipality (total 60 municipalities). Total 488 partly overlapping domains are required. The main problem is breakdown by regions because the quarterly survey does not aim at getting the data which represent regional unit.

7 2006 August 24-28 Labour statistics Concise notations of different GREG estimators: Notation G1, G8 G2, G9 G3, G10 G4, G11 G5, G12 G6, G13 G7, G14 Auxiliary information used Number of employees Taxable income Days worked Number of employees and taxable income Number of employees and days worked Taxable income and days worked All variables G1 – G7 refer to auxiliary information at NACE section level; G8 – G14 refer to auxiliary information at NACE section level & county;

8 2006 August 24-28 Labour statistics Distribution of weights g i for different GREG estimators 2004, in per cent g i G1G2G3G4G5G6G7G8G9G10G11G12G13G14 0.4 and less 0000000226734655 [0.4; 0.8) 1011111771188 9 [0.8; 1.2) 97 96959696949459 7565475252 [1.2;1.6) 222333426 7 258 1.6 and more 000000066879910 Distribution of coefficients of variation for different GREG estimators 2004, in per cent CVHTG1G2G3G4G5G6G7G8G9G10G11G12G13G14 [0; 5)44 4344 70638382758886 [5; 10)1615141514151314 18871165 [10; 30)26 27 26 1113671035 30 and > 1516 1516 5634444

9 2006 August 24-28 Labour statistics Distribution of Statistical Estimates by size of the coefficient of correlation (CV) 2004 CVAll variablesAverage number of employees GREGHTGREGHT Mean9.89.814.47.07.018.5 Median2.52.56.86.81.91.911.9 [0; 5)70.143.776.732.4 [5; 10)13.515.510.014.8 [10; 30)11.425.78.18.131.4 [30; 50)1.21.29.59.51.01.013.3 [50; 100)3.73.75.65.64.34.38.18.1

10 2006 August 24-28 Labour statistics Deviation of estimates of Average Number of Employees 2003 compare to the figures from Annual Survey on Earnings, in %

11 2006 August 24-28 Labour statistics Average number of full-time units Average number of employees Distribution of Statistical Estimates by size of the Coefficient of Variation (CV) 2004

12 2006 August 24-28 Labour statistics Distribution of Statistical Estimates for Average Monthly Gross Earnings by size of the coefficient of variation (CV) 2004

13 2006 August 24-28 Labour statistics Improvement foreseen for annual data 2005:  The auxiliary variables should be used to fix the totals in the enterprise size groups;  Maybe gross remuneration also should be used as auxiliary information;  Regression imputation may be implemented.

14 2006 August 24-28 Labour statistics Usage of data of Social Insurance for other purpose than annual data of earnings:  From 2006 - estimation of data for small enterprises (9 and less employees) in QSE;  Planed for estimation for QSE;  Planed for SES 2006;  Planed for Labour Cost survey 2008.

15 2006 August 24-28 Labour statistics Burden diminished for enterprises because of usage of administrative sources:  Rejection of Annual Survey of Earnings: about 40 000 enterprises and 21 variable, once per year;  Rejection of collecting data from small enterprises (4 or less employees) in QSE: about 1300 enterprises and 35 variables, every quarter;  Future plans to use administrative sources for SES 2006: 4 variables will be dropped, sample size in this survey approximately 8 000 local units and 150 000 employees, every four year.

16 2006 August 24-28 Labour statistics Thank you for your attention !


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