This data set is a subset of synthetically generated real Austrian SES (Structural Earnings Survey) data.
Usage
data(ses)
Format
A data frame with 115691 observations on the following 28 variables.
location
geographical location with levels AT1
(eastern Austria), AT2 (southern Austria), and AT3
(western Austria).
NACE1
economic branch given in NACE (C - O) 1-digit
classification.
size
employment size range in 5 categories.
economicFinanc
form of economic and financial control (levels
A = public and financial control, B = private control).
payAgreement
collective bargaining agreement with levels
A = national level pay agreement or interconfederal agreement,
B = industry agreement,
C = agreement of individual industries in individual regions,
D = enterprise or single employer agreement,
E = agreement applying only to workers in the local unit,
F = any other type of agreement,
N = no collective agreement exists
IDunit
ID for place of employment.
sex
gender with levels female and male.
age
age in age classes.
education
highest education.
occupation
occupation with levels 11 = Legislators and
seniors officials,
12 = Corporate managers,
13 = Managers of small enterprises,
21 = Physical, mathematical and engineering science professionals,
22 = Life science and health professionals,
23 = Teaching professionals,
24 = Other professionals,
31 = Physical and engineering science associate professionals,
32 = Life science and health associate professionals,
33 = Teaching associate professionals,
34 = Other associate professionals,
41 = Office clerks,
42 = Customer services clerks,
51 = Personal and protective services workers,
52 = Models, salespersons and demonstrators,
61 = Skilled agricultural and fishery workers,
71 = Extraction and building trades workers,
72 = Metal, machinery and related trades workers,
73 = Precision, handicraft, craft printing and related trades workers,
74 = Other craft and related trades workers,
81 = Stationary plant and related operators,
82 = Machine operators and assemblers,
83 = Drivers and mobile plant operators,
91 = Sales and services elementary occupations,
92 = Agricultural, fishery and related labourers,
93 = Labourers in mining, construction, manufacturing and transport
contract
type of contract. Levels A = indefinite
duration, employment contract, B = temporary fixed duration
C = apprentice.
fullPart
full-time working time (FT) or part-time employee
(PT).
lengthService
The total length of service in the enterprises
in the reference month is be based on the number of completed years of
service.
weeks
the number of weeks in the reference year to which
the gross annual earnings relate is mentioned. That is the employee's
working time actually paid during the year and should correspond to the
actual gross annual earnings.
hoursPaid
the number of hours paid in the reference month
which means these hours actually paid including all normal and overtime
hours worked and remunerated by the employee during the month.
overtimeHours
the number of overtime hours paid in the
reference month. Overtime hours are those worked in addition to those of
the normal working month.
shareNormalHours
the share of a full timer's normal
hours. The hours contractually worked of a part-time employee are
expressed as percentages of the number of normal hours worked by a
full-time employee in the local unit.
holiday
the annual days of holiday leave (in full days).
notPaid
examples of annual bonuses and allowances are
Christmas and holiday bonuses, 13th and 14th month payments and
productivity bonuses, hence any periodic, irregular and exceptional
bonuses and other payments that do not feature every pay period. Besides
the main difference between annual earnings and monthly earnings is the
inclusion of payments that do not regularly occur in each pay period.
earningsOvertime
earnings related to overtime.
paymentsShiftWork
These special payments for shift work are
premium payments during the reference month for shirt work, night work or
weekend work where they are not treated as overtime.
earningsMonth
the gross earnings in the reference month
covers remuneration in cash paid during the reference month before any
tax deductions and social security deductions and social security
contributions payable by wage earners and retained by the employer.
earnings
gross annual earnings in the reference year.
earningsHour
hourly earnings, being the quotient of monthly
earnings and the number of hours paid in the reference month.
weightsEmployers
sampling weights in the first stage at
employer level.
weightsEmployees
sampling weights corresponding to the second
stage at employee level.
weights
the final sampling weights, which is the product of
weightsEmployers and weighsEmployees.
Details
The Structural Earnings Survey (SES) is conducted in almost all European
Countries, and the most important figures are reported to Eurostat. SES is a
complex survey of enterprises and establishments with more than 10 employees,
NACE C-O, including a large sample of employees. In many countries, a
two-stage design is used where in the first stage a stratified sample of
enterprises and establishments on NACE 1-digit level, NUTS 1 and employment
size range is used, and large enterprises have higher inclusion
probabilities. In stage 2, systematic sampling is applied in each enterprise
using unequal inclusion probabilities regarding employment size range
categories.
The data set in the package consists of enterprise and employees data from 500
places of work. Note that this is a subset of synthetic data set that is
simulated from the original Austrian SES data.
Author(s)
Matthias Templ, Karoline Geissler
Source
This is a synthetic data set based on Austrian SES data from 2006.
References
A. Alfons and M. Templ (2013) Estimation of Social Exclusion Indicators from
Complex Surveys: The R Package laeken. Journal of Statistical
Software, 54(15), 1–25. URL http://www.jstatsoft.org/v54/i15/
T. Geissberger (2009) Verdienststrukturerhebung 2006, Struktur und Verteilung
der Verdienste in Oesterreich, Statistik Austria, ISBN 978-3-902587-97-8.
M. Templ (2012) Comparison of perturbation methods based on pre-defined quality
indicators, UNECE Work Session on Statistical Data Editing, Tarragona,
Spain.