Kandidatuppsats - Statistiska Institutionen

Transkript

Kandidatuppsats
Statistiska institutionen
Bachelor thesis, Department of Statistics
Nr 2013:5
Design and quality of LFS in
three countries- a comparison
Design och kvalitet av AKU i tre länder- en
jämförelse
Bahar Acar och Soma Bedri
Självständigt arbete 15 högskolepoäng inom Statistik III, VT 2013
Handledare: Lars Lyberg
2
Abstract
LFS is a panel survey that is conducted in many countries. Since LFS is relevant to each
country's labor force status it is important that this survey is accurate. In this thesis, we
check the design and quality of the LFS in three different countries. These countries are
Sweden, Australia and the United States. These countries differ in resources, survey
climate and culture. We make comparisons and checks of differences in methodology
used in the three countries.
What we come up with is that the implementation of LFS in respective country is quite
similar. The main difference between the countries is the non-sampling errors that occur
in this type of panel design and implementation. What is most striking is the level of
non-response that differs significantly between the countries. We also examine the
measures that are taken to reduce these types of errors.
Other possible external factors that can also affect classifying the individuals in the LFS
are also addressed.
Key words: Panel survey, classification, proxy, nonresponse, non-sampling error and
reference weeks.
Sammanfattning
Arbetskraftsundersökningen (AKU) är en panel undersökning som förekommer i ett
flertal länder. Då AKU är av betydelse för varje lands arbetskraftsstatus måste
undersökningen vara tillförlitlig. I denna uppsats undersöker vi design och kvalitet i tre
olika länder. De länder vi valt att undersöka är Sverige, Australien och U.S.A. då de
skiljer sig åt i resurser, klimat och kultur.
Vi jämför och studerar skillnader i metodologin bakom de metod papper som varje land
tillhandahåller. Vi finner att genomförandet av AKU i respektive land är snarlika. Det
som främst skiljer länderna åt är de icke- urvalsfel som förekommer i denna typ av
panel undersökningar. Det som är mest utmärkande är nivån på bortfallet som skiljer sig
markant mellan länderna. Vi studerar även de åtgärder som görs för att minska dessa
typer av fel.
Andra möjliga externa faktorer som kan påverka klassificeringen av individer i AKU är
något vi också tar upp.
Nyckelord: Panel undersökning, klassificering, indirekta intervjuer, rotation, bortfall,
icke- urvalsfel och referens veckor.
Preface
Firstly, we would like to thank our supervisor Lars Lyberg for his patience and
guidance. Employees of the U.S. Bureau of Labor Statistics, the Australian Bureau of
Statistics, Elisabet Andersson, Jan Hörngren and Anna Broman at Statistics Sweden are
individuals we want to thank. They have shown us great interest and involvement in
answering our questions.
Table of contents
1. Introduction……………………………………………………………………. …….7
1.1 Purpose ............................................................................................................... 7
1.2 Restrictions ...................................................................................................... 7,8
2.
LFS..…………………………………………………………………………………...Fel
! Bokmärket är inte definierat.
2.1 Terms and definitions ......................... Fel! Bokmärket är inte definierat.,9,10
2.2 Possible error sources .................................................................................. 10,11
3. Design and quality of the LFS………………………………………………………..
11
3.1 Measurements and definitions.......................................................................... 12
3.1.1 Sweden ............................................................................................................. 12
3.1.2 Australia ...................................................................................................... 12,13
3.1.3 The United States ............................................................................................. 13
3.1.4 Comparison ................................................................................................. 13,14
3.2 Population and objects ..................................................................................... 14
3.2.1 Sweden ............................................................................................................. 14
3.2.2 Australia ...................................................................................................... 14,15
3.2.4 Comparison ................................................................................................. 15,16
3.3 Frame and sample design ................................................................................. 16
3.3.1 Sweden ............................................................................................................. 16
3.3.2 Australia ........................................................................................................... 17
3.3.4 Comparison ...................................................................................................... 18
3.4 Nonresponse ..................................................................................................... 18
3.4.1 Sweden ........................................................................................................ 19,20
3.4.2 Australia ........................................................................................................... 20
3.4.3 The United States ........................................................................................ 21,22
3.4.4 Comparison ................................................................................................. 22,23
3.5 Data collection and coding ............................................................................... 24
3.5.1 Sweden ............................................................................................................. 25
3.5.2 Australia ........................................................................................................... 25
3.5.4 Comparison ................................................................................................. 26,27
3.6
3.6.1
3.6.2
3.6.3
3.6.4
3.7
3.7.1
3.7.2
3.7.3
3.8.4
3.8
3.8.1
3.8.2
3.8.3
3.8.4
Estimation procedures ...................................................................................... 28
Sweden.............................................................................................................. 28
Australia....................................................................................................... 28,29
The United States...................................... 2Fel! Bokmärket är inte definierat.
Comparison ............................................... 2Fel! Bokmärket är inte definierat.
Measurment error ................................ 2Fel! Bokmärket är inte definierat.,30
Sweden.............................................................................................................. 30
Australia............................................................................................................ 30
The United States.............................................................................................. 30
Comparison ....................................................................................................... 31
Reference weeks ............................................................................................... 31
Sweden.............................................................................................................. 31
Australia............................................................................................................ 32
The United States.............................................................................................. 32
Comparison ....................................................................................................... 32
4. External factors and comparability………………………………………………..32
4.1 Labor market programs ............................................................................... 32,33
4.2 Education ..................................................................................................... 33,34
5. Conclusion………………………………………………………………………...34
References…………………………………………………………………………...35
1 Introduction
In our thesis, we have chosen to examine how comparable international statistics are in
terms of the Labor Force Survey (LFS). The LFS is a survey that describes the
development of the labor of its people within a country. LFS produces monthly,
quarterly and annual statistics with an emphasis on both the number and proportion of
people employed and unemployed. This is also the only source of continuous data on
the overall unemployment rate and provides the official unemployment rate. Which
people are included in this type of survey? This varies between countries. In Sweden
people aged 15 – 74 are included in the sample while in Australia they are interested in
people aged 15 old and older and in the U.S. they include people who are 16 years and
older in the sample.
We have chosen to present the methodological differences in LFS in three countries and
examine whether they are different across countries or not. The countries that we
selected for our study are Sweden, Australia and the U.S. We chose these countries
since they are far from each other and differ in resources, politics and also culture. We
will review and discuss possible methodological differences and report quantitative as
well as qualitative differences that are meaningful, including differences in the
definitions. More in-depth interesting methodological issues that are valuable for the
production of statistics on this type of surveys are also presented.
We also examine whether Sweden, Australia and the U.S. follow any agreed
international frameworks. Are some countries more different than others in this context?
The goal of this thesis is to discuss any uncertainties regarding methodology design in
LFS between these three countries. Hence contribute to a better understanding of the
differences in the implementation of LFS.
1.1 Purpose
The purpose of this thesis is to compare the methodological design and quality in LFS
between Sweden, Australia and the U.S. Most of the comparisons are based on LFS
documents published by the respective countries statistical bureaus and also survey
methodology papers that are published for each country by International Labor
Organization (ILO) and Eurostat together with other scientific sources.
1.2 Restrictions
Since the overall levels of the unemployment rate differ between Sweden, Australia and
the U.S there are various factors that may be the underlying reasons for this. Such
differences may be due to labor market policy, labor laws, transfer systems and
demographics. But we will not focus on these types of issues in this thesis.
We have limited our thesis to dimensions and definitions that are of interest to us such
as, measurements and definitions, population and objects, frame sample design,
nonresponse, data collection and coding, estimation procedures, measurement errors
and reference weeks.
Labor market programs and education are often directly linked to institutional
differences and is briefly discussed on how they affect the comparability. See chapter 4.
In the United States LFS is called the CPS (current population survey).
2 LFS
LFS is a survey carried out regularly in many countries including these three. The aim is
to describe the development of the labor market for the entire population of a specific
age group and this age range varies among countries. In Sweden, the target population
is people between 15-74 years old, in Australia 15 years old and older and in the U.S.
16 years old and older.
LFS produces statistics with an emphasis on both the number and proportion of people
employed and unemployed. It is the only source of continuous data on the overall
unemployment rate and these data also represent the official unemployment rate. The
results of the surveys are used in conjunction with other labor market statistics as a basis
for planning and decision-making for the government.
The statistics produced by the LFS are subject to international coordination and is based
on the International Labor Organization´s (ILO) recommendations and the convention
of labor statistics. The surveys are then adapted to international requirements.
2.1 Terms and definitions
Within the concept of LFS, individuals are classified in the sample. Individuals are
either employed, unemployed or not in the labor force. Below you get a more visual
idea of what this means.
Figure 1: Classification of individuals
Source: Self-conducted
To be classified as employed, the requirement is that one must have performed at least
one hour of work in a specific week called the reference week.
Whether this person is employed, self-employed or an unpaid helper in a company
belonging to the family or another member of the same household, this individual is still
classified as employed. Persons who were temporarily absent from such work during
the reference week is also included in this classification, whether the absence is paid or
not.
To be classified as unemployed, it is required that you were not employed during the
reference week. Additionally, you should have looked for work in the past four weeks,
in other words the reference week and three weeks back and would have been able to
work during the reference week. Unemployed includes persons who are not actively
looking for work, but who have a job to start within three months, provided that they
would have been able to work during the reference week or were waiting to start a new
job within four weeks.
Persons not employed nor unemployed are classified instead as not in the labor force. In
other words, the survey first determines if a person is employed. If this is not the case,
you go on to see if the person is unemployed. If the person does not meet the conditions
above then classify him/her as not in the labor force.
The employment rate is calculated as the proportion of the employed population, while
the unemployment rate is the number of unemployed relative to the number of persons
in the labor force. Overall, Sweden, Australia and the U.S. all define individuals who
are employed and unemployed similarly according to ILO’s methodology papers
(2011). Below you can see the definition for the unemployment rate:
Definition 1: The unemployment rate
(Source: Self-made)
The unemployment rate is based on the number of unemployed, but also on the number
of persons in the labor force. Sweden, Australia and the U.S. and most other countries
classify individuals who are in education as employees and this can also have an effect
on the size of the labor force distribution. In the diagram below the unemployment rate
chart for Sweden, Australia and United States, and seven other countries are shown.
Diagram 1: Unemployment rates, 10 countries 2011-2013
(Source: BLS, 2011-2013)
The countries' unemployment rates published in 2011-2013 gave difference in
performance and value of the relative number of unemployment. The results differ
significantly for Sweden, Australia and the U.S.
Sweden had in 2011-2013 an unemployment rate of about 7 percent, Australia 5 percent
and the U.S around 9 percent. Japan have an unemployment rate around 4 percent
which is pretty similar to Australia while the United Kingdom have an unemployment
rate around 8 percent which is close to Sweden and the U.S unemployment rate. The
difference in unemployment rates between countries may be due to various factors
within the country. If the share of employed persons is higher domestically then the
unemployment rate will drop. The differences in unemployment rates may be due to
institutional differences, the education system structure or differences in classifying the
individuals in the LFS. The length of the unemployment period may also vary from
country to country and may also have an effect on the unemployment rate within each
country. As we see, the unemployment rates between Sweden, Australia and the U.S is
quite comparable. The differences may be in countries' definitions, measurement
methods and nonresponse rates, more of this in Chapter 3.
2.2 Possible error sources
In order to understand the design of a sample survey and what aspects of this that may
affect the quality, here is an overview of how such a study is done. We will also briefly
give an introduction to the most common error sources associated with the different
stages in a survey. How these differs between the countries are described further in
Chapter 3.
The goal of a survey is to provide overall measures of the properties of the objects in a
particular target population. The objects may include individuals, households or
businesses. When carrying out a sample survey the process begins with defining a target
population whose properties you want to describe by the survey. If countries for some
reason use different target population this means that it describes the different
populations in different countries, which in turn indicates that the statistics are less
comparable. Countries also have to choose a sampling frame, which reflects the target
population. Often some type of registry is used at this stage of the survey. These
registers may include population registers, housing registers or address registers. If the
frame does not exactly cover the intended target population, this can lead to over or
under-coverage, referred to as coverage error (Marsden & Wright, 2010).
The data collection method may vary depending on what object you want to measure.
This may involve personal visits, telephone interviews and online questionnaires. How
one should be carrying out a data collection is always a matter of quality and cost, the
goal is to keep the nonresponse and measurement error and other errors as small as
possible given the survey budget.
Measurement error may be due to lack of interviewers training and that may influence
the respondents answers, that the sample person misunderstood the questions or that the
interview did not take place directly with the sample person but with another household
member.
After the data collection is complete, data must in most cases be processed before it can
be analyzed. Here a risk of processing errors may occur.
3 Design and quality of the LFS
In this chapter we will compare the design and quality of the methodological
characteristics regarding LFS. In this context, quality can be defined by the following
five dimensions. These are content, accuracy, timeliness, comparability and coherence,
and availability and clarity (Biemer & Lyberg, 2003). Content mainly refers to
statistical characteristics, e.g. target population, reference period. Accuracy concern
sources of uncertainty and its effects on statistics.
Timeliness covers the time aspects that play a part in how well the statistics describes
the current situation. Comparability and coherence concerns possibilities for
comparison over time and between groups and how well different statistics can be used
together. Availability and clarity concerns statistical physical availability and its
intelligibility. The quality report can be reported once these components have been
established and defined correctly. This framework for quality declaration is the one used
for official statistics by Statistics Sweden (SCB). We have analyzed the quality
declaration for each country and compared them with each other. Sweden, Australia
and the U.S. all have similar definitions on the concept of quality in their statistical
procedures. Our purpose here is to examine some quality components that are
explanatory for a good quality in the LFS and examine similarities and differences
between the countries. These components may have several sub-components that we
will highlight and we will also begin each section with a brief introduction of the topic.
3.1 Measurements and definitions
In the LFS there are measurements that may be more significant than others. The key
measurements of LFS are the number of employed and unemployed, number of
individuals inside and outside the labor force, employment and activity rate and at last
the employment level in the country. These variables are the basis of the measurement
and definitions for such a survey. Below you have a comparison of Sweden, Australia
and the U.S. measurements and definitions.
3.1.1 Sweden
In Sweden the statistical system is consistent with the EU regulations, ILO and Eurostat
when LFS is conducted. The definitions and measurements for Sweden in the
methodology report (ILO 2011) is summarized. Only the key measurements are
highlighted.
Current employment refers to individuals 15-74 years old who during the reference
week worked for one hour or more either as a paid hired employee, self-employed or as
an unpaid helper in a family business or as helper in a business owned by household
members. Employment also refers to individuals who were temporarily not at work and
had an enterprise or another job on the side. Reference period for employment is the
latest full calendar week preceding the interview (moving).
Current unemployment refers to individuals who during the reference week was not
working but were available to work and are actively seeking for a job. Reference period
for seeking work is within four weeks, the three weeks preceding the reference week
and the reference week. The reference period for availability for work include the
reference week and the following two weeks. Unemployment also refers to individuals
that found a job and starts within three months or begin within 14 days from the end of
the reference week.
Underemployment refers to working time and individuals who are employed but are
working less than they would like to and are available to work more during the
reference week or within 14 days from the last day of the reference week.
3.1.2 Australia
Australia is a founding member of the ILO and follows the recommendations for LFS.
The definitions and measurements for Australia in the methodology report (ILO 2011)
is summarized.
Current employment refers to individuals aged 15 years and older who during the
reference week worked for one hour or more for a salary in a business or farm or selfemployed. This also includes individuals who worked for one hour or more without
salary for family business or farm or were an employee but were away from work for
less than four weeks up to the end of reference week. Reference period for employment
is the latest full calendar week preceding the interview (moving).
Current unemployment and definition of unemployment is persons who were not
employed during the reference week. These persons had actively looked for full time or
part time work at any time in the four weeks up to the end of the reference week, and
were available for work during the reference week. It also refers to individuals who
were waiting to start a new job within four weeks from the end of the reference week,
and could have started in the reference week if the job had been available then. The
reference period for seeking work is four weeks, the three weeks preceding the
reference week plus the reference week. Reference period for availability for work is the
latest full calendar week preceding the interview (moving).
Underemployment is related to working time. The definition of underemployment is an
individual who want to and are available for more hours of work than they currently
have. A person employed part-time who want to work more hours and are available to
start work with more hours, either in the reference week or in the four weeks subsequent
to the survey; or persons employed full-time who worked part-time hours in the
reference week for economic reasons. It is assumed that these people wanted to work
full-time in the reference week and would have been available to do so.
3.1.3 The United States
The U.S. are following the ILO recommendations for LFS. The definitions and
measurements for the U.S. in the methodology report (ILO 2011) is summarized.
Current employment is defined as an employed individual who are working at a paid
job or business for at least one hour during the reference week, or are working without
pay in a family business for 15 or more hours during the reference week or held a job or
owned a business from which they were temporarily absent. Reference period for
employment is the week containing the 12th of the month (fixed).
Current unemployment and the definition of unemployment is individuals who had no
employment during the reference week but were available for work at that time except
for temporary illness, and had made active efforts to find employment sometime during
the four week period ending with the reference week. Persons who were waiting to be
recalled to a job from which they had been laid off need not be actively looking to be
classified as unemployed. Reference period for seeking work is the four weeks
preceding the interview date (moving). Reference period for availability for work is the
week containing the 12th of the month (fixed).
The definition of underemployment is related to working time. It refers to those who
worked part time for economic reasons, that is, people who wanted a full time job but
worked less than 35 hours during the reference week for reasons such as slack work or
the inability to find full-time work.
3.1.4 Comparison
All three countries follow the ILO recommendations for LFS, in which Australia is also
a founding member. Comparing the definitions across the countries indicates no
significant differences overall.
The reference period for availability to work differs a bit across the countries. Also
underemployment that refers to employed persons differs. In Sweden it refers to persons
who are available to work additional hours within 2 weeks after the end of the survey
period, whereas in Australia it refers to persons within 4 weeks including those who
otherwise work full time but for some economic reasons have worked part time during
the reference week. To be counted as an underemployed, in the U.S., you must have
been working less than 35 hours per week in all jobs.
3.2 Population and objects
When a survey is carried out one must first define a target population, i.e. the
population of individuals or households you want to describe.
The observed population is individuals living in private households in each country. If it
is only possible to use private households, then individuals living in collective
households who have a connection to a private household are then also included and
counted as part of the household. Inductees and even individuals who do community
service are generally excluded in the reporting of results, but is still widely used in the
target population at least when living in private households.
3.2.1 Sweden
In Sweden, the data collection process is made continuously every week and covers the
entire country and population. The survey covers residents of the country who are
present or temporarily absent but who are resident in the country with an up-hole state
or have the intention to stay in Sweden for over a year. This leads to that certain groups
of immigrants without citizenship are excluded in the study because they are classified
as non-permanent residents in the country. These individuals are not included in the
population register within the country and therefore not included in the sampling frame
either.
The definition of household and household members is that a household consists either
of one person who lives alone or with a group of other persons which live at the same
address and share housekeeping money. Usual household members who are temporarily
absent are enumerated also in the survey and the population should be in the age groups
between 15 and 74 years old.
3.2.2 Australia
In Australia the periodicity of data collection is ongoing monthly and the geographical
coverage of the data collection is the whole country and the whole population is
covered, also here excluding armed forces and foreigners. The survey covers only the
usual residents presented. The definition of a usual resident is that residents are defined
using the '12/16 month rule', which means incoming overseas travelers who are not
currently counted in the population must be resident in Australia for a total period of 12
months or more, during the 16 month follow-up period to then be included in the
estimated resident population. The '12/16 month rule' therefore takes account of those
persons who may have left Australia briefly and returned, while still being resident for
12 months out of 16. Similarly, it takes account of Australians who live most of the time
overseas but periodically return to Australia for short periods.
The definition of household and household members is that a household is defined as a
group of one or more persons in a dwelling. Usual household members who are
temporarily absent are enumerated in the survey regarding labor related questions. The
age coverage is that the labor related questions of the survey relate to the population of
15 years old and over.
In the U.S. the periodicity of data collection is monthly ongoing as well, and the
collection of data covers the entire country and population excluding armed forces,
persons living in institutions and the homeless people.
The U.S.’s definition of a usual resident is the place where a person usually lives and
sleeps. Household members are persons who were present or temporarily absent, whose
usual place of residence at the time of interview is the sample unit. The CPS is not
limited to the U.S. citizens. It also includes foreign citizens residing in the U.S. who are
not living in embassies. The labor related questions of the survey relate to the
population aged 16 years and over.
3.2.4 Comparison
The data collection is quite similar between the U.S. and Australia as it is done monthly,
while for Sweden it is done every week where the whole country and population are
covered. In Australia the armed force and foreigners are excluded, and in the U.S.
armed force, persons living in institutions and homeless people are excluded.
From the above information it can be concluded that the U.S. is more specific in the
classification and definition of a resident. In Sweden it is enough to have a residence
permit and be included in the population register. In Australia they are more ´´flexible´´
about the definition of usual resident.
The definition of the household and household members is quite similar across the three
countries. For Australia, what is included in the household is described more in detail.
In the U.S a different methodology is used for establishing household/no household
membership. The unit of observation is a household address, not a person, and being a
household member is not confined to the U.S. citizens only.
Comparing the labor related questions of the survey, Sweden’s population relates to an
interval 15-74 years old, Australia to the population of 15 years old and over, and the
U.S. to the 16 years old and over.
The main population of the LFS is private households. There may be some effects on
subgroups, such as foreign born, which might to greater extent live in certain types of
collective households. Possibly, it may also have an impact on the student group, as not
all people in boarding schools are connected to a private household. In countries that
cannot distinguish between them the number of unemployed and employed are slightly
higher than in the other two countries.
Another thing worth emphasizing is that the U.S. studies the employed from age 16 into
account compared to Sweden and Australia. This gives a slightly lower estimate of the
unemployment rate. But since these are relatively few employees among 15 year olds,
the effect of excluding them is not so significant.
3.3 Frame and sample design
LFS in the various countries is based on a probability sample from a sampling frame,
i.e. a register or something equivalent. The quality of the sampling frame is based on
how well it covers the target population for the survey. The problem with this is that it
can lead to over-coverage of individuals who do not belong to the target population,
such as the deceased or emigrated. The opposite problem is under-coverage. If
individuals belonging to the target population are not in the frame, for example, migrant
individuals who intend to stay in the country for more than a year, then this can cause
coverage bias.
The access to registers differs across the countries. Individual selection of persons can
be conducted only if there is a reliable register of individuals, which many countries
don’t have. Household samples can be made both on the basis of lists of individuals and
registers of addresses or dwelling units. General frames are population or last census or
the list of addresses used in the latest census. There are also countries that use postal
databases.
LFS is a panel survey with rotating samples, which means that sample persons, is
included in the survey on several occasions. The selection process can be described as
stratified systematic sampling with rotating panel sample.
3.3.1 Sweden
Sweden use a sampling frame in form of a population register, this sampling frame is
updated daily in the country. The sample is stratified and variables used for
stratification is geographic region, socio-economic characteristics, age and sex.
Ultimate sampling units are individuals and sample size is 29500 ultimate sampling
units
per
month.
(ILO, 2011 & SCB, 2013)
In Sweden’s rotation procedure, a quarter consists of three different samples, one for
each month of the quarter. Each sample is divided into eight different rotation groups.
Rotation scheme is structured such that the 7/8th of each of the three monthly samples
during the quarter recur every three months and 1/8th of the sample are replaced by new
sample persons.
This means that each person is included in the survey a total of eight times over a two
year period. People who are chronically ill or admitted for care more than a year
forward, and senior citizens over 64 who are not employed or job seekers is interviewed
beyond the first interview only once per years.
3.3.2 Australia
The sampling frame for Australia is an area-based list of dwellings, partly based on the
Population Census. The sampling frame is updated every 5 years. Variables used for
stratification is geographic region. Ultimate sampling units are dwellings, in a sample
size of 29000 ultimate sampling units per month (Linacre, 2007).
Households selected for the LFS are interviewed each month for eight months, with
one-eighth of the sample being replaced each month. The matched rotation group
method calculates monthly movements using the 7/8th of the sampled dwellings that are
common between consecutive months under the LFS rotation scheme. This method
produces an increase in employment (seasonally adjusted) over the last four months of
about 30,000 less than the published estimate.
However, some caution should be used in interpreting matched rotation group estimates,
as they have a tendency to underestimate employment growth. If an adjustment were
made for this effect, the estimated change in employment from the matched rotation
group estimate would be closer to the published figure.
The U.S use a sampling frame called Master address file based on Decennial Census
and this sampling frame is updated continually. The sample is a stratified sample and
variables used for stratification is geographic region, urbanisation, population size of
locality, socio-economic characteristics, labour force characteristics and other
characteristics that are highly correlated with unemployment (ILO, 2011).The CPS
sample is a probability sample and consist of several independent samples in each state.
Ultimate sampling units are dwellings with a sample size of 60000 ultimate sampling
units per month.
In the U.S rotation procedure they use eight interviews that are dispersed across 16
months and rotation scheme follows a 4-8-4 pattern. (Current Population Survey,
Design and Methodology, Technical Paper 66, October 2006) in CPS a housing unit is
interviewed in 4 consecutive months, not in sample for the next 8 months, interviewed
the next 4 months and then retired from sample. The rotation scheme is designed so
outgoing housing units are replaced by housing units from the same hit string which
have similar characteristics.
In any single month, one-eighth of the sample housing units are interviewed for the
first time another eighth is interviewed for the second time and so on. The sample for 1
month is then composed of units from two or three consecutive samples. One new
sample designation-rotation group is activated each month. The new rotation group
replaces the rotation group retiring permanently from sample. One rotation group is
reactivated each month after its 8-month resting period. The returning rotation group
replaces the rotation group beginning its 8-month resting period.
3.3.4 Comparison
The sampling frame for Sweden and the U.S are updated continually while in Australia
it is only updated every 5 years. Australia is using an area based list of dwellings partly
based on the population census, Sweden is using the population register as sampling
frame and the U.S. uses Master address file (MAF) based on decennial census.
All three countries uses stratified sampling with similar variables, but U.S. uses a few
more samples. Sweden differs from the two countries in a way that it uses a sampling
frame where the ultimate sample units are individuals.
Individual sample can only be made if there is a reliable register of individuals, which
several countries have a lack of. Household sample can, however, be made both on the
basis of lists of individuals and registries of addresses or dwelling units. Regular frames
are population registers or latest census or the list of addresses used in the latest census.
The design of the sample frames in turn affects the ability of countries to collect data
even for collective households.
The rotation procedure in each country varies across countries. The main difference is
that the U.S rotation procedure use eight interviews that are dispersed across 16 months
and rotation scheme follows a 4-8-4 pattern. (Current Population Survey, Design and
Methodology, Technical Paper 66, October 2006).
3.4 Nonresponse
There are two major types of non-response but since LFS is a sample survey the item
nonresponse rate is one of the contributing factors affecting comparability of the results.
Item non-response refers to the absence of any requested variable to be collected for a
sample person. Sometimes unit nonresponse is present referring to only certain values
missing for the sample person.
In LFS nonresponse is considered to be problematic. If the person selected differs in
various ways from those participating, there is a risk that the estimates are skewed.
Which in turn results in biased results and increased variances, since the sample the
estimates are based on becomes less than planned (Lundström & Särndal, 2001)
There is information by uncertainty figures for this increased uncertainty in the
estimates, which itself don’t have any impact on the comparability.
The purpose is to highlight if the division between the unemployed and employed
differs between the nonresponse and the respondents, as this may lead to bias in the
estimates.
However, if such biases are present the comparability may be affected. The main reason
for non-response is that either the sample person could not be reached for interview or
the sample persons refuses to participate in the survey (Biemer & Lyberg, 2003)
Non-response follow-ups are precious and you need to invest efforts and resources in
order to reduce nonresponse rates. Since nonresponse rates are a quality indicator
nonresponse reduction is an important quality (Groves, 2006)
3.4.1 Sweden
Sweden has a nonresponse rate of 29.3% (SCB, April 2013) among the target
population aged 15-74 years old. Below is an overview of non-response development in
LFS during 1963-2010 and 2001-2012.
Diagram 2: Nonresponse Rate in the Swedish Labor Force Survey 1963-2010.
(Source: Hörngren, SCB 2011)
Diagram 3: Non-response in LFS 2001-2012, the age group 15-74, unweight in percent
on an annual basis
(Source: SCB, 2013)
The measures SCB mainly use to counteract nonresponse are that they are searching for
phone numbers for new people in the sample through automated telephone replacement
that provides additional phone numbers.
In some cases contact letters are sent to the persons.
Another measure to counteract the nonresponse is that interviewers are trained in refusal
conversion where they first must go a basic education for two years with the help of a
mentor and then another supplementary education where the interviewer is trained in
refusal conversion.
Since 1993 Statistics Sweden uses additional information in estimation procedures from
SCB's employment register and from the employment service register of job seekers to
reduce the nonresponse distortions. This additional information consists of variables
connected with the key variables in the LFS and the response and nonresponse
distribution.
The use of auxiliary information in this way reduces the nonresponse error significantly
compared to the previous estimation procedure.
For employees, it means that nonresponse error is reduced to less than one percent and
for the unemployed to less than three percent (SCB, 2013). No more studies to estimate
the systematic error due to the nonresponse has been made recently.
In addition to these measures SCB do no further adjustment for either object
nonresponse or unit nonresponse. Substitution (no response is replaced by another
person's answers) and imputation (assumptions about how a person would have
answered) are methods not applied in LFS.
3.4.2 Australia
The LFS achieves a high response rate of close to 97 percent. The current nonresponse
rate is 3.5 percent among the target population aged 15 years old and over (ILO, 2011)
Labor force characteristic of non-responding households are not imputed. Rather, the
labor force status for persons in non- responding households is recorded as ´´not
applicable´´.
In contrast, the LFS does not include any responding households because only fully
responding households contribute to the estimates, with any under-enumeration in the
survey being automatically compensated for by the weighting process.
Every effort was made to reduce nonresponse (Australia Bureau of Statistics, 2012) and
other no sampling errors by careful design and testing of the questionnaire, training and
supervision of interviewers, and undertaking extensive editing and quality control
procedures at all stages of data processing and follow-up of respondents.
The U.S. has a nonresponse rate of about 9 percent (April 2013) among the target
population aged 16 years and over.
Diagram 4: CPS
Nonresponse Rates
March 2010- March
2011
(Source: Census, 2013)
There are three main sources (Current Population Survey, Design and Methodology,
Technical Paper 66, October 2006) of nonresponse in CPS. Unit nonresponse (referred
to as type A noninterview), person nonresponse and item nonresponse.
Imputation procedures are implemented for item nonresponse. However, because there
is no way of ensuring that the errors of item imputation will balance out, even on
expected out, item nonresponse also introduces potential bias into the estimates. One
measure of controlling the nonresponse error is field representative (FR) guidelines.
Response/ nonresponse rate guidelines have been developed for FRs to help ensure the
quality of the data collected and maintain high response rates.
The CPS supervisor takes appropriate remedial action if an FR whose response rate,
household no interview rate (type A) or minutes-per-case falls below the fully
acceptable range based on quarters work.
Another way to monitor and control nonresponse error is the production and review of
summary reports. They are used to detect changes in historical response patterns.
The Census Bureau and the Bureau of Labor Statistics has formed an interagency work
group to examine CPS nonresponse in detail.
One goal was to share possible reasons and solutions for the declining CPS nonresponse
rates. To help the Regional Office (RO) Operations understand LFS field operations, to
solicit and share the ROs views on the causes of the increasing nonresponse rates, and
to evaluate methods to decrease these rates, a list of questions was prepared. All of the
answers provide an insight into the CPS operations that may affect nonresponse and
follow- up procedures for household interviews.
Because the CPS is a panel survey information is often available at some point in time
from households that were nonrespondents at another point.
Some assessment can be made of the effect of nonresponse on labor force classification
by using data from adjacent months and examine the month-to-month flows of people
from labor force categories to nonresponse as well as from nonresponse to labor force
categories. Comparisons can then be made for CPS between households that responded
both months and households that responded one month but failed to respond in other
month. However, the effect of nonresponse bias is considered to be small. (Dixon,
2002)
3.4.4 Comparison
It is remarkable that nonresponse rate varies from 3 percent to almost 30 percent.
Australia´s rate is undeniably good in this context and can partially be explained by the
fact the survey is mandatory. The U.S is also considered to have a good nonresponse
rate and this can partially be due to that the United States has face-to-face interviews,
but it cannot explain the whole difference.
In the U.S remedial action is taken if the interviewer’s response rate falls below the
fully acceptable range.
The United States is the only country using imputations as a measure to prevent
nonresponse. Imputation procedures are more likely to be used to compensate for
missing items. These measures may also explain, partially, the U.S. nonresponse level.
Sweden has a steadily increasing rate which can be explained, at least partially, by a
recent increase in sample size from 20 to 29 thousand and no interviewer supervisors in
the organization. As a result of increased sample size the number of interviewers has
also increased and this has in recent years given rise to a relatively high proportion of
less experienced interviewers.
There have been a number of non-response projects at Statistics Sweden.
In Statistics Sweden’s current project (2010/2011) on nonresponse Jan Hörngren (SCB)
examines how the problem of the increasing nonresponse and a more difficult ‘’survey
climate’’ has led to that the fight against the nonresponse has intensified. For this
reason, SCB has implemented a so-called ‘’umbrella project’’ for trying to reduce the
nonresponse.
The overall task of the umbrella project was to generate, manage and coordinate actions
aimed at reducing nonresponse in SCB's individual and household survey.
Within this umbrella project all ongoing and new actions and ideas have been collected
that can contribute to reducing the nonresponse of SCB's individual and household
surveys. The results of the umbrella project have contributed to improved and more
effective contact strategies, and also improved tracking procedures.
A prototype for a nonresponse barometer light has been developed and there is also a
project of inflow database of surveys started. SCB constantly reviews and improve their
policies and internal procedures of data collection that affect nonresponse.
In the U.S. they put a lot of effort to reach out to all the persons on the given address
and therefore allow any knowledgeable adult household member to answer the
questions to the extent possible. Also in Australia this method is used where the first
responsible adult aged 18 years or older in the household is allowed to answer the
questions.
In the LFS sometimes indirect interviews are used, this means that a person who is 18
years and older or family member are responsible for the respondent's answers. This is
not obvious in all countries, but it does exist in Australia and the U.S. as they are
countries that use household survey rather than individual study and often have higher
levels of proxy. Sweden’s proxy levels should not have any significant effect on the
estimates according to A. Broman (Personal communication, 16 may 2013). High levels
of proxy in a survey could affect the unemployment level in the country to the person
responsible for the respondent's answers may not have full information about the
respondent. The responsible adult may not know whether the respondent worked at least
one hour during the reference week or not.
The share of indirect interviews varies across countries, Australia and the U.S use the
method ARA (Any Responsible Adult) this means that a person who is 18 years old and
older are responsible for the respondent's answers. Australia and the United States use
this method in their production of LFS and that’s why the proportion of indirect
interviews should be high in their countries. A British experimental study on this
subject has been carried out (Dawe & Knight 1997). The experimental study first
interviewed respondent in the sample, then interviewed his/her partner to answer
questions about him/her about his qualities. This report showed that the net error for the
classification of employment status was small. In other words, the Swedish levels of
proxy interviews did not have any noticeable impact on the estimates, but may have it in
Australia and the USA`s estimates as proxy levels are higher in each country.
When speculating about the high nonresponse rate in Sweden we could look at several
aspects that can be the cause of this. One may wonder whether it has to do with the
individuals' attitudes within the country or if it has to do with the interviewer's lack of
communication ability, or if it has to do with the respondent's sensitivity. Some
questions may be perceived as sensitive and the respondent might in many cases not
want to answer these or answer something else because it sounds better or it could be
that the respondent may not answer at all. The result will be misleading. Sweden should
have supervisors for the interviewers and continually monitor the interviewer’s
nonresponse rates. This is already done in the U.S. and it may be one of several
explanatory factors for their relatively low nonresponse rate. Sweden should consider
taking more action and comparing themselves with other countries in this context.
3.5 Data Collection and Coding
There are several ways to collect data. The actual collection consists of measurements
or observations, measuring instruments, etc. In individual studies, the questionnaire is
the typical instrument. The forms that are been used, are distributed by mail or
interviews. Interviews can be conducted either face to face or over the telephone, and
computer assisted interviews are most commonly used in household surveys.
Face to face interviews involve a trained interviewer visiting the provider to conduct the
survey. Advantages of this method of data collection are higher response rates and
improved data quality (Russell, 2006). Interviewers are able to help respondents
understand the questions and provide correct answers, thereby allowing for the
collection of more complex data. The improved quality of the data means that less data
editing and correction is required at a later stage. However, face to face interviews are
expensive. There are costs involved in time and travel to reach the respondents, and in
the recruitment, training, and management of an interviewer work force. Other
disadvantages are that data can possibly be subject to bias caused by the interviewer's
appearance and attitude, and that respondents may not feel free to disclose sensitive or
private information to an interviewer.
In telephone interviews the providers are asked the survey questions over the telephone.
This reduces the costs compared to face to face interviews as fewer interviewers are
needed and there are no travel costs involved. Telephone interviews can also produce
more timely results. Call-backs for 'not-answering' and follow-ups for additional
information are relatively quick and inexpensive (Gillham, 2005)
As with other methods of data collection, there are some drawbacks associated with this
approach. There are limits on the number and complexity of questions that can be asked
and, because of the ease with which the respondent can terminate the interview, nonresponse and partial nonresponse can be higher than with face to face interviews.
A computer-assisted interview consists of an interviewer entering the data into a
computer as they are provided. As a result, there are some cross checks that needs to be
done throughout the interview (Maxfield & Babbie, 2011). This will improve the
quality of the data and also the overall timeliness of the data processing.
To get good readings through a questionnaire, it is important that the form is well
designed in terms of language, instructions, order of the questions, etc. Practical testing
should be included in the design of a questionnaire.
In LFS occupation coding is a very important action when processing the collected data.
Occupation coding is a time consuming, expensive and also considered to be a big error
source in a survey process. It is considerable to improve the quality when coding for
occupation. Coding is a classification process in LFS when you have respondent’s
answers from which the interviewers have collected. The answer of which occupation a
respondent have can be assigned by a code number. These occupation codes are referred
to the employment status information that the interviewers have collected and then
special staff or the interviewer will use this information to derive labor force
classifications.
3.5.1 Sweden
In Sweden the main mode of data collection is computer-assisted telephone
interviewing (CATI) and is not compulsory. The persons selected are informed by letter
about two weeks in advance if they have been selected to participate in the LFS and the
upcoming telephone interview. At the first interview a careful survey of the person's
employment situation in general is made and the specific reference week is determined.
On subsequent occasions only changes in certain variables are recorded, such as labor
force status, occupation and workplace. Details of the work situation during the
reference week are however registered every time, regardless of the previous answers. If
you are unable to reach the person selected by phone in a few cases a visit interview is
made.
In some cases, such as for illness or language difficulties, an indirect interview is done
which means that another person is responsible for the successful person's behalf
(Beijron, Karlsson, and Andersson SCB 2013).
3.5.2 Australia
A number of methods are used by the Australian bureau of statistics (ABS) for
collecting data. The most commonly used in labor-related surveys are interviews.
The interview method of data collection involves an interviewer contacting data
providers, asking the questions, and recording the responses. Interviews can be
personal, where the data provider is interviewed personally, or involving Any
Responsible Adult (ARA). According to this method the survey questions are asked for
the first responsible adult (aged 18 years or older in the household) and are contacted by
the interviewer. This person will answer the questions on behalf of all members of the
household to the extent and coverage of the survey.
The main mode of data collection is computer-assisted telephone interviewing (CATI)
and is compulsory. The households selected for the LFS are interviewed each month for
eight months, with one eighth of the sample being replaced each month.
For the first month that a household is included in the survey, an interviewer takes
contact with the usual residents of the home and conducts an interview face to face. If
possible, the second month and other months that the household is in the survey the
interview is conducted by telephone. If housing does not have a phone, or do not want
to be interviewed by telephone, interviewers continue to conduct monthly interviews
face to face.
Intensive follow up procedures for nonresponse are in place for household surveys. For
both face-to-face interviews and telephone interviews, interviewers make a number of
attempts to contact households at different times of the day and on different days during
the week. For providers unable to be contacted by telephone, a face-to-face visit is
attempted. If the provider can still not be contacted within the survey period after
repeated attempts, and the dwelling has been verified as not vacant, the dwelling is
listed as a non-contact (Australian bureau of statistics).
According to ILO (Survey methodology, 2011) the main method of data collection are
computer-assisted personal interviewers (CAPI) and is not compulsory.
In LFS, households are in sample for eight months. Each month, one-eighth of the
households are in sample for the first time, one-eighth for the second time etc.
Each month during interview week, field representatives (FRs) and computer assisted
telephone interviewers attempt to contact and interview a responsible person living in
each sample unit selected to complete a Current Population Survey (CPS) interview. An
introductory letter is sent to each sample household prior to its 1st and 5th month
interviews. The letter describes the CPS, announces the forthcoming visit, and provides
respondents with information regarding their rights under the Privacy Act, the voluntary
nature of the survey, and the guarantees of confidentiality for the information they
provide.
A personal visit interview is required for all first month-in-sample households because
the CPS sample is strictly a sample of addresses. The U. S. Census Bureau has no way
of knowing who the occupants of the sample household are, or even whether the
household is occupied or eligible for interview. For some households, telephone
interviews are conducted, if, during the initial personal contact, the respondent requests
a telephone interview (Bureau of Labor Statistics).
3.5.4 Comparison
The three countries have similar approach before the actual data collection, an
introductory letter is sent to each sample household which announces the forthcoming
visit or the upcoming telephone interview. Whereas the U.S. main mode of data
collection is CAPI, Sweden and Australia uses CATI as the major method of data
collection.
When data have been collected then coding can be conducted manually by an operator/
coder or automatically by special designed software. Sometimes one may want to
combine both.
Below you have a visual view of the coding process.
(Source: Biemer & Lyberg, 2003)
The three above basic input components are used so that the interviewer can after make
the judgment of what code number to assign for the element. There are several errors
that could occur during the coding process these errors may be hard to detect by the
statistics bureaus.
Some coding errors that could occur during the coding process are:
•Error due to coding rules. The coding rules are not always properly defined and a coder
might even disagree about proper code number.
•Error due to not so good quality in coding operation. This is because there is a sense of
subjective activity involved. Sometimes coders must read between the lines and use
their own judgment to code the response, these good skills takes time to develop.
•Error due to big coding operations. Large surveys can be quite hard to manage.
Therefor it is difficult to manage and control the error in such operations.
The coding operations can take several forms and some of these are either manually or
manual-computer assisted. A coding error occurs if an element is assigned a code
number other than the correct one.
If computer-assisted coding can increase cost savings without a reduction in data quality
and preferably with an improvement then we would be very interested in using such a
system. In a study by (Bushell, 1997) where the author in an experiment compares a
clerical method of occupation coding with computer assisted coding with respect to data
quality. The result of using 300 sets of occupation information in LFS data and split this
into two stages using two different types of procedures. The result was that coding
reliability and accuracy was not significantly higher in computer assisted occupation
coding system. The conclusion was that they find small difference between the clerical
and computer assisted coding but they need to study this further before recommending
one procedure before another.
Sweden has very little control of the interviewers' work. One does not know if the
interviews have taken place or not and regular monitoring has just recently been
implemented. Therefore, it can easily happen that the interviewer will cheat on answer
sheets and data collection, as the data collection is seldom followed up by someone. The
United States has a particular program in their computer system that checks up cheating
by interviewers and you can track if it occurred. One might think that it must be hard to
fake a natural response pattern, but cheating actually occurs and Sweden should
consider creating a similar program that the U.S uses to combat this dilemma. The
reason cheating and substandard interviewing can happen is partly due to the fact that
Swedish interviewers have many different responsibilities and work with many various
survey studies simultaneously. This can contribute to biased estimates. The CPS also
uses re-interviews, which is a very powerful tool and a good way to control the
measurement error.
3.6 Estimation procedures
In the stage where data should be processed for LFS data processers must give weight to
each individual record and countries use several steps to process the data. In LFS each
record has a specific weight that corresponds to the inverse of the probability of
selection. Self-weighted data occur when all sampled units are given the same weight.
Adjustments are made to this weight to account for non-response that cannot be handled
through imputation. In the final weighting step all of the record weights are adjusted so
that the aggregate totals will match with independently derived population estimates for
various age-sex groups by province and major sub-provincial areas. One feature of the
LFS weighting process is that all individuals within a dwelling are assigned the same
weight.
Estimates from the Labor Force Survey (LFS) are based on information collected from
people in a sample of dwellings or individuals, rather than all dwellings and all
individuals in a country. Hence the estimates produced may differ from those that
would have been produced if the entire population had been included in the survey. The
most common measure of the likely difference is the Standard Error (SE).
Most estimates associated with the labor market are subject to seasonal variation, when
annually-recurring fluctuations attributable to climate and regular institutional events
such as vacations, and holiday seasons. Seasonal adjustment is used to remove seasonal
variations, in order to facilitate analysis of short-term change for major indicators such
as employment and unemployment by age and sex, employment by industry, and class
of worker, employee or self-employed. Many of these indicators are seasonally adjusted
at national and provincial levels. Seasonal adjustments are made using the X-12ARIMA method.
Below you see the estimation procedures used for each country (ILO methodological
paper 2011).
3.6.1 Sweden
In Sweden the percentage of all eligible ultimate sampling units that are interviewed is
76% and the percentage of refusals in the total non-response is equal to 11%. The
sample is not self-weighted, weighting factors are used to adjust for sample design,
survey non-response, and bench-marking (to ensure consistency between survey
estimates and those from other reliable sources e.g. Census).
The results are adjusted for seasonal variations. Data series seasonally adjusted for
Population, employed, employment by population, unemployed, unemployment rate,
labor force, labor force rate, not in the labor force, labor force by population. The
method used for seasonal adjustment is X-12 ARIMA.
3.6.2 Australia
Australia`s percentage of all eligible ultimate sampling units that are interviewed is 97%
and the percentage of refusals in the total non-response is1%.
The sample is not self-weighted and the weighting factors are used to adjust for benchmarking.
The results are adjusted for seasonal variations the most major data series are seasonally
adjusted and method used for seasonal adjustment is Autoregressive Integrated Moving
Average (ARIMA).
The U.S percentage of all eligible ultimate sampling units that are interviewed is 92%
and percentage of refusals in the total non-response is equal to 17%.The sample is not
self-weighted and weighting factors are used to adjust for sample design, survey nonresponse, bench-marking.
The results are adjusted for seasonal variations and data series seasonally adjusted is
1060 seasonally adjusted series. Method used for seasonal adjustment is X-12 ARIMA.
3.6.4 Comparison
When comparing the countries the main differences is in acceptable ultimate sampling
unit rate, refusals in the total non-response and in their standard errors for total
unemployment.
Sweden have eligible unit sampling rate 76% and refusals in the total non-response
11%. Australia 97% in eligible unit sampling rate and 2% in total non-response due to
refusals. The U.S have rate of eligible unit sampling equal to 92% respectively 0, 2%
for total non-response. This may be due to interviewer’s lack of education and ability to
impact the respondents.
X12-ARIMA is used to model the data as ARIMA and produce forecasts based on
ARIMA models. X12-ARIMA is a computer package that can be used automatically in
order to transform data, detect and replace outliers, identify and estimate models and
seasonally adjust time series and produce forecasts and back casts .
3.7 Measurement error
Measurement error is considered to be the most complex source of nonsampling errors
in surveys.
As can be seen from the figure below the measurement process comprises six primary
components. These components are defined as the interviewer, the respondent, the data
collection mode, the questionnaire, the information system and the interview setting.
Together these contributes to the overall measurement error for a survey.
Figure 3: Potential sources of measurement error (Source: Biemer & Lyberg, 2003)
Measurement errors have both a random and a systematic part. The random
measurement error reflects the general uncertainty in the answers. There is always some
risk that an answer happens to be different from the truth.
Systematic measurement errors are incurred if, for example, many misinterpret a
question in a certain way. The results will then be distorted by being partly based on the
incorrect interpretation.
To find out how the measurement errors appear in a survey a measurement error study
is required. Such can be performed in a number of ways. Possible methods are, for
example, registry studies, or re-interviews.
3.6.1 Sweden
Measurement error studies, e.g. re-interviews, are not very common in Sweden.
3.6.2 Australia
Measurement error studies, e.g. re-interviews, are not very common in Sweden.
The U.S performs reinterviews. A selected number of households are reinterviewed
each month to determine whether the information obtained in the first interview was
correct. (U. S. Bureau of Labor Statistics, February 2009). The information gained from
these reinterviews is used to improve the entire training program for the interviewers.
3.6.4 Comparison
The U.S. is the only country using reinterviews as a method to find out how the
measurement errors appear in the CPS. To estimate and reduce response errors in
interview surveys conducting reinterviews is an effective method.
Pamela D. McGovern and John M. Bushery has written a paper ‘’Data mining the CPS
reinterview: digging into response error’’ which illustrates how reinterview data can
help identify sources of error and focus research to improve data quality.
This research, which is experimental in nature, identifies characteristics associated with
inconsistent reporting of '' unemployed'' status. These characteristics may give guidance
in the improvement of the questions and survey procedures to obtain more reliable
estimates of unemployment.
Several studies have been made regarding reinterwievs. Another example is a
reinterview study conducted by the U.S Census Bureau which evaluates the quality of
the census results (Biemer & Lyberg, 2003)
In this study, to get information from those who would contribute to evaluating the
census error professional staff from Census Bureau revisited a sample of
establishments. A conclusion they came to was a substantial amount of measurement
error in the number of reported employees. Further analysis showed that the
respondent's estimate or guesswork gave about 75 percent error in the reports. This
maybe because of the burden to check the company's records and provide accurate
figures were tougher than the respondent would be willing to assume. Instead, they used
what was available and '' close enough''.
3.8 Reference weeks
The use of ongoing measurement weeks is used in most countries since 2005. What may
differ countries between is that some countries use specific measurement weeks, while
in other countries they instead allows the respondent to answer questions from the week
before the interview. The consequence of the latter may be that you get lower estimates
for months with weeks when it is difficult to reach the individuals of the sample. This
difference should not affect the comparability of unemployment to a greater extent, for
annual estimates. However, other variables such as persons in employment and hours
worked can be more affected.
3.8.1 Sweden
In Sweden the reference period for employment is the latest full calendar week
preceding the interview and it is moving. The respondents are evenly distributed
throughout the year all week and they is also tied to a specific reference week.
3.8.2 Australia
In Australia the reference period for employment is also the latest full calendar week
preceding the interview and it is also moving. Even in this case the respondents are tied
to a specific reference week.
3.8.3 United States
In the U.S the reference period for the employment is the week containing the 12h of
the month and is fixed. Here the week containing the 19th of the month is the interview
week, in which the questions are asked the week before the interview.
3.8.4 Comparison
The respondent’s link to a specific measurement week differs for the U.S. compared to
Australia and Sweden. There are no indications that this would affect the comparability.
The link with the measurement weeks has not been deemed to have any significant
impact on the classification of the labour status.
4 External factors and comparability
All statistics produced are important for the country. The government's decision to take
action on the LFS is based on statistics produced by the countries. When these steps are
taken, it is not only time consuming but also large financial actions that are needed. It is
therefore important how to define variables in the LFS as this is of great importance for
decision making for the government. We will in this chapter discuss the possible
external factors that may affect the comparability of countries within the LFS. The
factors that we choose to discuss are the policy programs and also education, it is in
interesting for us how countries define and classify individuals within these factors.
4.1 Labor market programs
In the LFS, the classification of individuals differs between countries. By this I mean
that the classification of persons employed in labor market programs may affect
comparability. This may affect comparability for some labor market programs when
they are classified as a work of which the people involved in these labor market
programs then also classified as underemployed. If countries use different terms for
what applies to one person in a labor market program to be classified as employed if
this is the case then these countries will probably not be as comparable at this point. In
general this will not affect the comparability of the quality of LFS but rather it will
explain differences in unemployment rates between countries (Kluve, 2006) (Kuddo,
2009).
In Sweden, if an interview respondent are participating in a labor market program, and
if that person is involved and working on the production of the workplace products and
services that he / she also receives a salary for then the requirements to fulfill in order
that that person be classified as employed. But it does not always mean that it
automatically mean that people who are active in a labor market program directly
classified as unemployed. Sweden rate some other labor market programs as a form of
study, this is not as formal studies. This requires that the person who gets interviewed
actively participates in the employment services activity, then it suffices therefore not
just being registered as a jobseeker. Australia define individuals who performed some
work for pay or profit during the reference period but were registered as jobseekers at
an employment office are classified as employed. If this another individual is receiving
unemployment benefits during the reference period and at the same time performed at
work for pay is still classified as employed. The United States require that one needs to
be paid during the reference week and at the same time are active in a labor market
program then are classified as employed, so in this case interview respondents is
classified as unemployed when he/she is not receiving salary from the employer
(Eurostat) (ILO 2011).
It does not arise lack of comparability of programs resemble to each other, but if they
are organized in different ways, they can do it. If countries classify participants into
different employment status, although countries have the same principles in the
classification then this can lead to the creation of defects as participant in one country
receives a salary while in the other country receive no salary, but any type of financial
compensation and thus may be in different employment statuses. This will also leads to
that countries are not comparable.
4.2
Education
Factors linked to the educational system in countries can only affect the comparability
of statistics on countries that classifies apprentices with pay since different countries to
also classify them into different employment status.
According to Eurostat's recommendation to people in apprenticeships or traineeships
considered employed if they receive a salary. Unpaid apprentices and trainees should
however not be considered as employed. This means that an apprentice labor status in
the LFS is determined if the person receives a salary from the employer or not.
Therefore, countries comparable only if apprenticeships are designed the same and if
they are handled in the same way in each countries LFS.
In Sweden’s LFS an apprentice is classified as an employed if he/she receives a salary
from the employer to employee. This means that Sweden follows Eurostat
recommendations. If the case is that no salary is paid then it means that the student is
not classified as employed by participating in this form of education. In Australia one
classifies paid apprentices and trainees as employed and unpaid apprentices and trainees
are classified as unemployed. Persons who performed some work for pay or profit
during the reference period but were subject to compulsory schooling are classified as
employed and also persons who performed some work for pay or profit during the
reference period but were full-time or part-time students are classified as employed.
The United States one needs to be paid during the reference week to be classified as
employed in the LFS so in this case apprentice is classified as unemployed when he/she
is not receiving salary from the employer (Eurostat) (ILO 2011).
If all the countries have apprentices who receive a salary in the same way, then the
comparability between the countries is not affected. But if there are differences in the
apprentices receiving wage or not, then may explain differences in unemployment rates
between countries. Whether an apprentice receives a salary from the employer or not
then decides in which employment status individual is classified in.
6 Conclusion
The purpose of this thesis was to examine whether the LFS/CPS design and quality
differ between Sweden, Australia and the United States. After having studied each
country’s methods papers and other scientific articles we found only marginal
differences among the countries. The major differences that we did find were
substantially favoring the U.S where they proved to be more advanced regarding the
nonresponse, interview and data collection design.
We find the difference in the nonresponse levels across the countries very interesting.
Sweden’s extremely high level of nonresponse compared to the U.S is remarkable.
Australia's nonresponse is very low, but this is understandable since their LFS is
mandatory and individuals risk paying a fine if they do not participate. Sweden's
Statistical Bureau is aware that nonresponse is problematic and they are constantly
working on various projects on how to tackle it. These measures have not been
sufficient, but the weaknesses lie with interviewers and respondents. It is perhaps
important for the main users to convey to the
Swedish population the message that this unwillingness to participate might be a big
long term problem for critical decision-making. Another important issue is
measurement error studies. A type of action that the United States uses to reduce
measurement error is through re-interviews. This method is not often applied in either
Sweden or Australia. It is probably a matter of resources, which the United States can
greatly take benefit from.
Regarding the quality of the LFS for the different countries, it is important that the
results reported are accurate. Countries should develop and improve procedures
regarding non-sampling error, classification of individuals and coding of occupation.
These types of errors are impossible to get away with and have a significant effect on
the results presented.
Finally, we think that the LFS is an important social and political responsibility and that
it is important for each country to take responsibility for producing accurate statistics
for the country's decision making at the government level and for future development.
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