Method for Distributing Migrant ‘Workers’
1. Introduction
The aim of this report is to provide a detailed description of the methodology for distributing the
estimated number of long-term (LT) migrant workers who are first time arrivals in the International
Passenger Survey (IPS) to local authority (LA) level.
2. Data Sources
The IPS is used to get the total number of workers in England and Wales (E&W). It is this number
that is distributed. The IPS is a survey of a random sample of passengers entering and leaving the
UK by air, sea or the Channel Tunnel. Over a quarter of a million face to face interviews are carried
out each year.
The methodology uses administrative data from the Department for Work and Pensions (DWP) to
distribute the national level LT migrant workers estimate from the IPS to LA level. Two sets of data
are used in the distribution methodology and both are originally sourced from HM Revenue and
Customs (HMRC) National Insurance and pay-as-you-earn System (NPS) 1. These sources are:
•
•
The Lifetime Labour Market Database (L2)
The Migrant Workers Scan (MWS)
The L2 is a 1% extract of data from the NPS and has over 750,000 individuals in the sample
spanning over 30 years. For sample members the L2 holds information on the date of registration
and for migrants the self reported date of arrival in the UK. The L2 also contains information on the
number of weeks that a person has been active in a tax year. Activities include:
•
•
•
•
•
employment (confined to weeks in that activity without start and end dates for each period
in employment)
self employment
tax credit
benefit activity
child care (via Child Benefit)
The address information in the L2 is sourced from the Customer Information System (CIS) which is
the primary customer contact database used by both HMRC and DWP. The address at registration
in the tax year of arrival is used from the L2. Addresses in the L2 are held as ‘periods’ with start
and end dates. Any new notification of address will automatically terminate a past period and open
1
The NPS collects, validates and stores information on National Insurance contributions. In 2008 the database was
expanded to record and validate payment of tax through the pay-as-you-earn system. The NPS holds detailed
information on periods of employment, self employment, sickness, tax credits, unemployment and periods of non-liability
(e.g. caring for children) back to 1975. The NPS data holds records for anyone who has ever had a National Insurance
Number in the UK. This includes data on people who may no longer be resident in the UK, and people who have died.
The database currently holds over 75 million records, which continues to grow as new people reach age 16 and enter the
NPS. The NPS also includes data on the registration and identification of migrants from abroad who need a National
Insurance Number to work or claim benefits.
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Method for Distributing Migrant ’Workers‘
a new address period. Addresses may span a number of years. Updates to address can be
generated by the following activities:
•
•
Any contact with DWP or HMRC systems, for example:
o First registration for a National Insurance Number (NINo)
o Benefit claims
o Tax Credit claims and awards
o Self assessment for tax purposes
o Self employment
o Changes of circumstances (name at marriage for example)
o Insolvency
o Employment
o Registration with the Government Gateway for internet services
Contact with LAs who access DWP or HMRC systems for claims to Housing Benefit
or Council Tax Benefit
The MWS is a 100% extract of migrants that are registered on the NPS. The MWS contains
information on all overseas nationals who have been registered and have been allocated a NINo.
This dataset includes registration details, self reported arrival dates, some demographic details and
address at registration. The MWS includes both short-term (ST) and LT migrants. As there is no
activity information included with the data, and migrants do not have to de-register from the MWS
when they leave the country, there is no way to distinguish between these two types of migrants.
These sources are considered suitable to distribute the national level LT migrant workers estimate
from the IPS to LA level because workers require a NINo to work legally in the United Kingdom
(UK). Illegal workers are not included in the L2 and MWS. It is possible that the national level LT
migrant workers estimate from the IPS contains some people who will go onto work illegally.
However, it is assumed that this number is small because it is thought that illegal workers are
unlikely to tell IPS interviewers that they plan to work.
These data sources are used to distribute the national level LT migrant workers estimate from the
IPS to LA level in the following ways:
• The L2 is used to get the proportion of migrants that are LT workers in each LA.
• The MWS is used to get the count of migrants in each LA.
3. Defining migrants, workers and length of stay in the different data
sources
3.1 Identifying long-term migrant workers in the IPS
A LT migrant is defined in the IPS as a person who moves to a country other than that of his or her
usual residence for a period of at least a year (12 months), so that the country of destination
effectively becomes his or her new country of residence.
A worker in the IPS is defined as;
a) Aged 16+ and
b) States one of the following reasons for visit (RFV) on their questionnaire
• Definite job to go to
• Looking for work
• Working holiday
• Business
• Accompany/join whose previous occupation was work
• Other whose previous occupation was not “houseperson” or “retired”.
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Method for Distributing Migrant ’Workers‘
The different components of the IPS migrant worker definition map to the data-sources that are
being used to distribute the IPS to LA level in the following ways:
•
•
•
•
•
•
Definite job to go to - All migrants who state “Definite job to go to” as their reason for
visit should appear on the L2 and MWS data, although whether they actually appear in
the LT Worker estimates depends on when they apply for a NINo and when that work
actually commences (see section 3.3 ).
Looking for work - Those people who do not have a definite job to go to, but who are
“looking for work” on the IPS will appear in the L2 and MWS data if they register for a
NINo.
Working holiday - Those migrants who are undertaking a working holiday are
theoretically required to register for a NINo if they work whilst on holiday in this country,
and are therefore included in the worker figure because it is assumed they will appear
on the L2 and MWS data.
Business - This category includes those who are self-employed. The L2 and MWS
capture self-employed people as they must register for a NINo for taxation and National
Insurance purposes. However, this RFV category also includes workers who are
employed and paid by overseas employers, and who therefore are unlikely to have
registered for a NINo.
Accompany/join whose previous occupation was work – It is assumed that someone is
unlikely to stop work if they were previously employed, so though their RFV is
accompany/join they may still go on to work.
Other - The other category includes anyone who has more than one main reason for
visit and cannot state that one is more significant than the other. It is assumed that if
this is the case then one of the main reasons for visit is likely to be “to work”. The
previous occupation categories “Houseperson” and “retired” have been removed from
the “Other” category because it is assumed that someone is unlikely to start work if they
were previously retired or a houseperson, so in their case one of their main reasons for
visit is probably a reason other than work.
The way in which a LT migrant worker is identified in the IPS is summarised in Figure 3.1.
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Method for Distributing Migrant ’Workers‘
Figure 3.1
Identifying a long-term migrant worker in the IPS
START
1. Is the country of
residence 12 months ago
outside the UK and
intended length of stay
greater than 12 months?
YES
Not a LT
Migrant
NO
LT Migrant
YES
•
•
•
•
•
NO
•
LT migrant
worker
2. Is the migrant over 16
and the RFV one of the
following?
Definite job to go to
Looking for work
Working Holiday
Business
Accompany/join whose
previous occupation
was work
Other but previous
occupation not retired or
houseperson
LT migrant
non-worker
3.2 Identifying Migrants in the MWS
The total number of LT migrant workers in England and Wales identified in the IPS is distributed
using the MWS and L2. The MWS is used to get the actual count of migrant NINo registrations in
an LA. The MWS has been linked with data from the Higher Education Statistics Agency (HESA).
This linking is done to identify those people who have registered for a National Insurance Number
(NINo) and who are therefore in the MWS but who are students. The students who are identified
are taken out of the MWS as it is assumed that their main reason for visit is to come to study and
not to work (see ”Method for Distributing Migrant ‘Students’”). Therefore, for the years 2007/8,
2008/9 and 2009/10, the MWS data that is used in the worker distribution refers to the MWS count
less those cases that have been identified as students by linking with HESA.
The Office for National Statistics (ONS) does not have record level address data from the MWS for
the years 2005/6 and 2006/7. Therefore, for these years it is not possible to link the MWS with
HESA data and take out people that are believed to be students, as has been done for the other
years. Students are taken out of the top level number that is being distributed from the MWS and
L2 but for 2005/6 and 2006/7 the distribution will still include students.
The MWS includes both ST and LT migrants with no way of distinguishing between these two
types of migrants. Consequently, the L2 is used to get the proportion of migrants that are LT
workers in each LA.
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Method for Distributing Migrant ’Workers‘
3.3 Identifying a LT migrant worker in the L2
A first time arrival migrant worker has been identified in the L2 as someone of working age (16-59
for women and 16-64 for men) who has a foreign country of origin (the country of origin is used as
a proxy for nationality) or foreign nationality code at registration. Some cases have been identified
where the nationality is ‘British’ but the country of origin is ‘foreign’. These are people who appear
to have dual nationality but who do not necessarily have the right to reside in the United Kingdom
(UK). For the purposes of this work these people have been classified as foreign inbound migrants
and their country of origin has been used as a proxy for their alternative nationality.
A migrant in the L2 is classified as present in the UK for the period that there is some type of
activity record (i.e. employment, self employment, tax credit, benefit activity, child benefit) for that
person. In addition, any period between arrival and registration is classed as resident, even if this
is not supported by any activity. This assumption has been made because you would not
necessarily expect any observable activity during this period e.g. workers who do not have a job
arranged prior to arrival and who take some time to secure employment.
Once a migrant stops appearing as active in the L2 in any of these activities then it is assumed that
the migrant has departed and is no longer present in the UK. Given that there are no start and end
dates for most of the activities and the date of departure is not captured, it is assumed that the
person left the country at some point during the last year that there was any activity. For example,
someone arriving in Year 1, having activities in Year 1 and Year 2, and no activity in Year 3 is
assumed to have left during Year 2.
The methodology is based on the hypothesis that the vast majority of working age migrants will be
engaged in some form of income generating activity whilst they are resident in the UK. However,
there are two groups of people who have been defined as resident when they are not interacting.
These are:
•
•
Those who have a state pension paid in the UK. This is because it is thought that these
people are likely to have been in the UK for a long time and regard the UK as their longterm home. These are kept resident from their last observable interaction.
Women aged over 40 and men aged over 50 who have been caring for children (child
benefit) for 15 years or more. This is because these people are less likely to return to work
after child care and therefore should not be counted out of the UK when they do not
interact. Evidence from previous L2 analysis suggests that older mothers have much lower
employment rates generally.
It is accepted that migrants could appear as inactive in the L2 but be working illegally or staying
with friends and family. For these reasons this methodology could count migrants out of the
country when they are in fact resident. However, it should be noted that more migrants are being
captured in the L2 than in the IPS (Figure 3.2) which is evidence to suggest that the methodology
is not prematurely counting migrants out of the country when they are in fact resident.
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Method for Distributing Migrant ’Workers‘
Figure 3.2
Comparison of LT migrant workers in the L2 and IPS, E&W, 2005/6 to 2009/10
LT workers (thousands)
300
IPS
250
L2
200
150
100
50
0
2005/6
2006/7
2007/8
2008/9
2009/10
Year
Where a migrant has only one form of activity in the L2, the weeks in that activity are taken as the
period that the migrant is present in the UK in the tax year. If a migrant has more than one
employment activity in the tax year the lack of start and end dates means that it is impossible to tell
from the L2 whether these employment activities run alongside each other or one activity follows
on from the end of another activity. In these instances an average of the minimum and maximum
time that a migrant could have been present, according to the activity data in the L2, is used. For
instance, if a migrant had a record of one employment period of 26 weeks and one employment
period of 13 weeks in a particular tax year, then the minimum period the migrant could have been
in the country is 26 weeks (if the periods of employment ran alongside each other) and the
maximum period is 39 weeks (if the periods of employment followed on from each other).
Therefore, their length of time present in the tax year is calculated as being the average of these
two estimates which is 32 weeks. Figure 3.3 shows the proportion of worker arrivals in the L2 who
have more than one period of employment in the arrival year.
Percentage
Figure 3.3
LT First Arrivals for employment in the UK by number of employments in arrival tax years
2005/6 to 2009/10
100
90
80
70
60
50
40
30
20
10
0
2+ employments
1 employment
JSA only
2005/6
2006/7
2007/8
2008/9
2009/10
Year
Note JSA=Job Seeker’s Allowance
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Method for Distributing Migrant ’Workers‘
Migrants in the L2 have been split into LT and ST, based on assumptions about length of stay and
departures. ST migrants are those migrants who either have less than 52 weeks activity in one
year and none in the second year, or less than 52 weeks activity spanning two years and none in
the third. Therefore their length of stay is assumed to be less than a year. Migrants with an arrival
with no subsequent activity are assumed to have left in the same year as arrival and are also
classified as ST migrants. LT migrants are migrants who have 52 or more weeks of activity,
spanning 1 or more consecutive years. The different types of ST and LT migrants that have been
identified in the L2 are summarised in Figure 3.4.
Figure 3.4
Types of Migrants Identified in the L2
In this methodology a “departure” has to be identified to work out whether someone is a long or
short-term migrant. For the purposes of categorising a migrant as short-term, two years of data are
required after the arrival year. For example, "type 2" short-term migrants are defined as those who
arrive in year 1 and depart in year 2 with less than 52 weeks activity across both years. They are
assumed to have departed in year 2 because they have no activity in year 3. Therefore, two years
of data after the year of arrival are needed to be able to say they have departed.
In the year 2008/2009 ONS only have access to one year of data after the arrival year, meaning
that Type 2 and Type 3 short-term migrants cannot be identified until another year’s data is
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Method for Distributing Migrant ’Workers‘
available. This results in some short-term migrants being classified as long-term incorrectly.
Therefore in 2008/2009 ONS estimate how many migrants arrived and are likely to depart in the
following year.
This estimate is produced on the basis of the proportions of Type 2 and 3 arrivals in previous years
by subcontinent of origin. The estimated proportions are then applied to the data and the requisite
number of cases are converted from long-term arrivals to short-term arrivals. The cases that have
been converted using the estimation are then allocated new 'arrival types' for ease of identification
in the data. "Type 7" are the newly estimated equivalents of "Type 2" and "Type 8" are the newly
estimated equivalents of "Type 3" in 2008/2009.
For the year 2009/10 it is not known whether the migrants are long or short-term. For this year
therefore an approach is needed to split the migrants into long and short-term. This is done by
calculating the average change in the LT/ST split over the last three years and then applying this
forward to 2009/10. This is the method that will be used to calculate the LT/ST split for the latest
year on an ongoing basis.
Tables 3.1 and 3.2 show the proportion of migrants classified as each type in each tax year.
Table 3.1
Percentage of ST migrants in each migrant type identified in the L2, tax years 2005/6 to
2008/9, UK
2005/6 2006/7 2007/8 2008/9
Type 1
35.9% 32.8% 38.3% 42.8%
Type 2
53.6% 54.0% 49.0%
Type 3
10.6% 13.2% 12.7%
Type 7
46.5%
Type 8
10.7%
Table 3.2
Percentage of LT migrants in each migrant type identified in the L2, tax years 2005/6 to
2008/9, UK
2005/6 2006/7 2007/8 2008/9
Type 4
2.2%
0.7%
0.9%
1.7%
Type 5
0.2%
0.4%
0.4%
0.1%
Type 6
97.6%
98.9%
98.7%
98.2%
Although it is felt the classification assumptions are the best possible given the available data,
there is potential for some migrants to be wrongly classified (e.g. LT when in fact they are ST and
vice versa). There are two situations where a misclassification of type is possible.
•
•
Some Type 2 (and therefore Type 7) migrants may be LT rather than ST, because there
might be a gap between their activities. It is not currently possible to measure the gap
between activities. If the gap between the activities was included it could potentially bring
the length of stay up to 52 weeks or more, which would result in them being classified as a
LT migrant rather than a ST migrant.
A misclassification may have occurred for LT migrants Type 5 and 6. Where there is activity
of 52 weeks or more spanning two years or more, it is assumed that the migrants are in the
country between activities, or that the activities are continuous over the two years with no
gap in between. However, these migrants could potentially be circular migrants – i.e. they
could be in the UK for several months and work, go overseas, and then come back the
following year and work for several more months. Adding the two lots of activity together
gives activity of longer than 52 weeks, but this does not necessarily mean that the person is
working continuously over this time. Exploratory analysis that has been done to try and
identify circular migrants that may be being misclassified suggests that this number is
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Method for Distributing Migrant ’Workers‘
small. It should be noted that some circular migrants will already be correctly classified as
ST, for example, those migrants who arrive in Year 1 and stay for three months and rearrive in Year 2 and stay another three months, (although only the first arrival would be
captured on L2, compared to 2 arrivals in different years on the IPS). However, if the same
pattern was also displayed in year 3 the migrant would be classified as LT.
A migrant is defined as a worker in the L2 if they have registered for a NINo within six months of
arrival and they have an employment, Job Seekers’ Allowance (JSA) or Working Tax Credit
activity. Those migrants in the L2 claiming JSA within six months of arrival have been included as
migrant workers because to be claiming JSA a person has to be actively seeking employment and
the IPS worker definition includes those “looking for work”.
Figure 3.5 shows the pattern in lag time between arrival and registration for migrants identified in
the L2 for each year. In each year the vast majority of migrants have registered within six months
of arrival. Therefore, it is assumed that those taking more than six months to register have come
into the country for a reason other than work. This means that only those who registered within six
months of arrival are included in the worker distribution. Those who take longer than six months
after arrival to register for a NINo are classified as LT migrants who came in for other reasons.
Figure 3.5
Lag in months between arrival in the UK and NINo registration in the L2, tax years 2005/6 to
2009/10
180
Migrants (Thousands)
160
140
120
2005/6
2006/7
2007/8
2008/9
2009/10
100
80
60
40
20
0
Less 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 3536+
than
1
Months
The L2 records address at registration. This is not necessarily address at arrival. ONS are
attempting to distribute migrant workers to the LA that they first live in. Defining a migrant worker
as someone who registers no more than six months after arrival limits the potential for the address
at registration to be different from the address at arrival.
The methodology that is used to identify LT migrant workers in the L2 is summarised in Figure 3.6.
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Method for Distributing Migrant ’Workers‘
Figure 3.6
Identifying LT migrant workers, LT migrant others and ST migrants in the L2 where three
years of data is available
START
1. Is the migrant of working
age and the country of origin
is outside the UK?
YES
Less than 12 months
Not a
Migrant
NO
Migrant
2. What is the
inferred length of
stay?
Greater than12
months
Long-Term
4. Are there 6
months or less
between arrival
and registration?
YES
ShortTerm
LT Worker
YES
3. Does the LT migrant
have an employment/selfemployment record, JSA
record or Working Tax
Credit?
NO
NO
LT Other
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Method for Distributing Migrant ’Workers‘
The L2 migrant worker estimate includes some students who register for a NINo for employment
purposes whilst studying. The presence of students in the L2 could potentially affect the distribution
of migrant workers because students tend to go to certain places (e.g. university towns and cities).
In addition, by linking the MWS with HESA data it is possible to take some higher education
students out of the MWS data that the L2 is being applied to. Potential students in the L2 have
been identified using the following criteria:
(1) Arrived for the first time and were prime University age (between 18 and 24 inclusive)
and;
Arrived when most Higher Education establishments start their academic year (in September or
October)
and;
Had either no "pay" or "pay" below £3000 per year as it was likely to be a part-time job that
they did alongside their studies.
or
(2) Any age at arrival with a known student hall of residence address in the year of arrival as non
students are unlikely to reside in a student hall of residence
or
(3) Any age at arrival with a full time education liability in the year of arrival
The estimated number of potential students identified in the L2 in 2008/9 was 21,700. The number
found in the HESA/MWS linking in 2008/9 was 21,597. The HESA data only includes a sub-section
of LT student migrants, as it does not capture those in colleges of further education or in language
schools. Therefore, this is evidence that this methodology is not capturing all students in the L2.
The L2 migrant worker definitions do not map exactly to the IPS migrant worker definitions.
Although there is confidence that those who actually secure work will be reflected in the data, the
IPS may potentially capture some migrant workers who are not captured in the L2. For instance,
the IPS includes people who state that they are ‘looking for work’, but who may never secure work,
or be eligible to claim out of work benefits. These people are likely to be missing from the L2 data.
In addition, some workers in the IPS will never be captured in the L2 data. These are largely the
following types of cases:
•
•
Au-Pairs who work for families who use the exceptional NI rules meaning they do not have
to pay NI (and hence register for a NINo)
Business workers who arrive in the UK but continue to be paid by their home state, for
example, workers who come to set up / install / transfer machinery to a new factory, but
remain employed by their foreign employer. However, these are more likely to be ST
migrant workers.
Despite these cases, the number of LT migrant workers that are being estimated from the L2 is
higher than the number being captured on the IPS (see Figure 3.2).
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Method for Distributing Migrant ’Workers‘
4. Method of distributing the E&W IPS LT migrant estimates to LA level
The method summarised in figure 3.6 means that the following counts can be obtained from the
L2:
•
•
•
LT workers
LT non-workers
ST (all)
Given that the MWS count for each geographic area will include a combination of LT workers, LT
non-workers and ST with no way of knowing how many of each there are, the total number of LT
worker registrations in the MWS is not available. Therefore, the LT worker count from the L2 is
used to get an estimate of the number of LT workers in the MWS in each LA.
However, the 1% L2 sample size means that the split from the L2 is not considered robust enough
to be used directly at LA level in the case of 317 LAs. These LAs are geographically grouped
based on Nomenclature of Units for Territorial Statistics (NUTS) 2 groupings (Annex A). The split of
LT workers, LT non-workers and ST (summing to 1) is calculated from the L2 for the relevant
NUTS grouping and in each LA in that grouping the proportion that constitutes LT workers is
applied to the LA level MWS count to get a LT worker figure in each LA in the NUTS grouping.
The criteria used for grouping LAs and the way they are grouped is as follows:
•
•
•
If the standard errors of the migrant count in an LA over the years 2005/6 to 2008/9 is
under 25% AND the average of the sample sizes is over 20 then the LA is left as stand
alone LA 3.
The remaining 317 LAs which fail to meet these criteria are grouped based on the NUTS 3
groups with any LAs that can be used without being grouped taken out. If the standard
errors of the migrant count in these groupings over the years 2005/6 to 2008/9 is under
25% AND the average of the sample sizes is over 20 then they are left in the NUTS 3
grouping with any LAs who can be used without being grouped taken out. A total of 203
LAs are grouped in their NUTS 3 group.
Any groups that fail to meet this criteria (i.e. the standard errors of the migrant count in
these groupings over the years 2005/6 to 2008/9 is over 25% AND the average of the
sample sizes is under 20) will be grouped into NUTS 2 4 groupings (with any LAs that can
be used without being grouped or can be used in a NUTS 3 geography taken out) which
are larger and therefore more robust. A total of 114 LAs are grouped in their NUTS 2 group.
In the course of the research the possibility of grouping LAs based on intermediate geographies 5
and Output Area classifications 6 have been explored. Grouping LAs based on intermediate
geographies has been dismissed because feedback from the work done in Phase 1 of the
2
NUTS was created by the European Office for Statistics (Eurostat) as a single hierarchical classification of spatial units
used for statistical production across the European Union. In England NUTS 3 relates to counties and groups of unitary
authorities. In Wales NUTS 3 relates to group of unitary authorities. There are 105 NUTS 3 areas in E&W.
3
A standard error of 25% has been selected as the cut off because for the long term migration estimates ONS advise
that a migration figure with a standard error of over 25% is not considered to be reliable. In addition, 20 contacts has
been used as a cut off because that was the minimum threshold that was used when constructing the intermediate
geographies which are used in the current method.
4
In England NUTS 2 relates to counties and groups of counties. In Wales NUTS 2 relates to groups of unitary
authorities. There are 32 NUTS 2 areas in E&W.
5
More information on intermediate geographies can be found at: http://www.ons.gov.uk/ons/guide-method/methodquality/imps/archive-material/archive-background-information/improved-methods-for-population-statistics-revisions-archive-material-/impact-of-the-new-migration-geography.pdf
6
More information on Output Area Classifications can be found at: http://www.ons.gov.uk/ons/guidemethod/geography/products/area-classifications/national-statistics-area-classifications/national-statistics-2001-areaclassifications/available-geographies/output-areas/index.html
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Method for Distributing Migrant ’Workers‘
Migration Statistics Improvement Programme suggested that they were unpopular with some
users 7. Output Area Classification could not be used without complication because this
classification does not necessarily group contiguous LAs.
The split of LT workers, LT non-workers and ST from the L2 is considered robust enough to be
used directly at LA level in the case of 59 LAs. In these cases the proportion that constitutes LT
workers is applied directly to the MWS count in that particular LA to get a LT worker figure in the
LA. The LAs that this methodology applies to are listed in Annex A. This also shows how the other
LAs are grouped.
The splits from the L2 can justifiably be applied to the MWS to produce LA level LT worker
estimates because the L2 and MWS regional distributions are very similar. The figures below show
this for two example tax years 2008/9 (Figure 4.1) and 2009/10 (Figure 4.2).
Figure 4.1
Comparison of MWS and L2 regional distribution in E&W for tax year 2008/9
Percentage of migrants
50
40
30
L2
MWS
20
10
0
North
East
North
West
Yorkshire East
West
and the Midlands Midlands
Humber
East
London
South
East
South
West
Wales
Region
Figure 4.2
Comparison of MWS and L2 regional distribution in E&W for tax year 2009/10
Percentage of migrants
60
50
40
L2
30
MWS
20
10
0
North
East
North
West
Yorkshire East
West
and the Midlands Midlands
Humber
East
London
South
East
South
West
Wales
Region
7
This feedback is available in the report “Analysis of responses to the user engagement exercise and conclusions from
ONS”
Office for National Statistics | Research Report | 13
Method for Distributing Migrant ’Workers‘
Given that L2 data is being used to distribute the E&W IPS data, ideally the characteristics of the
migrant workers captured in the L2 should be similar to those that are captured on the IPS. To
investigate the extent to which this is the case the demographic characteristics of LT and ST
migrant workers that are captured on the L2 and the IPS have been compared. At E&W level the
age and sex characteristics of LT and ST migrant workers that are captured on the L2 and the IPS
are similar. However, the nationality characteristics are different. The main differences are:
•
•
•
There are proportionally more LT migrant workers from Australia/New Zealand in the IPS
than in the L2.
There are proportionally more LT migrant workers from the A10 countries in the L2 than in
the IPS. However, there are proportionally less ST migrant workers from the A10 countries
in the L2 than in the IPS.
There are proportionally more migrant workers from Asia in both the LT and ST in the L2
than the IPS. This is particularly noticeable for the ST migrants.
To take account of these differences the numbers from each source are split into subcontinent
groups set out below.
•
•
•
•
EU15/A10
Asia
Australia/New Zealand
Rest of the World
These subcontinent groupings have been selected because
there are significant differences between how these groups
are captured in the IPS and the L2
For each subcontinent grouping a weighting factor is calculated to adjust the L2 E&W subcontinent
totals for LT migrant workers to match the IPS E&W totals. This adjustment weight is calculated by
using the following formula:
Adjustment weight = IPS subcontinent count / L2 subcontinent count
The geographical distribution of these subcontinent groupings is obtained from the L2 data. The
subcontinent weighting factors are applied to the geographic distribution of LT migrants in the L2.
This gives a weighted geographical distribution for each subcontinent group. The weighting limits
any bias that is introduced from how the L2 captures LT migrant workers relative to the IPS.
The weighted subcontinent geographic distribution is used to recalculate the subcontinent split for
each geography grouping. These splits are then applied to the LT worker figure that is produced
from the L2 and MWS. For those LAs that are directly distributed the weighted LA level
subcontinent split is directly assigned to the LA level LT worker figure. In the case of those LAs that
are included in a NUTS based geographic group, the weighted subcontinent distributions are used
to calculate the subcontinent split at the relevant NUTS based geography. These subcontinent
splits are then assigned to all LAs within the relevant NUTS geography. This gives the number of
LT workers by subcontinent in each LA.
The LT number of workers by subcontinent in each LA is used to calculate LA distribution for each
subcontinent. This is used to distribute the IPS LT workers figures for E&W so that an LA
distribution for each subcontinent grouping is obtained. In each LA these can be summed together
to produce an LT migrant worker estimate for each LA.
The method of distributing the E&W IPS LT migrant estimates to LA level is summarised in Figure
4.3 8. A worked example of the methodology is provided in Annex B.
8
In figure 4.3 proportion is abbreviated to ‘prop’, distribution to ‘distr’ and geography to ‘geog’. The
Australia/New Zealand and Rest of World groups are referred to as ‘Aus/NZ’ and ‘Rest’ respectively.
Office for National Statistics | Research Report | 14
Method for Distributing Migrant ’Workers‘
Figure 4.3
Detailed diagram of worker methodology
Group LAs into geographic groupings, using NUTS 2 and 3 groupings (to reduce variability across
years for small LAs)
Calculate LT worker, LT non-worker and ST split in the L2 for each geographic group and then assign
to LAs (i.e. all LAs in a geographic group have the same split)
Prop of LT non-workers in L2
Prop of LT workers in L2
Prop of ST in L2
Apply proportion of LT workers to MWS count in each LA
LT worker figure in each LA from L2 and MWS
Calculate a subcontinent weighting factor that adjusts L2 E&W subcontinent totals for LT workers to
match the IPS E&W subcontinent totals for LT workers.
EU15/A10 weight
Asia weight
Aus/NZ weight
Rest weight
These subcontinent groupings have been selected because there are significant
differences between how these three groups are captured in the IPS and the L2.
Split L2 LT worker raw data into subcontinent groupings to get the geographic group distributions for
each and apply the relevant subcontinent weighting factor to each set of counts
This weighting limits bias in how the L2 captures migrant workers from different subcontinents relative to the IPS.
EU15/A10 weighted
geog group distr
Asia weighted geog
group distr
Aus/NZ weighted
geog group distr
Rest weighted geog
group distr
Calculate subcontinent split for each geographic group using weighted distributions above and then
assign splits to LAs (i.e. all LAs in a geographic group have the same subcontinent split)
Prop of EU/A10
Prop of Asia
Prop of Aus/NZ
Prop of Rest
Apply subcontinent split to LT worker figure from L2 and MWS
LT workers by subcontinent in each LA
Calculate LA distributions for each subcontinent
Distribute IPS E&W LT worker subcontinent totals using subcontinent LA distributions in step above
EU15/A10 LA distr
Asia LA distr
Aus/NZ LA distr
Rest LA distr
Sum subcontinent distributions together
LT workers in each LA
Office for National Statistics | Research Report | 15
Method for Distributing Migrant ’Workers‘
Annex A
Table A.1
LAs where the L2 LT workers, LT non-workers and ST proportions are applied directly to LA
level
LA code
00AB
00AC
00AE
00AG
00AH
00AJ
00AK
00AL
00AM
00AN
00AP
00AQ
00AS
00AT
00AU
00AW
00AX
00AY
00AZ
00BA
00BB
00BC
00BE
00BG
00BH
00BJ
00BK
00BN
00BR
00BY
00CG
00CJ
00CN
00CQ
00CS
00CX
00CZ
00DA
00FA
00FK
00FN
00FY
00GA
00HB
00HG
00HN
00JA
00KA
00MC
00MD
00MG
00ML
LA name
Barking and Dagenham
Barnet
Brent
Camden
Croydon
Ealing
Enfield
Greenwich
Hackney
Hammersmith and Fulham
Haringey
Harrow
Hillingdon
Hounslow
Islington
Kensington and Chelsea
Kingston upon Thames
Lambeth
Lewisham
Merton
Newham
Redbridge
Southwark
Tower Hamlets
Waltham Forest
Wandsworth
Westminster
Manchester
Salford
Liverpool
Sheffield
Newcastle upon Tyne
Birmingham
Coventry
Sandwell
Bradford
Kirklees
Leeds
Kingston upon Hull, City of UA
Derby UA
Leicester UA
Nottingham UA
Herefordshire, County of UA
Bristol, City of UA
Plymouth UA
Bournemouth UA
Peterborough UA
Luton UA
Reading UA
Slough UA
Milton Keynes UA
Brighton and Hove UA
Office for National Statistics | Research Report | 16
Method for Distributing Migrant ’Workers‘
00MS
00PT
12UB
34UF
38UC
42UD
45UE
Southampton UA
Cardiff UA
Cambridge
Northampton
Oxford
Ipswich
Crawley
Table A.2
Geographic groupings for the remaining 317 LAs
Group
UKE31
Group name
Barnsley, Doncaster and
Rotherham
NUTS level
3
UKK12
3
UKH22
Bath and North East
Somerset, North
Somerset and South
Gloucestershire
Bedfordshire CC
UKJ11
Berkshire
3
UKJ13
Buckinghamshire CC
3
UKH12
Cambridgeshire CC
3
UKD2
Cheshire
2
UKD22
Cheshire CC
3
UKK3
Cornwall and Isles of
Scilly
2
UKD1
Cumbria
2
UKF1
Derbyshire and
Nottinghamshire
2
3
LA code
00CC
00CE
00CF
00HA
00HC
00HD
LA name
Barnsley
Doncaster
Rotherham
Bath and North East Somerset UA
North Somerset UA
South Gloucestershire UA
09UC
09UD
09UE
00MA
00MB
00ME
00MF
11UB
11UC
11UE
11UF
12UC
12UD
12UE
12UG
00ET
00EU
13UB
13UC
13UD
13UE
13UG
13UH
15UB
15UC
15UD
15UE
15UF
15UG
15UH
16UB
16UC
16UE
17UB
17UC
17UD
17UF
17UG
17UH
17UJ
Mid Bedfordshire
Bedford
South Bedfordshire
Bracknell Forest UA
West Berkshire UA
Windsor and Maidenhead UA
Wokingham UA
Aylesbury Vale
Chiltern
South Bucks
Wycombe
East Cambridgeshire
Fenland
Huntingdonshire
South Cambridgeshire
Halton UA
Warrington UA
Chester
Congleton
Crewe and Nantwich
Ellesmere Port and Neston
Macclesfield
Vale Royal
Caradon
Carrick
Kerrier
North Cornwall
Penwith
Restormel
Isles of Scilly
Allerdale
Barrow-in-Furness
Copeland
Amber Valley
Bolsover
Chesterfield
Derbyshire Dales
Erewash
High Peak
North East Derbyshire
Office for National Statistics | Research Report | 17
Method for Distributing Migrant ’Workers‘
UKK4
UKK43
Devon
Devon CC
2
3
UKK2
Dorset and Somerset
2
UKD12
East Cumbria
3
UKL2
East Wales
2
UKE1
East Yorkshire and
Northern Lincolnshire
2
UKH3
Essex
2
UKH33
Essex CC
3
UKK13
Gloucestershire
3
UKK1
Gloucestershire,
Wiltshire and
Bristol/Bath area
2
17UK
37UB
37UC
37UD
37UE
37UF
37UG
37UJ
00HH
18UB
18UC
18UD
18UE
18UG
18UH
18UK
18UL
00HP
19UC
19UD
19UE
19UG
19UH
19UJ
16UD
16UF
16UG
00NJ
00NL
00NN
00PD
00PP
00PR
00FB
00FC
00FD
00KF
00KG
22UB
22UC
22UD
22UE
22UF
22UG
22UH
22UJ
22UK
22UL
22UN
22UQ
23UB
23UC
23UD
23UE
23UF
23UG
00HX
South Derbyshire
Ashfield
Bassetlaw
Broxtowe
Gedling
Mansfield
Newark and Sherwood
Rushcliffe
Torbay UA
East Devon
Exeter
Mid Devon
North Devon
South Hams
Teignbridge
Torridge
West Devon
Poole UA
Christchurch
East Dorset
North Dorset
Purbeck
West Dorset
Weymouth and Portland
Carlisle
Eden
South Lakeland
Flintshire UA
Wrexham
Powys UA
The Vale of Glamorgan
Monmouthshire UA
Newport UA
East Riding of Yorkshire UA
North East Lincolnshire UA
North Lincolnshire UA
Southend-on-Sea UA
Thurrock UA
Basildon
Braintree
Brentwood
Castle Point
Chelmsford
Colchester
Epping Forest
Harlow
Maldon
Rochford
Tendring
Uttlesford
Cheltenham
Cotswold
Forest of Dean
Gloucester
Stroud
Tewkesbury
Swindon UA
Office for National Statistics | Research Report | 18
Method for Distributing Migrant ’Workers‘
UKD32
Greater Manchester
North
3
UKD31
Greater Manchester
South
3
UKJ3
2
UKJ33
Hampshire and Isle of
Wight
Hampshire CC
UKH23
Hertfordshire
3
UKI1
UKJ4
UKJ42
Inner London
Kent
Kent CC
2
2
3
UKD4
Lancashire
2
UKD43
Lancashire CC
3
3
00BL
00BM
00BP
00BQ
00BW
00BS
00BT
00BU
00MR
00MW
24UB
24UC
24UD
24UE
24UF
24UG
24UH
24UJ
24UL
24UN
24UP
26UB
26UC
26UD
26UE
26UF
26UG
26UH
26UJ
26UK
26UL
00AA
00LC
29UB
29UC
29UD
29UE
29UG
29UH
29UK
29UL
29UM
29UN
29UP
29UQ
00EX
00EY
30UD
30UE
30UF
30UG
30UH
30UJ
30UK
30UL
30UM
30UN
30UP
30UQ
Bolton
Bury
Oldham
Rochdale
Wigan
Stockport
Tameside
Trafford
Portsmouth UA
Isle of Wight UA
Basingstoke and Deane
East Hampshire
Eastleigh
Fareham
Gosport
Hart
Havant
New Forest
Rushmoor
Test Valley
Winchester
Broxbourne
Dacorum
East Hertfordshire
Hertsmere
North Hertfordshire
St0 Albans
Stevenage
Three Rivers
Watford
Welwyn Hatfield
City of London
Medway UA
Ashford
Canterbury
Dartford
Dover
Gravesham
Maidstone
Sevenoaks
Shepway
Swale
Thanet
Tonbridge and Malling
Tunbridge Wells
Blackburn with Darwen UA
Blackpool UA
Burnley
Chorley
Fylde
Hyndburn
Lancaster
Pendle
Preston
Ribble Valley
Rossendale
South Ribble
West Lancashire
Wyre
Office for National Statistics | Research Report | 19
Method for Distributing Migrant ’Workers‘
UKF22
Leicestershire CC and
Rutland
3
UKF30
Lincolnshire
3
UKD5
Merseyside
2
UKH13
Norfolk
3
UKE2
UKE22
North Yorkshire
North Yorkshire CC
2
3
UKF23
Northamptonshire
3
UKC2
Northumberland and
Tyne and Wear
2
UKI2
Outer London
2
UKI22
Outer London - South
3
UKJ14
Oxfordshire
3
00FP
31UB
31UC
31UD
31UE
31UG
31UH
31UJ
32UB
32UC
32UD
32UE
32UF
32UG
32UH
00BX
00BZ
00CA
00CB
33UB
33UC
33UD
33UE
33UF
33UG
33UH
00FF
36UB
36UC
36UD
36UE
36UF
36UG
36UH
34UB
34UC
34UD
34UE
34UG
34UH
00CH
00CK
00CL
00CM
35UB
35UC
35UD
35UE
35UF
35UG
00AD
00AR
00BD
00AF
00BF
38UB
38UD
38UE
38UF
Rutland UA
Blaby
Charnwood
Harborough
Hinckley and Bosworth
Melton
North West Leicestershire
Oadby and Wigston
Boston
East Lindsey
Lincoln
North Kesteven
South Holland
South Kesteven
West Lindsey
Knowsley
St0 Helens
Sefton
Wirral
Breckland
Broadland
Great Yarmouth
King's Lynn and West Norfolk
North Norfolk
Norwich
South Norfolk
York UA
Craven
Hambleton
Harrogate
Richmondshire
Ryedale
Scarborough
Selby
Corby
Daventry
East Northamptonshire
Kettering
South Northamptonshire
Wellingborough
Gateshead
North Tyneside
South Tyneside
Sunderland
Alnwick
Berwick-upon-Tweed
Blyth Valley
Castle Morpeth
Tynedale
Wansbeck
Bexley
Havering
Richmond upon Thames
Bromley
Sutton
Cherwell
South Oxfordshire
Vale of White Horse
West Oxfordshire
Office for National Statistics | Research Report | 20
Method for Distributing Migrant ’Workers‘
UKG2
Shropshire and
Staffordshire
2
UKK23
Somerset
3
UKG24
Staffordshire CC
3
UKH14
Suffolk
3
UKJ23
Surrey
3
UKJ2
Surrey, East and West
Sussex
2
UKC1
Tees Valley and
Durham
2
UKG35
Walsall and
Wolverhampton
Warwickshire
3
UKG13
3
00GF
00GL
39UB
39UC
39UD
39UE
39UF
40UB
40UC
40UD
40UE
40UF
41UB
41UC
41UD
41UE
41UF
41UG
41UH
41UK
42UB
42UC
42UE
42UF
42UG
42UH
43UB
43UC
43UD
43UE
43UF
43UG
43UH
43UJ
43UK
43UL
43UM
21UC
21UD
21UF
21UG
21UH
00EB
00EC
00EE
00EF
00EH
20UB
20UD
20UE
20UF
20UG
20UH
20UJ
00CU
00CW
44UB
44UC
44UD
Telford and Wrekin UA
Stoke-on-Trent UA
Bridgnorth
North Shropshire
Oswestry
Shrewsbury and Atcham
South Shropshire
Mendip
Sedgemoor
South Somerset
Taunton Deane
West Somerset
Cannock Chase
East Staffordshire
Lichfield
Newcastle-under-Lyme
South Staffordshire
Stafford
Staffordshire Moorlands
Tamworth
Babergh
Forest Heath
Mid Suffolk
St0 Edmundsbury
Suffolk Coastal
Waveney
Elmbridge
Epsom and Ewell
Guildford
Mole Valley
Reigate and Banstead
Runnymede
Spelthorne
Surrey Heath
Tandridge
Waverley
Woking
Eastbourne
Hastings
Lewes
Rother
Wealden
Hartlepool UA
Middlesbrough UA
Redcar and Cleveland UA
Stockton-on-Tees UA
Darlington UA
Chester-le-Street
Derwentside
Durham
Easington
Sedgefield
Teesdale
Wear Valley
Walsall
Wolverhampton
North Warwickshire
Nuneaton and Bedworth
Rugby
Office for National Statistics | Research Report | 21
Method for Distributing Migrant ’Workers‘
UKG3
West Midlands
2
UKJ24
West Sussex
3
UKL1
West Wales and The
Valleys
2
UKE4
West Yorkshire
2
UKK15
Wiltshire CC
3
UKG12
Worcestershire
3
44UE
44UF
00CR
00CT
45UB
45UC
45UD
45UF
45UG
45UH
00NA
00NC
00NE
00NG
00NQ
00NS
00NU
00NX
00NZ
00PB
00PF
00PH
00PK
00PL
00PM
00CY
00DB
46UB
46UC
46UD
46UF
47UB
47UC
47UD
47UE
47UF
47UG
Stratford-on-Avon
Warwick
Dudley
Solihull
Adur
Arun
Chichester
Horsham
Mid Sussex
Worthing
Isle of Anglesey
Gwynedd UA
Conwy
Denbighshire
Ceredigion UA
Pembrokeshire UA
Carmarthenshire UA
Swansea UA
Neath Port TalbotUA
Bridgend
Rhondda, Cynon, Taff UA
Merthyr Tydfil UA
Caerphilly
Blaenau Gwent
Torfaen
Calderdale
Wakefield
Kennet
North Wiltshire
Salisbury
West Wiltshire
Bromsgrove
Malvern Hills
Redditch
Worcester
Wychavon
Wyre Forest
Office for National Statistics | Research Report | 22
Method for Distributing Migrant ’Workers‘
Annex B: Example of LT migrant worker distribution method
B.1 Data that is used in the LT migrant worker distribution
This section presents applied examples of how the LT migrant worker estimate for mid-2008 is
produced for ten LAs. The methodology uses hypothetical data for the IPS total long-term workers
estimate for E&W split by subcontinent grouping (Table B.1).
Table B.1
IPS data used in the LT migrant worker distribution methodology
IPS totals for LT migrant workers
EU
Asia
Australia and New Zealand (Aus/NZ)
Rest of World (Rest)
2007/8
1200
500
500
200
This IPS data is distributed using the following hypothetical administrative data (Table B.2):
•
•
the number of LT worker, LT non-worker and ST migrants from the L2 by subcontinent
grouping
the total number of NINo registrations for each of these LAs from the MWS.
Table B.2
Administrative data used in the LT migrant worker distribution methodology
L2 migrants
EU
LT workers
Asia
Aus/NZ
Rest
Total
LT nonworkers
25
10
20
50
100
0
0
10
0
10
100
200
120
300
500
250
100
180
150
100
100
250
100
200
400
250
75
360
200
200
ST
MWS
All NINo
registrations
100
50
60
100
300
100
25
90
100
100
318
456
298
615
1348
731
189
678
359
412
LA
A
B
C
D
E
F
G
H
I
J
25
100
40
100
150
100
50
80
75
40
25
50
40
100
150
100
25
50
50
40
25
40
20
50
100
50
25
40
25
10
B.2 The distribution method
1) The proportion of LT migrant workers is calculated for each LA (Table B.3) using the following
formula:
Proportion of LT migrant workers = LT migrant workers / Sum (LT migrant workers + LT migrant
non-workers + ST migrants)
Office for National Statistics | Research Report | 23
Method for Distributing Migrant ’Workers‘
Table B.3
Calculating the Proportion of LT workers in the L2 for each LA
LT
workers
L2 migrants
LT nonworkers
100
200
120
300
500
250
100
180
150
100
100
250
100
200
400
250
75
360
200
200
ST
L2 based migrant proportions
LT
LT nonST
workers
workers
LA
A
B
C
D
E
F
G
H
I
J
100
50
60
100
300
100
25
90
100
100
0.33
0.40
0.43
0.50
0.42
0.42
0.50
0.29
0.33
0.25
0.33
0.50
0.36
0.33
0.33
0.42
0.37
0.57
0.44
0.50
0.33
0.10
0.21
0.17
0.25
0.17
0.13
0.14
0.22
0.25
2) The MWS count is then applied to the L2 based LT migrant worker proportion to calculate an LT
migrant worker estimate for each LA (Table B.4). The number of LT migrant workers is calculated
using the following formula:
LT migrant workers in LA A = MWS count in LA A * LT migrant worker in LA A
Table B.4
Applying the MWS count to the L2 based LT migrant worker proportions
MWS
LT
migrant
worker
proportion
LT
worker
318
456
298
615
1348
731
189
678
359
412
0.33
0.40
0.43
0.50
0.42
0.42
0.50
0.29
0.33
0.25
106
182
128
308
562
305
95
194
120
103
LA
A
B
C
D
E
F
G
H
I
J
3) A subcontinent weighting factor is calculated (Table B.5). This is calculated using the following
formula:
Subcontinent weighting factor = IPS subcontinent LT migrant worker estimate/L2 subcontinent LT
migrant worker estimate
Office for National Statistics | Research Report | 24
Method for Distributing Migrant ’Workers‘
Table B.5
Calculating the Subcontinent weighting factor
Subcontinent
grouping
EU15/A10
Asia
Australia/NZ
Rest
IPS
subcontinent LT
migrant worker
estimate
1200
500
500
200
L2 subcontinent
LT migrant
worker estimate
Subcontinent
weighting factor
760
630
385
225
1.58
0.79
1.30
0.89
4) The subcontinent weighting factor is applied to L2 LT migrant workers by subcontinent in each
LA to give a subcontinent weighted estimate in each LA (Table B.6). This is calculated using the
following formula:
Subcontinent LT migrant worker weighted estimate in LA A = L2 migrant worker subcontinent
count in LA A * subcontinent weighting factor
Table B.6
Calculating the Subcontinent LT Migrant Worker weighted estimate
EU
L2 LT migrant worker count
Asia
Aus/NZ
Rest
LA
A
B
C
D
E
F
G
H
I
J
Weighting
factor
25
100
40
100
150
100
50
80
75
40
25
50
40
100
150
100
25
50
50
40
25
40
20
50
100
50
25
40
25
10
25
10
20
50
100
0
0
10
0
10
1.58
0.79
1.30
0.89
EU*weight
Asia*weight
Aus/NZ*weight
Rest*weight
40
158
63
158
237
158
79
126
119
63
20
40
32
79
119
79
20
40
40
32
33
52
26
65
130
65
33
52
33
13
22
9
18
45
89
0
0
9
0
9
LA
A
B
C
D
E
F
G
H
I
J
Office for National Statistics | Research Report | 25
Method for Distributing Migrant ’Workers‘
5) The subcontinent weighted estimate is used to calculate the proportion of LT migrant workers in
each LA from each subcontinent. The split on the right hand side in Table B.7 is calculated using
the following example formula:
EU prop in LA A = EU weighted estimate in LA A / sum (EU+Asia+Aus/NZ+Rest) in LA A
Table B.7
Calculating the subcontinent split in each LA
EU
Weighted estimates
Asia
Aus/NZ
Rest
EU
22
9
18
45
89
0
0
9
0
9
0.35
0.61
0.46
0.46
0.41
0.52
0.60
0.56
0.62
0.54
Proportions
Asia
Aus/NZ
Rest
LA
A
B
C
D
E
F
G
H
I
J
40
158
63
158
237
158
79
126
119
63
20
40
32
79
119
79
20
40
40
32
33
52
26
65
130
65
33
52
33
13
0.17
0.15
0.23
0.23
0.21
0.26
0.15
0.17
0.21
0.27
0.28
0.20
0.19
0.19
0.23
0.22
0.25
0.23
0.17
0.11
0.19
0.03
0.13
0.13
0.15
0.00
0.00
0.04
0.00
0.08
6) The subcontinent proportional split that is calculated in step 5 is used to calculate the total
number of LT migrant workers (see step 2) in each subcontinent grouping in each LA (Table B.8).
EU LT migrant workers in LA A = Total LT migrant workers in LA A * EU prop in LA A
Table B.8
Calculating the total number of LT migrant workers in each subcontinent grouping in each
LA
Proportions
EU
Asia
Aus/NZ
Rest
LT
migrant
workers
LT migrant workers
EU
Asia
Aus/NZ
Rest
LA
A
B
C
D
E
F
G
H
I
J
0.35
0.61
0.46
0.46
0.41
0.52
0.60
0.56
0.62
0.54
0.17
0.15
0.23
0.23
0.21
0.26
0.15
0.17
0.21
0.27
0.28
0.20
0.19
0.19
0.23
0.22
0.25
0.23
0.17
0.11
0.19
0.03
0.13
0.13
0.15
0.00
0.00
0.04
0.00
0.08
106
182
128
308
562
305
95
194
120
103
37
111
58
140
232
160
57
108
75
56
18
28
29
70
116
80
14
34
25
28
30
37
24
58
127
66
24
45
20
11
21
6
16
40
87
0
0
8
0
8
7) The subcontinent LT migrant workers in each LA is used to calculate a LA percentage
distribution of LT migrant workers for each subcontinent (Table B.9).
Proportion of EU LT migrant workers in LA A = (EU LT migrant workers in LA A/Total EU LT
migrant workers)
Office for National Statistics | Research Report | 26
Method for Distributing Migrant ’Workers‘
Table B.9
Calculating the LA proportional distribution of LT migrant workers for each subcontinent
Count of LT migrant workers
EU
Asia Aus/NZ
Rest
Proportion of LT migrant workers
EU
Asia Aus/NZ
Rest
LA
A
B
C
D
E
F
G
H
I
J
Total
37
111
58
140
232
160
57
108
75
56
1034
18
28
29
70
116
80
14
34
25
28
442
30
37
24
58
127
66
24
45
20
11
442
21
6
16
40
87
0
0
8
0
8
186
0.04
0.11
0.06
0.14
0.22
0.15
0.06
0.10
0.07
0.05
1
0.04
0.06
0.07
0.16
0.26
0.18
0.03
0.08
0.06
0.06
1
0.07
0.08
0.05
0.13
0.29
0.15
0.05
0.10
0.05
0.02
1
0.11
0.03
0.09
0.22
0.47
0.00
0.00
0.04
0.00
0.04
1
8) This proportional distribution is then used to distribute the IPS subcontinent totals across the
LAs (Table B.10).
EU LT migrant worker estimate in LA A = IPS LT migrant worker EU total * Prop of EU LT migrant
workers in LA A
Office for National Statistics | Research Report | 27
Method for Distributing Migrant ’Workers‘
Table B.10
Distributing the IPS LT migrant subcontinent totals across the LAs
Proportions of LT migrant workers
EU
Asia
Aus/NZ
Rest
LA
A
B
C
D
E
F
G
H
I
J
0.04
0.11
0.06
0.14
0.22
0.15
0.06
0.10
0.07
0.05
0.04
0.06
0.07
0.16
0.26
0.18
0.03
0.08
0.06
0.06
0.07
0.08
0.05
0.13
0.29
0.15
0.05
0.10
0.05
0.02
0.11
0.03
0.09
0.22
0.47
0.00
0.00
0.04
0.00
0.04
IPS LT
migrant
total
1,200
500
500
200
LT migrant worker estimate
EU
Asia
Aus/NZ
Rest
LA
A
B
C
D
E
F
G
H
I
J
43
129
67
162
269
186
66
125
87
65
20
32
33
79
131
90
16
38
28
32
34
42
27
66
144
75
27
51
23
12
23
6
17
43
94
0
0
9
0
9
9) The subcontinent totals are then added together to get the overall LT migrant worker figure for
each LA (Table B11).
Table B.11
Calculating the overall LT migrant worker estimate for each LA
EU
Asia
Aus/NZ
Total
Rest
LA
A
B
C
D
E
F
G
H
I
J
43
129
67
162
269
186
66
125
87
65
20
32
33
79
131
90
16
38
28
32
34
42
27
66
144
75
27
51
23
12
23
6
17
43
94
0
0
9
0
9
120
209
144
350
638
351
109
223
138
118
Office for National Statistics | Research Report | 28