Quarterly Labour Force Survey 2012
St. Lucia, 2012
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Identification
Survey ID Number
LCA_2012_QLFS-Q3_v01_M
Title
Quarterly Labour Force Survey 2012
Subtitle
Third Quarter
Country
| Name | Country code |
|---|---|
| St. Lucia | SLU |
Study type
Labor Force Survey [hh/lfs]
Series Information
The St. Lucia Labour Force Survey, 2012 Round 3 (LFS3) is the third round of the quaterly continuous labour force survey for 2012. The St Lucia Labour Force Survey was first conducted in 1992 when the first survey was completed with the assistance of the ILO regional office in Port of Spain Trinidad and Tobago. The ILO labour specialist who guided the process was Ms Grace Strachan. From 1994 to 2000 it has been a continous survey done during the first six and the last six months of each year, respectively. From the third quarter of 2002 to the first quarter of 2010 the survey was done continuously during the four quarters of each year with a rolling one week reference period.
For the periods from the 2nd quarter of 2010 to the 2nd quarter of 2011, no labour force survey was done, this was replaced by a labour module within the 2010 Census. From the 3rd quarter of 2011 to the present the continuous quarterly labour force survey has continued and is expected to continue into the forseeable future. The survey is coordinated by the Director of Statistics, Mr Edwin St Catherine who is the sampling and data processing specialist for the survey. He is assisted by Ms Jacinta Francis who is responsible for the maintenance, publication and dissemination of results. The two main supervisors for the survey are Ms Martha Joseph and Ms Urmain Gray. The regional ILO Office in Port of Spain continues to support the development and mordernisation of the survey through the support of Dr Reynold Simmons.
For the periods from the 2nd quarter of 2010 to the 2nd quarter of 2011, no labour force survey was done, this was replaced by a labour module within the 2010 Census. From the 3rd quarter of 2011 to the present the continuous quarterly labour force survey has continued and is expected to continue into the forseeable future. The survey is coordinated by the Director of Statistics, Mr Edwin St Catherine who is the sampling and data processing specialist for the survey. He is assisted by Ms Jacinta Francis who is responsible for the maintenance, publication and dissemination of results. The two main supervisors for the survey are Ms Martha Joseph and Ms Urmain Gray. The regional ILO Office in Port of Spain continues to support the development and mordernisation of the survey through the support of Dr Reynold Simmons.
Abstract
The Labour Force Survey aims to collect information on the supply side of the labour market. It provides information on the extent of available and unused labour time and on relationships between employment and income. Thus, the data collected can be used for:
Macro-economic monitoring:- from an economic point of view, a main objective of collecting data on the economically active population is to provide basic information on the size and structure of a country's workforce. The unemployment rate in particular is widely used as an overall indicator of the current performance of a country's economy.
Human resources development: The economy is changing all the time. In order to meet the needs of the changing economy, people need to be trained. These areas of training must therefore be identified.
Employment policies: For an economy to work at its maximum potential, all persons wanting to have work should have jobs. Some persons may wish to have full-time jobs, and can only find part-time work. We need to know what proportion of the labour force these people represent in order to assess the social effects of government employment policies.
Income Support and social programmes: For the majority of people, employment income is their main means of support. People need not only jobs, but more importantly, productive jobs in order to receive reasonable incomes. We need to know what levels of income are being earned by different groups of persons.
Macro-economic monitoring:- from an economic point of view, a main objective of collecting data on the economically active population is to provide basic information on the size and structure of a country's workforce. The unemployment rate in particular is widely used as an overall indicator of the current performance of a country's economy.
Human resources development: The economy is changing all the time. In order to meet the needs of the changing economy, people need to be trained. These areas of training must therefore be identified.
Employment policies: For an economy to work at its maximum potential, all persons wanting to have work should have jobs. Some persons may wish to have full-time jobs, and can only find part-time work. We need to know what proportion of the labour force these people represent in order to assess the social effects of government employment policies.
Income Support and social programmes: For the majority of people, employment income is their main means of support. People need not only jobs, but more importantly, productive jobs in order to receive reasonable incomes. We need to know what levels of income are being earned by different groups of persons.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Households;
- Individuals.
- Individuals.
Version
Version Description
- vQ1_2012: Basic raw data, obtained from data scanning and verification (before automated editing).
- vQ1_2012M: Edited data with derived variables and weights, second version, for internal use only.
File labeling:
LFSPQ1_2012 is the person file for the labour force survey for the 1st quarter of 2012
LFSHQ1_2012 is the housing file for the labour force survey for the 1st quarter of 2012
- vQ1_2012M: Edited data with derived variables and weights, second version, for internal use only.
File labeling:
LFSPQ1_2012 is the person file for the labour force survey for the 1st quarter of 2012
LFSHQ1_2012 is the housing file for the labour force survey for the 1st quarter of 2012
Version Date
2012-05-04
Version Notes
The core elements of the St Lucia Labour Force survey (LFS) has not changed very much from the 2nd Quarter of 2008. From the 2nd quarter of 2008 the reference periods within the LFS survey was updated from a 2-month reference period for seeking work to a four week period and from a three week period for availability to work to a one week reference period for availability to work. In addition, the question on availabity for additional work was updated to ensure the accurate measurement of under-employment. These changes have brought the St Lucia LFS in line with regional and international standards.
In the last three quarters of 2008 a module was added to the LFS questionnaire to collect data on the informal sector. This module was added to the employment section of the LFS questionnaire and included Question 27A to Question 27L. The inclusion of this section of the questionnaire allowed for the measurement of the formal and informal sector and the identification of formal and informal businesses based on the following cirteria:
The 1-2 Survey (1-represents the Labour Force Survey and 2-represents an establishment survey to obtain detailed establishment level data from persons identified in the LFS as self-employed with employees or self employed without employees) was helpful in setting the broad framework within which all enterprises and employees in St Lucia could be located. To classify an enterprise identified using this means as informal as opposed to formal, the following criteria was applied:
Criterion 1: The individual has to be an active worker (or owner of a business) aged 15 years old or above.
Cr. 2: This worker has to be the head of a business (self-employed as own-account worker or employer).
Cr. 3: The business does not keep formal accounts.( No Profit and Loss Account of balance Sheet)
Cr. 4: The type of ownership is a household/individual unincorporated enterprise.
Cr. 5: At least a part of the production is sold.
1-2 Survey which was done in combination with an investment climate survey helped to assist policy makers identify areas to assist with the development of small businesses
To incorporate the HUEM (Household Unincorporated Enterprises with Market Output). First the size of the sample desired was determined based on:
The key statistic/indicator to be generated by the labour force, the unemployment rate, on the informal Sector Survey side, key indicators, related to the numbers of persons whose status is
5. Self-employed with employee
6. Self-employed without employee
Total of 450 cases were expected, 350 were obtained. The sample was selected in such a way that it was large enough to reliably estimate some of the indicators stemming from the smallest sub-populations. In this case, it was numbers of self employed persons or the “unemployment rate”.
In the last three quarters of 2008 a module was added to the LFS questionnaire to collect data on the informal sector. This module was added to the employment section of the LFS questionnaire and included Question 27A to Question 27L. The inclusion of this section of the questionnaire allowed for the measurement of the formal and informal sector and the identification of formal and informal businesses based on the following cirteria:
The 1-2 Survey (1-represents the Labour Force Survey and 2-represents an establishment survey to obtain detailed establishment level data from persons identified in the LFS as self-employed with employees or self employed without employees) was helpful in setting the broad framework within which all enterprises and employees in St Lucia could be located. To classify an enterprise identified using this means as informal as opposed to formal, the following criteria was applied:
Criterion 1: The individual has to be an active worker (or owner of a business) aged 15 years old or above.
Cr. 2: This worker has to be the head of a business (self-employed as own-account worker or employer).
Cr. 3: The business does not keep formal accounts.( No Profit and Loss Account of balance Sheet)
Cr. 4: The type of ownership is a household/individual unincorporated enterprise.
Cr. 5: At least a part of the production is sold.
1-2 Survey which was done in combination with an investment climate survey helped to assist policy makers identify areas to assist with the development of small businesses
To incorporate the HUEM (Household Unincorporated Enterprises with Market Output). First the size of the sample desired was determined based on:
The key statistic/indicator to be generated by the labour force, the unemployment rate, on the informal Sector Survey side, key indicators, related to the numbers of persons whose status is
5. Self-employed with employee
6. Self-employed without employee
Total of 450 cases were expected, 350 were obtained. The sample was selected in such a way that it was large enough to reliably estimate some of the indicators stemming from the smallest sub-populations. In this case, it was numbers of self employed persons or the “unemployment rate”.
Scope
Notes
The scope of the Labour Force Survey includes:
- HOUSEHOLD: Household characteristics, quality of dwelling unit, available facilities, amount of rent paid and use of information communication technologies
- PERSONS: Demographic informaiton on all persons within the household, education and training recieved, current and usual activity status of persons, employment conditions such as hours worked, whether seeking additional work, indicators of quality of work performed by household members over the age of 14 years, the unemployed and conditions of unemployment, e.g. duration of unemployment, methods of upkeep by the unemployed. The economically inactive, intensions to join the labour force.
- HOUSEHOLD: Household characteristics, quality of dwelling unit, available facilities, amount of rent paid and use of information communication technologies
- PERSONS: Demographic informaiton on all persons within the household, education and training recieved, current and usual activity status of persons, employment conditions such as hours worked, whether seeking additional work, indicators of quality of work performed by household members over the age of 14 years, the unemployed and conditions of unemployment, e.g. duration of unemployment, methods of upkeep by the unemployed. The economically inactive, intensions to join the labour force.
Coverage
Geographic Coverage
National Coverage
Universe
The survey covered all de jure non-institutional household members (usual residents), it focuses on the employment, unemployment and current activity or inactivity status of all persons aged 15 years and over resident in the household.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Central Statistics Office of Saint Lucia | Ministry of Finance and Economic Affairs |
Producers
| Name | Affiliation | Role |
|---|---|---|
| International Labour Organisation | United Nations | Technical Support |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Governmment of Saint Lucia | GOSL | Finance |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Edwin St Catherine | Central Statistics Office | Survey Coordinator |
| Burt Collymore | Central Statistics Office | Database Systems Engineer |
| Jacinta Francis | Central Statistics Office | Statistician III |
| Martha Joseph | Central Statistics Office | Statistical Assistant |
Sampling
Sampling Procedure
Every quarter (three months) approximately 1,000 households are interviewed, there is a one third overlap between the households interviewed between each round of the survey.
The Multi-Stage sampling procedure developed for the St. Lucia MS (Master Sample) Frame is used for the execution of the labour force survey:
The two stage process of sample selection in the ST. LUCIA MS entails the selection of the PSUs within the districts. This is followed by the systematic selection of the cluster of households or USU (Ultimate Sampling Units) within the selected PSUs. The two stages in the design is elaborated as follows:
a. In the first stage, a sampling frame is constructed consisting of all of the enumeration districts from the census of 2001. The size of each enumeration district is measured in units of clusters of households. In the case of the ST. LUCIA MS, approximately seven or eight households were allocated per cluster. The clusters which are allocated to the EDs all have an equal probability of selection within the specified geographic domain in which they are allocated. In addition, the number of clusters allocated to an ED is a measure of the size of the ED. Clusters, therefore ensure the selection of EDs or Primary Sampling Units with probability proportional to the size of the ED. The ST. LUCIA MS frame consists of nine sub-samples / replicates, with each replicate selected with a probability of (1 / (16 * 9)) or 1 / 144.
b. In the second stage a non-compact cluster of households is selected within the selected PSU using systematic random sampling. There are three elements to the selection of this non-compact cluster. Firstly, there is the sample interval, which is a measure of the size of the ED in terms of the total number of households it contains. The larger the ED or PSU the larger will be the sample interval assigned and consequently the larger will be the number of clusters assigned to the ED. This approach ensures that the total number of households selected in any selected ED is approximately the same. In the case of the "Castries" in the ST. LUCIA MS frame the approximate number is five (5). Secondly, the random start is determined by use of a random number generator. With a Microsoft EXCEL spreadsheet the formulae takes the following form, =ROUND(RAND()*E1,0)+1, where E1 is the cell containing the sample interval (or total number of clusters assigned) RAND() is the function which generates the random number. The round() function is used to round the result to the nearest whole number. The third element of choosing the non compact cluster is a combination of the above. A random number (r) is choosen between 1 and the sample interval value, I, inclusive, then to this number is added the sample interval for the full list of households within the primary sample unit. Thus, the list of selected households would be r, r + I, r + 2I, r + 3I, r + 4I,……, r + (n - 1)I, where n is the cluster size assigned to the district, in the case of Castries n is five.
A. Size of the Sample
As has been explained before the decision to use a sampling fraction of 1 : 16 and to assign nine replicates to each District (the geographic domain) was based on the need to take advantage of the small size of the countries covered by this MECOVI project. This was done by increasing the "spread" of the sample across EDs and as a result improving the precision of the estimates which can be obtained from it. In addition, attention was paid to ensuring that were the CSO of ST. LUCIA to consider developing further its Integrated Household Survey Programme, the ground work would have been laid through this Master Sample Frame design for periodic, ad hoc or continuous sample surveys. The achievement of this objective has already been demonstrated through the use of this Sample Frame in the conduct of St. Lucia's continuous Labour Force Survey.
Therefore for any one sub-sample given that there are nine, the sampling fraction is 1 / 16 by 1 / 9 or 1 / 144. If a periodic, ad hoc or quarterly survey included the use of three replicates then the sampling fraction for these three replicates would be 3 / 144 or 1 /16 by 3 / 9. In both cases the resultant sampling fraction is the product of the sampling probability for the Master Sampling frame and the probability of selection of a specific number of replicates.
B. Master Sample Domains of Study and Stratification
1. Domains of Study:
The Master Sample frame was subdivided into eleven areas for the purpose of the provision of estimates from samples selected from this frame. The following list of the ten domains or sub-populations is based on the Districts which formed the basis for the collection of information on the population in the 2001 Census.
The total number of PSUs in the ST. LUCIA MS is 401, a breakdown of the number of PSUs by District is shown in the table above. The average size of the PSUs was 118 approximately with a standard deviation of approximately 47. This configuration does not in the near term present a major problem for sample implementation, since the EDs/PSUs size does not exceed 100 by too great an extent, in addition, while consideration must be given to splitting EDs which have grown in size to over 200, there are not as exist in the case of St. Vincent and the Grenadines a significant number of excessively large EDs. Continuous maintenance of this situation is required and can be done by splitting all EDs over 200 in size into smaller ones of approximate size 100. The main objective of controlling the size of the PSUs, is to reduce variability and thereby improve the precision of estimates from the sample. The more equal the sizes of the PSUs the more likely the variance of characteristics between PSUs will be minimized and inversely the precision of the samples derived from the estimates from the Master Sample Frame increased.
2. Stratification
As shown in the table above each of the domains of study was stratified according to specific criteria. In the more urban domains the criteria used was the percentage of Managers, professional, sub-professionals in the population. The PSUs or EDs were therefore arranged in descending order of the proportion of this group in the population of the ED. In the rural domains the PSUs were arranged in descending order of the proportion of agriculture workers in the population of the ED. In the case of Canaries and Anse-la-Raye, the sizes of the populations in these domains mandated a joining of the two to allow for the creation of a large enough domain for reporting purposes.
The Multi-Stage sampling procedure developed for the St. Lucia MS (Master Sample) Frame is used for the execution of the labour force survey:
The two stage process of sample selection in the ST. LUCIA MS entails the selection of the PSUs within the districts. This is followed by the systematic selection of the cluster of households or USU (Ultimate Sampling Units) within the selected PSUs. The two stages in the design is elaborated as follows:
a. In the first stage, a sampling frame is constructed consisting of all of the enumeration districts from the census of 2001. The size of each enumeration district is measured in units of clusters of households. In the case of the ST. LUCIA MS, approximately seven or eight households were allocated per cluster. The clusters which are allocated to the EDs all have an equal probability of selection within the specified geographic domain in which they are allocated. In addition, the number of clusters allocated to an ED is a measure of the size of the ED. Clusters, therefore ensure the selection of EDs or Primary Sampling Units with probability proportional to the size of the ED. The ST. LUCIA MS frame consists of nine sub-samples / replicates, with each replicate selected with a probability of (1 / (16 * 9)) or 1 / 144.
b. In the second stage a non-compact cluster of households is selected within the selected PSU using systematic random sampling. There are three elements to the selection of this non-compact cluster. Firstly, there is the sample interval, which is a measure of the size of the ED in terms of the total number of households it contains. The larger the ED or PSU the larger will be the sample interval assigned and consequently the larger will be the number of clusters assigned to the ED. This approach ensures that the total number of households selected in any selected ED is approximately the same. In the case of the "Castries" in the ST. LUCIA MS frame the approximate number is five (5). Secondly, the random start is determined by use of a random number generator. With a Microsoft EXCEL spreadsheet the formulae takes the following form, =ROUND(RAND()*E1,0)+1, where E1 is the cell containing the sample interval (or total number of clusters assigned) RAND() is the function which generates the random number. The round() function is used to round the result to the nearest whole number. The third element of choosing the non compact cluster is a combination of the above. A random number (r) is choosen between 1 and the sample interval value, I, inclusive, then to this number is added the sample interval for the full list of households within the primary sample unit. Thus, the list of selected households would be r, r + I, r + 2I, r + 3I, r + 4I,……, r + (n - 1)I, where n is the cluster size assigned to the district, in the case of Castries n is five.
A. Size of the Sample
As has been explained before the decision to use a sampling fraction of 1 : 16 and to assign nine replicates to each District (the geographic domain) was based on the need to take advantage of the small size of the countries covered by this MECOVI project. This was done by increasing the "spread" of the sample across EDs and as a result improving the precision of the estimates which can be obtained from it. In addition, attention was paid to ensuring that were the CSO of ST. LUCIA to consider developing further its Integrated Household Survey Programme, the ground work would have been laid through this Master Sample Frame design for periodic, ad hoc or continuous sample surveys. The achievement of this objective has already been demonstrated through the use of this Sample Frame in the conduct of St. Lucia's continuous Labour Force Survey.
Therefore for any one sub-sample given that there are nine, the sampling fraction is 1 / 16 by 1 / 9 or 1 / 144. If a periodic, ad hoc or quarterly survey included the use of three replicates then the sampling fraction for these three replicates would be 3 / 144 or 1 /16 by 3 / 9. In both cases the resultant sampling fraction is the product of the sampling probability for the Master Sampling frame and the probability of selection of a specific number of replicates.
B. Master Sample Domains of Study and Stratification
1. Domains of Study:
The Master Sample frame was subdivided into eleven areas for the purpose of the provision of estimates from samples selected from this frame. The following list of the ten domains or sub-populations is based on the Districts which formed the basis for the collection of information on the population in the 2001 Census.
The total number of PSUs in the ST. LUCIA MS is 401, a breakdown of the number of PSUs by District is shown in the table above. The average size of the PSUs was 118 approximately with a standard deviation of approximately 47. This configuration does not in the near term present a major problem for sample implementation, since the EDs/PSUs size does not exceed 100 by too great an extent, in addition, while consideration must be given to splitting EDs which have grown in size to over 200, there are not as exist in the case of St. Vincent and the Grenadines a significant number of excessively large EDs. Continuous maintenance of this situation is required and can be done by splitting all EDs over 200 in size into smaller ones of approximate size 100. The main objective of controlling the size of the PSUs, is to reduce variability and thereby improve the precision of estimates from the sample. The more equal the sizes of the PSUs the more likely the variance of characteristics between PSUs will be minimized and inversely the precision of the samples derived from the estimates from the Master Sample Frame increased.
2. Stratification
As shown in the table above each of the domains of study was stratified according to specific criteria. In the more urban domains the criteria used was the percentage of Managers, professional, sub-professionals in the population. The PSUs or EDs were therefore arranged in descending order of the proportion of this group in the population of the ED. In the rural domains the PSUs were arranged in descending order of the proportion of agriculture workers in the population of the ED. In the case of Canaries and Anse-la-Raye, the sizes of the populations in these domains mandated a joining of the two to allow for the creation of a large enough domain for reporting purposes.
Response Rate
On average the response rate on the Saint Lucia Labour force survey is over 85%.
Weighting
Sample weights were calculated for each of the data files. Sample weights for the household data were computed as the inverse of the probability of selection of the household, computed at the sampling domain level (Districts). The household weights were adjusted for non-response at the domain level, and were then normalized by a constant factor so that the total weighted number of households equals the total unweighted number of households. The household weight variable is called WU and is used with the HH data and the Person weight variable is called WT and is used with the persons dataset.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2012-07-01 | 2012-09-30 | Round 3 - 2012 |
Data Collection Mode
Face-to-face [f2f]
Supervision
The role of the supervisor is to coordinator field data collection activities, including management of the field teams, supplies and equipment, finances, maps and listings. Additionally, the field supervisor assigned the work to the interviewers, spot checked work, maintained field control documents, and sent completed questionnaires and progress reports to the central office.
The field editor is responsible for checking for missed questions, skip errors, fields incorrectly completed, and checking for inconsistencies in the data.
The field editor is responsible for checking for missed questions, skip errors, fields incorrectly completed, and checking for inconsistencies in the data.
Data Collection Notes
During the quarterly conduct of the labour force survey, sixty nine enumeration districts are visited each month. Approximately 15 interviewers are employed to conduct the survey. Within the Statistical Office two supervisors are responsible for allocating each interviewer to an enumeration district for the conduct of follow-up field visits and telephone calls to households if clarification on responses obtained by enumerators is required. Each interviewer is allocated between 5 to 7 interviews to conduct within the enumeration district based on a specific sample interval. The interview is given an evelope with 7 to 10 questionnaires, a visitation record from the 2010 Census of population and housing or a subsequently updated listing of households and an enumeration district map.
SAINT LUCIA FIELD PROCEDURES
1. The Officer Supervisor (who in this case is also the field supervisor) receives the attached list of EDs for the month from me, in this case it is the month of March 2013. The list has the following headings:
DISTRICT SUBSAMPLE EDNumber H/HLDS INTERVAL
START 1 2 3 4
DISTRICT - District of Residence
SUBSAMPLE - SubSample Number
EDNumber - Enumeration District Number
H/HLDS - Number of household in the Enumeration District
INTERVAL - Sample Interval (if household number 3, 11, 19, 27 are selected the interval is 8)
START-This is a random start equal to or less than the sample interval, in our example this is 3
1 (The column heading 1, indicates that this is the first household to be interviewed, it is the same as the random start household, in our example this is household 3)
2 (The column heading 2, indicates that this is the second household to be interviewed, it is the same as the random start household plus the sample interval, in our example this is household 11)
3 (The column heading 3, indicates that this is the third household to be interviewed, it is the same as the second household number plus the sample interval, in our example this is household 19) etc
The office supervisor then writes in the DISTRICT No, SUBSAMPLE No, EDNumber and the selected household number on the front cover of each of the 7 households questionnaires selected to be interviewed for the Enumeration District (represented by the enumeration district numberor EDNumber). This is so because the total number of households in the ED is 55 and the last household to be interviewed will be household number 51. The seven blank questionnaires with this information written on the front cover of each is placed in an envelop with the ED Number written on the envelop. A few additional blank questionnaires are also placed in the envelop in case a question is damaged and has to be re-written.
The office supervisor then places two additional items in the envelop for the enumerator:
1) The Visitation Record: In the example I am using the ED Number is 01903. I have attached an actual visitation record so you can see exactly how our addresses are written on an actual visitation record which is the main document we use to locate the selected household.Using the visitation record the enumerator will be required to visit households numbers, note on the visitation record the column is headed "Household Number"
For household numbers 003, 011, 019, 027 in the visitation record the enumerator will find the address of household number as (see actual visitation record attached 01903VisitationRecord)
a) 003 Across the Bridge - Buhdoo Catherine (name of head of household) located at Trou, Rouge
b) 011 Dorville, Ann - (name of head of household) located at Trou, Rouge
c) 019 Everlyn, Beverly - (name of head of household) located at Trou, Rouge
The building number is used in some cases to identify the household number to interview where there are building numbers on the Map corresponding to building numbers on the visitation record.
2) An ED Map: I have attached the map for ED 01903 here as an example, in many cases these maps are numbered with building numbers which assist in the location of the correct household number as shown in the case of ED 00200 which is attached. The visitation record can be matched to the map and they are in sequence.
The enumerator having received an ED Map, a visitation record and seven questionnaire with the EDNumber and household number written on each questionnaire has all needed to locate the household and conduct the interview. The enumerator then writes in the address on the questionnaire, this address can easily be verified by the Office/Field Supervisor as shown above.
Upon completion of the interview the enumerator returns to the office with the completed questionnaires. The supervisor checks that all questionnaire contain a phone number on the front cover and any details of missing information with the enumerator. The enumeratorleaves the office and the supervisor randomly calls households to verify the responses provided on the questionnaire. If the information cannot be validated over the phone the Supervisor makes a personal visit to the respondent to verify the content of the interview. Afterthis random check the envelope of seven completed questionnaires is accepted and sent to the coder/editor for subsequent scanning.
SAINT LUCIA FIELD PROCEDURES
1. The Officer Supervisor (who in this case is also the field supervisor) receives the attached list of EDs for the month from me, in this case it is the month of March 2013. The list has the following headings:
DISTRICT SUBSAMPLE EDNumber H/HLDS INTERVAL
START 1 2 3 4
DISTRICT - District of Residence
SUBSAMPLE - SubSample Number
EDNumber - Enumeration District Number
H/HLDS - Number of household in the Enumeration District
INTERVAL - Sample Interval (if household number 3, 11, 19, 27 are selected the interval is 8)
START-This is a random start equal to or less than the sample interval, in our example this is 3
1 (The column heading 1, indicates that this is the first household to be interviewed, it is the same as the random start household, in our example this is household 3)
2 (The column heading 2, indicates that this is the second household to be interviewed, it is the same as the random start household plus the sample interval, in our example this is household 11)
3 (The column heading 3, indicates that this is the third household to be interviewed, it is the same as the second household number plus the sample interval, in our example this is household 19) etc
The office supervisor then writes in the DISTRICT No, SUBSAMPLE No, EDNumber and the selected household number on the front cover of each of the 7 households questionnaires selected to be interviewed for the Enumeration District (represented by the enumeration district numberor EDNumber). This is so because the total number of households in the ED is 55 and the last household to be interviewed will be household number 51. The seven blank questionnaires with this information written on the front cover of each is placed in an envelop with the ED Number written on the envelop. A few additional blank questionnaires are also placed in the envelop in case a question is damaged and has to be re-written.
The office supervisor then places two additional items in the envelop for the enumerator:
1) The Visitation Record: In the example I am using the ED Number is 01903. I have attached an actual visitation record so you can see exactly how our addresses are written on an actual visitation record which is the main document we use to locate the selected household.Using the visitation record the enumerator will be required to visit households numbers, note on the visitation record the column is headed "Household Number"
For household numbers 003, 011, 019, 027 in the visitation record the enumerator will find the address of household number as (see actual visitation record attached 01903VisitationRecord)
a) 003 Across the Bridge - Buhdoo Catherine (name of head of household) located at Trou, Rouge
b) 011 Dorville, Ann - (name of head of household) located at Trou, Rouge
c) 019 Everlyn, Beverly - (name of head of household) located at Trou, Rouge
The building number is used in some cases to identify the household number to interview where there are building numbers on the Map corresponding to building numbers on the visitation record.
2) An ED Map: I have attached the map for ED 01903 here as an example, in many cases these maps are numbered with building numbers which assist in the location of the correct household number as shown in the case of ED 00200 which is attached. The visitation record can be matched to the map and they are in sequence.
The enumerator having received an ED Map, a visitation record and seven questionnaire with the EDNumber and household number written on each questionnaire has all needed to locate the household and conduct the interview. The enumerator then writes in the address on the questionnaire, this address can easily be verified by the Office/Field Supervisor as shown above.
Upon completion of the interview the enumerator returns to the office with the completed questionnaires. The supervisor checks that all questionnaire contain a phone number on the front cover and any details of missing information with the enumerator. The enumeratorleaves the office and the supervisor randomly calls households to verify the responses provided on the questionnaire. If the information cannot be validated over the phone the Supervisor makes a personal visit to the respondent to verify the content of the interview. Afterthis random check the envelope of seven completed questionnaires is accepted and sent to the coder/editor for subsequent scanning.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Central Statistical Office | CSO | Ministry of Finance, Economic Affairs and Social Security |
Questionnaires
Questionnaires
The questionnaire is administered to all members of the household. Questions 1 through 6 are to be completed for all members of the household, these questions cover age, sex, relation to head of household, country of birth etc. All subsequent questions refer to persons 15 year of age and older. The questionnaire is divided into five parts:
PART 1:For all members of the household (regardless of age) - Demographic and emigration questions
PART 2: To be completed for persons 15 years and older - Education, Training, activities during the reference week or month, working at a job, on vacation, methods of seeking work, availability for employment
PART 3: For persons employed during the reference week - Number of actual hours of work, number of usual hours of work, seeking additional work, status in employment, industry and occupation of employment
PART 3A: For persons holding more than one job during the reference week - Number of actual hours of work, number of usual hours of work, seeking additional work, status in employment, industry and occupation of employment
PART 4: For persons unemployed during the reference week - Lenght of unemployment, means of support, occupation in last job
PART 5: For persons not in the labour force during the reference week, first seekers, means of support, intention to join the labour force in the future.
The questionnaire used to conduct the labour force survey is provided as an external resource.
PART 1:For all members of the household (regardless of age) - Demographic and emigration questions
PART 2: To be completed for persons 15 years and older - Education, Training, activities during the reference week or month, working at a job, on vacation, methods of seeking work, availability for employment
PART 3: For persons employed during the reference week - Number of actual hours of work, number of usual hours of work, seeking additional work, status in employment, industry and occupation of employment
PART 3A: For persons holding more than one job during the reference week - Number of actual hours of work, number of usual hours of work, seeking additional work, status in employment, industry and occupation of employment
PART 4: For persons unemployed during the reference week - Lenght of unemployment, means of support, occupation in last job
PART 5: For persons not in the labour force during the reference week, first seekers, means of support, intention to join the labour force in the future.
The questionnaire used to conduct the labour force survey is provided as an external resource.
Data Processing
Data Editing
Data editing takes place at a number of stages throughout the processing, including:
a) Office editing and coding when the questionnaires are delivered to the Statistics Office by the enumerators
b) During data verification of the scanned questionnaire
c) Structure checking and consistency editing and completeness is performed after data capture to MS SQL Server
d) Secondary editing is completed in CSPRO where a software program for this purpose have been written
e) Final production of SPSS data files after all editing is completed in CSPRO.
a) Office editing and coding when the questionnaires are delivered to the Statistics Office by the enumerators
b) During data verification of the scanned questionnaire
c) Structure checking and consistency editing and completeness is performed after data capture to MS SQL Server
d) Secondary editing is completed in CSPRO where a software program for this purpose have been written
e) Final production of SPSS data files after all editing is completed in CSPRO.
Data Appraisal
Estimates of Sampling Error
Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts are made during implementation of the quarterly labour force survey to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.
If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formulae for calculating sampling errors. However, the quarterly labour force sample survey is the result of a multi-stage stratified design, and consequently needs to use more complex formulae. The SPSS complex samples module is being used to calculate sampling errors for the quarterly labour force survey for St Lucia. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. This method is documented in the SPSS file CSDescriptives.pdf found under the Help, Algorithms options in SPSS.
Sampling errors have been calculated for a select set of statistics (all of which are proportions due to the limitations of the Taylor linearization method) for the national sample. For each statistic for which sample errors are computed, the estimate, its standard error, the coefficient of variation (or relative error -- the ratio between the standard error and the estimate), the design effect, and the square root design effect (DEFT -- the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used), as well as the 95 percent confidence intervals (+/-2 standard errors).
Details of the sampling errors are presented in the sampling errors table presented in the external resources.
If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formulae for calculating sampling errors. However, the quarterly labour force sample survey is the result of a multi-stage stratified design, and consequently needs to use more complex formulae. The SPSS complex samples module is being used to calculate sampling errors for the quarterly labour force survey for St Lucia. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. This method is documented in the SPSS file CSDescriptives.pdf found under the Help, Algorithms options in SPSS.
Sampling errors have been calculated for a select set of statistics (all of which are proportions due to the limitations of the Taylor linearization method) for the national sample. For each statistic for which sample errors are computed, the estimate, its standard error, the coefficient of variation (or relative error -- the ratio between the standard error and the estimate), the design effect, and the square root design effect (DEFT -- the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used), as well as the 95 percent confidence intervals (+/-2 standard errors).
Details of the sampling errors are presented in the sampling errors table presented in the external resources.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Director of Statistics | Central Statistics Office | edwins@stats.gov.lc | www.stats.gov.lc |
| Jacinta Francis | Central Statistics Office | edwins@stats.gov.lc | www.stats.gov.lc |
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Access authority
| Name | Affiliation | URL |
|---|---|---|
| Central Statistics Office of Saint Lucia | Ministry of Finance and Economic Affairs | www.stats.gov.lc |
Metadata production
DDI Document ID
DDI_LCA_2012_QLFS-Q3_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Central Statistics Office of St. Lucia | CSO-SLU | Ministry of Finance, Economic Affairs and National Development | Documentation of the Labour Force Survey |
Date of Metadata Production
2012-09-28
DDI Document version
Version 1.0 (September 2012)
Version 2.0 (March 2014) Modified by the World Bank Microdata Library.
Version 2.0 (March 2014) Modified by the World Bank Microdata Library.