Pakistan Social & Living Standards Measurement survey (PSLM)Â is flagship survey of Pakistan Bureau of Statistics and the main mechanism to provide data for Monitoring Development plans at National/Provincial/District level for evidence-based policy making. PSLM surveys are being conducted since 2004 at alternate years and have become regular activity of PBS since 2015.
PSLM district level survey is the main source of monitoring developments plans at district level & its data used for Estimation of Multidimensional Poverty Index (MPI) by PD&SI. UN has adopted new development plan for post 2015 monitoring called Sustainable Development Goals (SDGs). Under SDGs there are 17 goals, 169 targets and 234 indicators. By considering the ground realities and SDGs, questionnaire of PSLM survey has been reviewed by technical committee. On the recommendations of technical committee changes has been incorporated and Modules regarding Disability, Migration, Information communication technology, Solid Waste Management, FIES and assets has been included in PSLM district level questionnaire for monitoring of related indicators at district level. Further 21 SDGs indicators will be reported through the survey at district level. In previous rounds of district level PSLM survey, the sample size of approximately 5300 block covering 80,000 households were covered. However, for PSLM 2019-20, sample size has been raised to 6500 blocks covering 195,000 households by considering disability variable, as disability is a rare event and for reliable estimates 30 household has been enumerated from each selected block. Further, AJ&K and GB at district level are covered in this survey; previously, AJ&K and GB were representative at overall province level.
The indicators are developed at district level in the following sectors.
Seven PSLM District Level Surveys have been completed 2004-05, 2006-07, 2008-09, 2010-11, 2012-13, 2014-15 and 2019-20
The Pakistan Social and Living Standards Measurement (PSLM) District Level Survey 2019-20 is a flagship initiative of the Pakistan Bureau of Statistics (PBS), designed to generate district-level estimates for key social sectors. This survey covered a nationally representative sample of 195,000 households, ensuring comprehensive data collection across the country.
A significant milestone in the history of PBS, this survey was the first to be conducted electronically, utilizing tablet-based data collection with an Android-based software developed exclusively by the Support Services Wing of PBS. This software, integrated with Enterprise Resource Planning (ERP) solutions, enhanced transparency, efficiency, and credibility in the data collection process. The adoption of digital methodologies also facilitated the timely availability of high-quality data, thereby strengthening evidence-based policymaking and research.
The Pakistan Bureau of Statistics (PBS) is the national statistical organization responsible for the collection, processing, compilation, and dissemination of official statistics across various sectors, supporting data-driven decision-making at the national and regional levels.
To ensure comprehensive and efficient data collection, PBS operates a network of 34 Regional Field Offices and 115 District Offices strategically located across Pakistan. These offices are fully equipped with modern resources and staffed with trained and experienced field personnel, ensuring the accurate and timely collection of data from diverse geographical and socio-economic settings. By leveraging its well-established infrastructure and professional workforce, PBS upholds the credibility, transparency, and reliability of national statistics, playing a crucial role in policy formulation, socio-economic planning, and development initiatives. The Field activities of the twelveth round of PSLM Surveys were carried out during October, 2019 to March, 2020.
Universe
The universe for survey consists of all urban and rural areas of four provinces of Pakistan, ICT, and Azad Jammu & Kashmir & Gilgit Baltistan excluded military restricted areas. It is worth mentioning here that areas of FATA now merged in Khyber Pakhtunkhwa have been covered in this survey.
Sampling Frame
After Census-2017 sample frame of PBS has been updated and now used for sample selection of PSLM 2019-20. Each enumeration block is comprised to 200-250 houses on the average with well-defined boundaries and maps. In urban areas each enumeration block is treated as PSU while in rural areas villages are divided into blocks with well-defined boundaries & maps and each separate block within village is considered as PSU.
The numbers of enumeration block in urban and rural areas of the country are:
NUMBER OF ENUMERATION BLOCKS AS PER SAMPLING FRAME 2017
| Province | Urban | Rural | Total |
Khyber Pakhtunkhwa | 3267 | 22538 | 25805 |
Punjab | 27162 | 59841 | 87003 |
Sindh | 21892 | 17239 | 39131 |
Balochistan | 1839 | 8383 | 10222 |
Islamabad | 726 | 789 | 1515 |
Azad Jammu & Kashmir | 526 | 3496 | 4022 |
Gilgit/Baltistan | 148 | 1098 | 1246 |
Total | 55560 | 113384 | 168944 |
Urban and rural part of each administrative district for all four provinces, Azad Jammu & Kashmir and Gilgit Baltistan has been considered as two separate independent stratums. Domain of estimation is district for all provinces.
A two stage stratified random sample design has been adopted for the survey.
Enumeration Blocks in both Urban and Rural domain are taken as Primary Sampling Units (PSUs). Sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS) method of sampling scheme. In both urban and rural domains, the number of households in an enumeration block has been taken as measure of size (MOS).
The households of sample PSUs have been taken as Secondary Sampling Units (SSUs). 30 households have been selected from urban and rural domains respectively by using systematic sampling technique. It is pertinent to mention here that prevalence of disability variable is rare, therefore, 30 households at the second stage has been selected randomly for true representation and coverage of disability variable. Previously, 12 and 16 households from urban and rural areas were selected respectively.
As already mentioned that disability variable has been added for the first time in district level PSLM survey, therefore, sample size has been estimated keeping in view the coverage and representation of rare event of disability variable. All socio-economic indicators i.e. Net Enrollment Rate, Prenatal care, Immunization etc. are representative at 5% Margin of Error (MOE) and Disability is representative at 11% MOE district level for four provinces of Pakistan.
Keeping in view the variation observed in the population about the characteristics for which estimates are to be developed, distribution of population in the urban & rural domains, geographical level of estimates required, availability of field resources and cost, and especially for disability variable coverage, the sample size of 195,000 households covering 6500 sampled areas (enumeration blocks & villages) have been considered sufficient to generate variable estimates at district level in respect of four provinces including Azad Jammu & Kashmir and GB.
 Province/Districts | SAMPLE PSUs | COVERED PSUs | ||||
| URBANBLOCKS | RURALBLOCKS | TOTAL | URBANBLOCKS | RURALBLOCKS | TOTAL | |
| PAKISTAN | 2005 | 4231 | 6236 | 1848 | 3825 | 5673 |
| PUNJAB | 932 | 2035 | 2967 | 901 | 1878 | 2779 |
| SINDH | 802 | 654 | 1456 | 720 | 622 | 1342 |
| KHYBERPAKHTUNKHWA | Â 127 | Â 903 | Â 1030 | Â 123 | Â 877 | Â 1000 |
| BALOCHISTAN | 144 | 639 | 783 | 104 | 448 | 552 |
607 sample blocks were not covered due to lockdown restriction implementation to control spread of COVID-19 pandemic, un-approachable/security problems/military restricted areas in the country. Province wise details of dropped areas are as under:
| Province | Urban | Rural | Total |
Khyber Pakhtunkhwa | 04 | 26 | 30 |
Punjab | 31 | 157 | 188 |
Sindh | 82 | 32 | 114 |
Balochistan | 40 | 191 | 231 |
Azad Jammu &Kashmir | 02 | 23 | 25 |
Gilgit/Baltistan | 01 | 18 | 19 |
Total | 160 | 447 | 607 |
Â
Population aged 10 years and older that can read and write a simple statement with understanding in any language expressed as percentage of total population aged 10 years and older.
Numerator of Literacy: – Population aged 10 years and older that is literate.sc1q01a(can a person read simple statement in any language with full understanding)=1 and sc1q02a(can a person write simple statement in any language with full understanding =1
Denominator of Literacy: – Population aged 10 years and older.
Disaggregated analysis by, age group, gender, region, and by quintile (only at provincial level) etc. are available in reports.
Out of School consists of those children age 5-16 years who have never been to school and those children who attended school and left afterwards.
Out of School =Never been to School + Dropout
Never Been to School:
Numerator: – Raised sum of all individuals aged 5-16 years who reported never been to school in educational status.
Denominator: -Raised sum of all individuals aged 5-16 years.
Dropout:
Numerator: – Raised sum of all individuals aged 5-16 years who reported attended school in the past(dropout).
Denominator: -Raised sum of all individuals aged 5-16 years
Disaggregated analysis by, age group, gender, region, and by quintile (only at provincial level) etc. are available in reports.
Net enrolment rate: [Number of children aged 6-10 years attending Primary level (classes 1-5) divided by number of children aged 6-10 years] multiplied by 100.
Numerator of NER: Raised sum of all individuals aged 6-10 years who report currently attending primary level class (1-5).
Denominator of NER: Raised sum of all individuals aged 6-10 years.
Disaggregated analysis by, age group, gender, region, and by quintile (only at provincial level) etc. are available in reports.
Net enrolment rate: [Number of children aged 11-13 years attending Middle Level (classes 6-8) divided by number of children aged 11-13 years] multiplied by 100.
Numerator of NER: Raised sum of all individuals aged 11-13 years who report currently attending Middle level class (6-8).
Denominator of NER: Raised sum of all individuals aged 11-13 years
Disaggregated analysis by, age group, gender, region, and by quintile (only at provincial level) etc. are available in reports.
Net enrolment rate: [Number of children aged 14-15 years attending Matric Level (classes 9-10) divided by number of children aged 14-15 years] multiplied by 100.
Numerator of NER: Raised sum of all individuals aged 14-15 years who report currently attending Matric level class (9-10).
Denominator of NER: Raised sum of all individuals aged 14-15 years.
Disaggregated analysis by, age group, gender, region, and by quintile (only at provincial level) etc. are available in reports.
Children aged 12-23 months who reported having received full immunization who also have an immunization card, expressed as a percentage of all children aged 12-23 months. To be classified as fully immunized a child must have received: ’BCG’, PENTA1, PENTA2, PENTA3, PNEUM1, PNEUM2, PNEUM3, Polio0, Polio1, Polio2, Polio3, IPV and Measles1.
Computation Method: –
It is calculated for all children who had a health card, using all immunizations reported, and these were recorded on the card. It is likely that all will have been recorded on the card.
Full immunization means that the child has received: BCG, PENTA1, PENTA2, PENTA3, PNEUM1, PNEUM2, PNEUM3, Polio0, Polio1, Polio2, Polio3, IPV and Measles1.
Disaggregation:
Disaggregated analysis available by gender, region, and by quintile (only at provincial level) etc.
Ever married women aged 15 – 49 years who had given birth in the last three years and who had attended at least one pre-natal consultation during the last pregnancy, expressed as a percentage of all ever married women aged 15 – 49 years who had given birth in the last three years.
Computation Method:-
Currently married women aged 15 – 49 years who had given birth in the last three years and who had attended at least one pre-natal consultation during the last pregnancy, expressed as a percentage of all currently married women aged 15 – 49 years who had given birth in the last three years.
Currently married women aged 15-49 years who had given birth in the last three years and who had attended a pre-natal consultation at the source indicated expressed as a percentage of all of the same women who had had a pre-natal consultation.
Disaggregation:
Disaggregated analysis available by gender, region, and by quintile (only at provincial level) etc.
UN has adopted new development plan for post 2015 monitoring called Sustainable Development Goals (SDGs). Under SDGs, initially there were 17 goals, 169 targets and approximately 505 indicators, after review and input from all member states now the indicators are reduced to 234 with 17 goals and 169 targets. SDGs have extensive and wider agenda tam MDGs and it put greater emphasis on disaggregation at all levels. Therefore  it will be important to improve the availability and access to data and statistics disaggregated by income, gender, age, race, ethnicity, migratory status, disability, geographic location and other characteristics relevant in national context.
As mentioned above PSLM survey was one of the main mechanism for monitoring of MDGs, therefore keeping in view the new development agenda of SDGs and changing ground realities, Technical committee for PSLM has been reconstituted with the approval of Chief Statistician to review the PSLM Questionnaire and recommend necessary amendments/inclusions.
| Indicator | Definition | Â | Â | Â | Â | 2018-19 | 2019-20 |
| 1.2.2 | Proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition | – | 14.6 | ||||
| 2.1.2 | Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES) | Â | 16% | ||||
| 3.1.2 | Proportion of births attended by skilled health personnel. | Â | 68% | ||||
| 3.b.1 | Proportion of the target population covered by all vaccines included in their national program | 68% | 70% | ||||
| 4.1.2 | Completion rate (primary education, lower secondary education, upper secondary education) | (a) 66% | (a) 67% | ||||
| Â | (b) Lower Secondary | (b) 46% | (b) 47% | ||||
| Â | (c) Upper Secondary | (c) 21% | (c) 23% | ||||
| 4.2.2 | Participation rate in organized learning (one year before the official primary entry age), by sex | 32% | 19% | ||||
| 4.6.1 | Percentage of population in a given age group achieving at least a fixed level of proficiency in functional (a) literacy and (b) numeracy skills, by sex. | 60% | 60% | ||||
| 5.b.1 | Proportion of individuals who own a mobile telephone, by sex | Â | 45% | ||||
| 6.1.1 | Proportion of population using safely managed drinking water services. | 95% 69% | 94% 74% | ||||
| 6.2.1 | Proportion of population using safely managed sanitation | (a) 70% | (a) 68% | ||||
| Â | (b) Specific place of hand-washing facility with soap and water. | (b) 50% | (b) 54% | ||||
| 7.1.1 | Proportion of population with access to electricity | 91% | 91% | ||||
| 7.1.2 | Proportion of population with primary reliance on clean fuels and technology | 35% | 37% | ||||
| 9.1.1 | Proportion of the rural population who live within 2 km of an all-season road | – | 88% | ||||
| 11.2.1 | Proportion of population that has convenient access to public transport by sex, age, and persons with disabilities. | Â | 44% | ||||
| 17.8.1 | Proportion of individuals using the Internet. | 17% | 19% | ||||