This is the Seventh Edition of the District Level Survey which is being conducted under the PSLM project from 2004 to 2015. It provides information at the National/ Provincial/District level with urban/ rural breakdown. This Survey has been designed to collect the data from 195000 households based on 6500 urban & rural Primary sampling units (PSUs). The period of field enumeration of PSLM 2019-20 was from October 2019 to March 2020.

Abstract

The PSLM Project is designed to provide Social & Economic indicators in the alternate years at provincial and district levels. The project was initiated in July 2004 and will continue up to June 2015. The data generated through surveys is used to assist the government In formulating the poverty reduction strategy as well as development plans at district level and for the rapid assessment of program in the overall context of MDGs. As such this survey is one of the main mechanisms for monitoring MDGs indicators. It provides a set of representative, population-based estimates of social indicators and their progress under the PRSP/MDGs. For Millennium Development Goals (MDGs), UN has set 18 targets for 48 indicators for its member countries to achieve by 2015. Pakistan has committed to implement 16 targets and 37 indicators out of which 6 targets and 13 indicators are monitored through PSLM Surveys. The PSLM surveys are conducted at district level and at Provincial level respectively at alternate years. PSLM District level survey collects information on key Social indicators whereas through provincial level surveys (Social & HIES) collects information on social indicators as well as on Income and Consumption while in specific sections also information is also collected about household size; the number of employed people and their employment status, main sources of income; consumption patterns; the level of savings; and the consumption of the major food items. However, Planning Commission also uses this data for Poverty analysis.

Another important objective of the PSLM Survey is to try to establish the distributional impact of development programs; whether the poor have benefited from the program or whether increased government expenditure on the social sectors has been captured by the better off. The sample size of PSLM surveys district level is approximately 80000 households and approximately 18000 at Provincial level.

Main Indicators: Indicators on Demographic characteristics, Education, Health, Employment, Household Assets, Household Amenities, Population Welfare and Water Supply & Sanitation are developed at National/Provincial /District levels.

Geographic coverage

National coverage

Analysis unit

Households and Individuals

Universe

The universe of this survey consists of all urban and rural areas of all four provinces, AJK and Gilgit Baltistan. FATA and Military restricted areas have been excluded from the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: Pakistan Bureau of statistics PBS has developed its own urban area frame. Each city/town is divided into enumeration blocks. Each enumeration block is comprised to 200-250 households on the average with well-defined boundaries and maps .The list of enumeration blocks as updated from field on the prescribed Performa by Quick Count Technique in 2013 for urban and the list of villages/mouzas/dehs or its part (block), updated during House listing in 2011 for conduct of Population Census, are taken as sampling frame. Enumeration blocks and villages are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively. A project to update the rural blocks is currently in hand.

Stratification Plan

Urban Areas: Large sized cities having population five laces and above have been treated as independent stratum. Each of these cities has further been sub-stratified into low, middle and high income groups. The remaining cities/towns within each defunct administrative division have been grouped together to constitute an independent stratum.

Rural Areas: The entire rural domain of a district for Khyber Pakhtunkhwa, Punjab, and Sindh provinces has been considered as independent stratum, whereas in Balochistan province defunct administrative division has been treated as stratum.

Sample Size and its Allocation: To determine optimum sample size for this survey, 6 indicators namely Literacy rate, Net enrolment rate at primary level, Population 10+ that ever attended school, Contraceptive prevalence of women age 15-49 years, Children age 12-23 months who are fully immunized and post natal consultation for ever married women aged 15-49 years were taken into consideration. Keeping in view the prevalence of these indicators at different margin of errors, reliability of estimates and field resources available a sample of size 19620 households distributed over 1368 PSUs (567 urban and 801 rural) has been considered sufficient to produce reliable estimates in respect of all four provinces with urban rural breakdown, however data was collected from 1307 PSU’S by covering 17989 household.

Sample Design: A two-stage stratified sample design has been adopted for this survey.

Selection of primary sampling Units (PSUs): Enumeration blocks in urban and rural domains have been taken as PSUs. In urban and rural domains sample PSUs from each stratum have been selected by PPS method of sampling scheme; using households in each block as Measure of size (MOS).

Selection of Secondary Sampling Units (SSUs): Households within PSU have been considered as SSUs. 16 and 12 households have been selected from urban/rural domains respectively by systematic sampling scheme with a random start.

Sampling deviation

Out of 1368 PSUs, of all four provinces 61 PSUs (11 urban and 50 rural PSUs) of Balochistan were dropped due to bad law and order situation and the remaining 1307 PSUs (556 urban and 751 rural) comprising 17989 households were covered.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

At both individual and household level, the PSLM Survey collects information on a wide range of topics using an integrated questionnaire. The questionnaire comprises a number of different sections, each of which looks at a particular aspect of household behavior or welfare. Data collected under Round IX includes education, diarrhea, immunization, reproductive health, pregnancy history, maternity history, family planning, pre and post-natal care and access to basic services.

Cleaning operations

Data quality in PSLM Survey has been ensured through a built in system of checking of field work by the supervisors in the field and by the in charge of the concerned Regional/Field offices. Teams from the headquarters also pay surprise visits and randomly check the work done by the enumerators. Regional/ Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried at the PBS headquarter Islamabad and specially designed data entry programme had a number of built in consistency checks.

Data appraisal

To determine the reliability of the estimates confidence interval and Standard error of important key indicators have been worked out and are attached at the end of each section of the survey report, provided under the 'Related Materials' tab

Introduction Effective policymaking relies on high-quality data to understand social contexts, identify target populations, and evaluate interventions. In low and middle-income countries (LMICs), household surveys often fill data gaps, providing insights into social dynamics and policy impacts. In Pakistan, the Pakistan Demographic Health Survey (PDHS) and Pakistan Social and Living Standards Measurement (PSLM) are crucial sources of information. While both surveys cover health and socioeconomic indicators, their methodologies and questionnaires vary, leading to potential discrepancies in data. Methods This paper compares PDHS 2017-18, PSLM 2018-19 (provincial level) and PSLM 2019-20 (district level) using family planning and child immunization modules as examples. Similar indicators under each section are examined for differences using weighted proportion t-test. For family planning, we analyzed PDHS 2017-18 and PSLM 2018-19 because PSLM 2019-20, doesn’t have family planning section. For immunization, we analyzed PDHS 2017-18, PSLM 2018-19 and PSLM 2019-20. Results Analysis reveals high concordance in family planning indicators with differences of within two percent. Differences in the rates of BCG which is given at birth are under one percent and for the first dose of pentavalent vaccine are near one percent. However, the differences start diverging thereafter and are near nine percent for dose 3 of the pentavalent vaccine. There is high level of concordance between the results of the provincial and district PSLM surveys conducted one year apart. Conclusion We describe the differences and relative similarities of the PSLM and PDHS surveys, as means to better incorporate their evidence in policy decisions. Both PSLM and PDHS serve a slightly different niche in that PDHS provides more in depth understanding of family planning whereas PSLM connects many health and social indicators with economic measures and gives granularity at the district level. However, to enhance the confidence of policymakers in both the surveys, we describe their concordance and differences and how they may be used in policy decisions.

Data from 500 x 5m palm transects in tropical American forests recording all palm individuals and assigning them to growthclasses from seedlings to adults. All palm records are geo-referenced to one 5 x 5m subunit of a transect. Additional ecological data are recorded to suppport the data.

About this dataset

Context

The dataset tabulates the Palm Coast population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Palm Coast across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Palm Coast was 102,113, a 3.72% increase year-by-year from 2022. Previously, in 2022, Palm Coast population was 98,455, an increase of 4.96% compared to a population of 93,805 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Palm Coast increased by 69,133. In this period, the peak population was 102,113 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Palm Coast is shown in this column.
• Year on Year Change: This column displays the change in Palm Coast population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Palm Coast Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Palm Desert population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Palm Desert across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Palm Desert was 51,951, a 0.33% increase year-by-year from 2022. Previously, in 2022, Palm Desert population was 51,781, an increase of 0.22% compared to a population of 51,668 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Palm Desert increased by 7,351. In this period, the peak population was 53,438 in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Palm Desert is shown in this column.
• Year on Year Change: This column displays the change in Palm Desert population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Palm Desert Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the West Palm Beach population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of West Palm Beach across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of West Palm Beach was 124,130, a 2.42% increase year-by-year from 2022. Previously, in 2022, West Palm Beach population was 121,200, an increase of 2.79% compared to a population of 117,915 in 2021. Over the last 20 plus years, between 2000 and 2023, population of West Palm Beach increased by 41,540. In this period, the peak population was 124,130 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the West Palm Beach is shown in this column.
• Year on Year Change: This column displays the change in West Palm Beach population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for West Palm Beach Population by Year. You can refer the same here

Graph and download economic data for Per Capita Personal Income in Palm Beach County, FL (PCPI12099) from 1969 to 2023 about Palm Beach County, FL; Miami; personal income; per capita; FL; personal; income; and USA.

This statistic shows the palm kernel oil consumption in the United States from 2000 to 2023. According to the report, domestic palm kernel oil consumption in the U.S. is expected to reach approximately *** thousand metric tons in 2023.

Graph and download economic data for Unemployment Rate in Palm Bay-Melbourne-Titusville, FL (MSA) (PALM312UR) from Jan 1990 to May 2025 about Palm Bay, FL, unemployment, rate, and USA.

Absolute differences in family planning indicators for PDHS and PSLM.

Graph and download economic data for Unemployment Rate in Palm Beach County, FL (FLPALM2URN) from Jan 1990 to May 2025 about Palm Beach County, FL; Miami; FL; unemployment; rate; and USA.

The dataset contains the data related to women empowerment from "PSLM Survey of Pakistan"

This dataset tracks annual distribution of students across grade levels in Palm Harbor Middle School

Historical Dataset of Palm Harbor Middle School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1987-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1987-2023),Asian Student Percentage Comparison Over Years (1992-2023),Hispanic Student Percentage Comparison Over Years (1992-2023),Black Student Percentage Comparison Over Years (1991-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1991-2023),Free Lunch Eligibility Comparison Over Years (1991-2023),Reduced-Price Lunch Eligibility Comparison Over Years (1999-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2010-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2010-2022)

Historical Dataset of Palm River Elementary School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1987-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1987-2023),Asian Student Percentage Comparison Over Years (1988-2012),Hispanic Student Percentage Comparison Over Years (1991-2023),Black Student Percentage Comparison Over Years (1991-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1991-2023),Free Lunch Eligibility Comparison Over Years (1991-2023),Reduced-Price Lunch Eligibility Comparison Over Years (1999-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2010-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2010-2022)

Historical Dataset of Palm Beach Central High School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2005-2023),Total Classroom Teachers Trends Over Years (2005-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2005-2023),Asian Student Percentage Comparison Over Years (2005-2023),Hispanic Student Percentage Comparison Over Years (2005-2023),Black Student Percentage Comparison Over Years (2005-2023),White Student Percentage Comparison Over Years (2005-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (2005-2023),Free Lunch Eligibility Comparison Over Years (2005-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2005-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2010-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2010-2022),Graduation Rate Comparison Over Years (2012-2022)

Historical Dataset of Palm Beach Lakes High School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1993-2023),Total Classroom Teachers Trends Over Years (1993-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1993-2023),Asian Student Percentage Comparison Over Years (1993-2023),Hispanic Student Percentage Comparison Over Years (1993-2023),Black Student Percentage Comparison Over Years (1993-2023),White Student Percentage Comparison Over Years (1993-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1993-2023),Free Lunch Eligibility Comparison Over Years (1993-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2002-2022),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2010-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2010-2022),Graduation Rate Comparison Over Years (2012-2022)

Historical Dataset of Coconut Palm K-8 Academy is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1987-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1987-2023),Asian Student Percentage Comparison Over Years (1988-2022),Hispanic Student Percentage Comparison Over Years (1991-2023),Black Student Percentage Comparison Over Years (1991-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1991-2023),Free Lunch Eligibility Comparison Over Years (1991-2023),Reduced-Price Lunch Eligibility Comparison Over Years (1999-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2011-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2011-2022)

Historical Dataset of Palm Canyon is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2013-2023),Total Classroom Teachers Trends Over Years (2013-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2013-2023),Asian Student Percentage Comparison Over Years (2013-2023),Hispanic Student Percentage Comparison Over Years (2013-2023),Black Student Percentage Comparison Over Years (2013-2023),White Student Percentage Comparison Over Years (2012-2023),Diversity Score Comparison Over Years (2013-2023),Free Lunch Eligibility Comparison Over Years (2012-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2016-2020)