The literacy rate measures the percentage of people aged 15 and above who are able to read and write. In 2019, Pakistan's total literacy rate was around 58 percent, with less than 46.49 percent of women being literate and more than 69.29 percent of men.

Women in Pakistan need education

In Pakistan, women’s education is in dire need of improvement, and so far, the number of illiterate women has not decreased - on the contrary, it has been going up for years. Although education for both genders is not prohibited in Pakistan, women are generally not as well educated as men. But it doesn’t stop there: Pakistan is one of the countries deemed worst for women in general when it comes to quality of life and safety.

Economy and education

Pakistan is a predominantly Muslim country with a low urbanization rate, meaning the majority of its population live in rural areas, where education is traditionally harder to come by than in cities. Pakistan is still a developing country, and typically, most of the inhabitants work in the primary sector, since Pakistan is rich in arable land. However, the tertiary sector generates the lion’s share of GDP. If the country wants to make the leap to being a developed nation, education and equality need to be higher on the list.

Actual value and historical data chart for Pakistan Literacy Rate Adult Total Percent Of People Ages 15 And Above

Pakistan PK: Literacy Rate: Youth Female: % of Females Aged 15-24 data was reported at 65.548 % in 2014. This records an increase from the previous number of 63.438 % for 2013. Pakistan PK: Literacy Rate: Youth Female: % of Females Aged 15-24 data is updated yearly, averaging 61.463 % from Dec 1981 (Median) to 2014, with 11 observations. The data reached an all-time high of 65.548 % in 2014 and a record low of 23.833 % in 1981. Pakistan PK: Literacy Rate: Youth Female: % of Females Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Pakistan PK: Literacy Rate: Adult: % of People Aged 15 and Above data was reported at 56.977 % in 2014. This records an increase from the previous number of 55.595 % for 2013. Pakistan PK: Literacy Rate: Adult: % of People Aged 15 and Above data is updated yearly, averaging 54.893 % from Dec 1981 (Median) to 2014, with 11 observations. The data reached an all-time high of 56.977 % in 2014 and a record low of 25.725 % in 1981. Pakistan PK: Literacy Rate: Adult: % of People Aged 15 and Above data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Education Statistics. Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Graph and download economic data for Literacy Rate, Adult Total for Pakistan (SEADTLITRZSPAK) from 1981 to 2021 about Pakistan, literacy, adult, and rate.

Historical dataset showing Pakistan literacy rate by year from 1981 to 2019.

Actual value and historical data chart for Pakistan Literacy Rate Youth Female Percent Of Females Ages 15 24

Pakistan PK: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 data was reported at 0.822 Ratio in 2014. This records an increase from the previous number of 0.799 Ratio for 2013. Pakistan PK: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 data is updated yearly, averaging 0.777 Ratio from Dec 1981 (Median) to 2014, with 11 observations. The data reached an all-time high of 0.822 Ratio in 2014 and a record low of 0.536 Ratio in 1981. Pakistan PK: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Education Statistics. Gender parity index for youth literacy rate is the ratio of females to males ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Yearly (annual) dataset of the Pakistan Adult Literacy Rate, including historical data, latest releases, and long-term trends from 1981-12-31 to 2019-12-31. Available for free download in CSV format.

Pakistan PK: Literacy Rate: Youth: % of People Age 15-24 data was reported at 72.795 % in 2014. This records an increase from the previous number of 71.636 % for 2013. Pakistan PK: Literacy Rate: Youth: % of People Age 15-24 data is updated yearly, averaging 70.769 % from Dec 1981 (Median) to 2014, with 11 observations. The data reached an all-time high of 72.795 % in 2014 and a record low of 34.783 % in 1981. Pakistan PK: Literacy Rate: Youth: % of People Age 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Pakistan PK: Literacy Rate: Youth Male: % of Males Aged 15-24 data was reported at 79.766 % in 2014. This records an increase from the previous number of 79.404 % for 2013. Pakistan PK: Literacy Rate: Youth Male: % of Males Aged 15-24 data is updated yearly, averaging 79.144 % from Dec 1981 (Median) to 2014, with 11 observations. The data reached an all-time high of 80.288 % in 2012 and a record low of 44.503 % in 1981. Pakistan PK: Literacy Rate: Youth Male: % of Males Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Pakistan: Ratio of female to male students in tertiary level education: The latest value from 2023 is 0.96 percent, an increase from 0.95 percent in 2022. In comparison, the world average is 1.16 percent, based on data from 62 countries. Historically, the average for Pakistan from 1971 to 2023 is 0.67 percent. The minimum value, 0.27 percent, was reached in 1992 while the maximum of 1.07 percent was recorded in 2014.

Financial overview and grant giving statistics of Pakistan Literacy Fund

Pakistan Literacy Rate: Male: Urban data was reported at 82.400 % in 2015. This records an increase from the previous number of 81.600 % for 2014. Pakistan Literacy Rate: Male: Urban data is updated yearly, averaging 80.300 % from Jun 2006 (Median) to 2015, with 9 observations. The data reached an all-time high of 82.400 % in 2015 and a record low of 77.100 % in 2006. Pakistan Literacy Rate: Male: Urban data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G007: Vital Statistics: Sex Ratio & Literacy Rate.

Description: This dataset presents comprehensive employment and demographic statistics for various districts across Pakistan, with a focus on gender-specific and regional insights. The dataset covers a range of indicators related to the labor market, population, and literacy rates, offering valuable insights into the socio-economic landscape of the country.

Columns: - Province: The administrative division within Pakistan. - Division: Subdivisions within provinces. - District: The specific geographic districts within divisions. - Indicator: This column captures a diverse set of socio-economic indicators, including but not limited to: - Total Population: The total population of the district. - Employment Rate: The proportion of the working-age population currently employed. - Labor Force: The number of individuals actively participating in the labor force. - Working Age Population: The count of individuals within the working-age bracket. - Literacy Rate: The percentage of the population with basic literacy skills. - Gender-specific Employment Data: Employment data for both male and female populations, including employment rates, labor force participation, and more. - Area Type: Distinguishes between urban and rural areas within districts. - Total: Represents the total value of the corresponding indicator, typically combining both male and female data. - Male: Provides gender-specific data for male individuals. - Female: Provides gender-specific data for female individuals.

Significance of the "Indicator" Column: The "Indicator" column serves as the key to understanding various socio-economic aspects of each district in Pakistan. It offers a comprehensive view of the employment landscape, population dynamics, and literacy rates. By analyzing different indicators, researchers and data enthusiasts can gain insights into: - The distribution of employment opportunities across regions and gender. - The educational attainment of the population. - Labor force participation and unemployment trends. - Demographic variations within districts.

This dataset empowers analysts to explore the nuances of employment and demographic patterns, facilitating evidence-based research and informed policy decisions. Whether you're interested in gender-specific employment, literacy rates, or overall labor market dynamics, this dataset provides a valuable resource for in-depth investigations and data-driven insights into Pakistan's diverse socio-economic landscape.

Women Education Rate in South Asia (1960-2010)

Data sourced from the (World Bank), analyzing the percentage of women without education across South Asia over five decades, for different age groups.

Dataset Overview

This dataset contains information on the percentage of women aged 15 and older with no education across South Asian countries from 1960 to 2010. The data is recorded every five years, capturing the changes in education levels for women in countries like Afghanistan, Bangladesh, India, Pakistan, Nepal, and Sri Lanka.

The dataset includes the percentage of women without education in the following age groups with details of countries and years:

Columns

• 15-19 years
• 20-24 years
• 25-29 years
• 30-34 years
• 35-39 years
• 40-44 years
• 45-49 years
• 50-54 years
• 55-59 years
• 60-64 years
• 65-69 years
• 70-74 years
• Above 75 years
• Country: The country in South Asia.
• Year: The year in which the data was recorded (every 5 years from 1960 to 2020).

The data provides valuable insights into the education gaps faced by women of different age groups in South Asia, and how these gaps have evolved over time. It helps in analyzing regional differences, trends over time, and the impact of education policies on women's educational outcomes.

Usage

This dataset can be used for:

• Trend analysis on the improvement or decline of female education across different age groups.
• Comparative analysis between countries in South Asia.
• Understanding the socio-economic factors influencing female education rates in various age groups.

This statistic shows the number of illiterate adults in Pakistan from 2008 to 2015. In 2013, approximately ***** million individuals in Pakistan were illiterate.

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

Abstract

The main objective of the interventions supported by this impact evaluation is to strengthen linkages between communities and school to improve education outcomes. Rigorous evidence generated from the research will provide valuable information to Pakistani policy makers, donors and development practitioners on the ways in which school based management reforms can be strengthened in low-governance environments like Sindh, Pakistan. The findings of this research are valuable for the ongoing dialogue with the GoSindh on school based management, one of the critical reform area supported under the Second Sindh Education Sector Program (SEP-II).

The impact evaluation is a component of the World Bank's ongoing technical and advisory support to the Government of Sindh for improving the quality and performance of government primary schools as part of its medium-term, multi-pronged Sindh Education Sector Reform Program (SERP-II). An important subprogram under SERP and SERP-II has been the revitalization of school management committees (SMCs) in government schools, with the provision of annual school improvements grants and basic guidelines on SMCs rights, roles and responsibilities across Sindh province. An area of concern in these early efforts has been poor or dissipating community interest and engagement. The interventions piloted in select districts of rural Sindh were designed by the World Bank in partnership with the Reform Support Unit, which is the implementation arm of the Education and Literacy Department of GoSindh. The aim of these interventions was to explore concrete ways to elicit meaningful and sustained local community engagement in improving education outcomes.

Both the baseline survey and the interventions were implemented in three pilot districts in 2012 and 2013. The core intervention being evaluated is community engagement to revitalize SMCs under two distinct mechanisms: 1) a community-level meeting to engage the community in a dialogue for school improvement via SMCs; 2) a virtual network of community members to engage in a similar dialogue supported through text messages on mobile phones.

The first intervention arm makes use of an existing social platform, enabling community members to participate in traditional meetings to acquire information and engage the community in dialogue and discussion on school-related issues. The second arm has created an innovative virtual platform through which registered community members receive school-related information, anonymously send text messages about these issues and receive a summary of key observations or issues twice every month.

The baseline survey, documented here, was implemented in January 2012 - January 2013. There is no midline survey for this study. The endline survey will start in January 2015.

Geographic coverage

Mirpur Khas, Mitiari and Sanghar districts in Sindh province.

Analysis unit

The unit of randomization for the intervention is a village.

Administered questionnaires have the following units of analysis: individuals (teachers, students, parents), households, schools, and communities.

Universe

All primary schools and rural households in Mirpur Khas, Mitiari and Sanghar districts in Sindh province.

Kind of data

Sample survey data [ssd]

Sampling procedure

The districts chosen for the study were based on district ranks in terms of school density in the district and school participation rates from the Pakistan Social and Living Standards Measurement Survey (PSLM) and Administrative School Census (ASC) data respectively. One district each was chosen from the low, middle and top category to make an overall representative sample of rural Sindh. By this method, the final districts selected were Mirpur Khas, Mitiari and Sanghar. Using the ASC data in terms of number of schools, Mitiari was ranked the third smallest district, Mirpur Khas was ranked at number twelve (middle rank) and Sanghar at number eighteen (top rank). Using the PSLM for education indicators (proportion of adults who ever attended school and school participation rate of primary-age children), Sanghar ranked at the top followed by Mitiari (median) and lastly by Mirpur Khas.

The Administrative School Census (ASC) data is collected by the Government of Sindh every year to provide an updated list of primary schools in all districts of Sindh. The census data for 2010-2011 was used to randomly draw 300 villages within our sample districts. However, because of poor quality of administrative census data, researchers conducted a census listing of all households and also mapped all primary schools in these 300 villages to set the population frame for the study.

• School Sampling Strategy

The school sampling strategy was primarily to target all primary schools in the main settlement that were either open on the day of visit or closed for a period of less than one year. In addition, 15% of the remaining schools in these villages were also surveyed to capture spillover effects. For villages with no school in the main settlement, all schools located out of the main settlement were surveyed1. For villages that did not meet these criteria, all schools were sampled even if the school was closed for more than one year. 4 villages had to be dropped because no school was found in village-level mapping of primary schools.

• Household Sampling Strategy

The household sampling strategy for each village was to randomly select 20 households from the main settlement and 8 households from the peripheral settlements conditional on the household having at least one child of school going age (5-16 years). From this list, the first 16 households were to be surveyed and in case the head of the household was not available, the household was substituted from the list of four buffer households. For the peripheral settlement, any 4 out of the 8 households were surveyed2. In addition, household questionnaires were also administered to all SMC members from the target schools, approximately 4 households in a village.

Overall, on the school level 514 school, 454 head teacher, 409 teacher and 4,573 student questionnaires were administered. On the household level, 6,505 head of the household, 6,503 spouse, 5,281 child and 901 school management committee questionnaires were administered.

Mode of data collection

Face-to-face [f2f]

Research instrument

School Surveys

Detailed data on school-level variables such as enrollment, attendance, teacher on-task, facilities, school committees, funding and expenditure were collected through a set of four questionnaires: School Observation, Teacher Roster, Head Teacher and Teacher Questionnaire. In addition, a list of School Management Committees (SMC) members was enumerated at the school-level for household surveys.

School Observation Questionnaire

School questionnaire consisted of five sections and was based on the observation of the enumerator about school building, facilities, hygiene conditions, on-going classroom practices and teacher activities. The questionnaire also required the enumerator to record school GPS coordinates and school visit details.

Head Teacher Questionnaire

Head Teacher questionnaire compromised of two parts: information based on the head teacher’s knowledge and information based on official school records. The first part gathered data on the respondent’s personal and professional background as well as his knowledge of students, school facilities and SMC. The second part collected official school details on school improvement plan, enrollment, attendance, fee, SMC funds and expenditures.

School Teacher Questionnaire

Teacher questionnaire consisted of nine sections and was administered to all teachers present in the school . It gathered the personal and professional information of the teacher as well as his perceptions on SMC functionality, student learning and returns to education.

Teacher Roster Questionnaire

Teacher Roster collected information on teachers that are currently teaching in the school and those that left or transferred over the last two years. The survey recorded teacher information on attendance, contact number, gender, contract type, pay scale and class taught. For teachers that have left, it also covered information on reasons for leaving school. The information for the roster is to be provided by the head teacher or the senior most teacher in the school.

Household Surveys

The baseline survey also covered households to gather information on demographic and socioeconomic characteristics, parent choices about child’s school, parent engagement with school’s SMC, adult perceptions of returns to schooling and quality of learning through four set of questionnaires: Household Roster, Household Head Questionnaire, Spouse of Head Questionnaire and SMC Member Questionnaire.

Household Roster Questionnaire

The household roster questionnaire collected information about gender, age, marital status, education and job status of all members of the household. This roster information was filled by the head of the household but in case of his absence, the survey was filled by other members that were required to explain their relationship to the head.

Head of the Household Questionnaire

The head of the household questionnaire consisted of fifteen sections and collected detailed information on family members, education, consumption pattern, business details, household expenditures and incomes. It also recorded information on about the respondent’s aspirations, awareness about the SMC, trust in the education system and perceptions about returns to education and quality of learning in the respective school.

Questionnaire for Female

Pakistan PK: Educational Attainment: At Least Bachelor's or Equivalent: Population 25+ Years: Total: % Cumulative data was reported at 8.753 % in 2014. This records an increase from the previous number of 7.991 % for 2013. Pakistan PK: Educational Attainment: At Least Bachelor's or Equivalent: Population 25+ Years: Total: % Cumulative data is updated yearly, averaging 7.991 % from Dec 2012 (Median) to 2014, with 3 observations. The data reached an all-time high of 8.753 % in 2014 and a record low of 7.542 % in 2012. Pakistan PK: Educational Attainment: At Least Bachelor's or Equivalent: Population 25+ Years: Total: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed Bachelor's or equivalent.; ; UNESCO Institute for Statistics; ;