Abstract

The Country Opinion Survey in Sri Lanka assists the World Bank Group (WBG) in gaining a better understanding of how stakeholders in Sri Lanka perceive the WBG. It provides the WBG with systematic feedback from national and local governments, multilateral/bilateral agencies, media, academia, the private sector, and civil society in Sri Lanka on 1) their views regarding the general environment in Sri Lanka; 2) their overall attitudes toward the WBG in Sri Lanka; 3) overall impressions of the WBG’s effectiveness and results, knowledge work and activities, and communication and information sharing in Sri Lanka; and 4) their perceptions of the WBG’s future role in Sri Lanka.

Geographic coverage

• Western Province
• Eastern Province
• Northern Province
• Southern Province
• North Western Province
• Central Province
• Uva Province
• Sabaragamuwa Province
• North Central Province

Analysis unit

Stakeholder

Universe

Opinion leaders from national and local governments, multilateral/bilateral agencies, media, academia, the private sector, and civil society.

Kind of data

Sample survey data [ssd]

Sampling procedure

From June to August 2021, 541 stakeholders of the WBG in Sri Lanka were invited to provide their opinions on the WBG’s work in the country by participating in a Country Opinion Survey. Participants were drawn from the Office of the President, Prime Minister; office of a Minister; office of a Parliamentarian; employees of ministries/ministerial departments/implementation agencies; Project Management Units (PMUs) overseeing implementation of WBG projects; consultants/contractors working on WBG-supported projects/programs; local governments; independent government institutions; the judiciary; state-owned enterprises; bilateral and multilateral agencies; private sector organizations; the financial sector and private banks; private foundations; NGOs and community-based organizations; faith-based groups; youth groups; academia/research institutes/think tanks; and the media.

Mode of data collection

Other [oth]

Research instrument

English, Sinhala and Tamil.

Response rate

47%

Sri Lanka Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 1.100 % in 2019. This records a decrease from the previous number of 1.700 % for 2016. Sri Lanka Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 1.700 % from Dec 2012 (Median) to 2019, with 3 observations. The data reached an all-time high of 3.500 % in 2012 and a record low of 1.100 % in 2019. Sri Lanka Multidimensional Poverty Headcount Ratio: World Bank: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sri Lanka – Table LK.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Graph and download economic data for Bank Deposits to GDP for Sri Lanka (DDOI02LKA156NWDB) from 1960 to 2019 about Sri Lanka, deposits, banks, depository institutions, and GDP.

Abstract

The World Bank is interested in gauging the views of clients and partners who are either involved in development in Sri Lanka or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the Bank's team that works in Sri Lanka, more in-depth insight into how the Bank's work is perceived. This is one tool the Bank uses to assess the views of its critical stakeholders. With this understanding, the World Bank hopes to develop more effective strategies, outreach and programs that support development in Sri Lanka. The World Bank commissioned an independent firm to oversee the logistics of this effort in Sri Lanka.

The survey was designed to achieve the following objectives: - Assist the World Bank in gaining a better understanding of how stakeholders in Sri Lanka perceive the Bank; - Obtain systematic feedback from stakeholders in Sri Lanka regarding: · Their views regarding the general environment in Sri Lanka; · Their perceived overall value of the World Bank in Sri Lanka; · Overall impressions of the World Bank as related to programs, poverty reduction, personal relationships, effectiveness, knowledge base, collaboration, and its day-to-day operation; and · Perceptions of the World Bank's communication and outreach in Sri Lanka. - Use data to help inform the Sri Lanka country team's strategy.

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Sri Lanka

Kind of data

Sample survey data [ssd]

Sampling procedure

In December 2011 and January 2012, 550 stakeholders of the World Bank in Sri Lanka were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from among the office of the President, Prime Minister, or Minister; employees of a ministry or ministerial department; the office of a Parliamentarian; Project Implementation Units (PIUs) or Project Management Units (PMUs); local government officials or staff; bilateral or multilateral agencies; private sector organizations; NGOs (including CBOs); the media; independent government institutions; trade unions; faith-based groups; academia or research institutes; and the judiciary.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Questionnaire consists of 8 Sections:

1. Background Information: The first section asked respondents for their current position; specialization; familiarity and involvement with the Bank; and geographic location.

2. General Issues facing Sri Lanka: Respondents were asked to indicate what they thought were the most important development priorities, and which areas would contribute most to poverty reduction and economic growth in Sri Lanka, as well as rating their perspective on the next generation in Sri Lanka.

3. Overall Attitudes toward the World Bank: Respondents were asked to rate the Bank’s overall effectiveness in Sri Lanka and their agreement with various statements regarding the Bank’s programs, poverty mission, relationships, and collaboration. Respondents were also asked to indicate the areas which they perceived as the Bank’s top priorities, the areas it would be most productive for the Bank to focus its resources and research, what the Bank’s level of involvement should be, the instrument most and least effective at reducing poverty in Sri Lanka, what they felt were the Bank’s greatest values and greatest weaknesses in its work, and with which groups the Bank should work more.

4. The Work of the World Bank: Respondents were asked to rate their level of importance and the Bank’s level of effectiveness across twenty-two areas in which the Bank was involved, such as helping to reduce poverty and encouraging greater transparency in governance.

5. The Way the World Bank does Business: Respondents were asked to rate the Bank’s level of effectiveness in the way it does business, including the Bank’s knowledge, personal relationships, collaborations, and poverty mission.

6. Project/Program Related Issues: Respondents were asked to rate their level of agreement with a series of statements regarding the Bank’s programs, day-to-day operations, and collaborations in Sri Lanka.

7. The Future of the World Bank in Sri Lanka: Respondents were asked to rate how significant a role the Bank should play in Sri Lanka’s development and to indicate what the Bank could to make itself of greater value and to what reasons respondents attributed failed or slow reform efforts.

8. Communication and Outreach: Respondents were asked to indicate where they get information about development issues and the Bank’s development activities in Sri Lanka, as well as how they prefer to receive information from the Bank. Respondents were also asked to indicate their awareness of the Bank’s Access to Information policy, their past experience requesting information, their access to the Internet, and their usage of the Bank’s website.

Response rate

A total of 296 stakeholders participated in the country survey (54%).

Sri Lanka LK: GDP: Final Consumption Expenditure: Households and NPISHs: Linked Series data was reported at 19,158,507.000 LKR mn in 2023. This records an increase from the previous number of 16,310,959.000 LKR mn for 2022. Sri Lanka LK: GDP: Final Consumption Expenditure: Households and NPISHs: Linked Series data is updated yearly, averaging 1,754,619.190 LKR mn from Dec 1990 (Median) to 2023, with 29 observations. The data reached an all-time high of 19,158,507.000 LKR mn in 2023 and a record low of 298,478.175 LKR mn in 1990. Sri Lanka LK: GDP: Final Consumption Expenditure: Households and NPISHs: Linked Series data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sri Lanka – Table LK.World Bank.WDI: Gross Domestic Product: Nominal. Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. This series has been linked to produce a consistent time series to counteract breaks in series over time due to changes in base years, source data and methodologies. Thus, it may not be comparable with other national accounts series in the database for historical years. Data are in local currency, at current prices.;World Bank staff estimates based on World Bank national accounts data archives, OECD National Accounts, and the IMF WEO database.;;

This dataset provides a comprehensive look at population and migration trends in five South Asian countries: Afghanistan, Bangladesh, India, Pakistan, and Sri Lanka, covering the years 1960 to 2023. The data is sourced directly from the World Bank API and contains detailed statistics on total population and net migration for each year.

This dataset is ideal for:

• Time-series analysis to study population trends over six decades.
• Migration studies to assess policy impacts and demographic shifts.
• Data visualization for dashboards and presentations.
• Machine learning applications in predictive analytics.

Columns: - Country: Name of the country. - Year: Year of the recorded data. - Total Population: The total population of the country. - Net Migration: Net migration balance (positive for immigration surplus, negative for emigration surplus).

Key Insights: - Afghanistan: Significant migration shifts due to conflicts and crises. - India: Continuous population growth with varying migration trends. - Bangladesh: A history of large emigration and its impact on demographics. - Pakistan: Migration surpluses in some years and large outflows in others. - Sri Lanka: Gradual population growth and consistent emigration patterns.

Individuals using the Internet (% of population) in Sri Lanka was reported at 51.2 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Sri Lanka - Individuals using the Internet (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Contains data from the World Bank's data portal covering the following topics which also exist as individual datasets on HDX: Agriculture and Rural Development, Aid Effectiveness, Economy and Growth, Education, Energy and Mining, Environment, Financial Sector, Health, Infrastructure, Social Protection and Labor, Poverty, Private Sector, Public Sector, Science and Technology, Social Development, Urban Development, Gender, Climate Change, External Debt, Trade.

Graph and download economic data for Population, Total for Sri Lanka (POPTOTLKA647NWDB) from 1960 to 2024 about Sri Lanka and population.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

National coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Sri Lanka is 1005.

Mode of data collection

Mobile telephone

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

Sri Lanka LK: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 39.800 % in 2016. This records an increase from the previous number of 39.200 % for 2012. Sri Lanka LK: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 37.800 % from Dec 1985 (Median) to 2016, with 8 observations. The data reached an all-time high of 41.000 % in 2002 and a record low of 32.400 % in 1990. Sri Lanka LK: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sri Lanka – Table LK.World Bank.WDI: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Graph and download economic data for Population Growth for Sri Lanka (SPPOPGROWLKA) from 1961 to 2024 about Sri Lanka, population, and rate.

Graph and download economic data for Literacy Rate, Adult Total for Sri Lanka (SEADTLITRZSLKA) from 1981 to 2023 about Sri Lanka, literacy, adult, and rate.

GDP, PPP (current international $) in Sri Lanka was reported at 342603896901 USD in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Sri Lanka - GDP, PPP (current international $) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Abstract

This data is from the first round of a unique, cross-country panel survey conducted in Sri Lanka by the Secure Livelihoods Research Consortium (SLRC). The Overseas Development Institute (ODI) is the lead organisation of SLRC. SLRC partners who participated in the survey were: the Centre for Poverty Analysis (CEPA) in Sri Lanka, Feinstein International Center (FIC, Tufts University), the Sustainable Development Policy Institute(SDPI) in Pakistan, Humanitarian Aid and Reconstruction, based at Wageningen University (WUR) in the Netherlands, the Nepal Centre for Contemporary Research (NCCR), and the Food and Agriculture Organization (FAO).

This survey generated the first round of data on people's livelihoods, their access to and experience of basic services, and their views of governance actors. SLRC will attempt to re-interview the same respondents in 2015 to find out how the livelihoods and governance perceptions of people shift (or not) over time, and which factors may have contributed towards that change.

Geographic coverage

Sri Lanka: Jaffna, Mannar and Trincomalee districts Rural and urban

Analysis unit

Some questions are at the level of individuals in household (e.g. livelihood activities, education levels); other questions are at the household level (e.g. assets). A sizeable share of the questionnaire is devoted to perceptions based questions, which are at the individual (respondent) level.

Universe

Randomly selected households in purposely sampled sites (sampling procedure varied slightly by country).

Within a selected household, only one household members was interviewed about the household. Respondents were adults and we aimed to interview a fairly even share of men/ women. In some countries this was achieved, but in other countries the share of male respondents is substantially higher (e.g. Pakistan).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy was designed to select households that are relevant to the main research questions and as well as being of national relevance, while also being able to produce statistically significant conclusions at the study and village level. To meet these objectives, purposive and random sampling were combined at different stages of the sampling strategy. The first stages of the sampling process involved purposive sampling, with random sampling only utilized in the last stage of the process. Sampling locations were selected purposely (including districts and locations within districts), and then randomly households were selected within these locations. A rigorous sample is geared towards meeting the objectives of the research. The samples are not representative for the case study countries and cannot be used to represent the case study countries as a whole, nor for the districts. The samples are representative at the village level, with the exception of Uganda.

Sampling locations (sub-regions or districts, sub-districts and villages) were purposively selected, using criteria, such as levels of service provision or levels of conflict, in order to locate the specific groups of interest and to select geographical locations that are relevant to the broader SLRC research areas and of policy relevance at the national level. For instance, locations experienced high/ low levels of conflict and locations with high/ low provision of services were selected and locations that accounted for all possible combinations of selection criteria were included. Survey locations with different characteristics were chose, so that we could explore the relevance of conflict affectedness, access to services and variations in geography and livelihoods on our outcome variables. Depending on the administrative structure of the country, this process involved selecting a succession of sampling locations (at increasingly lower administrative units).

The survey did not attempt to achieve representativeness at the country /or district level, but it aimed for representativeness at the sub-district /or village level through random sampling (Households were randomly selected within villages so that the results are representative and statistically significant at the village level and so that a varied sample was captured. Households were randomly selected using a number of different tools, depending on data availability, such as random selection from vote registers (Nepal), construction of household listings (DRC) and a quasi-random household process that involved walking in a random direction for a random number of minutes (Uganda).

The samples are statistically significant at the survey level and village level (in all countries) and at the district level in Sri Lanka and sub-region level in Uganda. The sample size was calculated with the aim to achieve statistical significance at the study and village level, and to accommodate the available budget, logistical limitations, and to account for possible attrition between 2012-2015. In a number of countries estimated population data had to be used, as recent population data were not available.

The minimum overall sample size required to achieve significance at the study level, given population and average household size across districts, was calculated using a basic sample size calculator at a 95% confidence level and confidence interval of 5. The sample size at the village level was again calculated at the using a 95% confidence level and confidence interval of 5. . Finally, the sample was increased by 20% to account for possible attrition between 2012 and 2015, so that the sample size in 2015 is likely to be still statistically significant.

The overall sample required to achieve the sampling objectives in selected districts in each country ranged from 1,259 to 3,175 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

One questionnaire per country that includes household level, individual level and respondent level perceptions based questions.

The general structure and content of the questionnaire is similar across all five countries, with about 80% of questions similar, but tailored to the country-specific process. Country-specific surveys were tailored on the basis of a generic survey instrument that was developed by ODI specifically for this survey.

The questionnaires are published in English.

Cleaning operations

CSPro was used for data entries in most countries.

Data editing took place at a number of stages throughout the processing, including: • Office editing and coding • During data entry • Structure checking and completeness • Extensive secondary editing conducted by ODI

Response rate

The required sample sizes were achieved in all countries. Response rates were extremely high, ranging from 99%-100%.

Sampling error estimates

No further estimations of sampling error was conducted beyond the sampling design stage.

Data appraisal

Done on an ad hoc basis for some countries, but not consistently across all surveys and domains.

Sri Lanka LK: BOP: Financial Account: Foreign Direct Investment: Net Inflows: % of GDP data was reported at 1.577 % in 2017. This records an increase from the previous number of 1.097 % for 2016. Sri Lanka LK: BOP: Financial Account: Foreign Direct Investment: Net Inflows: % of GDP data is updated yearly, averaging 1.064 % from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 2.850 % in 1997 and a record low of -0.030 % in 1977. Sri Lanka LK: BOP: Financial Account: Foreign Direct Investment: Net Inflows: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sri Lanka – Table LK.World Bank: Balance of Payments: Capital and Financial Account. Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. This series shows net inflows (new investment inflows less disinvestment) in the reporting economy from foreign investors, and is divided by GDP.; ; International Monetary Fund, International Financial Statistics and Balance of Payments databases, World Bank, International Debt Statistics, and World Bank and OECD GDP estimates.; Weighted average; Note: Data starting from 2005 are based on the sixth edition of the IMF's Balance of Payments Manual (BPM6).

Deposit money banks'' assets to GDP (%) in Sri Lanka was reported at 76.59 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Sri Lanka - Deposit money banks' assets to GDP - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Liabilities to BIS banks, locational, total in Sri Lanka was reported at 10357971000 in 2025, according to the World Bank collection of development indicators, compiled from officially recognized sources. Sri Lanka - Liabilities to BIS banks, locational, total - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Private credit by deposit money banks to GDP (%) in Sri Lanka was reported at 49.68 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Sri Lanka - Private credit by deposit money banks to GDP - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely-designed Household Survey includes modules that measure the cognitive skills (reading, writing and numeracy), socio-emotional skills (personality, behavior and preferences) and job-specific skills (subset of transversal skills with direct job relevance) of a representative sample of adults aged 15 to 64 living in urban areas, whether they work or not. The cognitive skills module also incorporates a direct assessment of reading literacy based on the Survey of Adults Skills instruments. Modules also gather information about family, health and language.

Geographic coverage

The STEP target population is the urban population aged 15 to 64 included. Sri Lanka sampled both urban and rural areas. Areas are classified as rural or urban based on each country's official definition.

Analysis unit

The units of analysis are the individual respondents and households. A household roster is undertaken at the start of the survey and the individual respondent is randomly selected among all household members aged 15 to 64 included. The random selection process was designed by the STEP team and compliance with the procedure is carefully monitored during fieldwork.

Universe

The target population for the Sri Lanka STEP survey comprised all non-institutionalized persons 15 to 64 years of age (inclusive) living in private dwellings in urban and rural areas of Sri Lanka at the time of data collection. Exclusions The target population excludes: - Foreign diplomats and non-nationals working for international organizations; - People in institutions such as hospitals or prisons; - Collective dwellings or group quarters; - Persons living outside the country at the time of data collection, e.g., students at foreign universities; - Persons who are unable to complete the STEP assessment due to a physical or mental condition, e.g., visual impairment or paralysis.

The sample frame for the selection of first stage sample units was the Census 2011/12

Kind of data

Sample survey data [ssd]

Sampling procedure

The Sri Lanka sample size was 2,989 households. The sample design is a 5 stage stratified sample design. The stratification variable is Urban-Rural indicator.

First Stage Sample The primary sample unit (PSU) is a Grama Niladari (GN) division. The sampling objective was to conduct interviews in 200 GNs, consisting of 80 urban GNs and 120 rural GNs. Because there was some concern that it might not be possible to conduct any interviews in some initially selected GNs (e.g. due to war, conflict, or inaccessibility, for some other reason), the sampling strategy also called for the selection of 60 extra GNs (i.e., 24 urban GNs and 36 rural GNs) to be held in reserve for such eventualities. Hence, a total of 260 GNs were selected, consisting of 200 'initial' GNs and 60 'reserve' GNs. Two GNS from the initial sample of GNs were not accessible and reserve sampled GNs were used instead. Thus a total of 202 GNs were activated for data collection, and interviews were conducted in 200 GNs. The sample frame for the selection of first stage sample units was the list of GNs from the Census 2011/12. Note: The sample of first stage sample units was selected by the Sri Lanka Department of Census & Statistics (DCS) and provided to the World Bank. The DCS selected the GNs with probability proportional to size (PPS), where the measure of size was the number of dwellings in a GN.

Second Stage Sample The second stage sample unit (SSU) is a GN segment, i.e., GN BLOCK. One GN Block was selected from each activated PSU (i.e., GN). According to the Sri Lanka survey firm, each sampled GN was divided into a number of segments, i.e., GN Blocks, with approximately the same number of households, and one GN Block was selected from each sampled GN.

Third Stage Sample The third stage sample unit is a dwelling. The sampling objective was to obtain interviews at 15 dwellings within each selected SSU.

Fourth Stage Sample The fourth stage sample unit is a household. The sampling objective was to select one household within each selected third stage dwelling.

Fifth Stage Sample The fourth stage sample unit is an individual aged 15-64 (inclusive). The sampling objective was to select one individual with equal probability from each selected household.

Please refer to the Sri Lanka STEP Survey Weighting Procedures Summary for additional information on sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

The STEP survey instruments include: (i) A Background Questionnaire developed by the WB STEP team. (ii) A Reading Literacy Assessment developed by Educational Testing Services (ETS).

All countries adapted and translated both instruments following the STEP Technical Standards: 2 independent translators adapted and translated the Background Questionnaire and Reading Literacy Assessment, while reconciliation was carried out by a third translator. - The survey instruments were both piloted as part of the survey pretest. - The adapted Background Questionnaires are provided in English as external resources. The Reading Literacy Assessment is protected by copyright and will not be published.

Cleaning operations

STEP Data Management Process 1. Raw data is sent by the survey firm 2. The WB STEP team runs data checks on the Background Questionnaire data. - ETS runs data checks on the Reading Literacy Assessment data. - Comments and questions are sent back to the survey firm. 3. The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data. 4. The WB STEP team and ETS check the data files are clean. This might require additional iterations with the survey firm. 5. Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies. 6. ETS scales the Reading Literacy Assessment data. 7. The WB STEP team merges the Background Questionnaire data with the Reading Literacy Assessment data and computes derived variables.

Detailed information data processing in STEP surveys is provided in the 'Guidelines for STEP Data Entry Programs' document provided as an external resource. The template do-file used by the STEP team to check the raw background questionnaire data is provided as an external resource.

Response rate

The response rate for Sri Lanka (urban and rural) was 63%. (See STEP Methodology Note Table 4).

Sampling error estimates

A weighting documentation was prepared for each participating country and provides some information on sampling errors. Weighting documentation is provided as an external resource.