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Chart and table of population level and growth rate for the La Paz, Bolivia metro area from 1950 to 2025.
4,37,473 (Persons) in 2012.
The highest city in the world with a population of more than one million is La Paz. The Capital of Bolivia sits ***** meters above sea level, and is more than 1,000 meters higher than the second-ranked city, Quito. La Paz is also higher than Mt. Fuji in Japan, which has a height of 3,776 meters. Many of the world's largest cities are located in South America. The only city in North America that makes the top 20 list is Denver, Colorado, which has an altitude of ***** meters.
937.904 (Persons) in 2012.
https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/E12DBWhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/E12DBW
KAV 6572 cover memo
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.
The cities that are covered are La Paz, El Alto, Cochabamba and Santa Cruz de la Sierra.
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 15 to 64 years old. The random selection process was designed by the STEP team and compliance with the procedure is carefully monitored during fieldwork.
The STEP target population is the population 15-64 years old, living in urban areas, as defined by each country's statistical office. The following are excluded from the sample: - Residents of institutions (prisons, hospitals, etc.) - Residents of senior homes and hospices - Residents of other group dwellings such as college dormitories, halfway homes, workers' quarters, etc. - Persons living outside the country at the time of data collection
Sample survey data [ssd]
Stratified 3-stage sample design was implemented in Bolivia. The stratification variable is city-wealth category. There are 20 strata created by grouping the primary sample units (PSUs) into the 4 cities, i.e.,1- La Paz, 2-El Alto, 3-Cochabamba, 4-Santa Cruz de la Sierra, and 5 wealth categories, i.e., 1-Poorest, 2-Moderately Poor, 3-Middle Wealth, 4-Moderately Rich, 5-Rich.
The source of the sample frame of the first stage units is the 2001 National Census of Population and Housing carried out by the National Institute of Statistics. The primary sample unit (PSU) is a Census Sector. A sample of 218 PSUs was selected from the 10,304 PSUs on the sample frame. This sample of PSUs was comprised of 160 'initial' PSUs and 58 'reserve' PSUs. Of the 218 sampled PSUs, there were 169 activated PSUs consisting of 155 Initial Sampled PSUs and 14 Reserve sampled PSUs. Among the 160 'initial' PSUs, 5 PSUs were replaced due to security concerns; also, 14 reserve PSUs were activated to supplement the sample for initial PSUs where the target sample of 15 interviews was not achieved due to high levels of non-response; thus, only 169 PSUs were actually activated during data collection. The PSUs were grouped according to city-wealth strata, and within each city-wealth stratum PSUs were selected with probability proportional to size (PPS), where the measure of size was the number of households in a PSU.
The second stage sample unit (SSU) is a household. The sampling objective was to obtain interviews at 15 households within each of the initial PSU sample, resulting in a final initial sample of 2,400 interviews. At the second stage of sample selection, 45 households were selected in each PSU using a systematic random method. The 45 households were randomly divided into 15 'Initial' households, and 30 'Reserve' households that were ranked according to the random sample selection order. Note: Due to higher than expected levels of non-response in some PSUs, additional households were sampled; thus, the final actual sample in some PSUs exceeded 45 households.
The third stage sample unit was an individual 15-64 years old (inclusive). The sampling objective was to select one individual with equal probability from each selected household.
Face-to-face [f2f]
The STEP survey instruments include:
All countries adapted and translated both instruments following the STEP technical standards: two independent translators adapted and translated the STEP background questionnaire and Reading Literacy Assessment, while reconciliation was carried out by a third translator.
The survey instruments were piloted as part of the survey pre-test.
The background questionnaire covers such topics as respondents' demographic characteristics, dwelling characteristics, education and training, health, employment, job skill requirements, personality, behavior and preferences, language and family background.
The background questionnaire, the structure of the Reading Literacy Assessment and Reading Literacy Data Codebook are provided in the document "Bolivia STEP Skills Measurement Survey Instruments", available in external resources.
STEP data management process:
1) Raw data is sent by the survey firm 2) The World Bank (WB) STEP team runs data checks on the background questionnaire data. Educational Testing Services (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 if 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 on data processing in STEP surveys is provided in "STEP Guidelines for Data Processing" document, available in external resources. The template do-file used by the STEP team to check raw background questionnaire data is provided as an external resource, too.
An overall response rate of 43% was achieved in the Bolivia STEP Survey. All non-response cases were documented (refusal/not found/no eligible household member, etc.) and accounted for during the weighting process. In such cases, a reserve household was activated to replace the initial household. Procedures are described in "Operation Manual" that is provided as an external resource.
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Key information about Bolivia Monthly Earnings
The documented dataset covers Enterprise Survey (ES) panel data collected in Bolivia in 2006, 2010 and 2017, as part of Latin America and the Caribbean Enterprise Surveys rollout, an initiative of the World Bank. The objective of the Enterprise Survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms.
Enterprise Surveys target a sample consisting of longitudinal (panel) observations and new cross-sectional data. Panel firms are prioritized in the sample selection, comprising up to 50% of the sample. For all panel firms, regardless of the sample, current eligibility or operating status is determined and included in panel datasets.
Bolivia ES 2010 was conducted in June 2010 and October 2010, Bolivia ES 2016 was carried out in January and June of 2017. Stratified random sampling was used to select the surveyed businesses. Data was collected using face-to-face interviews.
Data from 1,339 establishments was analyzed: 433 businesses were from 2006 only, 97 - from 2010 only, 197 - from 2017 only, 170 firms were from 2010 and 2017, 196 - from 2006 and 2010, 246 firms were from 2006, 2010 and 2017.
The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively measure characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.
National
The primary sampling unit of the study is an establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.
The whole population. The whole population, or universe of the study, is the non-agricultural economy. It comprises: all manufacturing sectors according to the group classification of ISIC Revision 3.1: (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.
Sample survey data [ssd]
Three levels of stratification were used in this country: industry, establishment size, and region.
Industry stratification was designed as follows: the universe was stratified into Manufacturing industries (ISIC Rev. 3.1 codes 15- 37), Retail industries (ISIC code 52) and Other Services (ISIC codes 45, 50, 51, 55, 60-64, and 72).
Size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).
The sample frame for 2017 consisted of listings of firms from two sources: for panel firms the list of 362 firms from the Bolivia 2010 ES was used, and for fresh firms (i.e., firms not covered in 2010) Economic Census, updated by Encuestas y Estudios (2016) was used.
In 2010, regional stratification was defined in three locations (city and the surrounding business area): La Paz, Santa Cruz, and Cochabamba.
Face-to-face [f2f]
Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.
Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.
Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.
Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.
1.343.967 (Persons) in 2012.
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License information was derived automatically
The Bolivia Demographic and Health Survey (Encuesta Nacional de Demografía y Salud 1989 ENDSA) was carried out by the Instituto Nacional de Estadística (INE) with technical assistance from the Institute for Resource Development (IRD). The survey was part of the worldwide Demographic and Health Surveys Program supported by the United States Agency for lntemational Development. The purpose of the survey was to collect data on a national sample of women (and their children under five), from which estimates could be made regarding fertility levels and trends, fertility preferences, knowledge and use of family planning, indicators of maternal and child health, and infant and child mortality levels. A nationally representative sample of 7923 women 15-49 years of age were interviewed in the Bolivia DHS survey (ENDSA) between February and July 1989. The information about child health is based on live births to these women during the preceding five years. For purposes of the survey, the sample was designed to provide representative estimates for the nine departments, with the exception of Beni and Pando which, due to their low population density, were treated as one entity. For this report, the departments were grouped according to region: La Paz, Oruro and Potosf in the Altiplano; Cochabamba, Tarija and Chuquisaca in the Valle; and Santa Cruz, Beni and Pando in the Llanos.
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Chart and table of population level and growth rate for the La Paz, Bolivia metro area from 1950 to 2025.