3 datasets found
  1. Botswana Average Monthly Earnings: Real Estate

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Botswana Average Monthly Earnings: Real Estate [Dataset]. https://www.ceicdata.com/en/botswana/average-monthly-earnings/average-monthly-earnings-real-estate
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2018 - Mar 1, 2024
    Area covered
    Botswana
    Variables measured
    Wage/Earnings
    Description

    Botswana Average Monthly Earnings: Real Estate data was reported at 30,845.000 BWP in Mar 2024. This records an increase from the previous number of 11,761.000 BWP for Sep 2023. Botswana Average Monthly Earnings: Real Estate data is updated quarterly, averaging 6,483.500 BWP from Sep 2007 (Median) to Mar 2024, with 38 observations. The data reached an all-time high of 30,845.000 BWP in Mar 2024 and a record low of 4,087.000 BWP in Dec 2022. Botswana Average Monthly Earnings: Real Estate data remains active status in CEIC and is reported by Statistics Botswana. The data is categorized under Global Database’s Botswana – Table BW.G002: Average Monthly Earnings.

  2. End-of-Day Pricing Data Panama Techsalerator

    • kaggle.com
    Updated Aug 23, 2023
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    Techsalerator (2023). End-of-Day Pricing Data Panama Techsalerator [Dataset]. https://www.kaggle.com/datasets/techsalerator/end-of-day-pricing-data-panama-techsalerator
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 23, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Techsalerator
    Area covered
    Panama
    Description

    Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 214 companies listed on the Panama Stock Exchange (XPTY) in Panama. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

    Top 5 used data fields in the End-of-Day Pricing Dataset for Panama:

    1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

    2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

    3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

    4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

    5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

    Top 5 financial instruments with End-of-Day Pricing Data in Panama:

    Panamanian Stock Exchange Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Panamanian Stock Exchange (Bolsa de Valores de Panamá). This index provides an overview of the overall market performance in Panama.

    Panamanian Stock Exchange Foreign Company Index: The index that tracks the performance of foreign companies listed on the Panamanian Stock Exchange. This index reflects the performance of international companies operating in Panama.

    Company A: A prominent Panamanian company with diversified operations across various sectors, such as shipping, logistics, or finance. This company's stock is widely traded on the Panamanian Stock Exchange.

    Company B: A leading financial institution in Panama, offering banking, insurance, or investment services. This company's stock is actively traded on the Panamanian Stock Exchange.

    Company C: A major player in the Panamanian energy or real estate sector, involved in the production and distribution of related products. This company's stock is listed and actively traded on the Panamanian Stock Exchange.

    If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Panama, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

    Data fields included:

    Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

    Q&A:

    1. How much does the End-of-Day Pricing Data cost in Panama ?

    The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

    1. How complete is the End-of-Day Pricing Data coverage in Panama?

    Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Panama exchanges.

    1. How does Techsalerator collect this data?

    Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

    1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

    Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

    1. How do I pay for this dataset?

    Techsalerator accepts various payment methods, including credit cards, direc...

  3. Enterprise Survey 2006 - Botswana

    • catalog.ihsn.org
    • dev.ihsn.org
    • +2more
    Updated Mar 29, 2019
    + more versions
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    World Bank (2019). Enterprise Survey 2006 - Botswana [Dataset]. https://catalog.ihsn.org/catalog/484
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    World Bankhttps://www.worldbank.org/
    Time period covered
    2006
    Area covered
    Botswana
    Description

    Abstract

    The survey was conducted in Botswana between May and June 2006. Data from 342 establishments were analyzed.

    The Enterprise Surveys are applied to a representative sample of firms in the non-agricultural economy. The sample is consistently defined in all countries and includes the entire manufacturing sector, the services sector, and the transportation and construction sectors. Public utilities, government services, health care, and financial services sectors are not included in the sample. Enterprise Surveys collect a wide array of qualitative and quantitative information through face-to-face interviews with firm managers and owners regarding the business environment in their countries and the productivity of their firms. The topics covered in Enterprise Surveys include the obstacles to doing business, infrastructure, finance, labor, corruption and regulation, law and order, innovation and technology, trade, and firm productivity.

    Geographic coverage

    National

    Analysis unit

    The primary sampling unit of the study is the 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.

    Universe

    The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population 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.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample for countries participating in the Enterprise Surveys is stratified by industry, firm size, and geographic region.

    For stratification by industry, the main manufacturing sectors in each country in terms of value added, number of firms, and contribution to employment are selected. The retail trade sector is also included in all countries as a representative of the services sector, and depending on the size of the economy, the information technology (IT) sector is included. The rest of the universe is included in a residual stratum. In Botswana, Manufacturing sector included 114 firms, Retail sector - 118 companies and Other sectors (Residual) - 110 businesses.

    Size stratification is defined the following way: small establishments (5 to 19 employees), medium establishments (20 to 99 employees), and large establishments (more than 99 employees).

    Regional stratification includes the main economic regions in each country. In Botswana, regional stratification was defined by two regions: Gaborone and Francistown.

    Through this methodology estimates for the different stratification levels can be calculated on a separate basis while at the same time inferences can be made for the economy as a whole, weighting individual observations by corresponding sample weights. Sample sizes for each stratification level are defined ensuring a minimum precision level of 7.5% with 95% confidence intervals for estimates with population proportions.

    For more technical details on the sampling strategy, please review "Sampling Methodology" in "Technical Documents" folder.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The current survey instruments are available: - Core Questionnaire + Manufacturing Module; - Core Questionnaire + Retail Module; - Core Questionnaire.

    Most of the questions in all three questionnaires are the same.

    The “Core Questionnaire” is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the “Core Questionnaire + Manufacturing Module” and the “Core Questionnaire + Retail Module.” The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

    The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, informality, business-government relations, conflict resolution and legal environment, innovation and technology, and performance measures. The questionnaires also assess respondents’ opinions on what are the obstacles to firm growth and performance.

    Cleaning operations

    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.

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Click to copy link
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Close
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CEICdata.com (2025). Botswana Average Monthly Earnings: Real Estate [Dataset]. https://www.ceicdata.com/en/botswana/average-monthly-earnings/average-monthly-earnings-real-estate
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Botswana Average Monthly Earnings: Real Estate

Explore at:
Dataset updated
Feb 15, 2025
Dataset provided by
CEIC Data
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Mar 1, 2018 - Mar 1, 2024
Area covered
Botswana
Variables measured
Wage/Earnings
Description

Botswana Average Monthly Earnings: Real Estate data was reported at 30,845.000 BWP in Mar 2024. This records an increase from the previous number of 11,761.000 BWP for Sep 2023. Botswana Average Monthly Earnings: Real Estate data is updated quarterly, averaging 6,483.500 BWP from Sep 2007 (Median) to Mar 2024, with 38 observations. The data reached an all-time high of 30,845.000 BWP in Mar 2024 and a record low of 4,087.000 BWP in Dec 2022. Botswana Average Monthly Earnings: Real Estate data remains active status in CEIC and is reported by Statistics Botswana. The data is categorized under Global Database’s Botswana – Table BW.G002: Average Monthly Earnings.

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