21 datasets found
  1. Number of computer households worldwide 2014-2029

    • statista.com
    Updated Apr 19, 2024
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    Statista Research Department (2024). Number of computer households worldwide 2014-2029 [Dataset]. https://www.statista.com/topics/1070/pcs/
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    Dataset updated
    Apr 19, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    The global number of households with a computer in was forecast to continuously increase between 2024 and 2029 by in total 88.6 million households (+8.6 percent). After the fifteenth consecutive increasing year, the computer households is estimated to reach 1.1 billion households and therefore a new peak in 2029. Notably, the number of households with a computer of was continuously increasing over the past years.Computer households are defined as households possessing at least one computer.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of households with a computer in countries like Caribbean and Africa.

  2. Laptop Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 3, 2024
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    Dataintelo (2024). Laptop Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-laptop-market
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    pdf, pptx, csvAvailable download formats
    Dataset updated
    Dec 3, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Laptop Market Outlook



    The global laptop market size is projected to grow significantly from USD 150 billion in 2023 to an estimated USD 230 billion by 2032, representing a compound annual growth rate (CAGR) of 4.9%. This growth is driven by a variety of factors including technological advancements, increasing demand for remote work solutions, and the continuous rise in e-learning. The proliferation of digital content, coupled with the need for portable computing devices, is further propelling the market. The shift towards more powerful, energy-efficient, and lightweight devices is also contributing to this upward trend. As consumers and businesses alike continue to value mobility without compromising on performance, the laptop market is poised for sustained growth over the forecast period.



    One of the primary growth factors for the laptop market is the increase in remote work and distance learning opportunities. With the global shift towards remote working environments, particularly accelerated by the COVID-19 pandemic, there has been an unprecedented demand for portable and efficient computing devices. Laptops offer the flexibility needed for remote work, enabling users to access work-related resources from any location. The education sector has also witnessed a surge in demand as educational institutions have increasingly adopted digital learning platforms, necessitating the widespread use of laptops for students and educators. This trend is expected to continue as both the corporate world and educational institutions recognize the long-term benefits of flexible work and learning models.



    Technological advancements in the laptop market are another critical growth driver. The development of high-performance processors, enhanced graphics capabilities, and longer battery life are setting new benchmarks in the industry. Manufacturers are focusing on innovation to meet the increasing expectations of consumers who are seeking devices that can handle more complex tasks. The advent of 5G technology and its integration into laptops is also expected to create new opportunities by enabling faster connectivity and improved performance. Additionally, the trend towards thinner and lighter laptops, such as ultrabooks, continues to gain traction, appealing to consumers who prioritize both portability and power.



    The growth of the gaming industry is also significantly impacting the laptop market. Gaming laptops, which boast powerful processors and high-end graphics cards, are increasingly in demand. The rise of eSports and competitive gaming has fueled the need for devices that can deliver immersive gaming experiences. Moreover, the growing popularity of virtual reality (VR) and augmented reality (AR) has further driven the demand for high-performance laptops. As gaming becomes more mainstream and diverse, manufacturers are investing in developing specialized gaming laptops that cater to different segments of gamers, from casual players to serious enthusiasts.



    Regionally, Asia Pacific is expected to exhibit the highest growth in the laptop market, driven by a burgeoning middle-class population and rapid digitalization. Countries like China and India are witnessing an increased adoption of laptops across various sectors, including education and business. North America and Europe remain key markets due to their technological infrastructure and high adoption rates of new technologies. Meanwhile, Latin America and the Middle East & Africa are gradually emerging as potential growth areas, with increasing investments in technology and education sectors. As the global landscape evolves, regional dynamics will continue to play a significant role in shaping the future of the laptop market.



    Product Type Analysis



    The laptop market is broadly segmented into various product types, each catering to distinct consumer needs and preferences. Traditional laptops continue to dominate the market due to their versatility and affordability. These devices are favored by a wide range of consumers, from students to professionals, due to their well-balanced features that offer adequate performance for everyday tasks. Manufacturers have been focusing on enhancing the specifications of traditional laptops to include better processors, increased storage, and improved battery life, ensuring they remain competitive in a market with evolving consumer demands.



    2-in-1 laptops, also known as convertible laptops, are gaining popularity due to their multifunctionality. These devices can switch between laptop and tablet modes, offering users the flexibility to use them for both work and entertainment purposes. The

  3. Penetration rate of computer households worldwide 2014-2029

    • statista.com
    Updated Apr 19, 2024
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    Statista Research Department (2024). Penetration rate of computer households worldwide 2014-2029 [Dataset]. https://www.statista.com/topics/1070/pcs/
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    Dataset updated
    Apr 19, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    The global household computer penetration in was forecast to continuously increase between 2024 and 2029 by in total 2.4 percentage points. After the eleventh consecutive increasing year, the computer penetration rate is estimated to reach 52.78 percent and therefore a new peak in 2029. Depicted is the estimated share of households owning at least one computer.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the household computer penetration in countries like Australia & Oceania and Caribbean.

  4. Global export data of Used Laptops

    • volza.com
    csv
    Updated Dec 5, 2025
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    Volza FZ LLC (2025). Global export data of Used Laptops [Dataset]. https://www.volza.com/p/used-laptops/export/export-from-china/
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    csvAvailable download formats
    Dataset updated
    Dec 5, 2025
    Dataset provided by
    Volza
    Authors
    Volza FZ LLC
    License

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

    Variables measured
    Count of exporters, Sum of export value, 2014-01-01/2021-09-30, Count of export shipments
    Description

    117838 Global export shipment records of Used Laptops with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

  5. A

    ‘Marin County Land Use Survey 2011’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jun 7, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘Marin County Land Use Survey 2011’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-marin-county-land-use-survey-2011-37d3/f6b2be4b/?iid=018-175&v=presentation
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    Dataset updated
    Jun 7, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Area covered
    Marin County
    Description

    Analysis of ‘Marin County Land Use Survey 2011’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/af572d1a-4313-43a5-9f1f-1d020093afb1 on 26 January 2022.

    --- Dataset description provided by original source is as follows ---

    This map is designated as Final.

    Land-Use Data Quality Control

    Every published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process.

    Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legendspecific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photointerpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.

    Provisional data sets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.

    The 2011 Marin County land use survey data was developed by the State of California, Department of Water Resources (DWR) through its Division of Integrated Regional Water Management (DIRWM) and Division of Statewide Integrated Water Management (DSIWM). Land use boundaries were digitized and land use data was gathered by staff of DWR’s North Central Region using extensive field visits and aerial photography. Land use polygons in agricultural areas were mapped in greater detail than areas of urban or native vegetation. Quality control procedures were performed jointly by staff at DWR’s DSIWM headquarters, under the leadership of Jean Woods, and North Central Region, under the supervision of Kim Rosmaier. This data was developed to aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standards version 2.1, dated March 9, 2016. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov. This data represents a land use survey of Marin County conducted by the California Department of Water Resources, North Central Regional Office staff. The field work for this survey was conducted during June 2011 by staff visiting each field and noting what was grown. Land use field boundaries were digitized using ArcGIS 9.3 then ArcGIS 10.0 using 2010 National Agriculture Imagery Program (NAIP) one-meter imagery as the base. To facilitate digitizing, Marin was divided in 2 portions, the Point Reyes area and all other areas of Marin County. These two areas were recombined after each portion was finished. The outer boundary of this land use survey coincides with the county line revisions completed by the California Department of Forestry and Fire Protection in 2009. Field boundaries were not drawn to represent legal parcel (ownership) boundaries, or meant to be used as parcel boundaries. Images and land use boundaries were loaded onto laptop computers that were used as the field data collection tools. Staff took these laptops into the field and virtually all the areas were visited to positively identify the land uses. Land use codes were digitized in the field using ESRI ArcMAP software, version 10.0. Global positioning system (GPS) units connected to the laptops were used to confirm the field team's location with respect to the fields. Staff took these laptops into the field and virtually all the areas were visited to positively identify the land uses. Land use codes were digitized in the field on laptop computers using ESRI ArcMAP software, version 10.0. The field team used a customized menu program to facilitate the gathering of field data. Before final processing, standard quality control procedures were performed jointly by staff at DWR’s North Central Region, and at DSIWM headquarters under the leadership of Jean Woods. Senior Land and Water Use Supervisor. After quality control procedures were completed, the data was finalized. The positional accuracy of the digital line work, which is based upon the orthorectified NAIP imagery, is approximately 6 meters. The land use attribute accuracy for agricultural fields is high, because almost every delineated field was visited by a surveyor. The accuracy is 95 percent because some errors may have occurred. Possible sources of attribute errors are: a) Human error in the identification of crop types, b) Data entry errors.

    --- Original source retains full ownership of the source dataset ---

  6. A

    ‘Calaveras County Land Use Survey 2015’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 28, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Calaveras County Land Use Survey 2015’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-calaveras-county-land-use-survey-2015-72ee/cf3d2921/?iid=019-804&v=presentation
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    Dataset updated
    Jan 28, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Area covered
    Calaveras County
    Description

    Analysis of ‘Calaveras County Land Use Survey 2015’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/09618f89-b1d4-4bde-bccf-7e46afb6dee8 on 28 January 2022.

    --- Dataset description provided by original source is as follows ---

    This map is designated as Final.

    Land-Use Data Quality Control

    Every published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process.

    Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legend specific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photointerpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.

    Provisional data sets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.

    The 2015 Calaveras County land use survey data was developed by the State of California, Department of Water Resources (DWR) through its Division of Integrated Regional Water Management (DIRWM) and Division of Statewide Integrated Water Management (DSIWM). Land use boundaries were digitized and land use data were gathered by staff of DWR’s North Central Region using extensive field visits and aerial photography. Land use polygons in agricultural areas were mapped in greater detail than areas of urban or native vegetation. Quality control procedures were performed jointly by staff at DWR’s DSIWM headquarters, under the leadership of Jean Woods, and North Central Region, under the supervision of: Kim Rosmaier. This data was developed to aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standards version 2.1, dated March 9, 2016. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov.

    SPECIAL NOTE FOR CALAVERAS 2015 SURVEY

    The Calaveras 2015 landuse survey took place prior to the Butte Fire that impacted a large portion of Calaveras County during September 2015. The survey only shows landuse for pre-fire conditions. There was no survey post fire. This data represents a land use survey of Calaveras County conducted by the California Department of Water Resources, North Central Regional Office staff. Land use field boundaries were digitized with ArcGIS 10.3 using 2014 U.S.D.A National Agriculture Imagery Program (NAIP) one-meter imagery as the base. Agricultural fields were delineated by following actual field boundaries instead of using the centerlines of roads to represent the field borders. Field boundaries were reviewed and updated using 2015 Landsat 8 imagery. Field boundaries were not drawn to represent legal parcel (ownership) boundaries, and are not meant to be used as parcel boundaries. The field work for this survey was conducted from August 31, 2015 through September 10, 2015. Images, land use boundaries and ESRI ArcMap software were loaded onto laptop computers that were used as the field data collection tools. Staff took these laptops into the field and virtually all agricultural fields were visited to identify the land use. Global positioning System (GPS) units connected to the laptops were used to confirm the surveyor's location with respect to the fields. Land use codes were digitized in the field using dropdown selections from defined domains. Agricultural fields the staff were unable to access were designated 'E' in the Class field for Entry Denied in accordance with the 2009 Landuse Legend. Upon completion of the survey, a Python script was used to convert the data table into the standard land use format. ArcGIS geoprocessing tools and topology rules were used to locate errors for quality control. The primary focus of this land use survey is mapping agricultural fields. Urban residences and other urban areas were delineated using aerial photo interpretation. Some urban areas may have been missed. Rural residential land use was delineated by drawing polygons to surround houses and other buildings along with some of the surrounding land. These footprint areas do not represent the entire footprint of urban land. Sources of irrigation water were identified for general areas and occasionally supplemented by information obtained from landowners. Water source information was not collected for each field in the survey, so the water source listed for a specific agricultural field may not be accurate. Before final processing, standard quality control procedures were performed jointly by staff at DWR’s North Central Region, and at DSIWM headquarters under the leadership of Jean Woods. Senior Land and Water Use Supervisor. After quality control procedures were completed, the data was finalized. The positional accuracy of the digital line work, which is based upon the orthorectified NAIP imagery, is approximately 6 meters. The land use attribute accuracy for agricultural fields is high, because almost every delineated field was visited by a surveyor. The accuracy is 95 percent because some errors may have occurred. Possible sources of attribute errors are: a) Human error in the identification of crop types, b) Data entry errors.

    --- Original source retains full ownership of the source dataset ---

  7. f

    ML models performance (RFE).

    • plos.figshare.com
    xls
    Updated Nov 27, 2023
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    Muntequa Imtiaz Siraji; Ahnaf Akif Rahman; Mirza Muntasir Nishat; Md Abdullah Al Mamun; Fahim Faisal; Lamim Ibtisam Khalid; Ashik Ahmed (2023). ML models performance (RFE). [Dataset]. http://doi.org/10.1371/journal.pone.0294803.t015
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    xlsAvailable download formats
    Dataset updated
    Nov 27, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Muntequa Imtiaz Siraji; Ahnaf Akif Rahman; Mirza Muntasir Nishat; Md Abdullah Al Mamun; Fahim Faisal; Lamim Ibtisam Khalid; Ashik Ahmed
    License

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

    Description

    Depression is a psychological state of mind that often influences a person in an unfavorable manner. While it can occur in people of all ages, students are especially vulnerable to it throughout their academic careers. Beginning in 2020, the COVID-19 epidemic caused major problems in people’s lives by driving them into quarantine and forcing them to be connected continually with mobile devices, such that mobile connectivity became the new norm during the pandemic and beyond. This situation is further accelerated for students as universities move towards a blended learning mode. In these circumstances, monitoring student mental health in terms of mobile and Internet connectivity is crucial for their wellbeing. This study focuses on students attending an International University of Bangladesh to investigate their mental health due to their continual use of mobile devices (e.g., smartphones, tablets, laptops etc.). A cross-sectional survey method was employed to collect data from 444 participants. Following the exploratory data analysis, eight machine learning (ML) algorithms were used to develop an automated normal-to-extreme severe depression identification and classification system. When the automated detection was incorporated with feature selection such as Chi-square test and Recursive Feature Elimination (RFE), about 3 to 5% increase in accuracy was observed by the method. Similarly, a 5 to 15% increase in accuracy has been observed when a feature extraction method such as Principal Component Analysis (PCA) was performed. Also, the SparsePCA feature extraction technique in combination with the CatBoost classifier showed the best results in terms of accuracy, F1-score, and ROC-AUC. The data analysis revealed no sign of depression in about 44% of the total participants. About 25% of students showed mild-to-moderate and 31% of students showed severe-to-extreme signs of depression. The results suggest that ML models, incorporating a proper feature engineering method can serve adequately in multi-stage depression detection among the students. This model might be utilized in other disciplines for detecting early signs of depression among people.

  8. Global import data of Use Laptop

    • volza.com
    csv
    Updated May 31, 2025
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    Volza FZ LLC (2025). Global import data of Use Laptop [Dataset]. https://www.volza.com/p/use-laptop/import/
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    csvAvailable download formats
    Dataset updated
    May 31, 2025
    Dataset provided by
    Volza
    Authors
    Volza FZ LLC
    License

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

    Variables measured
    Count of importers, Sum of import value, 2014-01-01/2021-09-30, Count of import shipments
    Description

    223920 Global import shipment records of Use Laptop with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

  9. L

    Lithuania LT: Foreign Direct Investment Position: Outward: Total:...

    • ceicdata.com
    Updated May 13, 2022
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    CEICdata.com (2022). Lithuania LT: Foreign Direct Investment Position: Outward: Total: Manufacture of Computers and Peripheral Equipment [Dataset]. https://www.ceicdata.com/en/lithuania/foreign-direct-investment-position-by-industry-oecd-member-annual/lt-foreign-direct-investment-position-outward-total-manufacture-of-computers-and-peripheral-equipment
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    Dataset updated
    May 13, 2022
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2010 - Dec 1, 2023
    Area covered
    Lithuania
    Description

    Lithuania LT: Foreign Direct Investment Position: Outward: Total: Manufacture of Computers and Peripheral Equipment data was reported at 0.000 EUR mn in 2023. This stayed constant from the previous number of 0.000 EUR mn for 2022. Lithuania LT: Foreign Direct Investment Position: Outward: Total: Manufacture of Computers and Peripheral Equipment data is updated yearly, averaging 0.000 EUR mn from Dec 2005 (Median) to 2023, with 15 observations. The data reached an all-time high of 0.000 EUR mn in 2023 and a record low of 0.000 EUR mn in 2023. Lithuania LT: Foreign Direct Investment Position: Outward: Total: Manufacture of Computers and Peripheral Equipment data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Position: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  10. Lithuania LT: Foreign Direct Investment Income: Inward: USD: Total: Repair...

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Lithuania LT: Foreign Direct Investment Income: Inward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities [Dataset]. https://www.ceicdata.com/en/lithuania/foreign-direct-investment-income-usd-by-industry-oecd-member-annual/lt-foreign-direct-investment-income-inward-usd-total-repair-of-computers-personal-and-household-goods-other-personal-service-activities
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    Dataset updated
    Jan 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
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Lithuania
    Description

    Lithuania LT: Foreign Direct Investment Income: Inward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data was reported at 0.022 USD mn in 2023. This records an increase from the previous number of -0.307 USD mn for 2022. Lithuania LT: Foreign Direct Investment Income: Inward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data is updated yearly, averaging 0.022 USD mn from Dec 2005 (Median) to 2023, with 17 observations. The data reached an all-time high of 1.732 USD mn in 2006 and a record low of -1.181 USD mn in 2013. Lithuania LT: Foreign Direct Investment Income: Inward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Income: USD: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  11. Lithuania LT: Foreign Direct Investment Income: Outward: Total: Manufacture...

    • ceicdata.com
    Updated May 7, 2022
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    CEICdata.com (2022). Lithuania LT: Foreign Direct Investment Income: Outward: Total: Manufacture of Computers and Peripheral Equipment [Dataset]. https://www.ceicdata.com/en/lithuania/foreign-direct-investment-income-by-industry-oecd-member-annual/lt-foreign-direct-investment-income-outward-total-manufacture-of-computers-and-peripheral-equipment
    Explore at:
    Dataset updated
    May 7, 2022
    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
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Lithuania
    Description

    Lithuania LT: Foreign Direct Investment Income: Outward: Total: Manufacture of Computers and Peripheral Equipment data was reported at 0.000 EUR mn in 2023. This stayed constant from the previous number of 0.000 EUR mn for 2022. Lithuania LT: Foreign Direct Investment Income: Outward: Total: Manufacture of Computers and Peripheral Equipment data is updated yearly, averaging 0.000 EUR mn from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 0.000 EUR mn in 2023 and a record low of 0.000 EUR mn in 2023. Lithuania LT: Foreign Direct Investment Income: Outward: Total: Manufacture of Computers and Peripheral Equipment data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Income: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  12. Lithuania LT: Foreign Direct Investment Financial Flows: Outward: Total:...

    • ceicdata.com
    Updated May 11, 2022
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    CEICdata.com (2022). Lithuania LT: Foreign Direct Investment Financial Flows: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities [Dataset]. https://www.ceicdata.com/en/lithuania/foreign-direct-investment-financial-flows-by-industry-oecd-member-annual/lt-foreign-direct-investment-financial-flows-outward-total-repair-of-computers-personal-and-household-goods-other-personal-service-activities
    Explore at:
    Dataset updated
    May 11, 2022
    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
    Dec 1, 2010 - Dec 1, 2023
    Area covered
    Lithuania
    Description

    Lithuania LT: Foreign Direct Investment Financial Flows: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data was reported at -3.400 EUR mn in 2023. This records a decrease from the previous number of 0.000 EUR mn for 2022. Lithuania LT: Foreign Direct Investment Financial Flows: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data is updated yearly, averaging 0.150 EUR mn from Dec 2010 (Median) to 2023, with 7 observations. The data reached an all-time high of 1.850 EUR mn in 2010 and a record low of -3.400 EUR mn in 2023. Lithuania LT: Foreign Direct Investment Financial Flows: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Financial Flows: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  13. L

    Lithuania LT: Foreign Direct Investment Income: Outward: USD: Total: Repair...

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    CEICdata.com, Lithuania LT: Foreign Direct Investment Income: Outward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities [Dataset]. https://www.ceicdata.com/en/lithuania/foreign-direct-investment-income-usd-by-industry-oecd-member-annual/lt-foreign-direct-investment-income-outward-usd-total-repair-of-computers-personal-and-household-goods-other-personal-service-activities
    Explore at:
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2005 - Dec 1, 2022
    Area covered
    Lithuania
    Description

    Lithuania LT: Foreign Direct Investment Income: Outward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data was reported at 0.000 USD mn in 2022. This stayed constant from the previous number of 0.000 USD mn for 2020. Lithuania LT: Foreign Direct Investment Income: Outward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data is updated yearly, averaging 0.000 USD mn from Dec 2005 (Median) to 2022, with 12 observations. The data reached an all-time high of 0.211 USD mn in 2015 and a record low of -0.578 USD mn in 2018. Lithuania LT: Foreign Direct Investment Income: Outward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Income: USD: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  14. France Foreign Direct Investment Position: Outward: Total: Repair of...

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). France Foreign Direct Investment Position: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities [Dataset]. https://www.ceicdata.com/en/france/foreign-direct-investment-position-by-industry-oecd-member-annual/foreign-direct-investment-position-outward-total-repair-of-computers-personal-and-household-goods-other-personal-service-activities
    Explore at:
    Dataset updated
    Jan 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
    Dec 1, 2015 - Dec 1, 2023
    Area covered
    France
    Description

    France Foreign Direct Investment Position: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data was reported at 193.000 EUR mn in 2023. This records a decrease from the previous number of 233.000 EUR mn for 2022. France Foreign Direct Investment Position: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data is updated yearly, averaging 73.500 EUR mn from Dec 2013 (Median) to 2023, with 10 observations. The data reached an all-time high of 233.000 EUR mn in 2022 and a record low of -37.000 EUR mn in 2018. France Foreign Direct Investment Position: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s France – Table FR.OECD.FDI: Foreign Direct Investment Position: by Industry: OECD Member: Annual. Reverse investment:Reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) has never been observed or is very negligible. It would be treated as portfolio investment in theory. Netting of reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). Resident Special Purpose Entities (SPEs) do not exist or are not significant and are recorded as zero in the FDI database. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Nominal value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Direct Influence/Indirect Control (DIIC) method. Debt between fellow enterprises are completely covered. Collective investment institutions not covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the resident direct investor. Outward FDI positions are allocated according to the activity of the resident direct investor. Statistical unit: Enterprise.

  15. C

    Czech Republic CZ: Foreign Direct Investment Position: Outward: USD: Total:...

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Czech Republic CZ: Foreign Direct Investment Position: Outward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities [Dataset]. https://www.ceicdata.com/en/czech-republic/foreign-direct-investment-position-usd-by-industry-oecd-member-annual/cz-foreign-direct-investment-position-outward-usd-total-repair-of-computers-personal-and-household-goods-other-personal-service-activities
    Explore at:
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2013 - Dec 1, 2023
    Area covered
    Czechia
    Description

    Czech Republic CZ: Foreign Direct Investment Position: Outward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data was reported at 1.775 USD mn in 2023. This records an increase from the previous number of 1.756 USD mn for 2022. Czech Republic CZ: Foreign Direct Investment Position: Outward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data is updated yearly, averaging 0.102 USD mn from Dec 2013 (Median) to 2023, with 10 observations. The data reached an all-time high of 2.949 USD mn in 2020 and a record low of -10.106 USD mn in 2013. Czech Republic CZ: Foreign Direct Investment Position: Outward: USD: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Czech Republic – Table CZ.OECD.FDI: Foreign Direct Investment Position: USD: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is not applied in the recording of total inward and outward FDi transactions and positions. Such cases have never been observed. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. Resident Special Purpose Entities (SPEs) do not exist or are not significant and are recorded as zero in the FDI database. Valuation method used for listed inward and outward equity positions: Own funds at book value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Nominal value.; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered. Collective investment institutions are covered as direct investment enterprises. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  16. C

    Czech Republic CZ: Foreign Direct Investment Income: Outward: USD: Total:...

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Czech Republic CZ: Foreign Direct Investment Income: Outward: USD: Total: Manufacture of Computers and Peripheral Equipment [Dataset]. https://www.ceicdata.com/en/czech-republic/foreign-direct-investment-income-usd-by-industry-oecd-member-annual/cz-foreign-direct-investment-income-outward-usd-total-manufacture-of-computers-and-peripheral-equipment
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2013 - Dec 1, 2023
    Area covered
    Czechia
    Description

    Czech Republic CZ: Foreign Direct Investment Income: Outward: USD: Total: Manufacture of Computers and Peripheral Equipment data was reported at 0.000 USD mn in 2023. This stayed constant from the previous number of 0.000 USD mn for 2022. Czech Republic CZ: Foreign Direct Investment Income: Outward: USD: Total: Manufacture of Computers and Peripheral Equipment data is updated yearly, averaging 0.000 USD mn from Dec 2013 (Median) to 2023, with 11 observations. The data reached an all-time high of 0.000 USD mn in 2023 and a record low of 0.000 USD mn in 2023. Czech Republic CZ: Foreign Direct Investment Income: Outward: USD: Total: Manufacture of Computers and Peripheral Equipment data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Czech Republic – Table CZ.OECD.FDI: Foreign Direct Investment Income: USD: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is not applied in the recording of total inward and outward FDi transactions and positions. Such cases have never been observed. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. Resident Special Purpose Entities (SPEs) do not exist or are not significant and are recorded as zero in the FDI database. Valuation method used for listed inward and outward equity positions: Own funds at book value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Nominal value.; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered. Collective investment institutions are covered as direct investment enterprises. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  17. C

    Czech Republic CZ: Foreign Direct Investment Income: Outward: Total: Repair...

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Czech Republic CZ: Foreign Direct Investment Income: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities [Dataset]. https://www.ceicdata.com/en/czech-republic/foreign-direct-investment-income-by-industry-oecd-member-annual/cz-foreign-direct-investment-income-outward-total-repair-of-computers-personal-and-household-goods-other-personal-service-activities
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2013 - Dec 1, 2022
    Area covered
    Czechia
    Description

    Czech Republic CZ: Foreign Direct Investment Income: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data was reported at 1.495 CZK mn in 2022. This records a decrease from the previous number of 23.781 CZK mn for 2021. Czech Republic CZ: Foreign Direct Investment Income: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data is updated yearly, averaging 0.000 CZK mn from Dec 2013 (Median) to 2022, with 10 observations. The data reached an all-time high of 23.781 CZK mn in 2021 and a record low of -491.291 CZK mn in 2013. Czech Republic CZ: Foreign Direct Investment Income: Outward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Czech Republic – Table CZ.OECD.FDI: Foreign Direct Investment Income: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is not applied in the recording of total inward and outward FDi transactions and positions. Such cases have never been observed. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. Resident Special Purpose Entities (SPEs) do not exist or are not significant and are recorded as zero in the FDI database. Valuation method used for listed inward and outward equity positions: Own funds at book value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Nominal value.; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered. Collective investment institutions are covered as direct investment enterprises. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  18. C

    Czech Republic CZ: Foreign Direct Investment Income: Inward: Total: Repair...

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Czech Republic CZ: Foreign Direct Investment Income: Inward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities [Dataset]. https://www.ceicdata.com/en/czech-republic/foreign-direct-investment-income-by-industry-oecd-member-annual/cz-foreign-direct-investment-income-inward-total-repair-of-computers-personal-and-household-goods-other-personal-service-activities
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2013 - Dec 1, 2023
    Area covered
    Czechia
    Description

    Czech Republic CZ: Foreign Direct Investment Income: Inward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data was reported at 325.766 CZK mn in 2023. This records an increase from the previous number of -3,482.382 CZK mn for 2022. Czech Republic CZ: Foreign Direct Investment Income: Inward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data is updated yearly, averaging 92.876 CZK mn from Dec 2013 (Median) to 2023, with 9 observations. The data reached an all-time high of 472.688 CZK mn in 2018 and a record low of -3,482.382 CZK mn in 2022. Czech Republic CZ: Foreign Direct Investment Income: Inward: Total: Repair of Computers, Personal and Household Goods: Other Personal Service Activities data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Czech Republic – Table CZ.OECD.FDI: Foreign Direct Investment Income: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is not applied in the recording of total inward and outward FDi transactions and positions. Such cases have never been observed. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. Resident Special Purpose Entities (SPEs) do not exist or are not significant and are recorded as zero in the FDI database. Valuation method used for listed inward and outward equity positions: Own funds at book value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Nominal value.; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered. Collective investment institutions are covered as direct investment enterprises. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  19. South Korea KR: Foreign Direct Investment Income: Outward: Total:...

    • ceicdata.com
    Updated May 14, 2022
    + more versions
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    CEICdata.com (2022). South Korea KR: Foreign Direct Investment Income: Outward: Total: Manufacture of Computers and Peripheral Equipment [Dataset]. https://www.ceicdata.com/en/korea/foreign-direct-investment-income-by-industry-oecd-member-annual/kr-foreign-direct-investment-income-outward-total-manufacture-of-computers-and-peripheral-equipment
    Explore at:
    Dataset updated
    May 14, 2022
    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
    Dec 1, 2013 - Dec 1, 2022
    Area covered
    South Korea
    Description

    South Korea Foreign Direct Investment Income: Outward: Total: Manufacture of Computers and Peripheral Equipment data was reported at 604.535 USD mn in 2022. This records an increase from the previous number of 534.553 USD mn for 2021. South Korea Foreign Direct Investment Income: Outward: Total: Manufacture of Computers and Peripheral Equipment data is updated yearly, averaging 761.105 USD mn from Dec 2013 (Median) to 2022, with 10 observations. The data reached an all-time high of 1.514 USD bn in 2017 and a record low of 274.429 USD mn in 2015. South Korea Foreign Direct Investment Income: Outward: Total: Manufacture of Computers and Peripheral Equipment data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Korea – Table KR.OECD.FDI: Foreign Direct Investment Income: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series excluding resident SPEs only. Valuation method used for listed inward and outward equity positions: Own funds at book value. Valuation method used for unlisted inward equity positions: Own funds at book value. Valuation method used for unlisted outward equity positions: Own funds at book value, Accumulation of FDI equity flows, Book values. Valuation method used for inward debt positions: Nominal value. Valuation method used for outward debt positions: Market value.; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationship (FDIR). Fellow enterprises are partially covered in FDI transactions and positions. However given the reporting treshold, almost all of the value of transactions of fellows are covered in the statistics. Collective investment institutions are included as direct investment enterprises. Non-profit institutions serving households are included as direct investors (outward FDI transactions and positions). FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

  20. S

    South Korea KR: Foreign Direct Investment Position: Outward: Total:...

    • ceicdata.com
    Updated May 9, 2022
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    CEICdata.com (2022). South Korea KR: Foreign Direct Investment Position: Outward: Total: Manufacture of Computers and Peripheral Equipment [Dataset]. https://www.ceicdata.com/en/korea/foreign-direct-investment-position-by-industry-oecd-member-annual
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    Dataset updated
    May 9, 2022
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2013 - Dec 1, 2023
    Area covered
    South Korea
    Description

    KR: Foreign Direct Investment Position: Outward: Total: Manufacture of Computers and Peripheral Equipment data was reported at 3.745 USD bn in 2023. This records a decrease from the previous number of 4.982 USD bn for 2022. KR: Foreign Direct Investment Position: Outward: Total: Manufacture of Computers and Peripheral Equipment data is updated yearly, averaging 4.156 USD bn from Dec 2013 (Median) to 2023, with 11 observations. The data reached an all-time high of 6.178 USD bn in 2019 and a record low of 1.839 USD bn in 2014. KR: Foreign Direct Investment Position: Outward: Total: Manufacture of Computers and Peripheral Equipment data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Korea – Table KR.OECD.FDI: Foreign Direct Investment Position: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series excluding resident SPEs only. Valuation method used for listed inward and outward equity positions: Own funds at book value. Valuation method used for unlisted inward equity positions: Own funds at book value. Valuation method used for unlisted outward equity positions: Own funds at book value, Accumulation of FDI equity flows, Book values. Valuation method used for inward debt positions: Nominal value. Valuation method used for outward debt positions: Market value.; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationship (FDIR). Fellow enterprises are partially covered in FDI transactions and positions. However given the reporting treshold, almost all of the value of transactions of fellows are covered in the statistics. Collective investment institutions are included as direct investment enterprises. Non-profit institutions serving households are included as direct investors (outward FDI transactions and positions). FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

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Statista Research Department (2024). Number of computer households worldwide 2014-2029 [Dataset]. https://www.statista.com/topics/1070/pcs/
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Number of computer households worldwide 2014-2029

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6 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 19, 2024
Dataset provided by
Statistahttp://statista.com/
Authors
Statista Research Department
Description

The global number of households with a computer in was forecast to continuously increase between 2024 and 2029 by in total 88.6 million households (+8.6 percent). After the fifteenth consecutive increasing year, the computer households is estimated to reach 1.1 billion households and therefore a new peak in 2029. Notably, the number of households with a computer of was continuously increasing over the past years.Computer households are defined as households possessing at least one computer.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of households with a computer in countries like Caribbean and Africa.

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