100+ datasets found
  1. Capital market firms: COVID-19 effect on cloud technology worldwide 2021

    • statista.com
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    Statista, Capital market firms: COVID-19 effect on cloud technology worldwide 2021 [Dataset]. https://www.statista.com/statistics/1321937/pandemic-influence-cloud-technology-capital-market-worldwide/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 2021
    Area covered
    Worldwide
    Description

    The coronavirus pandemic has affected the traditional working environment of capital market firms worldwide leading to the wider application of cloud technology. According to ** percent of respondents in a survey conducted in 2021, the coronavirus has shown the importance of cloud usage when improving firm processes. Cloud technology was also considered to be an important factor when improving user experience by ** percent of experts. Overall investment has increased as ** percent of experts noted increased spending on cloud-related activities/technology.

  2. Effect of coronavirus on major global stock indices 2020-2021

    • statista.com
    Updated Jun 27, 2025
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    Statista (2025). Effect of coronavirus on major global stock indices 2020-2021 [Dataset]. https://www.statista.com/statistics/1251618/effect-coronavirus-major-global-stock-indices/
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 5, 2020 - Nov 14, 2021
    Area covered
    Worldwide
    Description

    While the global coronavirus (COVID-19) pandemic caused all major stock market indices to fall sharply in March 2020, both the extent of the decline at this time, and the shape of the subsequent recovery, have varied greatly. For example, on March 15, 2020, major European markets and traditional stocks in the United States had shed around ** percent of their value compared to January *, 2020. However, Asian markets and the NASDAQ Composite Index only shed around ** to ** percent of their value. A similar story can be seen with the post-coronavirus recovery. As of November 14, 2021 the NASDAQ composite index value was around ** percent higher than in January 2020, while most other markets were only between ** and ** percent higher. Why did the NASDAQ recover the quickest? Based in New York City, the NASDAQ is famously considered a proxy for the technology industry as many of the world’s largest technology industries choose to list there. And it just so happens that technology was the sector to perform the best during the coronavirus pandemic. Accordingly, many of the largest companies who benefitted the most from the pandemic such as Amazon, PayPal and Netflix, are listed on the NADSAQ, helping it to recover the fastest of the major stock exchanges worldwide. Which markets suffered the most? The energy sector was the worst hit by the global COVID-19 pandemic. In particular, oil companies share prices suffered large declines over 2020 as demand for oil plummeted while workers found themselves no longer needing to commute, and the tourism industry ground to a halt. In addition, overall share prices in two major stock exchanges – the London Stock Exchange (as represented by the FTSE 100 index) and Hong Kong (as represented by the Hang Seng index) – have notably recovered slower than other major exchanges. However, in both these, the underlying issue behind the slower recovery likely has more to do with political events unrelated to the coronavirus than it does with the pandemic – namely Brexit and general political unrest, respectively.

  3. Macro Effects of COVID-19 on the Manufacturing Sector

    • ibisworld.com
    Updated Jul 20, 2020
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    IBISWorld (2020). Macro Effects of COVID-19 on the Manufacturing Sector [Dataset]. https://www.ibisworld.com/blog/macro-effects-of-covid-19-on-the-manufacturing-sector/1/1126/
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    Dataset updated
    Jul 20, 2020
    Dataset authored and provided by
    IBISWorld
    Time period covered
    Jul 20, 2020
    Description

    The macro challenges faced by the sector today are expected to result in a more robust manufacturing sector tomorrow.

  4. Google Stock Prices Since COVID-19 started

    • kaggle.com
    zip
    Updated Sep 13, 2022
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    Anubhav Goyal (2022). Google Stock Prices Since COVID-19 started [Dataset]. https://www.kaggle.com/datasets/anubhavgoyal10/google-stock-prices-since-the-pandemic-started
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    zip(15353 bytes)Available download formats
    Dataset updated
    Sep 13, 2022
    Authors
    Anubhav Goyal
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This dataset contains the stock prices of Google since the COVID-19 pandemic began. There are 7 columns in this dataset:

    FeatureDescription
    DataDate on which the market was open
    OpenStock price at which market was open
    HighHighest price of stock on that date
    LowLowest price of stock on that dated
    ClosePrice of stock when market closed
    Adj CloseAdjusted closed price after considering some factors
    VolumeVolume of trade which took place during the day
  5. f

    The impacts of COVID-19: Interacted.

    • datasetcatalog.nlm.nih.gov
    • figshare.com
    Updated Mar 15, 2023
    + more versions
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    Wright, Taylor; Brodeur, Abel; Beland, Louis-Philippe (2023). The impacts of COVID-19: Interacted. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001030173
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    Dataset updated
    Mar 15, 2023
    Authors
    Wright, Taylor; Brodeur, Abel; Beland, Louis-Philippe
    Description

    We examine the determinants of the consequences of COVID-19 on employment and wages in the United States. Guided by a pre-analysis plan, we investigate whether the economic consequences of COVID-19 were larger for certain occupations, using four indexes: workers relatively more exposed to disease, workers that work with proximity to coworkers, essential/critical workers and workers who can easily work remotely. We find that individuals that work in proximity to others are more affected while individuals able to work remotely and essential workers are less affected by the pandemic. We also present suggestive evidence that our indexes are likely explanations why certain demographic groups such as younger and minority workers have worse labor market outcomes during the pandemic.

  6. US technology market growth impact of coronavirus (COVID-19) 2022

    • statista.com
    Updated Aug 15, 2020
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    Statista (2020). US technology market growth impact of coronavirus (COVID-19) 2022 [Dataset]. https://www.statista.com/statistics/1122209/us-tech-market-covid-19-impact-2020/
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    Dataset updated
    Aug 15, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Analysts' forecast of the COVID-19 pandemic's impact on the U.S. technology market has improved with time. As of the first quarter of 2021, the U.S. tech spending in 2021 is projected to grow by six percent.

  7. o

    Data from: The Impact of U.S. School Closures on Labor Market Outcomes...

    • openicpsr.org
    delimited
    Updated Oct 18, 2022
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    Kairon Shayne Garcia; Benjamin Cowan (2022). The Impact of U.S. School Closures on Labor Market Outcomes during the COVID-19 Pandemic [Dataset]. http://doi.org/10.3886/E182101V1
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    delimitedAvailable download formats
    Dataset updated
    Oct 18, 2022
    Dataset provided by
    Washington State University and NBER
    Washington State University
    Authors
    Kairon Shayne Garcia; Benjamin Cowan
    License

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

    Area covered
    United States
    Description

    A substantial fraction of k-12 schools in the United States closed their in-person operations during the COVID-19 pandemic. These closures may have altered the labor supply decisions of parents of affected children due to a need to be at home with children during the school day. In this paper, we examine the impact of school closures on parental labor market outcomes. We test whether COVID-19 school closures have a disproportionate impact on parents of school-age children (ages 5-17 years old). Our results show that both women’s and men’s work lives were affected by school closures, with both groups seeing a reduction in work hours and the likelihood of working full-time but only women being less likely to work at all. We also find that closures had a corresponding negative effect on the earnings of parents of school-aged children. These effects are concentrated among parents without a college degree and parents working in occupations that do not lend themselves to telework, suggesting that such individuals had a more difficult time adjusting their work lives to school closures.

  8. Impact of Covid-19 on Employment - ILOSTAT

    • kaggle.com
    zip
    Updated May 1, 2021
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    Vineeth (2021). Impact of Covid-19 on Employment - ILOSTAT [Dataset]. https://www.kaggle.com/datasets/vineethakkinapalli/impact-of-covid19-on-employment-ilostat
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    zip(11347 bytes)Available download formats
    Dataset updated
    May 1, 2021
    Authors
    Vineeth
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Data obtained from ILOSTAT website. Collated various datasets from covid monitoring section. Most of the estimates are from 2020.

    Description about columns: 1. country - Name of Country 2. total_weekly_hours_worked(estimates_in_thousands) - Total weekly hours worked of employed persons 3. percentage_of_working_hrs_lost(%) - Percentage of hours lost compared to the baseline (4th quarter of 2019) 4. percent_hours_lost_40hrs_per_week(thousands) - Percentage of hours lost compared to the baseline (4th quarter of 2019) expressed in full-time equivalent employment losses. This measure is constructed by dividing the number of weekly hours lost due to COVID-19 and dividing them by 40. 5. percent_hours_lost_48hrs_per_week(thousands) - Percentage of hours lost compared to the baseline (4th quarter of 2019) expressed in full-time equivalent employment losses. This measure constructed by dividing the number of weekly hours lost due to COVID-19 and dividing them by 48. 6. labour_dependency_ratio - Ratio of dependants (persons aged 0 to 14 + persons aged 15 and above that are either outside the labour force or unemployed) to total employment. 7. employed_female_25+_2019(estimates in thousands) - Employed female in 2019 who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). 8. employed_male_25+_2019(estimates in thousands) - Employed male in 2019 who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). 9. ratio_of_weekly_hours_worked_by_population_age_15-64 - Ratio of total weekly hours worked to population aged 15-64.

  9. f

    The effects of the Covid-19 pandemic, policy responses and macroeconomic...

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Aug 23, 2022
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    Vo, Duc Hong; Nguyen, Hung Le-Phuc; Bui, Hung Quang; Tran, Thao (2022). The effects of the Covid-19 pandemic, policy responses and macroeconomic fundamentals on the market risks across 24 Vietnamese sectors. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000448956
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    Dataset updated
    Aug 23, 2022
    Authors
    Vo, Duc Hong; Nguyen, Hung Le-Phuc; Bui, Hung Quang; Tran, Thao
    Description

    The effects of the Covid-19 pandemic, policy responses and macroeconomic fundamentals on the market risks across 24 Vietnamese sectors.

  10. f

    Summary of COVID-19 data.

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated May 10, 2024
    + more versions
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    Henderson, Max; Webb, Edward J. D.; Hulme, Claire; Munyombwe, Theresa; Kingsbury, Sarah R.; Martin, Adam; West, Robert; Conaghan, Philip G. (2024). Summary of COVID-19 data. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001476994
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    Dataset updated
    May 10, 2024
    Authors
    Henderson, Max; Webb, Edward J. D.; Hulme, Claire; Munyombwe, Theresa; Kingsbury, Sarah R.; Martin, Adam; West, Robert; Conaghan, Philip G.
    Description

    BackgroundLong-term health conditions can affect labour market outcomes. COVID-19 may have increased labour market inequalities, e.g. due to restricted opportunities for clinically vulnerable people. Evaluating COVID-19’s impact could help target support.AimTo quantify the effect of several long-term conditions on UK labour market outcomes during the COVID-19 pandemic and compare them to pre-pandemic outcomes.MethodsThe Understanding Society COVID-19 survey collected responses from around 20,000 UK residents in nine waves from April 2020-September 2021. Participants employed in January/February 2020 with a variety of long-term conditions were matched with people without the condition but with similar baseline characteristics. Models estimated probability of employment, hours worked and earnings. We compared these results with results from a two-year pre-pandemic period. We also modelled probability of furlough and home-working frequency during COVID-19.ResultsMost conditions (asthma, arthritis, emotional/nervous/psychiatric problems, vascular/pulmonary/liver conditions, epilepsy) were associated with reduced employment probability and/or hours worked during COVID-19, but not pre-pandemic. Furlough was more likely for people with pulmonary conditions. People with arthritis and cancer were slower to return to in-person working. Few effects were seen for earnings.ConclusionCOVID-19 had a disproportionate impact on people with long-term conditions’ labour market outcomes.

  11. Threshold GARCH results.

    • plos.figshare.com
    xls
    Updated Apr 16, 2024
    + more versions
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    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti (2024). Threshold GARCH results. [Dataset]. http://doi.org/10.1371/journal.pone.0295853.t006
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    xlsAvailable download formats
    Dataset updated
    Apr 16, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti
    License

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

    Description

    The COVID-19 pandemic has emerged as a significant event of the current century, introducing substantial transformations in economic and social activities worldwide. The primary objective of this study is to investigate the relationship between daily COVID-19 cases and Pakistan stock market (PSX) return volatility. To assess the relationship between daily COVID-19 cases and the PSX return volatility, we collected secondary data from the World Health Organization (WHO) and the PSX website, specifically focusing on the PSX 100 index, spanning from March 15, 2020, to March 31, 2021. We used the GARCH family models for measuring the volatility and the COVID-19 impact on the stock market performance. Our E-GARCH findings show that there is long-term persistence in the return volatility of the stock market of Pakistan in the period of the COVID-19 timeline because ARCH alpha (ω1) and GARCH beta (ω2) are significant. Moreover, is asymmetrical effect is found in the stock market of Pakistan during the COVID-19 period due to Gamma (ѱ) being significant for PSX. Our DCC-GARCH results show that the COVID-19 active cases have a long-term spillover impact on the Pakistan stock market. Therefore, the need of strong planning and alternative platform should be needed in the distress period to promote the stock market and investor should advised to make diversified international portfolio by investing in high and low volatility stock market to save their income. This study advocated the implications for investors to invest in low volatility stock especially during the period of pandemics to protect their return on investment. Moreover, policy makers and the regulators can make effective policies to maintain financial stability during pandemics that is very important for the country’s economic development.

  12. COVID-19 Impact on Food Security, Livelihoods and Local Markets (Jul - Sep...

    • microdata.unhcr.org
    • catalog.ihsn.org
    • +1more
    Updated Feb 19, 2021
    + more versions
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    UNHCR (2021). COVID-19 Impact on Food Security, Livelihoods and Local Markets (Jul - Sep 2020) - Zimbabwe [Dataset]. https://microdata.unhcr.org/index.php/catalog/294
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    Dataset updated
    Feb 19, 2021
    Dataset provided by
    United Nations High Commissioner for Refugeeshttp://www.unhcr.org/
    Authors
    UNHCR
    Time period covered
    2020 - 2021
    Area covered
    Zimbabwe
    Description

    Abstract

    Assessment of the impact of the COVID-19 pandemic on food security, livelihoods and local markets for refugees in urban areas.

    Geographic coverage

    Urban areas in Zimbabwe

    Analysis unit

    Household

    Universe

    Urban refugees

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Random sampling

    Mode of data collection

    Computer Assisted Telephone Interview [cati]

  13. f

    Pak return and covid.

    • figshare.com
    xlsx
    Updated Apr 16, 2024
    + more versions
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    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti (2024). Pak return and covid. [Dataset]. http://doi.org/10.1371/journal.pone.0295853.s001
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Apr 16, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti
    License

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

    Description

    The COVID-19 pandemic has emerged as a significant event of the current century, introducing substantial transformations in economic and social activities worldwide. The primary objective of this study is to investigate the relationship between daily COVID-19 cases and Pakistan stock market (PSX) return volatility. To assess the relationship between daily COVID-19 cases and the PSX return volatility, we collected secondary data from the World Health Organization (WHO) and the PSX website, specifically focusing on the PSX 100 index, spanning from March 15, 2020, to March 31, 2021. We used the GARCH family models for measuring the volatility and the COVID-19 impact on the stock market performance. Our E-GARCH findings show that there is long-term persistence in the return volatility of the stock market of Pakistan in the period of the COVID-19 timeline because ARCH alpha (ω1) and GARCH beta (ω2) are significant. Moreover, is asymmetrical effect is found in the stock market of Pakistan during the COVID-19 period due to Gamma (ѱ) being significant for PSX. Our DCC-GARCH results show that the COVID-19 active cases have a long-term spillover impact on the Pakistan stock market. Therefore, the need of strong planning and alternative platform should be needed in the distress period to promote the stock market and investor should advised to make diversified international portfolio by investing in high and low volatility stock market to save their income. This study advocated the implications for investors to invest in low volatility stock especially during the period of pandemics to protect their return on investment. Moreover, policy makers and the regulators can make effective policies to maintain financial stability during pandemics that is very important for the country’s economic development.

  14. Socio-economic impact of COVID-19 - Dataset - data.gov.uk

    • ckan.publishing.service.gov.uk
    Updated Aug 14, 2020
    + more versions
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    ckan.publishing.service.gov.uk (2020). Socio-economic impact of COVID-19 - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/socio-economic-impact-of-covid-19
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    Dataset updated
    Aug 14, 2020
    Dataset provided by
    CKANhttps://ckan.org/
    Description

    This briefing presents evidence on the socio-economic impact of COVID-19 on London and Londoners​ Topics included in the briefing focus on recent data releases published in the preceding months that tell us how social policy issues are evolving in London since the start of the COVID-19 pandemic For more on the health and demographic impacts see the Demographic Impact Briefing and for labour market impacts see Labour Market Analysis. A page linking to all Covid-19 related data and analyses can be found here.

  15. i

    Effects of COVID-19 on Global Healthcare Systems

    • ibisworld.com
    Updated Apr 16, 2020
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    IBISWorld (2020). Effects of COVID-19 on Global Healthcare Systems [Dataset]. https://www.ibisworld.com/blog/covid19-effects-global-healthcare-systems/99/5644/
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    Dataset updated
    Apr 16, 2020
    Dataset authored and provided by
    IBISWorld
    Time period covered
    Apr 16, 2020
    Description

    Amid the global health crisis, IBISWorld has tapped the expertise of our global research team to better understand how healthcare systems are faring amid COVID-19.

  16. d

    COVID-19 Impact on Food Insecurity

    • catalog.data.gov
    • data.kingcounty.gov
    • +1more
    Updated Feb 2, 2024
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    data.kingcounty.gov (2024). COVID-19 Impact on Food Insecurity [Dataset]. https://catalog.data.gov/dataset/covid-19-impact-on-food-insecurity
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    Dataset updated
    Feb 2, 2024
    Dataset provided by
    data.kingcounty.gov
    Description

    Public Health — Seattle & King County is monitoring changes in key economic, social, and other health indicators resulting from strategies to slow the spread of COVID-19.

  17. Impact of COVID-19 on insurance market growth globally 2020

    • statista.com
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    Statista, Impact of COVID-19 on insurance market growth globally 2020 [Dataset]. https://www.statista.com/statistics/1180764/impact-covid19-insurance-market-growth-global/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    Worldwide
    Description

    The COVID-19 pandemic decreased the growth of insurance markets globally in 2020. The growth rate of emerging markets, excluding China, have been hit the hardest and will be *** percent lower than forecasted at the end of 2019 due to the pandemic.

  18. d

    Replication Data and Code for: Effects of the COVID-19 pandemic on the...

    • dataone.org
    Updated Dec 28, 2023
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    Morales, Leonardo Fabio; Bonilla-Mejía, Leonardo; Pulido, Jose; Flórez, Luz A.; Hermida, Didier; Pulido-Mahech, Karen L.; Lasso-Valderrama, Francisco (2023). Replication Data and Code for: Effects of the COVID-19 pandemic on the Colombian labour market: Disentangling the effect of sector-specific mobility restrictions [Dataset]. http://doi.org/10.5683/SP3/QSUWVY
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Morales, Leonardo Fabio; Bonilla-Mejía, Leonardo; Pulido, Jose; Flórez, Luz A.; Hermida, Didier; Pulido-Mahech, Karen L.; Lasso-Valderrama, Francisco
    Description

    The data and programs replicate tables and figures from "Effects of the COVID-19 pandemic on the Colombian labour market: Disentangling the effect of sector-specific mobility restrictions", by Morales, Bonilla-Mejía, Pulido, Flórez, Hermida, Pulido-Mahech and Lasso-Valderrama. Please see the ReadMe file for additional details.

  19. H

    Replication Data for: "A Pandemic Crossing the Border: The Impact of...

    • dataverse.harvard.edu
    Updated Jul 24, 2023
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    Irvin Rojas; Jisang Yu (2023). Replication Data for: "A Pandemic Crossing the Border: The Impact of Covid-19 in the US on the Mexican Labor Market" [Dataset]. http://doi.org/10.7910/DVN/J6WUGJ
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 24, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Irvin Rojas; Jisang Yu
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Mexico, Mexico-United States border, United States
    Description

    The labor markets in the US and Mexico are closely linked through migrant workers and remittances and the changes in remittance flow may alter labor allocations in the origin households. In this paper, we investigate how the prevalence of the Covid-19 epidemic in the US affected the local labor market in Mexico. We construct a Mexican municipality-level measure of the exposure to Covid-19 in the US using data on Covid-19 prevalence across US states and data on migrants' destinations across the US states. We find a positive effect of Covid-19 exposure in the US on the hours worked among workers in Mexico yet no significant effects were found for the local wages. We also find that the effect varies across subgroups which indicates that the responses in hours worked depend on the household dynamics, the nature of the occupation-specific tasks, and the migration intensity. Finally, we document the potential mechanism behind the effect on the hours worked, which is through the changes in remittances sent to the origin municipalities in Mexico.

  20. Z

    COVID-19 Vaccine Development Tools Market - By Technology (Lab Technologies,...

    • zionmarketresearch.com
    pdf
    Updated Nov 23, 2025
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    Zion Market Research (2025). COVID-19 Vaccine Development Tools Market - By Technology (Lab Technologies, PCR & qPCR, Flow Cytometry, Spectrometry, Electron Microscopy, and Next Generation Sequencing), By End-Use (CROs and Pharma & BioPharma Firms), And By Region- Global Industry Perspective, Comprehensive Analysis, and Forecast, 2024 - 2032 [Dataset]. https://www.zionmarketresearch.com/report/covid-19-vaccine-development-tools-market
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    pdfAvailable download formats
    Dataset updated
    Nov 23, 2025
    Dataset authored and provided by
    Zion Market Research
    License

    https://www.zionmarketresearch.com/privacy-policyhttps://www.zionmarketresearch.com/privacy-policy

    Time period covered
    2022 - 2030
    Area covered
    Global
    Description

    COVID-19 Vaccine Development Tools Market size is set to expand from $ 7.12 B in 2023 to $ 15.46 B by 2032, with CAGR of around 9% from 2024 to 2032.

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Statista, Capital market firms: COVID-19 effect on cloud technology worldwide 2021 [Dataset]. https://www.statista.com/statistics/1321937/pandemic-influence-cloud-technology-capital-market-worldwide/
Organization logo

Capital market firms: COVID-19 effect on cloud technology worldwide 2021

Explore at:
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Sep 2021
Area covered
Worldwide
Description

The coronavirus pandemic has affected the traditional working environment of capital market firms worldwide leading to the wider application of cloud technology. According to ** percent of respondents in a survey conducted in 2021, the coronavirus has shown the importance of cloud usage when improving firm processes. Cloud technology was also considered to be an important factor when improving user experience by ** percent of experts. Overall investment has increased as ** percent of experts noted increased spending on cloud-related activities/technology.

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