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Author: Brandon Buell
Publisher: International Monetary Fund
ISBN: 1513582496
Category : Business & Economics
Languages : en
Pages : 61
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Book Description
The COVID-19 pandemic underscores the critical need for detailed, timely information on its evolving economic impacts, particularly for Sub-Saharan Africa (SSA) where data availability and lack of generalizable nowcasting methodologies limit efforts for coordinated policy responses. This paper presents a suite of high frequency and granular country-level indicator tools that can be used to nowcast GDP and track changes in economic activity for countries in SSA. We make two main contributions: (1) demonstration of the predictive power of alternative data variables such as Google search trends and mobile payments, and (2) implementation of two types of modelling methodologies, machine learning and parametric factor models, that have flexibility to incorporate mixed-frequency data variables. We present nowcast results for 2019Q4 and 2020Q1 GDP for Kenya, Nigeria, South Africa, Uganda, and Ghana, and argue that our factor model methodology can be generalized to nowcast and forecast GDP for other SSA countries with limited data availability and shorter timeframes.
Author: Brandon Buell
Publisher: International Monetary Fund
ISBN: 1513582496
Category : Business & Economics
Languages : en
Pages : 61
Get Book Here
Book Description
The COVID-19 pandemic underscores the critical need for detailed, timely information on its evolving economic impacts, particularly for Sub-Saharan Africa (SSA) where data availability and lack of generalizable nowcasting methodologies limit efforts for coordinated policy responses. This paper presents a suite of high frequency and granular country-level indicator tools that can be used to nowcast GDP and track changes in economic activity for countries in SSA. We make two main contributions: (1) demonstration of the predictive power of alternative data variables such as Google search trends and mobile payments, and (2) implementation of two types of modelling methodologies, machine learning and parametric factor models, that have flexibility to incorporate mixed-frequency data variables. We present nowcast results for 2019Q4 and 2020Q1 GDP for Kenya, Nigeria, South Africa, Uganda, and Ghana, and argue that our factor model methodology can be generalized to nowcast and forecast GDP for other SSA countries with limited data availability and shorter timeframes.
Author: Karim Barhoumi
Publisher: International Monetary Fund
ISBN:
Category : Business & Economics
Languages : en
Pages : 23
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Book Description
The COVID-19 crisis has had a tremendous economic impact for all countries. Yet, assessing the full impact of the crisis has been frequently hampered by the delayed publication of official GDP statistics in several emerging market and developing economies. This paper outlines a machine-learning framework that helps track economic activity in real time for these economies. As illustrative examples, the framework is applied to selected sub-Saharan African economies. The framework is able to provide timely information on economic activity more swiftly than official statistics.
Author: Cesar Calderon
Publisher: World Bank Publications
ISBN: 1464815682
Category : Business & Economics
Languages : en
Pages : 136
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Book Description
The COVID-19 pandemic has taken a toll on human life and brought major disruption to economic activity across the world. Despite a late arrival, the COVID-19 virus has spread rapidly across Sub-Saharan Africa in recent weeks. Economic growth in Sub-Saharan Africa is projected to decline from 2.4 percent in 2019 to -2.1 to -5.1 percent in 2020, the first recession in the region in 25 years. The coronavirus is hitting the region’s three largest economies —Nigeria, South Africa, and Angola— in a context of persistently weak growth and investment. In particular, countries that depend on oil and mining exports would be hit the hardest. The negative impact of the COVID-19 crisis on household welfare would be equally dramatic. African policymakers need to develop a two-pronged strategy of “saving lives and protecting livelihoods.†? This strategy includes relief measures and recovery measures aimed at strengthening health systems, providing income support to workers and liquidity support to viable businesses. However, financing of these policies will be challenging amid deteriorating fiscal positions and heightened public debt vulnerabilities. Therefore, African countries will require financial assistance from their development partners -including COVID-19 related multilateral assistance and a debt service stand still with creditors.
Author: Alvi, Muzna Fatima
Publisher: Intl Food Policy Res Inst
ISBN:
Category : Political Science
Languages : en
Pages : 144
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Book Description
It is widely recognized that periods of crisis affect men and women differently, mediated by their access to resources and information, as well as social and institutional structures that may systematically disadvantage women from being able to access relief, institutional support, and rehabilitation. To capture the gendered impacts of the COVID-19 pandemic and lockdowns, we conducted phone surveys in seven countries spread across Asia and Africa. The study was designed as a longitudinal panel study with five rounds of data collection in Ghana, Nepal, Nigeria, and Senegal, and three rounds of data collection in Kenya, Niger, and Uganda. Both men and women were administered the same survey, with some modifications made across countries to adapt to local contexts. This report gives an overview of our findings covering several topics including income loss, coping strategies, labor and time use, food and water insecurity and child education outcomes. We find widespread reports of income loss, which declined over time, but increased again as countries experienced a resurgence in COVID-19 cases and fatality. We find that households first depleted savings when faced with income loss and over time, use of savings reduced while other measures began to be adopted. Women reported greater food and water insecurity compared to men, including worrying about insufficient food and eating less than usual. This is particularly worrying since a large proportion of women also did not have adequately diverse diets. Moderate to severe water insecurity was reported in many of the countries, and as with food insecurity, women were more likely to report issues with accessing water for drinking and other household activities. In some countries, additional modules were added to capture country specific issues of policy relevance, such agriculture extension, mental health, and child marriage. The results make it clear that proactive investments will be needed, including social safety nets, favorable credit policies, nutrition and water investments, to ensure that the crisis does not further widen the gender gap in resources and achievements in rural areas of low- and middle-income countries.
Author: Zhao, Peng
Publisher: IGI Global
ISBN: 1799887952
Category : Computers
Languages : en
Pages : 349
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Book Description
There has been a multitude of studies focused on the COVID-19 pandemic across fields and disciplines as all sectors of life have had to adjust the way things are done and adapt to the constantly shifting environment. These studies are crucial as they provide support and perspectives on how things are changing and what needs to be done to stay afloat. Connecting COVID-19-related studies and big data analytics is crucial for the advancement of industrial applications and research areas. Applied Big Data Analytics and Its Role in COVID-19 Research introduces the most recent industrial applications and research topics on COVID-19 with big data analytics. Featuring coverage on a broad range of big data technologies such as data gathering, artificial intelligence, smart diagnostics, and mining mobility, this publication provides concrete examples and cases of usage of data-driven projects in COVID-19 research. This reference work is a vital resource for data scientists, technical managers, researchers, scholars, practitioners, academicians, instructors, and students.
Author: M. Niranjanamurthy
Publisher: Springer Nature
ISBN: 9811615748
Category : Technology & Engineering
Languages : en
Pages : 370
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Book Description
This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.
Author:
Publisher:
ISBN: 9781464845680
Category : COVID-19 (Disease)
Languages : en
Pages : 136
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Book Description
Author: Luca Barbaglia
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
During the COVID-19 pandemic, economists have struggled to obtain reliable economic predictions, with standard models becoming outdated and their forecasting performance deteriorating rapidly. This paper presents two novelties that could be adopted by forecasting institutions in unconventional times. The first innovation is the construction of an extensive data set for macroeconomic forecasting in Europe. We collect more than a thousand time series from conventional and unconventional sources, complementing traditional macroeconomic variables with timely big data indicators and assessing their added value at nowcasting. The second novelty consists of a methodology to merge an enormous amount of non-encompassing data with a large battery of classical and more sophisticated forecasting methods in a seamlessly dynamic Bayesian framework. Specifically, we introduce an innovative "selection prior" that is used not as a way to influence model outcomes, but as a selecting device among competing models. By applying this methodology to the COVID-19 crisis, we show which variables are good predictors for nowcasting Gross Domestic Product and draw lessons for dealing with possible future crises.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The economic impact of the COVID-19 pandemic in Sub-Saharan Africa has been severe; however, countries are weathering the storm so far. Real GDP is estimated to contract by 2.0 percent in 2020-close to the lower bound of the forecast range in April 2020, and less than the contraction in advanced economies and other emerging markets and developing economies, excluding China. Available data from the second half of 2020 point to rebound in economic activity that explain why the contraction in the region was in the lower bound of the forecasts. It reflected a slower spread of the virus and lower COVID-19-related mortality in the region, strong agricultural growth, and a faster-than-expected recovery in commodity prices. Economic activity in the region is expected to rise to a range between2.3 and 3.4 percent in 2021, depending on the policy measures adopted by countries and the international community. However, prospects for a slow vaccine rollout, the resurgence of pandemic, and limited scope for additional fiscal support, could hold back the recovery in the region. Policies to support the economy in the near term should be complemented by structural reforms that encourage sustained investment, create jobs and enhance competitiveness. Reducing the countries' debt burden will release resources for public investment, in areas such as education, health, and infrastructure. Investments in human capital will help lower the risk of long-lasting damage from the pandemic which may become apparent over the longer term, and can enhance competitiveness and productivity. The next twelve months will be a critical period for leveraging the African Continental Free Trade Area in order to deepen African countries' integration into regional and global value chains. Finally, reforms that address digital infrastructure gaps and make the digital economy more inclusive "ensuring affordability but also building skills for all segments of society, are critical to improve connectivity, boost digital technology adoption, and generate more and better jobs for men and women.
Author: Jürgen Schwettmann
Publisher:
ISBN: 9783962506223
Category :
Languages : en
Pages :
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Book Description
