In Search Of Information Use Of Google Trends Data To Narrow Information Gaps For Low Income Developing Countries
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| Author | : Mr.Futoshi Narita |
| Publisher | : International Monetary Fund |
| Total Pages | : 51 |
| Release | : 2018-12-14 |
| Genre | : Business & Economics |
| ISBN | : 1484392531 |
Timely data availability is a long-standing challenge in policy-making and analysis for low-income developing countries. This paper explores the use of Google Trends’ data to narrow such information gaps and finds that online search frequencies about a country significantly correlate with macroeconomic variables (e.g., real GDP, inflation, capital flows), conditional on other covariates. The correlation with real GDP is stronger than that of nighttime lights, whereas the opposite is found for emerging market economies. The search frequencies also improve out-of-sample forecasting performance albeit slightly, demonstrating their potential to facilitate timely assessments of economic conditions in low-income developing countries.
| Author | : Mr. Paul A Austin |
| Publisher | : International Monetary Fund |
| Total Pages | : 47 |
| Release | : 2021-12-17 |
| Genre | : Business & Economics |
| ISBN | : 1616355433 |
As the pandemic heigthened policymakers’ demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short—triggering stronger interest in real time data to provide early signals of turning points in economic activity. In this paper, we examine how data extracted from the Google Places API and Google Trends can be used to develop high frequency indicators aligned to the statistical concepts, classifications, and definitions used in producing official measures. The approach is illustrated by use of Google data-derived indicators that predict well the GDP trajectories of selected countries during the early stage of COVID-19. To this end, we developed a methodological toolkit for national compilers interested in using Google data to enhance the timeliness and frequency of economic indicators.
| Author | : Olga Bespalova |
| Publisher | : International Monetary Fund |
| Total Pages | : 38 |
| Release | : 2022-11-11 |
| Genre | : Business & Economics |
| ISBN | : |
This paper improves short-term forecasting models of monthly tourism arrivals by estimating and evaluating a time-series model with exogenous regressors (ARIMA-X) using a case of Aruba, a small open tourism-dependent economy. Given importance of the US market for Aruba, it investigates informational value of Google Searches originating in the USA, flight capacity utilization on the US air-carriers, and per capita demand of the US consumers, given the volatility index in stock markets (VIX). It yields several insights. First, flight capacity is the best variable to account for the travel restrictions during the pandemic. Second, US real personal consumption expenditure becomes a more significnat predictor than income as the former better captured impact of the COVID-19 restrictions on the consumers’ behavior, while income boosted by the pandemic fiscal support was not fully directed to spending. Third, intercept correction improves the model in the estimation period. Finally, the pandemic changed econometric relationships between the tourism arrivals and their main determinants, and accuracy of the forecast models. Going forward, the analysts should re-estimate the models. Out-of-sample forecasts with 5 percent confidence intervals are produced for 18 months ahead.
| Author | : Beata Woźniak-Jęchorek |
| Publisher | : Taylor & Francis |
| Total Pages | : 250 |
| Release | : 2023-01-19 |
| Genre | : Business & Economics |
| ISBN | : 1000829154 |
This book examines the impact of the COVID-19 pandemic on changing labour markets and accelerating digitalisation of the workplace in Central and Eastern Europe. It provides an innovative and enriching take on the work experience from the pandemic times and discusses the challenges of ongoing changes in labour markets and workplaces in a way that is not covered by the extant literature. The impact of the COVID-19 pandemic and digitalisation on labour market outcomes is analysed throughout 12 chapters, by 34 labour market experts from various CEE countries. Most chapters are based on empirical methods yet are presented in an easy-to-follow way to make the book also accessible for a non-scientific audience. The volume addresses the three key goals: to better understand the impact of the COVID-19 pandemic on the adoption of workplace digitalisation in the selected labour markets in CEE countries and the potential trade-offs facing those who do and do not have access to this benefit to complement the labour market research by incorporating the outputs of changing demand for skills to contribute new insight into policies and regulations that govern the future of work The book argues that the recent COVID-19 pandemic was a sombre reminder of the relevance and necessity of digital technology for a variety of sectors and market activities. It concludes that to downside the risks of vanishing jobs, as well as to minimise the threats and maximise the opportunities of digitalisation in CEE countries, labour market partners need to consider an effective governance tool in terms of inclusive access to the digital environment, re-skilling, and balanced regulations of the more problematic facets of digital work. The book will be of interest to postgraduate researchers and academics in the fields of labour economics, regional economics, and macroeconomics. Additionally, due to the broader policy implications of the topic, the book will appeal to policymakers and experts interested in labour economics. The Introduction, Chapters 4 and 12 of this book are freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
| Author | : Agostino Capponi |
| Publisher | : Cambridge University Press |
| Total Pages | : 742 |
| Release | : 2023-04-30 |
| Genre | : Mathematics |
| ISBN | : 1316516199 |
Leveraging the research efforts of more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence. The text is structured around three main areas: 'Interactions with investors and asset owners,' which covers robo-advisors and price formation; 'Risk intermediation,' which discusses derivative hedging, portfolio construction, and machine learning for dynamic optimization; and 'Connections with the real economy,' which explores nowcasting, alternative data, and ethics of algorithms. Accessible to a wide audience, this invaluable resource will allow practitioners to include machine learning driven techniques in their day-to-day quantitative practices, while students will build intuition and come to appreciate the technical tools and motivation for the theory.
| Author | : OECD |
| Publisher | : OECD Publishing |
| Total Pages | : 267 |
| Release | : 2020-12-01 |
| Genre | : |
| ISBN | : 9264861750 |
The COVID-19 pandemic will cast a long shadow over the world’s economies and the economic outlook is very uncertain. This issue of the OECD Economic Outlook analyses the impacts of COVID-19 on the economy and puts forward projections for output, employment, prices, fiscal and current account balances.
| Author | : Omer Faruk Akbal |
| Publisher | : International Monetary Fund |
| Total Pages | : 36 |
| Release | : 2023-08-04 |
| Genre | : Business & Economics |
| ISBN | : |
Quarterly GDP statistics facilitate timely economic assessment, but the availability of such data are limited for more than 60 developing economies, including about 20 countries in sub-Saharan Africa as well as more than two-thirds of fragile and conflict-affected states. To address this limited data availablity, this paper proposes a panel approach that utilizes a statistical relationship estimated from countries where data are available, to estimate quarterly GDP statistics for countries that do not publish such statistics by leveraging the indicators readily available for many countries. This framework demonstrates potential, especially when applied for similar country groups, and could provide valuable real-time insights into economic conditions supported by empirical evidence.
| Author | : Sergio Consoli |
| Publisher | : Springer Nature |
| Total Pages | : 357 |
| Release | : 2021 |
| Genre | : Application software |
| ISBN | : 3030668916 |
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
| Author | : Hana Lipovská |
| Publisher | : Routledge |
| Total Pages | : 227 |
| Release | : 2020-04-15 |
| Genre | : Business & Economics |
| ISBN | : 1000061493 |
This book examines secessionism, separatism, and calls for independence in the European Union in recent history and within an economic context. It contributes to the deeper understanding of factors influencing the individual decision-making processes around secession, using economic analysis to answer a set of simple questions about who the secessionists are, what they really want, what their incentives are, and why it is easier to declare their secessionist tendencies than to vote for secession. This a highly topical theme, given the secessionist referenda in Catalonia, Scotland, Ukraine, Kosovo, and the United Kingdom, and this book offers a unique contribution to the debate. It is based on an exclusive survey carried out among members of the pro-independence parties and movements across 17 European countries and 56 European regions. It uses the instruments of the Political Economy of Conflict to reveal the importance of romantic and economic factors influencing the drive towards secession. Secessions have been regarded as a purely romantic phenomenon that cannot be rationalised, whereas this book connects the sensibility of romantic factors such as language, religion or ethnicity with the sense of economic factors through its rational, economic approach. Furthermore, it applies the standard methodology of microeconomic analysis to discover the impact of individual pro-secessionist factors. An integral part of the text presents a brief historic overview, uncovering the lesser-known path dependency. The book will find an audience among researchers, scholars, and students of economics and political science, as well as policy-makers and professionals engaged with a secessionist agenda.
| Author | : Karim Barhoumi |
| Publisher | : International Monetary Fund |
| Total Pages | : 23 |
| Release | : 2022-05-06 |
| Genre | : Business & Economics |
| ISBN | : |
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.
