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Displaying results 1 to 25 of 78.

  1. News and narratives in financial systems
    exploiting big data for systemic risk assessment
    Author: Nyman, Rickard; Kapadia, Sujit; Tuckett, David; Gregory, David; Ormerod, Paul; Smith, Robert
    Published: January 2018
    Publisher:  Bank of England, London

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    Language: English
    Media type: Book
    Format: Online
    Series: Staff working paper / Bank of England ; no. 704
    Subjects: Systemic risk; text mining; big data; sentiment; uncertainty; narratives; forecasting; early warning indicators
    Scope: 1 Online-Ressource (circa 58 Seiten), Illustrationen
  2. Prediction for big data through Kriging
    small sequential and one-shot designs
    Author: Kleijnen, Jack P. C.; Beers, Wim C. M. van
    Published: 9 July 2018
    Publisher:  CentER, Center for Economic Research, Tilburg

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    Series: Discussion paper / CentER, Center for Economic Research ; no. 2018, 022
    Subjects: Kriging; Gaussian process; big data; experimental design; nearest neighbor
    Scope: 1 Online-Ressource (circa 44 Seiten), Illustrationen
  3. The potential of big housing data: an application to the Italian real-estate market
    Author: Loberto, Michele; Luciani, Andrea; Pangallo, Marco
    Published: [2018]
    Publisher:  Banca d'Italia Eurosistema, [Rom]

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    Series: Temi di discussione / Banca d'Italia ; number 1171 (April 2018)
    Subjects: big data; machine learning; housing market
    Scope: 1 Online-Ressource (circa 60 Seiten), Illustrationen
  4. Dynamic Competition in Deceptive Markets
    Author: Johnen, Johannes
    Published: [2018]
    Publisher:  CORE, [Louvain-la-Neuve]

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    hdl: 2078.1/191641
    Series: CORE discussion papers ; 2017, 36
    Subjects: Consumer mistakes; deceptive products; shrouded attributes; big data; targeted pricing; consumer data; add-on pricing; price discrimination; industry dynamics
    Scope: 1 Online-Ressource (circa 70 Seiten), Illustrationen
  5. The transformation of public policy analysis in times of crisis
    a microsimulation-nowcasting method using Big Data
    Author: O'Donoghue, Cathal; Sologon, Denisa M.
    Published: February 2023
    Publisher:  IZA - Institute of Labor Economics, Bonn, Germany

    The urgency of the two crises, especially the COVID-19 pandemic, revealed the inadequacy of traditional statistical datasets and models to provide a timely support to the decision-making process in times of volatility. Drawing upon advances in data... more

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    The urgency of the two crises, especially the COVID-19 pandemic, revealed the inadequacy of traditional statistical datasets and models to provide a timely support to the decision-making process in times of volatility. Drawing upon advances in data analytics for public policy and the increasing availability of real-time data, we develop and evaluate a method for real-time policy evaluations of tax and social protection policies. Our method goes beyond the state-of-the-art by implementing an aligned or calibrated microsimulation approach to generate a counterfactual income distribution as a function of more timely external data than the underlying income survey. We evaluate the simulation performance between our approach and the transition matrix approach by undertaking a nowcast for a historical crisis, judging against an actual change and each other. Nowcasting emerges as a useful methodology for examining up-to-date statistics on labour force participation, income distribution, prices, and income inequality. We find significant differences between approaches when the calibration involves structural heterogenous changes. The model replicates the changes in income distribution over one year; over the longer term, the model is able to capture the trend, but the precision of the levels weakens the further we get from the estimation year.

     
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    hdl: 10419/272564
    Series: Discussion paper series / IZA ; no. 15937
    Subjects: big data; policy analysis; nowcasting; microsimulation; COVID-19
    Scope: 1 Online-Ressource (circa 38 Seiten), Illustrationen
  6. Revealing investors' sentiment amid COVID-19:
    the big data evidence based on internet searches
    Author: Armas, Jean Christine A.; Tuazon, Pamela Kaye A.
    Published: September 2020
    Publisher:  Bangko Sentral ng Pilipinas, [Malate Manila, Philippines]

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    Language: English
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    Format: Online
    Series: BSP working paper series ; no. 2020, 07
    Subjects: government policy; regulation and public health; stock market; panel data models; investor attitude; big data
    Scope: 1 Online-Ressource (circa 32 Seiten), Illustrationen
  7. Nowcasting world trade with machine learning
    a three-step approach
    Author: Chinn, Menzie David; Meunier, Baptiste; Stumpner, Sebastian
    Published: [2023]
    Publisher:  European Central Bank, Frankfurt am Main, Germany

    We nowcast world trade using machine learning, distinguishing between tree-based methods (random forest, gradient boosting) and their regression-based counterparts (macroeconomic random forest, linear gradient boosting). While much less used in the... more

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    We nowcast world trade using machine learning, distinguishing between tree-based methods (random forest, gradient boosting) and their regression-based counterparts (macroeconomic random forest, linear gradient boosting). While much less used in the literature, the latter are found to outperform not only the tree-based techniques, but also more "traditional" linear and non-linear techniques (OLS, Markov-switching, quantile regression). They do so significantly and consistently across different horizons and real-time datasets. To further improve performances when forecasting with machine learning, we propose a flexible three-step approach composed of (step 1) pre-selection, (step 2) factor extraction and (step 3) machine learning regression. We find that both pre-selection and factor extraction significantly improve the accuracy of machine-learning-based predictions. This three-step approach also outperforms workhorse benchmarks, such as a PCA-OLS model, an elastic net, or a dynamic factor model. Finally, on top of high accuracy, the approach is flexible and can be extended seamlessly beyond world trade.

     
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    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9789289961219
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    hdl: 10419/278668
    Series: Working paper series / European Central Bank ; no 2836
    Subjects: Wirtschaftsprognose; Internationale Wirtschaft; Prognoseverfahren; Künstliche Intelligenz; Data Mining; Big Data; Faktorenanalyse; Nowcasting; Forecasting; big data; large dataset; factor model; pre-selection
    Scope: 1 Online-Ressource (circa 51 Seiten), Illustrationen
  8. Derivative margin calls
    a new driver of MMF flows
    Author: Ghio, Maddalena; Rousová, Linda; Salakhova, Dilyara; Villegas Bauer, Germán
    Published: [2023]
    Publisher:  European Central Bank, Frankfurt am Main, Germany

    During the March 2020 market turmoil, euro area money-market funds (MMFs) experienced significant outflows, reaching almost 8% of assets under management. This paper investigates whether the volatility in MMF flows was driven by investors' liquidity... more

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    During the March 2020 market turmoil, euro area money-market funds (MMFs) experienced significant outflows, reaching almost 8% of assets under management. This paper investigates whether the volatility in MMF flows was driven by investors' liquidity needs related to derivative margin payments. We combine three highly granular unique data sources (EMIR data for derivatives, SHSS data for investor holdings of MMFs and Refinitiv Lipper data for daily MMF flows) to construct a daily fund-level panel dataset spanning from February to April 2020. We estimate the effects of variation margin paid and received by the largest holders of EUR-denominated MMFs on flows of these MMFs. The main findings suggest that variation margin payments faced by some investors holding MMFs were an important driver of the flows of EUR-denominated MMFs domiciled in euro area.

     
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    ISBN: 9789289959964
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    hdl: 10419/278476
    Series: Working paper series / European Central Bank ; no 2800 (March 2023)
    Subjects: liquidity risk; money market funds; big data; interconnectedness; non-bank financial intermediaries
    Scope: 1 Online-Ressource (circa 36 Seiten), Illustrationen
  9. Two approaches to saving the economy
    micro-level effects of Covid-19 lockdowns in Italy
    Author: Cseres-Gergely, Zsombor; Kecht, Valentin; Le Blanc, Julia; Onorante, Luca
    Published: 2023
    Publisher:  European Commission, Ispra

    In response to the two waves of Covid-19 in 2020, the Italian government implemented a general lockdown in March, but geographically targeted policies during fall. We exploit this natural experiment to compare the effects of the two policies in a... more

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    In response to the two waves of Covid-19 in 2020, the Italian government implemented a general lockdown in March, but geographically targeted policies during fall. We exploit this natural experiment to compare the effects of the two policies in a difference-in-differences design, leveraging a unique database combining traditional, municipality-level and big data at weekly frequency. We find that the general lockdown of the first wave strongly reduced mobility at a high price in terms of employment, while the targeted policies during the second wave induced a lower decrease in mobility and little additional economic cost. We also study the role of pre-existing municipality characteristics and labour market policies in shaping these responses. Our results suggest that working from home and short-term working schemes buffered the adverse consequences of the drop in economic activity on the labour market. Both mechanisms, however, acted more strongly in high-income areas and among white collar workers, further exacerbating existing inequalities.

     
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    hdl: 10419/283080
    Series: JRC working papers in economics and finance ; 2023, 1
    Subjects: Covid-19; human mobility; lockdowns; big data; differences-in-differences
    Scope: 1 Online-Ressource (circa 43 Seiten), Illustrationen
  10. Big techs, QR code payments and financial inclusion
    Author: Beck, Thorsten; Gambacorta, Leonardo; Huang, Yiping; Li, Zhenhua; Qiu, Han
    Published: May 2022
    Publisher:  Bank for International Settlements, Monetary and Economic Department, [Basel]

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    Series: BIS working papers ; no 1011
    Subjects: big tech; big data; QR code; banks; asymmetric information; financial inclusion; credit markets
    Scope: 1 Online-Ressource (circa 47 Seiten), Illustrationen
  11. Predicting firm exits with machine learning
    implications for selection into COVID-19 support and productivity growth
    Author: Davies, Lily; Kattenberg, Mark; Vogt, Benedikt
    Published: March 2023
    Publisher:  CPB Netherlands Bureau for Economic Policy Analysis, [Den Haag]

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    Series: CPB discussion paper
    Subjects: machine learning; big data; firm exits; COVID-19
    Scope: 1 Online-Ressource (circa 84 Seiten), Illustrationen
  12. Learning from experts
    energy efficiency in residential buildings
    Author: Billio, Monica; Casarin, Roberto; Costola, Michele; Veggente, Veronica
    Published: [2023]
    Publisher:  Leibniz Institute for Financial Research SAFE, Sustainable Architecture for Finance in Europe, [Frankfurt am Main]

    Measuring and reducing energy consumption constitutes a crucial concern in public policies aimed at mitigating global warming. The real estate sector faces the challenge of enhancing building efficiency, where insights from experts play a pivotal... more

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    Measuring and reducing energy consumption constitutes a crucial concern in public policies aimed at mitigating global warming. The real estate sector faces the challenge of enhancing building efficiency, where insights from experts play a pivotal role in the evaluation process. This research employs a machine learning approach to analyze expert opinions, seeking to extract the key determinants influencing potential residential building efficiency and establishing an efficient prediction framework. The study leverages open Energy Performance Certificate databases from two countries with distinct latitudes, namely the UK and Italy, to investigate whether enhancing energy efficiency necessitates different intervention approaches. The findings reveal the existence of non-linear relationships between efficiency and building characteristics, which cannot be captured by conventional linear modeling frameworks. By offering insights into the determinants of residential building efficiency, this study provides guidance to policymakers and stakeholders in formulating effective and sustainable strategies for energy efficiency improvement.

     
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    hdl: 10419/279413
    Series: SAFE working paper ; no. 403 (October 2023)
    Subjects: Energy efficiency; Energy Performance Certificate; Machine learning; Tree-based models; big data
    Scope: 1 Online-Ressource (circa 49 Seiten), Illustrationen
  13. Vacancy posting, firm balance sheets, and pandemic policy
    Author: Van Dijcke, David; Buckmann, Marcus; Turrell, Arthur; Key, Tomas
    Published: [2023]
    Publisher:  Bank of England, London

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    Series: Staff working paper / Bank of England ; no. 1033 (July 2023)
    Subjects: Covid-19; recession; vacancies; Indeed; job postings; job ads; heterogeneity,firm; firm-level; balance sheets; industry; big data; alternative data; labour market; naturallanguage processing
    Scope: 1 Online-Ressource (circa 57 Seiten), Illustrationen
  14. (Frisch-Waugh-Lovell)' on the estimation of regression models by row
    Author: Clarke, Damian; Paris Torres, Nicolás; Villena-Roldán, Benjamin
    Published: November 2023
    Publisher:  IZA - Institute of Labor Economics, Bonn, Germany

    We demonstrate that regression models can be estimated by working independently in a row-wise fashion. We document a simple procedure which allows for a wide class of econometric estimators to be implemented cumulatively, where, in the limit,... more

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    We demonstrate that regression models can be estimated by working independently in a row-wise fashion. We document a simple procedure which allows for a wide class of econometric estimators to be implemented cumulatively, where, in the limit, estimators can be produced without ever storing more than a single line of data in a computer's memory. This result is useful in understanding the mechanics of many common regression models. These procedures can be used to speed up the computation of estimates computed via OLS, IV, Ridge regression, LASSO, Elastic Net, and Non-linear models including probit and logit, with all common modes of inference. This has implications for estimation and inference with "big data", where memory constraints may imply that working with all data at once is particularly costly. We additionally show that even with moderately sized datasets, this method can reduce computation time compared with traditional estimation routines.

     
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    hdl: 10419/282757
    Series: Discussion paper series / IZA ; no. 16630
    Subjects: big data; estimation; regression; matrix inversion
    Scope: 1 Online-Ressource (circa 46 Seiten), Illustrationen
  15. Digitale Formatentwicklung
    Nutzerorientierte Medien für die vernetzte Welt
    Author: van Wyngaarden, Egbert
    Published: 2018
    Publisher:  Herbert von Halem Verlag, Köln

    "Digitale Formatentwicklung: Nutzerorientierte Medien für die vernetzte Welt" präsentiert eine bahnbrechende Methode für die Entwicklung innovativer Medien im digitalen Zeitalter. Anhand aktueller Praxisbeispiele vermittelt das Buch Ansätze und... more

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    "Digitale Formatentwicklung: Nutzerorientierte Medien für die vernetzte Welt" präsentiert eine bahnbrechende Methode für die Entwicklung innovativer Medien im digitalen Zeitalter. Anhand aktueller Praxisbeispiele vermittelt das Buch Ansätze und Werkzeuge für die Konzeption, Gestaltung und Verbreitung von neuartigen Medienangeboten. Aspekte wie Interaktion, Gamifizierung und Nutzerbeteiligung kommen dabei genauso zur Sprache wie Impact-Strategien, Reichweite und Social Media Marketing. Mithilfe von Design Thinking, agilen Methoden und Prototyping werden die Mediennutzer konsequent in den Mittelpunkt gerückt. Die branchenübergreifende Herangehensweise des Buches erschließt dem Leser immer wieder unerwartete, zukunftsweisende Perspektiven - ganz besonders in Bezug auf emergente Technologien wie Augmented Reality (AR), Virtual Reality (VR), Big Data, künstliche Intelligenz, maschinelles Lernen und das Internet der Dinge. "Digitale Formatentwicklung" ist ein Must-read für alle Erzähler und Medienschaffende, die die vielfältigen Chancen und Möglichkeiten des Digitalen nutzen wollen, um ihr Publikum zu erreichen und zu begeistern

     
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  16. Digitale Formatentwicklung
    Nutzerorientierte Medien für die vernetzte Welt
    Author: van Wyngaarden, Egbert
    Published: 2018
    Publisher:  Herbert von Halem Verlag, Köln

    "Digitale Formatentwicklung: Nutzerorientierte Medien für die vernetzte Welt" präsentiert eine bahnbrechende Methode für die Entwicklung innovativer Medien im digitalen Zeitalter. Anhand aktueller Praxisbeispiele vermittelt das Buch Ansätze und... more

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    Hochschule Kempten, Hochschulbibliothek
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    Hochschule Landshut, Hochschule für Angewandte Wissenschaften, Bibliothek
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    Evangelische Hochschule Nürnberg, Bibliothek
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    Technische Hochschulbibliothek Rosenheim
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    "Digitale Formatentwicklung: Nutzerorientierte Medien für die vernetzte Welt" präsentiert eine bahnbrechende Methode für die Entwicklung innovativer Medien im digitalen Zeitalter. Anhand aktueller Praxisbeispiele vermittelt das Buch Ansätze und Werkzeuge für die Konzeption, Gestaltung und Verbreitung von neuartigen Medienangeboten. Aspekte wie Interaktion, Gamifizierung und Nutzerbeteiligung kommen dabei genauso zur Sprache wie Impact-Strategien, Reichweite und Social Media Marketing. Mithilfe von Design Thinking, agilen Methoden und Prototyping werden die Mediennutzer konsequent in den Mittelpunkt gerückt. Die branchenübergreifende Herangehensweise des Buches erschließt dem Leser immer wieder unerwartete, zukunftsweisende Perspektiven - ganz besonders in Bezug auf emergente Technologien wie Augmented Reality (AR), Virtual Reality (VR), Big Data, künstliche Intelligenz, maschinelles Lernen und das Internet der Dinge. "Digitale Formatentwicklung" ist ein Must-read für alle Erzähler und Medienschaffende, die die vielfältigen Chancen und Möglichkeiten des Digitalen nutzen wollen, um ihr Publikum zu erreichen und zu begeistern

     
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  17. FRED-MD
    a monthly database for macroeconomic research
    Author: McCracken, Michael W.; Ng, Serena
    Published: 2015
    Publisher:  Federal Reserve Bank of St. Louis, Research Division, St. Louis, Mo.

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    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Format: Online
    Series: Working paper series / Federal Reserve Bank of St. Louis, Research Division ; 2015-012
    Subjects: diffusion index; forecasting; big data; factors
    Scope: Online Resource (29 S.), graph. Darst.
  18. Personal information management services methodology working paper
    Author: Smith, Jamie; Mitchell, Alan
    Published: 2014
    Publisher:  NESTA, London

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    Series: Nesta working paper series ; 14,08
    Subjects: personal data; privacy; big data
    Scope: Online-Ressource (17 S.), graph. Darst.
  19. The more you know
    information effects in job application rates by gender in a large field experiment
    Author: Gee, Laura K.
    Published: 2014
    Publisher:  Dep. of Economics, Tufts Univ., Medford, Mass.

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    Series: Economics Department working papers / Tufts University ; 2014,4
    Subjects: field experiment; labor search; social information; big data; gender,risk aversion; ambiguity aversion; uncertainty; herding; competition
    Scope: Online-Ressource (28 S.), graph. Darst.
  20. Analyzing disparities trends for health care insurance coverage among non-elderly adults in the US
    evidence from the behavioral risk factor surveillance system, 1993-2009
    Author: Assaf, Shireen; Campostrini, Stefano; Di Novi, Cinzia; Xu, Fang; Gotway, Carol A.
    Published: [2014]
    Publisher:  Department of Economics, Ca’ Foscari University of Venice, Venice Italy

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    Series: Working paper / Ca' Foscari University of Venice, Department of Economics ; 2014, no. 14
    Subjects: USA; big data; disparities; health plan; health surveillance data; P-splines; temporal trends; varying coefficient model
    Scope: 1 Online-Ressource (circa 23 Seiten), Illustrationen
  21. The impact of public policies on deforestation in the Brazilian Amazon
    Author: Cisneros Tersitsch, Marco Elías
    Published: 2017

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    Universitätsbibliothek Braunschweig
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    Staats- und Universitätsbibliothek Bremen
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    Universitätsbibliothek Clausthal
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    Fachhochschule Erfurt, Hochschulbibliothek
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    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
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    Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky
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  22. A low-cost and flexible approach for tracking jobs and economic activity related to innovative technologies
    Author: Mandel, Michael; Scherer, Judith
    Published: 2015
    Publisher:  NESTA, London

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Nesta working paper series ; 15,11
    Subjects: innovation; jobs; want ads; data collection; employment; big data; IT
    Scope: Online-Ressource (29 S.), Ill., graph. Darst.
  23. Social action on social media
    Author: Miller, Carl
    Published: 2015
    Publisher:  NESTA, London

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    Language: English
    Media type: Book
    Format: Online
    Series: Nesta working paper series ; 15,04
    Subjects: social media; social action; big data
    Scope: Online-Ressource (41 S.), graph. Darst.
  24. Peer-to-peer lending and financial innovation in the United Kingdom
    Author: Atz, Ulrich; Bholat, David
    Published: April 2016
    Publisher:  Bank of England, [London]

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Staff working paper / Bank of England ; no. 598
    Subjects: Peer-to-peer lending; crowdfunding; innovation; fintech; big data
    Scope: 1 Online-Ressource (circa 27 Seiten), Illustrationen
  25. Evaluating Covid-19's impact on firm performance in the carec region using night-time light data
    Azerbaijan, Georgia, Kazakhstan, and Mongolia
    Author: Karymshakov, Kamalbek; Azhgaliyeva, Dina; Mishra, Ranjeeta; Aseinov, Dastan
    Published: [2022]
    Publisher:  Asian Development Bank Institute, Tokyo, Japan

    This study examines economic activity measured with firm performance indicators using the changes in intensity of night-time light in four CAREC economies: Azerbaijan, Georgia, Kazakhstan, and Mongolia. The empirical analysis is based on the World... more

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    This study examines economic activity measured with firm performance indicators using the changes in intensity of night-time light in four CAREC economies: Azerbaijan, Georgia, Kazakhstan, and Mongolia. The empirical analysis is based on the World Bank Enterprise Survey (WBES) data for 2019 and a follow-up survey conducted during the COVID-19 pandemic. The Enterprise Survey dataset was enhanced with data on night-time light intensity from Google Earth and the strictness of "lockdown-style" policies, i.e., the stringency index from Hale et al. (2021). Using the probit regression model, this study investigates the impact of COVID-19 on firm performance and night-time light in CAREC countries. Firm performance is measured using four variables: decrease in sales, demand, export share, and working hours. Our results show that, as the night-time light increases, the likelihood of performance deterioration is reduced. Larger firms are more likely to maintain their performance than smaller firms. The sales in the manufacturing, clothing, and services sectors are more likely to decline than those in the food sector. Accordingly, the results point to a significant decline in the performance of firms operating in the service sector compared with those in the food sector during the pandemic.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/267765
    Series: ADBI working paper series ; no. 1332 (July 2022)
    Subjects: Central Asia; COVID-19; big data; firm performance; gender; SMEs
    Scope: 1 Online-Ressource (circa 29 Seiten), Illustrationen