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  1. (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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    Language: English
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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
  2. 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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    Media type: Book
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    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.
  3. Addressing data gaps with innovative data sources
    Author: Vizmanos, Jana Flor V.; Albert, Jose Ramon G.; Muñoz, Mika S.; Brucal, Arlan; Halili, Riza Teresita; Lumba, Angelo Jose; Patanñe, Gaile Anne
    Published: December 2022
    Publisher:  Philippine Institute for Development Studies, Quezon City, Philippines

    With the advent of digital transformation, ICT innovations have also led to a "data revolution" wherein more data is being captured, produced, stored, accessed, analyzed, archived, and reanalyzed, and at an exponential pace. An examination of new... more

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    With the advent of digital transformation, ICT innovations have also led to a "data revolution" wherein more data is being captured, produced, stored, accessed, analyzed, archived, and reanalyzed, and at an exponential pace. An examination of new data sources, including big data and crowd-sourced data, can complement traditional sources of statistics and can unlock insights that can ultimately lead to interventions for better outcomes by informing policies and actions toward attaining robust, sustainable, and inclusive development. This study will examine PIDS website download data and Twitter data to illustrate stories that can be obtained from new data sources and explore how access, analysis and use of new data sources can be promoted. Several quantitative tools are used on these new data sources, including (a) market basket analysis for website download data, (b) text mining (and sentiment analysis) for web scraped Twitter data, and (c) other big data analytics tools. Policy issues, including risk management for use of these new data sources, are also discussed.

     
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    hdl: 10419/284592
    Series: Discussion paper series / Philippine Institute for Development Studies ; no. 2022, 55 (December 2022)
    Subjects: data revolution; big data; new data sources; social media data; market-basket analysis; web scraping; text mining; sentiment analysis
    Scope: 1 Online-Ressource (circa 55 Seiten), Illustrationen
  4. 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
  5. Artificial intelligence and high-skilled work
    evidence from analysts
    Author: Grennan, Jillian; Michaely, Roni
    Published: 2020
    Publisher:  Swiss Finance Institute, Geneva

    Policymakers fear artificial intelligence (AI) will disrupt labor markets, especially for high-skilled workers. We investigate this concern using novel, task-specific data for security analysts. Exploiting variation in AI's power across stocks, we... more

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    Policymakers fear artificial intelligence (AI) will disrupt labor markets, especially for high-skilled workers. We investigate this concern using novel, task-specific data for security analysts. Exploiting variation in AI's power across stocks, we show analysts with portfolios that are more exposed to AI are more likely to reallocate efforts to soft skills, shift coverage towards low AI stocks, and even leave the profession. Analyst departures disproportionately occur among highly accurate analysts, leaving for non-research jobs. Reallocating efforts toward tasks that rely on social skills improve consensus forecasts. However, increased exposure to AI reduces the novelty in analysts' research which reduces compensation

     
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    Series: Research paper series / Swiss Finance Institute ; no 20, 84
    Swiss Finance Institute Research Paper ; No. 20-84
    Subjects: arti cial intelligence; big data; technology; automation; sell-side analysts; job displacement; labor and nance; social skills; non-cognitive skills; tasks; skill premium; skill-biased technological change; compensation
    Scope: 1 Online-Ressource (circa 74 Seiten), Illustrationen
  6. Attributing U.S. campylobacteriosis cases to food sources, season, and temperature
    Author: Hoffmann, Sandra; Ashton, Lydia; Todd, Jessica E.; Ahn, Jae-wan; Berck, Peter
    Published: February 2021
    Publisher:  United States Department of Agriculture, Economic Research Service, Washington, DC

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    Series: Economic research report ; number 284 (February 2021)
    Subjects: Campylobacter; food source attribution; foodborne illness; big data; FoodNet surveillance; Homescan© purchase data; food exposures; foodborne disease epidemiology; food safety; poultry exposure; berries; leafy greens
    Scope: 1 Online-Ressource (circa 56 Seiten), Illustrationen
  7. Big data and machine learning in central banking
    Author: Dörr, Sebastian; Gambacorta, Leonardo; Serena, José María
    Published: 2021
    Publisher:  Bank for International Settlements, Monetary and Economic Department, [Basel]

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    Series: BIS working papers ; no 930 (March 2021)
    Subjects: big data; central banks; machine learning; artificial intelligence; data science
    Scope: 1 Online-Ressource (circa 26 Seiten), Illustrationen
  8. Big data in Asian central banks
    Author: Cornelli, Giulio; Dörr, Sebastian; Gambacorta, Leonardo; Tissot, Bruno
    Published: February 2022
    Publisher:  Irving Fisher Committee on Central Bank Statistics, Bank for International Settlements, Basel

    This paper reviews the use of big data in Asian central banks, leveraging on a survey conducted among the members of the Irving Fisher Committee. The analysis reveals four main insights. First, Asian central banks define big data in a more... more

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    This paper reviews the use of big data in Asian central banks, leveraging on a survey conducted among the members of the Irving Fisher Committee. The analysis reveals four main insights. First, Asian central banks define big data in a more encompassing way that includes unstructured non-traditional as well as structured data sets. Second, interest in big data appears higher in Asia, including at the senior policy level; the focus is in particular on projects developed to process natural language, conduct nowcasting/monitoring exercises, and develop applications to extract economy insights as well as suptech/regtech solutions. Third, Asian central banks report dealing with big data to support a wide range of tasks. Fourth, big data poses new challenges, with specific attention paid in the region to cyber security and data strategy. As a result, there is a growing need for international policy cooperation, especially among public authorities in Asia to facilitate the use of payments data and promote innovative technological solutions.

     
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    Media type: Ebook
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    ISBN: 9789292595333
    Series: IFC working papers ; no 21
    Subjects: Asian central banks; artificial intelligence; big data; data science; international cooperation
    Scope: 1 Online-Ressource (circa 21 Seiten), Illustrationen
  9. Big tech, cloud computing, and accounting
    Author: Schoenfeld, Jordan
    Published: [2021]
    Publisher:  Tuck School of Business at Dartmouth], [Hanover, NH

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    Series: [Tuck School of Business working paper ; no. 3596065]
    Subjects: Audit; big data; financial accounting; internal control; technology
    Scope: 1 Online-Ressource (circa 54 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. Compiling granular population data using geospatial information
    Author: Mitterling, Thomas; Fenz, Katharina; Martinez, Arturo; Bulan, Joseph; Addawe, Mildred; Durante, Ron Lester; Martillan, Marymell
    Published: [2021]
    Publisher:  Asian Development Bank, Metro Manila, Philippines

    Granular spatial information on the distributions of human population is relevant to a variety of fields like health, economics, and other areas of public sector planning. This paper applies ensemble methods and aims at assessing their applicability... more

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    Granular spatial information on the distributions of human population is relevant to a variety of fields like health, economics, and other areas of public sector planning. This paper applies ensemble methods and aims at assessing their applicability to analyzing and forecasting population density on a grid level. In a first step, we use a Random Forest approach to estimate population density in the Philippines and Thailand on a 100 meter by 100-meter level. Second, we use different specifications of Random Forest and Bayesian model averaging techniques to create forecasts of the grid-level population density in three Thailand provinces and evaluate their predictive power.

     
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    hdl: 10419/259481
    Series: ADB economics working paper series ; no. 643 (December 2021)
    Subjects: population mapping; big data; random forest estimation; Philippines; Thailand
    Scope: 1 Online-Ressource (circa 31 Seiten), Illustrationen
  12. Creating data from unstructured text with Context Rule Assisted Machine Learning (CRAML)
    Author: Meisenbacher, Stephen; Norlander, Peter
    Published: 2022
    Publisher:  Global Labor Organization (GLO), Essen

    Popular approaches to building data from unstructured text come with limitations, such as scalability, interpretability, replicability, and real-world applicability. These can be overcome with Context Rule Assisted Machine Learning (CRAML), a method... more

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    Popular approaches to building data from unstructured text come with limitations, such as scalability, interpretability, replicability, and real-world applicability. These can be overcome with Context Rule Assisted Machine Learning (CRAML), a method and no-code suite of software tools that builds structured, labeled datasets which are accurate and reproducible. CRAML enables domain experts to access uncommon constructs within a document corpus in a low-resource, transparent, and flexible manner. CRAML produces document-level datasets for quantitative research and makes qualitative classification schemes scalable over large volumes of text. We demonstrate that the method is useful for bibliographic analysis, transparent analysis of proprietary data, and expert classification of any documents with any scheme. To demonstrate this process for building data from text with Machine Learning, we publish open-source resources: the software, a new public document corpus, and a replicable analysis to build an interpretable classifier of suspected "no poach" clauses in franchise documents.

     
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    hdl: 10419/267553
    Series: GLO discussion paper ; no. 1214
    Subjects: machine learning; natural language processing; text classification; big data
    Scope: 1 Online-Ressource (circa 56 Seiten), Illustrationen
  13. Cultural homophily and collaboration in superstar teams
    Author: Békés, Gábor; Ottaviano, Gianmarco I. P.
    Published: [2022]
    Publisher:  Centre for Economic Performance, London School of Economics and Political Science, London

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    Series: Discussion paper / Centre for Economic Performance ; no. 1873 (October 2022)
    Subjects: organizations; teams; culture; homophily; diversity; language; globalization; big data; panel data; sport
    Scope: 1 Online-Ressource (circa 48 Seiten), Illustrationen
  14. Decoding China's Covid-19 "virus exceptionalism"
    community-based digital contact tracing in Wuhan
    Author: Boeing, Philipp; Wang, Yihan
    Published: 2021
    Publisher:  ZEW - Leibniz Centre for European Economic Research, Mannheim, Germany

    During the COVID-19 pandemic, comprehensive, accurate, and timely digital contact tracing serves as a decisive measure in curbing viral transmission. Such a strategy integrates corporate innovation, government decision-making, citizen participation,... more

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    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
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    Universitätsbibliothek Mannheim
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    During the COVID-19 pandemic, comprehensive, accurate, and timely digital contact tracing serves as a decisive measure in curbing viral transmission. Such a strategy integrates corporate innovation, government decision-making, citizen participation, and community coordination with big data analytics. This article explores how key stakeholders in an open innovation ecosystem interact within the digital context to overcome challenges to public health and socio-economic welfare imposed by the pandemic. To enhance the digital contact tracing effectiveness, communities are deployed to moderate the interactions between government, enterprises and citizens. As an example, we study the community-based digital contact tracing in Wuhan, a representative case of China’s ‘virus exceptionalism’ in COVID-19 mitigation. We discuss the effectiveness of this strategy and raise critical ethical concerns regarding decision-making in R&D management.

     
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    hdl: 10419/232942
    Series: Discussion paper / ZEW ; no. 21, 028 (03/2021)
    Subjects: COVID-19; digital contact tracing; open innovation ecosystem; community; big data
    Scope: 1 Online-Ressource (28 Seiten), Illustrationen
  15. Demand estimation using managerial responses to automated price recommendations
    Author: García, Daniel; Tolvanen, Juha; Wagner, Alexander K.
    Published: June 2021
    Publisher:  CESifo, Center for Economic Studies & Ifo Institute, Munich, Germany

    We provide a new framework to identify demand elasticities in markets where managers rely on algorithmic recommendations for price setting, and apply it to a dataset containing bookings for a sample of mid-sized hotels in Europe. Using non-binding... more

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    We provide a new framework to identify demand elasticities in markets where managers rely on algorithmic recommendations for price setting, and apply it to a dataset containing bookings for a sample of mid-sized hotels in Europe. Using non-binding algorithmic price recommendations and observed delay in price adjustments by decision makers, we demonstrate that a control-function approach, combined with state-of-the-art model selection techniques, can be used to isolate exogenous price variation and identify demand elasticities across hotel room types and over time. We confirm these elasticity estimates with a difference-in-differences approach that leverages the same delays in price adjustments by decision makers. However, the difference-in-differences estimates are more noisy and only yield consistent estimates if data is pooled across hotels. We then apply our control-function approach to two classic questions in the dynamic pricing literature: the evolution of price elasticity of demand over time as well as the effects of a transitory price change on future demand due to the presence of strategic buyers. Finally, we discuss how our empirical framework can be applied directly to other decision-making situations in which recommendation systems are used.

     
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    hdl: 10419/236669
    Series: CESifo working paper ; no. 9127 (2021)
    Subjects: big data; causal inference; machine learning; revenue management; price recommendations; demand estimation
    Scope: 1 Online-Ressource (circa 59 Seiten), Illustrationen
  16. 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
  17. 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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  18. 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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  19. Does online search improve the match quality of new hires?
    Author: Gürtzgen, Nicole; Lochner, Benjamin; Pohlan, Laura; Berg, Gerard J. van den
    Published: February 17, 2021
    Publisher:  Institute for Employment Research of the Federal Employment Agency, Nürnberg

    This paper studies the effects of the high-speed internet expansion on the match quality of new hires. We combine data on internet availability at the local level with German individual register and vacancy data. Results show that internet... more

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    This paper studies the effects of the high-speed internet expansion on the match quality of new hires. We combine data on internet availability at the local level with German individual register and vacancy data. Results show that internet availability has no major impact on the stability of new matches and their wages. We confirm these findings using vacancy data, by explicitly comparing match outcomes of online and non-online recruits. Further results show that online recruiting not only raises the number of applicants and the share of unsuitable candidates per vacancy, but also induces employers to post more vacancies. Die Studie untersucht den Effekt der Expansion des Breitbandinternets auf die Matchqualität neu eingestellter Personen. Hierzu werden Daten zur regionalen Internetverfügbarkeit mit administrativen Individualdaten und Vakanzdaten für den deutschen Arbeitsmarkt kombiniert. Die Ergebnisse zeigen, dass eine Ausweitung der Breitbandinternet-Verfügbarkeit keinen größeren Einfluss auf die Stabilität und Entlohnung neu begonnener Beschäftigungsverhältnisse hat. Diese Resultate werden auf Basis von Analysen mit Vakanzdaten bestätigt. Diese Daten erlauben einen expliziten Vergleich der Matchqualität von Personen, die online rekrutiert wurden, mit der Matchqualität von Personen, die über andere Rekrutierungskanäle eingestellt wurden. Weiterhin zeigen die Ergebnisse, dass Online-Rekrutierung nicht nur die Anzahl der Bewerbungen und den Anteil ungeeigneter Bewerbungen erhöht, sondern ebenfalls zu einer höheren Anzahl von Vakanzen führt.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/234297
    Series: IAB-discussion paper ; 2021, 2
    Subjects: big data; labour market search intensity; matching function; online activity
    Scope: 1 Online-Ressource (circa 67 Seiten), Illustrationen
  20. Dynamic Competition in Deceptive Markets
    Author: Johnen, Johannes
    Published: [2018]
    Publisher:  CORE, [Louvain-la-Neuve]

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    VS 203
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    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
  21. 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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    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
  22. 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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    VS 65 (2015.012)
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    Language: English
    Media type: Book
    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.
  23. Forecasting oil prices
    can large BVARs help?
    Author: Bao Hoang Nguyen; Zhang, Bo
    Published: [2022]
    Publisher:  Australian National University, Crawford School of Public Policy, Canberra

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    Language: English
    Media type: Book
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    Series: CAMA working paper series ; 2022, 65 (October 2022)
    Subjects: forecasting; non-Gaussian; stochastic volatility; oil prices; big data
    Scope: 1 Online-Ressource (circa 31 Seiten), Illustrationen
  24. Forecasting oil prices
    can large BVARs help?
    Author: Nguyen, Bao; Zhang, Bo
    Published: [2022]
    Publisher:  University of Tasmania, [Hobart, Tasmania]

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    Source: Union catalogues
    Language: English
    Media type: Ebook
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    ISBN: 9781922708380
    Series: Discussion paper series / Tasmanian School of Business and Economics, University of Tasmania ; N 2022, 04
    Subjects: forecasting; non-Gaussian; stochastic volatility; oil prices; big data
    Scope: 1 Online-Ressource (circa 26 Seiten)
  25. Forecasting world trade using big data and machine learning techniques
    Author: Dubovik, Andrei; Elbourne, Adam; Hendriks, Bram; Kattenberg, Mark
    Published: October 2022
    Publisher:  CPB Netherlands Bureau for Economic Policy Analysis, [Den Haag]

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    Language: English
    Media type: Book
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    Series: CPB discussion paper
    Subjects: world trade; forecasting; big data; machine learning; largeBVAR
    Scope: 1 Online-Ressource