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Nikos Askitas

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Askitas, Nikos & Zimmermann, Klaus F., 2009. "Google Econometrics and Unemployment Forecasting," IZA Discussion Papers 4201, Institute of Labor Economics (IZA).

    Mentioned in:

    1. Measuring unemployment with Google
      by Economic Logician in Economic Logic on 2009-07-01 13:02:00

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Askitas, Nikos & Tatsiramos, Konstantinos & Verheyden, Bertrand, 2020. "Lockdown Strategies, Mobility Patterns and COVID-19," IZA Discussion Papers 13293, Institute of Labor Economics (IZA).

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health > Distancing and Lockdown > Measurement and effect on mobility

Working papers

  1. Nikos Askitas & Konstantinos Tatsiramos & Bertrand Verheyden, 2020. "Lockdown Strategies, Mobility Patterns and COVID-19," Papers 2006.00531, arXiv.org.

    Cited by:

    1. Davillas, Apostolos & Burdett, Ashley & Etheridge, Ben, 2021. "Weather, psychological wellbeing and mobility during the first wave of the Covid-19 pandemic," ISER Working Paper Series 2021-02, Institute for Social and Economic Research.
    2. Kim, Kijin & Kim, Soyoung & Lee, Donghyun & Park, Cyn-Young, 2022. "Impacts of Social Distancing Policy and Vaccination During the COVID-19 Pandemic in the Republic of Korea," ADB Economics Working Paper Series 658, Asian Development Bank.
    3. Bargain, Olivier B. & Aminjonov, Ulugbek, 2020. "Trust and Compliance to Public Health Policies in Times of COVID-19," IZA Discussion Papers 13205, Institute of Labor Economics (IZA).
    4. Echaniz, Eneko & Rodríguez, Andrés & Cordera, Rubén & Benavente, Juan & Alonso, Borja & Sañudo, Roberto, 2021. "Behavioural changes in transport and future repercussions of the COVID-19 outbreak in Spain," Transport Policy, Elsevier, vol. 111(C), pages 38-52.
    5. Scherf, Matthias & Matschke, Xenia & Rieger, Marc Oliver, 2022. "Stock market reactions to COVID-19 lockdown: A global analysis," Finance Research Letters, Elsevier, vol. 45(C).
    6. Rajeev K. Goel & Michael A. Nelson, 2023. "Aggressive COVID‐19 lockdown policies: What factors significantly drove them across nations?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 2211-2222, June.
    7. Massimiliano Ferraresi & Christos Kotsogiannis & Leonzio Rizzo & Riccardo Secomandi, 2020. "The ‘Great Lockdown’ and its Determinants," Working papers 91, Società Italiana di Economia Pubblica.
    8. Andrew G. Atkeson & Karen A. Kopecky & Tao Zha, 2024. "Four Stylized Facts About Covid‐19," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(1), pages 3-42, February.
    9. Kefan Xie & Benbu Liang & Maxim A. Dulebenets & Yanlan Mei, 2020. "The Impact of Risk Perception on Social Distancing during the COVID-19 Pandemic in China," IJERPH, MDPI, vol. 17(17), pages 1-17, August.
    10. Matthew Spiegel & Heather Tookes, 2022. "All or nothing? Partial business shutdowns and COVID-19 fatality growth," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-15, February.
    11. Guangyue Nian & Bozhezi Peng & Daniel (Jian) Sun & Wenjun Ma & Bo Peng & Tianyuan Huang, 2020. "Impact of COVID-19 on Urban Mobility during Post-Epidemic Period in Megacities: From the Perspectives of Taxi Travel and Social Vitality," Sustainability, MDPI, vol. 12(19), pages 1-29, September.
    12. Chakwizira, James, 2022. "Stretching resilience and adaptive transport systems capacity in South Africa: Imperfect or perfect attempts at closing COVID -19 policy and planning emergent gaps," Transport Policy, Elsevier, vol. 125(C), pages 127-150.
    13. Eckardt, Matthias & Kappner, Kalle & Wolf, Nikolaus, 2020. "Covid-19 across European Regions: the Role of Border Controls," CAGE Online Working Paper Series 507, Competitive Advantage in the Global Economy (CAGE).
    14. Laura Coroneo & Fabrizio Iacone, 2024. "Testing for equal predictive accuracy with strong dependence," Papers 2409.12662, arXiv.org.
    15. Majerčák Jozef & Vakulenko Sergej Petrovich, 2023. "The Impact of COVID-19 Pandemic on Population Mobility in the Czech Republic and Slovakia," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 14(1), pages 158-168, January.
    16. Martin Huber & Henrika Langen, 2020. "Timing matters: the impact of response measures on COVID-19-related hospitalization and death rates in Germany and Switzerland," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-19, December.
    17. Gonzalo Castex & Evgenia Dechter & Miguel Lorca, 2021. "COVID-19: The impact of social distancing policies, cross-country analysis," Economics of Disasters and Climate Change, Springer, vol. 5(1), pages 135-159, April.
    18. Cristina PRUND, 2020. "The Abrupt Fall Of The Labor Market: The Case Of The European Labor Market And The Impact Generated By Covid-19," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 14(1), pages 722-730, November.
    19. Veronika Harantová & Ambróz Hájnik & Alica Kalašová & Tomasz Figlus, 2022. "The Effect of the COVID-19 Pandemic on Traffic Flow Characteristics, Emissions Production and Fuel Consumption at a Selected Intersection in Slovakia," Energies, MDPI, vol. 15(6), pages 1-21, March.
    20. Matthew Spiegel & Heather Tookes, 2021. "Business Restrictions and COVID-19 Fatalities [The immediate effect of COVID-19 policies on social distancing behavior in the United States]," The Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5266-5308.
    21. Fakhar Shahzad & Jianguo Du & Imran Khan & Zeeshan Ahmad & Muhammad Shahbaz, 2021. "Untying the Precise Impact of COVID-19 Policy on Social Distancing Behavior," IJERPH, MDPI, vol. 18(3), pages 1-12, January.
    22. Patricio Goldstein & Eduardo Levy Yeyati & Luca Sartorio, 2021. "Lockdown fatigue: The diminishing effects of quarantines on the spread of COVID-19," Working Papers 35, Red Nacional de Investigadores en Economía (RedNIE).
    23. Hayakawa, Kazunobu & Keola, Souknilanh, 2021. "How is the Asian economy recovering from COVID-19? Evidence from the emissions of air pollutants," Journal of Asian Economics, Elsevier, vol. 77(C).
    24. Masagus M. Ridhwan & Jahen F. Rezki & Asep Suryahadi & Arief Ramayandi, 2021. "A The Impact Of Covid-19 Lockdowns On Household Income, Consumption, And Expectation: Evidence From High," Working Papers WP/07/2021, Bank Indonesia.
    25. Hayakawa, Kazunobu & Mukunoki, Hiroshi, 2021. "The impact of COVID-19 on international trade: Evidence from the first shock," Journal of the Japanese and International Economies, Elsevier, vol. 60(C).
    26. Islamaj,Ergys & Le,Duong Trung & Mattoo,Aaditya, 2021. "Lives versus Livelihoods during the COVID-19 Pandemic : How Testing Softens the Trade-off," Policy Research Working Paper Series 9696, The World Bank.
    27. Eisenmann, Christine & Nobis, Claudia & Kolarova, Viktoriya & Lenz, Barbara & Winkler, Christian, 2021. "Transport mode use during the COVID-19 lockdown period in Germany: The car became more important, public transport lost ground," Transport Policy, Elsevier, vol. 103(C), pages 60-67.
    28. Hayakawa, Kazunobu & Keola, Souknilanh & Urata, Shujiro, 2022. "How effective was the restaurant restraining order against COVID-19? A nighttime light study in Japan," Japan and the World Economy, Elsevier, vol. 63(C).
    29. Michał Wielechowski & Katarzyna Czech & Łukasz Grzęda, 2020. "Decline in Mobility: Public Transport in Poland in the time of the COVID-19 Pandemic," Economies, MDPI, vol. 8(4), pages 1-24, September.
    30. De Simone Elina & Mourao Paulo Reis, 2021. "What determines governments’ response time to COVID-19? A cross-country inquiry on the measure restricting internal movements," Open Economics, De Gruyter, vol. 4(1), pages 106-117, January.
    31. Ferraresi, Massimiliano & Kotsogiannis, Christos & Rizzo, Leonzio & Secomandi, Riccardo, 2020. "The ‘Great Lockdown’ and its determinants," Economics Letters, Elsevier, vol. 197(C).
    32. Etienne Farvaque & Hira Iqbal & Nicolas Ooghe, 2020. "Health politics? Determinants of US states’ reactions to COVID-19," Post-Print hal-03128875, HAL.
    33. Sparks, Kevin & Moehl, Jessica & Weber, Eric & Brelsford, Christa & Rose, Amy, 2022. "Shifting temporal dynamics of human mobility in the United States," Journal of Transport Geography, Elsevier, vol. 99(C).
    34. Souknilanh Keola & Kazunobu Hayakawa, 2021. "Do Lockdown Policies Reduce Economic and Social Activities? Evidence from NO2 Emissions," The Developing Economies, Institute of Developing Economies, vol. 59(2), pages 178-205, June.
    35. Donny Pasaribu & Deasy Pane & Yudi Suwarna, 2021. "How Do Sectoral Employment Structures Affect Mobility during the COVID-19 Pandemic?," Working Papers DP-2021-13, Economic Research Institute for ASEAN and East Asia (ERIA).
    36. Koopmans, Ruud, 2020. "A virus that knows no borders? Exposure to and restrictions of international travel and the global diffusion of COVID-19," Discussion Papers, Research Unit: Migration, Integration, Transnationalization SP VI 2020-103, WZB Berlin Social Science Center.
    37. Bracarense, Lílian dos Santos Fontes Pereira & Oliveira, Renata Lúcia Magalhães de, 2021. "Access to urban activities during the Covid-19 pandemic and impacts on urban mobility: The Brazilian context," Transport Policy, Elsevier, vol. 110(C), pages 98-111.
    38. Artís, Annalí Casanueva & Avetian, Vladimir & Sardoschau, Sulin & Saxena, Kavya, 2022. "Social Media and the Broadening of Social Movements: Evidence from Black Lives Matter," IZA Discussion Papers 15812, Institute of Labor Economics (IZA).
    39. Yuksel, Mutlu & Aydede, Yigit & Begolli, Francisko, 2020. "Dynamics of Social Mobility during the COVID-19 Pandemic in Canada," IZA Discussion Papers 13376, Institute of Labor Economics (IZA).
    40. Daniel L. Millimet & Christopher F. Parmeter, 2022. "COVID‐19 severity: A new approach to quantifying global cases and deaths," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1178-1215, July.
    41. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).

  2. Askitas, Nikos & Eichhorst, Werner & Fahrenholtz, Benedikt & Meys, Nicolas & Ody, Margard, 2018. "Industrial Relations and Social Dialogue in the Age of Collaborative Economy (IRSDACE)," IZA Research Reports 86, Institute of Labor Economics (IZA).

    Cited by:

    1. Keller, Berndt, 2020. "Interest representation and industrial relations in the age of digitalization ‒ an outline [Interessenvertretung und Arbeitsbeziehungen im Zeitalter der Digitalisierung - ein Überblick]," Industrielle Beziehungen. Zeitschrift für Arbeit, Organisation und Management, Verlag Barbara Budrich, vol. 27(3), pages 255-285.

  3. Askitas, Nikos, 2016. "Big Data Is a Big Deal But How Much Data Do We Need?," IZA Discussion Papers 9988, Institute of Labor Economics (IZA).

    Cited by:

    1. Ralf Thomas Münnich & Markus Zwick, 2016. "Big Data und was nun? Neue Datenbestände und ihre Auswirkungen," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(2), pages 73-77, October.
    2. Engels, Barbara, 2016. "Big-Data-Analyse: Ein Einstieg für Ökonomen," IW-Kurzberichte 78.2016, Institut der deutschen Wirtschaft (IW) / German Economic Institute.

  4. Askitas, Nikos, 2015. "Calling the Greek Referendum on the Nose with Google Trends," IZA Discussion Papers 9569, Institute of Labor Economics (IZA).

    Cited by:

    1. Gutiérrez, Antonio, 2023. "La brecha de género en el emprendimiento y la cultura emprendedora: Evidencia con Google Trends [Entrepreneurship gender gap and entrepreneurial culture: Evidence from Google Trends]," MPRA Paper 115876, University Library of Munich, Germany.
    2. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
    3. Askitas, Nikos, 2015. "Trend-Spotting in the Housing Market," IZA Discussion Papers 9427, Institute of Labor Economics (IZA).
    4. Francisco Vergara-Perucich, 2022. "Assessing the Accuracy of Google Trends for Predicting Presidential Elections: The Case of Chile, 2006–2021," Data, MDPI, vol. 7(11), pages 1-12, October.
    5. Nikos Askitas & Anoop Bindra Martinez & Fabio Saia Cereda & Nikolaos Askitas, 2024. "The IZA / Fable Swipe Consumption Index," CESifo Working Paper Series 11389, CESifo.
    6. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
    7. Fabo, B., 2017. "Towards an understanding of job matching using web data," Other publications TiSEM b8b877f2-ae6a-495f-b6cc-9, Tilburg University, School of Economics and Management.

  5. Askitas, Nikos, 2015. "Predicting Road Conditions with Internet Search," IZA Discussion Papers 9503, Institute of Labor Economics (IZA).

    Cited by:

    1. Nikos Askitas & Anoop Bindra Martinez & Fabio Saia Cereda & Nikolaos Askitas, 2024. "The IZA / Fable Swipe Consumption Index," CESifo Working Paper Series 11389, CESifo.

  6. Askitas, Nikos, 2015. "Predicting the Irish "Gay Marriage" Referendum," IZA Discussion Papers 9570, Institute of Labor Economics (IZA).

    Cited by:

    1. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.

  7. Askitas, Nikos, 2015. "Trend-Spotting in the Housing Market," IZA Discussion Papers 9427, Institute of Labor Economics (IZA).

    Cited by:

    1. Jean-Charles Bricongne & Baptiste Meunier & Sylvain Pouget, 2023. "Web-scraping housing prices in real-time: The Covid-19 crisis in the UK," SciencePo Working papers Main hal-04064185, HAL.
    2. David Coble & Pablo Pincheira, 2021. "Forecasting building permits with Google Trends," Empirical Economics, Springer, vol. 61(6), pages 3315-3345, December.
    3. Fabo, B., 2017. "Towards an understanding of job matching using web data," Other publications TiSEM b8b877f2-ae6a-495f-b6cc-9, Tilburg University, School of Economics and Management.
    4. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.

  8. Askitas, Nikos & Zimmermann, Klaus F., 2015. "The Internet as a Data Source for Advancement in Social Sciences," IZA Discussion Papers 8899, Institute of Labor Economics (IZA).

    Cited by:

    1. Luca Bonacini & Giovanni Gallo & Fabrizio Patriarca, 2021. "Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 275-301, January.
    2. Joana M. Barros & Ruth Melia & Kady Francis & John Bogue & Mary O’Sullivan & Karen Young & Rebecca A. Bernert & Dietrich Rebholz-Schuhmann & Jim Duggan, 2019. "The Validity of Google Trends Search Volumes for Behavioral Forecasting of National Suicide Rates in Ireland," IJERPH, MDPI, vol. 16(17), pages 1-18, September.
    3. Nwaobi, Godwin, 2019. "University Postgraduate Research Programmes: Digitization(ICT),Innovations and Applications," MPRA Paper 96730, University Library of Munich, Germany.
    4. van der Wielen, Wouter & Barrios, Salvador, 2021. "Economic sentiment during the COVID pandemic: Evidence from search behaviour in the EU," Journal of Economics and Business, Elsevier, vol. 115(C).
    5. Karolien Lenaerts & Miroslav Beblavý & Brian Fabo, 2016. "Prospects for utilisation of non-vacancy Internet data in labour market analysis—an overview," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-18, December.
    6. Mihai Mutascu & Florian Horky & Cristina Strango, 2023. "Good or bad? Digitalisation and green preferences," Post-Print hal-04180154, HAL.
    7. Rui Wang & Jing Kang, 2024. "Financial Interconnectedness and Bank Risk-Taking: Evidence from China," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 11819-11847, September.
    8. Francesco D'Amuri & Juri Marcucci, 2012. "The predictive power of Google searches in forecasting unemployment," Temi di discussione (Economic working papers) 891, Bank of Italy, Economic Research and International Relations Area.
    9. Alessia Naccarato & Andrea Pierini & Stefano Falorsi, 2015. "Using Google Trend Data To Predict The Italian Unemployment Rate," Departmental Working Papers of Economics - University 'Roma Tre' 0203, Department of Economics - University Roma Tre.
    10. Stefano Visintin & Kea Tijdens & Maarten van Klaveren, 2015. "Skill mismatch among migrant workers: evidence from a large multi-country dataset," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-34, December.
    11. Florin Paul Costel LILEA & Alexandru MANOLE & Maria MIREA & Andreea - Ioana MARINESCU, 2017. "Models Of Development Of Labour Productivity Forecast," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(4), pages 107-114, April.
    12. Pietro Giorgio Lovaglio & Mario Mezzanzanica & Emilio Colombo, 2020. "Comparing time series characteristics of official and web job vacancy data," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 85-98, February.
    13. Camélia TURCU & Mihai MUTASCU & Albert LESSOUA, 2020. "Firms’ Performance and Exports: The Case of Romanian Winemakers," LEO Working Papers / DR LEO 2747, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    14. Jyldyz Djumalieva & Antonio Lima & Cath Sleeman, 2018. "Classifying Occupations According to Their Skill Requirements in Job Advertisements," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-04, Economic Statistics Centre of Excellence (ESCoE).
    15. Raymundo M. Campos-Vázquez & Julio César Martínez Sánchez, 2024. "Habilidades buscadas por las empresas en el mercado laboral mexicano: un análisis de las ofertas laborales publicadas en internet/Skills sought by companies in the Mexican labor market: An analysis o," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 39(2), pages 243–278-2.
    16. Lucia Kureková & Miroslav Beblavý & Anna Thum-Thysen, 2015. "Using online vacancies and web surveys to analyse the labour market: a methodological inquiry," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-20, December.
    17. Ahood Almaleh & Muhammad Ahtisham Aslam & Kawther Saeedi & Naif Radi Aljohani, 2019. "Align My Curriculum: A Framework to Bridge the Gap between Acquired University Curriculum and Required Market Skills," Sustainability, MDPI, vol. 11(9), pages 1-13, May.
    18. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    19. Michael Weinhardt, 2021. "Big Data: Some Ethical Concerns for the Social Sciences," Social Sciences, MDPI, vol. 10(2), pages 1-14, January.
    20. Kureková, Lucia Mýtna & Žilin?íková, Zuzana, 2015. "Low-Skilled Jobs and Student Jobs: Employers' Preferences in Slovakia and the Czech Republic," IZA Discussion Papers 9145, Institute of Labor Economics (IZA).
    21. Fabio Milani, 2020. "Covid-19 Outbreak, Social Response, and Early Economic Effects: A Global VAR Analysis of Cross-Country Interdependencies," CESifo Working Paper Series 8518, CESifo.
    22. Asgari, Mahdi & Nemati, Mehdi & Zheng, Yuqing, 2018. "Nowcasting Food Stock Movement using Food Safety Related Web Search Queries," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266323, Southern Agricultural Economics Association.
    23. Yuan Zhou & Fang Dong & Yufei Liu & Liang Ran, 2021. "A deep learning framework to early identify emerging technologies in large-scale outlier patents: an empirical study of CNC machine tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 969-994, February.
    24. Nikolaos Askitas, 2016. "Big Data is a big deal but how much data do we need? [Big Data gut und schön. Aber wie viel Data brauchen wir?]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(2), pages 113-125, October.
    25. Brian Fabo & Martin Kahanec, 2020. "The Role of Computer Skills on the Occupation Level," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 6(2), pages 87-99.
    26. Jan Kinne & Janna Axenbeck, 2020. "Web mining for innovation ecosystem mapping: a framework and a large-scale pilot study," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2011-2041, December.
    27. Jan Drahokoupil & Brian Fabo, 2019. "The limits of foreign-led growth: Demand for digital skills by foreign and domestic firms in Slovakia," Working and Discussion Papers WP 7/2019, Research Department, National Bank of Slovakia.
    28. Beblavý, Miroslav & Fabo, Brian & Lenaerts, Karolien, 2016. "Skills Requirements for the 30 Most-Frequently Advertised Occupations in the United States: An analysis based on online vacancy data," CEPS Papers 11406, Centre for European Policy Studies.
    29. Naccarato, Alessia & Falorsi, Stefano & Loriga, Silvia & Pierini, Andrea, 2018. "Combining official and Google Trends data to forecast the Italian youth unemployment rate," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 114-122.
    30. Nikos Askitas & Anoop Bindra Martinez & Fabio Saia Cereda & Nikolaos Askitas, 2024. "The IZA / Fable Swipe Consumption Index," CESifo Working Paper Series 11389, CESifo.
    31. Beblavý, Miroslav & Fabo, Brian & Lenaerts, Karolien, 2016. "The Importance of Foreign Language Skills in the Labour Markets of Central and Eastern Europe: An assessment based on data from online job portals," CEPS Papers 11264, Centre for European Policy Studies.
    32. Kureková, Lucia Mýtna & Žilin?íková, Zuzana, 2016. "What is the Value of Foreign Work Experience? Analysing Online CV Data in Slovakia," IZA Discussion Papers 9921, Institute of Labor Economics (IZA).
    33. Albert Lessoua & Mihai Mutascu & Camélia Turcu, 2018. "Financial performance and exports: the case of Romanian winemakers," Working Papers 2018.07, International Network for Economic Research - INFER.
    34. Javier Sebastian, 2016. "Blockchain in financial services: Regulatory landscape and future challenges," Working Papers 16/21, BBVA Bank, Economic Research Department.
    35. Fabo, B., 2017. "Towards an understanding of job matching using web data," Other publications TiSEM b8b877f2-ae6a-495f-b6cc-9, Tilburg University, School of Economics and Management.
    36. Simionescu, Mihaela & Cifuentes-Faura, Javier, 2022. "Can unemployment forecasts based on Google Trends help government design better policies? An investigation based on Spain and Portugal," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 1-21.
    37. Jan Drahokoupil & Brian Fabo, 2022. "The limits of foreign-led growth: Demand for skills by foreign and domestic firms," Review of International Political Economy, Taylor & Francis Journals, vol. 29(1), pages 152-174, January.
    38. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
    39. Lucia Mýtna Kureková & Zuzana Žilinčíková, 2016. "Are student jobs flexible jobs? Using online data to study employers’ preferences in Slovakia," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-14, December.
    40. Stefano Visintin & Kea Tijdens & Stephanie Steinmetz & Pablo de Pedraza, 2015. "Task implementation heterogeneity and wage dispersion," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-24, December.

  9. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Health and Well-Being in the Crisis," IZA Discussion Papers 5601, Institute of Labor Economics (IZA).

    Cited by:

    1. Blanchflower, David G. & Oswald, Andrew J., 2011. "Antidepressants and Age," IZA Discussion Papers 5785, Institute of Labor Economics (IZA).
    2. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    3. Blanchflower, David G. & Oswald, Andrew J., 2016. "Antidepressants and age: A new form of evidence for U-shaped well-being through life," Journal of Economic Behavior & Organization, Elsevier, vol. 127(C), pages 46-58.
    4. Kronenberg, C. & Jacobs, R. & Zucchelli, E., 2015. "The impact of a wage increase on mental health: Evidence from the UK minimum wage," Health, Econometrics and Data Group (HEDG) Working Papers 15/08, HEDG, c/o Department of Economics, University of York.
    5. Frijters, P. & Johnston, D.W. & Lordan, G. & Shields, M., 2013. "Exploring the relationship between macroeconomic conditions and problem drinking as captured by Google searches in the US," Health, Econometrics and Data Group (HEDG) Working Papers 13/02, HEDG, c/o Department of Economics, University of York.
    6. Alberto Montagnoli & Mirko Moro, 2014. "Everybody Hurts: Banking Crises and Individual Wellbeing," Working Papers 2014010, The University of Sheffield, Department of Economics.
    7. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    8. Guzi, Martin & de Pedraza, Pablo, 2013. "A Web Survey Analysis of the Subjective Well-being of Spanish Workers," IZA Discussion Papers 7618, Institute of Labor Economics (IZA).
    9. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Detecting Mortgage Delinquencies," IZA Discussion Papers 5895, Institute of Labor Economics (IZA).
    10. Katolik, Aleksandra & Oswald, Andrew J., 2017. "Antidepressants for Economists and Business-School Researchers: An Introduction and Review," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 71(4), pages 448-463.
    11. Askitas, Nikos, 2015. "Calling the Greek Referendum on the Nose with Google Trends," IZA Discussion Papers 9569, Institute of Labor Economics (IZA).
    12. de Pedraza, Pablo & Vollbracht, Ian, 2020. "The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve," GLO Discussion Paper Series 515, Global Labor Organization (GLO).
    13. Daniel Farhat, 2017. "Awareness of Sexually Transmitted Disease and Economic Misfortune Using Search Engine Query Data," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 16(1), pages 101-108, June.
    14. Katolik, Aleksandra & Oswald, Andrew J., 2017. "Antidepressants for Economists and Business-School Researchers: An Introduction and Review," CAGE Online Working Paper Series 338, Competitive Advantage in the Global Economy (CAGE).

  10. Askitas, Nikos & Zimmermann, Klaus F., 2011. "The Toll Index: Innovation-based Economic Telemetry," IZA Policy Papers 31, Institute of Labor Economics (IZA).

    Cited by:

    1. Döhrn, Roland, 2013. "Transportation Data as a Tool for Nowcasting Economic Activity – The German Road Pricing System as an Example," Ruhr Economic Papers 395, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

  11. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Detecting Mortgage Delinquencies," IZA Discussion Papers 5895, Institute of Labor Economics (IZA).

    Cited by:

    1. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    2. Chiara L. Comolli & Daniele Vignoli, 2019. "Spread-ing uncertainty, shrinking birth rates," Econometrics Working Papers Archive 2019_08, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    3. Askitas, Nikos, 2015. "Trend-Spotting in the Housing Market," IZA Discussion Papers 9427, Institute of Labor Economics (IZA).
    4. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    5. Simon Oehler, 2019. "Developments in the residential mortgage market in Germany – what can Google data tell us?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
    6. Tang, Mengxuan & Hu, Yang & Corbet, Shaen & Hou, Yang (Greg) & Oxley, Les, 2024. "Fintech, bank diversification and liquidity: Evidence from China," Research in International Business and Finance, Elsevier, vol. 67(PA).
    7. Guzi, Martin & de Pedraza, Pablo, 2013. "A Web Survey Analysis of the Subjective Well-being of Spanish Workers," IZA Discussion Papers 7618, Institute of Labor Economics (IZA).
    8. de Pedraza, Pablo & Vollbracht, Ian, 2020. "The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve," GLO Discussion Paper Series 515, Global Labor Organization (GLO).
    9. David Coble & Pablo Pincheira, 2021. "Forecasting building permits with Google Trends," Empirical Economics, Springer, vol. 61(6), pages 3315-3345, December.
    10. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    11. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).

  12. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Nowcasting Business Cycles Using Toll Data," IZA Discussion Papers 5522, Institute of Labor Economics (IZA).

    Cited by:

    1. Jannsen, Nils, 2023. "Der Lkw-Maut-Fahrleistungsindex: Ein nützlicher Frühindikator für die Industrieproduktion," Kiel Insight 2023.02, Kiel Institute for the World Economy (IfW Kiel).
    2. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    3. Ademmer, Martin & Beckmann, Joscha & Bode, Eckhardt & Boysen-Hogrefe, Jens & Funke, Manuel & Hauber, Philipp & Heidland, Tobias & Hinz, Julian & Jannsen, Nils & Kooths, Stefan & Söder, Mareike & Stame, 2021. "Big Data in der makroökonomischen Analyse," Kieler Beiträge zur Wirtschaftspolitik 32, Kiel Institute for the World Economy (IfW Kiel).
    4. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2022. "Testing big data in a big crisis: Nowcasting under COVID-19," JRC Working Papers in Economics and Finance 2022-06, Joint Research Centre, European Commission.
    5. Döhrn, Roland, 2013. "Transportation Data as a Tool for Nowcasting Economic Activity – The German Road Pricing System as an Example," Ruhr Economic Papers 395, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    6. de Pedraza, Pablo & Vollbracht, Ian, 2020. "The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve," GLO Discussion Paper Series 515, Global Labor Organization (GLO).
    7. Nikos Askitas & Anoop Bindra Martinez & Fabio Saia Cereda & Nikolaos Askitas, 2024. "The IZA / Fable Swipe Consumption Index," CESifo Working Paper Series 11389, CESifo.
    8. Riccardo Corradini, 2019. "A Set of State–Space Models at a High Disaggregation Level to Forecast Italian Industrial Production," J, MDPI, vol. 2(4), pages 1-53, November.
    9. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
    10. Chew Lian Chua & Sarantis Tsiaplias & Ruining Zhou, 2024. "Constructing a high‐frequency World Economic Gauge using a mixed‐frequency dynamic factor model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2212-2227, September.
    11. Indaco, Agustín, 2020. "From twitter to GDP: Estimating economic activity from social media," Regional Science and Urban Economics, Elsevier, vol. 85(C).
    12. Boysen-Hogrefe, Jens & Groll, Dominik & Hoffmann, Timo & Jannsen, Nils & Kooths, Stefan & Sonnenberg, Nils & Stamer, Vincent, 2023. "Deutsche Wirtschaft im Frühjahr 2023: Konjunktur fängt sich, Auftriebskräfte eher gering [German economy in spring 2023: Economy is stabilizing but little momentum going forward]," Kieler Konjunkturberichte 101, Kiel Institute for the World Economy (IfW Kiel).
    13. Roland Döhrn & Sönke Maatsch, 2012. "Der RWI/ISL-Containerumschlag-Index," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 92(5), pages 352-354, May.
    14. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
    15. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    16. Selod,Harris & Soumahoro,Souleymane, 2020. "Big Data in Transportation : An Economics Perspective," Policy Research Working Paper Series 9308, The World Bank.

  13. Nikos Askitas, 2010. "What Makes Persistent Identifiers Persistent?," RatSWD Working Papers 147, German Data Forum (RatSWD).

    Cited by:

    1. Brigitte Hausstein, 2012. "Die Vergabe von DOI-Namen für Sozialund Wirtschaftsdaten Serviceleistungen der Registrierungsagentur da|ra," RatSWD Working Papers 193, German Data Forum (RatSWD).

  14. Nikos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Discussion Papers of DIW Berlin 899, DIW Berlin, German Institute for Economic Research.

    Cited by:

    1. Hantzsche, Arno, 2022. "Fiscal uncertainty and sovereign credit risk," European Economic Review, Elsevier, vol. 148(C).
    2. Gutiérrez, Antonio, 2023. "La brecha de género en el emprendimiento y la cultura emprendedora: Evidencia con Google Trends [Entrepreneurship gender gap and entrepreneurial culture: Evidence from Google Trends]," MPRA Paper 115876, University Library of Munich, Germany.
    3. Luca Bonacini & Giovanni Gallo & Fabrizio Patriarca, 2021. "Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 275-301, January.
    4. Chun Li & Jianhua He & Xingwu Duan, 2020. "The Relationship Exploration between Public Migration Attention and Population Migration from a Perspective of Search Query," IJERPH, MDPI, vol. 17(7), pages 1-18, April.
    5. David Iselin & Boriss Siliverstovs, 2013. "Mit Zeitungen Konjunkturprognosen erstellen: Eine Vergleichsstudie für die Schweiz und Deutschland," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 7(3), pages 104-117, September.
    6. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
    7. Pavlicek, Jaroslav & Kristoufek, Ladislav, 2015. "Nowcasting unemployment rates with Google searches: Evidence from the Visegrad Group countries," FinMaP-Working Papers 34, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    8. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    9. Bennöhr, Lars & Oestmann, Marco, 2014. "Determinants of house price dynamics. What can we learn from search engine data?," Working Paper 153/2014, Helmut Schmidt University, Hamburg.
    10. Chi, Tsung-Li & Liu, Hung-Tsen & Chang, Chia-Chien, 2023. "Hedging performance using google Trends–Evidence from the indian forex options market," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 107-123.
    11. Fantazziini, Dean, 2014. "Nowcasting and Forecasting the Monthly Food Stamps Data in the US using Online Search Data," MPRA Paper 59696, University Library of Munich, Germany.
    12. Mr. Serhan Cevik, 2020. "Where Should We Go? Internet Searches and Tourist Arrivals," IMF Working Papers 2020/022, International Monetary Fund.
    13. Juan Camilo Anzoátegui-Zapata & Juan Camilo Galvis-Ciro, 2020. "Disagreements in Consumer Inflation Expectations: Empirical Evidence for a Latin American Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 99-122, November.
    14. Jiawei Du, 2020. "A Research on Cross-sectional Return Dispersion and Volatility of US Stock Market during COVID-19," Papers 2007.11546, arXiv.org, revised Mar 2021.
    15. van der Wielen, Wouter & Barrios, Salvador, 2021. "Economic sentiment during the COVID pandemic: Evidence from search behaviour in the EU," Journal of Economics and Business, Elsevier, vol. 115(C).
    16. Vicente, María Rosalía & López-Menéndez, Ana J. & Pérez, Rigoberto, 2015. "Forecasting unemployment with internet search data: Does it help to improve predictions when job destruction is skyrocketing?," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 132-139.
    17. Johannes Bock, 2018. "Quantifying macroeconomic expectations in stock markets using Google Trends," Papers 1805.00268, arXiv.org.
    18. Chien-jung Ting & Yi-Long Hsiao, 2022. "Nowcasting the GDP in Taiwan and the Real-Time Tourism Data," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 12(3), pages 1-2.
    19. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    20. Karaman Örsal, Deniz Dilan, 2021. "Onlinedaten und Konsumentscheidungen: Voraussagen anhand von Daten aus Social Media und Suchmaschinen," Edition HWWI: Chapters, in: Straubhaar, Thomas (ed.), Neuvermessung der Datenökonomie, volume 6, pages 157-172, Hamburg Institute of International Economics (HWWI).
    21. Michał Chojnowski & Piotr Dybka, 2017. "Is Exchange Rate Moody? Forecasting Exchange Rate with Google Trends Data," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(1), pages 1-21, June.
    22. Pete Richardson, 2018. "Nowcasting and the Use of Big Data in Short-Term Macroeconomic Forecasting: A Critical Review," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 65-87.
    23. Smith, Geoffrey Peter, 2012. "Google Internet search activity and volatility prediction in the market for foreign currency," Finance Research Letters, Elsevier, vol. 9(2), pages 103-110.
    24. Karolien Lenaerts & Miroslav Beblavý & Brian Fabo, 2016. "Prospects for utilisation of non-vacancy Internet data in labour market analysis—an overview," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-18, December.
    25. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    26. Böhme, Marcus H. & Gröger, André & Stöhr, Tobias, 2020. "Searching for a better life: Predicting international migration with online search keywords," Journal of Development Economics, Elsevier, vol. 142(C).
    27. Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
    28. Bangwayo-Skeete, Prosper F. & Skeete, Ryan W., 2015. "Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach," Tourism Management, Elsevier, vol. 46(C), pages 454-464.
    29. Monokroussos, George, 2015. "Nowcasting in Real Time Using Popularity Priors," MPRA Paper 68594, University Library of Munich, Germany.
    30. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
    31. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    32. Jianchun Fang & Wanshan Wu & Zhou Lu & Eunho Cho, 2019. "Using Baidu Index To Nowcast Mobile Phone Sales In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(01), pages 83-96, March.
    33. Rahlff, Helen & Rinne, Ulf & Sonnabend, Hendrik, 2023. "COVID-19, School Closures and (Cyber)Bullying in Germany," IZA Discussion Papers 16650, Institute of Labor Economics (IZA).
    34. Costanza Catalano & Andrea Carboni & Claudio Doria, 2023. "How can Big Data improve the quality of tourism statistics? The Bank of Italy's experience in compiling the "travel" item in the Balance of Payments," Questioni di Economia e Finanza (Occasional Papers) 761, Bank of Italy, Economic Research and International Relations Area.
    35. Zhongchen Song & Tom Coupé, 2023. "Predicting Chinese consumption series with Baidu," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 21(3), pages 429-463, July.
    36. Liwen Ling & Dabin Zhang & Shanying Chen & Amin W. Mugera, 2020. "Can online search data improve the forecast accuracy of pork price in China?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 671-686, July.
    37. Ramya Rajajagadeesan Aroul & Sanjiv Sabherwal & Sergiy Saydometov, 2022. "FEAR Index, city characteristics, and housing returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(1), pages 173-205, March.
    38. Caterina Schiavoni & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "A dynamic factor model approach to incorporate Big Data in state space models for official statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 324-353, January.
    39. Maria De Paola & Vincenzo Scoppa, 2010. "Consumers’ Reactions To Negative Information On Product Quality: Evidence From Scanner Data," Working Papers 201012, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    40. Francesco D'Amuri & Juri Marcucci, 2012. "The predictive power of Google searches in forecasting unemployment," Temi di discussione (Economic working papers) 891, Bank of Italy, Economic Research and International Relations Area.
    41. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    42. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
    43. Alessia Naccarato & Andrea Pierini & Stefano Falorsi, 2015. "Using Google Trend Data To Predict The Italian Unemployment Rate," Departmental Working Papers of Economics - University 'Roma Tre' 0203, Department of Economics - University Roma Tre.
    44. Yann Algan & Fabrice Murtin & Elizabeth Beasley & Kazuhito Higa & Claudia Senik, 2019. "Well-being through the Lens of the Internet," SciencePo Working papers Main halshs-02096551, HAL.
    45. Melody Y. Huang & Randall R. Rojas & Patrick D. Convery, 2020. "Forecasting stock market movements using Google Trend searches," Empirical Economics, Springer, vol. 59(6), pages 2821-2839, December.
    46. Francesco D’Amuri & Juri Marcucci, 2010. "“Google it!”Forecasting the US Unemployment Rate with a Google Job Search index," Working Papers 2010.31, Fondazione Eni Enrico Mattei.
    47. Gulsah Senturk, 2022. "Can Google Search Data Improve the Unemployment Rate Forecasting Model? An Empirical Analysis for Turkey," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 9(2), pages 229-244, July.
    48. Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
    49. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
    50. Brodeur, Abel & Clark, Andrew E. & Flèche, Sarah & Powdthavee, Nattavudh, 2020. "COVID-19, Lockdowns and Well-Being: Evidence from Google Trends," IZA Discussion Papers 13204, Institute of Labor Economics (IZA).
    51. Nagao, Shintaro & Takeda, Fumiko & Tanaka, Riku, 2019. "Nowcasting of the U.S. unemployment rate using Google Trends," Finance Research Letters, Elsevier, vol. 30(C), pages 103-109.
    52. Pietro Giorgio Lovaglio & Mario Mezzanzanica & Emilio Colombo, 2020. "Comparing time series characteristics of official and web job vacancy data," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 85-98, February.
    53. Long Wen & Chang Liu & Haiyan Song, 2019. "Forecasting tourism demand using search query data: A hybrid modelling approach," Tourism Economics, , vol. 25(3), pages 309-329, May.
    54. Peter Kuhn, 2014. "The internet as a labor market matchmaker," IZA World of Labor, Institute of Labor Economics (IZA), pages 1-18, May.
    55. Yan Yan & Jiancheng Guan, 2019. "Entrepreneurial ecosystem, entrepreneurial rate and innovation: the moderating role of internet attention," International Entrepreneurship and Management Journal, Springer, vol. 15(2), pages 625-650, June.
    56. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    57. Mihnea Constantinescu, 2023. "Sparse Warcasting," Working Papers 01/2023, National Bank of Ukraine.
    58. Lucia Kureková & Miroslav Beblavý & Anna Thum-Thysen, 2015. "Using online vacancies and web surveys to analyse the labour market: a methodological inquiry," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-20, December.
    59. Rodrigo Mulero & Alfredo García-Hiernaux, 2021. "Forecasting Spanish unemployment with Google Trends and dimension reduction techniques," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(3), pages 329-349, September.
    60. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
    61. Andrea Fasulo & Alessia Naccarato & Alessio Pizzichini, 2019. "Nowcasting the Italian unemployment rate with Google Trends," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 73(4), pages 29-40, October-D.
    62. Bentzen, Jeanet, 2020. "In Crisis, We Pray: Religiosity and the COVID-19 Pandemic," CEPR Discussion Papers 14824, C.E.P.R. Discussion Papers.
    63. Artem Meshcheryakov & Stoyu I Ivanov, 2017. "Investor's sentiment in predicting the Effective Federal Funds Rate," Economics Bulletin, AccessEcon, vol. 37(4), pages 2767-2796.
    64. Rubén Jesús Pérez-López & Jesús Everardo Olguín Tiznado & María Mojarro Magaña & Claudia Camargo Wilson & Juan Andrés López Barreras & Jorge Luis García-Alcaraz, 2019. "Information Sharing with ICT in Production Systems and Operational Performance," Sustainability, MDPI, vol. 11(13), pages 1-18, July.
    65. Anastasiou, Dimitrios & Bragoudakis, Zacharias & Giannoulakis, Stelios, 2021. "Perceived vs actual financial crisis and bank credit standards: Is there any indication of self-fulfilling prophecy?," Research in International Business and Finance, Elsevier, vol. 58(C).
    66. Jichang Dong & Wei Dai & Ying Liu & Lean Yu & Jie Wang, 2019. "Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based Data Collection Method," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1605-1629, September.
    67. Erik Christian Montes Schütte, 2018. "In Search of a Job: Forecasting Employment Growth in the US using Google Trends," CREATES Research Papers 2018-25, Department of Economics and Business Economics, Aarhus University.
    68. David G. Blanchflower & Alex Bryson, 2021. "The Economics of Walking About and Predicting Unemployment," DoQSS Working Papers 21-24, Quantitative Social Science - UCL Social Research Institute, University College London.
    69. Eli Arditi & Eldad Yechiam & Gal Zahavi, 2015. "Association between Stock Market Gains and Losses and Google Searches," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-12, October.
    70. Askitas, Nikos & Zimmermann, Klaus F., 2009. "Prognosen aus dem Internet: Weitere Erholung am Arbeitsmarkt erwartet," IZA Standpunkte 13, Institute of Labor Economics (IZA).
    71. Oscar Claveria, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-10, December.
    72. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    73. Heather R. Tierney & Bing Pan, 2012. "A poisson regression examination of the relationship between website traffic and search engine queries," Netnomics, Springer, vol. 13(3), pages 155-189, October.
    74. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
    75. Tang, Mengxuan & Hu, Yang & Corbet, Shaen & Hou, Yang (Greg) & Oxley, Les, 2024. "Fintech, bank diversification and liquidity: Evidence from China," Research in International Business and Finance, Elsevier, vol. 67(PA).
    76. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    77. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    78. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Detecting Mortgage Delinquencies," IZA Discussion Papers 5895, Institute of Labor Economics (IZA).
    79. McLaren, Nick & Shanbhogue, Rachana, 2011. "Using internet search data as economic indicators," Bank of England Quarterly Bulletin, Bank of England, vol. 51(2), pages 134-140.
    80. Dimpfl, Thomas & Langen, Tobias, 2015. "A Cross-Country Analysis of Unemployment and Bonds with Long-Memory Relations," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112921, Verein für Socialpolitik / German Economic Association.
    81. Daud, Siti Nurazira Mohd & Ahmad, Abd Halim & Khalid, Airil & Azman-Saini, W.N.W., 2022. "FinTech and financial stability: Threat or opportunity?," Finance Research Letters, Elsevier, vol. 47(PB).
    82. Georgios Bampinas & Theodore Panagiotidis & Christina Rouska, 2018. "Volatility persistence and asymmetry under the microscope: The role of information demand for gold and oil," Working Paper series 18-13, Rimini Centre for Economic Analysis.
    83. Samvel S. Lazaryan & Nikita E. German, 2018. "Forecasting Current GDP Dynamics With Google Search Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 83-94, December.
    84. Fang, Yi & Wang, Qi & Wang, Fan & Zhao, Yang, 2023. "Bank fintech, liquidity creation, and risk-taking: Evidence from China," Economic Modelling, Elsevier, vol. 127(C).
    85. Ying Liu & Yibing Chen & Sheng Wu & Geng Peng & Benfu Lv, 2015. "Composite leading search index: a preprocessing method of internet search data for stock trends prediction," Annals of Operations Research, Springer, vol. 234(1), pages 77-94, November.
    86. Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Businesses with Big Data: Findings for the UK," CEP Occasional Papers 44, Centre for Economic Performance, LSE.
    87. Daniel Borup & Erik Christian Montes Schütte, 2019. "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers 2019-13, Department of Economics and Business Economics, Aarhus University.
    88. Andrea Fasulo & Alessio Guandalini & Marco D. Terribili, 2017. "Google Trends For Nowcasting Quarterly Household Consumption Expenditure," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 71(4), pages 2-10, October-D.
    89. Aaronson, Daniel & Brave, Scott A. & Butters, R. Andrew & Fogarty, Michael & Sacks, Daniel W. & Seo, Boyoung, 2022. "Forecasting unemployment insurance claims in realtime with Google Trends," International Journal of Forecasting, Elsevier, vol. 38(2), pages 567-581.
    90. Sebastian Schmitz, 2019. "The Effects of Germany's Statutory Minimum Wage on Employment and Welfare Dependency," German Economic Review, Verein für Socialpolitik, vol. 20(3), pages 330-355, August.
    91. Maria De Paola & Vincenzo Scoppa & Valeria Pupo, 2014. "Absenteeism in the Italian Public Sector: The Effects of Changes in Sick Leave Policy," Journal of Labor Economics, University of Chicago Press, vol. 32(2), pages 337-360.
    92. Robin Niesert & Jochem Oorschot & Chris Veldhuisen & Kester Brons & Rutger-Jan Lange, "undated". "Can Google Search Data Help Predict Macroeconomic Series?," Tinbergen Institute Discussion Papers 19-021/III, Tinbergen Institute.
    93. Chiu, Peng-Chia & Teoh, Siew Hong & Zhang, Yinglei & Huang, Xuan, 2023. "Using Google searches of firm products to detect revenue management," Accounting, Organizations and Society, Elsevier, vol. 109(C).
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  15. Askitas, Nikos & Zimmermann, Klaus F., 2009. "Prognosen aus dem Internet: Weitere Erholung am Arbeitsmarkt erwartet," IZA Standpunkte 13, Institute of Labor Economics (IZA).

    Cited by:

    1. Askitas, Nikos & Zimmermann, Klaus F., 2009. "Googlemetrie und Arbeitsmarkt in der Wirtschaftskrise," IZA Standpunkte 17, Institute of Labor Economics (IZA).

  16. Askitas, Nikos & Zimmermann, Klaus F., 2009. "Googlemetrie und Arbeitsmarkt in der Wirtschaftskrise," IZA Standpunkte 17, Institute of Labor Economics (IZA).

    Cited by:

    1. Jan Goebel & Christian Krekel & Tim Tiefenbach & Nicholas R. Ziebarth, 2014. "Natural Disaster, Environmental Concerns, Well-Being and Policy Action," CINCH Working Paper Series 1405, Universitaet Duisburg-Essen, Competent in Competition and Health.
    2. Mihaela Simionescu & Dalia Streimikiene & Wadim Strielkowski, 2020. "What Does Google Trends Tell Us about the Impact of Brexit on the Unemployment Rate in the UK?," Sustainability, MDPI, vol. 12(3), pages 1-10, January.
    3. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    4. Simionescu, Mihaela & Raišienė, Agota Giedrė, 2021. "A bridge between sentiment indicators: What does Google Trends tell us about COVID-19 pandemic and employment expectations in the EU new member states?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).

Articles

  1. Nikolaos Askitas, 2017. "Explaining opinion polarisation with opinion copulas," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-11, August.

    Cited by:

    1. Liu, Fangzhou & Zhang, Zengjie & Buss, Martin, 2019. "Robust optimal control of deterministic information epidemics with noisy transition rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 577-587.

  2. Nikolaos Askitas, 2016. "Big Data is a big deal but how much data do we need? [Big Data gut und schön. Aber wie viel Data brauchen wir?]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(2), pages 113-125, October.
    See citations under working paper version above.
  3. Nikolaos Askitas, 2016. "Predicting Road Conditions with Internet Search," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-12, August.
    See citations under working paper version above.
  4. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.

    Cited by:

    1. Nikos Askitas, 2016. "Predicting Road Conditions with Internet Search," RatSWD Working Papers 252, German Data Forum (RatSWD).
    2. Silvia Peracchi, 2022. "The Migration Crisis in the Local News: Evidence from the French-Italian Border," CESifo Working Paper Series 10070, CESifo.
    3. Chiara L. Comolli & Daniele Vignoli, 2019. "Spread-ing uncertainty, shrinking birth rates," Econometrics Working Papers Archive 2019_08, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    4. Rik Chakraborti & Gavin Roberts, 2020. "Anti-Gouging Laws, Shortages, and COVID-19: Insights from Consumer Searches," Journal of Private Enterprise, The Association of Private Enterprise Education, vol. 35(Winter 20), pages 1-20.
    5. Fantazzini, Dean & Shakleina, Marina & Yuras, Natalia, 2018. "Big Data for computing social well-being indices of the Russian population," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 50, pages 43-66.
    6. Cebrián, Eduardo & Domenech, Josep, 2024. "Addressing Google Trends inconsistencies," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    7. de Pedraza, Pablo & Vollbracht, Ian, 2020. "The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve," GLO Discussion Paper Series 515, Global Labor Organization (GLO).
    8. Silvia Peracchi, 2023. "Migration Crisis in the Local News: Evidence from the French-Italian Border," LIDAM Discussion Papers IRES 2023021, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    9. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    10. Andrius Grybauskas & Vaida Pilinkienė & Mantas Lukauskas & Alina Stundžienė & Jurgita Bruneckienė, 2023. "Nowcasting Unemployment Using Neural Networks and Multi-Dimensional Google Trends Data," Economies, MDPI, vol. 11(5), pages 1-23, April.
    11. Pablo Pedraza & Ian Vollbracht, 2023. "General theory of data, artificial intelligence and governance," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    12. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).

  5. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "Health and well-being in the great recession," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 26-47, April.

    Cited by:

    1. Luca Bonacini & Giovanni Gallo & Fabrizio Patriarca, 2021. "Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 275-301, January.
    2. Yu Qin & Hongjia Zhu, 2018. "Run away? Air pollution and emigration interests in China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(1), pages 235-266, January.
    3. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
    4. Chiara L. Comolli & Daniele Vignoli, 2019. "Spread-ing uncertainty, shrinking birth rates," Econometrics Working Papers Archive 2019_08, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Botezat, Alina, 2017. "Austerity plan announcements and the impact on the employees’ wellbeing," Journal of Economic Psychology, Elsevier, vol. 63(C), pages 1-16.
    6. Askitas, Nikos, 2015. "Calling the Greek Referendum on the Nose with Google Trends," IZA Discussion Papers 9569, Institute of Labor Economics (IZA).
    7. Nikos Askitas & Anoop Bindra Martinez & Fabio Saia Cereda & Nikolaos Askitas, 2024. "The IZA / Fable Swipe Consumption Index," CESifo Working Paper Series 11389, CESifo.
    8. Kronenberg, Christoph & Boehnke, Jan R., 2019. "How did the 2008-11 financial crisis affect work-related common mental distress? Evidence from 393 workplaces in Great Britain," Economics & Human Biology, Elsevier, vol. 33(C), pages 193-200.
    9. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
    10. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).

  6. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    See citations under working paper version above.
  7. Nikolaos Askitas & Klaus F. Zimmermann, 2013. "Nowcasting Business Cycles Using Toll Data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(4), pages 299-306, July.
    See citations under working paper version above.
  8. Nikos Askitas & Klaus Zimmermann, 2009. "Googlemetrie und Arbeitsmarkt," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 89(7), pages 489-496, July.

    Cited by:

    1. Jan Goebel & Christian Krekel & Tim Tiefenbach & Nicholas R. Ziebarth, 2014. "Natural Disaster, Environmental Concerns, Well-Being and Policy Action," CINCH Working Paper Series 1405, Universitaet Duisburg-Essen, Competent in Competition and Health.
    2. Askitas, Nikos & Zimmermann, Klaus F., 2009. "Googlemetrie und Arbeitsmarkt in der Wirtschaftskrise," IZA Standpunkte 17, Institute of Labor Economics (IZA).
    3. Mihaela Simionescu & Dalia Streimikiene & Wadim Strielkowski, 2020. "What Does Google Trends Tell Us about the Impact of Brexit on the Unemployment Rate in the UK?," Sustainability, MDPI, vol. 12(3), pages 1-10, January.
    4. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    5. Simionescu, Mihaela & Raišienė, Agota Giedrė, 2021. "A bridge between sentiment indicators: What does Google Trends tell us about COVID-19 pandemic and employment expectations in the EU new member states?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).

  9. Nikos Askitas & Klaus F. Zimmermann, 2009. "Prognosen aus dem Internet: weitere Erholung am Arbeitsmarkt erwartet," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 76(25), pages 402-408.
    See citations under working paper version above.
  10. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    See citations under working paper version above.

Software components

  1. Nikos Askitas, 2011. "WEEKLYCLAIMS: Stata module to Get Weekly Initial Jobless Claims from the US Dept. of Labor," Statistical Software Components S457249, Boston College Department of Economics, revised 17 Jun 2012.

    Cited by:

    1. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Detecting Mortgage Delinquencies," IZA Discussion Papers 5895, Institute of Labor Economics (IZA).

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