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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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Bargain, Olivier & Aminjonov, Ulugbek, 2020. "Trust and Compliance to Public Health Policies in Times of COVID-19," IZA Discussion Papers 13205, Institute of Labor Economics (IZA).
    6. 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.
    7. 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).
    8. Andrew Atkeson & Karen A. Kopecky & Tao Zha, 2020. "Four Stylized Facts about COVID-19," FRB Atlanta Working Paper 2020-15, Federal Reserve Bank of Atlanta.
    9. 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.
    10. 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).
    11. 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).
    12. 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.
    13. Laura Coroneo & Fabrizio Iacone, 2021. "Testing for equal predictive accuracy with strong dependence," Discussion Papers 21/03, Department of Economics, University of York.
    14. Wolf, Nikolaus & Eckardt, Matthias, 2020. "Covid-19 across European Regions: the Role of Border Controls," CEPR Discussion Papers 15178, C.E.P.R. Discussion Papers.
    15. Millimet, Daniel L. & Parmeter, Christopher F., 2021. "COVID-19 Severity: A New Approach to Quantifying Global Cases and Deaths," IZA Discussion Papers 14116, Institute of Labor Economics (IZA).
    16. 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.
    17. Etienne Farvaque & Hira Iqbal & Nicolas Ooghe, 2020. "Health politics? Determinants of US states’ reactions to COVID-19," Post-Print hal-03128875, HAL.
    18. 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).
    19. Burdett, Ashley & Davillas, Apostolos & Etheridge, Ben, 2021. "Weather, Psychological Wellbeing and Mobility during the First Wave of the COVID-19 Pandemic," IZA Discussion Papers 14119, Institute of Labor Economics (IZA).
    20. Massimiliano Ferraresi & Christos Kotsogiannis & Leonzio Rizzo & Riccardo Secomandi, 2020. "The ‘Great Lockdown’ and its Determinants," Working papers 91, Società Italiana di Economia Pubblica.
    21. 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.
    22. 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.
    23. 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.
    24. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
    25. Eduardo Levy Yeyati & Patricio Goldstein & Luca Sartorio, 2021. "Lockdown Fatigue: The Diminishing Effects of Quarantines on the Spread of COVID-19," CID Working Papers 391, Center for International Development at Harvard University.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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).
    31. 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.
    32. 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.
    33. 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).
    34. Ferraresi, Massimiliano & Kotsogiannis, Christos & Rizzo, Leonzio & Secomandi, Riccardo, 2020. "The ‘Great Lockdown’ and its determinants," Economics Letters, Elsevier, vol. 197(C).
    35. 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).
    36. 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.
    37. 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.
    38. 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.
    39. 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).
    40. 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.
    41. 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.

  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. Engels, Barbara, 2016. "Big-Data-Analyse: Ein Einstieg für Ökonomen," IW-Kurzberichte 78.2016, Institut der deutschen Wirtschaft (IW) / German Economic Institute.
    2. 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.

  4. 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.

  5. 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," Post-Print 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.

  6. 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. Maarten van Klaveren & Kea Tijdens & Stefano Visintin, 2015. "Skill Mismatch among Migrant Workers: Evidence from A Large Multi-Country Dataset," Working Papers id:7342, eSocialSciences.
    2. Brian Fabo & Miroslav Beblavý & Karolien Lenaerts, 2017. "The importance of foreign language skills in the labour markets of Central and Eastern Europe: assessment based on data from online job portals," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(3), pages 487-508, August.
    3. 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.
    4. Nwaobi, Godwin, 2019. "University Postgraduate Research Programmes: Digitization(ICT),Innovations and Applications," MPRA Paper 96730, University Library of Munich, Germany.
    5. 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.
    6. Mutascu, Mihai & Horky, Florian & Strango, Cristina, 2023. "Good or bad? Digitalisation and green preferences," Energy Economics, Elsevier, vol. 121(C).
    7. Fabio Milani, 2020. "COVID-19 Outbreak, Social Response, and Early Economic Effects: A Global VAR Analysis of Cross-Country Interdependencies," Working Papers 192004, University of California-Irvine, Department of Economics.
    8. 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.
    9. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    10. 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.
    11. 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.
    12. 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.
    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. 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).
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. VAN DER WIELEN Wouter & BARRIOS Salvador, 2020. "Fear and Employment During the COVID Pandemic: Evidence from Search Behaviour in the EU," JRC Working Papers on Taxation & Structural Reforms 2020-08, Joint Research Centre.
    21. 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).
    22. 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.
    23. 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).
    24. 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.
    25. Michael Weinhardt, 2021. "Big Data: Some Ethical Concerns for the Social Sciences," Social Sciences, MDPI, vol. 10(2), pages 1-14, January.
    26. 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.
    27. Beblav�, 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.
    28. 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.
    29. 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.
    30. 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.
    31. Javier Sebastian, 2016. "Blockchain in financial services: Regulatory landscape and future challenges," Working Papers 16/21, BBVA Bank, Economic Research Department.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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).

  7. 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. Askitas, Nikos, 2015. "Trend-Spotting in the Housing Market," IZA Discussion Papers 9427, Institute of Labor Economics (IZA).
    3. 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.
    4. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
    5. 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.
    6. 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.

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

    Cited by:

    1. 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).
    2. Askitas, Nikos, 2015. "Trend-Spotting in the Housing Market," IZA Discussion Papers 9427, Institute of Labor Economics (IZA).
    3. 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).
    4. 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.
    5. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    6. David Coble & Pablo Pincheira, 2021. "Forecasting building permits with Google Trends," Empirical Economics, Springer, vol. 61(6), pages 3315-3345, December.
    7. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    8. 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".
    9. 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.
    10. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.

  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. 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).
    2. 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).
    3. Blanchflower, David G. & Oswald, Andrew J., 2011. "Antidepressants and Age," IZA Discussion Papers 5785, Institute of Labor Economics (IZA).
    4. 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.
    5. 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.
    6. 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).
    7. Alberto Montagnoli & Mirko Moro, 2014. "Everybody Hurts: Banking Crises and Individual Wellbeing," Working Papers 2014010, The University of Sheffield, Department of Economics.
    8. Askitas, Nikos, 2015. "Calling the Greek Referendum on the Nose with Google Trends," IZA Discussion Papers 9569, Institute of Labor Economics (IZA).
    9. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    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. Blanchflower, David G; Oswald, Andrew, 2011. "Antidepressants and Age," CAGE Online Working Paper Series 44, Competitive Advantage in the Global Economy (CAGE).
    12. 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.
    13. Frijters, Paul & Johnston, David W. & Lordan, Grace & Shields, Michael A., 2013. "Exploring the relationship between macroeconomic conditions and problem drinking as captured by Google searches in the US," Social Science & Medicine, Elsevier, vol. 84(C), pages 61-68.
    14. 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.
    15. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Detecting Mortgage Delinquencies," IZA Discussion Papers 5895, Institute of Labor Economics (IZA).

  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. "Nowcasting Business Cycles Using Toll Data," IZA Discussion Papers 5522, Institute of Labor Economics (IZA).

    Cited by:

    1. 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).
    2. 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).
    3. 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.
    4. 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.
    5. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    6. 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).
    7. Selod,Harris & Soumahoro,Souleymane, 2020. "Big Data in Transportation : An Economics Perspective," Policy Research Working Paper Series 9308, The World Bank.
    8. Indaco, Agustín, 2019. "From Twitter to GDP: Estimating Economic Activity From Social Media," MPRA Paper 95885, University Library of Munich, Germany.
    9. 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.
    10. 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).
    11. 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.
    12. 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," Working Papers 2022-06, Joint Research Centre, European Commission.
    13. 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.
    14. 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.

  12. 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).

  13. 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. 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. 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.
    3. Zhongchen Song & Tom Coupé, 2022. "Predicting Chinese consumption series with Baidu," Working Papers in Economics 22/19, University of Canterbury, Department of Economics and Finance.
    4. Brodeur, Abel & Clark, Andrew E. & Fleche, Sarah & Powdthavee, Nattavudh, 2020. "COVID-19, Lockdowns and Well-Being: Evidence from Google Trends," GLO Discussion Paper Series 552, Global Labor Organization (GLO).
    5. 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.
    6. Brian Fabo & Miroslav Beblavý & Karolien Lenaerts, 2017. "The importance of foreign language skills in the labour markets of Central and Eastern Europe: assessment based on data from online job portals," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(3), pages 487-508, August.
    7. Jorge M. Agüero, 2019. "Information and Behavioral Responses with More than One Agent: The Case of Domestic Violence Awareness Campaigns," Working papers 2019-04, University of Connecticut, Department of Economics.
    8. Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Business with Big Data: Findings from the UK," National Institute of Economic and Social Research (NIESR) Discussion Papers 442, National Institute of Economic and Social Research.
    9. Yang, Xin & Pan, Bing & Evans, James A. & Lv, Benfu, 2015. "Forecasting Chinese tourist volume with search engine data," Tourism Management, Elsevier, vol. 46(C), pages 386-397.
    10. David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    11. Caprotti, Federico, 2016. "Defining a new sector in the green economy: Tracking the techno-cultural emergence of the cleantech sector, 1990–2010," Technology in Society, Elsevier, vol. 46(C), pages 80-89.
    12. Bentzen, Jeanet Sinding, 2021. "In crisis, we pray: Religiosity and the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 541-583.
    13. 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.
    14. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
    15. 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).
    16. David G. Blanchflower & Alex Bryson, 2021. "The Economics of Walking About and Predicting Unemployment," NBER Working Papers 29172, National Bureau of Economic Research, Inc.
    17. Park, Sungjun & Kim, Jinsoo, 2018. "The effect of interest in renewable energy on US household electricity consumption: An analysis using Google Trends data," Renewable Energy, Elsevier, vol. 127(C), pages 1004-1010.
    18. Jacques Bughin, 2015. "Google searches and twitter mood: nowcasting telecom sales performance," Netnomics, Springer, vol. 16(1), pages 87-105, August.
    19. Christoph Safferling & Aaron Lowen, 2011. "Economics in the Kingdom of Loathing: Analysis of Virtual Market Data," Working Paper Series of the Department of Economics, University of Konstanz 2011-30, Department of Economics, University of Konstanz.
    20. 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).
    21. 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.
    22. Yann Algan & Elizabeth Beasley & Florian Guyot & Kazuhito Higad & Fabrice Murtin & Claudia Senik, 2015. "Big Data Measures of Well-Being: Evidence from a Google Well-Being Index in the US," PSE Working Papers hal-03429943, HAL.
    23. Kholodilin, Konstantin A. & Siliverstovs, Boriss, 2012. "Measuring regional inequality by internet car price advertisements: Evidence for Germany," Economics Letters, Elsevier, vol. 116(3), pages 414-417.
    24. Hou, Xiaohui & Gao, Zhixian & Wang, Qing, 2016. "Internet finance development and banking market discipline: Evidence from China," Journal of Financial Stability, Elsevier, vol. 22(C), pages 88-100.
    25. Kovács, Olivér, 2017. "Az ipar 4.0 komplexitása - II [The Complexity of Industry 4.0 - Part 2]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 970-987.
    26. 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.
    27. Simeon Vosen & Torsten Schmidt, 2012. "A monthly consumption indicator for Germany based on Internet search query data," Applied Economics Letters, Taylor & Francis Journals, vol. 19(7), pages 683-687, May.
    28. 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.
    29. F. Antolini & L. Grassini, 2019. "Foreign arrivals nowcasting in Italy with Google Trends data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2385-2401, September.
    30. 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.
    31. 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.
    32. 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.
    33. Tefft, Nathan, 2011. "Insights on unemployment, unemployment insurance, and mental health," Journal of Health Economics, Elsevier, vol. 30(2), pages 258-264, March.
    34. Mirko Seithe & Lena Calahorrano, 2014. "Analysing Party Preferences Using Google Trends," CESifo Working Paper Series 4631, CESifo.
    35. George Monokroussos & Yongchen Zhao, 2020. "Nowcasting in Real Time Using Popularity Priors," Working Papers 2020-01, Towson University, Department of Economics, revised Feb 2020.
    36. 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.
    37. 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.
    38. Aleksandar Bradic, 2012. "The Role of Social Feedback in Financing of Technology Ventures," Papers 1301.2196, arXiv.org.
    39. Pirschel, Inske, 2016. "Forecasting euro area recessions in real-time," Kiel Working Papers 2020, Kiel Institute for the World Economy (IfW Kiel).
    40. Olivier Gergaud & Victor Ginsburgh, 2016. "Evaluating the Economic Effects of Cultural Events," Working Papers ECARES ECARES 2016-24, ULB -- Universite Libre de Bruxelles.
    41. D'Amuri, Francesco/FD & Marcucci, Juri/JM, 2009. ""Google it!" Forecasting the US unemployment rate with a Google job search index," MPRA Paper 18248, University Library of Munich, Germany.
    42. Schmitz, Sebastian, 2017. "The effects of Germany's new minimum wage on employment and welfare dependency," Discussion Papers 2017/21, Free University Berlin, School of Business & Economics.
    43. 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.
    44. 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.
    45. Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
    46. 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.
    47. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    48. Semen Son Turan, 2014. "Internet Search Volume and Stock Return Volatility: The Case of Turkish Companies," Information Management and Business Review, AMH International, vol. 6(6), pages 317-328.
    49. Nuarpear Lekfuangfu & Voraprapa Nakavachara & Paphatsorn Sawaengsuksant, 2017. "Glancing at Labour Market Mismatch with User-generated Internet Data," PIER Discussion Papers 53, Puey Ungphakorn Institute for Economic Research.
    50. Dimitrios Anastasiou & Zacharias Bragoudakis & Stelios Giannoulakis, 2020. "Perceived vs actual financial crisis and bank credit standards: is there any indication of self-fulfilling prophecy?," Working Papers 277, Bank of Greece.
    51. Bai, Lijuan & Yan, Xiangbin & Yu, Guang, 2019. "Impact of CEO media appearance on corporate performance in social media," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    52. Fabio Milani, 2020. "COVID-19 Outbreak, Social Response, and Early Economic Effects: A Global VAR Analysis of Cross-Country Interdependencies," Working Papers 192004, University of California-Irvine, Department of Economics.
    53. Döhrn, Roland & Mitze, Timo & Schmidt, Torsten & Tauchmann, Harald & Vosen, Simeon, 2010. "Analyse und Prognose des Spar- und Konsumverhaltens privater Haushalte: Endbericht - November 2010," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 69982.
    54. Kureková, Lucia Mýtna & Beblavy, Miroslav & Thum, Anna-Elisabeth, 2014. "Using Internet Data to Analyse the Labour Market: A Methodological Enquiry," IZA Discussion Papers 8555, Institute of Labor Economics (IZA).
    55. 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.
    56. 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.
    57. Simeon Vosen & Torsten Schmidt, 2011. "Forecasting private consumption: survey‐based indicators vs. Google trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(6), pages 565-578, September.
    58. Francesco, D'Amuri, 2009. "Predicting unemployment in short samples with internet job search query data," MPRA Paper 18403, University Library of Munich, Germany.
    59. Ahmed Shoukry Rashad, 2022. "The Power of Travel Search Data in Forecasting the Tourism Demand in Dubai," Forecasting, MDPI, vol. 4(3), pages 1-11, July.
    60. 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.
    61. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
    62. 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.
    63. 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.
    64. Li, Xin & Pan, Bing & Law, Rob & Huang, Xiankai, 2017. "Forecasting tourism demand with composite search index," Tourism Management, Elsevier, vol. 59(C), pages 57-66.
    65. Hantzsche, Arno, 2022. "Fiscal uncertainty and sovereign credit risk," European Economic Review, Elsevier, vol. 148(C).
    66. 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.
    67. Yann Algan & Fabrice Murtin & Elizabeth Beasley & Kazuhito Higa & Claudia Senik, 2019. "Well-being through the Lens of the Internet," Post-Print halshs-02096551, HAL.
    68. 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.
    69. 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.
    70. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
    71. 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.
    72. 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.
    73. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    74. 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.
    75. Schmidt, Torsten & Vosen, Simeon, 2012. "Using Internet Data to Account for Special Events in Economic Forecasting," Ruhr Economic Papers 382, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    76. Daniel Aaronson & Scott A. Brave & R. Andrew Butters & Daniel W. Sacks & Boyoung Seo, 2020. "Using the Eye of the Storm to Predict the Wave of Covid-19 UI Claims," Working Paper Series WP 2020-10, Federal Reserve Bank of Chicago.
    77. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    78. 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.
    79. Peter Kuhn, 2014. "The internet as a labor market matchmaker," IZA World of Labor, Institute of Labor Economics (IZA), pages 1-18, May.
    80. 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.
    81. Sengtha Chay & Nophea Sasaki, 2011. "Using Online Tools to Assess Public Responses to Climate Change Mitigation Policies in Japan," Future Internet, MDPI, vol. 3(2), pages 1-13, April.
    82. Burcu Kapar & Jose Olmo, 2021. "Analysis of Bitcoin prices using market and sentiment variables," The World Economy, Wiley Blackwell, vol. 44(1), pages 45-63, January.
    83. Scheffel, Eric Michael, 2012. "Political uncertainty in a data-rich environment," MPRA Paper 37318, University Library of Munich, Germany.
    84. Pablo Pedraza & Ian Vollbracht, 2023. "General theory of data, artificial intelligence and governance," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    85. Zeynalov, Ayaz, 2014. "Nowcasting Tourist Arrivals to Prague: Google Econometrics," MPRA Paper 60945, University Library of Munich, Germany.
    86. 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.
    87. 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.
    88. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
    89. 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.
    90. Dimitrios Anastasiou & Konstantinos Drakos, 2021. "Nowcasting the Greek (semi‐) deposit run: Hidden uncertainty about the future currency in a Google search," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1133-1150, January.
    91. Pietro Giorgio Lovaglio, 2022. "Do job vacancies variations anticipate employment variations by sector? Some preliminary evidence from Italy," LABOUR, CEIS, vol. 36(1), pages 71-93, March.
    92. Azusa Matsumoto & Kohei Matsumura & Noriyuki Shiraki, 2013. "Potential of Search Data in Assessment of Current Economic Conditions," Bank of Japan Research Papers 2013-04-18, Bank of Japan.
    93. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    94. Maria De Paola & Vincenzo Scoppa, 2013. "Consumers’ Reactions to Negative Information on Product Quality: Evidence from Scanner Data," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 42(3), pages 235-280, May.
    95. Cedric Mbanga & Ali F. Darrat & Jung Chul Park, 2019. "Investor sentiment and aggregate stock returns: the role of investor attention," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 397-428, August.
    96. Vakrman, Tomas & Kristoufek, Ladislav, 2015. "Underpricing, underperformance and overreaction in initial pubic offerings: Evidence from investor attention using online searches," FinMaP-Working Papers 35, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    97. 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.
    98. 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.
    99. Jan Goebel & Christian Krekel & Tim Tiefenbach & Nicolas Ziebarth, 2015. "How natural disasters can affect environmental concerns, risk aversion, and even politics: evidence from Fukushima and three European countries," Journal of Population Economics, Springer;European Society for Population Economics, vol. 28(4), pages 1137-1180, October.
    100. 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).
    101. Yakubu, Hanan & Kwong, C.K., 2021. "Forecasting the importance of product attributes using online customer reviews and Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    102. 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.
    103. 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.
    104. Takao Noguchi & Neil Stewart & Christopher Y Olivola & Helen Susannah Moat & Tobias Preis, 2014. "Characterizing the Time-Perspective of Nations with Search Engine Query Data," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-5, April.
    105. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    106. Claveria, Oscar, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 53(1), pages 1-3.
    107. 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.
    108. 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.
    109. 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).
    110. 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.
    111. Jamal Bouoiyour & Refk Selmi & Aviral Kumar Tiwari, 2015. "Is Bitcoin Business Income or Speculative Bubble? Unconditional vs. Conditional Frequency Domain Analysis," Post-Print hal-01879684, HAL.
    112. Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
    113. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
    114. Merve Alanyali & Tobias Preis & Helen Susannah Moat, 2016. "Tracking Protests Using Geotagged Flickr Photographs," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-8, March.
    115. Dean Fantazzini & Mario Maggi, 2014. "Proposed Coal Power Plants and Coal-To-Liquids Plants: Which Ones Survive and Why?," DEM Working Papers Series 082, University of Pavia, Department of Economics and Management.
    116. 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.
    117. Consolo, Agostino & Foroni, Claudia & Martínez Hernández, Catalina, 2021. "A mixed frequency BVAR for the euro area labour market," Working Paper Series 2601, European Central Bank.
    118. Pin Guo & Yue Shen, 2016. "The impact of Internet finance on commercial banks’ risk taking: evidence from China," China Finance and Economic Review, Springer, vol. 4(1), pages 1-19, December.
    119. 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.
    120. 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.
    121. 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.
    122. 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.
    123. John W Ayers & Kurt Ribisl & John S Brownstein, 2011. "Using Search Query Surveillance to Monitor Tax Avoidance and Smoking Cessation following the United States' 2009 “SCHIP” Cigarette Tax Increase," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-7, March.
    124. Chien-jung Ting & Yi-Long Hsiao & Rui-jun Su, 2022. "Application of the Real-Time Tourism Data in Nowcasting the Service Consumption in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(4), pages 1-4.
    125. Andree Ehlert & Jan Seidel & Ursula Weisenfeld, 2020. "Trouble on my mind: the effect of catastrophic events on people’s worries," Empirical Economics, Springer, vol. 59(2), pages 951-975, August.
    126. Grzegorz Michal Bulczak, 2021. "Use of Google Trends to Predict the Real Estate Market: Evidence from the United Kingdom," International Real Estate Review, Global Social Science Institute, vol. 24(4), pages 613-631.
    127. Jorge M. Agüero & Trinidad Beleche, 2016. "Health Shocks and the Long-Lasting Change in Health Behaviors: Evidence from Mexico," Working papers 2016-26, University of Connecticut, Department of Economics.
    128. Nathan, Max & Rosso, Anna, 2015. "Mapping digital businesses with big data: Some early findings from the UK," Research Policy, Elsevier, vol. 44(9), pages 1714-1733.
    129. Tong Liu & Guojun He & Alexis Lau, 2018. "Avoidance behavior against air pollution: evidence from online search indices for anti-PM2.5 masks and air filters in Chinese cities," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(2), pages 325-363, April.
    130. Oestmann, Marco & Bennöhr, Lars, 2015. "Determinants of house price dynamics. What can we learn from search engine data?," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113198, Verein für Socialpolitik / German Economic Association.
    131. 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.
    132. 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.
    133. VAN DER WIELEN Wouter & BARRIOS Salvador, 2020. "Fear and Employment During the COVID Pandemic: Evidence from Search Behaviour in the EU," JRC Working Papers on Taxation & Structural Reforms 2020-08, Joint Research Centre.
    134. 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.
    135. Marta Crispino & Vincenzo Mariani, 2023. "A tool to nowcast tourist overnight stays with payment data and complementary indicators," Questioni di Economia e Finanza (Occasional Papers) 746, Bank of Italy, Economic Research and International Relations Area.
    136. Semen Son-Turan, 2016. "The Impact of Investor Sentiment on the "Leverage Effect"," International Econometric Review (IER), Econometric Research Association, vol. 8(1), pages 4-18, April.
    137. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
    138. 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.
    139. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German Car Sales Using Google Data and Multivariate Models," MPRA Paper 67110, University Library of Munich, Germany.
    140. 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.
    141. 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).
    142. Agüero, Jorge M. & Beleche, Trinidad, 2017. "Health shocks and their long-lasting impact on health behaviors: Evidence from the 2009 H1N1 pandemic in Mexico," Journal of Health Economics, Elsevier, vol. 54(C), pages 40-55.
    143. Levent Bulut, 2015. "Google Trends and Forecasting Performance of Exchange Rate Models," IPEK Working Papers 1505, Ipek University, Department of Economics.
    144. 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.
    145. Mohamed Arouri & Amal Aouadi & Philippe Foulquier & Frédéric Teulon, 2013. "Can Information Demand Help to Predict Stock Market Liquidity ? Google it !," Working Papers 2013-24, Department of Research, Ipag Business School.
    146. Thomas Dimpfl & Tobias Langen, 2019. "How Unemployment Affects Bond Prices: A Mixed Frequency Google Nowcasting Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 551-573, August.
    147. Huang, Xiankai & Zhang, Lifeng & Ding, Yusi, 2017. "The Baidu Index: Uses in predicting tourism flows –A case study of the Forbidden City," Tourism Management, Elsevier, vol. 58(C), pages 301-306.
    148. 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.
    149. 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).
    150. Li, Xin & Ma, Jian & Wang, Shouyang & Zhang, Xun, 2015. "How does Google search affect trader positions and crude oil prices?," Economic Modelling, Elsevier, vol. 49(C), pages 162-171.
    151. David Iselin & Boriss Siliverstovs, 2016. "Using newspapers for tracking the business cycle: a comparative study for Germany and Switzerland," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1103-1118, March.
    152. Cheng, Maoyong & Qu, Yang, 2020. "Does bank FinTech reduce credit risk? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
    153. Latoeiro, Pedro & Ramos, Sofía B. & Veiga, Helena, 2013. "Predictability of stock market activity using Google search queries," DES - Working Papers. Statistics and Econometrics. WS ws130605, Universidad Carlos III de Madrid. Departamento de Estadística.
    154. 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.
    155. 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.
    156. Huijian Han & Zhiming Li & Zongwei Li, 2023. "Using Machine Learning Methods to Predict Consumer Confidence from Search Engine Data," Sustainability, MDPI, vol. 15(4), pages 1-12, February.
    157. Calahorrano, Lena & Seithe, Mirko, 2014. "Analysing Party Preferences Using Google Trends," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100294, Verein für Socialpolitik / German Economic Association.
    158. Grazia Biorci & Antonella Emina & Michelangelo Puliga & Lisa Sella & Gianna Vivaldo, 2016. "Tweet-tales: moods of socio-economic crisis?," Working Papers 04/2016, IMT School for Advanced Studies Lucca, revised Jul 2016.
    159. Jaroslav Pavlicek & Ladislav Kristoufek, 2014. "Can Google searches help nowcast and forecast unemployment rates in the Visegrad Group countries?," Papers 1408.6639, arXiv.org.
    160. 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.
    161. Dean Fantazzini, 2014. "Nowcasting and Forecasting the Monthly Food Stamps Data in the US Using Online Search Data," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-27, November.
    162. Askitas, Nikos & Zimmermann, Klaus F., 2009. "Googlemetrie und Arbeitsmarkt in der Wirtschaftskrise," IZA Standpunkte 17, Institute of Labor Economics (IZA).
    163. Serhan Cevik, 2022. "Where should we go? Internet searches and tourist arrivals," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4048-4057, October.
    164. Pincheira, Pablo & Hernández, Ana María, 2019. "Forecasting Unemployment Rates with International Factors," MPRA Paper 97855, University Library of Munich, Germany.
    165. Anastasiou, Dimitrios & Drakos, Konstantinos, 2021. "European depositors’ behavior and crisis sentiment," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 117-136.
    166. Mihnea Constantinescu, 2023. "Sparse Warcasting," Working Papers 01/2023, National Bank of Ukraine.
    167. 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.
    168. 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.
    169. Bas Scheer, 2022. "Addressing Unemployment Rate Forecast Errors in Relation to the Business Cycle," CPB Discussion Paper 434, CPB Netherlands Bureau for Economic Policy Analysis.
    170. Mario Maggi & Pierpaolo Uberti, 2021. "Google search volumes for portfolio management: performances and asset concentration," Annals of Operations Research, Springer, vol. 299(1), pages 163-175, April.
    171. 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.
    172. 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.
    173. 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.
    174. 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.
    175. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    176. 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.
    177. Johannes Bock, 2018. "Quantifying macroeconomic expectations in stock markets using Google Trends," Papers 1805.00268, arXiv.org.
    178. 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.
    179. 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.
    180. Branislav Saxa, 2014. "Forecasting Mortgages: Internet Search Data as a Proxy for Mortgage Credit Demand," Working Papers 2014/14, Czech National Bank.
    181. Baumann, Alexendra & Wohlrabe, Klaus, 2019. "Publikationen von Wirtschaftsforschungsinstituten im deutschsprachigen Raum - Eine bibliometrische Analyse [Publications of Economic Research Insitutes in the German Speaking Area - A bibliometric ," MPRA Paper 92240, University Library of Munich, Germany.
    182. Tuhkuri, Joonas, 2016. "ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe," ETLA Reports 54, The Research Institute of the Finnish Economy.
    183. 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.
    184. 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).
    185. Botezat, Alina, 2017. "Austerity plan announcements and the impact on the employees’ wellbeing," Journal of Economic Psychology, Elsevier, vol. 63(C), pages 1-16.
    186. F. Kuchler & M. Bowman & M. Sweitzer & C. Greene, 2020. "Evidence from Retail Food Markets That Consumers Are Confused by Natural and Organic Food Labels," Journal of Consumer Policy, Springer, vol. 43(2), pages 379-395, June.
    187. Tsoyu Calvin Lin & Shih-Hsun Hsu, 2020. "Forecasting Housing Markets from Number of Visits to Actual Price Registration System," International Real Estate Review, Global Social Science Institute, vol. 23(4), pages 505-536.
    188. 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.
    189. Voraprapa Nakavachara & Nuarpear Lekfuangfu, 2017. "Predicting the Present Revisited: The Case of Thailand," PIER Discussion Papers 70, Puey Ungphakorn Institute for Economic Research.
    190. Florian Schaffner, 2015. "Predicting US bank failures with internet search volume data," ECON - Working Papers 214, Department of Economics - University of Zurich.
    191. Rodrigo Mulero & Alfredo Garcia-Hiernaux, 2023. "Forecasting unemployment with Google Trends: age, gender and digital divide," Empirical Economics, Springer, vol. 65(2), pages 587-605, August.
    192. Vozlyublennaia, Nadia, 2014. "Investor attention, index performance, and return predictability," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 17-35.
    193. Meshcheryakov, Artem & Winters, Drew B., 2022. "Retail investor attention and the limit order book: Intraday analysis of attention-based trading," International Review of Financial Analysis, Elsevier, vol. 81(C).
    194. 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.
    195. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Detecting Mortgage Delinquencies," IZA Discussion Papers 5895, Institute of Labor Economics (IZA).
    196. 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).
    197. Gomes, Pedro & Taamouti, Abderrahim, 2016. "In search of the determinants of European asset market comovements," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 103-117.
    198. Jun, Seung-Pyo & Yoo, Hyoung Sun & Choi, San, 2018. "Ten years of research change using Google Trends: From the perspective of big data utilizations and applications," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 69-87.
    199. Wang, Jue & Athanasopoulos, George & Hyndman, Rob J. & Wang, Shouyang, 2018. "Crude oil price forecasting based on internet concern using an extreme learning machine," International Journal of Forecasting, Elsevier, vol. 34(4), pages 665-677.

  14. 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).

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

    Cited by:

    1. 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.
    2. 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).
    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. 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.

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, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.

    Cited by:

    1. Askitas, Nikos, 2015. "Predicting Road Conditions with Internet Search," IZA Discussion Papers 9503, Institute of Labor Economics (IZA).
    2. 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).
    3. Silvia Peracchi, 2022. "The Migration Crisis in the Local News: Evidence from the French-Italian Border," CESifo Working Paper Series 10070, CESifo.
    4. 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.
    5. Pablo Pedraza & Ian Vollbracht, 2023. "General theory of data, artificial intelligence and governance," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    6. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    7. 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.
    8. 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".
    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. 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).

  4. 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. Askitas, Nikos, 2015. "Calling the Greek Referendum on the Nose with Google Trends," IZA Discussion Papers 9569, Institute of Labor Economics (IZA).
    2. 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.
    3. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    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. 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.
    6. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
    7. 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.
    8. 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.
    9. Botezat, Alina, 2017. "Austerity plan announcements and the impact on the employees’ wellbeing," Journal of Economic Psychology, Elsevier, vol. 63(C), pages 1-16.

  5. 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.
  6. 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.
  7. 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. 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.
    2. 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).
    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. 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.
    5. Askitas, Nikos & Zimmermann, Klaus F., 2009. "Googlemetrie und Arbeitsmarkt in der Wirtschaftskrise," IZA Standpunkte 17, Institute of Labor Economics (IZA).

  8. 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.
  9. 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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