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The predictive power of Google searches in forecasting US unemployment
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- 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.
- Sebastian Doerr & Leonardo Gambacorta & José María Serena Garralda, 2021. "Big data and machine learning in central banking," BIS Working Papers 930, Bank for International Settlements.
- Falik Shear & Badar Nadeem Ashraf & Mohsin Sadaqat, 2020. "Are Investors’ Attention and Uncertainty Aversion the Risk Factors for Stock Markets? International Evidence from the COVID-19 Crisis," Risks, MDPI, vol. 9(1), pages 1-15, December.
- 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.
- Mihaela Simionescu & Javier Cifuentes-Faura, 2022. "Forecasting National and Regional Youth Unemployment in Spain Using Google Trends," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1187-1216, December.
- 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.
- 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.
- Knut Lehre Seip & Yunus Yilmaz & Michael Schröder, 2019. "Comparing Sentiment- and Behavioral-Based Leading Indexes for Industrial Production: When Does Each Fail?," Economies, MDPI, vol. 7(4), pages 1-18, October.
- Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024.
"Search and Predictability of Prices in the Housing Market,"
Management Science, INFORMS, vol. 70(1), pages 415-438, January.
- Timmermann, Allan & Møller, Stig & Pedersen, Thomas & Schütte, Erik Christian Montes, 2021. "Search and Predictability of Prices in the Housing Market," CEPR Discussion Papers 15875, C.E.P.R. Discussion Papers.
- Matteo Accornero & Mirko Moscatelli, 2018. "Listening to the buzz: social media sentiment and retail depositors' trust," Temi di discussione (Economic working papers) 1165, Bank of Italy, Economic Research and International Relations Area.
- 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.
- 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.
- Pijush Kanti Das & Prabir Kumar Das, 2024. "Improvement in Inflation Forecasting: Ensembling Text Mining with Macro Data in Machine Learning Models," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 16(6), pages 1-92, June.
- Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021.
"Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg,"
Forecasting, MDPI, vol. 3(4), pages 1-30, October.
- Fantazzini, Dean & Pushchelenko, Julia & Mironenkov, Alexey & Kurbatskii, Alexey, 2021. "Forecasting internal migration in Russia using Google Trends: Evidence from Moscow and Saint Petersburg," MPRA Paper 110452, University Library of Munich, Germany.
- 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).
- 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.
- Castelnuovo, Efrem & Tran, Trung Duc, 2017.
"Google It Up! A Google Trends-based Uncertainty index for the United States and Australia,"
Economics Letters, Elsevier, vol. 161(C), pages 149-153.
- Efrem Castelnuovo & Trung Duc Tran, 2017. "Google It Up! A Google Trends-based Uncertainty Index for the United States and Australia," CESifo Working Paper Series 6695, CESifo.
- Efrem Castelnuovo & Trung Duc Tran, 2018. "Google it up! A Google Trends-based Uncertainty Index for the United States and Australia," "Marco Fanno" Working Papers 0223, Dipartimento di Scienze Economiche "Marco Fanno".
- Efrem Castelnuovo & Trung Duc Tran, 2017. "Google It Up! A Google Trends-Based Uncertainty Index for the United States and Australia," Melbourne Institute Working Paper Series wp2017n27, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
- Castelnuovo, Efrem & Duc Tran, Trung, 2017. "Google It Up! A Google Trends-based Uncertainty Index for the United States and Australia," MPRA Paper 82297, University Library of Munich, Germany.
- Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
- Sarun Kamolthip, 2021.
"Macroeconomic Forecasting with LSTM and Mixed Frequency Time Series Data,"
PIER Discussion Papers
165, Puey Ungphakorn Institute for Economic Research.
- Sarun Kamolthip, 2021. "Macroeconomic forecasting with LSTM and mixed frequency time series data," Papers 2109.13777, arXiv.org.
- 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.
- Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
- Poza, Carlos & Monge, Manuel, 2020. "A real time leading economic indicator based on text mining for the Spanish economy. Fractional cointegration VAR and Continuous Wavelet Transform analysis," International Economics, Elsevier, vol. 163(C), pages 163-175.
- Chiara Sotis, 2021. "How do Google searches for symptoms, news and unemployment interact during COVID-19? A Lotka–Volterra analysis of google trends data," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(6), pages 2001-2016, December.
- Konstantinos N. Konstantakis & Despoina Paraskeuopoulou & Panayotis G. Michaelides & Efthymios G. Tsionas, 2021. "Bank deposits and Google searches in a crisis economy: Bayesian non‐linear evidence for Greece (2009–2015)," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5408-5424, October.
- 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.
- 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.
- Bentzen, Jeanet, 2020. "In Crisis, We Pray: Religiosity and the COVID-19 Pandemic," CEPR Discussion Papers 14824, C.E.P.R. Discussion Papers.
- Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Gonzalez-Fernandez, Marcos & Miffre, Joelle, 2020.
"Fear of hazards in commodity futures markets,"
Journal of Banking & Finance, Elsevier, vol. 119(C).
- Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Gonzalez-Fernandez, Marcos & Miffre, Joelle, 2019. "Fear of Hazards in Commodity Futures Markets," MPRA Paper 100528, University Library of Munich, Germany, revised 06 May 2020.
- Adrian Fernandez-Perez & Ana-Maria Fuertes & Marcos Gonzalez-Fernandez & Joelle Miffre, 2020. "Fear of Hazards in Commodity Futures Markets," Post-Print hal-02931680, HAL.
- Vera Z. Eichenauer & Ronald Indergand & Isabel Z. Martínez & Christoph Sax, 2022. "Obtaining consistent time series from Google Trends," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 694-705, April.
- Michele Costola & Matteo Iacopini & Carlo R. M. A. Santagiustina, 2020. "Public Concern and the Financial Markets during the COVID-19 outbreak," Papers 2005.06796, arXiv.org.
- Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
- Agnese Carella & Federica Ciocchetta & Valentina Michelangeli & Federico Maria Signoretti, 2020. "What can we learn about mortgage supply from online data?," Questioni di Economia e Finanza (Occasional Papers) 583, Bank of Italy, Economic Research and International Relations Area.
- Laurent Ferrara & Anna Simoni, 2023.
"When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
- Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
- Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print hal-03919944, HAL.
- Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
- Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
- Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
- Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
- 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).
- 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.
- Alexander Jung & Patrick Kuehl, 2021.
"Can central bank communication help to stabilise inflation expectations?,"
Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 298-321, July.
- Jung, Alexander & Kühl, Patrick, 2021. "Can central bank communication help to stabilise inflation expectations?," Working Paper Series 2547, European Central Bank.
- Behera, Sarthak & Sadana, Divya, 2022. "The Impact of Visibility on School Athletic Finances: An Empirical Analysis using Google Trends," MPRA Paper 114818, University Library of Munich, Germany.
- Matteo Iacopini & Carlo R.M.A. Santagiustina, 2021.
"Filtering the intensity of public concern from social media count data with jumps,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1283-1302, October.
- Matteo Iacopini & Carlo R. M. A. Santagiustina, 2020. "Filtering the intensity of public concern from social media count data with jumps," Papers 2012.13267, arXiv.org.
- Matteo Iacopini & Carlo Romano Marcello Alessandro Santagiustina, 2021. "Filtering the Intensity of Public Concern from Social Media Count Data with Jumps," Post-Print hal-04494229, HAL.
- Matteo Iacopini & Carlo Romano Marcello Alessandro Santagiustina, 2021. "Filtering the Intensity of Public Concern from Social Media Count Data with Jumps," SciencePo Working papers Main hal-04494229, HAL.
- Georgios Bampinas & Theodore Panagiotidis & Christina Rouska, 2019.
"Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil,"
Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 180-197, February.
- 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.
- Gillmann, Niels & Kim, Alisa, 2021. "Quantification of Economic Uncertainty: a deep learning approach," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242421, Verein für Socialpolitik / German Economic Association.
- Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2022.
"Does online salience predict charitable giving? Evidence from SMS text donations,"
Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 134-149.
- Carlo Perroni & Kimberley Ann Scharf & Oleksandr Talavera & Linh Vi, 2021. "Does Online Salience Predict Charitable Giving? Evidence from SMS Text Donations," CESifo Working Paper Series 9436, CESifo.
- Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2022. "Does Online Salience Predict Charitable Giving? Evidence from SMS Text Donations," CEPR Discussion Papers 17030, C.E.P.R. Discussion Papers.
- Eric Bax, 2019. "Computing a Data Dividend," Papers 1905.01805, arXiv.org, revised Jun 2019.
- García, Juan R. & Pacce, Matías & Rodrigo, Tomasa & Ruiz de Aguirre, Pep & Ulloa, Camilo A., 2021. "Measuring and forecasting retail trade in real time using card transactional data," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1235-1246.
- Daniel Borup & Erik Christian Montes Schütte, 2022.
"In Search of a Job: Forecasting Employment Growth Using Google Trends,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 186-200, January.
- 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.
- Tian, Yu-Xin & Zhang, Chuan, 2023. "An end-to-end deep learning model for solving data-driven newsvendor problem with accessibility to textual review data," International Journal of Production Economics, Elsevier, vol. 265(C).
- Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
- Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
- Fantazzini, Dean, 2020.
"Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries,"
Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
- Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," MPRA Paper 102315, University Library of Munich, Germany.
- Marcos González-Fernández & Carmen González-Velasco, 2019. "An approach to predict Spanish mortgage market activity using Google data," Economics and Business Letters, Oviedo University Press, vol. 8(4), pages 209-214.
- Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
- Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018.
"Nowcasting GDP Growth by Reading the Newspapers,"
Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 17-33.
- Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018. "Nowcasting GDP Growth by Reading Newspapers," Post-Print hal-03205161, HAL.
- Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018. "Nowcasting GDP Growth by Reading Newspapers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205161, HAL.
- 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.
- Götz, Thomas B. & Knetsch, Thomas A., 2017. "Google data in bridge equation models for German GDP," Discussion Papers 18/2017, Deutsche Bundesbank.
- Omid Zamani & Thomas Bittmann & Jens‐Peter Loy, 2024. "Does the internet bring food prices closer together? Exploring search engine query data in Iran," Journal of Agricultural Economics, Wiley Blackwell, vol. 75(2), pages 688-715, June.
- Ferrara, Laurent & Sheng, Xuguang Simon, 2022. "Guest editorial: Economic forecasting in times of COVID-19," International Journal of Forecasting, Elsevier, vol. 38(2), pages 527-528.
- Monge, Manuel & Claudio-Quiroga, Gloria & Poza, Carlos, 2024. "Chinese economic behavior in times of covid-19. A new leading economic indicator based on Google trends," International Economics, Elsevier, vol. 177(C).
- Niesert, Robin F. & Oorschot, Jochem A. & Veldhuisen, Christian P. & Brons, Kester & Lange, Rutger-Jan, 2020.
"Can Google search data help predict macroeconomic series?,"
International Journal of Forecasting, Elsevier, vol. 36(3), pages 1163-1172.
- 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.
- 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.
- Ilias Georgakopoulos, 2019. "Income and wealth inequality in Malta: evidence from micro data," CBM Working Papers WP/03/2019, Central Bank of Malta.
- Benedikt Maas, 2020.
"Short‐term forecasting of the US unemployment rate,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
- Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
- Caetano, Marco Antonio Leonel, 2021. "Political activity in social media induces forest fires in the Brazilian Amazon," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
- Per Nymand-Andersen, 2016. "Big data: the hunt for timely insights and decision certainty," IFC Working Papers 14, Bank for International Settlements.
- Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2021.
"Online Salience and Charitable Giving: Evidence from SMS Donations,"
CAGE Online Working Paper Series
536, Competitive Advantage in the Global Economy (CAGE).
- Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2021. "Online Salience and Charitable Giving : Evidence from SMS Donations," The Warwick Economics Research Paper Series (TWERPS) 1325, University of Warwick, Department of Economics.
- Cebrián, Eduardo & Domenech, Josep, 2024. "Addressing Google Trends inconsistencies," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
- 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).
- 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.
- Neto, David, 2021. "Are Google searches making the Bitcoin market run amok? A tail event analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
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- Afees A. Salisu & Ahamuefula E. Ogbonna & Idris Adediran, 2021. "Stock‐induced Google trends and the predictability of sectoral stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 327-345, March.
- Ferriani, Fabrizio & Gazzani, Andrea, 2022.
"Financial condition indices for emerging market economies: Can Google help?,"
Economics Letters, Elsevier, vol. 216(C).
- Fabrizio Ferriani & Andrea Gazzani, 2021. "Financial condition indices for emerging market economies: can Google help?," Questioni di Economia e Finanza (Occasional Papers) 653, Bank of Italy, Economic Research and International Relations Area.
- Brown, Alasdair & Reade, J. James & Vaughan Williams, Leighton, 2019. "When are prediction market prices most informative?," International Journal of Forecasting, Elsevier, vol. 35(1), pages 420-428.
- Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
- 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.
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- Necmettin Alpay Koçak, 2020. "The Role of Ecb Speeches in Nowcasting German Gdp," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2020(2), pages 05-20.
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"Forecasting tourist arrivals: Google Trends meets mixed-frequency data,"
Tourism Economics, , vol. 27(1), pages 129-148, February.
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"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.
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"The demand and supply of information about inflation,"
CIRANO Working Papers
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- Larson, William D. & Sinclair, Tara M., 2022.
"Nowcasting unemployment insurance claims in the time of COVID-19,"
International Journal of Forecasting, Elsevier, vol. 38(2), pages 635-647.
- William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," Working Papers 2020-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Aug 2020.
- William D. Larson & Tara M. Sinclair, 2020. "Nowcasting unemployment insurance claims in the time of COVID-19," CAMA Working Papers 2020-63, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," FHFA Staff Working Papers 20-02, Federal Housing Finance Agency.
- Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
- Federico Cingano & Marco Tonello, 2020.
"Law Enforcement, Social Control and Organized Crime: Evidence from Local Government Dismissals in Italy,"
Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(2), pages 221-254, July.
- Cingano, Federico & Tonello, Marco, 2020. "Law enforcement, social control and organized crime. Evidence from local government dismissals in Italy," GLO Discussion Paper Series 458, Global Labor Organization (GLO).
- Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022.
"Making text count: Economic forecasting using newspaper text,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
- Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
- Philip ME Garboden, 2019. "Sources and Types of Big Data for Macroeconomic Forecasting," Working Papers 2019-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
- Puhr, Harald & Müllner, Jakob, 2024. "Vox populi, vox dei: A concept and measure for grassroots socio-political risk using Google Trends," Journal of International Management, Elsevier, vol. 30(2).
- Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
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