Hal Varian
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:- Hal Varian, 1992.
"Mathematica Notebooks by Hal Varian,"
Mathematica codes
varian, .
Mentioned in:
- Dica de Economia Computacional
by Marcelo de Oliveira Passos in Theoria et Oeconomia on 2009-06-16 02:36:00
- Dica de Economia Computacional
- Varian, Hal R., 1996.
"Mathematica for economists,"
Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 11, pages 489-505,
Elsevier.
Mentioned in:
- Software for Research
by Anton Tarasenko in Economics and Development on 2016-01-15 01:06:24
- Software for Research
- Author Profile
- Ranking Economists as of December 2015
by Matthew Kahn in Environmental and Urban Economics on 2016-01-07 22:27:00 - Peers at Work as of August 2016
by Matthew Kahn in Environmental and Urban Economics on 2016-09-04 19:36:00 - The PHD Economics Cohort from 1993
by Matthew Kahn in Environmental and Urban Economics on 2017-12-05 05:11:00 - REPEC December 2018 Academic Economic Report Cards
by Matthew Kahn in Environmental and Urban Economics on 2019-01-04 01:16:00
- Ranking Economists as of December 2015
Wikipedia or ReplicationWiki mentions
(Only mentions on Wikipedia that link back to a page on a RePEc service)- Hyunyoung Choi & Hal Varian, 2012.
"Predicting the Present with Google Trends,"
The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
Mentioned in:
- Predicting the Present with Google Trends (Economic Record 2012) in ReplicationWiki ()
Working papers
- Hal Varian, 2018.
"Artificial Intelligence, Economics, and Industrial Organization,"
NBER Working Papers
24839, National Bureau of Economic Research, Inc.
- Hal Varian, 2018. "Artificial Intelligence, Economics, and Industrial Organization," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 399-419, National Bureau of Economic Research, Inc.
Cited by:
- Johanna Deperi & Ludovic Dibiaggio & Mohamed Keita & Lionel Nesta, 2023.
"Ideas Without Scale in French Artificial Intelligence Innovations,"
Post-Print
hal-04144817, HAL.
- Johanna Deperi & Ludovic Dibiaggio & Mohamed Keita & Lionel Nesta, 2023. "Ideas Without Scale in French Artificial Intelligence Innovations," SciencePo Working papers Main hal-04144817, HAL.
- Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021.
"Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data,"
Working Papers of Department of Management, Strategy and Innovation, Leuven
674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
- Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2021. "Artificial intelligence and industrial innovation: Evidence from firm-level data," ZEW Discussion Papers 21-036, ZEW - Leibniz Centre for European Economic Research.
- Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Economics, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
- Peipei Qi & Dandan Sun & Can Xu & Qiang Li & Qi Wang, 2023. "Can Data Elements Promote the High-Quality Development of China’s Economy?," Sustainability, MDPI, vol. 15(9), pages 1-19, April.
- Nan Zhou & Li Zhang & Shijian Li & Zhijian Wang, 2018. "Algorithmic Collusion in Cournot Duopoly Market: Evidence from Experimental Economics," Papers 1802.08061, arXiv.org.
- Alexandra Tsvetkova & Rudiger Ahrend & Joaquim Oliveira Martins & Alexander C. Lembcke & Polina Knutsson & Dylan Jong & Nikolaos Terzidis, 2020. "The spatial dimension of productivity: Connecting the dots across industries, firms and places," OECD Regional Development Working Papers 2020/01, OECD Publishing.
- Hanson, Gordon H., 2023.
"Immigration and Regional Specialization in AI,"
SocArXiv
9a45d, Center for Open Science.
- Gordon H. Hanson, 2021. "Immigration and Regional Specialization in AI," NBER Working Papers 28671, National Bureau of Economic Research, Inc.
- David Bounie & Antoine Dubus & Patrick Waelbroeck, 2020.
"Market for Information and Selling Mechanisms,"
CESifo Working Paper Series
8307, CESifo.
- David Bounie & Antoine Dubus & Patrick Waelbroeck, 2022. "Market for Information and Selling Mechanisms," CER-ETH Economics working paper series 22/367, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
- David Bounies & Antoine Dubus & Patrick Waelbroeck, 2020. "Market for Information and Selling Mechanisms," Working Papers ECARES 2020-07, ULB -- Universite Libre de Bruxelles.
- Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2021.
"Data Brokers Co-Opetition,"
Working Papers
202101, University of Liverpool, Department of Economics.
- Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2022. "Data brokers co-opetition [The impact of big data on firm performance: an empirical investigation]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 820-839.
- Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2019. "Data Brokers Co-Opetition," CESifo Working Paper Series 7523, CESifo.
- Stephanie Assad & Robert Clark & Daniel Ershov & Lei Xu, 2020.
"Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market,"
Working Paper
1438, Economics Department, Queen's University.
- Stephanie Assad & Robert Clark & Daniel Ershov & Lei Xu, 2020. "Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market," CESifo Working Paper Series 8521, CESifo.
- Nambisan, Satish & Wright, Mike & Feldman, Maryann, 2019. "The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes," Research Policy, Elsevier, vol. 48(8), pages 1-1.
- David Bounie & Antoine Dubus & Patrick Waelbroeck, 2021. "Competition and Mergers with Strategic Data Intermediaries," CESifo Working Paper Series 9339, CESifo.
- Liu, Yuandan & Tang, Tingfeng & Ah, Ranran & Luo, Limin, 2024. "Has digital technology promoted the restructuring of global value chains? Evidence from China," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 269-280.
- Ayoubi, Charles, 2020. "Machine learning in healthcare: Mirage or miracle for breaking the costs dead-lock?," Thesis Commons tc24d, Center for Open Science.
- Ajay K. Agrawal & Joshua S. Gans & Avi Goldfarb, 2018.
"Economic Policy for Artificial Intelligence,"
Working Papers
id:12823, eSocialSciences.
- Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
- Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2018. "Economic Policy for Artificial Intelligence," NBER Chapters, in: Innovation Policy and the Economy, Volume 19, pages 139-159, National Bureau of Economic Research, Inc.
- Avi Goldfarb & Joshua Gans & Ajay Agrawal, 2018. "Economic Policy for Artificial Intelligence," Working Papers id:12798, eSocialSciences.
- Ajay K. Agrawal & Joshua S. Gans & Avi Goldfarb, 2018. "Economic Policy for Artificial Intelligence," NBER Working Papers 24690, National Bureau of Economic Research, Inc.
- Wendy C.Y. LI & NIREI Makoto & YAMANA Kazufumi, 2019.
"Value of Data: There's No Such Thing as a Free Lunch in the Digital Economy,"
Discussion papers
19022, Research Institute of Economy, Trade and Industry (RIETI).
- Wendy C.Y. Li & Makoto Nirei & Kazufumi Yamana, 2018. "Value of Data: There’s No Such Thing as a Free Lunch in the Digital Economy," BEA Working Papers 0164, Bureau of Economic Analysis.
- Constance E. Helfat & Aseem Kaul & David J. Ketchen & Jay B. Barney & Olivier Chatain & Harbir Singh, 2023. "Renewing the resource‐based view: New contexts, new concepts, and new methods," Strategic Management Journal, Wiley Blackwell, vol. 44(6), pages 1357-1390, June.
- Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
- Wang, Linhui & Chen, Qi & Dong, Zhiqing & Cheng, Lu, 2024. "The role of industrial intelligence in peaking carbon emissions in China," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
- Jeremy K. Nguyen & Adam Karg & Abbas Valadkhani & Heath McDonald, 2022. "Predicting individual event attendance with machine learning: a ‘step-forward’ approach," Applied Economics, Taylor & Francis Journals, vol. 54(27), pages 3138-3153, June.
- Norbäck, Pehr-Johan & Persson, Lars, 2023. "Why Big Data Can Make Creative Destruction More Creative – But Less Destructive," Working Paper Series 1454, Research Institute of Industrial Economics.
- Haefner, Naomi & Wincent, Joakim & Parida, Vinit & Gassmann, Oliver, 2021. "Artificial intelligence and innovation management: A review, framework, and research agenda✰," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
- Ali Sunyaev & Niclas Kannengießer & Roman Beck & Horst Treiblmaier & Mary Lacity & Johann Kranz & Gilbert Fridgen & Ulli Spankowski & André Luckow, 2021. "Token Economy," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 457-478, August.
- Guy Aridor & Yishay Mansour & Aleksandrs Slivkins & Zhiwei Steven Wu, 2020. "Competing Bandits: The Perils of Exploration Under Competition," Papers 2007.10144, arXiv.org, revised Oct 2024.
- Yingying Lu & Yixiao Zhou, 2021. "A review on the economics of artificial intelligence," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1045-1072, September.
- Aur'elien Ouattara & Matthieu Bult'e & Wan-Ju Lin & Philipp Scholl & Benedikt Veit & Christos Ziakas & Florian Felice & Julien Virlogeux & George Dikos, 2021. "Scalable Econometrics on Big Data -- The Logistic Regression on Spark," Papers 2106.10341, arXiv.org.
- Pehr-Johan Norbäck & Lars Persson, 2024. "Why generative AI can make creative destruction more creative but less destructive," Small Business Economics, Springer, vol. 63(1), pages 349-377, June.
- Li, Juan & Ma, Shaoqi & Qu, Yi & Wang, Jiamin, 2023. "The impact of artificial intelligence on firms’ energy and resource efficiency: Empirical evidence from China," Resources Policy, Elsevier, vol. 82(C).
- Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2021.
"Exclusive Data, Price Manipulation and Market Leadership,"
Working Papers
202102, University of Liverpool, Department of Economics.
- Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2019. "Exclusive Data, Price Manipulation and Market Leadership," CESifo Working Paper Series 7853, CESifo.
- David Bounie & Antoine Dubus & Patrick Waelbroeck, 2023. "Competition Between Strategic Data Intermediaries with Implications for Merger Policy," Working Papers hal-03336520, HAL.
- Steffen, Nico & Wiewiorra, Lukas & Kroon, Peter, 2021. "Wettbewerb und Regulierung in der Plattform- und Datenökonomie," WIK Discussion Papers 481, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH.
- Martino Banchio & Giacomo Mantegazza, 2022. "Artificial Intelligence and Spontaneous Collusion," Papers 2202.05946, arXiv.org, revised Sep 2023.
- Lei Guo & Luying Xu, 2021. "The Effects of Digital Transformation on Firm Performance: Evidence from China’s Manufacturing Sector," Sustainability, MDPI, vol. 13(22), pages 1-18, November.
- Nguyen Van Phuoc, 2022. "The Critical Factors Impacting Artificial Intelligence Applications Adoption in Vietnam: A Structural Equation Modeling Analysis," Economies, MDPI, vol. 10(6), pages 1-16, June.
- Michael I.C. Nwogugu, 2019. "Complex Systems, Multi-Sided Incentives and Risk Perception in Companies," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-44704-3, March.
- Knudsen, Eirik Sjåholm & Lien, Lasse B. & Timmermans, Bram & Belik, Ivan & Pandey, Sujit, 2021. "Stability in turbulent times? The effect of digitalization on the sustainability of competitive advantage," Journal of Business Research, Elsevier, vol. 128(C), pages 360-369.
- Steven L. Scott & Hal R. Varian, 2013.
"Bayesian Variable Selection for Nowcasting Economic Time Series,"
NBER Working Papers
19567, National Bureau of Economic Research, Inc.
- Steven L. Scott & Hal R. Varian, 2015. "Bayesian Variable Selection for Nowcasting Economic Time Series," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 119-135, National Bureau of Economic Research, Inc.
Cited by:
- 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.
- Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
- 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.
- Nivín, Rafael & Pérez, Fernando, 2019.
"Estimación de un Índice de Condiciones Financieras para el Perú,"
Working Papers
2019-006, Banco Central de Reserva del Perú.
- Nivín, Rafael & Pérez, Fernando, 2019. "Estimación de un Índice de Condiciones Financieras para el Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 37, pages 49-64.
- Juan Tenorio & Wilder Pérez, 2023. "GDP nowcasting with Machine Learning and Unstructured Data to Peru," Working Papers 197, Peruvian Economic Association.
- 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," Working Papers hal-04159714, HAL.
- 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, 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.
- 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, 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, 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.
- Petrova, Diana & Trunin, Pavel, 2020. "Revealing the mood of economic agents based on search queries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 71-87.
- Obryan Poyser, 2017. "Exploring the determinants of Bitcoin's price: an application of Bayesian Structural Time Series," Papers 1706.01437, arXiv.org.
- Hulya Bakirtas & Vildan Gulpinar Demirci, 2022. "Can Google Trends data provide information on consumer’s perception regarding hotel brands?," Information Technology & Tourism, Springer, vol. 24(1), pages 57-83, March.
- Takahiro Yabe & Yunchang Zhang & Satish Ukkusuri, 2020. "Quantifying the Economic Impact of Extreme Shocks on Businesses using Human Mobility Data: a Bayesian Causal Inference Approach," Papers 2004.11121, arXiv.org.
- Liran Einav & Jonathan D. Levin, 2013.
"The Data Revolution and Economic Analysis,"
NBER Working Papers
19035, National Bureau of Economic Research, Inc.
- Liran Einav & Jonathan Levin, 2013. "The Data Revolution and Economic Analysis," NBER Chapters, in: Innovation Policy and the Economy, Volume 14, pages 1-24, National Bureau of Economic Research, Inc.
- Liran Einav & Jonathan Levin, 2014. "The Data Revolution and Economic Analysis," Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 1-24.
- Liran Einav & Johnathan Levin, 2013. "The Data Revolution and Economic Analysis," Discussion Papers 12-017, Stanford Institute for Economic Policy Research.
- Pérez, Fernando, 2018. "Nowcasting Peruvian GDP using Leading Indicators and Bayesian Variable Selection," Working Papers 2018-010, Banco Central de Reserva del Perú.
- Oosthuizen, A.M. & Inglesi-Lotz, R., 2022. "The impact of policy priority flexibility on the speed of renewable energy adoption," Renewable Energy, Elsevier, vol. 194(C), pages 426-438.
- Obryan Poyser, 2019. "Exploring the dynamics of Bitcoin’s price: a Bayesian structural time series approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 29-60, March.
- Yumin Shu & Zhongying Qi, 2020. "The Effect of Market-Oriented Government Fiscal Expenditure on the Evolution of Industrial Structure: Evidence from Shenzhen, China," Sustainability, MDPI, vol. 12(9), pages 1-17, May.
- M. Elshendy & A. Fronzetti Colladon & E. Battistoni & P. A. Gloor, 2021. "Using four different online media sources to forecast the crude oil price," Papers 2105.09154, arXiv.org.
- 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.
- Mr. Serhan Cevik, 2020. "Where Should We Go? Internet Searches and Tourist Arrivals," IMF Working Papers 2020/022, International Monetary Fund.
- Vegard H ghaug Larsen & Leif Anders Thorsrud, 2018.
"Business cycle narratives,"
Working Papers
No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Business Cycle Narratives," CESifo Working Paper Series 7468, CESifo.
- Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
- Ondrej Bednar, 2021. "The Causal Impact of the Rapid Czech Interest Rate Hike on the Czech Exchange Rate Assessed by the Bayesian Structural Time Series Model," International Journal of Economic Sciences, European Research Center, vol. 10(2), pages 1-17, December.
- Bleher, Johannes & Dimpfl, Thomas, 2022. "Knitting Multi-Annual High-Frequency Google Trends to Predict Inflation and Consumption," Econometrics and Statistics, Elsevier, vol. 24(C), pages 1-26.
- Zhang, Yunchang & Fricker, Jon D., 2021. "Quantifying the impact of COVID-19 on non-motorized transportation: A Bayesian structural time series model," Transport Policy, Elsevier, vol. 103(C), pages 11-20.
- 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.
- Hal Varian, 2021. "Economics at Google," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(4), pages 195-199, October.
- Siwen Zhou, 2021. "Exploring the driving forces of the Bitcoin currency exchange rate dynamics: an EGARCH approach," Empirical Economics, Springer, vol. 60(2), pages 557-606, February.
- Zhou, Siwen, 2018. "Exploring the Driving Forces of the Bitcoin Exchange Rate Dynamics: An EGARCH Approach," MPRA Paper 89445, University Library of Munich, Germany.
- Lu, Quanying & Li, Yuze & Chai, Jian & Wang, Shouyang, 2020. "Crude oil price analysis and forecasting: A perspective of “new triangle”," Energy Economics, Elsevier, vol. 87(C).
- Christoph F. Kurz & Martin Rehm & Rolf Holle & Christina Teuner & Michael Laxy & Larissa Schwarzkopf, 2019. "The effect of bariatric surgery on health care costs: A synthetic control approach using Bayesian structural time series," Health Economics, John Wiley & Sons, Ltd., vol. 28(11), pages 1293-1307, November.
- Z. B. Ön & A. M. Greaves & S. Akçer-Ön & M. S. Özeren, 2021. "A Bayesian test for the 4.2 ka BP abrupt climatic change event in southeast Europe and southwest Asia using structural time series analysis of paleoclimate data," Climatic Change, Springer, vol. 165(1), pages 1-19, March.
- Tripathi, Abhinava & Pandey, Ashish, 2021. "Information dissemination across global markets during the spread of COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 103-115.
- Dolan Antenucci & Michael Cafarella & Margaret Levenstein & Christopher Ré & Matthew D. Shapiro, 2014. "Using Social Media to Measure Labor Market Flows," NBER Working Papers 20010, National Bureau of Economic Research, Inc.
- Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
- C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.
- Lolić, Ivana & Matošec, Marina & Sorić, Petar, 2024. "DIY google trends indicators in social sciences: A methodological note," Technology in Society, Elsevier, vol. 77(C).
- Feroze, Navid, 2020. "Forecasting the patterns of COVID-19 and causal impacts of lockdown in top five affected countries using Bayesian Structural Time Series Models," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
- Alessandro Acquisti & Hal R. Varian, 2002.
"Contidioning Prices on Purchase History,"
Microeconomics
0210001, University Library of Munich, Germany.
- Alessandro Acquisti & Hal R. Varian, 2005. "Conditioning Prices on Purchase History," Marketing Science, INFORMS, vol. 24(3), pages 367-381, May.
Cited by:
- Krista J. Li & Sanjay Jain, 2016. "Behavior-Based Pricing: An Analysis of the Impact of Peer-Induced Fairness," Management Science, INFORMS, vol. 62(9), pages 2705-2721, September.
- Potoglou, Dimitris & Palacios, Juan & Feijoo, Claudio & Gómez Barroso, Jose-Luis, 2015. "The supply of personal information: A study on the determinants of information provision in e-commerce scenarios," 26th European Regional ITS Conference, Madrid 2015 127174, International Telecommunications Society (ITS).
- Wang, Yu & Li, Minqiang & Feng, Haiyang & Feng, Nan, 2023. "Which is better for competing firms with quality increasing: behavior-based price discrimination or uniform pricing?," Omega, Elsevier, vol. 118(C).
- Steven M. Shugan, 2008. "Editorial—Introduction to the Special Classics Issue," Marketing Science, INFORMS, vol. 27(1), pages 9-11, 01-02.
- Kummer, Michael & Schulte, Patrick, 2014. "Money and privacy: Android market evidence," ZEW Discussion Papers 14-131, ZEW - Leibniz Centre for European Economic Research.
- Pavan, Alessandro & Calzolari, Giacomo, 2009.
"Sequential contracting with multiple principals,"
Journal of Economic Theory, Elsevier, vol. 144(2), pages 503-531, March.
- Giacomo Calzolari & Alessandro Pavan, 2007. "Sequential Contracting with Multiple Principals," Discussion Papers 1457, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Pavan, Alessandro & Calzolari, Giacomo, 2007. "Sequential Contracting with Multiple Principals," CEPR Discussion Papers 6562, C.E.P.R. Discussion Papers.
- Giacomo Calzolari & Alessandro Pavan, 2008. "Sequential Contracting with Multiple Principals," Discussion Papers 1499, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Chongwoo Choe & Noriaki Matsushima, 2021.
"Behavior-Based Price Discrimination and Product Choice,"
Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 58(2), pages 263-273, March.
- Chongwoo Choe & Noriaki Matsushima, 2020. "Behavior-Based Price Discrimination and Product Choice," ISER Discussion Paper 1079, Institute of Social and Economic Research, Osaka University.
- Shota Ichihashi, 2020.
"Online Privacy and Information Disclosure by Consumers,"
American Economic Review, American Economic Association, vol. 110(2), pages 569-595, February.
- Shota Ichihashi, 2019. "Online Privacy and Information Disclosure by Consumers," Staff Working Papers 19-22, Bank of Canada.
- Noskova, Victoriia, 2021. "Voice assistants as gatekeepers for consumption? How information intermediaries shape competition," Ilmenau Economics Discussion Papers 161, Ilmenau University of Technology, Institute of Economics.
- Caleb S. Fuller, 2018. "Privacy law as price control," European Journal of Law and Economics, Springer, vol. 45(2), pages 225-250, April.
- Michael Kummer & Patrick Schulte, 2019.
"When Private Information Settles the Bill: Money and Privacy in Google’s Market for Smartphone Applications,"
Management Science, INFORMS, vol. 65(8), pages 3470-3494, August.
- Kummer, Michael E. & Schulte, Patrick, 2016. "When private information settles the bill: Money and privacy in Google's market for smartphone applications," ZEW Discussion Papers 16-031, ZEW - Leibniz Centre for European Economic Research.
- Vidyanand Choudhary & Anindya Ghose & Tridas Mukhopadhyay & Uday Rajan, 2005. "Personalized Pricing and Quality Differentiation," Management Science, INFORMS, vol. 51(7), pages 1120-1130, July.
- Satyajit Chatterjee & Dean Corbae & Kyle Dempsey & José-Víctor Ríos-Rull, 2020.
"A Quantitative Theory of the Credit Score,"
Working Papers
770, Federal Reserve Bank of Minneapolis.
- Satyajit Chatterjee & Dean Corbae & Kyle Dempsey & José‐Víctor Ríos‐Rull, 2023. "A Quantitative Theory of the Credit Score," Econometrica, Econometric Society, vol. 91(5), pages 1803-1840, September.
- Satyajit Chatterjee & Dean Corbae & Kyle P. Dempsey & José-Víctor Ríos-Rull, 2020. "A Quantitative Theory of the Credit Score," NBER Working Papers 27671, National Bureau of Economic Research, Inc.
- Satyajit c & Dean Corbae & Kyle Dempsey & Jose-Victor Rios-Rull, 2020. "A Quantitative Theory of the Credit Score," PIER Working Paper Archive 20-030, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Satyajit Chatterjee & Dean Corbae & Kyle Dempsey & José-Víctor Ríos-Rull, 2020. "A Quantitative Theory of the Credit Score," Working Papers 20-39, Federal Reserve Bank of Philadelphia.
- Flavio Pino, 2022. "The microeconomics of data – a survey," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 635-665, September.
- Stefano Colombo & Aldo Pignataro, 2022. "Information accuracy and collusion," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(3), pages 638-656, August.
- Florian Hoffmann & Roman Inderst & Marco Ottaviani, 2013. "Hypertargeting, Limited Attention, and Privacy: Implications for Marketing and Campaigning," Working Papers 479, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Tatiana V. Komarova & Denis Nekipelov & Evgeny Yakovlev, 2011.
"Identification, data combination and the risk of disclosure,"
CeMMAP working papers
CWP38/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Komarova, Tatiana & Nekipelov, Denis & Yakovlev, Evgeny, 2018. "Identification, data combination and the risk of disclosure," LSE Research Online Documents on Economics 79384, London School of Economics and Political Science, LSE Library.
- Tatiana Komarova & Denis Nekipelov & Evgeny Yakovlev, 2018. "Identification, data combination, and the risk of disclosure," Quantitative Economics, Econometric Society, vol. 9(1), pages 395-440, March.
- Bruno Jullien & Markus Reisinger & Patrick Rey, 2022.
"Personalized Pricing and Distribution Strategies,"
Working Papers
hal-03632634, HAL.
- Jullien, Bruno & Reisinger, Markus & Rey, Patrick, 2022. "Personalized Pricing and Distribution Strategies," CEPR Discussion Papers 17139, C.E.P.R. Discussion Papers.
- Bruno Jullien & Markus Reisinger & Patrick Rey, 2023. "Personalized Pricing and Distribution Strategies," Management Science, INFORMS, vol. 69(3), pages 1687-1702, March.
- Jullien, Bruno & Reisinger, Markus & Rey, Patrick, 2019. "Personalized Pricing and Distribution Strategies," TSE Working Papers 19-995, Toulouse School of Economics (TSE), revised Mar 2022.
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ces0202, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics.
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"Analyzing Cost Efficient Production Behavior Under Economies of Scope: A Nonparametric Methodology,"
IZA Discussion Papers
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"Nonparametric tests of collectively rational consumption behavior: An integer programming procedure,"
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"Revealed Preference Analysis with Normal Goods: Application to Cost-of-Living Indices,"
American Economic Journal: Microeconomics, American Economic Association, vol. 12(3), pages 165-188, August.
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"Bayesian Analysis for a Theory of Random Consumer Demand: The Case of Indivisible Goods,"
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"Efficiency Of Infrastructure: The Case Of Container Ports,"
Anais do XXXIV Encontro Nacional de Economia [Proceedings of the 34th Brazilian Economics Meeting]
124, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
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"Group Consumption with Caring Individuals,"
Working Papers ECARES
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"The Effects of Allowance Price on Energy Demand under a Personal Carbon Trading Scheme,"
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"Testable implications of general equilibrium models: An integer programming approach,"
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"How Efficient is Public Spending in Education?,"
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"Nonparametric Production Analysis under Alternative Price Conditions,"
Public Economics Working Paper Series
ces0105, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics.
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"Commitment in intertemporal household consumption: a revealed preference analysis,"
2011 Meeting Papers
251, Society for Economic Dynamics.
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"A Measure of Rationality and Welfare,"
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"Technical and Economic Efficiency Measures under Short Run Profit Maximizing Behavior,"
Discussion Papers (REL - Recherches Economiques de Louvain)
2010022, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
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"Is utility transferable? a revealed preference analysis,"
Theoretical Economics, Econometric Society, vol. 10(1), January.
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"Nonparametric Analysis of Household Labor Supply: Goodness of Fit and Power of the Unitary and the Collective Model,"
The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 267-274, May.
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Working Papers of Department of Economics, Leuven
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Articles
- Hal R. Varian, 2012.
"Revealed Preference and its Applications,"
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Cited by:
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- Simon GB Cowan, 2013. "Welfare-increasing third-degree price discrimination," Economics Series Working Papers 652, University of Oxford, Department of Economics.
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"Labour Supply models,"
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- Aluma Dembo & Shachar Kariv & Matthew Polisson & John K.-H. Quah, 2021.
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VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order
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Software components
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Sorry, no citations of software components recorded.
Chapters
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