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Web data and Applied Economics Pablo de Pedraza Lisbon 26 th March 2013.

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Presentation on theme: "Web data and Applied Economics Pablo de Pedraza Lisbon 26 th March 2013."— Presentation transcript:

1 Web data and Applied Economics Pablo de Pedraza Lisbon 26 th March 2013

2 Web data & Applied Economics 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data 2.2.- Non reactive data: Google econometrics 2.3.- Non reactive data: the twitter miner 3.- The Webdatanet scientific structure & activities 4.- Proposal

3 Web data & Applied Economics 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data 2.2.- Non reactive data: Google econometrics 2.3.- Non reactive data: The twitter miner 3.- The Webdatanet scientific structure & activities 4.- Proposal

4 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) Economic Integration National politicsWelfare system GLOBALIZATION TRILEMMA (Rodrik 2002)

5 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) Economic Integration National politicsWelfare system Markets without governance

6 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) Economic Integration National politicsWelfare system Markets without governance Protectionism

7 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) Economic Integration National politicsWelfare system Markets without governance Protectionism Global Federalism -Non-market global institutions -Tremendous difficulties -Variety of systems, views, regulations. -European experience -WB, ILO, WTO… -Political Sciences, sociology, economy, psychology -Central role of web data collection experts bc Global comparable data: WEB DATA

8 Web data & Applied Economics 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data 2.2.- Non reactive data: Google econometrics 2.3.- Non reactive data: the twitter miner 3.- The Webdatanet scientific structure & activities 4.- Proposal

9 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data Wage Indicator - 80 countries (Wages, labor conditions & preferences) - quick & cheap access (IZA Institute, Bonn) -large and growing amount of data Traditional flow is too slow Special campaigns aiming at specific groups under- represented Good qualities (Pedraza 2010, Pedraza & Martin 2013)

10 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data CVWS process

11 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data Compare WI & SES Subjective job insecurity Happiness determinants -WI Wages > SES Wages → Education -Same salary determinants -Good special campaigns -Good performance of PS weights (Pedraza et al. 2010) Theoretical model of SJI Corroborated for five EU countries (Pedraza & Bustillo 2009) - Corroborate happiness literature -New findings regarding -Labour -Crisis impact on H determinants Forthcoming as IZA Discussion Paper

12 Web data & Applied Economics 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data 2.2.- Non reactive data: Google econometrics 2.3.- Non reactive data: the twitter miner 3.- The Webdatanet scientific structure & activities 4.- Proposal

13 2.- Types and examples of web data 2.2.- Non reactive data: Google econometrics -Askitas & Zimmerman (2009) Google search data -Choi & Variant (2012) -Other sources of data on real time economic activity - Available: http://www.google.com/trends/correlatehttp://www.google.com/trends/correlate Timely and at continual basis Countries & sometimes regions -Find: -Strong correlation bt: search keywords & unemployment rates -Internet activity help to predict complex and fast changing conditions -Econometrics not yet tap into amount of info MasterCard, Federal Express, UPS, Intuit… -Search engines forecast other economic indicators: Automobiles sales, unemployment claims, travel destinations, comsumers confidence

14 Web data & Applied Economics 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data 2.2.- Non reactive data: Google econometrics 2.3.- Non reactive data: the twitter miner 3.- The Webdatanet scientific structure & activities 4.- Proposal

15 2.- Types and examples of web data 2.3.- Non reactive data: twitter miner -Reips and Garaizar (2011) http://maps.iscience.deusto.es/ -iScience Maps -Allows to test the effect of an specific event in twitter -Not yet tested it correlation with economic variables

16 Web data & Applied Economics 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data 2.2.- Non reactive data: Google econometrics 2.3.- Non reactive data: the twitter miner 3.- The Webdatanet scientific structure & activities 4.- Proposal

17 Web data & Applied Economics 3.- The Webdatanet scientific structure & activities 3.1.- Scientific Goal 3.2.- Members 3.3.- Organization: Working Groups and Task forces (WGs & TFs) 3.4.- Activities 3.5.- Next meetings

18 Web data & Applied Economics 3.- The Webdatanet scientific structure & activities 3.1.- Scientific Goal 3.2.- Members 3.3.- Organization: Working Groups and Task forces (WGs & TFs) 3.4.- Activities 3.5.- Next meetings

19 3.- The Webdatanet scientific structure & activities 3.1.- Scientific Goal Scientific goal -Address methodological issues of web-based data collection (surveys, experiments, tests, non- reactive data collection, and mobile Internet research) and foster its scientific usage. -Contribute to the theoretical and empirical foundations of web-based data collection, stimulate its integration into the entire research process (i-science), and enhance the integrity and legitimacy of these new forms of data collection.

20 Web data & Applied Economics 3.- The Webdatanet scientific structure & activities 3.1.- Scientific Goal 3.2.- Members 3.3.- Organization: Working Groups and Task forces (WGs & TFs) 3.4.- Activities 3.5.- Next meetings

21 3.- The Webdatanet scientific structure & activities 3.2.- Members (Researchers from EU but also outside the EU) -Universities -Data collection Institutes -Research Institutes -Private firms -Statistical Institutes -80 members, 29 countries

22 Web data & Applied Economics 3.- The Webdatanet scientific structure & activities 3.1.- Scientific Goal 3.2.- Members 3.3.- Organization: Working Groups and Task forces (WGs & TFs) 3.4.- Activities 3.5.- Next meetings

23 WGs & TFs WG1 QualityWG2 InnovationWG3 Implementation TF1 Measuring wages via web surveys (S. Steinmetz) TF2 Evaluating questionnaire quality (A. Slavec) TF3 Mixed modes & representativ. (A.Jonsdottir & K. Kalgraff) TF4 Internet Panels Europe (A. Scherpenzeel) TF6 New types of measurement (U. Reips) TF7 Webdatametrics Workshops (U. Reips & K. Kissau) TF8 Dissemination WG2 (U. Reips & A. Selkala) TF9 iScience portals (U. Reips) TF15 Non-reactive data (N. Fornara) TF19 Mobile research ( R. Pinter & A. Wijnant) TF20 Paradata (I. Andreadis) TF22 Elections, Facebook & Twitter (R. Vatrapu, L. Kaczmirek) TF10 TSE Categorization (F. Thorsdottir & S. Biffignandi) TF 11 How web change empirical world (S. Steinmetz & K. Manfreda) TF16 Selecting surveys (M. Revilla) TF17 Web data & Official Statistics (S. Biffignandi) TF21 GenPopWeb (G.Nicolas) TF23 Applied Economics and web data (P. Pedraza) TF14 Development & supervision of the web (F. Serrano & C. Zimmerman) TF12 Master in webdatametrics (Alberto Villacampa) TF18 Organization of Iceland meeting (F. Thorsdottir, A. Jonsdottir & V. Vesteinsdottir)

24 3.- The Webdatanet scientific structure & activities 3.3.- Organization: Working Groups and Task forces (WGs & TFs) http://www.ijis.net/ijis7_1/ijis7_1_supplement.pdf

25 Web data & Applied Economics 3.- The Webdatanet scientific structure & activities 3.1.- Scientific Goal 3.2.- Members 3.3.- Organization: Working Groups and Task forces (WGs & TFs) 3.4.- Activities 3.5.- Next meetings

26 WGs & TFs WG1 QualityWG2 InnovationWG3 Implementation TF1 Measuring wages via web surveys (S. Steinmetz) TF2 Evaluating questionnaire quality (A. Slavec) TF3 Mixed modes & representativ. (A.Jonsdottir & K. Kalgraff) TF4 Internet Panels Europe (A. Scherpenzeel) TF6 New types of measurement (U. Reips) TF7 Webdatametrics Workshops (U. Reips & K. Kissau) TF8 Dissemination WG2 (U. Reips & A. Selkala) TF9 iScience portals (U. Reips) TF15 Non-reactive data (N. Fornara) TF19 Mobile research ( R. Pinter & A. Wijnant) TF20 Paradata (I. Andreadis) TF22 Elections, Facebook & Twitter (R. Vatrapu, L. Kaczmirek) TF10 TSE Categorization (F. Thorsdottir & S. Biffignandi) TF 11 How web change empirical world (S. Steinmetz & K. Manfreda) TF16 Selecting surveys (M. Revilla) TF17 Web data & Official Statistics (S. Biffignandi) TF21 GenPopWeb (G.Nicolas) TF23 Applied Economics and web data (P. Pedraza) TF14 Development & supervision of the web (F. Serrano & C. Zimmerman) TF12 Master in webdatametrics (Alberto Villacampa) TF18 Organization of Iceland meeting (F. Thorsdottir, A. Jonsdottir & V. Vesteinsdottir) WGs & TFs can use: -Meetings -STSMs (2500€) -Training Schools (TS) (Ljubljana 10-12 of April)(Ljubljana 10-12 of April) -Webdatametrics Workshops (WW) Bergamo Webdatametrics Workshop I (WG2 & WG3), 22 and 23 January 2013 -Workshops (GOR workshops) -Involvement of ESR & PhD students (STSM, TS, WW, TFs...) -AIAS-WEBDATANET Working papers

27 WGs & TFs WG1 QualityWG2 InnovationWG3 Implementation TF1 Measuring wages via web surveys (S. Steinmetz) TF2 Evaluating questionnaire quality (A. Slavec) TF3 Mixed modes & representativ. (A.Jonsdottir & K. Kalgraff) TF4 Internet Panels Europe (A. Scherpenzeel) TF6 New types of measurement (U. Reips) TF7 Webdatametrics Workshops (U. Reips & K. Kissau) TF8 Dissemination WG2 (U. Reips & A. Selkala) TF9 iScience portals (U. Reips) TF15 Non-reactive data (N. Fornara) TF19 Mobile research ( R. Pinter & A. Wijnant) TF20 Paradata (I. Andreadis) TF22 Elections, Facebook & Twitter (R. Vatrapu, L. Kaczmirek) TF10 TSE Categorization (F. Thorsdottir & S. Biffignandi) TF 11 How web change empirical world (S. Steinmetz & K. Manfreda) TF16 Selecting surveys (M. Revilla) TF17 Web data & Official Statistics (S. Biffignandi) TF21 GenPopWeb (G.Nicolas) TF23 Applied Economics and web data (P. Pedraza) TF14 Development & supervision of the web (F. Serrano & C. Zimmerman) TF12 Master in webdatametrics (Alberto Villacampa) TF18 Organization of Iceland meeting (F. Thorsdottir, A. Jonsdottir & V. Vesteinsdottir) WGs & TFs can use: -Meetings -STSMs (2500€) -Training Schools (TS) (Ljubljana 10-12 of April)(Ljubljana 10-12 of April) -Webdatametrics Workshops (WW) Bergamo Webdatametrics Workshop I (WG2 & WG3), 22 and 23 January 2013 -Workshops (GOR workshops) -Involvement of ESR & PhD students (STSM, TS, WW, TFs...) -AIAS-WEBDATANET Working papers 1.- Increase interaction, communication and understanding between web surveyors, other web based data collection experts and analyses. 2.- State of the art from a multidisciplinary perspective. 3.- Identify frontiers of knowledge 4.- Creative thinking 5.- Theoretical foundations of web surveys take into account innovations INCREASE interaction, communication and understanding across WEBDATANET disciplines WEBDATAMETRICS “General concept that emerges from the existing diverse variety of disciplines related to web data collection methods and analyses. Putting this knowledge together webdatametrics aim to generate new knowledge to take advance of ICT to collect data for scientific proposes” TF12 Master in webdatametrics (Alberto Villacampa)

28 Web data & Applied Economics 3.- The Webdatanet scientific structure & activities 3.1.- Scientific Goal 3.2.- Members 3.3.- Organization: Working Groups and Task forces (WGs & TFs) 3.4.- Activities 3.5.- Next meetings

29 Webdatanet scientific coordination 4.- Next meeting and events -Mannheim 7th, 8th March 2013 - 1st Trainning School: Implementing high quality web survyes, Ljubljana 10-12 April 2013 -Core Group Meeting, Salamanca 18-19 April 2013 (maybe also some TFs) -Iceland September 2013 (TF meetings, Webdatametrics Workshop, Key note speaker) -Greece, Spring 2014 -Cypus, Autum 2014

30 Web data & Applied Economics 1.- Why quick, reliable and internationally comparable data 1.1.- The Globalization Trilemma (Rodrik 2002) 2.- Types and examples of web data 2.1.- Web surveys: the Wage Indicator data 2.2.- Non reactive data: Google econometrics & the twitter miner 2.3.- Testing and experimenting 3.- The Webdatanet scientific structure & activities 4.- Proposal

31 Proposal WG1 QualityWG2 InnovationWG3 Implementation TF1 Measuring wages via web surveys (S. Steinmetz) TF2 Evaluating questionnaire quality (A. Slavec) TF3 Mixed modes & representativ. (A.Jonsdottir & K. Kalgraff) TF4 Internet Panels Europe (A. Scherpenzeel) TF6 New types of measurement (U. Reips) TF7 Webdatametrics Workshops (U. Reips & K. Kissau) TF8 Dissemination WG2 (U. Reips & A. Selkala) TF9 iScience portals (U. Reips) TF15 Non-reactive data (N. Fornara) TF19 Mobile research ( R. Pinter & A. Wijnant) TF20 Paradata (I. Andreadis) TF22 Elections, Facebook & Twitter (R. Vatrapu, L. Kaczmirek) TF10 TSE Categorization (F. Thorsdottir & S. Biffignandi) TF 11 How web change empirical world (S. Steinmetz & K. Manfreda) TF16 Selecting surveys (M. Revilla) TF17 Web data & Official Statistics (S. Biffignandi) TF21 GenPopWeb (G.Nicolas) TF23 Applied Economics and web data (P. Pedraza) TF14 Development & supervision of the web (F. Serrano & C. Zimmerman) TF12 Master in webdatametrics (Alberto Villacampa) TF18 Organization of Iceland meeting (F. Thorsdottir, A. Jonsdottir & V. Vesteinsdottir) -Start testing simple models using Google & Wage Indicator -Organize a training school on Google data & others -STSM (PhD) -Join proposals -Participate in our meetings -Help in organizing: -http://www.iza.org/conference_files/worldb2013/call_for_papershttp://www.iza.org/conference_files/worldb2013/call_for_papers -http://openeconomics.net/events/workshop-june-2013/http://openeconomics.net/events/workshop-june-2013/

32 Visit www.webdatanet.eu & contact us pablodepedraza@usal.eswww.webdatanet.eu Pablo de Pedraza Lisbon March 26th, 2013

33 Muito Obrigado Lisbon March 26th, 2013


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