Statistics and Computing: Having an Impact
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Publishing and Promotion in Economics: the Curse of the Top Five
Publishing and Promotion in Economics: The Curse of the Top Five James J. Heckman 2017 AEA Annual Meeting Chicago, IL January 7th, 2017 Heckman Curse of the Top Five Top 5 Influential, But Far From Sole Source of Influence or Outlet for Creativity Heckman Curse of the Top Five Table 1: Ranking of 2, 5 and 10 Year Impact Factors as of 2015 Rank 2 Years 5 Years 10 Years 1. JEL JEL JEL 2. QJE QJE QJE 3. JOF JOF JOF 4. JEP JEP JPE 5. ReStud JPE JEP 6. ECMA AEJae ECMA 7. AEJae ECMA AER 8. AER AER ReStud 9. JPE ReStud JOLE 10. JOLE AEJma EJ 11. AEJep AEJep JHR 12. AEJma EJ JOE 13. JME JOLE JME 14. EJ JHR HE 15. HE JME RED 16. JHR HE EER 17. JOE JOE - 18. AEJmi AEJmi - 19. RED RED - 20. EER EER - Note: Definition of abbreviated names: JEL - Journal of Economic Literature, JOF - Journal of Finance, JEP - Journal of Economic Perspectives, AEJae-American Economic Journal Applied Economics, AER - American Economic Review, JOLE-Journal of Labor Economics, AEJep-American Economic Journal Economic Policy, AEJma-American Economic Journal Macroeconomics, JME-Journal of Monetary Economics, EJ-Economic Journal, HE-Health Economics, JHR-Journal of Human Resources, JOE-Journal of Econometrics, AEJmi-American Economic Journal Microeconomics, RED-Review of Economic Dynamics, EER-European Economic Review; Source: Journal Citation Reports (Thomson Reuters, 2016). Heckman Curse of the Top Five Figure 1: Articles Published in Last 10 years by RePEc's T10 Authors (Last 10 Years Ranking) (a) T10 Authors (Unadjusted) (b) T10 Authors (Adjusted) Prop. -
Report on Statistical Disclosure Limitation Methodology
STATISTICAL POLICY WORKING PAPER 22 (Second version, 2005) Report on Statistical Disclosure Limitation Methodology Federal Committee on Statistical Methodology Originally Prepared by Subcommittee on Disclosure Limitation Methodology 1994 Revised by Confidentiality and Data Access Committee 2005 Statistical and Science Policy Office of Information and Regulatory Affairs Office of Management and Budget December 2005 The Federal Committee on Statistical Methodology (December 2005) Members Brian A. Harris-Kojetin, Chair, Office of William Iwig, National Agricultural Management and Budget Statistics Service Wendy L. Alvey, Secretary, U.S. Census Arthur Kennickell, Federal Reserve Board Bureau Nancy J. Kirkendall, Energy Information Lynda Carlson, National Science Administration Foundation Susan Schechter, Office of Management and Steven B. Cohen, Agency for Healthcare Budget Research and Quality Rolf R. Schmitt, Federal Highway Steve H. Cohen, Bureau of Labor Statistics Administration Lawrence H. Cox, National Center for Marilyn Seastrom, National Center for Health Statistics Education Statistics Robert E. Fay, U.S. Census Bureau Monroe G. Sirken, National Center for Health Statistics Ronald Fecso, National Science Foundation Nancy L. Spruill, Department of Defense Dennis Fixler, Bureau of Economic Analysis Clyde Tucker, Bureau of Labor Statistics Gerald Gates, U.S. Census Bureau Alan R. Tupek, U.S. Census Bureau Barry Graubard, National Cancer Institute G. David Williamson, Centers for Disease Control and Prevention Expert Consultant Robert Groves, University of Michigan and Joint Program in Survey Methodology Preface The Federal Committee on Statistical Methodology (FCSM) was organized by the Office of Management and Budget (OMB) in 1975 to investigate issues of data quality affecting Federal statistics. Members of the committee, selected by OMB on the basis of their individual expertise and interest in statistical methods, serve in a personal capacity rather than as agency representatives. -
Alberto Abadie
ALBERTO ABADIE Office Address Massachusetts Institute of Technology Department of Economics 50 Memorial Drive Building E52, Room 546 Cambridge, MA 02142 E-mail: [email protected] Academic Positions Massachusetts Institute of Technology Cambridge, MA Professor of Economics, 2016-present IDSS Associate Director, 2016-present Harvard University Cambridge, MA Professor of Public Policy, 2005-2016 Visiting Professor of Economics, 2013-2014 Associate Professor of Public Policy, 2004-2005 Assistant Professor of Public Policy, 1999-2004 University of Chicago Chicago, IL Visiting Assistant Professor of Economics, 2002-2003 National Bureau of Economic Research (NBER) Cambridge, MA Research Associate (Labor Studies), 2009-present Faculty Research Fellow (Labor Studies), 2002-2009 Non-Academic Positions Amazon.com, Inc. Seattle, WA Academic Research Consultant, 2020-present Education Massachusetts Institute of Technology Cambridge, MA Ph.D. in Economics, 1995-1999 Thesis title: \Semiparametric Instrumental Variable Methods for Causal Response Mod- els." Centro de Estudios Monetarios y Financieros (CEMFI) Madrid, Spain M.A. in Economics, 1993-1995 Masters Thesis title: \Changes in Spanish Labor Income Structure during the 1980's: A Quantile Regression Approach." 1 Universidad del Pa´ıs Vasco Bilbao, Spain B.A. in Economics, 1987-1992 Specialization Areas: Mathematical Economics and Econometrics. Honors and Awards Elected Fellow of the Econometric Society, 2016. NSF grant SES-1756692, \A General Synthetic Control Framework of Estimation and Inference," 2018-2021. NSF grant SES-0961707, \A General Theory of Matching Estimation," with G. Imbens, 2010-2012. NSF grant SES-0617810, \The Economic Impact of Terrorism: Lessons from the Real Estate Office Markets of New York and Chicago," with S. Dermisi, 2006-2008. -
Curriculum Vitae: Michael W. Trosset
Curriculum Vitae: Michael W. Trosset Department of Statistics Telephone: (812) 856-1178 Indiana University E-mail: [email protected] Bloomington, IN 47401 Web Page: http://www.math.wm.edu/∼trosset/ Education • University of California, Berkeley (Department of Statistics); Fannie & John Hertz Foundation Fellow, September 1978 to December 1981; Dissertation: Minimax Estimation With Side Conditions, directed by Peter J. Bickel; Ph.D., December 1983. • Rice University (Mathematics and Mathematical Sciences); B.A., summa cum laude, May 1978. Employment • Professor, Department of Statistics, Indiana University. August 2006 to present. • Director, Indiana Statistical Consulting Center. August 2006 to present. • Associate Professor, Department of Mathematics, College of William & Mary. August 1998 to June 2006. Promoted to Professor in April 2006. • Formerly Visiting Associate Professor and Adjunct Lecturer, Departments of Mathematics, Statistics, and Psychology, University of Arizona (August 1993 to July 1998); Senior Postdoctoral Fellow, W.M. Keck Center for Computational Biology and Visiting Lecturer, Department of Statistics, Rice Uni- versity (September 1996 to June 1997); Visiting Lecturer, Department of Computational & Applied Mathematics, Rice University (Spring 1993); Consultant (June 1988 to July 1998); Assistant Pro- fessor, Department of Statistics, University of Arizona (August 1984 to December 1988); Instructor, Department of Mathematical Sciences, Rice University (January 1982 to May 1984); Research Assis- tant, Division of -
Rankings of Economics Journals and Departments in India
WP-2010-021 Rankings of Economics Journals and Departments in India Tilak Mukhopadhyay and Subrata Sarkar Indira Gandhi Institute of Development Research, Mumbai October 2010 http://www.igidr.ac.in/pdf/publication/WP-2010-021.pdf Rankings of Economics Journals and Departments in India Tilak Mukhopadhyay and Subrata Sarkar Indira Gandhi Institute of Development Research (IGIDR) General Arun Kumar Vaidya Marg Goregaon (E), Mumbai- 400065, INDIA Email (corresponding author): [email protected] Abstract This paper is the first attempt to rank economics departments of Indian Institutions based on their research output. Two rankings, one based on publications in international journals, and the other based on publications in domestic journals are derived. The rankings based on publications in international journals are obtained using the impact values of 159 journals found in Kalaitzidakis et al. (2003). Rankings based on publications in domestic journals are based on impact values of 20 journals. Since there are no published studies on ranking of domestic journals, we derived the rankings of domestic journals by using the iterative method suggested in Kalaitzidakis et al. (2003). The department rankings are constructed using two approaches namely, the ‘flow approach’ and the ‘stock approach’. Under the ‘flow approach’ the rankings are based on the total output produced by a particular department over a period of time while under the ‘stock approach’ the rankings are based on the publication history of existing faculty members in an institution. From these rankings the trend of research work and the growth of the department of a university are studied. Keywords: Departments,Economics, Journals, Rankings JEL Code: A10, A14 Acknowledgements: The auhtors would like to thank the seminar participants at Indira Gandhi Institute of Development Research. -
Miguel De Carvalho
School of Mathematics Miguel de Carvalho Contact M. de Carvalho T: +44 (0) 0131 650 5054 Information The University of Edinburgh B: [email protected] School of Mathematics : mb.carvalho Edinburgh EH9 3FD, UK +: www.maths.ed.ac.uk/ mdecarv Personal Born September 20, 1980 in Montijo, Lisbon. Details Portuguese and EU citizenship. Interests Applied Statistics, Biostatistics, Econometrics, Risk Analysis, Statistics of Extremes. Education Universidade de Lisboa, Portugal Habilitation in Probability and Statistics, 2019 Thesis: Statistical Modeling of Extremes Universidade Nova de Lisboa, Portugal PhD in Mathematics with emphasis on Statistics, 2009 Thesis: Extremum Estimators and Stochastic Optimization Advisors: Manuel Esqu´ıvel and Tiago Mexia Advisors of Advisors: Jean-Pierre Kahane and Tiago de Oliveira. Nova School of Business and Economics (Triple Accreditation), Portugal MSc in Economics, 2009 Thesis: Mean Regression for Censored Length-Biased Data Advisors: Jos´eA. F. Machado and Pedro Portugal Advisors of Advisors: Roger Koenker and John Addison. Universidade Nova de Lisboa, Portugal `Licenciatura'y in Mathematics, 2004 Professional Probation Period: Statistics Portugal (Instituto Nacional de Estat´ıstica). Awards & ISBA (International Society for Bayesian Analysis) Honours Lindley Award, 2019. TWAS (Academy of Sciences for the Developing World) Young Scientist Prize, 2015. International Statistical Institute Elected Member, 2014. American Statistical Association Young Researcher Award, Section on Risk Analysis, 2011. National Institute of Statistical Sciences j American Statistical Association Honorary Mention as a Finalist NISS/ASA Best y-BIS Paper Award, 2010. Portuguese Statistical Society (Sociedade Portuguesa de Estat´ıstica) Young Researcher Award, 2009. International Association for Statistical Computing ERS IASC Young Researcher Award, 2008. 1 of 13 p l e t t si a o e igulctoson Applied Statistical ModelingPublications 1. -
Biometrics & Biostatistics
Hanley and Moodie, J Biomet Biostat 2011, 2:5 Biometrics & Biostatistics http://dx.doi.org/10.4172/2155-6180.1000124 Research Article Article OpenOpen Access Access Sample Size, Precision and Power Calculations: A Unified Approach James A Hanley* and Erica EM Moodie Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Canada Abstract The sample size formulae given in elementary biostatistics textbooks deal only with simple situations: estimation of one, or a comparison of at most two, mean(s) or proportion(s). While many specialized textbooks give sample formulae/tables for analyses involving odds and rate ratios, few deal explicitly with statistical considera tions for slopes (regression coefficients), for analyses involving confounding variables or with the fact that most analyses rely on some type of generalized linear model. Thus, the investigator is typically forced to use “black-box” computer programs or tables, or to borrow from tables in the social sciences, where the emphasis is on cor- relation coefficients. The concern in the – usually very separate – modules or stand alone software programs is more with user friendly input and output. The emphasis on numerical exactness is particularly unfortunate, given the rough, prospective, and thus uncertain, nature of the exercise, and that different textbooks and software may give different sample sizes for the same design. In addition, some programs focus on required numbers per group, others on an overall number. We present users with a single universal (though sometimes approximate) formula that explicitly isolates the impacts of the various factors one from another, and gives some insight into the determinants for each factor. -
JEROME P. REITER Department of Statistical Science, Duke University Box 90251, Durham, NC 27708 Phone: 919 668 5227
JEROME P. REITER Department of Statistical Science, Duke University Box 90251, Durham, NC 27708 phone: 919 668 5227. email: [email protected]. September 26, 2021 EDUCATION Ph.D. in Statistics, Harvard University, 1999. A.M. in Statistics, Harvard University, 1996. B.S. in Mathematics, Duke University, 1992. DISSERTATION \Estimation in the Presence of Constraints that Prohibit Explicit Data Pooling." Advisor: Donald B. Rubin. POSITIONS Academic Appointments Professor of Statistical Science and Bass Fellow, Duke University, 2015 - present. Mrs. Alexander Hehmeyer Professor of Statistical Science, Duke University, 2013 - 2015. Mrs. Alexander Hehmeyer Associate Professor of Statistical Science, Duke University, 2010 - 2013. Associate Professor of Statistical Science, Duke University, 2009 - 2010. Assistant Professor of Statistical Science, Duke University, 2006 - 2008. Assistant Professor of the Practice of Statistics and Decision Sciences, Duke University, 2002 - 2006. Lecturer in Statistics, University of California at Santa Barbara, 2001 - 2002. Assistant Professor of Statistics, Williams College, 1999 - 2001. Other Appointments Chair, Department of Statistical Science, Duke University, 2019 - present. Associate Chair, Department of Statistical Science, Duke University, 2016 - 2019. Mathematical Statistician (part-time), U. S. Bureau of the Census, 2015 - present. Associate/Deputy Director of Information Initiative at Duke, Duke University, 2013 - 2019. Social Sciences Research Institute Data Services Core Director, Duke University, 2010 - 2013. Interim Director, Triangle Research Data Center, 2006. Senior Fellow, National Institute of Statistical Sciences, 2002 - 2005. 1 ACADEMIC HONORS Keynote talk, 11th Official Statistics and Methodology Symposium (Statistics Korea), 2021. Fellow of the Institute of Mathematical Statistics, 2020. Clifford C. Clogg Memorial Lecture, Pennsylvania State University, 2020 (postponed due to covid-19). -
The American Statistician
This article was downloaded by: [T&F Internal Users], [Rob Calver] On: 01 September 2015, At: 02:24 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: 5 Howick Place, London, SW1P 1WG The American Statistician Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/utas20 Reviews of Books and Teaching Materials Published online: 27 Aug 2015. Click for updates To cite this article: (2015) Reviews of Books and Teaching Materials, The American Statistician, 69:3, 244-252, DOI: 10.1080/00031305.2015.1068616 To link to this article: http://dx.doi.org/10.1080/00031305.2015.1068616 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. -
Intra-Industry Trade and North-North Migration: How TTIP Would Change the Patterns
Model Data Results References Intra-Industry Trade and North-North Migration: How TTIP Would Change the Patterns Mario Larch1 Steffen Sirries1 1University of Bayreuth ETSG 2014 1 / 38 Model Data Results References Funding and Notes on the Project This project is funded by DFG within the Project \Gravity with Unemployment" part of a bigger research agenda: Heid and Larch (2012) for unemployment, Heid (2014) for informality up to now without labor market imperfections work in progress ! input is very welcome! 2 / 38 Model Data Results References Why trade and migration? I Traditional view: H-O-type trade models with migration: Trade substitutes for migration (Mundell (1957)). Signing free trade agreements lowers the pressure of migration. Expected (bilateral) correlation between trade and migration ! negative! Gaston and Nelson (2013) BUT... 3 / 38 Model Data Results References Why trade and migration? II 15 10 5 0 TRADEFLOWS in logs (normalized) −5 −5 0 5 10 15 20 MIGRATION STOCKS in logs (normalized) 4 / 38 Model Data Results References Why trade and migration? III 2 0 −2 Residuals of trade gravity −4 −5 0 5 Residuals of migration gravity corr(^etrade ; e^migr ) = 0:2304 5 / 38 Model Data Results References Why trade and migration? IV There might be more than just a spurious correlation between trade and migration. New trade models with intra-industry trade and north-north migration ! complementarity of trade and migration (e.g OECD). This is not new (Head and Ries (1998)): Migrants also bring along preferential access to the markets of the country of origin. We think simpler: Migrants are not just a factor but consumers and though they bring their demand! Migrants have idiosyncratic shocks which drive the migration decision! 6 / 38 Model Data Results References Why \A Quantitative Framework"?I One of the core issues in empirical international trade is the quantification of the welfare gains from trade liberalization. -
Biostatistics Student Paper Competition the Department of Biostatistics at BUSPH Is Soliciting Applications for the 2013 Student Paper Competition
Biostatistics Student Paper Competition The Department of Biostatistics at BUSPH is soliciting applications for the 2013 student paper competition. The competition is open to all students enrolled in the Biostatistics Program at Boston University in the spring term of 2013. The winner of the competition will receive $750 as a travel award to attend the summer Joint Statistical Meetings. Travel to other conferences (i.e. ENAR, Society for Clinical Trials, American Society of Human Genetics, International Genetic Epidemiology Society) is possible in negotiation with the award committee. All students are strongly encouraged to submit the abstracts from their papers to the Joint Statistical Meetings, which has a deadline of February 4th. Students would also be encouraged to consider entering the competitions sponsored by sections of the Joint Statistical Meetings (e.g. The Biometrics section Byar Young Investigator award, for details see http://www.bio.ri.ccf.org/Biometrics/winner.html). TIMETABLE: January 11th, 2013 at noon: Deadline for students to submit pdf of manuscript January 25th, 2013: Announcement of awards REQUIREMENTS: The paper should be prepared double spaced, in manuscript format, using guidelines for authors typical of a biostatistical journal (e.g. Biometrics, Statistics in Medicine, or Biostatistics). A pdf copy of the manuscript should be submitted to the chair of the award committee, Ching-Ti Liu ([email protected]). The reported work should be relevant to biostatistics and must be the work of the student, although the manuscript can be co-authored with a faculty advisor or a small number of collaborators. The student must be the first author of the manuscript. -
Biometrical Applications in Biological Sciences-A Review on the Agony for Their Practical Efficiency- Problems and Perspectives
Biometrics & Biostatistics International Journal Review Article Open Access Biometrical applications in biological sciences-A review on the agony for their practical efficiency- Problems and perspectives Abstract Volume 7 Issue 5 - 2018 The effect of the three biological sciences- agriculture, environment and medicine S Tzortzios in the people’s life is of the greatest importance. The chain of the influence of the University of Thessaly, Greece environment to the form and quality of the agricultural production and the effect of both of them to the people’s health and welfare consists in an integrated system Correspondence: S Tzortzios, University of Thessaly, Greece, that is the basic substance of the human life. Agriculture has a great importance in Email [email protected] the World’s economy; however, the available resources for research and technology development are limited. Moreover, the environmental and productive conditions are Received: August 12, 2018 | Published: October 05, 2018 very different from one country to another, restricting the generalized transferring of technology. The statistical methods should play a paramount role to insure both the objectivity of the results of agricultural research as well as the optimum usage of the limited resources. An inadequate or improper use of statistical methods may result in wrong conclusions and in misuse of the available resources with important scientific and economic consequences. Many times, Statistics is used as a basis to justify conclusions of research work without considering in advance the suitability of the statistical methods to be used. The obvious question is: What importance do biological researchers give to the statistical methods? The answer is out of any doubt and the fact that most of the results published in specialized journals includes statistical considerations, confirms its importance.