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Francis Joseph DiTraglia

Personal Details

First Name:Francis
Middle Name:Joseph
Last Name:DiTraglia
Suffix:
RePEc Short-ID:pdi336
[This author has chosen not to make the email address public]
http://www.ditraglia.com

Affiliation

Department of Economics
University of Pennsylvania

Philadelphia, Pennsylvania (United States)
http://www.econ.upenn.edu/
RePEc:edi:deupaus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
  2. Francis DiTraglia & Camilo García-Jimeno, 2016. "A Framework for Eliciting, Incorporating, and Disciplining Identification Beliefs in Linear Models," NBER Working Papers 22621, National Bureau of Economic Research, Inc.
  3. Francis J. DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM," PIER Working Paper Archive 14-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 04 Aug 2014.
  4. Francis J. DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 14-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 09 Dec 2014.
  5. Lisa R. Anderson & Jeffrey R. Gerlach & Francis J. DiTraglia, 2005. "Yes, Wall Street, There Is a January Effect! Evidence from Laboratory Auctions," Working Papers 15, Department of Economics, College of William and Mary.

Articles

  1. Minsu Chang & Francis J. DiTraglia, 2018. "A generalized focused information criterion for GMM," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 378-397, April.
  2. DiTraglia, Francis J., 2016. "Using invalid instruments on purpose: Focused moment selection and averaging for GMM," Journal of Econometrics, Elsevier, vol. 195(2), pages 187-208.
  3. DiTraglia, Francis J. & Gerlach, Jeffrey R., 2013. "Portfolio selection: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 305-323.
  4. Lisa Anderson & Francis DiTraglia & Jeffrey Gerlach, 2011. "Measuring altruism in a public goods experiment: a comparison of U.S. and Czech subjects," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 426-437, September.

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.

Working papers

  1. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.

    Cited by:

    1. Nguimkeu, Pierre & Denteh, Augustine & Tchernis, Rusty, 2019. "On the estimation of treatment effects with endogenous misreporting," Journal of Econometrics, Elsevier, vol. 208(2), pages 487-506.
    2. Francis J. DiTraglia & Camilo Garcia-Jimeno, 2020. "Identifying the effect of a mis-classified, binary, endogenous regressor," Papers 2011.07272, arXiv.org.
    3. Denni Tommasi & Lina Zhang, 2020. "Bounding Program Benefits When Participation is Misreported," Monash Econometrics and Business Statistics Working Papers 24/20, Monash University, Department of Econometrics and Business Statistics.
    4. Takahide Yanagi, 2018. "Inference on Local Average Treatment Effects for Misclassified Treatment," Papers 1804.03349, arXiv.org.

  2. Francis DiTraglia & Camilo García-Jimeno, 2016. "A Framework for Eliciting, Incorporating, and Disciplining Identification Beliefs in Linear Models," NBER Working Papers 22621, National Bureau of Economic Research, Inc.

    Cited by:

    1. Thorsten Drautzburg & Pooyan Amir-Ahmadi, 2017. "Identification through Heterogeneity," 2017 Meeting Papers 1087, Society for Economic Dynamics.
    2. Alessio Volpicella, 2019. "SVARs Identification through Bounds on the Forecast Error Variance," Working Papers 890, Queen Mary University of London, School of Economics and Finance.
    3. Matthew Masten & Alexandre Poirier, 2017. "Inference on breakdown frontiers," CeMMAP working papers 20/17, Institute for Fiscal Studies.
    4. Acemoglu, Daron & De Luca, Giacomo & De Feo, Giuseppe, 2017. "Weak States: Causes and Consequences of the Sicilian Mafia," CEPR Discussion Papers 12530, C.E.P.R. Discussion Papers.
    5. Bollinger, Christopher R. & van Hasselt, Martijn, 2017. "Bayesian moment-based inference in a regression model with misclassification error," Journal of Econometrics, Elsevier, vol. 200(2), pages 282-294.

  3. Francis J. DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM," PIER Working Paper Archive 14-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 04 Aug 2014.

    Cited by:

    1. Jeffrey T. Macher & Nathan H. Miller & Matthew Osborne, 2021. "Finding Mr. Schumpeter: technology adoption in the cement industry," RAND Journal of Economics, RAND Corporation, vol. 52(1), pages 78-99, March.
    2. Minsu Chang & Francis J. DiTraglia, 2020. "A Generalized Focused Information Criterion for GMM," Papers 2011.07085, arXiv.org.
    3. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Seojeong Lee, 2015. "A Consistent Variance Estimator for 2SLS When Instruments Identify Different LATEs," Discussion Papers 2015-01, School of Economics, The University of New South Wales.
    5. Liu, Chu-An, 2012. "A plug-in averaging estimator for regressions with heteroskedastic errors," MPRA Paper 41414, University Library of Munich, Germany.
    6. Lewbel, Arthur & Choi, Jin Young & Zhou, Zhuzhu, 2023. "Over-identified Doubly Robust identification and estimation," Journal of Econometrics, Elsevier, vol. 235(1), pages 25-42.
    7. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
    8. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
    9. Timothy B. Armstrong & Michal Koles'r, 2018. "Sensitivity Analysis using Approximate Moment Condition Models," Cowles Foundation Discussion Papers 2158R, Cowles Foundation for Research in Economics, Yale University, revised Feb 2019.
    10. Seojeong Lee, 2013. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Method of Moments Estimators," Discussion Papers 2013-09, School of Economics, The University of New South Wales.
    11. Leeb, Hannes & Pötscher, Benedikt M., 2012. "Testing in the Presence of Nuisance Parameters: Some Comments on Tests Post-Model-Selection and Random Critical Values," MPRA Paper 41459, University Library of Munich, Germany.
    12. Jonathan Chassot & Michael Creel, 2023. "Constructing Efficient Simulated Moments Using Temporal Convolutional Networks," Working Papers 1412, Barcelona School of Economics.
    13. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
    14. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2021. "Weighted-average least squares (WALS): Confidence and prediction intervals," EIEF Working Papers Series 2108, Einaudi Institute for Economics and Finance (EIEF), revised May 2021.
    15. Muhammad Qasim, 2024. "A weighted average limited information maximum likelihood estimator," Statistical Papers, Springer, vol. 65(5), pages 2641-2666, July.
    16. S. C. Pandhare & T. V. Ramanathan, 2020. "The robust focused information criterion for strong mixing stochastic processes with $$\mathscr {L}^{2}$$ L 2 -differentiable parametric densities," Statistical Inference for Stochastic Processes, Springer, vol. 23(3), pages 637-663, October.
    17. Shou-Yung Yin & Chu-An Liu & Chang-Ching Lin, 2021. "Focused Information Criterion and Model Averaging for Large Panels With a Multifactor Error Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 54-68, January.
    18. Liu, Chu-An, 2013. "Distribution Theory of the Least Squares Averaging Estimator," MPRA Paper 54201, University Library of Munich, Germany.
    19. Xu Cheng & Zhipeng Liao & Ruoyao Shi, 2013. "Uniform Asymptotic Risk of Averaging GMM Estimator Robust to Misspecification, Second Version," PIER Working Paper Archive 15-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Mar 2015.
    20. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP61/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Bai Huang & Tae-Hwy Lee & Aman Ullah, 2017. "A combined estimator of regression models with measurement errors," Indian Economic Review, Springer, vol. 52(1), pages 73-91, December.
    22. Bruce E. Hansen, 2017. "Stein-like 2SLS estimator," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 840-852, October.
    23. David M. Kaplan, 2019. "Unbiased Estimation as a Public Good," Working Papers 1911, Department of Economics, University of Missouri.
    24. Wang, Weiwei & Zhang, Qi & Zhang, Xinyu & Li, Xinmin, 2021. "Model averaging based on generalized method of moments," Economics Letters, Elsevier, vol. 200(C).
    25. Chu‐An Liu & Biing‐Shen Kuo, 2016. "Model averaging in predictive regressions," Econometrics Journal, Royal Economic Society, vol. 19(2), pages 203-231, June.
    26. Hansen, Bruce E., 2016. "Efficient shrinkage in parametric models," Journal of Econometrics, Elsevier, vol. 190(1), pages 115-132.
    27. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
    28. Hao Hao & Tae-Hwy Lee, 2023. "Boosting GMM with Many Instruments When Some Are Invalid or Irrelevant," Working Papers 202309, University of California at Riverside, Department of Economics.
    29. Edvard Bakhitov, 2020. "Frequentist Shrinkage under Inequality Constraints," Papers 2001.10586, arXiv.org.
    30. Maria Elena Bontempi & Jan Ditzen, 2023. "GMM-lev estimation and individual heterogeneity: Monte Carlo evidence and empirical applications," Papers 2312.00399, arXiv.org, revised Dec 2023.
    31. Ruoyao Shi & Zhipeng Liao, 2018. "An Averaging GMM Estimator Robust to Misspecification," Working Papers 201803, University of California at Riverside, Department of Economics.
    32. Boot, Tom, 2023. "Joint inference based on Stein-type averaging estimators in the linear regression model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1542-1563.
    33. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    34. Andres Ramirez-Hassan & Manuel Correa-Giraldo, 2018. "Focused econometric estimation for noisy and small datasets: A Bayesian Minimum Expected Loss estimator approach," Papers 1809.06996, arXiv.org.

  4. Francis J. DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 14-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 09 Dec 2014.

    Cited by:

    1. Xu Cheng & Zhipeng Liao & Ruoyao Shi, 2013. "Uniform Asymptotic Risk of Averaging GMM Estimator Robust to Misspecification, Second Version," PIER Working Paper Archive 15-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Mar 2015.
    2. Bruce E. Hansen, 2017. "Stein-like 2SLS estimator," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 840-852, October.
    3. Hansen, Bruce E., 2016. "Efficient shrinkage in parametric models," Journal of Econometrics, Elsevier, vol. 190(1), pages 115-132.

  5. Lisa R. Anderson & Jeffrey R. Gerlach & Francis J. DiTraglia, 2005. "Yes, Wall Street, There Is a January Effect! Evidence from Laboratory Auctions," Working Papers 15, Department of Economics, College of William and Mary.

    Cited by:

    1. Easterday, Kathryn E. & Sen, Pradyot K. & Stephan, Jens A., 2009. "The persistence of the small firm/January effect: Is it consistent with investors' learning and arbitrage efforts?," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 1172-1193, August.
    2. Françoise LE QUERE, 2008. "L'habillage de portefeuille par les gérants de fonds dans la littérature : incitations, effets et risques," LEO Working Papers / DR LEO 870, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    3. Danny Yeung, 2012. "The Impact of Institutional Ownership: A Study of the Australian Equity Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2012, January-A.
    4. Carlos Francisco Alves & Duarte André de Castro Reis, 2018. "Evidence of Idiosyncratic Seasonality in ETFs Performance," FEP Working Papers 603, Universidade do Porto, Faculdade de Economia do Porto.
    5. Françoise Le Quéré, 2010. "L’habillage de portefeuille par les gérants de fonds dans la littérature : incitations, effets et risques," Revue d'Économie Financière, Programme National Persée, vol. 97(2), pages 275-293.
    6. Sulaiman Mouselli & Hazem Al-Samman, 2016. "An Examination of the Month-of-the-year Effect at Damascus Securities Exchange," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 573-577.
    7. Priit Sander & Risto Veiderpass, 2012. "Testing the Turn-of-the-Year Effect on Baltic Stock Exchanges," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(2), pages 145-154, December.

Articles

  1. DiTraglia, Francis J., 2016. "Using invalid instruments on purpose: Focused moment selection and averaging for GMM," Journal of Econometrics, Elsevier, vol. 195(2), pages 187-208.
    See citations under working paper version above.
  2. DiTraglia, Francis J. & Gerlach, Jeffrey R., 2013. "Portfolio selection: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 305-323.

    Cited by:

    1. Rhee, S. Ghon & Wu, Feng (Harry), 2020. "Conditional extreme risk, black swan hedging, and asset prices," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 412-435.
    2. Balla, Eliana & Ergen, Ibrahim & Migueis, Marco, 2014. "Tail dependence and indicators of systemic risk for large US depositories," Journal of Financial Stability, Elsevier, vol. 15(C), pages 195-209.
    3. Mainik, Georg & Mitov, Georgi & Rüschendorf, Ludger, 2015. "Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 115-134.
    4. Long, Huaigang & Jiang, Yuexiang & Zhu, Yanjian, 2018. "Idiosyncratic tail risk and expected stock returns: Evidence from the Chinese stock markets," Finance Research Letters, Elsevier, vol. 24(C), pages 129-136.
    5. Long, Huaigang & Zhu, Yanjian & Chen, Lifang & Jiang, Yuexiang, 2019. "Tail risk and expected stock returns around the world," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 162-178.
    6. Chen, Yongfei & Wei, Yu & Bai, Lan & Zhang, Jiahao & Wang, Zhuo, 2023. "Connectedness and hedging effects among China's nonferrous metal, crude oil and green bond markets: An extreme perspective," Finance Research Letters, Elsevier, vol. 58(PA).
    7. Georg Mainik & Georgi Mitov & Ludger Ruschendorf, 2015. "Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz," Papers 1505.04045, arXiv.org.
    8. Asgar Ali & K. N. Badhani, 2023. "Tail risk, beta anomaly, and demand for lottery: what explains cross-sectional variations in equity returns?," Empirical Economics, Springer, vol. 65(2), pages 775-804, August.
    9. De Luca Giovanni & Zuccolotto Paola, 2017. "A double clustering algorithm for financial time series based on extreme events," Statistics & Risk Modeling, De Gruyter, vol. 34(1-2), pages 1-12, June.
    10. Yong-Jun Liu & Wei-Guo Zhang, 2019. "Possibilistic Moment Models for Multi-period Portfolio Selection with Fuzzy Returns," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1657-1686, April.
    11. Lorne N. Switzer & Jun Wang & Seungho Lee, 2017. "Extreme risk and small investor behavior in developed markets," Journal of Asset Management, Palgrave Macmillan, vol. 18(6), pages 457-475, October.
    12. Xunming Wang & Quansheng Ge & Xin Geng & Zhaosheng Wang & Lei Gao & Brett A. Bryan & Shengqian Chen & Yanan Su & Diwen Cai & Jiansheng Ye & Jimin Sun & Huayu Lu & Huizheng Che & Hong Cheng & Hongyan L, 2023. "Unintended consequences of combating desertification in China," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    13. Salisu, Afees A. & Adediran, Idris & Omoke, Philip C. & Tchankam, Jean Paul, 2023. "Gold and tail risks," Resources Policy, Elsevier, vol. 80(C).
    14. Vohra, Suprita & Fabozzi, Frank J., 2019. "Effectiveness of developed and emerging market FX options in active currency risk management," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 130-146.
    15. Montshioa, Keitumetse & Muteba Mwamba, John Weirstrass & Bonga-Bonga, Lumengo, 2021. "Asset allocation in extreme market conditions: a comparative analysis between developed and emerging economies," MPRA Paper 106248, University Library of Munich, Germany.

  3. Lisa Anderson & Francis DiTraglia & Jeffrey Gerlach, 2011. "Measuring altruism in a public goods experiment: a comparison of U.S. and Czech subjects," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 426-437, September.

    Cited by:

    1. Freundt, Jana & Lange, Andreas, 2021. "On the voluntary provision of public goods under risk," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
    2. Ros-Galvez, Alejandro & Rosa-García, Alfonso, 2014. "Private provision of a public good: cooperation and altruism of internet forum users," MPRA Paper 57560, University Library of Munich, Germany.
    3. Alex Imas & Sally Sadoff & Anya Samek, 2017. "Do People Anticipate Loss Aversion?," Management Science, INFORMS, vol. 63(5), pages 1271-1284, May.
    4. Imas, Alex, 2014. "Working for the “warm glow”: On the benefits and limits of prosocial incentives," Journal of Public Economics, Elsevier, vol. 114(C), pages 14-18.
    5. Peter Dolton & Richard S.J. Tol, 2019. "Correlates of Social Value Orientation: Evidence from a Large Sample of the UK Population," Working Paper Series 0119, Department of Economics, University of Sussex Business School.
    6. Vanessa Mertins & Andrea B. Schote & Jobst Meyer, 2013. "Variants of the Monoamine Oxidase A Gene (MAOA) Predict Free-riding Behavior in Women in a Strategic Public Goods Experiment," IAAEU Discussion Papers 201302, Institute of Labour Law and Industrial Relations in the European Union (IAAEU).
    7. Gylfason, Haukur Freyr & Arnardottir, Audur Arna & Kristinsson, Kari, 2013. "More on gender differences in lying," Economics Letters, Elsevier, vol. 119(1), pages 94-96.
    8. Evelyn Korn & Stephan Meisenzahl & Johannes Ziesecke, 2013. "How and when can economic skills enhance cooperation?," MAGKS Papers on Economics 201316, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    9. Alessia Aspide & Kathleen J. Brown & Matthew DiGiuseppe & Alexander Slaski, 2023. "Culture & European attitudes on public debt," New Political Economy, Taylor & Francis Journals, vol. 28(4), pages 509-525, July.
    10. Jana Vyrastekova & Esther-Mirjam Sent & Irene van Staveren, 2015. "Gender Beliefs and Cooperation in a Public Goods Game," Economics Bulletin, AccessEcon, vol. 35(2), pages 1148-1153.
    11. Jana Freundt & Andreas Lange, 2019. "On the Impact of Risky Private and Public Returns in the Private Provision of Public Goods - The Case of Social Investments," CESifo Working Paper Series 7458, CESifo.
    12. Peter Martinsson & Clara Villegas-Palacio & Conny Wollbrant, 2015. "Cooperation and social classes: evidence from Colombia," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 45(4), pages 829-848, December.
    13. Charles A. Holt & Sean P. Sullivan, 2023. "Permutation tests for experimental data," Experimental Economics, Springer;Economic Science Association, vol. 26(4), pages 775-812, September.

More information

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (3) 2014-12-03 2016-09-18 2017-10-01
  2. NEP-CBE: Cognitive and Behavioural Economics (1) 2005-04-03
  3. NEP-EXP: Experimental Economics (1) 2005-04-03
  4. NEP-FMK: Financial Markets (1) 2005-04-03
  5. NEP-ORE: Operations Research (1) 2017-10-01
  6. NEP-SOG: Sociology of Economics (1) 2016-09-18

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