IDEAS home Printed from https://ideas.repec.org/f/pli759.html
   My authors  Follow this author

Robert Pal Lieli

Personal Details

First Name:Robert
Middle Name:Pal
Last Name:Lieli
Suffix:
RePEc Short-ID:pli759
[This author has chosen not to make the email address public]
https://www.sites.google.com/site/robertplieli

Affiliation

Department of Economics and Business
Central European University

Budapest, Hungary
http://economics.ceu.edu/
RePEc:edi:deceuhu (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Mate Kormos & Robert P. Lieli & Martin Huber, 2023. "Treatment Effect Analysis for Pairs with Endogenous Treatment Takeup," Papers 2301.04876, arXiv.org.
  2. Yu-Chin Hsu & Robert P. Lieli, 2021. "Inference for ROC Curves Based on Estimated Predictive Indices," Papers 2112.01772, arXiv.org.
  3. Qingliang Fan & Yu-Chin Hsu & Robert P. Lieli & Yichong Zhang, 2019. "Estimation of Conditional Average Treatment Effects with High-Dimensional Data," Papers 1908.02399, arXiv.org, revised Jul 2021.
  4. Robert Pal Lieli & Yu-Chin Hsu, 2018. "Using the Area Under an Estimated ROC Curve to Test the Adequacy of Binary Predictors," CEU Working Papers 2018_1, Department of Economics, Central European University.
  5. Yu-Chin Hsu & Tsung-Chih Lai & Robert P. Lieli, 2017. "Estimating Counterfactual Treatment Effects to Assess External Validity," IEAS Working Paper : academic research 17-A011, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  6. Urmee Khan & Robert Lieli, 2016. "Information Flow Between Prediction Markets, Polls and Media: Evidence from the 2008 Presidential Primaries," Working Papers 201610, University of California at Riverside, Department of Economics.
  7. Robert P. Lieli & Yu-Chin Hsu, 2016. "The Null Distribution of the Empirical AUC for Classi ers with Estimated Parameters: a Special Case," IEAS Working Paper : academic research 16-A007, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  8. Marianna Endresz & Peter Harasztosi & Robert P. Lieli, 2015. "The Impact of the Magyar Nemzeti Bank's Funding for Growth Scheme on Firm Level Investment," MNB Working Papers 2015/2, Magyar Nemzeti Bank (Central Bank of Hungary).
  9. Yu-Chin Hsu & Robert P. Lieli & Tsung-Chih Lai, 2015. "Estimation and Inference for Distribution Functions and Quantile Functions in Endogenous Treatment Effect Models," IEAS Working Paper : academic research 15-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  10. Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2014. "Inverse Probability Weighted Estimation of Local Average Treatment Effects: A Higher Order MSE Expansion," IEAS Working Paper : academic research 14-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Aug 2014.
  11. Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2012. "Estimating Conditional Average Treatment Effects," CEU Working Papers 2012_16, Department of Economics, Central European University, revised 20 Jul 2012.
  12. Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2012. "Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT," IEAS Working Paper : academic research 12-A017, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  13. Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2010. "Inverse Propensity Score Weighted Estimation of Local Average Treatment Effects and a Test of the Unconfoundedness Assumption," CEU Working Papers 2012_9, Department of Economics, Central European University, revised 11 Aug 2010.

Articles

  1. Qingliang Fan & Yu-Chin Hsu & Robert P. Lieli & Yichong Zhang, 2022. "Estimation of Conditional Average Treatment Effects With High-Dimensional Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 313-327, January.
  2. Yu-Chin Hsu & Tsung-Chih Lai & Robert P. Lieli, 2022. "Counterfactual Treatment Effects: Estimation and Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 240-255, January.
  3. Yu-Chin Hsu & Tsung-Chih Lai & Robert P. Lieli, 2022. "Estimation and inference for distribution and quantile functions in endogenous treatment effect models," Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 22-50, January.
  4. Robert P Lieli & Augusto Nieto-Barthaburu, 2020. "On the Possibility of Informative Equilibria in Futures Markets with Feedback," Journal of the European Economic Association, European Economic Association, vol. 18(3), pages 1521-1552.
  5. Lieli, Robert P. & Stinchcombe, Maxwell B. & Grolmusz, Viola M., 2019. "Unrestricted and controlled identification of loss functions: Possibility and impossibility results," International Journal of Forecasting, Elsevier, vol. 35(3), pages 878-890.
  6. Robert P. Lieli & Yu-Chin Hsu, 2019. "Using the area under an estimated ROC curve to test the adequacy of binary predictors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 31(1), pages 100-130, January.
  7. Kónya, István & Benczúr, Péter & Szabó-Morvai, Ágnes & Lieli, Róbert & Reiff, Ádám, 2018. "Doktoranduszhallgatók VI. Nyári Műhelye. MKE-PTE KTK, Pécs, 2018. május 25-26 [6th Summer Conference of Doctoral Students]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 852-853.
  8. Kónya, István & Benczúr, Péter & Szabó-Morvai, Ágnes & Lieli, Róbert & Reiff, Ádám, 2018. "Előszó. A Magyar Közgazdaságtudományi Egyesület 11. konferenciája, Budapest, 2017. december 18-19 [Introduction. 11th Conference, Hungarian Society of Economics]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 685-686.
  9. Khan, Urmee & Lieli, Robert P., 2018. "Information flow between prediction markets, polls and media: Evidence from the 2008 presidential primaries," International Journal of Forecasting, Elsevier, vol. 34(4), pages 696-710.
  10. Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2015. "Estimating Conditional Average Treatment Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 485-505, October.
  11. Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2014. "Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 395-415, July.
  12. Donald, Stephen G. & Hsu, Yu-Chin & Lieli, Robert P., 2014. "Inverse probability weighted estimation of local average treatment effects: A higher order MSE expansion," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 132-138.
  13. Elliott, Graham & Lieli, Robert P., 2013. "Predicting binary outcomes," Journal of Econometrics, Elsevier, vol. 174(1), pages 15-26.
  14. Lieli, Robert P. & Stinchcombe, Maxwell B., 2013. "On The Recoverability Of Forecasters’ Preferences," Econometric Theory, Cambridge University Press, vol. 29(3), pages 517-544, June.
  15. Robert P. Lieli & Michael Springborn, 2013. "Closing the Gap between Risk Estimation and Decision Making: Efficient Management of Trade-Related Invasive Species Risk," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 632-645, May.
  16. Lieli, Robert P. & Nieto-Barthaburu, Augusto, 2010. "Optimal Binary Prediction for Group Decision Making," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 308-319.
  17. Lieli, Robert P. & White, Halbert, 2010. "The construction of empirical credit scoring rules based on maximization principles," Journal of Econometrics, Elsevier, vol. 157(1), pages 110-119, July.

Chapters

  1. Robert P. Lieli & Yu-Chin Hsu & Ágoston Reguly, 2022. "The Use of Machine Learning in Treatment Effect Estimation," Advanced Studies in Theoretical and Applied Econometrics, in: Felix Chan & László Mátyás (ed.), Econometrics with Machine Learning, chapter 0, pages 79-109, Springer.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 13 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 (9) 2013-01-07 2014-02-15 2015-08-30 2016-07-02 2017-08-27 2018-04-30 2019-08-26 2022-01-10 2023-02-13. Author is listed
  2. NEP-BIG: Big Data (1) 2019-08-26
  3. NEP-CFN: Corporate Finance (1) 2015-09-26
  4. NEP-CTA: Contract Theory and Applications (1) 2017-10-22
  5. NEP-CUL: Cultural Economics (1) 2016-06-04
  6. NEP-ENT: Entrepreneurship (1) 2015-09-26
  7. NEP-EXP: Experimental Economics (1) 2023-02-13
  8. NEP-GER: German Papers (1) 2015-08-30
  9. NEP-LMA: Labor Markets - Supply, Demand, and Wages (1) 2017-08-27
  10. NEP-MAC: Macroeconomics (1) 2015-09-26
  11. NEP-PAY: Payment Systems and Financial Technology (1) 2019-08-26
  12. NEP-RMG: Risk Management (1) 2012-11-03
  13. NEP-SOG: Sociology of Economics (1) 2014-02-15
  14. NEP-TRA: Transition Economics (1) 2015-09-26

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Robert Pal Lieli should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.