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Kaspar Wüthrich
(Kaspar Wuthrich)

Personal Details

First Name:Kaspar
Middle Name:
Last Name:Wuthrich
Suffix:
RePEc Short-ID:pwt1
[This author has chosen not to make the email address public]
https://sites.google.com/site/wuethricheconomics/research
Terminal Degree:2015 Department Volkswirtschaftlehre; Universität Bern (from RePEc Genealogy)

Affiliation

Department of Economics
University of California-San Diego (UCSD)

La Jolla, California (United States)
http://economics.ucsd.edu/
RePEc:edi:deucsus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
  2. Davide Viviano & Kaspar Wuthrich & Paul Niehaus, 2021. "(When) should you adjust inferences for multiple hypothesis testing?," Papers 2104.13367, arXiv.org, revised Apr 2023.
  3. Niklas Potrafke & Kaspar Wuthrich, 2020. "Green governments," Papers 2012.09906, arXiv.org, revised Mar 2022.
  4. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.
  5. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
  6. Chernozhukov, Victor & Fernández-Val, Iván & Melly, Blaise & Wüthrich, Kaspar, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," University of California at San Diego, Economics Working Paper Series qt5zm6m9rq, Department of Economics, UC San Diego.
  7. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Dec 2022.
  8. Karthik Muralidharan & Mauricio Romero & Kaspar Wüthrich, 2020. "Factorial Designs, Model Selection, and (Incorrect) Inference in Randomized Experiments," CESifo Working Paper Series 8137, CESifo.
  9. Niklas Potrafke & Fabian Ruthardt & Kaspar Wüthrich, 2020. "Protectionism and Economic Growth: Causal Evidence from the First Era of Globalization," CESifo Working Paper Series 8759, CESifo.
  10. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.
  11. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2019. "Inference on average treatment effects in aggregate panel data settings," CeMMAP working papers CWP32/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  12. Graham Elliott & Nikolay Kudrin & Kaspar Wuthrich, 2019. "Detecting p-hacking," Papers 1906.06711, arXiv.org, revised May 2021.
  13. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," University of California at San Diego, Economics Working Paper Series qt99n9197q, Department of Economics, UC San Diego.
  14. Huber, Martin & Wüthrich, Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," University of California at San Diego, Economics Working Paper Series qt4j29d8sc, Department of Economics, UC San Diego.
  15. Hiroaki Kaido & Kaspar Wuthrich, 2018. "Decentralization Estimators for Instrumental Variable Quantile Regression Models," Papers 1812.10925, arXiv.org, revised Sep 2020.
  16. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2018. "A $t$-test for synthetic controls," Papers 1812.10820, arXiv.org, revised Jul 2022.
  17. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2018. "Exact and robust conformal inference methods for predictive machine learning with dependent data," CeMMAP working papers CWP16/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  18. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2017. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," Papers 1712.09089, arXiv.org, revised May 2021.
  19. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  20. Blaise Melly und Kaspar Wüthrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
  21. Daniel Burkhard & Christian Schmid & Kaspar Wüthrich, 2015. "Financial incentives and physician prescription behavior: Evidence from dispensing regulations," Diskussionsschriften dp1511, Universitaet Bern, Departement Volkswirtschaft.
  22. Kaspar Wüthrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
  23. Kaspar Wüthrich, 2013. "Set Identification of Generalized Linear Predictors in the Presence of Non-Classical Measurement Errors," Diskussionsschriften dp1304, Universitaet Bern, Departement Volkswirtschaft.
  24. Andreas Bachmann & Kaspar Wüthrich, 2013. "Evaluating pay-as-you-go social security systems," Diskussionsschriften dp1310, Universitaet Bern, Departement Volkswirtschaft.

Articles

  1. Graham Elliott & Nikolay Kudrin & Kaspar Wüthrich, 2022. "Detecting p‐Hacking," Econometrica, Econometric Society, vol. 90(2), pages 887-906, March.
  2. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2021. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1849-1864, October.
  3. Hiroaki Kaido & Kaspar Wüthrich, 2021. "Decentralization estimators for instrumental variable quantile regression models," Quantitative Economics, Econometric Society, vol. 12(2), pages 443-475, May.
  4. Kaspar Wüthrich, 2020. "A Comparison of Two Quantile Models With Endogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 443-456, April.
  5. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly & Kaspar Wüthrich, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 123-137, January.
  6. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
  7. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
  8. Daniel Burkhard & Christian P. R. Schmid & Kaspar Wüthrich, 2019. "Financial incentives and physician prescription behavior: Evidence from dispensing regulations," Health Economics, John Wiley & Sons, Ltd., vol. 28(9), pages 1114-1129, September.
  9. Boes, Stefan & Nüesch, Stephan & Wüthrich, Kaspar, 2015. "Hedonic valuation of the perceived risks of nuclear power plants," Economics Letters, Elsevier, vol. 133(C), pages 109-111.

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. Davide Viviano & Kaspar Wuthrich & Paul Niehaus, 2021. "(When) should you adjust inferences for multiple hypothesis testing?," Papers 2104.13367, arXiv.org, revised Apr 2023.

    Cited by:

    1. Jeffrey D. Michler & Anna Josephson, 2021. "Recent Developments in Inference: Practicalities for Applied Economics," Papers 2107.09736, arXiv.org.

  2. Niklas Potrafke & Kaspar Wuthrich, 2020. "Green governments," Papers 2012.09906, arXiv.org, revised Mar 2022.

    Cited by:

    1. N. N., 2021. "WIFO-Monatsberichte, Heft 1/2021," WIFO Monatsberichte (monthly reports), WIFO, vol. 94(1), January.
    2. Daniela Kletzan-Slamanig & Franz Sinabell, 2021. "Der Beitrag der Konjunkturbelebung zur Transformation. Einordnung von Maßnahmen der Bundesländer," WIFO Monatsberichte (monthly reports), WIFO, vol. 94(1), pages 67-78, January.

  3. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.

    Cited by:

    1. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Dec 2022.
    3. Alecos Papadopoulos & Christopher F. Parmeter, 2022. "Quantile Methods for Stochastic Frontier Analysis," Foundations and Trends(R) in Econometrics, now publishers, vol. 12(1), pages 1-120, November.
    4. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    5. Kaspar Wüthrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    6. David Powell, 2020. "Quantile Treatment Effects in the Presence of Covariates," The Review of Economics and Statistics, MIT Press, vol. 102(5), pages 994-1005, December.

  4. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.

    Cited by:

    1. Aluko, Olufemi Adewale & Opoku, Eric Evans Osei, 2022. "The financial development impact of financial globalization revisited: A focus on OECD countries," International Economics, Elsevier, vol. 169(C), pages 13-29.
    2. Jun Ma & Vadim Marmer & Zhengfei Yu, 2021. "Inference on Individual Treatment Effects in Nonseparable Triangular Models," Papers 2107.05559, arXiv.org, revised Feb 2023.
    3. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Nov 2022.
    4. Elisa Toledo & Wilman Santiago Ochoa-Moreno & Rafael Alvarado & Lizeth Cuesta & Muntasir Murshed & Abdul Rehman, 2022. "Forest Area: Old and New Factors That Affect Its Dynamics," Sustainability, MDPI, vol. 14(7), pages 1-17, March.
    5. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    6. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2021. "A first-stage representation for instrumental variables quantile regression," Papers 2102.01212, arXiv.org, revised Feb 2022.

  5. Chernozhukov, Victor & Fernández-Val, Iván & Melly, Blaise & Wüthrich, Kaspar, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," University of California at San Diego, Economics Working Paper Series qt5zm6m9rq, Department of Economics, UC San Diego.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers CWP48/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.
    3. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2018. "Distribution regression with sample selection, with an application to wage decompositions in the UK," CeMMAP working papers CWP68/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    5. Valentina Corradi & Daniel Gutknecht, 2019. "Testing for Quantile Sample Selection," Papers 1907.07412, arXiv.org, revised Jan 2021.
    6. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    7. Ferdi Botha & John P. de New, 2020. "COVID-19 infections, labour market shocks, and subjective well-being," Melbourne Institute Working Paper Series wp2020n14, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    8. Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021. "Distributional conformal prediction," University of California at San Diego, Economics Working Paper Series qt2zs6m5p5, Department of Economics, UC San Diego.
    9. Ferdi Botha & John P. de New & Sonja C. de New & David C. Ribar & Nicolás Salamanca, 2020. "COVID-19 labour market shocks and their inequality implications for financial wellbeing," Melbourne Institute Working Paper Series wp2020n15, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.

  6. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Dec 2022.

    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.

  7. Karthik Muralidharan & Mauricio Romero & Kaspar Wüthrich, 2020. "Factorial Designs, Model Selection, and (Incorrect) Inference in Randomized Experiments," CESifo Working Paper Series 8137, CESifo.

    Cited by:

    1. Andres Gonzalez-Lira & Ahmed Mushfiq Mobarak, 2021. "Slippery Fish: Enforcing Regulation when Agents Learn and Adapt," NBER Working Papers 28610, National Bureau of Economic Research, Inc.
    2. Sokbae Lee & Bernard Salani'e, 2020. "Filtered and Unfiltered Treatment Effects with Targeting Instruments," Papers 2007.10432, arXiv.org, revised Apr 2023.
    3. Leaver,Clare & Ozier,Owen & Serneels,Pieter Maria & Zeitlin,Andrew, 2020. "Recruitment, Effort, and Retention Effects of Performance Contracts for Civil Servants : Experimental Evidence from Rwandan Primary Schools," Policy Research Working Paper Series 9395, The World Bank.
    4. Michael Grimm & Renate Hartwig, 2022. "All eyes on the price: An assessment of the willingness‐to‐pay for eyeglasses in rural Burkina Faso," Health Economics, John Wiley & Sons, Ltd., vol. 31(7), pages 1347-1367, July.
    5. Daniel Engler & Gunnar Gutsche & Amantia Simixhiu & Andreas Ziegler, 2022. "Social norms and individual climate protection activities: A framed field experiment for Germany," MAGKS Papers on Economics 202230, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Gallego, Francisco A. & Malamud, Ofer & Pop-Eleches, Cristian, 2020. "Parental monitoring and children's internet use: The role of information, control, and cues," Journal of Public Economics, Elsevier, vol. 188(C).
    7. Jorge Luis García & James J. Heckman, 2020. "Early Childhood Education and Life-cycle Health," NBER Working Papers 26880, National Bureau of Economic Research, Inc.
    8. Erika Deserranno & Philipp Kastrau & Gianmarco León-Ciliotta, 2021. "Promotions and productivity: The role of meritocracy and pay progression in the public sector," Economics Working Papers 1770, Department of Economics and Business, Universitat Pompeu Fabra.
    9. Philipp Ketz & Adam Mccloskey, 2021. "Short and Simple Confidence Intervals when the Directions of Some Effects are Known," Working Papers hal-03388199, HAL.
    10. Fernando, A. Nilesh, 2021. "Seeking the treated: The impact of mobile extension on farmer information exchange in India," Journal of Development Economics, Elsevier, vol. 153(C).
    11. Laura Derksen & Jason Kerwin & Natalia Ordaz Reynoso & Olivier Sterck, 2021. "Appointments: A More Effective Commitment Device for Health Behaviors," Papers 2110.06876, arXiv.org.
    12. Leon-Ciliotta, Gianmarco, 2022. "Promotions and Productivity: The Role of Meritocracy and Pay Progression in the Public Sector," CEPR Discussion Papers 15837, C.E.P.R. Discussion Papers.
    13. Seim, Brigitte & Jablonski, Ryan & Ahlbäck, Johan, 2020. "How information about foreign aid affects public spending decisions: Evidence from a field experiment in Malawi," Journal of Development Economics, Elsevier, vol. 146(C).
    14. Timothy B. Armstrong & Michal Kolesár & Soonwoo Kwon, 2020. "Bias-Aware Inference in Regularized Regression Models," Working Papers 2020-2, Princeton University. Economics Department..
    15. Toshi H. Arimura & Elke D. Groh & Miwa Nakai & Andreas Ziegler, 2022. "The causal effect of private and organizational climate-related identity on climate protection activities: Evidence from a framed field experiment in Japan," MAGKS Papers on Economics 202229, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    16. Seim, Brigitte & Jablonski, Ryan S. & Ahlback, Johan, 2020. "How information about foreign aid affects public spending decisions: evidence from a field experiment in Malawi," LSE Research Online Documents on Economics 105255, London School of Economics and Political Science, LSE Library.
    17. Kondylis,Florence,Loeser,John Ashton, 2021. "Intervention Size and Persistence," Policy Research Working Paper Series 9769, The World Bank.
    18. Balán, Pablo & Bergeron, Augustin & Tourek, Gabriel, 2020. "Local Elites as State Capacity: How City Chiefs Use Local Information to Increase Tax Compliance in the D.R. Congo," CEPR Discussion Papers 15138, C.E.P.R. Discussion Papers.
    19. Behaghel, Luc & Gignoux, Jérémie, 2020. "Social learning in agriculture: does smallholder heterogeneity impede technology diffusion in Sub-Saharan Africa?," CEPR Discussion Papers 15220, C.E.P.R. Discussion Papers.
    20. Davide Viviano & Kaspar Wuthrich & Paul Niehaus, 2021. "(When) should you adjust inferences for multiple hypothesis testing?," Papers 2104.13367, arXiv.org, revised Apr 2023.
    21. Yuehao Bai & Jizhou Liu & Max Tabord-Meehan, 2022. "Inference for Matched Tuples and Fully Blocked Factorial Designs," Papers 2206.04157, arXiv.org, revised Mar 2023.

  8. Niklas Potrafke & Fabian Ruthardt & Kaspar Wüthrich, 2020. "Protectionism and Economic Growth: Causal Evidence from the First Era of Globalization," CESifo Working Paper Series 8759, CESifo.

    Cited by:

    1. Niklas Potrafke & Kaspar Wüthrich, 2020. "Green Governments," CESifo Working Paper Series 8726, CESifo.
    2. Keliang Wang & Bin Zhao & Tianzheng Fan & Jinning Zhang, 2022. "Economic Growth Targets and Carbon Emissions: Evidence from China," IJERPH, MDPI, vol. 19(13), pages 1-16, June.

  9. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.

    Cited by:

    1. Corradi, Valentina & Rocha, Nadia & Ruta, Michele & Zylkin, Thomas & Santos Silva, JMC, 2022. "Machine Learning in International Trade Research - Evaluating the Impact of Trade Agreements," CEPR Discussion Papers 17325, C.E.P.R. Discussion Papers.
    2. Joshua Angrist, 2022. "Empirical Strategies in Economics: Illuminating the Path from Cause to Effect," NBER Working Papers 29726, National Bureau of Economic Research, Inc.

  10. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2019. "Inference on average treatment effects in aggregate panel data settings," CeMMAP working papers CWP32/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference In Differences," NBER Working Papers 25532, National Bureau of Economic Research, Inc.

  11. Graham Elliott & Nikolay Kudrin & Kaspar Wuthrich, 2019. "Detecting p-hacking," Papers 1906.06711, arXiv.org, revised May 2021.

    Cited by:

    1. Guido W. Imbens, 2021. "Statistical Significance, p-Values, and the Reporting of Uncertainty," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 157-174, Summer.
    2. Simona Malovana & Martin Hodula & Zuzana Gric & Josef Bajzik, 2022. "Borrower-Based Macroprudential Measures and Credit Growth: How Biased is the Existing Literature?," Working Papers 2022/8, Czech National Bank.

  12. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," University of California at San Diego, Economics Working Paper Series qt99n9197q, Department of Economics, UC San Diego.

    Cited by:

    1. Brantly Callaway, 2020. "Bounds on Distributional Treatment Effect Parameters using Panel Data with an Application on Job Displacement," Papers 2008.08117, arXiv.org.
    2. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    4. Afrouz Azadikhah Jahromi & Brantly Callaway, 2019. "Heterogeneous Effects of Job Displacement on Earnings," DETU Working Papers 1901, Department of Economics, Temple University.

  13. Huber, Martin & Wüthrich, Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," University of California at San Diego, Economics Working Paper Series qt4j29d8sc, Department of Economics, UC San Diego.

    Cited by:

    1. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    2. Holger Herz & Deborah Kistler & Christian Zehnder & Christian Zihlmann, 2022. "Hindsight Bias and Trust in Government: Evidence from the United States," CESifo Working Paper Series 9767, CESifo.
    3. Berno Buechel & Selina Gangl & Martin Huber, 2021. "How residence permits affect the labor market attachment of foreign workers: Evidence from a migration lottery in Liechtenstein," Papers 2105.11840, arXiv.org.
    4. Jan Priebe, 2020. "Quasi-experimental evidence for the causal link between fertility and subjective well-being," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(3), pages 839-882, July.
    5. Öberg, Stefan, 2021. "Treatment for natural experiments: How to improve causal estimates using conceptual definitions and substantive interpretations," SocArXiv pkyue, Center for Open Science.

  14. Hiroaki Kaido & Kaspar Wuthrich, 2018. "Decentralization Estimators for Instrumental Variable Quantile Regression Models," Papers 1812.10925, arXiv.org, revised Sep 2020.

    Cited by:

    1. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Dec 2022.
    2. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    3. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Papers 1910.04245, arXiv.org.
    4. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Nov 2022.
    5. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Koki Fusejima, 2020. "Identification of multi-valued treatment effects with unobserved heterogeneity," Papers 2010.04385, arXiv.org, revised Apr 2023.
    7. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.

  15. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2018. "A $t$-test for synthetic controls," Papers 1812.10820, arXiv.org, revised Jul 2022.

    Cited by:

    1. Billy Ferguson & Brad Ross, 2020. "Assessing the Sensitivity of Synthetic Control Treatment Effect Estimates to Misspecification Error," Papers 2012.15367, arXiv.org, revised Feb 2021.
    2. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
    3. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    4. Guido Imbens & Nathan Kallus & Xiaojie Mao, 2021. "Controlling for Unmeasured Confounding in Panel Data Using Minimal Bridge Functions: From Two-Way Fixed Effects to Factor Models," Papers 2108.03849, arXiv.org.
    5. Bruno Ferman & Cristine Pinto, 2021. "Synthetic controls with imperfect pretreatment fit," Quantitative Economics, Econometric Society, vol. 12(4), pages 1197-1221, November.
    6. Nicolaj S{o}ndergaard Muhlbach & Mikkel Slot Nielsen, 2019. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," Papers 1909.03968, arXiv.org, revised Feb 2021.
    7. Anish Agarwal & Rahul Singh, 2021. "Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy," Papers 2107.02780, arXiv.org, revised Nov 2022.
    8. Jianfei Cao & Shirley Lu, 2019. "Synthetic Control Inference for Staggered Adoption: Estimating the Dynamic Effects of Board Gender Diversity Policies," Papers 1912.06320, arXiv.org.
    9. Xingyu Li & Yan Shen & Qiankun Zhou, 2022. "Confidence Intervals of Treatment Effects in Panel Data Models with Interactive Fixed Effects," Papers 2202.12078, arXiv.org.

  16. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2018. "Exact and robust conformal inference methods for predictive machine learning with dependent data," CeMMAP working papers CWP16/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Borgschulte, Mark & Vogler, Jacob, 2020. "Did the ACA Medicaid expansion save lives?," Journal of Health Economics, Elsevier, vol. 72(C).
    2. Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021. "Distributional conformal prediction," University of California at San Diego, Economics Working Paper Series qt2zs6m5p5, Department of Economics, UC San Diego.
    3. Matteo Fontana & Gianluca Zeni & Simone Vantini, 2020. "Conformal Prediction: a Unified Review of Theory and New Challenges," Papers 2005.07972, arXiv.org, revised Jul 2022.
    4. Varun Gupta & Christopher Jung & Georgy Noarov & Mallesh M. Pai & Aaron Roth, 2021. "Online Multivalid Learning: Means, Moments, and Prediction Intervals," Papers 2101.01739, arXiv.org.

  17. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2017. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," Papers 1712.09089, arXiv.org, revised May 2021.

    Cited by:

    1. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2019. "Synthetic Controls with Staggered Adoption," Papers 1912.03290, arXiv.org, revised Jan 2021.
    2. Billy Ferguson & Brad Ross, 2020. "Assessing the Sensitivity of Synthetic Control Treatment Effect Estimates to Misspecification Error," Papers 2012.15367, arXiv.org, revised Feb 2021.
    3. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
    4. Ignacio Martinez & Jaume Vives-i-Bastida, 2022. "Bayesian and Frequentist Inference for Synthetic Controls," Papers 2206.01779, arXiv.org, revised Feb 2023.
    5. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference In Differences," NBER Working Papers 25532, National Bureau of Economic Research, Inc.
    6. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    7. Ferman, Bruno, 2017. "Matching Estimators with Few Treated and Many Control Observations," MPRA Paper 78940, University Library of Munich, Germany.
    8. Alberto Abadie & Jinglong Zhao, 2021. "Synthetic Controls for Experimental Design," Papers 2108.02196, arXiv.org, revised Dec 2022.
    9. Dennis Shen & Peng Ding & Jasjeet Sekhon & Bin Yu, 2022. "Same Root Different Leaves: Time Series and Cross-Sectional Methods in Panel Data," Papers 2207.14481, arXiv.org, revised Oct 2022.
    10. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2018. "The Augmented Synthetic Control Method," Papers 1811.04170, arXiv.org, revised Jul 2020.
    11. Bruno Ferman, 2021. "On the Properties of the Synthetic Control Estimator with Many Periods and Many Controls," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1764-1772, October.
    12. Achille Nazaret & Claudia Shi & David M. Blei, 2023. "On the Misspecification of Linear Assumptions in Synthetic Control," Papers 2302.12777, arXiv.org.
    13. Carlos J. Charotti & Nuno Palma & João Pereira dos Santos, 2022. "American Treasure and the Decline of Spain," Economics Discussion Paper Series 2201, Economics, The University of Manchester.
    14. Doerr, Luisa & Dorn, Florian & Gaebler, Stefanie & Potrafke, Niklas, 2020. "How new airport infrastructure promotes tourism: evidence from a synthetic control approach in German regions," Munich Reprints in Economics 84767, University of Munich, Department of Economics.
    15. Giovanni Mellace & Alessandra Pasquini, 2022. "Mediation Analysis Synthetic Control," Temi di discussione (Economic working papers) 1389, Bank of Italy, Economic Research and International Relations Area.
    16. Peter Backus & Thien Nguyen, 2021. "The Effect of the Sex Buyer Law on the Market for Sex, Sexual Health and Sexual Violence," Economics Discussion Paper Series 2106, Economics, The University of Manchester.
    17. Alberto Abadie & Jaume Vives-i-Bastida, 2022. "Synthetic Controls in Action," Papers 2203.06279, arXiv.org.
    18. Klößner, Stefan & Pfeifer, Gregor, 2015. "Synthesizing Cash for Clunkers: Stabilizing the Car Market, Hurting the Environment," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113207, Verein für Socialpolitik / German Economic Association.
    19. Claudia Shi & Dhanya Sridhar & Vishal Misra & David M. Blei, 2021. "On the Assumptions of Synthetic Control Methods," Papers 2112.05671, arXiv.org, revised Dec 2021.
    20. Lea Bottmer & Guido Imbens & Jann Spiess & Merrill Warnick, 2021. "A Design-Based Perspective on Synthetic Control Methods," Papers 2101.09398, arXiv.org, revised Apr 2023.
    21. Bruno Ferman & Cristine Pinto, 2021. "Synthetic controls with imperfect pretreatment fit," Quantitative Economics, Econometric Society, vol. 12(4), pages 1197-1221, November.
    22. Barber, Andrew & West, Jeremy, 2022. "Conditional cash lotteries increase COVID-19 vaccination rates," Journal of Health Economics, Elsevier, vol. 81(C).
    23. Jonathan Roth & Pedro H. C. Sant'Anna & Alyssa Bilinski & John Poe, 2022. "What's Trending in Difference-in-Differences? A Synthesis of the Recent Econometrics Literature," Papers 2201.01194, arXiv.org, revised Jan 2023.
    24. Jianfei Cao & Connor Dowd, 2019. "Estimation and Inference for Synthetic Control Methods with Spillover Effects," Papers 1902.07343, arXiv.org, revised Nov 2019.
    25. Jiafeng Chen, 2022. "Synthetic Control As Online Linear Regression," Papers 2202.08426, arXiv.org, revised Nov 2022.
    26. Simon Freyaldenhoven & Christian Hansen & Jorge Perez Perez & Jesse Shapiro, 2021. "Visualization, Identification, and stimation in the Linear Panel Event-Study Design," Working Papers 21-44, Federal Reserve Bank of Philadelphia.
    27. Kuosmanen, Timo & Zhou, Xun & Eskelinen, Juha & Malo, Pekka, 2021. "Design Flaw of the Synthetic Control Method," MPRA Paper 106328, University Library of Munich, Germany.
    28. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2018. "Exact and robust conformal inference methods for predictive machine learning with dependent data," CeMMAP working papers CWP16/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Nicolaj S{o}ndergaard Muhlbach & Mikkel Slot Nielsen, 2019. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," Papers 1909.03968, arXiv.org, revised Feb 2021.
    30. Jason Poulos, 2019. "State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual Prediction," Papers 1903.08028, arXiv.org, revised Mar 2023.
    31. Matias D. Cattaneo & Yingjie Feng & Filippo Palomba & Rocio Titiunik, 2022. "scpi: Uncertainty Quantification for Synthetic Control Methods," Papers 2202.05984, arXiv.org, revised Oct 2022.
    32. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
    33. Luis Alvarez & Bruno Ferman, 2023. "Extensions for Inference in Difference-in-Differences with Few Treated Clusters," Papers 2302.03131, arXiv.org.
    34. Isaiah Andrews & Drew Fudenberg & Lihua Lei & Annie Liang & Chaofeng Wu, 2022. "The Transfer Performance of Economic Models," Papers 2202.04796, arXiv.org, revised May 2023.
    35. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2019. "Inference on average treatment effects in aggregate panel data settings," CeMMAP working papers CWP32/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Vivek F. Farias & Andrew A. Li & Tianyi Peng, 2021. "Learning Treatment Effects in Panels with General Intervention Patterns," Papers 2106.02780, arXiv.org, revised Mar 2023.
    37. Giovanni Peri & Derek Rury & Justin C. Wiltshire, 2020. "The Economic Impact of Migrants from Hurricane Maria," NBER Working Papers 27718, National Bureau of Economic Research, Inc.
    38. Lucke, Bernd, 2022. "Growth Effects of European Monetary Union: A Synthetic Control Approach," MPRA Paper 115373, University Library of Munich, Germany.
    39. Zongwu Cai & Ying Fang & Ming Lin & Zixuan Wu, 2023. "A Quasi Synthetic Control Method for Nonlinear Models," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202305, University of Kansas, Department of Economics, revised Feb 2023.
    40. Cao, Jing & Ho, Mun S. & Ma, Rong & Teng, Fei, 2021. "When carbon emission trading meets a regulated industry: Evidence from the electricity sector of China," Journal of Public Economics, Elsevier, vol. 200(C).
    41. Justin Wiltshire, 2021. "allsynth: Synthetic control bias-corrections utilities for Stata," 2021 Stata Conference 15, Stata Users Group.
    42. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2018. "A $t$-test for synthetic controls," Papers 1812.10820, arXiv.org, revised Jul 2022.
    43. Hideki Shimada & Kenji Asano & Yu Nagai & Akito Ozawa, 2022. "Assessing the Impact of Offshore Wind Power Deployment on Fishery: A Synthetic Control Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(3), pages 791-829, November.
    44. Xingyu Li & Yan Shen & Qiankun Zhou, 2022. "Confidence Intervals of Treatment Effects in Panel Data Models with Interactive Fixed Effects," Papers 2202.12078, arXiv.org.

  18. Blaise Melly und Kaspar Wüthrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.

    Cited by:

    1. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.

  19. Daniel Burkhard & Christian Schmid & Kaspar Wüthrich, 2015. "Financial incentives and physician prescription behavior: Evidence from dispensing regulations," Diskussionsschriften dp1511, Universitaet Bern, Departement Volkswirtschaft.

    Cited by:

    1. Rachamin, Yael & Meier, Rahel & Valeri, Fabio & Rosemann, Thomas & Muheim, Leander, 2021. "Physician-dispensing as a determinant of clinical and process measurements in patients at increased cardiovascular risk: A cross-sectional study in Swiss general practice," Health Policy, Elsevier, vol. 125(10), pages 1305-1310.
    2. Gerfin, Michael & Müller, Tobias & Schmid, Christian, 2022. "Rents for Pills: Financial Incentives and Physician Behavior," VfS Annual Conference 2022 (Basel): Big Data in Economics 264037, Verein für Socialpolitik / German Economic Association.
    3. Alexander Ahammer & Ivan Zilic, 2017. "Do Financial Incentives Alter Physician Prescription Behavior? Evidence From Random Patient-GP Allocations," Economics working papers 2017-02, Department of Economics, Johannes Kepler University Linz, Austria.
    4. Boris Kaiser, 2017. "Gender-specific practice styles and ambulatory health care expenditures," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(9), pages 1157-1179, December.
    5. Müller, Tobias & Schmid, Christian & Gerfin, Michael, 2023. "Rents for Pills: Financial incentives and physician behavior," Journal of Health Economics, Elsevier, vol. 87(C).
    6. Olivia Bodnar & Hugh Gravelle & Nils Gutacker & Annika Herr, 2021. "Financial incentives and prescribing behaviour in primary care," Working Papers 181cherp, Centre for Health Economics, University of York.
    7. Peter Zweifel, 2022. "Preference measurement in health using experiments," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(1), pages 49-66, March.

Articles

  1. Graham Elliott & Nikolay Kudrin & Kaspar Wüthrich, 2022. "Detecting p‐Hacking," Econometrica, Econometric Society, vol. 90(2), pages 887-906, March.
    See citations under working paper version above.
  2. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2021. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1849-1864, October.
    See citations under working paper version above.
  3. Hiroaki Kaido & Kaspar Wüthrich, 2021. "Decentralization estimators for instrumental variable quantile regression models," Quantitative Economics, Econometric Society, vol. 12(2), pages 443-475, May.
    See citations under working paper version above.
  4. Kaspar Wüthrich, 2020. "A Comparison of Two Quantile Models With Endogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 443-456, April.
    See citations under working paper version above.
  5. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly & Kaspar Wüthrich, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 123-137, January.
    See citations under working paper version above.
  6. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    See citations under working paper version above.
  7. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    See citations under working paper version above.
  8. Daniel Burkhard & Christian P. R. Schmid & Kaspar Wüthrich, 2019. "Financial incentives and physician prescription behavior: Evidence from dispensing regulations," Health Economics, John Wiley & Sons, Ltd., vol. 28(9), pages 1114-1129, September.
    See citations under working paper version above.
  9. Boes, Stefan & Nüesch, Stephan & Wüthrich, Kaspar, 2015. "Hedonic valuation of the perceived risks of nuclear power plants," Economics Letters, Elsevier, vol. 133(C), pages 109-111.

    Cited by:

    1. Tanaka, Shinsuke & Zabel, Jeffrey, 2018. "Valuing nuclear energy risk: Evidence from the impact of the Fukushima crisis on U.S. house prices," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 411-426.
    2. Zhu, Hongjia & Deng, Yongheng & Zhu, Rong & He, Xiaobo, 2016. "Fear of nuclear power? Evidence from Fukushima nuclear accident and land markets in China," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 139-154.
    3. Ju-Hee Kim & Young-Kuk Kim & Seung-Hoon Yoo, 2023. "Does Proximity to a Power Plant Affect Housing Property Values of a City in South Korea? An Empirical Investigation," Energies, MDPI, vol. 16(4), pages 1-14, February.
    4. Ando, Michihito & Dahlberg, Matz & Engström, Gustav, 2017. "The Risks of Nuclear Disaster and Its Impact on Housing Prices," Working Paper Series 2017:2, Uppsala University, Department of Economics.
    5. Tajima, Kayo & Yamamoto, Masashi & Ichinose, Daisuke, 2016. "How do agricultural markets respond to radiation risk? Evidence from the 2011 disaster in Japan," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 20-30.
    6. Hsiao, Cody Yu-Ling & Chen, Hsing Hung, 2018. "The contagious effects on economic development after resuming construction policy for nuclear power plants in Coastal China," Energy, Elsevier, vol. 152(C), pages 291-302.
    7. Chuanwang Sun & Xiaochun Meng & Shuijun Peng, 2017. "Effects of Waste-to-Energy Plants on China’s Urbanization: Evidence from a Hedonic Price Analysis in Shenzhen," Sustainability, MDPI, vol. 9(3), pages 1-18, March.
    8. Fekrazad, Amir, 2019. "Earthquake-risk salience and housing prices: Evidence from California," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 78(C), pages 104-113.

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 28 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 (17) 2013-08-31 2014-12-24 2015-08-01 2016-04-04 2016-10-02 2017-03-12 2018-01-08 2018-07-30 2019-01-14 2019-01-14 2019-06-24 2020-01-13 2020-02-24 2020-09-21 2020-11-23 2021-02-01 2021-05-03. Author is listed
  2. NEP-BIG: Big Data (3) 2018-07-30 2019-01-14 2020-01-13
  3. NEP-MAC: Macroeconomics (3) 2013-11-29 2015-07-18 2021-01-11
  4. NEP-ORE: Operations Research (3) 2020-01-13 2020-11-23 2021-05-03
  5. NEP-AGE: Economics of Ageing (2) 2013-11-29 2015-07-18
  6. NEP-ENE: Energy Economics (2) 2020-12-14 2021-01-11
  7. NEP-ENV: Environmental Economics (2) 2020-12-14 2021-01-11
  8. NEP-EXP: Experimental Economics (2) 2020-01-06 2020-04-06
  9. NEP-GRO: Economic Growth (2) 2021-01-11 2021-11-01
  10. NEP-HIS: Business, Economic & Financial History (2) 2021-01-11 2021-11-01
  11. NEP-CDM: Collective Decision-Making (1) 2020-12-14
  12. NEP-CMP: Computational Economics (1) 2018-07-30
  13. NEP-DCM: Discrete Choice Models (1) 2021-03-01
  14. NEP-DGE: Dynamic General Equilibrium (1) 2013-11-29
  15. NEP-HEA: Health Economics (1) 2015-11-21
  16. NEP-INT: International Trade (1) 2021-01-11
  17. NEP-PBE: Public Economics (1) 2013-11-29
  18. NEP-PUB: Public Finance (1) 2015-07-18
  19. NEP-REG: Regulation (1) 2020-12-14

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