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Selecting Instrumental Variables in a Data Rich Environment

Citations

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Cited by:

  1. Tae-Hwy Lee & Tao Wang, 2023. "Estimation and Testing of Forecast Rationality with Many Moments," Papers 2309.09481, arXiv.org, revised Jul 2025.
  2. Tomohiro Ando & Naoya Sueishi, 2019. "On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator," Econometrics, MDPI, vol. 7(1), pages 1-14, March.
  3. Ludovica Gambaro & Guido Neidhöfer & C. Katharina Spieß, 2019. "The Effect of Early Childhood Education and Care Services on the Social Integration of Refugee Families," Discussion Papers of DIW Berlin 1828, DIW Berlin, German Institute for Economic Research.
  4. Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.
  5. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
  6. Bhatt, Vipul & Kishor, Kundan & Marfatia, Hardik, 2017. "Estimating excess sensitivity and habit persistence in consumption using Greenbook forecast as an instrument," MPRA Paper 79748, University Library of Munich, Germany.
  7. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2010. "LASSO Methods for Gaussian Instrumental Variables Models," Papers 1012.1297, arXiv.org, revised Feb 2011.
  8. Stephane Dees & M. Hashem Pesaran & L. Vanessa Smith & Ron P. Smith, 2009. "Identification of New Keynesian Phillips Curves from a Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(7), pages 1481-1502, October.
  9. Bayar, Omer, 2018. "Weak instruments and estimated monetary policy rules," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 308-317.
  10. Balakrishnan, Pulapre & Parameswaran, Mavannoor, 2025. "Inflation in India: Dynamics, distributional impact and policy implication," Structural Change and Economic Dynamics, Elsevier, vol. 74(C), pages 556-566.
  11. Victor Chernozhukov & Ivan Fernandez-Val & Chen Huang & Weining Wang, 2024. "Arellano-bond lasso estimator for dynamic linear panel models," CeMMAP working papers 09/24, Institute for Fiscal Studies.
  12. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
  13. Connor Lennon & Edward Rubin & Glen Waddell, 2025. "Machine learning the first stage in 2SLS: Practical guidance from bias decomposition and simulation," Papers 2505.13422, arXiv.org.
  14. Geoffrey R. Dunbar & Casey Jones, 2018. "The (Un)Demand for Money in Canada," Staff Working Papers 18-20, Bank of Canada.
  15. Berriel, Tiago & Medeiros, Marcelo C. & Sena, Marcelo J., 2016. "Instrument selection for estimation of a forward-looking Phillips Curve," Economics Letters, Elsevier, vol. 145(C), pages 123-125.
  16. Scheufele, Rolf, 2010. "Evaluating the German (New Keynesian) Phillips curve," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 145-164, August.
  17. Gehrig, Thomas & Iannino, Maria Chiara & Unger, Stephan, 2024. "Social responsibility and bank resiliency," Journal of Financial Stability, Elsevier, vol. 70(C).
  18. 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.
  19. Gambaro, Ludovica & Neidhöfer, Guido & Spiess, C. Katharina, 2021. "The effect of early childhood education and care services on the integration of refugee families," Labour Economics, Elsevier, vol. 72(C).
  20. Max-Sebastian Dov`i, 2021. "Inference on the New Keynesian Phillips Curve with Very Many Instrumental Variables," Papers 2101.09543, arXiv.org, revised Mar 2021.
  21. 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.
  22. Aeggarchat Sirisankanan, 2023. "The Response of Household Savings to Anticipated Income Changes: Natural Experiments Using Natural and Non-Natural Factors," Journal of Economic Development, The Economic Research Institute, Chung-Ang University, vol. 48(2), pages 1-31.
  23. Omer Bayar, 2022. "Reducing large datasets to improve the identification of estimated policy rules," Empirical Economics, Springer, vol. 63(1), pages 113-140, July.
  24. Hao Hao & Bai Huang & Tae-hwy Lee, 2024. "Model averaging estimation of panel data models with many instruments and boosting," Journal of Applied Statistics, Taylor & Francis Journals, vol. 51(1), pages 53-69, January.
  25. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
  26. Vipul Bhatt & N. Kundan Kishor & Hardik Marfatia, 2020. "Estimating Excess Sensitivity and Habit Persistence in Consumption Using Greenbook Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 257-284, April.
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