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Challenges For Econometric Model Selection

Citations

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Cited by:

  1. Tomohiro Ando & Ruey S. Tsay, 2009. "Model selection for generalized linear models with factor‐augmented predictors," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 207-235, May.
  2. Doko Tchatoka, Firmin & Wang, Wenjie, 2021. "Size-corrected Bootstrap Test after Pretesting for Exogeneity with Heteroskedastic or Clustered Data," MPRA Paper 110899, University Library of Munich, Germany.
  3. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2020. "Model uncertainty, nonlinearities and out-of-sample comparison: evidence from international technology diffusion," Working Papers hal-02790523, HAL.
  4. Kitagawa, Toru & Muris, Chris, 2016. "Model averaging in semiparametric estimation of treatment effects," Journal of Econometrics, Elsevier, vol. 193(1), pages 271-289.
  5. Faust, Jon & Gupta, Abhishek, 2010. "Posterior Predictive Analysis for Evaluating DSGE Models," MPRA Paper 26721, University Library of Munich, Germany.
  6. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls," Papers 1201.0224, arXiv.org, revised May 2012.
  7. McCloskey, Adam, 2017. "Bonferroni-based size-correction for nonstandard testing problems," Journal of Econometrics, Elsevier, vol. 200(1), pages 17-35.
  8. Ulaşan, Bülent, 2012. "Cross-country growth empirics and model uncertainty: An overview," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-69.
  9. De Luca, Giuseppe & Magnus, Jan R. & Peracchi, Franco, 2018. "Weighted-average least squares estimation of generalized linear models," Journal of Econometrics, Elsevier, vol. 204(1), pages 1-17.
  10. Castle Jennifer L. & Doornik Jurgen A & Hendry David F., 2011. "Evaluating Automatic Model Selection," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-33, February.
  11. Ekaterina V. Astafyeva & Maria Yu. Turuntseva, 2023. "Analysis of Opportunities to Improve the Quality of Natural Resource Price by Combining Forecasts Resulting from Methods Based on Regression Estimates of Weights [Анализ Возможностей Улучшения Каче," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 24-33, December.
  12. Adam Gorajek, 2019. "The Well-meaning Economist," RBA Research Discussion Papers rdp2019-08, Reserve Bank of Australia.
  13. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2021. "Interactive R&D Spillovers: an estimation strategy based on forecasting-driven model selection," Working Papers hal-03224910, HAL.
  14. Marcos Herrera & Jesus Mur & Manuel Ruiz-Marin, 2017. "A Comparison Study on Criteria to Select the Most Adequate Weighting Matrix," Working Papers 18, Instituto de Estudios Laborales y del Desarrollo Económico (IELDE) - Universidad Nacional de Salta - Facultad de Ciencias Económicas, Jurídicas y Sociales.
  15. Maribel Serna Rodríguez & Andrés Ramírez Hassan & Alexander Coad, 2019. "Uncovering Value Drivers of High Performance Soccer Players," Journal of Sports Economics, , vol. 20(6), pages 819-849, August.
  16. Gioldasis, Georgios & Musolesi, Antonio & Simioni, Michel, 2023. "Interactive R&D spillovers: An estimation strategy based on forecasting-driven model selection," International Journal of Forecasting, Elsevier, vol. 39(1), pages 144-169.
  17. Adem Kelifa, 2023. "Review of Tobit, Heckman and double hurdle econometric models: supported with evidences from the studies conducted in Ethiopia," SN Business & Economics, Springer, vol. 3(6), pages 1-14, June.
  18. 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.
  19. Shangram Bahadur Shah & Jirakiattikul Sopin & Kua-Anan Techato & Bibek Kumar Mudbhari, 2023. "A Systematic Review on Nexus Between Green Finance and Climate Change: Evidence from China and India," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 599-613, July.
  20. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
  21. Giuseppe Luca & Jan R. Magnus & Franco Peracchi, 2023. "Weighted-Average Least Squares (WALS): Confidence and Prediction Intervals," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1637-1664, April.
  22. Nathan Canen & Kyungchul Song, 2021. "Counterfactual analysis under partial identification using locally robust refinement," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 416-436, June.
  23. David Bywaters & Gareth Thomas, 2008. "Output Expectations and Forecasting of UK Manufacturing," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 36(2), pages 125-137, June.
  24. E Bataa & D R Osborn & D H Kim, 2006. "A Further Examination of the Expectations Hypothesis for the Term Structure," Centre for Growth and Business Cycle Research Discussion Paper Series 72, Economics, The University of Manchester.
  25. Giuseppe De Luca & Jan Magnus & Franco Peracchi, 2015. "On the Ambiguous Consequences of Omitting Variables," Tinbergen Institute Discussion Papers 15-061/III, Tinbergen Institute.
  26. Andrés Ramírez-Hassan, 2020. "Dynamic variable selection in dynamic logistic regression: an application to Internet subscription," Empirical Economics, Springer, vol. 59(2), pages 909-932, August.
  27. Ulaşan, Bülent, 2011. "Cross-country growth empirics and model uncertainty: An overview," Economics Discussion Papers 2011-37, Kiel Institute for the World Economy (IfW Kiel).
  28. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2020. "Model uncertainty, nonlinearities and out-of-sample comparison: evidence from international technology diffusion," SEEDS Working Papers 0120, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jan 2020.
  29. Pitarakis, J., 2004. "Model selection uncertainty and detection of threshold effects," Discussion Paper Series In Economics And Econometrics 0409, Economics Division, School of Social Sciences, University of Southampton.
  30. Tomohiro Ando & Jushan Bai, 2015. "Asset Pricing with a General Multifactor Structure," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 556-604.
  31. Doko Tchatoka, Firmin & Wang, Wenjie, 2021. "Uniform Inference after Pretesting for Exogeneity with Heteroskedastic Data," MPRA Paper 106408, University Library of Munich, Germany.
  32. Erdenebat Bataa & Dong H. Kim & Denise R. Osborn, 2007. "Expectations Hypothesis Tests in the Presence of Model Uncertainty," Discussion Paper Series 0703, Institute of Economic Research, Korea University.
  33. Doko Tchatoka, Firmin & Wang, Wenjie, 2020. "Uniform Inference after Pretesting for Exogeneity," MPRA Paper 99243, University Library of Munich, Germany.
  34. S. C. Pandhare & T. V. Ramanathan, 2020. "The focussed information criterion for generalised linear regression models for time series," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 62(4), pages 485-507, December.
  35. Yongfu Huang, 2005. "What determines financial development?," Bristol Economics Discussion Papers 05/580, School of Economics, University of Bristol, UK.
  36. Doko Tchatoka, Firmin & Wang, Wenjie, 2024. "Weak-Identification-Robust Bootstrap Tests after Pretesting for Exogeneity," MPRA Paper 123060, University Library of Munich, Germany.
  37. Gupta, Abhishek, 2010. "A Forecasting Metric for Evaluating DSGE Models for Policy Analysis," MPRA Paper 26718, University Library of Munich, Germany.
  38. Naoya Sueishi, 2013. "Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-16, July.
  39. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
  40. Daud Ali Aser & Esin Firuzan, 2022. "Improving Forecast Accuracy Using Combined Forecasts with Regard to Structural Breaks and ARCH Innovations," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(37), pages 1-25, December.
  41. 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.
  42. Ng, Serena, 2013. "Variable Selection in Predictive Regressions," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 752-789, Elsevier.
  43. Choi, Hwan-sik & Kiefer, Nicholas M., 2006. "Robust Model Selection in Dynamic Models with an Application to Comparing Predictive Accuracy," Working Papers 06-09, Cornell University, Center for Analytic Economics.
  44. Jon Faust, 2012. "DSGE Models: I Smell a Rat (and It Smells Good)," International Journal of Central Banking, International Journal of Central Banking, vol. 8(1), pages 53-64, March.
  45. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378, April.
  46. Heij, C. & Groenen, P.J.F. & van Dijk, D.J.C., 2006. "Time series forecasting by principal covariate regression," Econometric Institute Research Papers EI 2006-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  47. Cliff Huang & Hung-pin Lai, 2012. "Estimation of stochastic frontier models based on multimodel inference," Journal of Productivity Analysis, Springer, vol. 38(3), pages 273-284, December.
  48. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference for High-Dimensional Sparse Econometric Models," Papers 1201.0220, arXiv.org.
  49. Ekaterina V. Astafyeva & Maria Yu. Turuntseva, 2023. "Анализ Возможностей Улучшения Качества Прогнозов Цен На Природные Ресурсы Методами Комбинирования На Основе Регрессионных Оценок Весов," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 24-33, December.
  50. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2021. "Interactive R&D Spillovers: An estimation strategy based on forecasting-driven model selection," SEEDS Working Papers 0621, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jun 2021.
  51. Ramírez-Hassan, Andrés & Carvajal-Rendón, Daniela A., 2021. "Specification uncertainty in modeling internet adoption: A developing city case analysis," Utilities Policy, Elsevier, vol. 70(C).
  52. Brijesh Yadav & Lal Chand Malav & Shruti V. Singh & Sushil Kumar Kharia & Md. Yeasin & Ram Narayan Singh & Mahaveer Nogiya & Roshan Lal Meena & Pravash Chandra Moharana & Nirmal Kumar & Ram Prasad Sha, 2023. "Spatiotemporal Responses of Vegetation to Hydroclimatic Factors over Arid and Semi-arid Climate," Sustainability, MDPI, vol. 15(21), pages 1-29, October.
  53. Jan Lohmeyer & Franz Palm & Jean‐Pierre Urbain, 2024. "Consistency of averaged impulse response estimators in vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(5), pages 691-713, September.
  54. 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.
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