Fused LASSO as Non-Crossing Quantile Regression
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- Szendrei, Tibor & Bhattacharjee, Arnab & Schaffer, Mark E, 2024. "Fused LASSO as Non-crossing Quantile Regression," IZA Discussion Papers 17149, Institute of Labor Economics (IZA).
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- Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
- Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
- Szendrei, Tibor & Varga, Katalin, 2023. "Revisiting vulnerable growth in the Euro Area: Identifying the role of financial conditions in the distribution," Economics Letters, Elsevier, vol. 223(C).
- Alberto Abadie & Maximilian Kasy, 2019. "Choosing Among Regularized Estimators in Empirical Economics: The Risk of Machine Learning," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 743-762, December.
- V. Chernozhukov & I. Fernández-Val & A. Galichon, 2009.
"Improving point and interval estimators of monotone functions by rearrangement,"
Biometrika, Biometrika Trust, vol. 96(3), pages 559-575.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2008. "Improving Point and Interval Estimates of Monotone Functions by Rearrangement," Papers 0806.4730, arXiv.org, revised Nov 2008.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2009. "Improving point and interval estimators of monotone functions by rearrangement," SciencePo Working papers Main hal-03596970, HAL.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2009. "Improving point and interval estimators of monotone functions by rearrangement," Post-Print hal-03596970, HAL.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2008. "Improving point and interval estimates of monotone functions by rearrangement," CeMMAP working papers CWP17/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Bhattacharya, J. & DeLeire, T. & Haider, S. & Currie, J., 2003.
"Heat or Eat? Cold-Weather Shocks and Nutrition in Poor American Families,"
American Journal of Public Health, American Public Health Association, vol. 93(7), pages 1149-1154.
- Jayanta Bhattacharya & Thomas DeLeire & Steven Haider & Janet Currie, 2002. "Heat or Eat? Cold Weather Shocks and Nutrition in Poor American Families," NBER Working Papers 9004, National Bureau of Economic Research, Inc.
- Jiang, Liewen & Bondell, Howard D. & Wang, Huixia Judy, 2014. "Interquantile shrinkage and variable selection in quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 208-219.
- Yuhong Yang, 2005. "Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation," Biometrika, Biometrika Trust, vol. 92(4), pages 937-950, December.
- V. Chernozhukov & I. Fernández-Val & A. Galichon, 2009.
"Improving point and interval estimators of monotone functions by rearrangement,"
Biometrika, Biometrika Trust, vol. 96(3), pages 559-575.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2008. "Improving Point and Interval Estimates of Monotone Functions by Rearrangement," Papers 0806.4730, arXiv.org, revised Nov 2008.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2009. "Improving point and interval estimators of monotone functions by rearrangement," SciencePo Working papers hal-03596970, HAL.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2009. "Improving point and interval estimators of monotone functions by rearrangement," Post-Print hal-03596970, HAL.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2008. "Improving point and interval estimates of monotone functions by rearrangement," CeMMAP working papers CWP17/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Tilmann Gneiting & Roopesh Ranjan, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 411-422, July.
- Howard D. Bondell & Brian J. Reich & Huixia Wang, 2010. "Noncrossing quantile regression curve estimation," Biometrika, Biometrika Trust, vol. 97(4), pages 825-838.
- Koenker, Roger, 1984. "A note on L-estimates for linear models," Statistics & Probability Letters, Elsevier, vol. 2(6), pages 323-325, December.
- Figueres, Juan Manuel & Jarociński, Marek, 2020.
"Vulnerable growth in the euro area: Measuring the financial conditions,"
Economics Letters, Elsevier, vol. 191(C).
- Figueres, Juan Manuel & Jarociński, Marek, 2020. "Vulnerable growth in the Euro Area: Measuring the financial conditions," Working Paper Series 2458, European Central Bank.
- David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
- Timothy K. M. Beatty & Laura Blow & Thomas F. Crossley, 2014.
"Is there a ‘heat-or-eat’ trade-off in the UK?,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(1), pages 281-294, January.
- Tim Beatty & Laura Blow & Thomas Crossley, 2011. "Is there a "heat or eat" trade-off in the UK?," IFS Working Papers W11/09, Institute for Fiscal Studies.
- Timothy K.M. Beatty & Laura Blow & Thomas F. Crossley, 2011. "Is There a Heat or Eat Trade-off in the UK?," Koç University-TUSIAD Economic Research Forum Working Papers 1133, Koc University-TUSIAD Economic Research Forum.
- Racine, Jeff, 2000. "Consistent cross-validatory model-selection for dependent data: hv-block cross-validation," Journal of Econometrics, Elsevier, vol. 99(1), pages 39-61, November.
- Gneiting, Tilmann & Ranjan, Roopesh, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 411-422.
- Burlinson, Andrew & Davillas, Apostolos & Law, Cherry, 2022. "Pay (for it) as you go: Prepaid energy meters and the heat-or-eat dilemma," Social Science & Medicine, Elsevier, vol. 315(C).
- 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.
- Yun Yang & Surya T. Tokdar, 2017. "Joint Estimation of Quantile Planes Over Arbitrary Predictor Spaces," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1107-1120, July.
- Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
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JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
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This paper has been announced in the following NEP Reports:- NEP-ECM-2024-04-29 (Econometrics)
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