High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Ledoit, Olivier & Wolf, Michael, 2004.
"A well-conditioned estimator for large-dimensional covariance matrices,"
Journal of Multivariate Analysis, Elsevier, vol. 88(2), pages 365-411, February.
- Ledoit, Olivier & Wolf, Michael, 2000. "A well conditioned estimator for large dimensional covariance matrices," DES - Working Papers. Statistics and Econometrics. WS 10087, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
- Kong, Yinfei & Li, Yujie & Zerom, Dawit, 2019. "Screening and selection for quantile regression using an alternative measure of variable importance," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 435-455.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2022.
"Bayesian estimation and comparison of conditional moment models,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 740-764, July.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2019. "Bayesian Estimation and Comparison of Conditional Moment Models," Working Papers 19-51, Federal Reserve Bank of Philadelphia.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian Estimation and Comparison of Conditional Moment Models," Post-Print hal-03504122, HAL.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
- Manuel A. Domínguez & Ignacio N. Lobato, 2004. "Consistent Estimation of Models Defined by Conditional Moment Restrictions," Econometrica, Econometric Society, vol. 72(5), pages 1601-1615, September.
- Kleibergen, Frank & Paap, Richard, 2006.
"Generalized reduced rank tests using the singular value decomposition,"
Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
- Frank Kleibergen & Richard Paap, 2003. "Generalized Reduced Rank Tests using the Singular Value Decomposition," Tinbergen Institute Discussion Papers 03-003/4, Tinbergen Institute.
- Richard Paap & Frank Kleibergen, 2004. "Generalized Reduced Rank Tests using the Singular Value Decomposition," Econometric Society 2004 Australasian Meetings 195, Econometric Society.
- Kleibergen, F.R. & Paap, R., 2003. "Generalized Reduced Rank Tests using the Singular Value Decomposition," Econometric Institute Research Papers EI 2003-01, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- V. Joseph Hotz & Robert A. Miller & Seth Sanders & Jeffrey Smith, 1994.
"A Simulation Estimator for Dynamic Models of Discrete Choice,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(2), pages 265-289.
- Hotz, J.V. & Miller, R.A. & Sanders, S. & Smith, J., 1992. "A Simulation Estimator for Dynamic Models of Discrete Choice," GSIA Working Papers 1992-13, Carnegie Mellon University, Tepper School of Business.
- V. Joseph Hotz & Robert A. Miller & Seth Sanders & Jeffrey Smith, 1992. "A Simulation Estimator for Dynamic Models of Discrete Choice," Working Papers 9205, Harris School of Public Policy Studies, University of Chicago.
- Qiang Sun & Hongtu Zhu & Yufeng Liu & Joseph G. Ibrahim, 2015. "SPReM: Sparse Projection Regression Model For High-Dimensional Linear Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 289-302, March.
- Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020.
"Taming the Factor Zoo: A Test of New Factors,"
Journal of Finance, American Finance Association, vol. 75(3), pages 1327-1370, June.
- Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2019. "Taming the Factor Zoo: A Test of New Factors," NBER Working Papers 25481, National Bureau of Economic Research, Inc.
- Giglio, Stefano & Feng, Guanhao & Xiu, Dacheng, 2020. "Taming the Factor Zoo: A Test of New Factors," CEPR Discussion Papers 14266, C.E.P.R. Discussion Papers.
- A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018.
"A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models,"
Econometrica, Econometric Society, vol. 86(4), pages 1479-1512, July.
- Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models," Globalization Institute Working Papers 290, Federal Reserve Bank of Dallas.
- Chudik, A. & Kapetanios, G. & Pesaran, Hashem, 2016. "A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models," Cambridge Working Papers in Economics 1677, Faculty of Economics, University of Cambridge.
- Emre Barut & Jianqing Fan & Anneleen Verhasselt, 2016. "Conditional Sure Independence Screening," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1266-1277, July.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015.
"Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments,"
American Economic Review, American Economic Association, vol. 105(5), pages 486-490, May.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments," Papers 1501.03185, arXiv.org.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers 02/15, Institute for Fiscal Studies.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers CWP02/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
- Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992.
"Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?,"
Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
- Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
- Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
- Breitung, Jörg & Eickmeier, Sandra, 2011.
"Testing for structural breaks in dynamic factor models,"
Journal of Econometrics, Elsevier, vol. 163(1), pages 71-84, July.
- Breitung, Jörg & Eickmeier, Sandra, 2009. "Testing for structural breaks in dynamic factor models," Discussion Paper Series 1: Economic Studies 2009,05, Deutsche Bundesbank.
- Chatterjee, A. & Gupta, S. & Lahiri, S.N., 2015. "On the residual empirical process based on the ALASSO in high dimensions and its functional oracle property," Journal of Econometrics, Elsevier, vol. 186(2), pages 317-324.
- Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2021.
"Deep Neural Networks for Estimation and Inference,"
Econometrica, Econometric Society, vol. 89(1), pages 181-213, January.
- Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2018. "Deep Neural Networks for Estimation and Inference," Papers 1809.09953, arXiv.org, revised Sep 2019.
- Arthur P. Guillaumin & Adam M. Sykulski & Sofia C. Olhede & Frederik J. Simons, 2022. "The Debiased Spatial Whittle likelihood," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1526-1557, September.
- Jack Jewson & David Rossell, 2022. "General Bayesian loss function selection and the use of improper models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1640-1665, November.
- Boot, Tom & Nibbering, Didier, 2019.
"Forecasting using random subspace methods,"
Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
- Tom Boot & Didier Nibbering, 2016. "Forecasting Using Random Subspace Methods," Tinbergen Institute Discussion Papers 16-073/III, Tinbergen Institute, revised 11 Aug 2017.
- Gareth M. James & Peter Radchenko & Jinchi Lv, 2009. "DASSO: connections between the Dantzig selector and lasso," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 127-142, January.
- M. Fátima Salgueiro & Peter W. F. Smith & John W. McDonald, 2005. "Power of edge exclusion tests in graphical Gaussian models," Biometrika, Biometrika Trust, vol. 92(1), pages 173-182, March.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "Inference on Treatment Effects after Selection among High-Dimensional Controlsâ€," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(2), pages 608-650.
- Gonzalo, Jesús & Pitarakis, Jean-Yves, 2024.
"Out-of-sample predictability in predictive regressions with many predictor candidates,"
International Journal of Forecasting, Elsevier, vol. 40(3), pages 1166-1178.
- Pitarakis, Jean-Yves, 2020. "Out of sample predictability in predictive regressions with many predictor candidates," UC3M Working papers. Economics 31554, Universidad Carlos III de Madrid. Departamento de EconomÃa.
- Jesus Gonzalo & Jean-Yves Pitarakis, 2023. "Out of Sample Predictability in Predictive Regressions with Many Predictor Candidates," Papers 2302.02866, arXiv.org, revised Oct 2023.
- Kock, Anders Bredahl, 2016. "Consistent And Conservative Model Selection With The Adaptive Lasso In Stationary And Nonstationary Autoregressions," Econometric Theory, Cambridge University Press, vol. 32(1), pages 243-259, February.
- Matias D. Cattaneo & Michael Jansson & Whitney K. Newey, 2018.
"Inference in Linear Regression Models with Many Covariates and Heteroscedasticity,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1350-1361, July.
- Matias D. Cattaneo & Michael Jansson & Whitney K. Newey, 2015. "Inference in Linear Regression Models with Many Covariates and Heteroskedasticity," Papers 1507.02493, arXiv.org, revised Jan 2017.
- Matias Cattaneo & Michael Jansson & Whitney K. Newey, 2017. "Inference in linear regression models with many covariates and heteroskedasticity," CeMMAP working papers 03/17, Institute for Fiscal Studies.
- Cattaneo, Matias D & Jansson, Michael & Newey, Whitney K, 2018. "Inference in Linear Regression Models with Many Covariates and Heteroscedasticity," Department of Economics, Working Paper Series qt6rp7p9gs, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
- Matias Cattaneo & Michael Jansson & Whitney K. Newey, 2017. "Inference in linear regression models with many covariates and heteroskedasticity," CeMMAP working papers CWP03/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Stinchcombe, Maxwell B. & White, Halbert, 1998. "Consistent Specification Testing With Nuisance Parameters Present Only Under The Alternative," Econometric Theory, Cambridge University Press, vol. 14(3), pages 295-325, June.
- Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2022.
"Regularized estimation of high‐dimensional vector autoregressions with weakly dependent innovations,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 532-557, July.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2019. "Regularized Estimation of High-Dimensional Vector AutoRegressions with Weakly Dependent Innovations," Papers 1912.09002, arXiv.org, revised Jun 2021.
- Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
- Kim, Jae-Young, 1994. "Bayesian Asymptotic Theory in a Time Series Model with a Possible Nonstationary Process," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 764-773, August.
- Cragg, John G. & Donald, Stephen G., 1997. "Inferring the rank of a matrix," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 223-250.
- Marcelo C. Medeiros & Eduardo F. Mendes, 2017.
"Adaptive LASSO estimation for ARDL models with GARCH innovations,"
Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 622-637, October.
- Marcelo C. Medeiros & Eduardo F. Mendes, 2015. "Adaptative LASSO estimation for ARDL models with GARCH innovations," Textos para discussão 637, Department of Economics PUC-Rio (Brazil).
- Ilias Chronopoulos & Aristeidis Raftapostolos & George Kapetanios, 2024.
"Forecasting Value-at-Risk Using Deep Neural Network Quantile Regression,"
Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 636-669.
- Chronopoulos, Ilias & Raftapostolos, Aristeidis & Kapetanios, George, 2023. "Forecasting Value-at-Risk using deep neural network quantile regression," Essex Finance Centre Working Papers 34837, University of Essex, Essex Business School.
- Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
- Farrell, Max H., 2015.
"Robust inference on average treatment effects with possibly more covariates than observations,"
Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
- Max H. Farrell, 2013. "Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations," Papers 1309.4686, arXiv.org, revised Feb 2018.
- Haoyu Chen & Wenbin Lu & Rui Song, 2021. "Statistical Inference for Online Decision Making via Stochastic Gradient Descent," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(534), pages 708-719, April.
- Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
- Yousuf, Kashif & Ng, Serena, 2021.
"Boosting high dimensional predictive regressions with time varying parameters,"
Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
- Kashif Yousuf & Serena Ng, 2019. "Boosting High Dimensional Predictive Regressions with Time Varying Parameters," Papers 1910.03109, arXiv.org.
- Kuersteiner, Guido M., 2019. "Invariance principles for dependent processes indexed by Besov classes with an application to a Hausman test for linearity," Journal of Econometrics, Elsevier, vol. 211(1), pages 243-261.
- Laurent Callot & Mehmet Caner & A. Özlem Önder & Esra Ulaşan, 2021. "A Nodewise Regression Approach to Estimating Large Portfolios," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 520-531, March.
- Nielsen, Morten Ørregaard, 2009.
"A Powerful Test Of The Autoregressive Unit Root Hypothesis Based On A Tuning Parameter Free Statistic,"
Econometric Theory, Cambridge University Press, vol. 25(6), pages 1515-1544, December.
- Morten Ø. Nielsen, 2008. "A Powerful Test Of The Autoregressive Unit Root Hypothesis Based On A Tuning Parameter Free Statistic," Working Paper 1185, Economics Department, Queen's University.
- Morten Ørregaard Nielsen, 2008. "A Powerful Test of the Autoregressive Unit Root Hypothesis Based on a Tuning Parameter Free Statistic," CREATES Research Papers 2008-36, Department of Economics and Business Economics, Aarhus University.
- Halunga, Andreea G. & Orme, Chris D. & Yamagata, Takashi, 2017.
"A heteroskedasticity robust Breusch–Pagan test for Contemporaneous correlation in dynamic panel data models,"
Journal of Econometrics, Elsevier, vol. 198(2), pages 209-230.
- Andreea Halunga & Chris D. Orme & Takashi Yamagata, 2011. "A Heteroskedasticity Robust Breusch-Pagan Test for Contemporaneous Correlation in Dynamic Panel Data Models," Economics Discussion Paper Series 1118, Economics, The University of Manchester.
- Joseph P. Romano & Michael Wolf, 2005.
"Exact and Approximate Stepdown Methods for Multiple Hypothesis Testing,"
Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 94-108, March.
- Joseph Romano & Michael Wolf, 2003. "Exact and approximate stepdown methods for multiple hypothesis testing," Economics Working Papers 727, Department of Economics and Business, Universitat Pompeu Fabra.
- Qian, Junhui & Su, Liangjun, 2016.
"Shrinkage Estimation Of Regression Models With Multiple Structural Changes,"
Econometric Theory, Cambridge University Press, vol. 32(6), pages 1376-1433, December.
- Junhui Qian & Liangjun Su, 2014. "Shrinkage Estimation of Regression Models with Multiple Structural Changes," Working Papers 06-2014, Singapore Management University, School of Economics.
- Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
- Mohitosh Kejriwal & Xuewen Yu, 2021. "Generalized Forecast Averaging in Autoregressions with a Near Unit Root," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 83-102.
- Xiangyu Wang & Chenlei Leng, 2016. "High dimensional ordinary least squares projection for screening variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 589-611, June.
- Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022.
"On LASSO for predictive regression,"
Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
- Ji Hyung Lee & Zhentao Shi & Zhan Gao, 2018. "On LASSO for Predictive Regression," Papers 1810.03140, arXiv.org, revised Feb 2021.
- Davidson, James, 2002. "Establishing conditions for the functional central limit theorem in nonlinear and semiparametric time series processes," Journal of Econometrics, Elsevier, vol. 106(2), pages 243-269, February.
- Jianqing Fan & Quefeng Li & Yuyan Wang, 2017. "Estimation of high dimensional mean regression in the absence of symmetry and light tail assumptions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 247-265, January.
- Fan, Jianqing & Feng, Yang & Xia, Lucy, 2020. "A projection-based conditional dependence measure with applications to high-dimensional undirected graphical models," Journal of Econometrics, Elsevier, vol. 218(1), pages 119-139.
- Karim M. Abadir & Kaddour Hadri & Elias Tzavalis, 1999.
"The Influence of VAR Dimensions on Estimator Biases,"
Econometrica, Econometric Society, vol. 67(1), pages 163-182, January.
- Karim Abadir & Kaddour Hadri & Elias Tzavalis, "undated". "The Influence of VAR Dimensions on Estimator Biases," Discussion Papers 96/14, Department of Economics, University of York.
- James G. MacKinnon, 1983. "Model Specification Tests Against Non-Nested Alternatives," Working Paper 573, Economics Department, Queen's University.
- Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
- Sebastian Engelke & Adrien S. Hitz, 2020. "Graphical models for extremes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 871-932, September.
- 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.
- Benjamin Poignard & Manabu Asai, 2023.
"Estimation of high-dimensional vector autoregression via sparse precision matrix,"
The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 307-326.
- Benjamin Poignard & Manabu Asai, 2021. "Estimation of High Dimensional Vector Autoregression via Sparse Precision Matrix," Discussion Papers in Economics and Business 21-03, Osaka University, Graduate School of Economics.
- Newey, Whitney K, 1991.
"Uniform Convergence in Probability and Stochastic Equicontinuity,"
Econometrica, Econometric Society, vol. 59(4), pages 1161-1167, July.
- Newey, W.K., 1989. "Uniform Convergence In Probability And Stochastic Equicontinuity," Papers 342, Princeton, Department of Economics - Econometric Research Program.
- Sayar Karmakar & Marek Chudý & Wei Biao Wu, 2022. "Long‐term prediction intervals with many covariates," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 587-609, July.
- Alexandre Belloni & Victor Chernozhukov & Ying Wei, 2016.
"Post-Selection Inference for Generalized Linear Models With Many Controls,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 606-619, October.
- Alexandre Belloni & Victor Chernozhukov & Ying Wei, 2013. "Post-Selection Inference for Generalized Linear Models with Many Controls," Papers 1304.3969, arXiv.org, revised Mar 2016.
- Lin, Yingqian & Tu, Yundong, 2020. "Robust inference for spurious regressions and cointegrations involving processes moderately deviated from a unit root," Journal of Econometrics, Elsevier, vol. 219(1), pages 52-65.
- Ian W. McKeague & Min Qian, 2015. "An Adaptive Resampling Test for Detecting the Presence of Significant Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1422-1433, December.
- Fátima Salgueiro, M. & Smith, Peter W.F. & McDonald, John W., 2006. "Power of edge exclusion tests for graphical log-linear models," Journal of Multivariate Analysis, Elsevier, vol. 97(8), pages 1691-1701, September.
- Su, Liangjun & Hoshino, Tadao, 2016.
"Sieve instrumental variable quantile regression estimation of functional coefficient models,"
Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
- Su Liangjun & Tadao Hoshino, 2015. "Sieve Instrumental Variable Quantile Regression Estimation of Functional Coefficient Models," Working Papers 01-2015, Singapore Management University, School of Economics.
- Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
- Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023.
"Lasso inference for high-dimensional time series,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
- Robert Adamek & Stephan Smeekes & Ines Wilms, 2020. "Lasso Inference for High-Dimensional Time Series," Papers 2007.10952, arXiv.org, revised Sep 2022.
- Hansen, Bruce E., 2008. "Least-squares forecast averaging," Journal of Econometrics, Elsevier, vol. 146(2), pages 342-350, October.
- Xu Cheng & Zhipeng Liao & Frank Schorfheide, 2016.
"Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(4), pages 1511-1543.
- Xu Cheng & Zhipeng Liao & Frank Schorfheide, 2013. "Shrinkage estimation of high-dimensional factor models with structural instabilities," Working Papers 14-4, Federal Reserve Bank of Philadelphia.
- Xu Cheng & Zhipeng Liao & Frank Schorfheide, 2014. "Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities," NBER Working Papers 19792, National Bureau of Economic Research, Inc.
- Chunrong Ai & Xiaohong Chen, 2003. "Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions," Econometrica, Econometric Society, vol. 71(6), pages 1795-1843, November.
- Cheng, Xu & Hansen, Bruce E., 2015.
"Forecasting with factor-augmented regression: A frequentist model averaging approach,"
Journal of Econometrics, Elsevier, vol. 186(2), pages 280-293.
- Xu Cheng & Bruce E. Hansen, 2012. "Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach," PIER Working Paper Archive 12-046, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Christis Katsouris, 2023. "Statistical Estimation for Covariance Structures with Tail Estimates using Nodewise Quantile Predictive Regression Models," Papers 2305.11282, arXiv.org, revised Jul 2023.
- Alex Chinco & Adam D. Clark‐Joseph & Mao Ye, 2019. "Sparse Signals in the Cross‐Section of Returns," Journal of Finance, American Finance Association, vol. 74(1), pages 449-492, February.
- Wüthrich, Kaspar & Zhu, Ying, 2023. "Omitted Variable Bias of Lasso-Based Inference Methods: A Finite Sample Analysis," University of California at San Diego, Economics Working Paper Series qt1gp6g9gm, Department of Economics, UC San Diego.
- Jean-Yves Pitarakis, 2020. "A Novel Approach to Predictive Accuracy Testing in Nested Environments," Papers 2008.08387, arXiv.org, revised Oct 2023.
- Su, Liangjun & Jin, Sainan, 2012. "Sieve estimation of panel data models with cross section dependence," Journal of Econometrics, Elsevier, vol. 169(1), pages 34-47.
- Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
- Ngai Hang Chan & Chun Yip Yau & Rong-Mao Zhang, 2014. "Group LASSO for Structural Break Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 590-599, June.
- Hagemann, Andreas, 2012. "A simple test for regression specification with non-nested alternatives," Journal of Econometrics, Elsevier, vol. 166(2), pages 247-254.
- Andreas Hagemann, 2014. "Stochastic equicontinuity in nonlinear time series models," Econometrics Journal, Royal Economic Society, vol. 17(1), pages 188-196, February.
- Laura Coroneo & Fabrizio Iacone, 2020. "Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 391-409, June.
- Jianqing Fan & Jinchi Lv, 2008. "Sure independence screening for ultrahigh dimensional feature space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 849-911, November.
- Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
- Wang, Hansheng, 2009. "Forward Regression for Ultra-High Dimensional Variable Screening," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1512-1524.
- Kaspar Wüthrich & Ying Zhu, 2023. "Omitted Variable Bias of Lasso-Based Inference Methods: A Finite Sample Analysis," The Review of Economics and Statistics, MIT Press, vol. 105(4), pages 982-997, July.
- Gonzalo García-Donato & Rui Paulo, 2022. "Variable Selection in the Presence of Factors: A Model Selection Perspective," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(540), pages 1847-1857, October.
- Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
- Haoyu Chen & Wenbin Lu & Rui Song, 2021. "Statistical Inference for Online Decision Making: In a Contextual Bandit Setting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(533), pages 240-255, March.
- Caner, Mehmet & Medeiros, Marcelo & Vasconcelos, Gabriel F.R., 2023.
"Sharpe Ratio analysis in high dimensions: Residual-based nodewise regression in factor models,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 393-417.
- Mehmet Caner & Marcelo Medeiros & Gabriel Vasconcelos, 2020. "Sharpe Ratio Analysis in High Dimensions: Residual-Based Nodewise Regression in Factor Models," Papers 2002.01800, arXiv.org, revised Feb 2022.
- Lan Wang & Yichao Wu & Runze Li, 2012. "Quantile Regression for Analyzing Heterogeneity in Ultra-High Dimension," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 214-222, March.
- Bruce E. Hansen, 2007. "Least Squares Model Averaging," Econometrica, Econometric Society, vol. 75(4), pages 1175-1189, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023.
"Machine learning advances for time series forecasting,"
Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
- Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022.
"On LASSO for predictive regression,"
Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
- Ji Hyung Lee & Zhentao Shi & Zhan Gao, 2018. "On LASSO for Predictive Regression," Papers 1810.03140, arXiv.org, revised Feb 2021.
- Fan, Rui & Lee, Ji Hyung & Shin, Youngki, 2023.
"Predictive quantile regression with mixed roots and increasing dimensions: The ALQR approach,"
Journal of Econometrics, Elsevier, vol. 237(2).
- Rui Fan & Ji Hyung Lee & Youngki Shin, 2021. "Predictive Quantile Regression with Mixed Roots and Increasing Dimensions: The ALQR Approach," Papers 2101.11568, arXiv.org, revised Dec 2022.
- Tu, Yundong & Xie, Xinling, 2023. "Penetrating sporadic return predictability," Journal of Econometrics, Elsevier, vol. 237(1).
- Gerda Claeskens, 2012. "Focused estimation and model averaging with penalization methods: an overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(3), pages 272-287, August.
- Howard D. Bondell & Brian J. Reich, 2012. "Consistent High-Dimensional Bayesian Variable Selection via Penalized Credible Regions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1610-1624, December.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018.
"High-dimensional econometrics and regularized GMM,"
CeMMAP working papers
CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
- Loann David Denis Desboulets, 2018.
"A Review on Variable Selection in Regression Analysis,"
Econometrics, MDPI, vol. 6(4), pages 1-27, November.
- Loann David Denis Desboulets, 2018. "A Review on Variable Selection in Regression Analysis," Post-Print hal-01954386, HAL.
- Jingxuan Luo & Lili Yue & Gaorong Li, 2023. "Overview of High-Dimensional Measurement Error Regression Models," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
- Barbara Rossi, 2019.
"Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them,"
Economics Working Papers
1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
- Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
- Rossi, Barbara, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," CEPR Discussion Papers 14472, C.E.P.R. Discussion Papers.
- Marcelo C. Medeiros & Eduardo F. Mendes, 2015. "l1-Regularization of High-Dimensional Time-Series Models with Flexible Innovations," Textos para discussão 636, Department of Economics PUC-Rio (Brazil).
- Sophie Brana & Dalila Chenaf-Nicet & Delphine Lahet, 2023. "Drivers of cross-border bank claims: The role of foreign-owned banks in emerging countries," Working Papers 2023.06, International Network for Economic Research - INFER.
- Thilo Reinschlussel & Martin C. Arnold, 2024. "Information-Enriched Selection of Stationary and Non-Stationary Autoregressions using the Adaptive Lasso," Papers 2402.16580, arXiv.org, revised Jul 2024.
- Dai, Linlin & Chen, Kani & Sun, Zhihua & Liu, Zhenqiu & Li, Gang, 2018. "Broken adaptive ridge regression and its asymptotic properties," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 334-351.
- Ruggieri, Eric & Lawrence, Charles E., 2012. "On efficient calculations for Bayesian variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1319-1332.
- Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023.
"High dimensional semiparametric moment restriction models,"
Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
- Chaohua Dong & Jiti Gao & Oliver Linton, 2017. "High dimensional semiparametric moment restriction models," Monash Econometrics and Business Statistics Working Papers 17/17, Monash University, Department of Econometrics and Business Statistics.
- Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP69/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP04/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," Monash Econometrics and Business Statistics Working Papers 23/18, Monash University, Department of Econometrics and Business Statistics.
- Dong, C. & Gao, J. & Linton, O., 2018. "High Dimensional Semiparametric Moment Restriction Models," Cambridge Working Papers in Economics 1881, Faculty of Economics, University of Cambridge.
- Li, Xingxiang & Cheng, Guosheng & Wang, Liming & Lai, Peng & Song, Fengli, 2017. "Ultrahigh dimensional feature screening via projection," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 88-104.
- Liming Wang & Xingxiang Li & Xiaoqing Wang & Peng Lai, 2022. "Unified mean-variance feature screening for ultrahigh-dimensional regression," Computational Statistics, Springer, vol. 37(4), pages 1887-1918, September.
- Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019.
"Non-separable models with high-dimensional data,"
Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
- Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
- Alena Skolkova, 2023. "Instrumental Variable Estimation with Many Instruments Using Elastic-Net IV," CERGE-EI Working Papers wp759, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
More about this item
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2023-09-25 (Econometrics)
- NEP-ETS-2023-09-25 (Econometric Time Series)
- NEP-FOR-2023-09-25 (Forecasting)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2308.16192. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.