Bootstrapping factor-augmented regression models
Author
Abstract
Suggested Citation
DOI: 10.1016/j.jeconom.2014.04.015
Download full text from publisher
As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.
Other versions of this item:
- Silvia Gonçalves & Benoit Perron, 2012. "Bootstrapping factor-augmented regression models," CIRANO Working Papers 2012s-12, CIRANO.
References listed on IDEAS
- Jushan Bai & Serena Ng, 2002.
"Determining the Number of Factors in Approximate Factor Models,"
Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
- Yohei Yamamoto, 2019.
"Bootstrap inference for impulse response functions in factor‐augmented vector autoregressions,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 247-267, March.
- Yohei Yamamoto, 2012. "Bootstrap Inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions," Global COE Hi-Stat Discussion Paper Series gd12-249, Institute of Economic Research, Hitotsubashi University.
- YAMAMOTO, Yohei & 山本, 庸平, 2016. "Bootstrap Inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions," Discussion paper series HIAS-E-26, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
- Yoosoon Chang & Joon Y. Park, 2003. "A Sieve Bootstrap For The Test Of A Unit Root," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 379-400, July.
- Connor, Gregory & Korajczyk, Robert A, 1993. "A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-1291, September.
- Bernanke, Ben S. & Boivin, Jean, 2003.
"Monetary policy in a data-rich environment,"
Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
- Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
- Ludvigson, Sydney C. & Ng, Serena, 2007.
"The empirical risk-return relation: A factor analysis approach,"
Journal of Financial Economics, Elsevier, vol. 83(1), pages 171-222, January.
- Sydney C. Ludvigson & Serena Ng, 2005. "The Empirical Risk-Return Relation: A Factor Analysis Approach," NBER Working Papers 11477, National Bureau of Economic Research, Inc.
- Sydney Ludvigson & Serena Ng, 2006. "The Empirical Risk-Return Relation: a factor analysis approach," 2006 Meeting Papers 236, Society for Economic Dynamics.
- Eichengreen, Barry & Mody, Ashoka & Nedeljkovic, Milan & Sarno, Lucio, 2012.
"How the Subprime Crisis went global: Evidence from bank credit default swap spreads,"
Journal of International Money and Finance, Elsevier, vol. 31(5), pages 1299-1318.
- Barry Eichengreen & Ashoka Mody & Milan Nedeljkovic & Lucio Sarno, 2009. "How the Subprime Crisis Went Global: Evidence from Bank Credit Default Swap Spreads," NBER Working Papers 14904, National Bureau of Economic Research, Inc.
- Barry Eichengreen & Ashoka Mody & Milan Nedeljkovic & Lucio Sarno, 2012. "How the Subprime Crisis Went Global: Evidence from Bank Credit Default Swap Spreads," Working papers 21, National Bank of Serbia.
- Shintani, Mototsugu & Guo, Zi-Yi, 2011. "Finite Sample Performance of Principal Components Estimators for Dynamic Factor Models: Asymptotic vs. Bootstrap Approximations," EconStor Preprints 167627, ZBW - Leibniz Information Centre for Economics.
- Corradi, Valentina & Swanson, Norman R., 2014.
"Testing for structural stability of factor augmented forecasting models,"
Journal of Econometrics, Elsevier, vol. 182(1), pages 100-118.
- Valentina Corradi & Norman Swanson, 2013. "Testing for Structural Stability of Factor Augmented Forecasting Models," Departmental Working Papers 201314, Rutgers University, Department of Economics.
- Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
- Jushan Bai & Serena Ng, 2006. "Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions," Econometrica, Econometric Society, vol. 74(4), pages 1133-1150, July.
- Connor, Gregory & Korajczyk, Robert A., 1986. "Performance measurement with the arbitrage pricing theory : A new framework for analysis," Journal of Financial Economics, Elsevier, vol. 15(3), pages 373-394, March.
- Bai, Jushan & Ng, Serena, 2013. "Principal components estimation and identification of static factors," Journal of Econometrics, Elsevier, vol. 176(1), pages 18-29.
- Sydney C. Ludvigson & Serena Ng, 2009.
"Macro Factors in Bond Risk Premia,"
The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
- Sydeny C. Ludvigson & Serena Ng, 2005. "Macro Factors in Bond Risk Premia," NBER Working Papers 11703, National Bureau of Economic Research, Inc.
- Chamberlain, Gary & Rothschild, Michael, 1983.
"Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets,"
Econometrica, Econometric Society, vol. 51(5), pages 1281-1304, September.
- Gary Chamberlain & Michael Rothschild, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," NBER Working Papers 0996, National Bureau of Economic Research, Inc.
- Chamberlain, Gary & Rothschild, Michael, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Scholarly Articles 3230355, Harvard University Department of Economics.
- Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
- Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.
- Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
- Nikolay Gospodinov & Serena Ng, 2013. "Commodity Prices, Convenience Yields, and Inflation," The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 206-219, March.
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.- Yoshimasa Uematsu & Takashi Yamagata, 2019.
"Estimation of Weak Factor Models,"
DSSR Discussion Papers
96, Graduate School of Economics and Management, Tohoku University.
- Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053, Institute of Social and Economic Research, Osaka University.
- Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053r, Institute of Social and Economic Research, Osaka University, revised Mar 2020.
- repec:cte:wsrepe:23974 is not listed on IDEAS
- Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019.
"A diagnostic criterion for approximate factor structure,"
Journal of Econometrics, Elsevier, vol. 212(2), pages 503-521.
- Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "A diagnostic criterion for approximate factor structure," Papers 1612.04990, arXiv.org, revised Aug 2017.
- Patrick Gagliardini & Elisa Ossola & O. Scaillet, 2016. "A Diagnostic Criterion for Approximate Factor Structure," Swiss Finance Institute Research Paper Series 16-51, Swiss Finance Institute, revised Dec 2016.
- Mao Takongmo, Charles Olivier & Stevanovic, Dalibor, 2015.
"Selection Of The Number Of Factors In Presence Of Structural Instability: A Monte Carlo Study,"
L'Actualité Economique, Société Canadienne de Science Economique, vol. 91(1-2), pages 177-233, Mars-Juin.
- Dalibor Stevanovic & Charles Olivier Mao Takongmo, 2014. "Selection of the number of factors in presence of structural instability: a Monte Carlo study," CIRANO Working Papers 2014s-44, CIRANO.
- Jushan Bai & Kunpeng Li & Lina Lu, 2016.
"Estimation and Inference of FAVAR Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 620-641, October.
- Bai, Jushan & Li, Kunpeng & Lu, Lina, 2014. "Estimation and inference of FAVAR models," MPRA Paper 60960, University Library of Munich, Germany.
- Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
- Gonçalves, Sílvia & Perron, Benoit, 2020.
"Bootstrapping factor models with cross sectional dependence,"
Journal of Econometrics, Elsevier, vol. 218(2), pages 476-495.
- Sílvia GONÇALVES & Benoit PERRON, 2018. "Bootstrapping Factor Models With Cross Sectional Dependence," Cahiers de recherche 10-2018, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- GONÇALVES, Sílvia & PERRON, Benoit, 2018. "Bootstrapping factor models with cross sectional dependence," Cahiers de recherche 2018-07, Universite de Montreal, Departement de sciences economiques.
- Bai, Jushan & Ando, Tomohiro, 2013. "Multifactor asset pricing with a large number of observable risk factors and unobservable common and group-specific factors," MPRA Paper 52785, University Library of Munich, Germany, revised Dec 2013.
- Catherine Doz & Peter Fuleky, 2019.
"Dynamic Factor Models,"
Working Papers
2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
- Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," PSE-Ecole d'économie de Paris (Postprint) halshs-02491811, HAL.
- Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
- Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," Post-Print halshs-02491811, HAL.
- Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
- Min Seong Kim, 2021. "Robust Inference for Diffusion-Index Forecasts with Cross-Sectionally Dependent Data," Working papers 2021-04, University of Connecticut, Department of Economics.
- Liang Chen & Juan J. Dolado & Jesús Gonzalo, 2021.
"Quantile Factor Models,"
Econometrica, Econometric Society, vol. 89(2), pages 875-910, March.
- Chen, Liang, 2017. "Quantile Factor Models," UC3M Working papers. Economics 25299, Universidad Carlos III de Madrid. Departamento de EconomÃa.
- Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
- Dolado, Juan J & Chen, Liang & Gonzalo, Jesus, 2018. "Quantile Factor Models," CEPR Discussion Papers 12716, C.E.P.R. Discussion Papers.
- Chen, Liang & Dolado, Juan J. & Gonzalo, Jesús, 2020. "Quantile Factor Models," IZA Discussion Papers 13870, Institute of Labor Economics (IZA).
- Yoshimasa Uematsu & Takashi Yamagata, 2020. "Inference in Weak Factor Models," ISER Discussion Paper 1080, Institute of Social and Economic Research, Osaka University.
- Varlam Kutateladze, 2021. "The Kernel Trick for Nonlinear Factor Modeling," Papers 2103.01266, arXiv.org.
- Fan, Jianqing & Ke, Yuan & Liao, Yuan, 2021.
"Augmented factor models with applications to validating market risk factors and forecasting bond risk premia,"
Journal of Econometrics, Elsevier, vol. 222(1), pages 269-294.
- Jianqing Fan & Yuan Ke & Yuan Liao, 2016. "Augmented Factor Models with Applications to Validating Market Risk Factors and Forecasting Bond Risk Premia," Papers 1603.07041, arXiv.org, revised Sep 2018.
- 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.
- Kutateladze, Varlam, 2022. "The kernel trick for nonlinear factor modeling," International Journal of Forecasting, Elsevier, vol. 38(1), pages 165-177.
- Alain-Philippe Fortin & Patrick Gagliardini & O. Scaillet, 2022.
"Eigenvalue tests for the number of latent factors in short panels,"
Swiss Finance Institute Research Paper Series
22-81, Swiss Finance Institute.
- Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
- Massacci, Daniele, 2017. "Least squares estimation of large dimensional threshold factor models," Journal of Econometrics, Elsevier, vol. 197(1), pages 101-129.
- Jushan Bai & Serena Ng, 2020. "Simpler Proofs for Approximate Factor Models of Large Dimensions," Papers 2008.00254, arXiv.org.
- repec:gnv:wpaper:unige:76321 is not listed on IDEAS
- Nii Ayi Armah & Norman Swanson, 2010.
"Seeing Inside the Black Box: Using Diffusion Index Methodology to Construct Factor Proxies in Large Scale Macroeconomic Time Series Environments,"
Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 476-510.
- Nii Ayi Armah & Norman R. Swanson, 2008. "Seeing inside the black box: Using diffusion index methodology to construct factor proxies in large scale macroeconomic time series environments," Working Papers 08-25, Federal Reserve Bank of Philadelphia.
- Norman R. Swanson & Nii Ayi Armah, 2011. "Seeing Inside the Black Box: Using Diffusion Index Methodology to Construct Factor Proxies in Largescale Macroeconomic Time Series Environments," Departmental Working Papers 201105, Rutgers University, Department of Economics.
More about this item
Keywords
Factor model; Bootstrap; Asymptotic bias;All these keywords.
JEL classification:
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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:eee:econom:v:182:y:2014:i:1:p:156-173. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.