IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v118y2013i2p364-366.html

First-differenced inference for panel factor series

Author

Listed:
  • Ipatova, Ekaterina
  • Trapani, Lorenzo

Abstract

We complement existing inferential theory for panel factor models by deriving the asymptotics for the first differences of the estimated factors and common components obtained from a non-stationary panel factor model. As an application, we propose an estimator for the long run variance of the common components.

Suggested Citation

  • Ipatova, Ekaterina & Trapani, Lorenzo, 2013. "First-differenced inference for panel factor series," Economics Letters, Elsevier, vol. 118(2), pages 364-366.
    • Handle: RePEc:eee:ecolet:v:118:y:2013:i:2:p:364-366
    DOI: 10.1016/j.econlet.2012.11.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176512006167
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2012.11.026?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    2. Trapani, Lorenzo, 2013. "On bootstrapping panel factor series," Journal of Econometrics, Elsevier, vol. 172(1), pages 127-141.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    2. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    3. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    4. Yi‐Chiuan Wang & Jyh‐Lin Wu, 2015. "Fundamentals and Exchange Rate Prediction Revisited," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(8), pages 1651-1671, December.
    5. Holmes, Mark & Grimes, Arthur, 2005. "Is there long-run convergence of regional house prices in the UK?," Motu Working Papers 292891, Motu Economic and Public Policy Research.
    6. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    7. Reese, Simon, 2015. "Asymptotic Inference in the Lee-Carter Model for Modelling Mortality Rates," Working Papers 2015:16, Lund University, Department of Economics.
    8. Morana, Claudio, 2007. "Multivariate modelling of long memory processes with common components," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 919-934, October.
    9. Barigozzi, Matteo & Trapani, Lorenzo, 2020. "Sequential testing for structural stability in approximate factor models," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 5149-5187.
    10. Nuno Cassola & Claudio Morana, 2008. "Modeling Short-Term Interest Rate Spreads in the Euro Money Market," International Journal of Central Banking, International Journal of Central Banking, vol. 4(4), pages 1-37, December.
    11. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    12. Luya Wang & Zheng Li & Qi Li, 2023. "A Tale of Two Policies: Examining Treatment Effects on Housing Prices in Shenzhen, China," Annals of Economics and Finance, Society for AEF, vol. 24(2), pages 277-288, November.
    13. Jushan Bai & Josep Lluís Carrion‐i‐Silvestre, 2013. "Testing panel cointegration with unobservable dynamic common factors that are correlated with the regressors," Econometrics Journal, Royal Economic Society, vol. 16(2), pages 222-249, June.
    14. Herrerias, M.J., 2013. "The environmental convergence hypothesis: Carbon dioxide emissions according to the source of energy," Energy Policy, Elsevier, vol. 61(C), pages 1140-1150.
    15. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    16. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Papers 2111.11506, arXiv.org.
    17. Roman Matkovskyy, 2016. "Arbitrary temporal heterogeneity in time of European countries panel model," Economics Bulletin, AccessEcon, vol. 36(1), pages 576-587.
    18. Ghate, Chetan & Wright, Stephen, 2012. "The “V-factor”: Distribution, timing and correlates of the great Indian growth turnaround," Journal of Development Economics, Elsevier, vol. 99(1), pages 58-67.
    19. Morana, Claudio, 2009. "On the macroeconomic causes of exchange rate volatility," International Journal of Forecasting, Elsevier, vol. 25(2), pages 328-350.
    20. HORIE, Tetsushi & 堀江, 哲史 & YAMAMOTO, Yohei & 山本, 庸平, 2016. "Testing for Speculative Bubbles in Large-Dimensional Financial Panel Data Sets," Discussion Papers 2016-04, Graduate School of Economics, Hitotsubashi University.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    Statistics

    Access and download statistics

    Corrections

    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:ecolet:v:118:y:2013:i:2:p:364-366. 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/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.