IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2405.07420.html
   My bibliography  Save this paper

Robust Inference for High-Dimensional Panel Data Models

Author

Listed:
  • Jiti Gao
  • Bin Peng
  • Yayi Yan

Abstract

In this paper, we propose a robust estimation and inferential method for high-dimensional panel data models. Specifically, (1) we investigate the case where the number of regressors can grow faster than the sample size, (2) we pay particular attention to non-Gaussian, serially and cross-sectionally correlated and heteroskedastic error processes, and (3) we develop an estimation method for high-dimensional long-run covariance matrix using a thresholded estimator. Methodologically and technically, we develop two Nagaev-types of concentration inequalities: one for a partial sum and the other for a quadratic form, subject to a set of easily verifiable conditions. Leveraging these two inequalities, we also derive a non-asymptotic bound for the LASSO estimator, achieve asymptotic normality via the node-wise LASSO regression, and establish a sharp convergence rate for the thresholded heteroskedasticity and autocorrelation consistent (HAC) estimator. Our study thus provides the relevant literature with a complete toolkit for conducting inference about the parameters of interest involved in a high-dimensional panel data framework. We also demonstrate the practical relevance of these theoretical results by investigating a high-dimensional panel data model with interactive fixed effects. Moreover, we conduct extensive numerical studies using simulated and real data examples.

Suggested Citation

  • Jiti Gao & Bin Peng & Yayi Yan, 2024. "Robust Inference for High-Dimensional Panel Data Models," Papers 2405.07420, arXiv.org, revised Aug 2024.
  • Handle: RePEc:arx:papers:2405.07420
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2405.07420
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hansheng Wang & Bo Li & Chenlei Leng, 2009. "Shrinkage tuning parameter selection with a diverging number of parameters," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 671-683, June.
    2. Caner, Mehmet & Kock, Anders Bredahl, 2018. "Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso," Journal of Econometrics, Elsevier, vol. 203(1), pages 143-168.
    3. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Haowen Bao & Yongmiao Hong & Yuying Sun & Shouyang Wang, 2024. "Sparse Interval-valued Time Series Modeling with Machine Learning," Papers 2411.09452, arXiv.org.

    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. Cécile Couharde & Rémi Generoso, 2015. "Hydro-climatic thresholds and economic growth reversals in developing countries: an empirical investigation," EconomiX Working Papers 2015-26, University of Paris Nanterre, EconomiX.
    2. Peter Fuleky & Carl S. Bonham & Qianxue Zhao, 2013. "Estimating Demand Elasticities in Non-Stationary Panels: The Case of Hawaii's Tourism Industry," Working Papers 201314, University of Hawaii at Manoa, Department of Economics.
    3. Peppel-Srebrny, Jemima, 2021. "Not all government budget deficits are created equal: Evidence from advanced economies' sovereign bond markets," Journal of International Money and Finance, Elsevier, vol. 118(C).
    4. Jessica M. Mc Lay & Roy Lay-Yee & Barry J. Milne & Peter Davis, 2015. "Regression-Style Models for Parameter Estimation in Dynamic Microsimulation: An Empirical Performance Assessment," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 83-127.
    5. Mishra, Vinod & Smyth, Russell, 2014. "Convergence in energy consumption per capita among ASEAN countries," Energy Policy, Elsevier, vol. 73(C), pages 180-185.
    6. Liu, Duan & Yu, Nizhou & Wan, Hong, 2022. "Does water rights trading affect corporate investment? The role of resource allocation and risk mitigation channels," Economic Modelling, Elsevier, vol. 117(C).
    7. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    8. Bui Huy Nhuong & Ho Dinh Bao & Le Thanh Ha, 2024. "Embracing Green Foreign Direct Investment in a Journey toward Global Sustainable Economy: An Empirical Approach Using Statistical Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 14(5), pages 435-446, September.
    9. Zhongwei, Huang & Liu, Yishu, 2022. "The role of eco-innovations, trade openness, and human capital in sustainable renewable energy consumption: Evidence using CS-ARDL approach," Renewable Energy, Elsevier, vol. 201(P1), pages 131-140.
    10. Carmen Broto & Javier Díaz-Cassou & Aitor Erce-Domínguez, 2008. "The Sources of Capital Flows Volatility: Empirical Evidence for Emerging Countries," Money Affairs, CEMLA, vol. 0(1), pages 93-128, January-J.
    11. Iheonu O Chimere & Tochukwu Nwachukwu, 2020. "Macroeconomic determinants of household consumption in selected West African countries," Economics Bulletin, AccessEcon, vol. 40(2), pages 1596-1606.
    12. Manuchehr Irandoust, 2019. "Saving and investment causality: implications for financial integration in transition countries of Eastern Europe," International Economics and Economic Policy, Springer, vol. 16(2), pages 397-416, April.
    13. Ostadzad, Ali Hossein, 2022. "Innovation and carbon emissions: Fixed-effects panel threshold model estimation for renewable energy," Renewable Energy, Elsevier, vol. 198(C), pages 602-617.
    14. Awaworyi Churchill, Sefa & Inekwe, John & Smyth, Russell & Zhang, Xibin, 2019. "R&D intensity and carbon emissions in the G7: 1870–2014," Energy Economics, Elsevier, vol. 80(C), pages 30-37.
    15. Nicholas M. Odhiambo & Talknice Saungweme, "undated". "Does International Tourism Spur International Trade In Ssa Countries? A Dynamic Panel Data Analysis," Working Papers AESRI07, African Economic and Social Research Institute (AESRI).
    16. Zhao, Jun & Shahbaz, Muhammad & Dong, Kangyin, 2022. "How does energy poverty eradication promote green growth in China? The role of technological innovation," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    17. jean georges innocent magloire TAPE & Kouamé Jean-Marc N'DRI, 2023. "Gestion du risque opérationnel et performance des banques en zone UEMOA," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 14(2), pages 128-141, December.
    18. Kyoji Fukao & Cristiano Perugini, 2021. "The Long‐Run Dynamics of the Labor Share in Japan," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(2), pages 445-480, June.
    19. Po-Chin Wu & Chung-Chih Lee, 2018. "The non-linear impact of monetary policy on international reserves: macroeconomic variables nexus," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 165-185, February.
    20. Paolo Di Caro & Roberta Arbolino & Ugo Marani, 2018. "A note on the effects of human capital policies in Italy during the Great Recession," Economics Bulletin, AccessEcon, vol. 38(3), pages 1302-1312.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2405.07420. 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.

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