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A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance

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  • Boneva, Lena

    (Bank of England)

  • Linton, Oliver

    (University of Cambridge)

Abstract

What is the effect of funding costs on the conditional probability of issuing a corporate bond? We study this question in a novel dataset covering 5,610 issuances by US firms over the period from 1990 to 2014. Identification of this effect is complicated because of unobserved, common shocks such as the global financial crisis. To account for these shocks, we extend the common correlated effects estimator to settings where outcomes are discrete. Both the asymptotic properties and the sample behaviour of this estimator are documented. We find that for non-financial firms, yields are negatively related to bond issuance but that effect is larger in the pre-crisis period.

Suggested Citation

  • Boneva, Lena & Linton, Oliver, 2017. "A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance," Bank of England working papers 640, Bank of England.
  • Handle: RePEc:boe:boeewp:0640
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    Cited by:

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    2. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    3. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    4. Bartolucci, Francesco & Pigini, Claudia & Valentini, Francesco, 2021. "MCMC Conditional Maximum Likelihood for the two-way fixed-effects logit," MPRA Paper 110034, University Library of Munich, Germany.
    5. Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
    6. Abidi, Nordine & Miquel-Flores, Ixart, 2018. "Who benefits from the corporate QE? A regression discontinuity design approach," Working Paper Series 2145, European Central Bank.
    7. Feng, Qu, 2020. "Common factors and common breaks in panels: An empirical investigation," Economics Letters, Elsevier, vol. 187(C).
    8. Zaghini, Andrea, 2019. "The CSPP at work: Yield heterogeneity and the portfolio rebalancing channel," Journal of Corporate Finance, Elsevier, vol. 56(C), pages 282-297.
    9. Rachel Cho & Rodolphe Desbordes & Markus Eberhardt, 2022. "The causal effects of the darker side of financial development," Discussion Papers 2022-04, University of Nottingham, GEP.
    10. Chen, Jia & Shin, Yongcheol & Zheng, Chaowen, 2022. "Estimation and inference in heterogeneous spatial panels with a multifactor error structure," Journal of Econometrics, Elsevier, vol. 229(1), pages 55-79.
    11. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    12. Óscar Arce & Ricardo Gimeno & Sergio Mayordomo, 2017. "Making room for the needy: the credit-reallocation effects of the ECB’s corporate QE," Working Papers 1743, Banco de España.
    13. Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
    14. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    15. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    16. Eberhardt, Markus, 2018. "(At Least) Four Theories for Sovereign Default," CEPR Discussion Papers 13084, C.E.P.R. Discussion Papers.
    17. Mr. Markus Eberhardt & Mr. Andrea F Presbitero, 2018. "Commodity Price Movements and Banking Crises," IMF Working Papers 2018/153, International Monetary Fund.
    18. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    19. Jiti Gao & Oliver Linton & Bin Peng, 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Monash Econometrics and Business Statistics Working Papers 9/22, Monash University, Department of Econometrics and Business Statistics.
    20. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.

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    More about this item

    Keywords

    Heterogeneous panel data; discrete choice models; capital structure;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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