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Shrinkage Estimation of Common Breaks in Panel Data Models via Adaptive Group Fused Lasso

Author

Listed:
  • Su Liangjun

    (Singapore Management University)

  • Junhui Qian

    (Shanghai Jiao Tong University)

Abstract

In this paper we consider estimation and inference of common breaks in panel data models via adaptive group fused lasso. We consider two approaches — penalized least squares (PLS) for firstdifferenced models without endogenous regressors, and penalized GMM (PGMM) for first-differenced models with endogeneity. We show that with probability tending to one both methods can correctly determine the unknown number of breaks and estimate the common break dates consistently. We establish the asymptotic distributions of the Lasso estimators of the regression coefficients and their post Lasso versions. We also propose and validate a data-driven method to determine the tuning parameter used in the Lasso procedure. Monte Carlo simulations demonstrate that both the PLS and PGMM estimation methods work well in finite samples. We apply our PGMM method to study the effect of foreign direct investment (FDI) on economic growth using a panel of 88 countries and regions from 1973 to 2012 and find multiple breaks in the model.

Suggested Citation

  • Su Liangjun & Junhui Qian, 2015. "Shrinkage Estimation of Common Breaks in Panel Data Models via Adaptive Group Fused Lasso," Working Papers 07-2015, Singapore Management University, School of Economics.
    • Handle: RePEc:siu:wpaper:07-2015
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    File URL: http://ink.library.smu.edu.sg/soe_research/1745/
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    Citations

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    Cited by:

    1. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.
    2. Huanjun Zhu & Vasilis Sarafidis & Mervyn Silvapulle & Jiti Gao, 2015. "Testing for a Structural Break in Dynamic Panel Data Models with Common Factors," Monash Econometrics and Business Statistics Working Papers 20/15, Monash University, Department of Econometrics and Business Statistics.

    More about this item

    Keywords

    Adaptive Lasso; Change point; Group fused Lasso; Panel data; Penalized least squares; Penalized GMM; Structural change;
    All these 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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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