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Maximum likelihood estimation of dynamic panel threshold models

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  • N. R. Ramírez-Rondán

Abstract

Threshold estimation methods are developed for dynamic panels with individual specific fixed effects covering short time periods. Maximum likelihood estimation of the threshold and slope parameters is proposed using first difference transformations. Threshold estimate is shown to be consistent and its asymptotic distribution is nonstandard when the number of individuals grows to infinity for a fixed time period; the slope estimates are consistent and asymptotically normally distributed. The method is applied to a sample of 74 countries and 11 periods of 5-year averages to determine the effect of inflation rate on long-run economic growth.

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  • N. R. Ramírez-Rondán, 2020. "Maximum likelihood estimation of dynamic panel threshold models," Econometric Reviews, Taylor & Francis Journals, vol. 39(3), pages 260-276, March.
    • Handle: RePEc:taf:emetrv:v:39:y:2020:i:3:p:260-276
    DOI: 10.1080/07474938.2019.1624401
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    1. Seo, Myung Hwan & Linton, Oliver, 2007. "A smoothed least squares estimator for threshold regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 704-735, December.
    2. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
    3. Yu, Ping, 2013. "Inconsistency of 2SLS estimators in threshold regression with endogeneity," Economics Letters, Elsevier, vol. 120(3), pages 532-536.
    4. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    5. Noelle I. Samia & Kung-Sik Chan, 2011. "Maximum likelihood estimation of a generalized threshold stochastic regression model," Biometrika, Biometrika Trust, vol. 98(2), pages 433-448.
    6. Norman Loayza & Pablo Fajnzylber & César Calderón, 2005. "Economic Growth in Latin America and the Caribbean : Stylized Facts, Explanations, and Forecasts," World Bank Publications - Books, The World Bank Group, number 7315.
    7. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    8. Chang, Roberto & Kaltani, Linda & Loayza, Norman V., 2009. "Openness can be good for growth: The role of policy complementarities," Journal of Development Economics, Elsevier, vol. 90(1), pages 33-49, September.
    9. Kourtellos, Andros & Stengos, Thanasis & Tan, Chih Ming, 2016. "Structural Threshold Regression," Econometric Theory, Cambridge University Press, vol. 32(4), pages 827-860, August.
    10. Enders, Walter & Granger, Clive W J, 1998. "Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 304-311, July.
    11. Lancaster, Tony, 2000. "The incidental parameter problem since 1948," Journal of Econometrics, Elsevier, vol. 95(2), pages 391-413, April.
    12. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
    13. repec:adr:anecst:y:1991:i:20-21:p:05 is not listed on IDEAS
    14. Richard Blundell & Richard J. Smith, 1991. "Conditions initiales et estimation efficace dans les modéles dynamiques sur données de panel : une application au comportement d'investissement des entreprises," Annals of Economics and Statistics, GENES, issue 20-21, pages 109-123.
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    Cited by:

    1. Zhu, Chaowei & Zhang, Fan & Zhang, Yuling, 2023. "Revisiting financial opening and financial development: A regulation heterogeneity perspective," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 181-197.
    2. Bournakis, Ioannis & Ramirez-Rondan, Nelson R., 2022. "Does uncertainty matter for the fiscal consolidation and capital intensity nexus?," MPRA Paper 111592, University Library of Munich, Germany.
    3. Nelson R. Ramírez-Rondán & Marco E. Terrones, 2024. "Uncertainty and the uncovered interest parity condition: How are they related?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 160(4), pages 1505-1542, November.
    4. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.

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    More about this item

    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

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