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On estimating long-run effects in models with lagged dependent variables

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  • Reed, W. Robert
  • Zhu, Min

Abstract

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.

Suggested Citation

  • Reed, W. Robert & Zhu, Min, 2017. "On estimating long-run effects in models with lagged dependent variables," Economic Modelling, Elsevier, vol. 64(C), pages 302-311.
    • Handle: RePEc:eee:ecmode:v:64:y:2017:i:c:p:302-311
    DOI: 10.1016/j.econmod.2017.04.006
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    2. Luís Miguel Marques & José Alberto Fuinhas & António Cardoso Marques, 2019. "Are There Spillovers from China on the Global Energy-Growth Nexus? Evidence from Four World Regions," Economies, MDPI, vol. 7(2), pages 1-19, June.
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    6. Wang, Delu & Wang, Yadong & Jiang, Wuding & Shi, Xunpeng, 2023. "Has outward foreign direct investment alleviated industrial overcapacity in China? An empirical test of the upstream and downstream industrial links," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 250-263.

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    More about this item

    Keywords

    Hurwicz bias; Auto-Regressive Distributed-Lag (ARDL) models; Dynamic Panel Data (DPD) models; DPD estimators; long-run impact; long-run propensity; Fieller’s method; indirect inference; jackknifing;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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