IDEAS home Printed from https://ideas.repec.org/p/hwc/wpaper/007.html
   My bibliography  Save this paper

Estimating long run e ects in models with cross-sectional dependence using xtdcce2

Author

Listed:
  • Jan Ditzen

    (Centre for Energy Economics Research and Policy, Heriot-Watt University)

Abstract

This paper describes how to estimate long run effects in a large heterogeneous panel data model with cross sectional dependence in Stata using the user written command xtdcce2. It builds on Chudik et al. (2016) and explains how to estimate models using the CS-DL and CS-ARDL estimator. In addition it includes a method how to estimate an error correction model.

Suggested Citation

  • Jan Ditzen, 2019. "Estimating long run e ects in models with cross-sectional dependence using xtdcce2," CEERP Working Paper Series 007, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    • Handle: RePEc:hwc:wpaper:007
    as

    Download full text from publisher

    File URL: http://ceerp.hw.ac.uk/RePEc/hwc/wpaper/007.pdf
    File Function: First version, 2019
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Jeffrey Kouton & Sulpice Amonle, 2021. "Global value chains, labor productivity, and inclusive growth in Africa: empirical evidence from heterogeneous panel methods," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 23(1), pages 1-23, June.
    2. Afees A. Salisu & Ibrahim D. Raheem & Godstime O. Eigbiremolen, 2022. "The behaviour of U.S. stocks to financial and health risks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4607-4618, October.
    3. Arnab Bhattacharjee & Jan Ditzen & Sean Holly, 2022. "Spatial and Spatio-Temporal Error Correction, Networks and Common Correlated Effects," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology, volume 43, pages 37-60, Emerald Group Publishing Limited.
    4. Afees A. Salisu & Ahamuefula E. Ogbonna & Tirimisiyu F. Oloko & Idris A. Adediran, 2021. "A New Index for Measuring Uncertainty Due to the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    5. Jian Xue & Zeeshan Rasool & Raima Nazar & Ahmad Imran Khan & Shaukat Hussain Bhatti & Sajid Ali, 2021. "Revisiting Natural Resources—Globalization-Environmental Quality Nexus: Fresh Insights from South Asian Countries," Sustainability, MDPI, vol. 13(8), pages 1-19, April.
    6. Vasudeva N. R. Murthy & Natalya Ketenci, 2020. "Capital mobility in Latin American and Caribbean countries: new evidence from dynamic common correlated effects panel data modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-17, December.
    7. Lateef Olawale Akanni, 2020. "Climatic Variations and Spatial Price Differentials of Perishable Foods in Nigeria," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 5(1), pages 1-15, June.
    8. Bhattacharjee, A. & Ditzen, J. & Holly, S., 2020. "Spatial and Spatio-temporal Engle-Granger representations, Networks and Common Correlated Effects," Cambridge Working Papers in Economics 2075, Faculty of Economics, University of Cambridge.
    9. Felix Fofana N¡¯Zue, 2020. "Is External Debt Hampering Growth in the ECOWAS Region?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 12(4), pages 1-54, April.

    More about this item

    Keywords

    xtdcce2; parameter heterogeneity; dynamic panels; cross section dependence; common correlated effects; pooled mean-group estimator; mean-group estimator; error correction model; ardl; long run coefficients;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

    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:hwc:wpaper:007. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Antonio Carvalho (email available below). General contact details of provider: http://ceerp.hw.ac.uk/ .

    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.