IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/124015.html
   My bibliography  Save this paper

Metodología estándar de vectores autoregresivos (VAR) y de corrección del error (VEC)
[Standard methodology of vector autoregression (VAR) and error correction (VEC)]

Author

Listed:
  • John Michael, Riveros-Gavilanes

Abstract

English version This document provides a practical introduction to the standard methodology for estimating Vector Autoregression (VAR) models and their Vector Error Correction (VEC) approach in the context of cointegration. It covers basic concepts such as stationarity and unit roots, unit root testing, cointegration analysis, and the general estimation framework using Stata. The text does not delve into the mathematical formalization of the models but rather aims to serve as an applied estimation guide for undergraduate students. Spanish version Este documento presenta una introducción practica a la metodología estándar de la estimación de vectores auto-regresivos (VAR) y su aproximación de vectores con corrección del error (VEC) en el contexto de la cointegración. El documento presenta unas nociones básicas sobre el concepto de estacionariedad y raíz unitaria, la estimación de pruebas de raíces unitarias, la revisión de cointegración y el esquema general de estimación bajo el programa Stata. El texto no ahonda con la profundización matemática de los modelos sino más que nada aspira a ser una guía aplicada de estimación para los estudiantes de pregrado.

Suggested Citation

  • John Michael, Riveros-Gavilanes, 2025. "Metodología estándar de vectores autoregresivos (VAR) y de corrección del error (VEC) [Standard methodology of vector autoregression (VAR) and error correction (VEC)]," MPRA Paper 124015, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:124015
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/124015/1/MPRA_paper_123983.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Vector autoregresion; cointegracion; estacionariedad; series de tiempo;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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

    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:pra:mprapa:124015. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.