Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "8512"
  #_source: array:26 [
    "id" => "8512"
    "slug" => "var-modelling-of-macroeconomic-time-series-causality-and-shock-analysis"
    "yearMonth" => "1993-12"
    "year" => "1993"
    "title" => "Var Modelling of Macroeconomic Time Series : Causality and Shock Analysis"
    "description" => "INDJEHAGOPIAN, J.P. et MOURAD, M. (1993). <i>Var Modelling of Macroeconomic Time Series : Causality and Shock Analysis</i>. ESSEC Business School."
    "authors" => array:2 [
      0 => array:3 [
        "name" => "INDJEHAGOPIAN Jean-Pierre"
        "bid" => "B00000258"
        "slug" => "indjehagopian-jean-pierre"
      ]
      1 => array:1 [
        "name" => "MOURAD M."
      ]
    ]
    "ouvrage" => ""
    "keywords" => []
    "updatedAt" => "2020-12-17 18:37:46"
    "publicationUrl" => null
    "publicationInfo" => array:3 [
      "pages" => null
      "volume" => null
      "number" => null
    ]
    "type" => array:2 [
      "fr" => "Documents de travail"
      "en" => "Working Papers"
    ]
    "support_type" => array:2 [
      "fr" => "Editeur"
      "en" => "Publisher"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "Dans cet article, on décrit des relations dynamiques entre sept indexes pertinents du secteur de la production industrielle française, à partir d'une modélisation basée sur les données. On suppose que le processus générateur des données peut être représenté par une autorégression vectorielle (VAR) et on utilise l'approche de Caines et al. en relation avec le critère FPE pour spécifier la structure VAR. Les relations de causalité au sens de Granger entre les variables, déduites de l'estimation VAR sont étudiées. Enfin, on propose une procédure de sélection d'un ordre entre les variables d'un système économique afin que la méthode de Choleski  ne soit pas une méthode aveugle pour calculer les décompositions de la variance des erreurs de prévision et les fonctions de réponses. Cette procédure est appliquée au système économique étudié."
      "en" => "In this article we describe the dynamic relationships between seven indexes relevant to sectors of French industrial production, using a statistic model. It is assumed that the data-generating process can be accurately described by a vector autoregression (VAR) and the approach suggested by Caines, Keng and Sethi in relation to FPE criteria is used to specify the VAR structure. Granger's causality relationships between the variables deduced from the VAR estimation are studied. Lastly, we suggest a selection procedure for the ordering of the variables of an economic system so that the Choleski method is not applied blindly  to compute  the variance decompositions and impulse responses. This procedure is applied to the economic system being studied."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-11-21T14:21:49.000Z"
    "docTitle" => "Var Modelling of Macroeconomic Time Series : Causality and Shock Analysis"
    "docSurtitle" => "Working Papers"
    "authorNames" => "<a href="/cv/indjehagopian-jean-pierre">INDJEHAGOPIAN Jean-Pierre</a>, MOURAD M."
    "docDescription" => "<span class="document-property-authors">INDJEHAGOPIAN Jean-Pierre, MOURAD M.</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">1993</span>"
    "keywordList" => ""
    "docPreview" => "<b>Var Modelling of Macroeconomic Time Series : Causality and Shock Analysis</b><br><span>1993-12 | Working Papers </span>"
    "docType" => "research"
    "publicationLink" => "<a href="#" target="_blank">Var Modelling of Macroeconomic Time Series : Causality and Shock Analysis</a>"
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 8.670292
  +"parent": null
}