Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "7937"
  #_source: array:26 [
    "id" => "7937"
    "slug" => "causality-and-shock-analysis-in-the-french-industrial-sector"
    "yearMonth" => "1993-02"
    "year" => "1993"
    "title" => "Causality and Shock Analysis in the French Industrial Sector"
    "description" => "INDJEHAGOPIAN, J.P. et MOURAD, M. (1993). <i>Causality and Shock Analysis in the French Industrial Sector</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 21:00:33"
    "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" => "L'objet de ce papier est de présenter une modélisation des sept principaux indices mensuels de la production industrielle française à partir d'une approche empirique basée sur les données. Cette modélisation utilise l'analyse de causalité au sens de Granger et les autorégressions vectorielles. Les tests statistiques classiques de restriction sont utilisés pour détecter la non-causalité en relation avec le critère FPE d'Akaike."
      "en" => "This article illustrates the causal relationships according to Granger between the seven French  monthly industrial production variables uncorrected  for  seasonal variations. Dickey-Fuller's tests are used to decide the stationarity of all the variables. The series considered  in a wide sense as stationary are analyzed and modelled within an autoregressive vectorial (VAR) model constructed step by step. The infinite moving average (MA) representations of this VAR with orthogonalized innovations is made in order to analyze for each  component of the time series vector its sensitivity if shocks take place on its multiple causal variables. Finally for each component in the system VAR we constructed the equation of the variance decomposition for the different horizons."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-11-23T09:21:42.000Z"
    "docTitle" => "Causality and Shock Analysis in the French Industrial Sector"
    "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>Causality and Shock Analysis in the French Industrial Sector</b><br><span>1993-02 | Working Papers </span>"
    "docType" => "research"
    "publicationLink" => "<a href="#" target="_blank">Causality and Shock Analysis in the French Industrial Sector</a>"
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 8.822498
  +"parent": null
}