Measuring financial contagion: a directed acyclic graphs and error correction model
Selma Jayech and
Naceur Ben Zina
International Journal of Business Innovation and Research, 2013, vol. 7, issue 1, 40-60
Abstract:
Vector autoregressions (VARs) are economically interpretable only when identified by being transformed into a structural form the (SVAR) in which the contemporaneous variables stand in a well-defined causal order. These identifying transformations are not unique. It is widely believed that practitioners must choose between them using a priori theory or other criteria not rooted in the data under analysis. We show how to apply graph-theoretical approach of searching for causal structure based on relations of conditional independence to select the possible causal orders - or at least to reduce the admissible them to a narrow equivalence class. This study investigates the dynamic structure of four major stock markets using an error correction model and directed acyclic graphs (DAG). The DAG representation provides a structure of causality among these markets in a contemporaneous time. Building this contemporaneous structure and the estimated error correction model, innovation accounting techniques are applied.
Keywords: directed acyclic graph; DAG; variance decomposition; forecast errors; financial contagion; error correction; VAR; vector autoregression; SVAR; structured vector autoregression; contemporaneous variables; causal orders; identifying transformations; a priori theories; graph-theoretical approaches; causal structures; conditional independence; narrow equivalence classes; dynamic structures; stock markets; causality; contemporaneous time; contemporaneous structures; accounting techniques; USA; United States; United Kingdom; UK; France; Germany; New York; London; Frankfurt; Paris; business innovation; business research. (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbire:v:7:y:2013:i:1:p:40-60
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