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Causal ordering and inference on acyclic networks

Author

Listed:
  • Gopal K. Basak

    (Indian Statistical Institute)

  • Arnab Bhattacharjee

    (Heriot-Watt University)

  • Samarjit Das

    (Indian Statistical Institute)

Abstract

This paper develops a new identification result for the causal ordering of observation units in a recursive network or directed acyclic graph. Inferences are developed for an unknown spatial weights matrix in a spatial lag model under the assumption of recursive ordering. The performance of the methods in finite sample settings is very good. Application to data on portfolio returns produces interesting new evidences on the contemporaneous lead–lag relationships between the portfolios and generates superior predictions.

Suggested Citation

  • Gopal K. Basak & Arnab Bhattacharjee & Samarjit Das, 2018. "Causal ordering and inference on acyclic networks," Empirical Economics, Springer, vol. 55(1), pages 213-232, August.
    • Handle: RePEc:spr:empeco:v:55:y:2018:i:1:d:10.1007_s00181-018-1454-3
    DOI: 10.1007/s00181-018-1454-3
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    Cited by:

    1. 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.
    2. Otto, Philipp & Sibbertsen, Philipp, 2023. "Spatial autoregressive fractionally integrated moving average model," Hannover Economic Papers (HEP) dp-712, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Philipp Otto & Wolfgang Schmid, 2021. "Generalized Spatial and Spatiotemporal ARCH Models," Papers 2106.10477, arXiv.org.
    4. Deborah Gefang & Stephen G. Hall & George S. Tavlas, 2022. "Fast Two-Stage Variational Bayesian Approach to Estimating Panel Spatial Autoregressive Models with Unrestricted Spatial Weights Matrices," Papers 2205.15420, arXiv.org, revised Aug 2023.
    5. Philipp Otto & Wolfgang Schmid, 2023. "A general framework for spatial GARCH models," Statistical Papers, Springer, vol. 64(5), pages 1721-1747, October.
    6. Arnab Bhattacharjee & Sudipto Roy, 2019. "Abnormal Returns or Mismeasured Risk? Network Effects and Risk Spillover in Stock Returns," JRFM, MDPI, vol. 12(2), pages 1-13, March.
    7. Miryam S. Merk & Philipp Otto, 2022. "Estimation of the spatial weighting matrix for regular lattice data—An adaptive lasso approach with cross‐sectional resampling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(1), February.

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    More about this item

    Keywords

    Spatial weights matrix; Directed acyclic graphs; Recursive ordering; M-estimation; Portfolio returns; Partial identification;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • 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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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