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Does Systematic Sampling Preserve Granger Causality with an Application to High Frequency Financial Data?

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  • Gulasekaran Rajaguru

    (Bond Business School, Bond University, Robina, QLD 4226, Australia)

  • Michael O’Neill

    (Bond Business School, Bond University, Robina, QLD 4226, Australia)

  • Tilak Abeysinghe

    (Department of Economics, National University of Singapore, Singapore 117570, Singapore)

Abstract

In applied econometric literature, the causal inferences are often made based on temporally aggregated or systematically sampled data. A number of studies document that temporal aggregation has distorting effects on causal inference and systematic sampling of stationary variables preserves the direction of causality. Contrary to the stationary case, this paper shows for the bivariate VAR(1) system that systematic sampling induces spurious bi-directional Granger causality among the variables if the uni-directional causality runs from a non-stationary series to either a stationary or a non-stationary series. An empirical exercise illustrates the relative usefulness of the results further.

Suggested Citation

  • Gulasekaran Rajaguru & Michael O’Neill & Tilak Abeysinghe, 2018. "Does Systematic Sampling Preserve Granger Causality with an Application to High Frequency Financial Data?," Econometrics, MDPI, vol. 6(2), pages 1-24, June.
    • Handle: RePEc:gam:jecnmx:v:6:y:2018:i:2:p:31-:d:152860
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    References listed on IDEAS

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    2. Gulasekaran Rajaguru & Safdar Ullah Khan, 2021. "Causality between Energy Consumption and Economic Growth in the Presence of Growth Volatility: Multi-Country Evidence," JRFM, MDPI, vol. 14(10), pages 1-26, October.
    3. Bilson, Chris & Brailsford, Tim & Rajaguru, Gulasekaran, 2022. "Covered interest rate parity deviations in the Asia-Pacific," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    4. Michael O'Neill & Gulasekaran Rajaguru, 2020. "A response surface analysis of critical values for the lead‐lag ratio with application to high frequency and non‐synchronous financial data," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(4), pages 3979-3990, December.

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