Please use this identifier to cite or link to this item: https://doi.org/10.3390/econometrics6020031
Title: Does systematic sampling preserve granger causality with an application to high frequency financial data?
Authors: Rajaguru G.
O’neill M.
Abeysinghe T. 
Issue Date: 2018
Citation: Rajaguru G., O’neill M., Abeysinghe T. (2018). Does systematic sampling preserve granger causality with an application to high frequency financial data?. Econometrics 6 (2) : 31. ScholarBank@NUS Repository. https://doi.org/10.3390/econometrics6020031
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. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
Source Title: Econometrics
URI: https://scholarbank.nus.edu.sg/handle/10635/174600
ISSN: 2225-1146
DOI: 10.3390/econometrics6020031
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