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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 |
Appears in Collections: | Elements Staff Publications |
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