On the Validity of Granger Causality for Ecological Count Time Series
Konstantinos G. Papaspyropoulos () and
Dimitris Kugiumtzis
Additional contact information
Konstantinos G. Papaspyropoulos: Laboratory of Forest Economics, School of Forestry and Natural Environment, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Dimitris Kugiumtzis: Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Econometrics, 2024, vol. 12, issue 2, 1-21
Abstract:
Knowledge of causal relationships is fundamental for understanding the dynamic mechanisms of ecological systems. To detect such relationships from multivariate time series, Granger causality, an idea first developed in econometrics, has been formulated in terms of vector autoregressive (VAR) models. Granger causality for count time series, often seen in ecology, has rarely been explored, and this may be due to the difficulty in estimating autoregressive models on multivariate count time series. The present research investigates the appropriateness of VAR-based Granger causality for ecological count time series by conducting a simulation study using several systems of different numbers of variables and time series lengths. VAR-based Granger causality for count time series (DVAR) seems to be estimated efficiently even for two counts in long time series. For all the studied time series lengths, DVAR for more than eight counts matches the Granger causality effects obtained by VAR on the continuous-valued time series well. The positive results, also in two ecological time series, suggest the use of VAR-based Granger causality for assessing causal relationships in real-world count time series even with few distinct integer values or many zeros.
Keywords: causal relationships; count data; vector autoregressive models; Granger causality index; conditional Granger causality index; MINAR (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.mdpi.com/2225-1146/12/2/13/pdf (application/pdf)
https://www.mdpi.com/2225-1146/12/2/13/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:12:y:2024:i:2:p:13-:d:1391256
Access Statistics for this article
Econometrics is currently edited by Ms. Jasmine Liu
More articles in Econometrics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().