4.1. Publication Trend
Table 2 shows the publication trend of Granger causality documents from 1981 to 2023 as of 14 February 2023. The first paper indexed in the Web of Science database is titled “Granger-causality in multiple time series” by TjØstheim [
103]. This paper, which was published in 1981, has received 21 citations to date. This paper studied the problem of constrained estimation in models with a known causality structure. The second paper listed on the Web of Science database is “Granger causality and the time series analysis of political relationships” by Freeman [
104], which was published in 1983 with 168 citations as of 14 February 2023. This paper discussed the application of Granger causality in the study of political relationships. The third indexed paper is “Granger causality and policy effectiveness” authored by Buiter [
105] in 1984, which has received 18 citations. This paper discussed the Granger causality and policy effectiveness with an optimizing controller as well as the Granger causality and automatic stabilizers. Another paper titled “A note on tests of Granger causality” was also published in 1984. This paper by Bessler and Kling [
106] has received 18 citations. This paper studied the issue of the relationship between the annual economic activity and annual sunspots.
The annual number of publications from 1981 to 1990 were low at only a single digit each year. There was a small fluctuation in the number of publications from 1991 to 2005. However, after 2005, there was a spike in the overall annual publication rate until 2022. The highest number of papers was also recorded in 2022 with 1150 documents. Therefore, it is predicted that the number of documents published in 2023 will exceed the number of documents in 2022, as Granger causality received notable attention from researchers.
Table 2 tabulates the annual publication and citation metrics of Granger causality documents from 1981 to 2023. The publication and citation trend of Granger causality publications are described in
Figure 2.
From
Table 2, the highest total number of citations (TC) was recorded in 2011 with 22,709 citations. There are four papers among the top 10 cited papers which were published in 2011 that contributed to the high number of total citations. The paper by Friston [
107] titled “Functional and effective connectivity: a review” was the third most cited paper with 1862 citations. The fifth most cited paper titled “Twitter mood predicts the stock market” by Bollen et al. [
108] has received 1225 citations. The sixth most cited paper is “Network modelling methods for fMRI” by Smith et al. [
109] with 1209 citations. The paper “FIAR: an R package for analyzing functional integration in the brain” by “Roelstraete and Rosseel [
13] received 1055 citations.
The highest number of citations per paper (C/P) and highest number of citations per cited paper (C/CP) were achieved by the only paper “Granger causality and the time series analysis of political relationships” by Freeman [
104] published in 1983. This paper has received 168 citations. The
h-index was the highest at 70 in 2010, 2011, and 2014. This means that 70 papers have been cited at least 70 times in 2010, 2011, and 2014. The highest
g-index of 144 was recorded in 2010 and 2011. There were 144 documents with a total of 20,736 citations published in 2010 and 2011.
4.3. Country Contribution
Researchers from about 150 countries have contributed to the publication of Granger causality from 1981 to 2023. The top 3 countries with the highest total publication (TP) were China (3114 documents), the United States (2113 documents), and Turkey (874 documents). Among the 274,321 total citations received from the 11701 documents, the United States received the highest number of citations with 80055 citations, which was more than 29% of the total citations. Meanwhile, England had the most impactful publications with 46.64 citations per paper (C/P) and 51.66 citations per cited paper (C/CP). The United States had the highest
h-index (125) and
g-index (225). A total of 125 documents have been cited more than 125 times while 225 documents have a cumulative number of more than 50,625 citations. Even though China had the highest total number of publications (TP), the publication impact (measured by C/P and C/CP) of these publications fell behind England, Malaysia, the United States, Turkey, Pakistan, Australia, Germany, and Italy.
Table 5 demonstrates the top 10 countries with the high contributions in Granger causality publications.
The country co-authorship diagram generated by VOSviewer shows the synergy of research collaboration among countries. The node size in the country co-authorship diagram reflects the strength of co-authorship. That is, when a country has high co-authorship with other countries, the node of the country will be large [
110]. The colour of the node and line show the country cluster [
111]. The thickness of the line connecting the two nodes indicates the co-authorship link strength. The link strength is the number of publications with co-authorship between two countries. A shorter line also indicates a stronger link [
112]. The total link strength of a country reflects the co-authorship strength of the country with all other countries [
113,
114].
Table 6 explains the top 10 countries with the highest number of co-authorships. The United States had the highest total link strength of 1454 documents from their total of 2113 publications, followed by China (1386), England (840), Pakistan (686), France (617), Turkey (572), Germany (515), Australia (487), Malaysia (444), and Italy (409). This means that the United States had the highest number of collaboration with other countries.
Figure 3 depicts the country co-authorship diagram of Granger causality publications. The United States had the largest node followed by China because these two countries have high total link strengths with 1454 and 1386 documents, respectively. The largest link strength of 292 was between the United States and China. This means that the United States and China had the highest number of co-authorships between countries and the line between them is the thickest. China and Pakistan had the second highest link strength of 188, followed by the United States and England (102), the United States and Germany (100), China and England (93), and China and Taiwan (86).
There were 13 clusters in total. The first cluster is in bright red and made up of Argentina, Azerbaijan, Bosnia and Herzegovina, Chile, Croatia, Czech Republic, Greece, Hungary, Italy, Macedonia, Poland, Romania, Serbia, Slovakia, Slovenia, Switzerland, and Ukraine. The second cluster is dark green and consists of Bahrain, Brazil, Columbia, Ecuador, Egypt, Jordan, Mexico, Oman, Portugal, Qatar, Saudi Arabia, Spain, Tunisia, and Uruguay. The third cluster is dark blue and contains Bangladesh, Belgium, Cuba, Finland, Germany, Japan, Laos, Luxembourg, Netherlands, Scotland, Sweden, Thailand, and Uzbekistan. The fourth cluster is a dark yellow with Cameroon, Cyprus, Ethiopia, Ghana, Kenya, Nigeria, Russia, Turkey, and Vietnam. The fifth cluster is dark purple and made up of Côte d’Ivoire, Indonesia, Iran, Kazakhstan, New Zealand, China, Philippines, Singapore, and South Korea. The sixth cluster is in bright blue with Denmark, England, France, Ireland, Israel, Lebanon, North Ireland, and Sri Lanka. The seventh cluster (orange) consists of Australia, Bulgaria, Fiji, Iraq, Malaysia, and Pakistan. The brown cluster contains Latvia, Lithuania, Morocco, Taiwan, and Wales. Algeria, Austria, Kuwait, and the United Arab Emirates make up the light purple-pink cluster. Canada, Norway, and Uganda are in the light red cluster. Brunei, South Africa, and Zimbabwe are in the light green cluster. The United States and Barbados are in one cluster. India and Peru make up one cluster.
4.4. Journals
There are about 200 journals that have published documents on Granger causality.
Table 7 displays the top 10 journals of Granger causality publications. Clarivate Analytics assesses the importance of a journal by measuring the frequency an average document in a journal is cited in a year with the use of Journal Impact Factor (JIF). Journals in the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) have JIFs. JIFs can be used to compare journals within the same field. A JIF is defined as the average number of citations obtained per document published in the journal in the past two years [
115]. For example, the JIF 2021 for the journal
Renewable & Sustainable Energy Reviews was 16.799. This means that the average number of citations received in 2021 for the documents published in this journal in 2019 and 2020 was 16.799 [
116].
The Journal Citation Index (JCI), which is also computed by Clarivate Analytics, offers a single journal level index to compare journals across all fields. All the journals in the Web of Science database have a JCI even though some of the journals do not have a JIF [
117]. For JCI 2021, the analysed years are 2018, 2019, and 2020. The global baseline value is 1.00. Therefore, a JCI higher than 1.00 indicates a higher than average citation impact while a JCI lower than 1.00 indicates a lower than average citation impact. For example,
Energy Economics received a JCI 2021 of 3.05. This means that, across this journal, the published documents received 3.05 times more citations than the average in the field [
118].
CiteScore is a measurement of the journal impact factor by the Scopus database. CiteScore includes document types such as articles, conference papers, book chapters, and data papers. CiteScore is calculated by using the number of citations obtained by a journal in a year to the number of documents published in the last four years, divided by the total document listed in the Scopus database during those four years [
119]. For example,
Renewable & Sustainable Energy Reviews has a CiteScore 2021 of 28.5. This means that, the average number of citations obtained in 2021 for the documents published in 2017, 2018, 2019, and 2020 was 28.5 [
120].
The SCImago Journal Rank (SJR) evaluates journals indexed in the Scopus database by assigning weights to the citations with regard to the journal’s importance. Therefore, citations in highly impactful journals receive greater weights that citations in less important journals. SJR is the average number of weighted citations obtained during a year per paper published in the past three years. For example, the SJR 2021 for
Renewable & Sustainable Energy Reviews was 3.678. Documents published in 2018, 2019, and 2020 in this journal obtained 3.678 weighted citations during 2021. This value also shows that
Renewable & Sustainable Energy Reviews has high prestige [
121].
The Source Normalized Impact per Paper (SNIP) examines the citation impact by calculating the weighted citations with regard to the total citations in a field. SNIP considers field-specific variation in citations. In a field where a citation is less probable, the impact of the citation will be assigned a greater weight. Likewise, where the citation potential is high in the field, the impact of the citation will be lower [
122,
123]. Based on
Table 7,
Environmental Science and Pollution Research (260) published the most documents on Granger causality, followed by
Energy Economics (174),
Applied Economics (156),
Neuroimage (154),
Sustainability (150),
PLoS One (118),
Applied Economics Letters (113),
Economic Modelling (111),
Resources Policy (107), and
Renewable & Sustainable Energy Reviews (103).
4.5. Most Cited Publication
Table 8 reveals the top 10 most cited publications on Granger causality. The most cited document “Saliency, switching, attention and control: a network model of insula function” by Menon and Uddin [
92] received 2603 citations. This paper presented a network model that the insula is sensitive to salient events and its core function is to mark such events for extra processing and initiate appropriate control signals. The second most cited document “Elements of Causal Inference: Foundations and Learning Algorithms” by Peters et al. [
93] studied the concept of causality and related problems. The third most cited paper by Friston [
75] reviewed the development and practice of connectivity analyses in neuroimaging, functional connectivity, causal modelling, connectomics, and multivariate analyses of distributed patterns of brain responses. Sridharan et al. [
94] used functional magnetic resonance imaging to study the mechanisms underlying the switching of brain networks in experiments. The next most cited paper by Bollen et al. [
76] applied a Granger causality analysis and fuzzy neural network to investigate the hypothesis that public mood states are predictive of changes in Dow Jones Industrial Average (DJIA) closing values. The result showed that the accuracy of DJIA predictions can be significantly improved by the inclusion of specific public mood dimensions.
The sixth most cited paper by Smith et al. [
77] studied the comparison among connectivity estimation approaches by using simulated FMRI data. The seventh most cited paper by Baccala and Sameshima [
95] presented a new frequency-domain approach based on the concept of Granger causality to describe the relationships between multivariate time series based on the decomposition of multivariate partial coherences determined from multivariate autoregressive models. The next most cited paper by Nolte et al. [
96] presented an approach that is insensitive to false connectivity arising from volume conduction for interpreting EEG data in terms of brain connectivity. Roelstraete and Rosseel [
13] introduced a functional integration analysis in an R (FIAR) package to perform various techniques for studying integration in brain networks. Sugihara et al. [
97] proposed a method based on nonlinear state space reconstruction which can distinguish causality from correlation.
The co-citation analysis of cited references shows the prestigious documents which are frequently cited together from another document [
130].
Figure 4 shows the co-citation analysis of cited references on Granger causality. The papers by Granger [
1] and Engle and Granger [
131] were cited 683 times in the 11701 documents on Granger causality. These two papers also have the highest link strengths of 16100 and 11346, respectively. The papers by Engle and Granger [
131] and Johansen and Juselius [
132] also have a high co-citation with a link strength of 675. The papers by Phillips and Perron [
133] and Dickey and Fuller [
134] also have high co-citation with a link strength of 652. Another set of papers with high co-citation and link strength of 587 are by Granger [
1] and Dickey and Fuller [
134]. The papers by Engle and Granger [
131] and Dickey and Fuller [
134] were also highly co-cited together with a link strength of 571. The papers by Granger [
1] and Geweke [
8] were also frequently cited together in other documents with a link strength of 507. The papers by Phillips and Perron [
133], Dickey and Fuller [
134], and Johansen and Juselius [
132] also have high link strengths of 7666, 7488, and 6726, respectively.
The co-citation of cited sources was also performed using VOSviewer and is shown in
Figure 5.
Energy Economics has the highest total link strength of 545250, followed by
NeuroImage (517050), and
Energy Policy (505603).
Econometrica (332271),
Renewable & Sustainable Energy Reviews (294434),
Journal of Econometrics (274903),
Journal of Neuroscience (207006),
Proceedings of the National Academy of Sciences (202995),
Environmental Science and Pollution Research (199643), and
Energy (192916) also have high total link strengths.
The co-citation analysis of cited authors shows the main contributors in the field of Granger causality [
130]. The top 10 co-cited researchers are Granger, C.W.J. (6762 citations, 61075 total link strength), Shahbaz, M. (2369 citations, 54951 total link strength), Pesaran, M.H. (3394 citations, 53148 total link strength), Apergis, N. (1867 citations, 46640 total link strength), Narayan, P.K. (2046 citations, 42402 total link strength), Johansen, S. (3296 citations, 41108 total link strength), Engle, R.F. (2548 citations, 31723 total link strength), Phillips, P.C.B. (1888 citations, 28485 total link strength), Ozturk, I. (1019 citations, 27371 total link strength), and Dickey, D.A. (2175 citations, 26510 total link strength).
Figure 6 portrays the co-citation analysis of the cited authors in Granger causality publications.
4.6. Keyword Analysis
VOSviewer also provides the keyword co-occurrence map to study the relationships between the keywords to allow scholars to determine the key ideas and the linkage of these key ideas in creating a sub-field for current and future research trends [
135,
136].
Table 9 shows the top 10 keywords with the respective total link strengths in Granger causality. “Granger causality” occurred 3963 times in all the 11,701 documents with a total link strength of 12,891, followed by “cointegration” (2128 occurrences, 11,166 total link strength) and economic growth (1590 occurrences, 8321 total link strength).
Figure 7 depicts the keyword co-occurrence map of the Granger causality publications.
Based on
Figure 7, the keywords can be classified into four clusters. The first cluster is red and consists of autoregressive distributed lag (ARDL), carbon emissions, causal relationship, causality analysis, China, economic growth, energy consumption, environmental Kuznets curve (EKC), error correction, exports, foreign direct investment (FDI), financial development, gross domestic product (GDP), globalization, hypothesis, income, Malaysia, non-renewable energy, OECD countries, panel cointegration, panel data, tourism, trade, Turkey, unit root tests, and urbanization. The second cluster, which is green, is made up of autoregressive time series, COVID-19, crude oil, dependence, determinants, efficiency, energy, exchange rate, granger causality, impact, India, inference, inflation, investment, market, monetary policy, oil price, return, risk, stock market, stock returns, transmission, unemployment, United States, vector autoregressive (VAR) model, vector error correction model (VECM), vector autoregressions, and volatility. The third cluster is blue and contains activation, brain, coherence, cortex, dynamics, EEG, effective connectivity, feedback, fMRI, functional connectivity, information flow, oscillations, prefrontal cortex, synchronization, and transfer entropy. The final cluster is in yellow and consists of great crash.
The keyword overlay visualization map in
Figure 8 explains the trend of Granger causality publications over time. The colour of the node and line represent the year of the documents contained the keywords were published. A lighter colour of the node and line show the recent focus of keywords in Granger causality [
137]. The recent research in Granger causality focused on renewable energy, non-renewable energy, trade openness, carbon emissions, ARDL, EKC, and globalization. This shows that Granger causality is increasingly being applied to study environmental science, energy, and economics. The current trend in Granger causality also shows that many studies are involved in two or more research areas to broaden the application of Granger causality. Moreover, many current studies have focused on green and sustainability in their papers, such as in business, energy, and transportation. For example, nuclear energy and renewable energy have been studied to assess their impacts on the ecological quality in the United States [
138], economic sustainability has been studied together with green resources, digitization, and financial development in Vietnam [
139] while energy consumption has also been investigated together with tourist arrivals in the Middle East [
140].