Testing for Granger causality in heterogeneous mixed panels

Emirmahmutoğlu, Furkan; Köse, Nezir

doi:10.1016/j.econmod.2010.10.018

Cited by 399 publications

(353 citation statements)

References 28 publications

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“…Following the bootstrap procedure by Emirmahmutoglu and Kose [5], testing causality from x to y is summarized as follows:…”

Section: Panel Granger Causality Analysismentioning

confidence: 99%

“…The paper uses classical and augmented production functions as a basis for their tests, and thus does not account for cross-sectional dependence or homogeneity among countries. Additionally, their study looks at each country individually in a times-series 5 context, rather than in a panel. These factors may limit the inference one can make from the results.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The causality test proposed by Emirmahmutoglu and Kose [5] will be employed here that is based on the meta analysis of Fisher [28]. They extended the Lag Augmented VAR (LA-VAR) approach by Toda and Yamamoto [29], which uses the level VAR model with extra  , are column vectors of error terms, k i is the lag structure which is assumed to be known and may differ across crosssectional units, and dmax i is the maximal order of integration in the system for each i.…”

Section: Panel Granger Causality Analysismentioning

confidence: 99%

“…We employ the causality methodology proposed by Emirmahmutoglu and Kose [5] that controls for heterogeneity and cross-sectional dependence among cross-sections, addressing a shortcoming in the current literature. The members of the G7, although being the strongest economies are not similar in all aspects, and may have differentiating factors such as geography, climate, education, population size and government policy.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Renewable energy and growth: Evidence from heterogeneous panel of G7 countries using Granger causality

Chang

Gupta

Inglesi‐Lotz

et al. 2015

Renewable and Sustainable Energy Reviews

172

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In this paper we examine the causal relationship between renewable energy consumption and economic growth across the G7 countries, using annual data for the period of 1990 to 2011.By employing the causality methodology proposed by Emirmahmutoglu and Kose (2011), we investigate if there is a causal relationship between the variables. The advantage of this methodology is that it takes into account possible slope heterogeneity and cross-sectional dependency in a multivariate panel. The empirical results support the existence of a bidirectional causal relationship between economic growth and renewable energy for the overall panel. However, looking at the individual results for each country, the neutrality hypothesis is confirmed for Canada, Italy and the US; while for France and UK there is a unidirectional causality from GDP to renewable energy, and the opposite for Germany and Japan.

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“…Following the bootstrap procedure by Emirmahmutoglu and Kose [5], testing causality from x to y is summarized as follows:…”

Section: Panel Granger Causality Analysismentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Panel Granger Causality Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Renewable energy and growth: Evidence from heterogeneous panel of G7 countries using Granger causality

Chang

Gupta

Inglesi‐Lotz

et al. 2015

Renewable and Sustainable Energy Reviews

172

View full text Add to dashboard Cite

show abstract

“…Before proceeding for the Cointegration test, the econometric methodology says all the suggested variables in the model must be integrated in order I(1). Fowowe (2011) described that after testing the unit root there are two ways of testing the causality (i) the first condition is that when the variables are integrated in order I(1) and Cointegrated then the VECM is the best choice to be used, see also (Emirmahmutoglu & Kose, 2011;Fowowe, 2011;Moudatsou & Kyrkilis, 2011;Zhang, 2001) the (ii) way is that if the proposed variables are not integrated in the same order then the causality should be proceed by the VAR approach, see also (Fowowe, 2011;Toda & Phillips, 1993). But before going to the empirical analysis of a detailed summary of the proposed variables in Table 1.…”

Section: Data and Estimation Strategymentioning

confidence: 99%

Does Foreign Direct Investment Lead to Economic Growth? Evidences from Asian Developing Countries

Ali¹,

Mingque²

2018

IJEF

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The study about the interrelationship between FDI and economic growth in the host country is one of the hottest discussions. Some of the studies have evidence and consider FDI as the growth driver and some others don't. This study attempted to scrutinize the causal association of FDI with GDP in Indonesia, India, Malaysia and Bangladesh for the years of 1990 to 2014. Cointegration test has been applied in this study which shows that there is a long-term interrelationship within FDI and economic growth and then applied the Granger causality (GC) test which is based on the VECM. The short run results show that there are no evidence of causality direction from FDI to GDP and vice versa, whereas the long run results show that there is a positive impact of FDI and other variables to the GDP but not significant, and from GDP and other variables to FDI there is a negative interrelationship but significant. The results show the ambiguous interrelationship between FDI and economic growth.

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Investigation into the relationship between fatal work accidents, national income, and employment rate in developed and developing countries

Kahraman

Akay

Kılıç

2019

Journal of Occupational Health

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Objectives Industrial advances, as a result of globalization, causes many threats to the working life. These threats are generally associated with the level of economic development of countries. While threats from industrialization are decreasing in developed countries, developing countries are still faced with these threats. Therefore, this study aims to examine the relationship between fatal work accidents (FWA), and independent variables which are national income (NI) and employment rate (ER) in a number of selected countries. Methods In this study the relationship between FWA and independent variables which are NI and ER of 18 developed and developing countries and a region, between 2006 and 2015, was analyzed by applying panel data analysis. Results According to panel data analysis, whilst a 1% increase in the NI reduces the FWA rate by 1.1%, a 1% increase in the ER results in an increase of approximately 4% in the rate of FWA. Conclusions As a result, there was a negative relationship between the FWA and NI growth and a positive relationship with the ER

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Testing for Granger causality in heterogeneous mixed panels

Cited by 399 publications

References 28 publications

Renewable energy and growth: Evidence from heterogeneous panel of G7 countries using Granger causality

Renewable energy and growth: Evidence from heterogeneous panel of G7 countries using Granger causality

Does Foreign Direct Investment Lead to Economic Growth? Evidences from Asian Developing Countries

Investigation into the relationship between fatal work accidents, national income, and employment rate in developed and developing countries

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