Granger Causality Test of Science & Technology Innovation Expense and New Urbanization—A Case Study of Hangzhou City

2016 ◽  
pp. 1-10
Author(s):  
Yuezhen Lyu ◽  
Yuzhe Wu ◽  
Ye Lin
Keyword(s):  
Granger Causality ◽  
Technology Innovation ◽  
Granger Causality Test ◽  
Causality Test ◽  
Science Technology ◽  
New Urbanization

Linking energy consumption with economic growth: Rwanda as a case study

2021 ◽  
pp. 181-200
Author(s):  
Gerard Bikorimana ◽  
Charles Rutikanga ◽  
Didier Mwizerwa
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Causality Test ◽  
Ardl Bounds Test ◽  
Causal Direction ◽  
Bounds Test ◽  
Toda And Yamamoto

This paper analyzes the link between energy consumption and economic growth in Rwanda for the period 1985-2017. The ARDL bounds test was used to test for the existence of co-integration, while the Toda and Yamamoto granger causality test was applied to test for causal direction. The results from the estimation of the ARDL bounds test showed that there was no evidence of co-integration between the considered variables under study. Additionally, the empirical findings confirmed that there was no relationship between economic growth and energy consumption in Rwanda. The findings supported the "neutrality hypothesis" between energy consumption and economic growth. This implies that neither conservative nor expansive policies in relation to energy consumption have any effect on economic growth. Furthermore, the study found a uni-directional granger causality running from energy consumption to economic growth. The results of this findings are consistent with the "growth hypothesis" which postulates that energy consumption leads to economic growth

scholarly journals Uncertainty Due to Infectious Diseases and Stock–Bond Correlation

Econometrics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 17
Author(s):  
Konstantinos Gkillas ◽  
Christoforos Konstantatos ◽  
Costas Siriopoulos
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Infectious Diseases ◽  
Granger Causality ◽  
Predictive Value ◽  
High Frequency ◽  
Causal Relation ◽  
Granger Causality Test ◽  
Causality Test ◽  
Non Linear

We study the non-linear causal relation between uncertainty-due-to-infectious-diseases and stock–bond correlation. To this end, we use high-frequency 1-min data to compute daily realized measures of correlation and jumps, and then, we employ a nonlinear Granger causality test with the use of artificial neural networks so as to investigate the predictability of this type of uncertainty on realized stock–bond correlation and jumps. Our findings reveal that uncertainty-due-to-infectious-diseases has significant predictive value on the changes of the stock–bond relation.

scholarly journals R&D Investment, Financial and Environmental Performance Nexuses via Bootstrap Fourier Quantiles Granger Causality Test

Economies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 85
Author(s):  
Feng-Li Lin
Keyword(s):  
Financial Performance ◽  
Granger Causality ◽  
Environmental Performance ◽  
Co2 Emission ◽  
Positive Relationship ◽  
Granger Causality Test ◽  
Causality Test ◽  
Emission Reductions ◽  
Policy Makers ◽  
D Investment

This study investigated the relationship between R&D investments and financial and environmental performance. The direction, size, and significance of various phases of these variables were generated using the bootstrap Fourier quantiles Granger causality test. In our results, a positive relationship between R&D investment and CO2 emission reductions was found at two tails of quantiles. Additionally, we observed a significantly positive relationship between financial performance and CO2 emission reductions at the 0.5 quantile and above. The correlation between R&D investment and financial performance was identified to be positive under the 0.3, 0.4, 0.5 and 0.9 quantiles and negative under the 0.5 and 0.6 quantiles. The changing linkages among R&D investment, environmental performance and financial performance found in this study provide important information for policy makers, aiding in the development of R&D strategies to upgrade financial and environmental performance simultaneously.

The effect of spillover on the Granger causality test

2010 ◽  
Vol 37 (9) ◽  
pp. 1473-1486 ◽  
Author(s):  
Panagiotis Mantalos ◽  
Ghazi Shukur
Keyword(s):  
Granger Causality ◽  
Granger Causality Test ◽  
Causality Test

The relationship between financial development and economic growth in Eswatini (formerly Swaziland)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Siphe-okuhle Fakudze ◽  
Asrat Tsegaye ◽  
Kin Sibanda
Keyword(s):  
Economic Growth ◽  
Granger Causality ◽  
Financial Development ◽  
Granger Causality Test ◽  
Causality Test ◽  
Content Type ◽  
Distributed Lag ◽  
Long Run ◽  
Short Run ◽  
The Relationship

PurposeThe paper examined the relationship between financial development and economic growth for the period 1996 to 2018 in Eswatini.Design/methodology/approachThe Autoregressive Distributed Lag bounds test (ARDL) was employed to determine the long-run and short-run dynamics of the link between the variables of interest. The Granger causality test was also performed to establish the direction of causality between financial development and economic growth.FindingsThe ARDL results revealed that there is a long-run relationship between financial development and economic growth. The Granger causality test revealed bidirectional causality between money supply and economic growth, and unidirectional causality running from economic growth to financial development. The results highlight that economic growth exerts a positive and significant influence on financial development, validating the demand following hypothesis in Eswatini.Practical implicationsPolicymakers should formulate policies that aims to engineer more economic growth. The policies should strike a balance between deploying funds necessary to stimulate investment and enhancing productivity in order to enliven economic growth in Eswatini.Originality/valueThe study investigates the finance-growth linkage using time series analysis. It determines the long-run and short-run dynamics of this relationship and examines the Granger causality outcomes.

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