Dynamics Connectedness: TVP-VAR Insights into the Nexus between Selected Global Green Financial Instruments

Authors

  • Ganjar Primambudi Department of Economics, Kulliyyah of Economics and Management Sciences, International Islamic University Malaysia, Malaysia

DOI:

https://doi.org/10.18196/pas.v1i1.5

Keywords:

Carbon Policy, Dynamic Connectedness , Global Green Finance , Time-Varying Parameter Vector Autoregressive, Wavelet

Abstract

Research aims: This study investigates the dynamics of connectedness among global green financial instruments driven by low-carbon policies.

Design/Methodology/Approach: Employing the Time-Varying Parameter Vector Autoregressive (TVP-VAR) and Wavelet analysis, the researchers analyzed four primary variables derived from historical closing price indices, namely Global Carbon Efficient Index (SPGCEI), Global Clean Energy Index (SPGCE), Global Green Bond Index (SPGBI), and Global Sukuk Index (SPGSI). Daily data from January 2, 2015, to November 8, 2023, was considered. Data processing was then carried out utilizing E-Views 13 and R-Studio.

Research Findings: The findings demonstrated that a low-carbon policy stimulates green financing through the stock market and increases the bond and sukuk for carbon reduction. Moreover, the study revealed that the dynamic connectedness level of all variables was 45.25%. While the SPGCEI and SPGBI act as net pairwise transmitters, the SPGCE and SPGSI function as net pairwise receivers.

Theoretical Contribution/Originality: The study confirms that low-carbon policies drive green financing through stocks, promoting bond and sukuk activities for carbon reduction. By identifying the dynamic connectedness level and the roles of net transmitter and net receiver spillovers, it validates the impact of policies and introduces an innovative analytical framework for future research on the evolving dynamics of green finance.

Policy Implication: The study recommends regulatory efforts to enhance connectedness and liquidity in green financial instruments to foster an effective and sustainable low-carbon ecosystem.

References

Abakah, E. J. A., Tiwari, A. K., Sharma, A., & Mwamtambulo, D. J. (2022). Extreme Connectedness between Green Bonds, Government Bonds, Corporate Bonds and Other Asset Classes: Insights for Portfolio Investors. Journal of Risk and Financial Management, 15(10). https://doi.org/10.3390/jrfm15100477

Alola, A. A., & Kirikkaleli, D. (2019). The nexus of environmental quality with renewable consumption, immigration, and healthcare in the US: wavelet and gradual-shift causality approaches. Environmental Science and Pollution Research, 26(34), 35208–35217. https://doi.org/10.1007/s11356-019-06522-y

Anscombe, F. J., & Glynn, W. J. (1983). Distribution of the kurtosis statistic b2 for normal samples. Biometrika, 70(1), 227–234. https://doi.org/10.1093/biomet/70.1.227

Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions. Journal of Risk and Financial Management, 13(4), https://doi.org/10.3390/jrfm13040084

Ashraf, S., de Almeida, A. M. M., Naz, I., & Latief, R. (2023). Diversification of the Islamic stock market, Bitcoin, and Bullions in response to the Russia-Ukraine conflict and the COVID-19 outbreak. Heliyon, 9(8). https://doi.org/10.1016/j.heliyon.2023.e19023

Azhgaliyeva, D., Kapoor, A., & Liu, Y. (2020). Green bonds for financing renewable energy and energy efficiency in South-East Asia: a review of policies. Journal of Sustainable Finance and Investment, 10(2), 113–140. https://doi.org/10.1080/20430795.2019.1704160

Babu, M., Lourdesraj, A. A., Hariharan, C., Jayapal, G., Indhumathi, G., Sathya, J., & Kathiravan, C. (2022). Dynamics of volatility spillover between energy and environmental, social and sustainable indices. International Journal of Energy Economics and Policy, 12(6), 50-55. https://doi.org/10.32479/ijeep.13482

Balcilar, M., Gabauer, D., & Umar, Z. (2021a). Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach. Resources Policy, 73, 102219. https://doi.org/10.1016/j.resourpol.2021.102219

Bhuiyan, R. A., Rahman, M. P., Saiti, B., & Mat Ghani, G. (2019). Co-movement dynamics between global sukuk and bond markets: New insights from a wavelet analysis. International Journal of Emerging Markets, 14(4), 550–581. https://doi.org/10.1108/IJOEM-12-2017-0521

Broadstock, D., Ji, Q., Managi, S., & Zhang, D. (2021). Pathways to carbon neutrality: Challenges and opportunities. Resources, Conservation and Recycling, 169(February), 105472. https://doi.org/10.1016/j.resconrec.2021.105472

Chen, J., Li, L., Yang, D., & Wang, Z. (2023). The dynamic impact of green finance and renewable energy on sustainable development in China. Frontiers in Environmental Science, 10. https://doi.org/10.3389/fenvs.2022.1097181

Cui, Q., Ma, X., & Zhang, S. (2023). Does green finance drive low-carbon economic development? Evidence from China. Economic Research-Ekonomska Istrazivanja , 36(3). https://doi.org/10.1080/1331677X.2023.2183421

D’agostino, R. B. (1970). Transformation to normality of the null distribution of g1. Biometrika, 57(3), 679–681. https://doi.org/10.1093/biomet/57.3.679

da Silva, B. A., Constantino, M., de Oliveira, O. S., dos Santos, S. A. L., Tabak, B. M., & da Costa, R. B. (2019). New indicator for measuring the environmental sustainability of publicly traded companies: An innovation for the IPAT approach. Journal of Cleaner Production, 215, 354–363. https://doi.org/10.1016/j.jclepro.2019.01.039

Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66. https://doi.org/10.1016/j.ijforecast.2011.02.006

Diebold, F. X., & Yilmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119–134. https://doi.org/10.1016/j.jeconom.2014.04.012

Ehlers, T., Mojon, B., & Packer, F. (2020). Green bonds and carbon emissions: exploring the case for a rating system at the firm-level. BIS Quarterly Review, September, 31–47. https://ssrn.com/abstract=3748440

Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4), 813-836. https://doi.org/10.2307/2171846

Fisher, T. J., & Gallagher, C. M. (2012). New weighted portmanteau statistics for time series goodness of fit testing. Journal of the American Statistical Association, 107(498), 777–787. https://doi.org/10.1080/01621459.2012.688465

Fu, C., Lu, L., & Pirabi, M. (2023). Advancing green finance: a review of sustainable development. Digital Economy and Sustainable Development, 1(1), 1–19. https://doi.org/10.1007/s44265-023-00020-3

Gabauer, D., Chatziantoniou, I., & Stenfors, A. (2023). Model-free connectedness measures. Finance Research Letters, 54, 103804. https://doi.org/10.1016/j.frl.2023.103804

Gozgor, K., & Karakas, M. (2023). How do global financial markets affect the green bond markets? Evidence from different estimation techniques. Economic Research-Ekonomska Istrazivanja, 36(2). https://doi.org/10.1080/1331677X.2023.2177703

Gyamerah, S. A., Owusu, B. E., & Akwaa-Sekyi, E. K. (2022). Modelling the mean and volatility spillover between green bond market and renewable energy stock market. Green Finance, 4(3), 310–328. https://doi.org/10.3934/gf.2022015

Hammoudeh, S., Ajmi, A. N., & Mokni, K. (2020). Relationship between green bonds and financial and environmental variables: A novel time-varying causality. Energy Economics, 92, 104941. https://doi.org/10.1016/j.eneco.2020.104941

Hanif, W., Arreola Hernandez, J., Mensi, W., Kang, S. H., Uddin, G. S., & Yoon, S. M. (2021). Nonlinear dependence and connectedness between clean/renewable energy sector equity and European emission allowance prices. Energy Economics, 101, 105409. https://doi.org/10.1016/j.eneco.2021.105409

Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259. https://doi.org/10.1016/0165-1765(80)90024-5

Kartal, M. T., Kirikkaleli, D., & Ayhan, F. (2023). Nexus between non-performing loans and economic growth in emerging countries: Evidence from Turkey with wavelet coherence approach. International Journal of Finance and Economics, 28(2), 1250–1260. https://doi.org/10.1002/ijfe.2474

Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4

Kreibich, N., & Hermwille, L. (2021). Caught in between: credibility and feasibility of the voluntary carbon market post-2020. Climate Policy, 21(7), 939–957. https://doi.org/10.1080/14693062.2021.1948384

Lastrapes, W. D., & Wiesen, T. F. P. (2021). The joint spillover index. Economic Modelling, 94, 681–691. https://doi.org/10.1016/j.econmod.2020.02.010

Lu, X., Huang, N., Mo, J., & Ye, Z. (2023). Dynamics of the return and volatility connectedness among green finance markets during the COVID-19 pandemic. Energy Economics, 125. https://doi.org/10.1016/j.eneco.2023.106860

Michaelowa, A., Michaelowa, K., Hermwille, L., & Espelage, A. (2022). Towards net zero: making baselines for international carbon markets dynamic by applying ‘ambition coefficients.’ Climate Policy, 22(9–10), 1343–1355. https://doi.org/10.1080/14693062.2022.2108366

Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. https://doi.org/10.1016/S0165-1765(97)00214-0

Raddant, M., & Kenett, D. Y. (2021). Interconnectedness in the global financial market. Journal of International Money and Finance, 110. https://doi.org/10.1016/j.jimonfin.2020.102280

Rijanto, A. (2023). Co-Movements between an Asian Technology Stock Index and Cryptocurrencies during the COVID-19 Pandemic: A Bi-Wavelet Approach. Economies, 11(9). https://doi.org/10.3390/economies11090232

Rozman, A. T., & Azmi, N. A. (2022). Green Sukuk, Environmental Issues and Strategy. IOP Conference Series: Earth and Environmental Science, 1067(1). https://doi.org/10.1088/1755-1315/1067/1/012085

Schleussner, C. F., Lissner, T. K., Fischer, E. M., Wohland, J., Perrette, M., Golly, A., Rogelj, J., Childers, K., Schewe, J., Frieler, K., Mengel, M., Hare, W., & Schaeffer, M. (2016). Differential climate impacts for policy-relevant limits to global warming: The case of 1.5 °c and 2 °c. Earth System Dynamics, 7(2), 327–351. https://doi.org/10.5194/esd-7-327-2016

Thaker, H. M. T., & Mand, A. A. (2021). Bitcoin and stock markets: a revisit of relationship. Journal of Derivatives and Quantitative Studies, 29(3), 234–256. https://doi.org/10.1108/JDQS-07-2020-0016

Tiwari, A. K., Aikins Abakah, E. J., Gabauer, D., & Dwumfour, R. A. (2021). Green Bond, Renewable Energy Stocks and Carbon Price: Dynamic Connectedness, Hedging and Investment Strategies during COVID-19 pandemic. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3897284

Wang, K. H., Wang, Z. S., Yunis, M., & Kchouri, B. (2023). Spillovers and connectedness among climate policy uncertainty, energy, green bond and carbon markets: A global perspective. Energy Economics, 128, 107170. https://doi.org/10.1016/j.eneco.2023.107170

Wu, S., Tong, M., Yang, Z., & Zhang, T. (2021). Interconnectedness, systemic risk, and the influencing factors: Some evidence from China’s financial institutions. Physica A: Statistical Mechanics and Its Applications, 569. https://doi.org/10.1016/j.physa.2021.125765

Yadav, M. P., Ashok, S., Taghizadeh-Hesary, F., Dhingra, D., Mishra, N., & Malhotra, N. (2023). Uncovering time and frequency co-movement among green bonds, energy commodities and stock market. Studies in Economics and Finance. https://doi.org/10.1108/SEF-03-2023-0126

Yu, H., Jiang, Y., Zhang, Z., Shang, W. L., Han, C., & Zhao, Y. (2022). The impact of carbon emission trading policy on firms’ green innovation in China. Financial Innovation, 8(1). https://doi.org/10.1186/s40854-022-00359-0

Zhang, Y. F., & Umair, M. (2023). Examining the interconnectedness of green finance: an analysis of dynamic spillover effects among green bonds, renewable energy, and carbon markets. Environmental Science and Pollution Research, 30, 77605–77621. https://doi.org/10.1007/s11356-023-27870-w

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Published

2024-02-29

How to Cite

Primambudi, G. (2024). Dynamics Connectedness: TVP-VAR Insights into the Nexus between Selected Global Green Financial Instruments. Public Accounting and Sustainability, 1(1), 50–67. https://doi.org/10.18196/pas.v1i1.5

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