Time-varying Granger Causality Research Articles

Electronic Payments System and Banking Industry’s Return in Nigeria: A Time-Varying Granger Causality Approach

<p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">The paper is motivated by the growth of the electronic payments system and its relevance in enhancing the banking industry's earnings. Consequently, the paper examines the causal relationship between the electronic payments system and the banking industry's returns in Nigeria. The paper offers some important contributions to the literature involving the use of an approach that allows for data-driven identification of the change points in the electronic payments system and the banking industry's returns nexus. The paper discovered three important findings. First, the causal relationship between the electronic payments system and the banking industry's returns in Nigeria changes with time changes. Second, there is evidence of causality between the electronic payments system and returns on assets and equity, however, the causality was more evident under the recursive window. Third, the causal relationship was more evident in some specific periods such as 2020Q4, all quarters of 2015 to 2016, and 2020 to the end of 2023. The paper recommends that policymakers should revisit and reinvigorate the specific cashless policies instituted in 2012-2016 that aided higher returns to the banking industry. Similarly, the Central Bank of Nigeria and other banking industry players should intensify efforts to encourage the use of electronic payments due to their usefulness and ability to enhance the banking industry's earnings.</span></p>

Dynamic interactions between oil prices and renewable energy production in Italy amid the COVID-19 pandemic: wavelet and machine learning analyses

AbstractThis study examines the intricate dynamics between oil prices and renewable energy investments in Italy during the initial phase of the CoronaVirus Disease 2019 pandemic, a period characterized by significant economic and social upheaval. Utilizing advanced empirical techniques, such as Partial Wavelet Coherency analysis, Time-Varying Granger Causality, and Robinson Log-Periodogram tests, as well as Machine Learning (ML) regressions, this research uncovers nuanced insights into the interplay between oil prices and renewable energy series including biomass, solar, hydro, wind, and geothermal. Key findings indicate a predominant in-phase relationship with oil prices leading most renewable energy series, and unidirectional causality from renewables to oil prices in several instances, highlighting the potential influence of renewable energy on oil market dynamics. In robustness checks, ML models further elucidate the impact, with solar, hydro, and geothermal sources showing significant importance scores. These insights are critical for policymakers and stakeholders aiming to enhance energy security and transition towards sustainable energy sources amidst global crises.

Divisia Monetary Aggregates for India

Abstract In this paper, we are motivated by the fast growing literature that investigates the performance of Divisia monetary aggregates. We construct Divisia monetary aggregates for India using monthly data form January 2001 to March 2020 and present a comprehensive comparison across the Indian Divisia monetary aggregates at four levels of monetary aggregation, M1, M2, M3, and M4. We do so in the context of three classes of empirical models. In particular, we compute correlations between the cyclical components of the Divisia monetary aggregates and the cyclical component of the industrial production index. We test for Granger causality running from the Divisia monetary aggregates to industrial production. We also test for time-varying Granger causality. We find that the levels of the Divisia monetary aggregates Granger cause economic activity in India during normal times, but the causal link broke during and in the aftermath of the extremely unusual circumstances of the Covid-19 crisis.

Green environments reimagined through the lens of green finance, green innovations, green taxation, and green energies. Wavelet quantile correlation and rolling window-based quantile causality perspective

Unarguably, a compromised environment portends negativities to humankind. Hence, we explored the potential of green finance, green innovations, green taxes, and green energy for green developments in South Africa (SA). Annual time-series data spanning 1996–2022 and cutting-edge estimators exposed the predictive effects of the under-listed variables on green environments. This includes the wavelet quantile correlation, time-varying Granger causality, and rolling window-based non-parametric quantile causality. The novel insights underscore the vital role of green finance in ensuring green growth, irrespective of some notable divergences over time. Likewise, green innovations, green taxes, and green energies produced notable environmental enhancing effects with underlining asymmetric effects across the time and quantiles of the distributions. The outcomes of the recursive evolving window algorithm and the rolling window-based quantile correlation portray that green finance, green innovations, green taxes, and green energies are significant positive enablers of green growth in SA. SA should forestall all the factors leading to the observed divergences as a policy option. This could be achieved through improved green finances and consistent promotion of all relevant green initiatives. These steps will aid the green revolution and enable the emergence of green development in the republic.

The nexus between climate change, conflicts and food security in Somalia: empirical evidence from time-varying Granger causality

The nexus between climate change, conflicts and food security in Somalia: empirical evidence from time-varying Granger causality

Correlation meets causality: A holistic measure of financial contagion

This study introduces a new measure of financial contagion. We argue that a rapid increase in correlations between two series is necessary but not sufficient for contagion to occur, and develop a contagion test that combines dynamic conditional correlations with time-varying Granger causality. We empirically illustrate our new approach using systemic risk data covering the period 1996–2023. We show that there are periods when correlations increase rapidly without causality, as well as periods when causality is present but correlations do not increase. The proposed test enables data-driven detection of contagion episodes and provides a clear distinction between interconnectedness and contagion.

On the time-varying impact of China's bilateral political relations on its trading partners: “Doux commerce” or “trade follows the flag”?

We assess the impact of China's bilateral political relations with three main trading partners—the US, Germany, and the UK—on current account balances and exchange rates, over the 1960Q1–2022Q4 period. Relying on the lag-augmented VAR approach with time-varying Granger causality tests, we find that political relationships with China strongly matter in explaining the dynamics of current accounts and exchange rates, supporting the “trade follows the flag” view. Such relationships cause the evolution of the exchange rate (except in the UK) and the current account; these causal links being time-varying for the US and the UK and robust over the entire period for Germany. These findings suggest that policymakers should account for bilateral political relationships to understand the global macroeconomic consequences of political tensions.

Money-Output Revisited: Time-Varying Granger Causality Evidence from Forty-Three Countries

Money-Output Revisited: Time-Varying Granger Causality Evidence from Forty-Three Countries

Climate policy uncertainty, media coverage of climate change, and energy markets: New evidence from time-varying causality analysis

Climate change is one of the most critical issues in the last decade, making investigating climate change risks' effects on the economy vital. Employing a novel time-varying Granger causality approach, we test causality from climate policy uncertainty (CPU) to the index returns of clean energy and nonrenewable energy sectors between November 2009 and December 2021. Our analysis generally reveals a significant causality from CPU to S&P clean energy sector index return throughout the sample period. In contrast, very limited significant causality is observed running from the CPU to the S&P nonrenewable energy index return. This result implies that investments in clean energy firms are affected by the CPU due to the cost of reversing the decisions in uncertain environments. On the other hand, the U.S. newspaper media coverage of climate change has a significant impact not only on the clean energy index returns but also on non-renewable energy index returns, implying an increase in the media coverage regarding climate change influences the awareness of investors on climate change, which affects their trading strategies.

Exploring the dynamic capability of green technology innovation for achieving sustainable development: an empirical insight from China

ABSTRACT During the past several decades, the world has been putting strong emphasis on the role of environmental technology innovation which can reduce environmental degradation and promote sustainable development. This research sheds light on the impact of green technology or eco innovation on sustainable development for China. Additionally, the effects of other variables such as governance, information and communication technology, trade uncertainty and urban population are also analysed. The study employs Fully modified ordinary least squares (FMOLS) and Canonical Cointegration Regression (CCR) as the long run tests and Breitung and Candelon Spectral Granger-Causality as the time varying granger causality test. The results suggest that green innovation promotes sustainable development in the long run. The roles of governance quality and urbanization are also found to be positive while the role of ICT is found to be insignificant yet negative. The role of trade uncertainty is positive yet insignificant. Based on these results, the study calls for the private and public organizations and industries to invest in eco innovation. Different incentives from the government can also encourage private industries to invest in green innovation technologies.

Time-Varying Granger causality between dollarization, exchange rate and stock market: Lag-Augmented Vector Autoregressive (LA-VAR) Approach

Time-Varying Granger causality between dollarization, exchange rate and stock market: Lag-Augmented Vector Autoregressive (LA-VAR) Approach

The link between electricity consumption and stock market during the pandemic in Türkiye: a novel high-frequency approach

This article examines the relationship between electricity consumption and the stock market in the Turkish economy during the COVID-19 pandemic. A novel high-frequency model is used, incorporating the hourly energy consumption and Borsa Istanbul (BIST) National stock market index variables. To determine the effect of electricity consumption on the stock market index and vice versa, a high-frequency VAR-based spillover approach, time-varying Granger causality, and time-varying Bayesian VAR analysis are employed. The findings reveal a positive and weak relationship between electricity consumption and the stock market but it has a time-varying nature in an emerging market context in the post-COVID-19 period in the Turkish economy.

Time-Varying Bidirectional Causal Relationships between Transaction Fees and Economic Activity of Subsystems Utilizing the Ethereum Blockchain Network

The Ethereum blockchain network enables transaction processing and smart-contract execution through levies of transaction fees, commonly known as gas fees. This framework mediates economic participation via a market-based mechanism for gas fees, permitting users to offer higher gas fees to expedite processing. Historically, the ensuing gas fee volatility led to critical disequilibria between supply and demand for block space, presenting stakeholder challenges. This study examines the dynamic causal interplay between transaction fees and economic subsystems leveraging the network. By utilizing data related to unique active wallets and transaction volume of each subsystem and applying time-varying Granger causality analysis, we reveal temporal heterogeneity in causal relationships between economic activity and transaction fees across all subsystems. This includes (a) a bidirectional causal feedback loop between cross-blockchain bridge user activity and transaction fees, which diminishes over time, potentially signaling user migration; (b) a bidirectional relationship between centralized cryptocurrency exchange deposit and withdrawal transaction volume and fees, indicative of increased competition for block space; (c) decentralized exchange volumes causally influence fees, while fees causally influence user activity, although this relationship is weakening, potentially due to the diminished significance of decentralized finance; (d) intermittent causal relationships with maximal extractable value bots; (e) fees causally influence non-fungible token transaction volumes; and (f) a highly significant and growing causal influence of transaction fees on stablecoin activity and transaction volumes highlight its prominence. These results inform strategic considerations for stakeholders to more effectively plan, utilize, and advocate for economic activities on Ethereum, enhancing the understanding and optimization of within the rapidly evolving economy.

Geopolitical Risks and Food Inflation Dynamics in Nigeria: A Time-Varying Granger Causality Analysis

Geopolitical Risks and Food Inflation Dynamics in Nigeria: A Time-Varying Granger Causality Analysis

Time-varying causality relationships between trade openness, technological innovation, industrialization, financial development, and carbon emissions in Thailand.

Over the last twenty years, there has been swift growth in industrialization and technological advancements, driving economic progress. Nevertheless, it is inevitable that these sectors will bring about environmental shifts. Thus far, endeavors have been undertaken to assess the influence of industrialization and technological advancements on environmental deterioration. Additionally, the extensive discussion surrounding the impact of financial development, trade openness, and technological innovation on the environment has not yielded conclusive empirical findings. Studies often operate under the assumption of symmetric relationships, potentially leading to biased results. Adding to the discussion on the drivers of carbon neutrality, the time-dependent effects of critical aspects such as financial development and technological innovation should inform meaningful policies for environmental management. This article explores the time-varying causal association between trade openness, industrialization, financial development, technological innovation, and CO2 emissions in Thailand using novel time-varying Granger causality tests. The time-varying causality outcomes demonstrate that the associations change significantly over time, in contrast to the results of Toda-Yamamoto causality. Overall, there exists a bidirectional relationship between industrialization, financial development, trade openness, technological innovation, and CO2 emissions over different time sequences. These outcomes have implications for both policy and research.

A time-varying Granger Causality Approach to the Inflation-Insecurity Nexus in Nigeria

A time-varying Granger Causality Approach to the Inflation-Insecurity Nexus in Nigeria

Electronic Payments System and Banking Industry's Return in Nigeria: A Time-Varying Granger Causality Approach

Electronic Payments System and Banking Industry's Return in Nigeria: A Time-Varying Granger Causality Approach

On the relationship between oil market and European stock returns

This paper investigates the dynamic relationship between the oil market and European stock market returns using monthly data from May 2007 to April 2022 for 27 European Union member countries. A novel approach is adopted by using the time-varying Granger causality test and the structural vector auto-regression model to examine the causal links. Empirical results reveal strong evidence of time-varying causation between the variables, considering the oil market from both the supply-side and demand-side perspectives. In light of these findings, numerous policy considerations emerge, including refining risk management strategies for investors, reformulating economic and energy policies, the potential impact on monetary policy decisions, the need for ad hoc market regulations, facilitating investor education initiatives, promoting international cooperation, and advancing the transition to sustainable energy sources.

Time-varying connectedness and causality between oil prices and G7 economies exchange rates. Evidence from the COVID-19 and Russia-Ukraine crises

PurposeThis study aims to attempt to investigate the time-varying causality and price spillover effects between crude oil and exchange rate markets in G7 economies during the COVID-19 and Russia–Ukraine crises.Design/methodology/approachThis study uses time-varying Granger causality test and spillover index.FindingsThis study finds a time-varying causality between exchange rate returns and oil prices, implying that crude oil prices have the predictive power of the foreign exchange rate markets in G7 economies in their domain. Furthermore, the total spillover index is estimated to fall significantly around COVID-19 and war events. However, this index is relatively high – more than 57% during the first wave of COVID-19 and decreasing slightly during the Russia–Ukraine conflict.Practical implicationsThis outcome supports the hypothesis that the majority of the time-varying interaction between exchange rates and oil prices takes place in the short term. As a result, the time-varying characteristics provide straightforward insight for investors and policymakers to fully understand the intercorrelation between oil prices and the G7 exchange rate markets.Originality/valueFirst, this study has reexamined the oil–exchange rate nexus to highlight new evidence using novel time-varying Granger causality model recently proposed by Shi et al. (2018) and the spillover index proposed by Diebold and Yilmaz (2012). These approaches allow the author to improve understanding of time-varying causal associations and return transmission between exchange rates and oil prices. Second, compared to past papers, this paper has used data from December 31, 2019, to October 31, 2022, to offer a fresh and accurate structure between the markets, which indicates the unique experience of the COVID-19 outbreak and Russia–Ukraine war episodes. Third, this study analyzes a data set of seven advanced economies (G7) exhibiting significant variations in their economic situations and responding to global stress times.

The role of Renminbi internationalization in China’s petroleum security: a causal analysis amidst global uncertainties

ABSTRACT China’s import of petroleum resources increases in recent years despite structural reforms to the Chinese economy. Primary energy demand increased significantly amidst global uncertainties, and this is a premise for energy security concerns for the country. In this paper, we rely on monthly data spanning from January 2011 to December 2022 and incorporate the role of global economic uncertainty to examine the causal relationship between Renminbi internationalization (RMBI) and petroleum security in China. Based on the recent VAR-based time-varying Granger causality procedure, we found a significant bi-directional causality between RMBI and petroleum security. The findings imply that increasing acceptance of the Renminbi (RMB) in trade settlements and petroleum invoicing will promote China’s drive to achieve a sustainable and reliable supply of petroleum. However, we proffer some policy suggestions based on the empirical findings.