Causality Approach Research Articles

Relationship between Public Expenditure and Economic Development in Sub- Saharan Africa Countries: The VECM

This study examined the relationship between public expenditure and economic development in Sub-Saharan African nations using time series data from 1970 to 2021. The study employed the Vector Error Correction Model (VECM) and Granger Causality approaches, leveraging variables such as real GDP per capita and aggregate public expenditure. The short and long run outcomes show that government expenditure has a negative impact on economic development. In addition, the study's causality test reveals a bidirectional link between economic success and government spending. The call for a study pushes Tanzania's government to enhance its priorities while reinforcing programs such as cost-cutting and fiscal consolidation. It also underlines the need of government expenditure on development projects that are initiated and completed on time to minimize cost escalation

Impact of COVID-19 on China's business and economic conditions: the importance of quantile asymmetries.

China has remained a growth engine for the global economy for thelast several years. In this study, we assess the impact of COVID-19 on China's business and economic conditions; employing the quantile-on-quantile (QQ) regression and the quantile causality approaches. These econometrics batteries suit our research postulation, as they are capable to delineate underlying asymmetries across the whole distribution, based on which we can infer whether the response of China's business and economic conditions towardsCOVID-19 is heterogenous or homogenous. Utilizing the novel business and economic conditions measures, we observed that COVID-19 had initially disrupted both business and economic conditions in China. However, they showcased recovery over time. Our in-depth analysis allowed us to infer that the effect of COVID-19 on China's business and economic conditions is heterogeneous across different quantiles, and there is reliable evidence of asymmetry. The outcomes of quantile causality in mean and variance corroborate our primary estimations. These findings educate policymakers, companies, and other stakeholders to understand the nuances of China's business and economic conditions vis-a-vis COVID-19 in the short-run and as time elapsed.

The Impact of ICT on Financial Sector Development Under Structural Break: An Empirical Analysis of the Turkish Economy

This study is to examine the relationship between information and communication technology (ICT) and financial development in the Turkish economy during the period of 1986–2018. By empirical literature, economic growth, technological innovation, and financial globalization are added to the financial development model as explanatory variables. The autoregressive distributed lag (ARDL) model and Hatemi-J cointegration test with two structural breaks are applied to examine the presence of cointegration between the variables. Dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR) estimation techniques are applied for long-term estimates. The vector error correction model (VECM) Granger causality approach is used for causality analysis. Our empirical results show that under the structural break, ICT, economic growth, technological innovation, and financial globalization are cointegrated with financial development. In the presence of a structural break, ICT and technological innovation negatively affect financial development, while economic growth and financial globalization have a positive impact on financial development. The causality analysis determines that there is a one-way causality relationship running from ICT and economic growth to financial development. In addition, technological innovation and financial globalization lead to long-term financial development. Empirical findings have important policy recommendations for financial development in the Turkish economy.

Does the tourism and travel industry really matter to economic growth and environmental degradation in the US: A sustainable policy development approach

The tourism and travel industry (TTI) has become a vital developmental tool for boosting economic growth globally; however, this economic thriving is adversely connected to the environment. This study examines the impacts of eight TTI subsectors on economic growth and environmental pollution in the United States of America by contextualizing energy consumption and globalization. We applied the ARDL bounds test and Granger causality approach on time-series data (2005 1st quarter–2019 4th quarter). Granger causality uncovers TLGH, GLTH, and feedback hypotheses between TT subindustries. The subindustries supporting TLGH’s proposal that long-term investment in these sectors could enhance economic growth. In addition, industries supporting GLTH indicate that a strong economy would be beneficial for these industries. Maximum subindustries indicate a significant positive association with energy consumption. The long-run dynamics show that TT subindustries have different influences on greenhouse gases (CO2, CH4, N2O) and air pollutants (CO, NH3, NOx, SO2, VOC, and PM2.5). Long-run dynamics show that food and drinking places emit more GHG than other entertainment and hospitality subsectors. Amusement, gambling, and entertainment contribute more to air pollutants among the entertainment and hospitality subsectors. Road and railway transportation contribute more to GHG emissions than other travel sectors in the long run. Air transportation in the travel subsector is responsible for high air pollutants. The Granger causality results reveal that art, gambling and recreation in entertainment and hospitality industries, and ground transportation contribute the most to environmental pollution. Globalization has varying effects on economic growth, energy consumption, and environmental pollution indicators. We have provided sustainable policy implications for reducing GHG emissions and air pollutants.

Frequency-domain and time-varying asymmetric Granger causality between real effective exchange rates and remittances in Mexico

The sheer size of remittances has fostered an interest in investigating the consequences of these flows, particularly in remittance-dependent economies. This study relies on monthly data from 1995M01 to 2021M05 and uses both frequency-domain and time-varying causality approaches to investigate the asymmetric causality relationships between real effective exchange rates and remittances in Mexico. Two key results are obtained. First, according to the frequency domain causality test results, positive shocks to remittances lead to appreciation in the Mexican peso in the medium- and long-run cycles, but negative shocks to remittances do not lead to depreciation in the Mexican peso, thus suggesting non-asymmetry. Second, the results of time-varying causality based on heterogeneous errors support asymmetric behavior between real effective exchange rates and remittances, underscoring the importance of allowing asymmetries when investigating the causal relationship.

The Importance of Good Governance in the Government Organization

The intention of this research was to evaluate the influence of the implementation of good governance on the performance of one of the government organizations. The method used was a quantitative-descriptive with causality approach, which was then analyzed by PLS-SEM. The amount of the research sample was 303 of state civil apparatus at the Land Transportation Management Center throughout 38 provinces in Indonesia. The research findings explained that transparency has an impact on the increasing accountability and responsibility of government organizations but has no power to boost their performance. Accountability has an influence on increasing responsibility and the performance of an organization. Responsibility is also found to be effective in rebuilding the performance of government organizations. This research brings the latest issue to the surface. By linking all indicators of good governance factors, namely transparency-accountability, transparency-responsibility, and accountability-responsibility, which is rarely done in previous research that focused on the connection between good governance-performance. In addition to that, this research was also conducted at the Land Transportation Management Center throughout 38 provinces, so the level of accuracy would be high and had a huge impact on related government organizations in Indonesia. Doi: 10.28991/HIJ-2023-04-01-06 Full Text: PDF

Area and Production of Peanuts in Tamil Nadu: The Granger Causality Approach

Area and Production of Peanuts in Tamil Nadu: The Granger Causality Approach

Can environmental sustainability be decoupled from economic growth? Empirical evidence from Eastern Europe using the common correlated effect mean group test

The European Union (EU) and the Organisation for Economic Co-operation and Development (OECD) aim to develop long-term policies for their respective member countries. Having observed increasing dangers to the environment posed by rising economic growth, they are seeking pathways to enable policy action on economic growth and environmental sustainability. Given the facts in theoretical and empirical studies, this study assessed the validity of the decoupling hypothesis by investigating asymmetricity in the relationship between environmental sustainability and economic growth in nine Eastern European countries from 1998 to 2017 using the cross-section augmented Dickey-Fuller (CADF) unit root, panel corrected standard errors (PCSE), common correlated effect mean group (CCEMG), and Dumitrescu Hurlin causality approaches. Both population growth and drinking water are used as controlled variables. The outcomes establish strong cointegration among all the variables of interest. According to the results of CCEMG test, first, economic growth exerts short-term environmental degradation but has long-term environmental benefits in Eastern Europe; second, population growth and drinking water exert a positive effect on environmental sustainability in both the short- and long-run. The results of Dumitrescu Hurlin causality test indicate that environmental sustainability is unidirectionally affected by economic growth. Based on these outcomes, the following policy suggestions are made: (1) the EU and OECD should implement member-targeted policies on economic growth and fossil-fuel use towards regulating industrial pollution, water use, and population control; (2) the EU and OECD member countries should invest in environmental technologies through green research and development (R&D) to transform their dirty industrial processes and ensure productive energy use.

Dynamic causality between oil prices and stock market indexes in Russia and China: does US financial instability matter?

PurposeThis study aims to examine the dynamic bidirectional causality between oil price (OIL) and stock market indexes in net oil-exporting (Russia) and net oil-importing (China) countries.Design/methodology/approachThe authors use monthly data for the period starting from October 1995 to October 2021. In this study, the bootstrap rolling-window Granger causality approach introduced by Balcilar et al. (2010) and the probit regression model are performed in order to identify the bidirectional causality.FindingsThe results show that the causal periods mainly occur during economic, financial and health crises. For oil-exporting country, the results suggest that any increase (decrease) in the OIL leads to an appreciation (depreciation) in the stock market index. The effect of the stock market on OIL is more relevant for the oil-importing country than that for the oil-exporting one. The COVID-19 consequences are demonstrated in the impact of oil on the Russian stock market. The probit regression shows that the US financial instabilities increase the probability of causality between OIL and stock market indexes in Russia and China.Practical implicationsThe dynamic relationship between the variables must be taken into account in investment decisions. As financial instabilities in the USA drive the relationship between oil and stocks, investors should consider geopolitical, economic and financial elements when constructing their portfolios. Shareholders are required to include other assets in their portfolios since oil–stock relationship is highly risky.Originality/valueThis study provides further evidence of the bidirectional oil–stock causal link. Additionally, it examines the impact of financial instabilities on the probability that the OIL and the stock market index cause each other through the Granger effect.

English

The importance of a country’s financial system to its economic well-being cannot be underestimated. This paper seeks to investigate whether causation exists between Ghana’s financial system and economic growth. Ghana’s financial system was measured using the efficiency, depth, and stability of the stock market, while economic growth was measured as the Gross Domestic Growth (GDP) per capita growth. The measurement variables were purposively sampled from 2008 to 2020, spanning thirteen years of time series data. The granger causality approach was employed to test the financial system’s and economic growth’s causation. In analysis the data, the study employed the Augmented Fuller Dickey (ADF) and Phillip Perron (PP) to test the stationarity of the series, the Jerque Bera Variable to test the normality of the data and the VAR and Johansen cointegration to test the order of integration among the variables. The statistical test revealed that the variables were not cointegrated at level; there was a unit root in the series. There was no long or short run relationship among the variables. Furthermore, the regressors’ depth, efficiency, and stability of the stock market as proxies for the financial system of Ghana do not cause economic growth. It is recommended that regulatory bodies should pursue policies that would improve the effectiveness, efficiency, depth, and stability of other aspects of the country’s financial system and focus less on the stock market due to the discovered relationship between the stock market and economic growth.   Keywords: Financial system, economic growth, stock market.

Inflation and Poverty in Nigeria: A Granger Causality Approach

Inflation and Poverty in Nigeria: A Granger Causality Approach

Dynamic Relationship Between External Financial Flows and Total Market Capitalization in The Nigerian Capital Market: VECM Approach

The study examines the extent to which external financial flows influence market capitalization of Nigerian capital market for the period spanning 1981-2020. The study employed the VECM, regressors’ and ECT t-statistics causality approaches to establish the strong, short-run and long-run relationships. The study unveiled that all the external financial flows such as FDI, FPI, remittance and others used in this study have positive impacts on total annual market capitalization in the Nigerian capital market, especially in the long-run. The stock indices movement is respective to the change in external financial flows basic. The study suggested that the policy measures aimed at directing long run capital inflows should not be the same as those aimed at changing the short run patterns of flow. The study concludes that policy should be put in place to ensure the directions of both long run and short run financial flows have a suitable time rage.

Examining the roles of labour standards, economic complexity, and globalization in the biocapacity deficiency of the ASEAN countries

ABSTRACT With Singapore currently the world’s most natural capital (biocapacity) deficit alongside four other Association of Southeast Asian Nations (ASEAN) countries having varying degree of ecological deficit, i.e. Indonesia, Malaysia, the Philippines, and Thailand, it then offers a clear justification for a more scrutiny of the ASEAN states’ ecological footprint dynamics. To provide more insight on the drivers of ecological footprint in the overall panel and for each of the above-mentioned countries, the roles of economic complexity, average working hours, labour productivity, labour income share, and globalization were examined by employing the Dynamic Ordinary Least Squares Mean Group (DOLSMG) alongside the recently developed (non)time-variant Granger causality approaches. For the overall panel, the DOLSMG approach established that labour productivity, labour income share, and globalization reduce the biocapacity deficit by improving ecological quality while economic complexity worsen the region’s environmental quality. Additionally, in the overall panel, there is Granger causality evidence from the average working hour, labour income share, labour productivity, globalization, and economic complexity to ecological footprint. Moreover, the results of the two Granger causality approaches are unanimous in evidence. For instance, average working hours per year is a significant causal of ecological footprint in all the sampled countries at varying periods. Specifically, there are Granger causalities: from labour productivity to ecological footprint in Malaysia, the Philippines, Singapore and Thailand; from globalization to ecological footprint in Malaysia, the Philippines, Singapore, and Thailand; from economic complexity to ecological footprint in Indonesia, Malaysia, the Philippines, Singapore, and Thailand, all at varying times.

Do geopolitical oil price risk influence stock market returns and volatility of Pakistan: Evidence from novel non-parametric quantile causality approach

The influence of oil price disturbances and geopolitical risk on stock returns and volatility has been investigated by many scholars in different settings, though few of these have scrutinized this effect under distinct market trends. In this regard, this study investigates the causal upshot of geopolitical oil price threats on stock returns and volatility under distinct market trends in the Pakistan stock market. For this objective, the study utilizes a recently developed non-parametric quantile causality approach by exercising monthly data ranging between January 2004 and September 2022. The findings of the BDS and parameter stability tests expose that the series has nonlinear and unstable features, which leads to the novel model of non-parametric causality quantile. Likewise, the outcomes of the empirical analysis reveal that geopolitical oil price displacements have a causal influence on security returns only in normal market conditions, whereas it has a causal effect on volatility in all market conditions. This research makes policy suggestions for academics, businesses, and the Pakistani government based on its conclusions.

Analysis of the effect of extreme weather on the US domestic air network. A delay and cancellation propagation network approach

Flight delays are one of the most discussed, yet not fully understood, topics in the aviation industry. In this paper, we shed more light into propagation of flight delays by providing a spatio-temporal analysis of flight departure delays of the US domestic air network for the year 2017. The analysis focuses on four US air carriers (full-service and low-cost) and two time events characterized by extreme weather conditions, in addition to a baseline case free of extreme weather conditions. We constructed a Delay Propagation Network (DPN) for each (time event, airline) pair detecting patterns of causality between hourly delays in airports using a Granger Causality approach. In addition, we identified four (time event, airline) pairs with a volume of cancellations large enough to construct a Cancellation Propagation Network (CPN), analogously to DPNs. For the baseline case, we observed that central nodes of the airport network (i.e., hubs) usually act as absorbers or intermediary nodes in the DPN. DPNs were more homogeneously distributed in space for point-to-point than for hub-and-spoke networks. For extreme weather events, we observed that the size of a DPN increases with the percentage of canceled flights as long as this stays below 10%. Conversely, it suddenly decreases when the percentage exceeds such tipping point because most causal relationships among delays are lost due to the volume of cancellations. We also observed that some airports located in the region of the extreme weather event were among the central nodes of the DPN. Those airports, together with the hub airports, acted as the top generators, absorbers, or intermediary nodes of the DPN. On the other hand, CPNs monotonously increased in size with the proportion of canceled flights. CPNs are less noisy and therefore easier to interpret than DPNs, as cancellations stem primarily from the extreme weather event only. In CPNs, hubs act as cancellation absorbers, due to the larger volume of resources that airlines allocate there.

The Impact of Innovation Technology on Carbon Emissions in India

Numerous studies have examined the determinants of CO2 emission. However, earlier research has neglected to analyse the emission of CO2 resulting from the exchange of innovation technology. The present work contributes to the research stream by examining the relationship between innovation technology and environmental degradation in India from 1980 to 2021 during the time period of study. On the basis of the Auto Regressive Distributive Lag (ARDL) model and the Vector Error Correction (VECM) Granger Causality approach, the main finding is that innovation technologies are the primary contributors to India’s long-term CO2 emission. Short-term causality emerges from one-way causation between innovation technology and CO2 emissions. Additionally, a long-term feedback hypothesis between energy usage and CO2 emissions is rejected. Numerous critical tests are conducted to assure the stability of the model and the dependability of policy-relevant conclusions. This study proposes that the Indian government should invest more in research and development to increase its innovative technological power, which would be beneficial for environmental protection.

Time-Varying and Quantile-Based Relationship among Geopolitical Risks, Oil and Gold Prices

This paper probes the relationship between geopolitical risks (GPR), WTI oil, and gold prices utilizing the time-varying causality and quantile regression approaches. The sample period spans from January 1986 to January 2022, comprising 433 monthly observations and representing the longest common period of data availability. The results show that there is no causality between the pairs of GPR–WTI, and GPR–gold prices for the full sample period, while the causality between gold and WTI is unidirectional, running from gold to WTI. Using the rolling causality test, however, the findings show that the dynamic causal relations strengthen over time. The Granger causality from the gold prices to GPR and WTI is stronger than the other way around, suggesting that the gold market dominates the other two variables in terms of strength of the lead-lag structure of causality. Besides, the findings reveal the strongest causation effects between GPR and WTI spot prices. Before 2009, the causal relationship between WTI and GPR is mostly unidirectional while also a bidirectional linkage emerges, coinciding with the crisis periods including the Dot-Com and 2007 US Subprime crises. During the causal periods, these variables respond negatively to changes in others. For the COVID19 period, the direction of causality considerably changes in favor of WTI for the GPR–WTI pair whereas it is unchanged for the WTI–gold pair. The results indicate that WTI has positive and negative predictive powers for GPR and gold while it receives negative and positive causation effects from GPR and gold during the pandemic, respectively. The results, in overall, may offer important insights for investors and regulatory authorities in building portfolio and risk management strategies as well as pricing and trading activities and constructing monetary policies over various market conditions.

Time-varying causality nexus of (non)renewable electricity utilization, real output, and carbon emission among selected African states

AbstractAdding to the debate on the drivers of carbon neutrality, the perspective of time-dependent effect of crucial factors such as the renewable and conventional energy utilization should offer relevant policy for the stakeholders in the energy sector. On the empirical front, several studies have investigated the causal interaction between renewable and nonrenewable energy consumption, economic growth, and carbon dioxide (CO2) emission by using the conventional empirical approaches. In contrast, this study utilized a time-varying causality (TC) technique (which offers time inference) to determine the causal relationship between CO2 emission and its potential drivers such as energy source types and Gross Domestic Product (GDP) in South Africa, Egypt, Algeria, Libya, Nigeria, and Tunisia over the period spanning 1980Q1 and 2017Q4. Importantly, there is statistically significant evidence of causality as examined by the TC approach. For instance, causality from CO2 emission to renewable energy source for the period 2004Q1–2006Q3 and from GDP to CO2 emission during 2013Q2–2015Q3 were observed for South Africa. Moreover, the causality from non-renewable energy source to CO2 emission and from GDP to CO2 emission compares very well with Nigeria, Libya, and Algeria. Overall, the results largely indicate causality relationships among our variables for all the six countries over different time sequences. These results differ from the Toda–Yamamoto test, which only reveals a causality relationship in Egypt, Libya, and Tunisia. The empirical findings obtained from the time-varying causality approach are essential for designing and implementing appropriate energy policies, especially attaining these countries' Paris agreement and the Sustainable Development Goal 13 since the goals are time periodically assessed.

The potency of resource efficiency and environmental technologies in carbon neutrality target for Finland

Motivated by Finland's ambitious transition to circular economy through the reduction of consumable non-renewable resources and carbon neutral 2035, this study employs the Fourier approaches of stationarity, cointegration, causality alongside the long-run estimators of fully modified and dynamic least squares to examine the environmental aspects of resource productivity, environmental-related technologies, and export intensity over the period 1990–2020. Interestingly, given the two long-run estimators, the result established that a percent increase in raw material productivity yields a decline in greenhouse gas emission by a range of 61–70 percent. Additionally, there is a desirable and statistically significant impact of environmental-related technologies on greenhouse gas emission with an elasticity range of 0.16–0.18 in the long-run. While the intensity of export activities does not constitute a significant impact, economic growth as measured by Gross Domestic product (GDP) significantly hampers environmental sustainability in the long-run. Moreover, the causality approach including the Fourier Toda Yamamoto offers a strong inference along the insinuation of the long-run results for all the examined factors. Given this observation, relevant policy measures were highlighted to further guide decision makers in Finland on the pursuit of circular economy and carbon zero target.

Importance of institutional quality and technological innovation to achieve sustainable energy goal: Fresh policy insights

Globally, energy is considered a backbone for any country's sustainable growth. However, Pakistan has still encountered a massive energy crisis that affects its society economically. Therefore, policymakers keenly focused on distinguishing factors contributing to Pakistan's sustainable energy plan in the current scenario. Given the importance, it is vital to examine technological innovation, institutional quality, public-private partnerships in energy, and GDP with electricity consumption from 1980 to 2019. The study uses novel dynamic ARDL simulations, and Cumulative Fourier Frequency Domain Causality (CFFDC) approaches for empirical estimation. The findings show that GDP and institutional quality have an affirmative short- and long-run effect on energy consumption. On the other hand, technological innovation has a long-term positive influence on electricity consumption. In contrast, public-private partnerships in energy were found insignificant. The outcomes suggest that technological innovation, institutional quality, and GDP are the most effective determinants and have the greatest effect on energy consumption. Other problems must be addressed, such as pervasive corruption and bureaucratic complexities, underdeveloped grids, and insufficient resource management.