Causality Method Research Articles

GLACIAL: Granger and Learning-based Causality Analysis for Longitudinal Imaging Studies

The Granger framework is useful for discovering causal relations in time-varying signals. However, most Granger causality (GC) methods are developed for densely sampled time-series data. A substantially different setting, particularly common in medical imaging, is the longitudinal study design, where multiple subjects are followed and sparsely observed over time. Longitudinal studies commonly track several biomarkers, which are likely governed by nonlinear dynamics that might have subject-specific idiosyncrasies and exhibit both direct and indirect causes. Furthermore, real-world longitudinal data often suffer from widespread missingness. GC methods are not well-suited to handle these issues. In this paper, we propose an approach named GLACIAL (Granger and LeArning-based CausalIty Analysis for Longitudinal studies) to fill this methodological gap by marrying GC with a multi-task neural forecasting model. GLACIAL treats subjects as independent samples and uses the model’s average prediction accuracy on hold-out subjects to probe causal links. Input dropout and model interpolation are used to efficiently learn nonlinear dynamic relationships between a large number of variables and to handle missing values respectively. Extensive simulations and experiments on a real longitudinal medical imaging dataset show GLACIAL beating competitive baselines and confirm its utility. Our code is available at <a href='https://github.com/mnhng/GLACIAL'>https://github.com/mnhng/GLACIAL</a>

Legal Recreational Cannabis Sales and Opioid-Related Mortality in the 5 Years Following Cannabis Legalization in Canada: A Granger Causality Analysis

Objective: Little is known about the population-level impact of recreational cannabis legalization on trends in opioid-related mortality. Increased access to cannabis due to legalization has been hypothesized to reduce opioid-related deaths because of the potential opioid-sparing effects of cannabis. The objective of this study was to examine the relations between national retail sales of recreational (non-medical) cannabis and opioid overdose deaths in the 5 years following legalization in Canada. Method: Using time-series data, we applied Granger causality methods to evaluate the association between trends in legal recreational cannabis sales and opioid-related deaths over time. Both sales and opioid deaths grew over time, with the latter exhibiting significant increases following the onset of the COVID-19 pandemic. Results: We found no support for the hypothesis that increasing post-legalization sales Granger caused changes in opioid-related deaths in British Columbia, Ontario, or at the national level. Conclusions: These findings suggest that increases in legal recreational cannabis sales following legalization were not meaningfully associated with changes in opioid-related mortality. Further examination with longer follow-up periods will be needed as the legal cannabis market becomes more entrenched in Canada, but these findings converge with previous work suggesting legalization is not related to opioid overdose mortality and further undermine that hypothesized link as a basis for legalization in other jurisdictions.

Influence of individual's age on the characteristics of brain effective connectivity.

Given the increasing number of older adults in society, there is a growing need for studies on changes in the aging brain. The aim of this research is to investigate the effective connectivity of different age groups using resting-state functional magnetic resonance imaging (fMRI) and graph theory. By examining connectivity in different age groups, a better understanding of age-related changes can be achieved. Lifespan pilot data from the Human Connectome Project (HCP) were used to examine dynamic effective connectivity (dEC) changes across different age groups. The Granger causality method with time windowing was employed to calculate dEC. After extracting graph measures, statistical analyses were performed to compare the age groups. Support vector machine and decision tree classifiers were used to classify the different age groups based on the extracted graph measures. Based on the obtained results, it can be concluded that there are significant differences in the effective connectivity among the three age groups. Statistical analyses revealed disassortativity. The global efficiency exhibited a decreasing trend, and the transitivity measure showed an increasing trend with the advancing age. The decision tree classifier showed an accuracy of with Kruskal-Wallis selected features. This study demonstrates that changes in effective connectivity across different age brackets can serve as a tool for better understanding brain function during the aging process.

Is natural resource wealth a boon or a bane? The impact of oil rents and foreign direct investment on economic growth in Kazakhstan

The nexus between foreign direct investment, natural resource endowment, and their impact on sustained economic growth, is contentious. This study investigates the resource curse hypothesis and the effects of FDI on economic growth in Kazakhstan. The study covers the period from 1990 to 2022 and employs the Autoregressive Distributed Lag (ARDL) model and Toda-Yamamoto causality methods. The Bounds cointegration results reveal the existence of long-term equilibria between per capita GDP and the predictors. The findings reveal a significant impact of oil rents on economic growth, contradicting the resource curse hypothesis and suggesting a resource boon instead. In stark contrast, the impact of FDI on Kazakhstan’s economic growth is found to be insignificant, despite the presence of a causal nexus. Furthermore, economic freedom and export diversification have a positive significant impact on economic growth, while inflation exhibits a negative but significant impact. Although governance has a direct impact on GDP per capita, it is deemed insignificant, as the negative average governance index implies poor governance. Expectedly, the result establishes a causal effect between export diversification, economic freedom, governance, oil rents, and economic growth. This underscores the fundamental role played by the interplay of diversification, economic freedom, governance, and oil rents in fostering sustainable economic growth. In addition, economic freedom stimulates gross fixed capital formation, indicating that it enhances domestic investment. Notably, the findings refute the crowding-out effect of FDI on domestic investment in Kazakhstan. Consequently, to escape the resource curse and the Dutch disease syndrome, the study advocates for enhancing good governance capabilities in Kazakhstan. Thus, we recommend that good governance could reconcile the twin goals of economic diversification and deriving benefits from oil resources, ultimately transforming oil wealth into a boon in Kazakhstan.

Influence Analysis of The Factors Determining Consumer Decisions on The Marketing Performance of J&T Express in Pontianak

Digital technology, such as e-commerce, has changed the way people live by providing convenience, speed, comfort and efficiency. Freight forwarding services are vital in online transactions to deliver goods from sellers to buyers. The purpose of this study was conducted to determine the effect of customer orientation, promotional attractiveness, and competitive pricing on marketing performance. This research method uses the causality method which aims to test how much the cause-and-effect relationship between the independent variable and the dependent variable is. The population of this study were consumers totaling 13,577, from 2018-2023, and a sample of 100 respondents. The data analysis technique uses quantitative data analysis and uses a range scale measurement. The results of simultaneous testing (F test) indicate that customer orientation, promotional attractiveness, and competitive prices have a significant effect on marketing performance. The results of persial testing (t test) show that customer orientation, promotional attractiveness, and competitive prices have a significant effect on marketing performance.

The link between gender inequality, financial development, and economic growth in Nigeria: A spectral Granger causality approach

AbstractThe male and female genders have crucial roles to play in economic advancement. Thus, the main reason for this research is to pinpoint the causal link between gender inequality (GPIN), financial development (FIDX), inflation (INFL), and economic growth (GDPC) in Nigeria from the year 1980–2020 utilizing the Spectral Granger and Pairwise Granger causality methods and “Residual Augmented Least Square (RALS) cointegration. The RALS result show confirms the stationarity properties of the variables. The Spectral Granger causality outcomes show that GPIN granger causes GDPC in the long, medium, and short–term. In addition, the FIDX granger causes GDPC in the long and short–term, while the medium–term impact is insignificant. For INFL, causality only occurs in the long–term. On the other hand, the Pairwise Granger causality results show that GPIN and FIDX granger cause GDPC, while INFL is insignificant. Therefore, if GPIN and FIDX can predict economic expansion, policymakers need to create policies that can reduce diverse forms of inequalities, promote financial development, and reduce inflation to the barest minimum.

Promoting environmental sustainability: A policy perspective on hydroelectric power generation, foreign direct investments, and financial development

In today's rapidly evolving world, characterized by the menace of global warming and the ever-pressing call for sustainable energy solutions, the trilogy of hydroelectric power generation, foreign direct investment, and environmental quality is a compelling and indispensable dimension; all of which necessitate simultaneous consideration. In this quest, this research article aims to explore the nexus between hydroelectric power generation, foreign direct investment, and sustainability—within the framework of financial development. To this end, we have utilized annual data of the world's ten largest hydroelectric power-generating countries in the year 2021 for the period 1992–2019, and utilize the Westerlund-Edgerton LM Bootstrap, Augmented Mean Group, and Dumitrescu-Hurlin panel bootstrap causality methods as our main econometrics' batteries. Based on the empirical outcomes that study entails that financial development, foreign direct investments, and increasing economic growth reduce the environmental quality. We observed that hydroelectric power generation is an important driving force on environmental quality. The empirical outcomes further infer that as the financial development levels of countries increase, the positive impact of hydroelectric power generation on environmental quality becomes more significant. The study findings will help policymakers to organize environmental quality strategies that are more realistic and accurate.

Energy Poverty and Environmental Quality Nexus: Empirical Evidence from Selected South Asian Countries

South Asian countries are included in the economies of developing Asia. The region of South Asia is predominantly affected by energy poverty issues due to a heavy reliance on conventional energy and unpredictable access to energy services. It has about a quarter of the world's population and is home to three of the world's ten most populated countries: India, Pakistan, and Bangladesh. This study investigates environmental sustainability dynamics in South Asian countries from 2000 to 2021, utilizing the Cross-sectional Autoregressive Distributed Lag (CS-ARDL) and Dumitrescu-Hurlin (D-H) causality methods. The research offers insights into the long-term trends and causal relationships that shape environmental outcomes in South Asian nations. Based on empirical findings, in the long-term, it is revealed that increases in energy poverty, economic growth, income inequality, and capital formation raise greenhouse gas (GHG) emissions, while renewable energy and labor reduce GHG emissions. On the other hand, the error correction term shows the speed of adjustment toward equilibrium at 0.75%. Furthermore, the D-H panel causality reveals a directional link between variables. These findings highlight the urgent need for South Asian countries to implement policies to address energy poverty, promote renewable energy adoption, and reduce income inequality to mitigate GHG emissions and achieve long-term environmental sustainability effectively.

Influence of green ICT and socioeconomic factors on sustainable development: Evidence from Chinese provinces

We examine the impact of green information communication technology, while considering the conditioning role of other seminal factors. Using panel quantile-quantile granger causality testing and method of moments quantile regression for Chinese provinces for 2000–2019, we find that green information communication technology promotion, human capital, and urbanization positively impact green growth, while globalization, energy intensity, and carbon emissions are not significant. Results highlight the importance of green information communication technology for sustainable development.

Deep‐Learning Based Causal Inference: A Feasibility Study Based on Three Years of Tectonic‐Climate Data From Moxa Geodynamic Observatory

AbstractHighly sensitive laser strainmeters at Moxa Geodynamic Observatory (MGO) measure motions of the upper Earth's crust. Since the mountain overburden of the laser strainmeters installed in the gallery of the observatory is relatively low, the recorded time series are strongly influenced by local meteorological phenomena. To estimate the nonlinear effect of the meteorological variables on strain measurements in a non‐stationary environment, advanced methods capable of learning the nonlinearity and discovering causal relationships in the non‐stationary multivariate tectonic‐climate time series are needed. Methods for causal inference generally perform well in identifying linear causal relationships but often struggle to retrieve complex nonlinear causal structures prevalent in real‐world systems. This work presents a novel model invariance‐based causal discovery (CDMI) method that utilizes deep networks to model nonlinearity in a multivariate time series system. We propose to use the theoretically well‐established Knockoffs framework to generate in‐distribution, uncorrelated copies of the original data as interventional variables and test the model invariance for causal discovery. To deal with the non‐stationary behavior of the tectonic‐climate time series recorded at the MGO, we propose a regime identification approach that we apply before causal analysis to generate segments of time series that possess locally consistent statistical properties. First, we evaluate our method on synthetically generated time series by comparing it to other causal analysis methods. We then investigate the hypothesized effect of meteorological variables on strain measurements. Our approach outperforms other causality methods and provides meaningful insights into tectonic‐climate causal interactions.

Bitcoin, Fintech, Energy Consumption, and Environmental Pollution Nexus: Chaotic Dynamics with Threshold Effects in Tail Dependence, Contagion, and Causality

The study investigates the nonlinear contagion, tail dependence, and Granger causality relations with TAR-TR-GARCH–copula causality methods for daily Bitcoin, Fintech, energy consumption, and CO2 emissions in addition to examining these series for entropy, long-range dependence, fractionality, complexity, chaos, and nonlinearity with a dataset spanning from 25 June 2012 to 22 June 2024. Empirical results from Shannon, Rényi, and Tsallis entropy measures; Kolmogorov–Sinai complexity; Hurst–Mandelbrot and Lo’s R/S tests; and Phillips’ and Geweke and Porter-Hudak’s fractionality tests confirm the presence of entropy, complexity, fractionality, and long-range dependence. Further, the largest Lyapunov exponents and Hurst exponents confirm chaos across all series. The BDS test confirms nonlinearity, and ARCH-type heteroskedasticity test results support the basis for the use of novel TAR-TR-GARCH–copula causality. The model estimation results indicate moderate to strong levels of positive and asymmetric tail dependence and contagion under distinct regimes. The novel method captures nonlinear causality dynamics from Bitcoin and Fintech to energy consumption and CO2 emissions as well as causality from energy consumption to CO2 emissions and bidirectional feedback between Bitcoin and Fintech. These findings underscore the need to take the chaotic and complex dynamics seriously in policy and decision formulation and the necessity of eco-friendly technologies for Bitcoin and Fintech.

Analisis Pengaruh Persepsi Kebermanfaatan, Persepsi Kemudahan dan Persepsi Risiko Terhadap Minat UMKM untuk Bertransaksi Menggunakan Fintech/Financial Technology Sebagai Layanan Pembayaran Digital: Studi pada UMKM Kabupaten Nganjuk

This research is motivated by technological developments which are accelerating rapidly and penetrating various sectors of life. Technological progress has had many positive impacts, one of which is on the economic sector. Starting from limitations in making payments, an innovation was created that made things easier and faster. The aim of this research is to analyze whether perceived usefulness, perceived convenience and perceived risk partially and simultaneously UMKM influence interest in making transactions using Fintech/Financial Technology as a digital payment service. This research uses a quantitative approach with the causality method. In this research, the population of UMKM taken was operating in the culinary sector who were registered with the Nganjuk Regency Cooperatives and Micro Enterprises Service, totaling 544 UMKM. The sampling technique used a purposive sampling technique using the Slovin formula and the number of samples used in the research was 85 respondents obtained by distributing questionnaires/google forms. The tests carried out in this research used SPSS version 25 with multiple linear regression analysis methods. The conclusion of this research shows that perceived usefulness, perceived convenience and perceived risk partially and simultaneously have a significant influence on UMKM interest in using fintech as a digital payment service.

The role of environmental innovation on ecological footprint in nations with high technology exports concentrations in international trade

This study focuses on four major high-technology exporting countries––the USA, Germany, France, and China––to explore the long and short-run associations among ecological footprint, environmental technology patents, high-technology exports, and economic growth. The sample covering 1988–2019 is subject to a set of structural breaks, including 2009 Global Recession in addition to uncertainty in the order of integration captured by unit root tests, which provide basis for novel Fourier ARDL and Fourier Toda-Yamamoto causality methods. The Fourier ARDL findings reveal the importance of environmental technology innovations in dampening the level of ecological footprints and promoting a more sustainable environment in the USA, Germany, and France, whereas more high-technology exports in international trade worsen the ecological footprints in these countries in addition to the negative effects of economic growth in all countries including China. In contrast, high-technology exports appear to mitigate ecological footprint in China, however, eco-friendly technologies fail to reduce ecological footprints as in other analysed nations. The causality tests indicate bidirectional and unidirectional causal relationships among variables with the exception of China where the neutrality hypothesis holds between economic growth and ecological patents and also high-technology exports and ecological patents. These findings provide important insights in achieving sustainable development.

Firm Size on IDX BUMN 20 Stock Prices: The Role of Mediating Activity and Profitability

This study investigates if firm size increases stock prices using activity and profitability as mediating variables. It employs a quantitative causality method using secondary data from financial reports on firm websites and the IDX. The sample includes companies listed in the IDX BUMN 20 index from 2018-2021, using non-probability sampling and unbalanced panel data estimated with a random effects model. Data analysis involves descriptive statistics, mediation regression, and path analysis with Eviews 12 software. Results indicate firm size and profitability positively impact stock price, firm size positively impacts profitability, activity does not impact stock price, and activity and profitability do not mediate the firm size-stock price relationship

Cryptocurrency: A new player or a new crisis in financial markets? —— Evolutionary analysis of association and risk spillover based on network science

In recent years, cryptocurrency has attracted widespread research attention. Against the backdrop of financial globalization, the high volatility of cryptocurrency prices may pose a threat to the stability of the entire financial system. To explore the potential association and transmission of financial risks between cryptocurrency and traditional financial assets, this paper constructs a complex network using the Granger causality method and the DY spillover method. Based on data from 24 categories of assets or index returns from different markets, networks of association and risk spillover between cryptocurrency market and traditional financial markets are established under different time periods, the study covers the period from January 2015 to November 2023. Analyzing the mutual influence between cryptocurrency and traditional financial markets from the perspective of complex networks, and evaluating the market positioning, risk characteristics, and investment potential of cryptocurrency. Research findings indicate that cryptocurrency possesses not only monetary characteristics but also functions as an investment tool, significantly impacting the stability of traditional financial markets. Furthermore, different types of cryptocurrencies vary in market functions, risk characteristics, and investment potentials. Future research could further explore the nonlinear and dynamic associations between cryptocurrency and traditional financial markets, as well as the micro mechanisms and behavioral factors within cryptocurrency markets.

The Influence Of Raw Material Supply On Production Results At Adinda Embroidery Convection Tasikmalaya District

The research carried out by the author aims to find out and analyze the description of the supply of raw materials and production results at the Adinda Embroidery Convection, Tasikmalaya Regency. The influence of raw material supplies on production results at the Adinda Embroidery Convection, Tasikmalaya Regency. This research is quantitative research using the causality method with a survey approach. The sampling technique used was full sampling, namely using 48 months of data for 4 years from 2020 - 2023 at the Adinda Embroidery Convection. The analytical tool used in this research was simple regression using SPSS 26.0. The research results show that the supply of raw materials and production results at the Adinda Embroidery Convection in Tasikmalaya Regency fluctuates every month according to market conditions and consumer demand. The supply of raw materials has a significant effect on production results at the Adinda Embroidery Convection, Tasikmalaya Regency.

Pengaruh Literasi Keuangan, Self Control dan Inklusi Keuangan Terhadap Perilaku Menabung (Survei Pada Mahasiswa Fakultas Ekonomi dan Bisnis Universitas Perjuangan Tasikmalaya)

The aim of this research is to understand the influence of financial literacy, self-control and financial inclusion on saving behavior (survey of students at the Faculty of Economics and Business, Universitas Perjuangan Tasikmalaya). This research uses a quantitative causality method with a survey approach. The population taken in this research were students from the Faculty of Economics and Business, Universitas Perjuangan Tasikmalaya who were still active in 2023-2024. With a research sample of 100 respondents. The technique for determining the sample in this research uses nonprobability sampling, precisely using incidental sampling techniques. The data obtained in this research are primary data and secondary data. The analytical tool used in this research is multiple regression using SPSS Version 25. Based on the results of the F test, it shows that financial literacy, self-control and financial inclusion simultaneously have a significant effect on saving behavior. Based on the results of the T test, it shows that financial literacy and self-control partially have a significant effect on saving behavior. Meanwhile, partial financial inclusion has no significant effect on saving behavior.

Pengaruh Talent Management Dan Job Insecurity Terhadap Produktivitas Kerja Karyawan Ninja Ekspress Kota Tasikmalaya

This research aims to determine the influence of Talent Management and Job Insecurity on work productivity (survey of Ninja Ekspress employees in Tasikmalaya City). The method used in this research is causality through a survey approach. This research is quantitative research using the causality method with a survey approach. The sample in this research was 74 Ninja Ekspress warehouse employees. The analytical tool used in this research is multiple regression using SPSS 26.0. The research results show that Talent Management, Job Insecurity and Work Productivity of Tasikmalaya City Ninja Express Employees have a very good assessment classification. Talent Management and Job Insecurity simultaneously have a significant effect on the Work Productivity of Tasikmalaya City Ninja Express Employees. Talent Management partially has a significant effect on the work productivity of Ninja Ekspress employees in Tasikmalaya City. Job Insecurity partially has a significant effect on the Work Productivity of Tasikmalaya City Ninja Express Employees.

Asymmetric Analysis of Causal Relations in the Informality–Globalisation Nexus in Africa

This study examines the causal relationship between informality and globalisation in 30 African countries. It deviates from traditional research by adopting a bi-directional framework to address reverse causality. By applying the DH causality method in both linear and nonlinear frameworks, this research challenges the assumption of a linear relationship and finds that the causal structure is better explained within a nonlinear asymmetric context. This paper provides recommendations based on the identified causal relationships. For countries in which globalisation leads to informality, such as Angola, Congo, Guinea, Gambia, Mozambique, Sierra Leone, Tunisia, Tanzania, Uganda, Zambia, and Zimbabwe, the paper suggests policy measures to integrate the informal sector into the formal economy. These measures include designing programmes to facilitate transition, implementing skill development initiatives, and establishing support mechanisms for entrepreneurship and small businesses. Additionally, this paper advises the development of social safety nets, improved market access, effective monitoring and regulation mechanisms, education on the benefits of globalisation, and international cooperation. For countries experiencing positive shocks from informality to globalisation, this paper recommends targeted support programs for entrepreneurship, initiatives to formalize the sector, the enhancement of market access, and skill development tailored to the needs of the informal sector. These policy recommendations aim to capitalize on the positive shocks in informality by fostering entrepreneurship, formalization, market access, and skill development. In the case of negative shocks in globalisation leading to positive shocks in informality, the paper suggests implementing resilience-building policies for the informal sector during economic downturns, establishing social safety nets, and adopting flexible labour policies.

Social distancing during the COVID-19 pandemic: Potential impact and correlation with asthma

BackgroundNon-pharmaceutical interventions have been implemented globally to control the COVID-19 pandemic and have been shown to alleviate both allergies and respiratory infections. Although mask-wearing is an accepted non-pharmaceutical intervention, the effects of social distancing have not been thoroughly evaluated. ObjectivesTo evaluate the effects of social distancing on asthma trends in Seoul, South Korea. MethodsThis study included data from the National Health Insurance Service of South Korea, covering approximately 10 million people in Seoul. Daily and monthly data of patients with asthma from 2018 to 2021 were examined, and the degree of social distancing performance was measured using the number of subway users as an index. Pearson's correlation coefficient was used to determine the relationship between the two indices. The change-point detection technique, cross-correlation, and Granger causality method were used to assess the temporal causality between social distancing and asthma. ResultsThe number of patients with asthma decreased by 42.4 % from 2019 to 2020, while that of subway users decreased by 26.3 % during this period. Pearson's correlation analysis revealed significant positive correlations. Asthma and subway users showed a significant change in incidence following the implementation of social distancing; subway users showed a causal relationship with patients with asthma. ConclusionOur results showed that the number of subway users decreased after the implementation of strict social distancing, coinciding with a decrease in the number of patients with asthma. These findings suggest that social distancing measures implemented to control COVID-19 may reduce the incidence and exacerbation of asthma.