Cointegration Research Articles

TÜRKIYE'S FINANCIAL INTEGRATION AND EXPORT RELATIONSHIPWITH OECD COUNTRIES

Financial integration of countries is constantly increasing with their mutual trade. In other words, rising of partnership on international market ensure higher financial integration over time. Increasing of financial integration among countries also will be reason of raising the similarity and bilateral agreements of these countries. This paper shows that what countries have tendency to act together in terms of financial integration with Türkiye in the designated period. For this purpose, the stock market indexes of Belgium, France, Germany, Israel, Italy, Spain, Switzerland, and the United Kingdom those are top trading partner of Türkiye and members of the Organization for Economic Co-operation and Development (OECD) selected for this research. Gregory - Hansen (1996) cointegration test used to find the financial integration between the stock market indices of selected countries and Türkiye. The result of test method shows that the highest correlation is with Germany after Israel, and the second line is for the United Kingdom. According to result of the cointegration test, although Türkiye acts together with all selected countries, Germany stand on different point. This could explain with Germany is the major partner of Türkiye in terms of mutual trade.

An Historical Review of International Trade and CO2 Emissions in Pakistan: A Quantitative

Environmental protection has become an international issue, reflecting widespread concern about environmental degradation. Researchers have emphasized the importance of the environment in trade policy debates. The focus of this study is to explore the relationship that is present between trade openness and the quality of environment in Pakistan. This research investigates the famous nexus between trade and the environment. The study uses data from 1990-2021 for analysis. The emissions of CO2 (Metric tons per capita) serves as the proxy of Environmental quality as the dependent variable. Empirical analysis is done by applying Autoregressive Distributed Lag (ARDL) time series econometric technique. Trade openness is the main independent variable, whereas population, foreign direct investment, and non-renewable energy are used as control factors. The results obtained from co-integration test prove a long term relationship between CO2 emissions and trade openness. A study indicated that increased commercial openness leads to an increase in CO2 emissions, which promotes environmental degradation in Pakistan. It is proposed that trade policies take environmental protection into account.

Does energy poverty contribute to gender inequality and environmental degradation in Africa?

Purpose This study aims to examine whether energy poverty impacts gender inequality and CO2 emissions in African countries with the biggest economies by gross domestic product (GDP) per capita from 1996 to 2020. Additionally, this study examines the existence of the gender Kuznets curve (GKC) and the environmental Kuznets curve (EKC) theories. Furthermore, it evaluates the connection between economic development and carbon emissions, on the one hand, and economic development and gender inequality on the other. Design/methodology/approach This study uses the augmented Dickey–Fuller and Phillip–Perron unit root tests to determine the degree of integration between the variables. It also uses the Pedroni and Fisher–Combine Johansen cointegration tests to assess a long-run relationship between the variables. The authors adopted the pooled mean group (PMG)-autoregressive distributed lag model and used the E-Views 12 software to run the analysis. Findings The empirical analysis approves the long-run correlation among the variables used in this study. Increased energy poverty and GDP increase CO2 emissions, whereas income square hurts CO2 emissions. These results are consistent with the EKC hypothesis, which proposes a non-linear relationship between CO2 emissions and economic growth in the studied areas (similar to an inverted U shape). Long-term foreign direct investment (FDI) has a negative correlation with CO2 emissions. On the contrary, energy poverty, GDPsq and FDI find a positive relationship with gender inequality, whereas GDP finds a negative association with gender inequality. The negative relationship between GDPsq and gender inequality establishes a “U”-shaped connection between income and gender inequality. Thus, it supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality. Originality/value This study supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality.

Revisiting the environmental Kuznets curve hypothesis in the context of renewable and non-renewable energy in China

This research paper attempts to determine the effect of fossil fuel, renewable energy, and economic growth on carbon dioxide emissions and revisits China's Environmental Kuznets curve (EKC) hypothesis. The time series analysis will be performed for the years 1990 to 2020. To begin, Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) tests will be performed to verify the series' stationarity. Second, the cointegration test will be utilized to determine the validity of a cointegration vector before performing the Fully Modified Least Square approach to conduct long- and short-term estimation. The empirical analysis illustrates that renewable energy negatively and significantly affects short- and long-run carbon dioxide emissions. However, fossil fuel consumption only positively and significantly affects carbon dioxide emissions in the short run. The empirical evidence supports the Environment Kuznets Curve's hypothesis in China. Fossil fuel consumption has a considerably higher effect on carbon dioxide emissions than renewable energy. To avoid ecological damage in China, authorities must pay more consideration to encouraging the use of energy from renewable sources. This demonstrates that China's overall environmental performance first deteriorates before gradually improving with economic growth.

Overseas Capital Streams and Economic Growth Nexus: Pragmatic Insights from Nepal

The objective of the present research is to ascertain the impact of foreign capital inflows, including grants, loans, remittances, and income from tourism, on the economic growth of Nepal. This study utilizes secondary data acquired from several Nepalese economic surveys and World Bank reports. The data consists of 35 data points spanning from the fiscal years 1987/88 to 2021/22. The link between foreign capital inflows and GDP growth in Nepal is examined using fundamental statistical approaches like quantile regression, trace and Max-Eigen cointegration tests, and descriptive statistics. The results show that Nepal's grants, debt, foreign remittances, tourism earnings, and GDP growth co-integrate over the long term. Notably, 80.5 percent of Nepal's GDP growth fluctuation is accredited to foreign grants, loans, remittances, and tourism income. While foreign loans and grants are not statistically significant in and of themselves to measure GDP growth, foreign remittances and tourism income are. For every percentage increase in the median value of remittance and tourism income, the GDP grows by 0.251 and 0.816 percent, respectively. More revenue from tourism than from remittances goes towards Nepal's economic growth. Legislators can, therefore, enact suitable measures to encourage the expansion of the tourism industry

Does higher education lead to lower environmental pollution? New evidence from MENA countries using econometric panel data

Recognizing the critical significance of environmental preservation, this paper investigates the intricate relationship between higher education and environmental pollution in MENA countries from 2000 to 2018. The analysis incorporates three control variables: the globalization index, population, and gross domestic product (GDP). Employing a comprehensive methodology that includes panel unit root tests, Kao cointegration test, fixed effect GLS, fully modified ordinary least squares (FMOLS), and dynamic ordinary least squares (DOLS). As main results, we first found using GLS that higher education, globalization, and GDP per capita positively impact CO2 emissions in the MENA region. Subsequently, using FMOLS and DOLS, we found that except for GDP per capita, all other variables play a key role in mitigating CO2 emissions in the long run, thus validating the KURZNETS curve hypothesis for education and challenging it for economic growth in the MENA countries. Given the existing results, this study provides significant recommendations for policymakers and governments to reduce CO2 emissions.

LONG-TERM EQUILIBRIUM RELATIONSHIPS BETWEEN THE STOCK AND CRYPTOCURRENCIES MARKETS

This study investigates the long-term equilibrium relationships between the stock market, represented by the Dow Jones Industrial Average (DJIA), and a comprehensive range of 401 cryptocurrencies traded on Binance. Employing Johansen cointegration tests on data from January 2018 to May 2024, we examine pairwise relationships between 30 DJIA components and cryptocurrencies across various categories. Our findings reveal varying degrees of integration, with some stocks like Visa and Walt Disney Company showing strong cointegration with numerous cryptocurrencies. Sector-specific patterns emerge, such as significant links between technology stocks and platform tokens, and between financial services and DeFi tokens. Platform tokens exhibit the highest overall integration with stocks, followed by DeFi and NFT/Gaming domains. Notably, some cryptocurrencies, including major ones like Ethereum and Bitcoin, show high levels of cointegration, while others display independence. Stablecoins demonstrate strong cointegration with all stock prices. These results provide nuanced insights into the complex interactions between traditional and digital finance, contributing to our understanding of market integration, diversification strategies, and the evolving financial ecosystem.

The effect of nuclear and fossil fuel energy R&D expenditures on environmental qualities in Canada

Minimizing environmental problems and a clean ecosystem are at the top of countries’ political agendas. Although Canada is an eco-friendly country, the rapid increase in its ecological footprint (EF) and the decreasing load capacity factor (LCF) in recent years make the analysis of Canada’s environmental determinants important. In this context, the study analyzes the effects of fossil fuel and nuclear-related research and development (R&D) expenditures on the EF and LCF under the load capacity curve (LCC) and environmental Kuznets curve (EKC) conditions for the period 1981–2022, employing the Bayer-Hanck cointegration test and the Fourier-ADL approach. The findings indicate that the EKC and LCC hypotheses are valid for Canada, that fossil fuel R&D reduces the LCF, and that nuclear energy R&D contributes to environmental development. Therefore, Canadian policymakers should promote nuclear energy technologies and use the financial resources provided by economic expansion for clean energy purposes.

A Panel Analysis on the Nexus between Financial Development, Oil Production, and Trade-Openness and Its Impact on Sustainable Economic Growth: Evidence from Selected Arab Economies

In accordance with the United Nations Sustainable Development Goals agenda for decent and sustainable economic growth highlighted in the UNSDGs-8, several economies over the years have been on the quest for drivers for decent and sustainable economic growth, of which the Arab bloc is no exception. To this end, the present study draws strength from the classical growth model while exploring the dynamic nexus between oil production and economic growth while accounting for other key growth drivers like gross capital formulation accumulation, labour, trade openness, and financial development for a balanced panel of selected Arab economies. To operationalise the study objectives, the present study leverages second-generational panel econometric approaches. The econometrics techniques applied circumvent the cross-sectional dependency and slope heterogeneity in the sampled bloc. For co-integration analysis, the Westerlund’s panel co-integration test affirms a long-run equilibrium relationship between the study’s outlined variables. Furthermore, for long-run estimates, the present study leverages the common correlated effects mean group (CCEMG) methodology and the augmented mean group (AMG) method for robustness and soundness of the results and coefficients. The present study corroborates the trade-induced growth hypothesis in the entire panel at a p < 0.001 statistical level, which resonates with the mercantilism school of thought. Additionally, the present study also affirms the Solow–Swan hypothesis, where gross capital formation accumulation and labour drive economic growth. Interestingly, the panel bloc shows that oil production is a key driver to the nation’s economic growth, at a p < 0.05 statistical level. However, from a policy standpoint, there are policy suggestions for diversification of the Arab economies to move from a mono-economy dependent on oil production to other sectors like service, industry, and manufacturing, which require labour, capital accumulation, and more. Further policy caveats are outlined in the concluding section.

Impact of Selected Asian Stock Market Movement on Indian Stock Market

The involvement of people in the stock market has also increased in recent days. Thus, as a result, the volatility of the market has also increased. The profit-to-loss ratio on the stock market trade has also been on the lower side. The difficulties in the stock market have been unpredictable, thus upsetting the interests of the investors. This study compares the movement of the Indian stock markets (Sensex and Nifty) with six other major Asian stock markets (Japan, China, Hong Kong, Singapore, South Korea, and Taiwan) and tries to find the relationship between them. This study is done to check whether the movement of the major Asian stock markets is a predictor of the movement of the Indian stock markets. Statistical tools such as ordinary least squares, the Granger co-integration test, and a correlation matrix are used in this study to calculate the relationships. The result of this study will be helpful for stock market investors, particularly the short-term traders (intra-day traders) on the BSE and NSE.

Credit risk and Tunisian bank stability in the Covid-19 wave

<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Times New Roman,Times,serif"><span dir="ltr" lang="EN-US"><span style="color:black">Banks are at the core of economic functioning in various countries and are the cause of their development in various fields. In a changing environment, they must deal with certain risks and maintain financial stability as the ultimate objective. The primary objective of this study is to examine the correlation between credit risk and bank stability within the Tunisian banking sector, with a specific focus on understanding the moderating impact of the COVID-19 pandemic. To achieve this, we employ several econometric techniques, including panel unit root and cointegration tests, panel Vector Error Correction Model (VECM), Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS). Our empirical analysis relies on a panel dataset that encompasses a comprehensive sample of 8 Tunisian banks over 2000-2020. The results of our analysis unveil a significant negative relationship between credit risk and bank stability, indicating that higher levels of credit risk exert a detrimental effect on the overall stability of Tunisian banks. Furthermore, our study highlights that this adverse impact is further exacerbated during the COVID-19 pandemic, suggesting that the pandemic acts as a moderator. The findings of this study hold substantial implications for policymakers, regulators, and bank managers in Tunisia. They emphasize the critical importance of implementing robust risk management practices to mitigate credit risk and bolster bank stability. Additionally, the research underscores the need to consider the unique challenges introduced by external shocks, such as the COVID-19 pandemic, when assessing the overall stability of the banking system.</span></span></span></span></p>

Asymptotics of Cointegration Tests for High-Dimensional Var(k)

Abstract The paper studies nonstationary high-dimensional vector autoregressions of order k, VAR(k). Additional deterministic terms such as trend or seasonality are allowed. The number of time periods, T, and the number of coordinates, N, are assumed to be large and of the same order. Under this regime the first-order asymptotics of the Johansen likelihood ratio (LR), Pillai–Bartlett, and Hotelling–Lawley tests for cointegration are derived: the test statistics converge to nonrandom integrals. For more refined analysis, the paper proposes and analyzes a modification of the Johansen test. The new test for the absence of cointegration converges to the partial sum of the Airy1 point process. Supporting Monte Carlo simulations indicate that the same behavior persists universally in many situations beyond those considered in our theorems. The paper presents empirical implementations of the approach for the analysis of S&P100 stocks and of cryptocurrencies. The latter example has a strong presence of multiple cointegrating relationships, while the results for the former are consistent with the null of no cointegration.

Does fiscal expenditure matter for agricultural development? Examining the impact of technological progress on food production

AbstractRice is a staple food for vast population of China and it remarkably contributes toward China's food security. Several fiscal programs have been implemented by Chinese central government for sustainable agriculture production. In this study, we examine the long‐run influence of agricultural public investment (API) and (agro)chemical inputs use (i.e., fertilizer and pesticide) on rice yield in main rice‐producing provinces of China. Second‐generation panel unit root tests, Westerlund error correction model cointegration test, Augmented‐Mean Group (AMG) and Common Correlated Effect Mean Group (CCEMG) estimation techniques have been used in this article. The co‐integration test results reveal strong evidence of the existence of the long‐run co‐integrating link between the considered series. The results of the AMG and CCEMG methods show that (i) API, (ii) fertilizer use, and (iii) power consumption for agricultural machinery positively and significantly impact rice productivity, whereas pesticide usage affects it negatively. Panel quantile regression showed that API, fertilizer use, power consumption, and sown area are significant and positive at 0.10–0.90 quantiles. The results also indicate that pesticide usage increases rice production at 0.10–0.30 quantiles but decreases rice production at 0.40–0.90 quantile levels. Based on these findings, we derive pertinent implications for China's food security.

Revisiting the interest rate-investment nexus in India: fresh perspective from non-parametric analysis

PurposeIt is generally believed that business spending on capital expenditure tends to decrease as interest rates rise, and vice versa, this is not always the case. The previous literature produces inconclusive results vis-à-vis the interest rate and investment nexus. This study analyzes the responsiveness of investment to changes in high and low levels of interest rates in India through a quantile-based, non-parametric method utilizing annual data from 1980 to 2022.Design/methodology/approachThis study uses Quantile-on-quantile (QQ) technique proposed by Sim and Zhou (2015) to examine the impact of interest rate quantiles on quantiles of investment. In addition, long-term association and the direction of causality are estimated through the Cho et al. (2015) test of quantile cointegration and the Jeong et al. (2012) Granger causality in quantile (GCQ) test, respectively.FindingsThe empirical evidence validates that the linkage between investments and interest rate is not consistently negative and varies from quantile to quantile. The study finds a negative impact at median quantiles and a positive impact at extreme higher quantiles. Conversely, the impact at lower quantiles is negligible, which is also observed from quantile cointegration, indicating the presence of a statistically significant association above the median quantiles. Additionally, the study finds one interesting finding that there exists unidirectional causality from investment to interest rates in India rather than other way around.Research limitations/implicationsThe study provides significant implications for policymakers as it suggests that during extreme economic conditions, the effectiveness of traditional monetary policy tools to boost capital formation is restricted. Policymakers may consider alternative measures to stimulate investment during these time periods. The study additionally posits that the neoclassical theory of investment may not be readily applicable in emerging economies in its unaltered state, mostly due to the lack of well-developed financial markets.Originality/valueThere is a limited literature available on non-linear linkage between interest rates and investment. The present study adds to the existing knowledge by investigating how investment responds differently to fluctuations in interest rates, while incorporating the complete distribution of both the variables.

Balancing growth and sustainability: The long‐run impact of financial and technological innovations on India's ecological footprint

AbstractThis study examines the effects of financial and technological innovations on India's ecological footprint—a comprehensive indicator of environmental degradation. Although previous research has addressed the individual impacts of these innovations, their collective influence has not been thoroughly investigated. Using data from 1973 to 2018 and employing ARDL Bounds and Bayer‐Hanck cointegration tests, we find a long‐run relationship between innovations, economic growth, energy consumption, and the ecological footprint. Notably, while the short‐term impact of innovations appears detrimental, both financial and technological innovations demonstrate a long‐term beneficial effect on the environment, which suggests that initial investments in innovation may have short‐term environmental costs, but ultimately contribute to environmental improvement. Additionally, this study confirms the harmful long‐term effects of energy consumption and economic growth on the environment. These findings underscore the importance of transitioning to cleaner energy sources, improving energy efficiency, and implementing robust environmental policies to foster sustainable development in India.

Does financial development and economic growth matter for services export? Cross-country evidence from OECD countries

The unprecedented growth in the export of services and its accompanying economic incentives has invited discussions on service export determinants. Against this background, the present article is an attempt to test whether the contemporary theories on causal links between exports, financial development and growth hold for services export. For realizing the objective, we employed the panel cointegration technique for Organization for Economic Co-operation and Development (OECD) countries over a period of 23 years (2000–22). Findings of both first and second generation cointegration test indicate a long run equilibrium between services export, financial development and growth. However, there are differences in the short and long association, as outcomes of panel auto autoregressive distributed lag (ARDL) approach show financial development to be significant determinant of services export only over long run. Additionally, granger causality test suggests a feedback mechanism prevalent between services export-financial development, services export-growth and financial development-growth. The empirical evidence offered in the study elucidates the significance of continuously developing the financial markets and institutions for achieving sustained growth in export of services. The bi-directional relationship between the variables also presents an opportunity to strengthen economic growth and financial development process through policies aimed at expanding services export.

Impulsive Response Analysis of Financial Markets in QUAD Economies: A VAR Modelling Approach

Financial market integration remains a key focus in academic finance, especially given how crucial it is to portfolio diversification. The purpose of this research is to investigate a crucial yet underexplored aspect like the cointegration of economies with formal or unofficial military ties, focusing on countries within the Quad strategic forum—India, Japan, Australia, and the United States. The daily closing values of benchmark stock market indices of Quad economies viz. Nikkie 225 for Japan, S&P ASX 200 for Australia, NASDAQ composite for the United States, and S&P Sensex for India were considered. Unit root tests, Johansen Cointegration tests, VAR (Vector Autoregressive) model, and the Granger Causality statistics are computed for data analysis. Additionally, the Impulse response function and variance decomposition are computed for better financial market predictions. The result reveals intriguing dynamics: while the Indian stock market initially responds positively to shocks in the Australian market, this effect diminishes over time. Also, movements in the Australian and United States stock markets significantly contribute to predicting fluctuations in the Indian market, contrasting with the limited predictive power of the Japanese stock market. These findings carry significant practical implications for international investors, offering valuable guidance for optimizing portfolio diversification strategies amidst geopolitical and economic complexities. This paper contributes to academic literature by offering empirical insights into the short-term dynamics and causal relationships of Quad countries’ stock markets, setting a foundation for future studies on long-term trends and market responses to external factors.

Competency and efficacy of energy futures: empirical investigation from emerging economy

PurposeThe purpose of this study is to analyze the price discovery and market efficiency of energy futures traded in India. The study also examines the volatility spillover effect between the cash and futures markets of energy commodities.Design/methodology/approachThe study uses crude oil and natural gas spot and futures series traded at Multi Commodity Exchange (MCX), India. To evaluate the objectives, the paper employs the cointegration test, causality check, dynamic ordinary least squares (DOLS) method and Baba, Engle, Kraft and Kroner (BEKK) GARCH Model.FindingsThe study supports the long-run association between the selected markets. Unlike natural gas, in the case of crude oil bidirectional, flow of information is observed. The study rejects the unbiasedness and efficient market hypothesis of the energy futures market in India. Further, the study confirms that the selected energy commodities indicate bidirectional shock transmission between their respective cash and futures markets.Practical implicationsThe study will assist the commodity market participants in designing their trading strategy. The volatility signal will be used by investors and portfolio managers for risk management and portfolio adjustment. Regulators will be able to anticipate future spillover and can design policies to strengthen the market.Originality/valueThe paper evaluates the three aspects of the energy futures market, namely price discovery, market efficiency and volatility slipover. To the best of the authors’ knowledge, studies on efficacy and shock transmission in the context of the energy futures market in India are rare. Further, the study also contributes by investigating the price discovery process of the energy futures market.

COVID-19 pandemic, oil prices and Saudi stock market: empirical evidence from ARDL modeling and Bayer–Hanck cointegration approach

In 2020, the world experienced several significant events, including the coronavirus (COVID-19) pandemic and the collapse of international crude oil prices. The rapid spread of this pandemic has dramatic impacts on financial markets all over the world, thereby increasing market risk aversion in an unprecedented way since the subprime financial crisis. The decline in stock markets implied volatilities of equity and oil prices, thereby heightening turmoil in global financial markets despite comprehensive and substantial financial reforms. To this end, we investigated the likely effects of this pandemic on the Saudi stock market while controlling for oil prices based on daily data for a period from 1/1/2020 to 19/9/2022. To ascertain the existence of a long-run equilibrium relationship between the variables, we applied autoregressive distributed lag (ARDL) modeling and the error correction model, with this ultimately revealing the existence of strong cointegration in the long run. The ARDL bounds test was found to be robust by combined cointegration tests, thus providing further evidence of a strong relationship in the long run. Granger causality tests also yielded evidence of causality between the variables in both directions. The total COVID-19 confirmed cases and oil prices also caused movements in stock returns in the short run. Our findings have some prominent implications for asset managers and policymakers to improve stock market efficiency and boost global economic activity. Saudi authorities can consequently remove the regulatory and legal obstacles to develop their stock market and better improve the risk management, which will allow to make quick decisions in response to any oil price volatilities. Policymakers should also adopt proactive strategies that can comfort stock investors’ anxieties over the increasing oil price volatilities. Finally, the findings should be treated with some cautions because of the limited sample size and the tests’ statistical inference. Nevertheless, they do open opportunities for further studies to look in more detail at how the COVID-19 pandemic affected, over the short and long run, monetary and fiscal policy coordination, financial stability, and various other macroeconomic indicators in Saudi Arabia.

The Impact of Renewable Energy; Financial Development and Economic Growth on Carbon Emission: Empirical Evidence from Pakistan

This research investigates the impact of renewable energy; financial development, economic growth, nonrenewable energy and natural resource rents on carbon emissions in Pakistan. An annual data series ranging from 1990 to 2022 is used; while Pesaran’s et al. (2001) cointegration test is utilized and empirical results confirm that renewable energy, financial development, nonrenewable energy and economic growth have long run cointegrating relation with carbon emissions. The results further provide evidence that utilization of clean energy combats carbon emission while financial development, economic growth and unclean energy promote carbon emission. Natural resource rents also help in combating carbon emission but only in long run. These results are reliable as guided by diagnostics used in this research. This research suggests that both clean energy and natural resources must be promoted to combat carbon emissions while financial development; economic growth and nonrenewable energy may be escalated carefully because these are promoting environmental pollution in Pakistan.