Run Relationship Research Articles

Does Japan's energy consumption impact its environmental degradation? Evidence from ARDL technique

Using annual data from 1990 through 2021, this study looked into the roles of economic growth, energy use, globalization, and regulatory quality in Japan. In our analysis, we make use of the ARDL techniques. Using the ARDL, according to empirical data, GDP and fossil fuel have a positive and significant connection with CO2, meaning any increase in GDP and fossil fuel will lead to increase in environmental degradation in the long-run. On the other hand, renewable energy has a negative and significant relationship with CO2 in the long-run, meaning that, any increase in the consumption of renewable energy will reduce environmental degradation in Japan. While globalization and regulatory quality have negative and insignificant association with CO2 in the lung-run. In the short-term, GDP, renewable energy, fossil fuel and globalization are all statistically significantly linked negatively to CO2 emissions. Our study also uses FMOLS, DOLS and CRR analysis which also support the ARDL model. According to our findings with FMOLS, DOLS and CRR outputs, shows long run relationship between CO2 and economic growth, renewable energy usage, use of fossil fuels, globalization, and trade openness in Japan. In addition, Pearson correlation was employed to test the connections between the variables. Our findings therefore give the Japanese government and the rest of the world additional information to help them think about renewable energy usage as the most reliable strategy to cut back on CO2 emissions.

CAUSAL RELATIONSHIPS BETWEEN FDI AND ECONOMIC GROWTH IN INDIAN INDUSTRIAL SECTORS: A SEM APPROACH

Purpose: This empirical investigation comes from the inconclusive evidence produced by a flurry of previous empirical studies on foreign direct investment (FDI)-growth nexus. The study recognizes the fact that the treatment of FDI inflows in an aggregate form instead of a Select sector for correlating it with economic growth in India. Design/Methodology/Approach: The purpose of the study is based on Top Five Sectors (Service sector, Telecommunication Sector, Drugs and Pharmaceutical sector, Chemical Sector, Metallurgical industries) in India. I collected data from the DPIIT website (Secondary Data) for the period 2022-2023. We are Using stalactitical tools like ADF Stationarity, VECM, VAR, SEM Model. Originality/Value: This study applies Structure Equation model with vector autoregressive specification to examine as to how sector-wise FDI inflows can affect the growth of respective sectors in the context of an emerging economy like India for the period from April 2022 to March 2023. Findings: FDI and growth both for the short and long run. On the basis of the findings, the study suggests economic policymakers to rejuvenate the primary sector of India so that it can attract and absorb more FDI and ensure sustainable Sectoral growth. The study examined that Computer Software & Hardware, Service Sector, Trading Sector, Non-Conventional Energy, Drugs & Pharmaceuticals with FDI had shown significant short run relationship Keywords: FDI, Sectoral Growth, Economy Growth, SEM Model.

Government Expenditure and Economic Growth in Kenya

Despite Kenya being one of the fastest growing economies in Africa, Kenya continues to face key challenges in economic growth. The government therefore has a key responsibility to instigate consistent and inclusive economic growth if the country is to achieve the economic pillar of the Vision 2030 of attaining an economic growth rate of 10% consistently. The aim of study therefore was to assess the relationship between government expenditure and economic growth in Kenya with the specific objectives being to assess the relationship of the types of government expenditure and economic growth in Kenya while incorporating the moderating effect of inflation on the relationship. The theoretical framework of the study was based on the Wagner’s organic state theory, Keynesian theory (1936), Wise and Peacock theory and the Musgrave theory of public expenditure. The study adopted a quantitative causal research design and a modified Barro (1990) model to assess the causality and the existence of short and long run relationships. The study adopted techniques like the Vector autoregression model (VAR), granger causality test, test for cointegration and the Vector error correction model (VECM) to analyze short run relationships, long run relationships of the variables and causation between the variables. Findings of the study showed that the types of government expenditure collectively granger causes economic growth and more specifically in the short run the study concluded that economic growth has had an insignificant relationship with government consumption expenditure, a negative relationship with government expenditure, a positive relationship with government transfer payments and an insignificant relationship with inflation. Similarly, in the long run the study concluded that economic growth has had a negative relationship with government consumption expenditure, a positive relationship with government investment expenditure, a negative with government transfer payments and the moderating the moderating effect of inflation was noted to be negative relationship. The findings of the study will not only contribute to the existing literature but it will also be used to develop fresh methods and techniques for boosting Kenya's economic growth in relation to government spending by both the government officials and other policy makers in an effort to achieve the economic pillar of vision 2030 and beyond.

Re-evaluating the impact of unemployment rate on Health outcomes in Nigeria using an ARDL approach

This study examines the impact of unemployment rate on health outcomes in Nigeria from 1985 to 2022. The study adopts the annual time series data obtained from Central Bank of Nigeria. Statistical Bulletin and World Development Indicators. This study uses life expectancy and child mortality as the two metrics for health outcomes. The ARDL Bounds Test for co-integration shows there exists long run relationship between the variables. The study employed the ARDL model and results show that unemployment rate has negative and positive impacts on the two metrics respectively in both the short run and long run. While other variables like population growth, total labor force, and government expenditure on health show statistically significant impact on life expectancy in Nigeria. The study recommends that to improve life expectancy and reduce child mortality, there should be an investment in primary healthcare, health awareness campaigns, education, sustainable economic growth, social safety nets, population control strategies, and a skilled labor force.

Exploring the Relationship between Economic Growth, Renewable Energy and Carbon Emissions: A Case of Cuba

In the modern era, balancing economic growth and environmental sustainability has become one of the greatest challenges, especially for the emerging nations. As a case of examining the decoupling of economic growth from carbon emissions, Cuba’s historical reliance on fossil fuels, especially during the U.S. embargo, is quite interesting. In this article we have examined the impact of economic growth upon the carbon emissions of Cuba. We extracted annual time series data for the dependent variable (Carbon Emissions) and explanatory variables (Economic Growth and Renewable Energy Consumption) for the period spanning from 1990 to 2020. To determine the long run relationship between the variables, we used Auto regressive distributed lags (ARDL) bounds test of co-integration. The empirical findings revealed the existence of a long-run relationship among the variables of the model. We found that economic growth has a significant positive impact upon carbon emissions; furthermore, there is also a bi-directional causality between the economic growth and the carbon emissions. This research could help the policymakers to establish novel and efficient policies to tackle the environmental issues and move closer to the attainment of sustainable development goals.

Factors Affecting Tax Revenue Growth in Uganda

Purpose – The study sought to identify the determinants of tax revenue growth in Uganda, utilizing time series quarterly data spanning from 2008 to 2023. Design/methodology/approach – An autoregressive distributive lag - Error Correction Model was employed to establish the long run and short run relationships between the variables. Findings – The study findings demonstrated that agriculture, industry and services sectors negatively affect the growth of tax revenue in the short run and long run. Trade openness and exchange rates positively affect tax revenue growth in the long run. Inflation exhibited an insignificant effect on tax revenue growth in the short run and long run. The study recommends directing policy towards enhancing trade openness, further economic integration and improving trade facilitation. Originality/value – This paper provides a deeper understanding of the determinants of tax revenue growth in Uganda.

PROMOTING COCOA EXPORT FOR TRANSFORMATIVE AND SUSTAINABLE AGRICULTURAL GROWTH IN NIGERIA

This study was carried out to assess whether cocoa export crop could serve as driver for transformative and sustainable agricultural growth in Nigeria. Data were collected from secondary sources. Vector Error correction, impulse response and variance decomposition were used as analytical tools. The results showed that the in the short run the coefficient of determination (R2) was 0.507 indicating that 50.7% of the variation in agricultural growth was explained by cocoa export, exchange rate, government expenditure and labour. There is a positive short run relationship and a negative long run relationship between cocoa export and agricultural growth. Labour exhibits an adverse effect in the short and long run on agricultural growth. Also, the result shows a short and long run positive relationship between exchange rate, government agricultural spending, and agricultural growth. Agricultural growth responded positively to a unit shock in Cocoa export and exchange rate in both the short run and long run. It was recommended that government should be proactive in its responsibilities by increasing budgetary allocation to agriculture and monitoring of its distribution, incentivize local investors and cocoa farmers, put in place viable export policy and appropriate exchange rate policy to stabilize the Nigerian economy. This will restore the place of Nigeria in the competitive cocoa market as well as increase agricultural growth.

Exploring the relationship between macroeconomic indicators and sectoral indices of Indian stock market.

The influence of macroeconomic indicators makes it important to study the relationship between macroeconomic indicators and stock market return. On further analysis it can be observed that different sectors respond differently to change in the macroeconomic indicator that is important for investors, researchers and policy makers. The autoregressive distributed lag (ARDL) model is applied to study influence of macroeconomic indicators on sectoral return of NSE from April 2012 to August 2024. Findings of the study show that macroeconomic indicators influence sectoral return in the short run as well as long run and the influence is differential. The analysis of long run relationship shows that Foreign Institutional Investment (FII) significantly affects all the sectoral indices except IT. Index of industrial production (IIP) have significant relationship with Auto, IT, Media, Metal and Pharma. Money supply (MS) significantly affects Bank, FMCG and IT in the long run. Wholesale Price Index (WPI) has significant relationship with Auto, FMCG and Media in the long run. Economic Policy Uncertainty Index (EPU) affects Auto, FMCG and Pharma in the long run. Crude oil price (COP) has significant effect only on Media in the long run. Exchange rate (ER) does not have significant effect on any of the sectoral index. In the long run FII, IIP, EPU, MS and WIP are major determinants of stock market return. In the short run FII, ER and COP are major determinants of stock market return.

IMPACT OF PUBLIC DEBT ON NIGERIA ECONOMY

This study seeks to evaluate the impact of public debts on economic growth in Nigeria using time series data from 1983 to 2023. To achieve these objectives, the time series data were subjected to unit root test to remove the possibility of spurious regression due to non-stationarity of data. Three models were formulated and an Autoregressive Distributed Lag (ARDL) Cointegration Technique was used as method of analysis. The variables used in the study were further subjected to bound test and other econometric tests. The data were co-integrated at order 1(1) and order 1(0). The long run relationship of the underlying variables is detected through the F-statistic (Wald test). To achieve the objectives of this study, three economic models were formulated to proxy public debt and economic growth in Nigeria. The model one shows that economic growth can be proxy with financial development variable (FINDEV) while public debt is proxies with other variables such as federal government bond, external debts etc. The result of the findings shows that public debts affect economic growth in Nigeria. Also, it reveals that external debts are important in Nigeria but its effect does not significantly affect economic growth in Nigeria and that domestic debt is finance with huge resources but does not significantly affect economic growth. The study therefore, recommended that government should ensure that all public debts match the amount of infrastructure in the country as the major reason for borrowing should be to finance infrastructure. Therefore, whatever policy the government embarks upon should be stable, very relevant to the Nigerian economy, and also creates an enabling environment for existing and potential investors that would contribute to economic growth.

Effect of Financial Development on Poverty: An Empirical Case Study of Pakistan

This research emphases on the effect of Financial Development (FII) on poverty of Pakistan. Time series data from 1980 to 2024 is used in this study and Auto Regressive Distribution Lag (ARDL) technique is incorporated to estimate the regression result. Foreign Direct Investment (FDI), inflation, domestic credit to private sector by bank, poverty headcount ratio at national poverty lines are the variables used in this study. Long run relationship is found between FII and poverty. Regression results have ascertained that a joint effect of FII and FDI significantly reduces poverty. For the policy recommendation this study process to create concentrated policies for attracting FDI and using it with FII for lowering down the poverty pressures.

Effects of Financial Development on Economic Growth in Pakistan: Does FDI Matter?

This research focuses on the effect of Financial Development (FND) on economic growth, of Pakistan. Time series data from 1980 to 2024 is used in this study and Auto Regressive Distribution Lag (ARDL) technique is used to estimate the regression result. GDP growth, Foreign Direct Investment (FDI), domestic credit to private sector by bank, are the variables used in this study. Long run relationship is found between FND and economic growth. The long run coefficient results indicate that FND and FDI alone are negatively associated with economic growth. However, interaction of FND and FDI possesses significant positive effect on economic growth. This study suggests that FND and FDI are the important factors to solve the pertained low economic growth issue of Pakistan. As a policy recommendation, this study invites to follow the creditable policies for inviting FND and FDI due to having a significant potential for favouring economic growth.

Sector Value Addition in GDP and CO2 Emanation in Sri Lanka

This study investigates the impact of agriculture, industry, and service sector value added in the gross domestic production (GDP) on carbon (CO2) emissions in Sri Lanka from 1965 to 2023. The study employed the Autoregressive Distribution Lagged (ARDL) bound test to investigate the study variables; long run relationship. The study results show that carbon emissions and value added in agriculture have negative significant association while value added in service and carbon emission has positive significant association in both short and long run. The results analysis does not support the EKC hypothesis in Sri Lanka. Furthermore, in this study, The EKC hypothesis contradicts in the sense that Sri Lanka moves from the secondary to the tertiary sector (Services) but CO2 emissions do not decrease but rather increase with rising income that is the new findings of the research. Thus, the implication of the research is that staying service economy is not the only way of reducing CO2 emissions because value added services in GDP are also associated with CO2 emissions. As well as other factors that affect CO2 emissions such as environmental awareness, technique effects, trade openness, and environmental regulations, are welcome to further researchers.

Evaluating the Impact of Energy Price and Energy Consumption on Environmental Sustainability in Case of Pakistan

Energy prices and energy consumption are pivotal factors influencing environmental sustainability. Fluctuations in energy prices can significantly affect consumer and industrial behavior, impacting the choice of energy sources and overall energy demand. Using annual time series data from 1990 to 2023, this study aims to assess, by Energy Price and Energy Consumption, Environmental Sustainability in Case of Pakistan. For stationary of the variables, the study applied Augmented Dickey - Fuller (ADF) test using unit root. Furthermore, used in order to observe the long-run co-integration between the variables was the Autoregressive Distributed Lag (ARDL) Model, ARDL Bound test and Error Correction Method. The results show that consumption of renewable energy and energy price help to lower CO2 emissions. Conversely, trade and foreign direct investment as well as non-renewable energy consumption raise CO2 emissions in Pakistan. Moreover, research confirms that EKC exists in Pakistan. The ARD Bound Test results show long run relationships between the variables. The Error Correction Model indicates that, on average, 73.40 percent error will be corrected from short run to long run equilibrium annually. In order to investigate the stability of the projected coefficients, the last study used Cumulative Sum (CUSUM) of Recursive Residuals & Cumulative Sum (CUSUMQ) of Recursive Residual Square. The result shows that it is stable as CUSUM is within 5% level of significance and CUSUMSQ is also within boundaries of 5% significance level. The study recommends that, engage with global initiatives and partnerships focused on sustainable energy practices. Sharing knowledge and resources can help Pakistan adopt best practices and technologies that enhance environmental sustainability.

Reassessing the military spending–economic growth nexus in the ‘shadows’: selected Balkan countries, 1990–2022

ABSTRACT Informality plays a pivotal role in developing and transition economies, where it can hinder growth, policy effectiveness, and competition, while also reducing regulatory burdens and enhancing competitiveness. Military expenditures (milex) support national security, attract capital, and promote social order but may divert resources from more productive sectors. This study builds on existing literature to re-examine the milex–economic growth nexus in the context of informality across selected Balkan countries (1990-2022). Using panel autoregressive distributed lag (P-ARDL) and cross-sectional augmented (CS) P-ARDL models, it explores both short – and long – run relationships. By incorporating widely accepted informality indicators, the study ensures consistency and comparability with prior research. Findings reveal that milex negatively impacts economic growth, even when informality is accounted for. While informality boosts growth in the short – run, it undermines it in the long – run. These results, confirmed through robustness checks, offer critical insights for policymakers aiming to promote sustainable development, social stability, and national security.

Evaluation of Long Run Relationship between Financial Development and Economic Performance in Nigeria

Evaluation of Long Run Relationship between Financial Development and Economic Performance in Nigeria

CRYPTOCURRENCY AND ITS DISRUPTIVE POTENTIAL: INVESTIGATING LONG-RUN AND SHORT-RUN RELATIONSHIPS WITH SOME SELECTED MACROECONOMIC INDICATORS

The advent of cryptocurrency and underlying blockchain technology has ushered in a new era of digital finance, challenging traditional economic frameworks and prompting a reassessment of the macroeconomic landscape. This research work delves into the multifaceted economic impact of cryptocurrency, examining its potential implications for monetary policy, financial stability, and economic growth. This study uses a time series approach, that is Johansen cointegration and Granger causality in determining both the long and short run relationship that exist between the exchange rate of cryptocurrency prices (Binance coin, Bitcoin, Dogecoin, Ethereum, And Ripple) versus the U.S dollar and GDP from January, 2018 to July, 2023. And While, it also focuses on checking the long run and short run equilibrium relationship between the economic/financial variables and cryptocurrency market capitalization from January, 2018 to July, 2023. It considers a monthly data for both the exchange rates of the selected cryptocurrency prices versus the U.S dollar and the selected economic/financial time series variables. Finally, the study reveals that the result obtained from both tests. That is, the Johansen cointegration test and Granger causality Test, shows that short run effects exist more among the studied time series variables than in the long-run, and that changes in the selected cryptocurrency prices can be used to predict changes in the macroeconomic variables and indicators.

Macroeconomic Factors and Stock Market Performance Based on New Evidence: A Case Study from Nigeria

The nexus between macroeconomic conditions and stock market performance is multifaceted in nature. One of the considerations of investors before investing in the stock market is to assess the macro-economic environment of the country. There have been divergent views on the relationship between stock market and macro-economic variables in literature and this debate is inconclusive. This study included the variable that measures the overall macroeconomic environment i.e. Country Policy and Institutional Assessment (CPIA), which is imperative and novel because it has been ignored in the past. This study provided empirical evidence on the relationship between selected macro-economic factors and stock market performance in Nigeria from 2003 to 2022. The foundational theory for this study is the Arbitrage Pricing Theory (APT). The study employed the Autoregressive Distributed Lag (ARDL) cointegration approach to examine relationship between macroeconomic variables and stock market performance in Nigeria. The ARDL results established a short-run linear relationship and non-existence of long run relationship among the variables. The results suggested that stock performance in Nigeria was influenced positively by GDP growth although it was an insignificant influence. However, the study that the found overall macroeconomic environment, inflation, and interest rate spread, having a negative yet insignificant influence over the stock market performance. These findings are important for policy makers because the overall macro-economic environment considers the effectiveness of the policies and actions taken as well as the institutional arrangements a country's government and central bank to regulate and control the economy. This study recommends the need for proper institutional arrangement and policy framework to manage and maintain stable macro-economic environment to promote stock market performance.

Exploring the relationship between macroeconomic indicators and sectoral indices of Indian stock market

Background of the study The influence of macroeconomic indicators makes it important to study the relationship between macroeconomic indicators and stock market return. On further analysis it can be observed that different sectors respond differently to change in the macroeconomic indicator that is important for investors, researchers and policy makers. Methods The autoregressive distributed lag (ARDL) model is applied to study influence of macroeconomic indicators on sectoral return of NSE from April 2012 to August 2024. Results Findings of the study show that macroeconomic indicators influence sectoral return in the short run as well as long run and the influence is differential. The analysis of long run relationship shows that Foreign Institutional Investment (FII) significantly affects all the sectoral indices except IT. Index of industrial production (IIP) have significant relationship with Auto, IT, Media, Metal and Pharma. Money supply (MS) significantly affects Bank, FMCG and IT in the long run. Wholesale Price Index (WPI) has significant relationship with Auto, FMCG and Media in the long run. Economic Policy Uncertainty Index (EPU) affects Auto, FMCG and Pharma in the long run. Crude oil price (COP) has significant effect only on Media in the long run. Exchange rate (ER) does not have significant effect on any of the sectoral index. Conclusion In the long run FII, IIP, EPU, MS and WIP are major determinants of stock market return. In the short run FII, ER and COP are major determinants of stock market return.

Non-Renewable Energy Consumption and Economic Growth: Evidence from Uganda

Back Ground: This paper concerns itself with an investigation on non-renewable energy consumption and economic growth, the case of Uganda. The arguments of a causal relationship between non-renewable energy consumption and economic growth have dissenting view. Methods: It used time series data econometric techniques to establish a causal link between variables of study. The Vector error correction and structural vector autoregression, Granger for causal linkage and Johansen co-integration test was carried out to ascertain if there exists a long run relationship between non-renewable energy consumption and real GDP. Results: The results support the growth hypothesis between non-renewable energy consumption and economic growth in the long run as shown in the VECM. This SVAR shows that these results are not significant. Conclusion: The conclusion therefore is that non-renewable energy consumption in regard to economic growth is mainly attributed to imported fossil fuels particularly diesel that is used in thermal generators to run electricity hence unable to support the growth process over the long run. Novelty: This paper provides insights on how energy drives economic growth and sustainable development. It also captures the impact of investment into overall economic growth that is in line with the contemporary global agenda.

Are the Crypto Markets Shock Resilient to COVID-19? A Comparative Investigation of Trading Prices and Volumes

The emergence of crypto currency as an alternative source of currency has been dubbed as one of the greatest phenomenon of the 21st century. Over the years, crypto currencies have grossly interrupted the traditional financial system and they continue to act as a catalyst for its revolution. However, cryptocurrencies have not been free from misery and controversies. The aim of this study is to explore and investigate empirically the impact of Covid-19 pandemic on price and volume dynamics in crypto markets. The study makes use of two data samples, but these samples are analyzed separately and independently. The first sample consists of Top Five Cryptocurrencies in terms of market capitalization (Bitcoin, Ethereum, XRP, Binance coin and Litecoin) as at 7 November 2020. The second one is made up of the Bottom Five Cryptocurrencies among the top 40 cryptocurrencies (FTX Token, Huobi Token, Filecoin, Dash and Decreed) as at 7 November 2020 again. The data among the Top Five Cryptocurrencies ranges from 2014 to 2021 and the data among the Bottom Five Cryptocurrencies ranges from 2018 to 2021.. The empirical results reveal that all crypto-currencies are integrated at order 1 i.e. I (1). The empirical analysis confirms presence of strong evidence for intra-and-inter long run relationship between price and volume dynamics within the crypto market irrespective of whether it is pre-pandemic or pandemic period. More so, there is convincing evidence from the results that much of the variance among the prices and volumes of the top five cryptocurrencies is attributed to the Bitcoin price-volume dynamics. This implies that it is critical for crypto market traders, investors and portfolio managers, before making any investment decision must consider the dynamics of price and trading volumes of BITCOIN as they hugely impact the prices and volumes of other altcoins.