Short-run Association Research Articles

The Relationship between Geopolitical Events and the Crude Oil Prices: An Application of ARDL Model

This paper aims to explore the short-run and long-run relationship between geopolitical events and crude oil prices for the period 2000-2023. In addition to geopolitical events, we included the market factors whose data were available in the right part of the equation. To investigate long-run cointegration, this paper used quarterly data and employed the Autoregressive distributed lagged (ARDL) bounds testing approach developed by (Pesaran et al., 2001). Study findings from the ARDL bound testing approach confirm the existence of a long-run and short-run association between geopolitical events and crude oil prices. Furthermore, the findings from the ARDL model revealed that, among others, world crude oil production; OECD’s crude oil stocks, and OECD economic growth have a significant effect on the dependent variable (crude oil prices) both in the long run and short run.

The Association between Credit Risk Management and Banks’ Performance in Bangladesh: A Panel ARDL Approach

This paper aims to empirically investigate both the long-run and short-run association between credit risk management and commercial banks’ performance of Bangladesh by employing a panel data collected from 23 Dhaka Stock Exchange (DSE) listed conventional commercial banks over a period of 13 years spanning from 2008-2020. The study incorporates capital adequacy ratio (CAR), non-performing loan ratio (NPLR), and geographical loan concentration ratio (GLCR) as the indicators of credit risk management, while considering return on asset (ROA) as the performance measure. The results indicate that there is a significant positive long run as well as short-run relationship between CAR and ROA. In addition, the study reveals a short-run negative relationship between NPLR and ROA. The study suggests that commercial banks may maintain sufficient capital to absorb any substantial loan loss without collecting any emergency funds.

An Empirical Analysis of Short Run and Long Run Association between Debt Servicing and External Debt in Pakistan

Pakistan is at a crucial juncture where the escalating debt servicing cost of Rs 7.3 trillion is set to consume the majority of the projected revenue of Rs 9.2 trillion, which includes Rs 5.2 trillion allocated to the provinces. This study explores the interaction between debt servicing and external debt stock in Pakistan. It analyzes the impact of variables such as the debt service ratio, fiscal deficit, exchange rate, and globalization on external debt stock, using annual data from 1990 to 2020 obtained from the World Development Indicators (WDI) and the Pakistan Economic Survey. The stationarity of the variables is tested using the Augmented Dickey-Fuller (ADF) test. The Auto-regressive Distributed Lag (ARDL) bound test is utilized to investigate the long-term relationship among the endogenous and exogenous variables, and the Error Correction Model (ECM) is applied to study short-term dynamics. The findings indicate a negative long-term relationship between debt service and external debt, while fiscal deficit, exchange rate, and globalization show significant positive correlations with foreign debt. The study provides policy recommendations to alleviate the external debt burden.

Linkage between Crude Oil, Gold, INR-USD Reference Rate and Sensex amidst Covid-19 Pandemic: A Cointegration and Causality Analysis

The primary purpose of this paper is to analyse the shortrun and long-run association between crude oil prices, gold prices, USD-INR reference rate, and stock market index across the COVID-19 pandemic. We have employed Johansen's cointegration test to measure the long-run association among the variables. To measure the short-run association of variables, we employed vector autoregression, and then, to find the direction of causality, we used the Granger causality test. The cointegration test results show that variables are not cointegrated in the precrisis as well as during the crisis period; hence, there is no long-run association among the variables. The VAR results show that gold price was influenced by the stock market index in the pre-crisis era; however, during the crisis, no association was observed. Similar results can also be found in crude oil, USD-INR reference rate, gold price, and stock market. The results also show that the relationships among the variables are dynamic and ever-changing in the preCOVID and during the COVID-19 pandemic.

Impact of human capital and natural resources on environmental quality in South Asia

AbstractThis study examines the importance of human capital and natural resources on environmental quality in South Asia by using panel data that ranges from 1975 to 2021. Advanced cointegration approaches establish the long-term linkages between human capital, natural resources, economic growth, economic growth squared, urban population, industrial value added, and ecological footprint. To explore the long and short-run association among these variables, this study applied the panel autoregressive distributed lags (ARDL) model. The outcome designates that human capital has a negative and significant alliance with environmental quality, whereas economic growth and economic growth square affect environmental quality positively and negatively, confirming the existence of the environmental Kuznets curve (EKC) hypothesis. Urban population growth and natural resources have significant negative associations with environmental pollution, whereas industrial value added increases the pollution levels in South Asia. Lastly, the outcome of the interaction between human capital and natural resource rent on the ecological footprint has a significant positive effect. This study recommends that South Asian nations improve their human capital to promote industrial modernization, expansion of green technology, and energy-efficient habits. Utilizing natural resources also helps South Asian nations maintain a clean ecosystem. Additionally, South Asian nations ought to vigilantly track the negative consequences of industrialization on the atmosphere. Thus, ecological sustainability requires human capital and natural resources.

THE EFFECT OF CRUDE OIL PRICE VOLATILITY ON INFLATION IN INDIA: EVIDENCE FROM ARDL APPROACH

India has been experiencing the issue of rising crude oil prices since 2017, after a low-price regime from 2014 to 2017. Inflation was also moderate during the low-crude oil price regime. It has been empirically seen that a rise in crude oil prices exerts a significant impact on the inflationary situation of the nation. Rising oil prices and their spillover into higher general price levels might exacerbate the crisis in a nation that is already struggling with the declining demand for investment and consumption. The domestic oil price needs to be controlled by the government to boost demand while controlling inflation without putting further stress on the populace. Against this background, the present research aims to investigate the relationship between the crude oil price and the inflation rate in the nation using the data from 1991 to 2020 (before Covid years). This paper also aims to investigate the effect of crude oil prices and inflation on economic growth in India. The paper has used an Autoregressive Distributed lag model to investigate the long-run and short-run association between them. Our analysis shows that the prices of crude oil have a statistically significant impact on India’s inflation rate over the long and short terms. KEYWORDS: Inflation, Crude oil price, India, Spillover, ARDL, Granger Causality, GDP

IMPACT OF GLOBAL ECONOMIC FACTORS WITH FOREIGN INVESTMENTS ON INDIAN ECONOMIC DEVELOPMENT- AN EVENT STUDY

Purpose: The present stage of economic development is the basis for this empirical inquiry, which shows that foreign direct investment (FDI) significantly affects the destination countrys steady, high-quality, and healthy economic growth. To attract more international investment, every country experiencing economic globalisation is working to provide a favourable climate for businesses. Design/Methodology/Approach: I gathered five global institutional metrics global inflation, global gross domestic product, global production manager index, dollar index, and global equity index from the DPIIT websites secondary data for the years 2013-2023. These metrics form the basis of my studys primary objective. We are Using stalactitical tools like Unit root Test, ARDL Approach & OLS Model. Originality/Value: The researchers in this study used OLS (Least Squares) regression: Institutional variables effects on FDI flows were the focus of this research. To determine the effect of institutional characteristics (independent variables) on foreign direct investment (FDI) flows (dependent variable), this research used the ordinary least square approach. Findings: The study found with the help of ARDL model that the Institutional indicators had are having the positive coefficient value and stated that Global Economic Metrics which shown short run association with FDI flows, Time constraints, geographical constraints, or the inaccessibility of necessary data from appropriate sources are all obstacles that any research project must overcome. KEYWORDS: FDI, Global Metrics, Economy Growth, OLS Model.

The Bound Test Approach of the Money Demand Determinants in Nepal

The theory of money demand is an empirically tested theory of Nepal. It aimed at estimating the money demand function in Nepal. The causal research designs were used for the study. An annual time series from 1980/81 to 2021/22 was used as the data. The research used the Bound test and Auto-regressive Distributive lag model (ARDL). Moreover, a unit root test, bound test, stability diagnostic test, and normality test were used. The empirical result indicates the existence of both short-run and long-run relationships between money demand and real gross domestic production. Furthermore, money demand has a good short-run association with inflation and the consumer price index, whereas it has a long-run relationship. The disequilibrium is corrected in the one log period with a speed of adjustment of 0.75 percent. The study concludes an association between broad money supply and real gross domestic production in Nepal exists.

Exploring the Influence Dynamism of Economic Factors on Fluctuation of Exchange Rate - An Empirical Investigation for India Using ARDL Model

The Indian Foreign Exchange Market has experienced significant changes over the past decade, due to high degree of instability of the Indian Rupee leading to its devaluation against major global currencies. Exchange rate is considered as one of crucial indicators to determine the economic growth. Volatility of exchange rate of each day is influenced by various factors such as demand and supply, Gross Domestic Product, Interest rate, employment rate, public debt, balance of payments, inflation etc. Though there are multiple causes to determine the movement of exchange rate, but still the accurate level of causation is unpredictable. Keeping this in mind, this paper tries to attempt the relationship that exists between the exchange rate and select macroeconomic factors. To analyse the extent of influence of the selected variables on the exchange rate, the research paper uses 10 years of data spanning from Jan 2013 to Nov 2022. Further, the study uses monthly data of above-mentioned variables to bring out the analysis to meet the objectives. Descriptive statistics is used to find the characteristics of the data, correlation analysis and Ordinary Least Square method is used to find the relationship and impact level select macroeconomic factors on exchange rate. Autoregressive Distributed Lag (ARDL) model is used to find if any short run and long run association exists between the variables and the exchange rate.

Impact of Retail Payments’ Digitalization on Indian Economy: A Critical Appraisal

Technological innovations in the Indian banking sector brought tremendous change in the way banking transactions are carried out by firms and individuals. Besides the benefits like convenience, speed and, access, events such as demonetization and covid outbreak fuelled the growth of online banking transactions even more in India. Based on the payment statistics in 2020, the share of instant payments and other electronic payments accounted for nearly two-fifth of all payments and it is estimated to grow to 71.7% by the end of 2025. The present study aimed at analysing the impact of digital payments on Indian economic growth based on the quarterly observations during the period FY 2015-16 to FY 2020-21. The results showed the existence of a long-run association and a short-run association between Gross Domestic Product (GDP) and retail digital payments.

Linkage of Non-Fungible (NFT) Tokens to Measures of Uncertainty: Does Fear Bode Well for NFT Holders?

The study investigates the relationship between the returns of Non-Fungible Tokens (NFT) and its categories; and fear indices during times of crisis. The fear indices considered are Global Fear Index (GFI), Global Economic Policy Uncertainty Index (GEPU), Twitter based Economic Uncertainty Index (TEU), Global Consumer Confidence Index (CCI), Infectious Diseases Equity Market Volatility Index (IDEMV) and Crypto Volatility Index (CVI). Employing Granger Causality Test, Autoregressive Distributed Lag technique and ARDL Bounds test on data for the period starting 1st February 2020 and ending 28th February 2022, it is found that short run association exists between TEU, CVI and NFT returns. Further, GFI leads NFT Art returns while TEU leads NFT Metaverse returns by lag 5 and lag 2 respectively. No association between fear metrics and NFT Collectible, NFT Game and NFT utility is observed. No long run association in found between NFT returns and fear indices except TEU which influences NFT returns. It is concluded that NFT, NFT Art and NFT Metaverse returns have positive association to at least one fear index during times of turmoil, especially for the short run.

A pathway to a sustainable future: Investigating the contribution of technological innovations, clean energy, and Women's empowerment in mitigating global environmental challenges

This study aims to provide insights into the pathway toward a sustainable future by investigating the factors contributing to environmental sustainability. In this pursuit, the current study empirically analyzes the role of economic growth, technological innovation, clean energy consumption, and women empowerment toward global environmental quality from 1991 to 2015. For empirical analysis, autoregressive distributive lag and fourier frequency domain causality models are employed to test the long-medium and short-run association between the selected variables. Fully modified ordinary least squares and canonical cointegration regression estimations are also applied for robustness. The empirics of this study reveal that economic growth deteriorates the environmental quality in the long and short run. However, technological innovation, clean energy consumption, and women's empowerment help improve environmental quality in the long and short run. In addition, the robust analysis also authenticates the long-run outcomes of the study. This study suggests policy recommendations aimed at a sustainable future by establishing strong regulatory policy instruments, enforcing environmental laws, promoting energy-efficient technologies in industries and households, implementing women's employment protection policies, and strong regulatory policy instruments to achieve emission reduction in the global perspective.

A nexus between sustainability, energy utilisation and economic growth at aggregate and disaggregate level: a case of India

PurposeThe growth of the Indian economy is accompanied by the rising trend of energy utilisation and its devastating effect on the environment. It is vital to understand the nexus between energy utilisation, climate and environment degradation and growth to devise a constructive policy framework for achieving the goal of sustainable growth. This study aims to analyse the long- and short-run association and direction of association between energy utilisation, carbon emission and growth of the Indian economy in the presence of structural break.Design/methodology/approachThe study probes the association and direction of association between variables at both aggregate (total energy utilisation, total carbon emission and gross domestic product [GDP]) and disaggregates level (coal utilisation and coal emission, oil utilisation and oil emission, natural gas utilisation and natural gas emission along with GDP) over the time period of 50 years, i.e. 1971–2020. Autoregressive distributed lag model is used to examine the association between the variables and presence of structural break is confirmed with the help of Zivot–Andrews unit root test. To check the direction of association, vector error correction model Granger causality is performed.FindingsAggregate carbon emissions are affected positively by aggregate energy consumption and GDP in both short and long run. Bidirectional causality exists between total emissions and GDP, whereas a unidirectional causality runs from energy consumption towards carbon emission and GDP in the long run. At disaggregate level, consumption of coal energy impacts positively, whereas GDP influences coal emission negatively in the long run only. Furthermore, consumption of oil and GDP influences oil emissions positively in the long run. Lastly, natural gas is the energy source that has the fewest emissions in both short and long run.Originality/valueThere is a rapidly growing body of research on the connections and cause-and-effect relationships between energy use, economic growth and carbon emissions, but it has not conclusively proved how important the presence of structural breaks or changes within the economy is in shaping the outcomes of the aforementioned variables, especially when focusing on the Indian economy. By including the impact of structural break on the association between energy use, carbon emission and growth, where energy use and carbon emission are evaluated at both aggregate and disaggregate level, the current study aims to fill this gap in Indian literature.

The Impact of Policy Interventions on Systemic Risk across Banks

What is the impact of policy interventions on the systemic risk of banks? To answer this question, we analyze a comprehensive sample that combines an original set of bank-specific bailout events with the balance sheets of key affected and nonaffected European banks between 2005 and 2014. We find a positive and significant association of guarantees with systemic risk that is somewhat weaker in the long run when the regulator appoints members to the supervisory board. The short run association between recapitalizations and systemic risk is also positive for large and less capitalized banks, while in the long run, recapitalizations are linked with reduced systemic importance, especially for less profitable banks and in cases when the regulator limits management pay. Liquidity injections are positively linked with systemic risk, but the long-run effect is mitigated for small or better capitalized banks. In the short run, injecting liquidity is associated with reduced systemic risk when the regulator imposes restrictions on supervisory board composition or on management pay or capital payouts.

Macroeconomic Indicators of Economic Growth using Panel Data: A Study from South Asian Countries

Economic development is a most imperative element in figuring out the well-being of the citizens in a country. The present study analyzes the effect of key macroeconomic indicators on the Economic development of South Asian countries. The study intends to scrutinize the long-run and short-run association between Economic development and several macroeconomic variables by using panel data analysis. During ultimate 10 years, a few South Asian countries (SA) had economic instability. The study is aimed to investigate the macroeconomic indicators of some selected SA countries’ economic growth. The static linear panel statistics model had been used for figuring out the consequences of unbiased macroeconomic variables on the gross domestic product (GDP) of SA member countries including Bangladesh, India, Pakistan, and Nepal. While explained variable of examines is analysis is gross domestic product (quantity), the unbiased variables are current account balance general government gross debt, general government revenue, general government total expenditure, inflation (average consumer prices), population, the volume of exports of goods and services, volume of imports of goods and services. The analysis proposed is grounded on a panel data (cross-sectional time series data) approach. The data set of this exploration involves four SA members among 9 countries (cross-sectional units). The effects of 8 macroeconomic indicators on gross domestic product volume were examined. The paper also empirically analyzes the (negative impacts of the global financial crisis) on four SA countries’ economic growth during the 1980 – 2020 periods (time series). In this environment, the goods of macroeconomic parameters are anatomized using panel data series. The main findings of this model indicate that the level of population, general government revenue, inflation (average consumer prices), and volume of exports of goods and services, positively affects economic growth. The findings of this paper will be used for increasing the economic growth of south Asian countries.

Macroeconomic Indicators of Economic Growth using Panel Data: A Study from South Asian Countries

Economic development is a most imperative element in figuring out the well-being of the citizens in a country. The present study analyzes the effect of key macroeconomic indicators on the Economic development of South Asian countries. The study intends to scrutinize the long-run and short-run association between Economic development and several macroeconomic variables by using panel data analysis. During ultimate 10 years, a few South Asian countries (SA) had economic instability. The study is aimed to investigate the macroeconomic indicators of some selected SA countries’ economic growth. The static linear panel statistics model had been used for figuring out the consequences of unbiased macroeconomic variables on the gross domestic product (GDP) of SA member countries including Bangladesh, India, Pakistan, and Nepal. While explained variable of examines is analysis is gross domestic product (quantity), the unbiased variables are current account balance general government gross debt, general government revenue, general government total expenditure, inflation (average consumer prices), population, the volume of exports of goods and services, volume of imports of goods and services. The analysis proposed is grounded on a panel data (cross-sectional time series data) approach. The data set of this exploration involves four SA members among 9 countries (cross-sectional units). The effects of 8 macroeconomic indicators on gross domestic product volume were examined. The paper also empirically analyzes the (negative impacts of the global financial crisis) on four SA countries’ economic growth during the 1980 – 2020 periods (time series). In this environment, the goods of macroeconomic parameters are anatomized using panel data series. The main findings of this model indicate that the level of population, general government revenue, inflation (average consumer prices), and volume of exports of goods and services, positively affects economic growth. The findings of this paper will be used for increasing the economic growth of south Asian countries.

Impact of Petroleum Energy Price Volatility on Commodity Prices in Ghana

The purpose of this article is to demonstrate the relationship between petroleum energy volatility and commodity prices in Ghana, which are indexed (energy grains, meat, and cooking oil), as well as to provide an empirical specification of the impact's direction. With reference to time series literature, the paper examined energy and commodity price connection models such as augmented dickey fuller, granger causality, co-integration, vector autoregressive and the vector error correction models used in estimating the association among petroleum energy volatility and the three selected commodity variables. The paper found that, there is a long run relationship between petroleum energy volatility and commodity prices in Ghana from 2011 to 2022. A single equation error correction model suggested that, petroleum energy shocks increase prices of grains, meat and cooking oil in both the short and long run. Impulse response function and variance decomposition conducted on the variables also suggested that there is both short and long run association between the variables.

Defining the role of renewable energy, economic growth, globalization, energy consumption, and population growth on PM2.5 concentration: evidence from South Asian countries.

Rapid industrialization and economic development in South Asia (SA) caused serious air pollution-related issues. Air pollutants, particularly fine particulate matter (PM2.5), have negative effects on health, instigating widespread concern. The current study is an attempt to analyze the impact of non-renewable energy (NRE), globalization (GLO), GDP, renewable energy (RE), and population (POP) on PM2.5 concentration in SA from 1998 to 2020. In doing so, this study incorporated advanced and robust econometric techniques, i.e., Pesaran (Economet Rev 34(6-10), 1089-1117, 2015), to check the cross-sectional dependency, and the unit root presence checked through Cross-sectional Im, Pesaran, and Shin (CIPS) and Cross-sectionally Augmented Dickey-Fuller (CADF) unit root tests. Moreover, the long and short-run association among the selected variables was analyzed through Westerlund and Edgerton (Econ Lett 97(3), 185-190, 2007), cointegration test, and cross-sectional augmented ARDL (CS-ARDL). The empirical results indicate that the panel was cross-sectionally correlated, stationary at the first difference, and co-integrated in the long run. Moreover, the CS-ARDL model indicates a positive association between GDP and PM2.5 concentration. Similarly, NRE and POP contribute significantly to increasing the PM2.5 concentration in SA. However, RE and GLO play an important role to decrease the PM2.5 concentration in SA.

ECONOMICS IS NOTHING WITHOUT THE IMPACT OF MACROECONOMIC DETERMINANTS ON ECONOMY OF PAKISTAN

This research aims to find the impact of Macroeconomic Variables on Economic Growth of Pakistan. The study helps to understand the implications of Personal Remittances, Inflation Deflator, Electric Consumption, Foreign Direct Investment, Imports, Mineral Resources, GDP Per Capita, Gross Capital Formation, Domestic Credit to Private Investment, Real Effective Exchange Rate, and Broad Money on the Gross Domestic Product of Pakistan. The 51 years of time series data is taken from 1971 to 2021 which is collected from the website of State Bank of Pakistan, International Financial Statistics and from World Development Bank Indicators for the years 2021-2022. The model is tested by using Ordinary least square. All the variables are significant. R2 is 0.98 which shows that selected independent variables are explaining the variation in dependent variable with the highest percentage. F-Statistics confirms the overall goodness of fit of the model. Stationarity level of the data is analyzed by Augmented Dickey-Fuller (ADF) test. Durbin Watson is 2.0, which is an indication of no autocorrelation. Descriptive Statistics are calculated to see the probability of Jarque Berra. To check the Normality Histogram is drawn. Stability of the model, serial correlation, heteroscedasticity, Normality and Structural Stability diagnostic tests have been applied on the data. LM Test, Ramsey Reset Test, Breusch-Pagan-Godfrey test, Correlation, Covariance Matrix, Correlogram, forecast model, CUSUM and CUSUM SQ and recursive stability graph has been tested to fulfill the conditions of time series analysis. Co-integration test has shown that there is long run association between variants.Another test to see the short run association between change ables show that there is neither one way nor two way causality among them..The findings are that macroeconomic variables Broad Money, Gross Capital Formation in $, Minerals and GDPPC$ have positive significant relationship with is significant relationship with GDP and their respective t-values are 3.6808, 10.99676, 3.55973, 3.0824338 and 2.7287. Imports, Foreign Direct Investment, Electric Consumption and Direct Credit on Private Investment have significant negative relationship with Economic Growth of Pakistan. Their respective t – values are -3.10085, -2.72875, -2.61744 and -6.15435. Personal Remittances, Exchange Rate and Inflation Deflator have insignificant relationship with GDP and their respective t-values 0.809843, 1.062302 and -0.10167.Government should ensure peaceful environment for foreigners to invest in Pakistan. The law-and-order situation, political unrest, high rate of unemployment, increase in prices, devaluation of currency and widening energy crisis needs to be handled from individual level to aggregate level. Keywords: Remittances, Foreign Direct Investment, Gross Domestic Product, Exchange Rate, ADF, ARD.

Analyzing the factors contribute to achieving sustainable development goals in Pakistan: A novel policy framework

Pakistan is in a terrifying and devastating energy crisis. Recently, the prediction for energy consumption has intensified compared to its production capacity, which is problematic for Pakistan's social and economic stability. Hence, it is vital to examine the link between power consumption, power prices, urban transition, other electricity use, and economic expansion from 1970 to 2018 in Pakistan. For analysis, the second-generation econometric technique of Lee and Strazicich (2013), novel Augmented Autoregressive Distributed Lag (AARDL), and Frequency Domain Causality (FDC) is useful to detect the long-medium and short-run association among the variables. The results show that power consumption stimulates economic expansion in the short and long-run, though the rise in power prices declines economic activity in the short and long-run. Also, urban transition and other electricity use are a substantial positive and negative impact on economic expansion in the short and long-run. The outcome suggests that efficient energy supply, low-cost power prices, proper urban transition management, and other energy use could be useful for policymakers to achieve SDGs 7 and 11 in Pakistan.