Long-run Unidirectional Causality Research Articles

Connexion Between Cryptocurrencies Liquid and Futures Markets: Discernment from Static, Dynamic and Wavelet Approach

The knowledge of the interconnectedness between liquid and futures markets of cryptocurrencies amidst dynamic contemporary environment can be enriched through the full characterization of the direction, persistence and intensity of information flows between these markets. So, the present study attempts to investigate the static and dynamic connexions between liquid and futures markets of Bitcoin, Ethereum, Litecoin, Ripple XRP and Bitcoin Cash from June 2018 to June 2022. The connexion between their liquid and futures markets is first investigated using unconditional correlation, Johansen’s cointegration, vector error correction and Wald’s block exogeneity. Their estimates discern connexions encompassing significant long-run relationships between their liquid and futures markets; momentous unidirectional long-run causality from their futures market to liquid market; and momentous bidirectional short-run causality from their liquid market to futures market and from their futures market to liquid market. The present treatise encompasses methodological advancement in the investigation of interconnectedness between these markets by employing a dynamic conditional correlation model and a wavelet transform framework. Their discerned estimates indicate that the markets of Bitcoin, Litecoin, Ethereum and Bitcoin Cash have only momentous long-run perseverance, lingering and spillover effects of shocks’ sway on conditional correlations. However, there is momentous short- and long-run perseverance, lingering and spillover effects in the case of Ripple XRP. The wavelet coherence analysis also confirms these results by indicating a bidirectional short-run causal relation and a long-run positive comovement between liquid returns and futures returns of these cryptocurrencies. These discernments may help investors, portfolio managers and policymakers to enhance hedging effectiveness through optimal portfolio allocation and monitor financial contagion to attain and sustain financial stability in economies.

Determinants of the investments: a case study of Côte d Ivoire

Purpose- Based on the importance of investments in supporting the economic growth in the country, the main objective of this study is to investigate the determinants of the investment in Cote d’Ivoire over the period 1980-2020. In order to achieve the objective, this study examines the interactive effect of external debt, communication infrastructures, imports and inflation on the investments in Cote d’Ivoire. Methodology- Annual time series data over the period 1980-2020 were employed in this study. The data are obtained from the World Bank. The ADF unit root test, Johansen cointegration test, OLS model, Granger causality test, and CUSUM test were applied to analyze the data. Ordinary Least Squares (OLS) model has been used in this study to estimate the coefficient of the variables, and it has been subjected to a number of statistical diagnostic tests, namely, the normality, serial correlation, and heteroscedasticity tests to ascertain its statistical adequacy. Findings- The ADF unit root test results indicated that all variables in the model are not stationary at the level but became stationary after first differencing. The Cointegration test pointed to a significant long-run relationship among the variables. Besides, the results of OLS model showed that investment is positively and significantly related with communication infrastructures, importing and inflation, but it is related negatively and insignificantly with external debt. Imports have the biggest effect on the investment. The Granger causality test shows that there are no short-run causality relationships between the variables. However, there are bidirectional long-run causality relationships between investment, external debt and importing, and unidirectional long-run causality relationships running from communication infrastructures and inflation to investment. Lastly, CUSUM test indicated that there are no structural changes in the model. Conclusion- The study therefore recommends that the government should use external debt more efficiently, reduce corruption, improve the infrastructure and create an attractive investment climate, as well as reducing most tariff and nontariff barriers, which will support the investment in the country.

Aplicação da VECM para Medir o Impacto Econômico do Turismo em São Tomé e Príncipe Integrando Variáveis Macroeconômicas

This quantitative research aims to analyze the long-run relationship and causality between economic development, tourism, and other macroeconomic variables in the context of Sao Tome and Principe (STP). First, the Augmented Dickey and Fuller (ADF) and Phillips and Perron (PP) unit root test is applied, followed by the Johansen cointegration test and the Vector Error Correction Model (VECM). Gross domestic product (GDP), tourism receipts (TR), foreign direct investment (FDI), Unemployment rate (UR), and Inflation (INF) are the variables used in the econometric model from 1993 to 2019. The findings indicate a positive long-run relationship between GDP and the explanatory variables TR and FDI. It also indicates a negative long-run relationship between GDP and the variables INF and UR. In terms of short-run causality, the results reveal a unidirectional causality running from GDP to FDI and INF and bidirectional causality between TR and INF. Furthermore, it suggests a long-run unidirectional causality from all independent variables to GDP. This is the first quantitative study that presents a new perspective of tourism in the context of STP by applying the VECM and integrating several macroeconomic variables.

Aplicação da VECM para Medir o Impacto Econômico do Turismo em São Tomé e Príncipe Integrando Variáveis Macroeconômicas

This quantitative research aims to analyze the long-run relationship and causality between economic development, tourism, and other macroeconomic variables in the context of Sao Tome and Principe (STP). First, the Augmented Dickey and Fuller (ADF) and Phillips and Perron (PP) unit root test is applied, followed by the Johansen cointegration test and the Vector Error Correction Model (VECM). Gross domestic product (GDP), tourism receipts (TR), foreign direct investment (FDI), Unemployment rate (UR), and Inflation (INF) are the variables used in the econometric model from 1993 to 2019. The findings indicate a positive long-run relationship between GDP and the explanatory variables TR and FDI. It also indicates a negative long-run relationship between GDP and the variables INF and UR. In terms of short-run causality, the results reveal a unidirectional causality running from GDP to FDI and INF and bidirectional causality between TR and INF. Furthermore, it suggests a long-run unidirectional causality from all independent variables to GDP. This is the first quantitative study that presents a new perspective of tourism in the context of STP by applying the VECM and integrating several macroeconomic variables.

The Main Determinants of the Government Expenditure: A Case Study of Côte D’ivoire

Abstract Based on the importance of government expenditure in supporting economic growth in the country, the main objective of this study is to investigate the determinants of government expenditure in Cote d’Ivoire over the period 1980-2020. To achieve the objective, this study examines the effect of external debt, national income, inflation, and population on government expenditure, by using the ADF unit root test, Johansen cointegration test, Granger causality test, and CUSUM test. Results from the Johansen cointegration test indicated that there are long-run relationships among the variables. Government expenditure is positively related to external debt, national income, and population, but it is negatively related to inflation. The population has the biggest effect on government expenditure. The Granger causality test shows that there is a unidirectional short-run causality relationship running from external debt to government expenditure, but there is no evidence of any short-run causality relationship between national income, inflation, population, and government expenditure. On the other hand, there are bidirectional long-run causality relationships between inflation, population, and government expenditure, and unidirectional long-run causality relationships running from external debt and national income to government expenditure in Côte d’Ivoire. Lastly, the CUSUM test indicated that there are no structural changes in the model. The study recommends that the government should use government expenditure more efficiently in improving the infrastructure and creating an attractive investment climate, as well as upgrading the quality of human capital by improving the education system, health services, and the standard of living.

Assessing the role of ICT, governance, and infrastructure on inbound tourism demand in India

PurposeThe main purpose of the present research is to explore the possible effectiveness of information and communication technology (ICT), infrastructure development, exchange rate and governance on inbound tourism demand using time series data in India.Design/methodology/approachThe stationarity of the variables is checked by using the ADF, PP and KPSS unit root tests. The paper uses the Bayer-Hanck and auto-regressive distributed lag (ARDL) bounds testing approach to cointegration to examine the existence of long-run relationships; the error-correction mechanism for the short-run dynamics and the vector error correction method (VECM) to test the direction of causality.FindingsThe findings of the research indicate the presence of cointegration among the variables. Further, long-run results indicate infrastructure development, word-of-mouth and ICT have a positive and significant linkage with international tourist arrivals in India. However, ICT has a positive and significant effect on tourist arrivals in the short run as well. The VECM results indicate long-run unidirectional causality from infrastructure, ICT, governance and exchange rate to tourist arrivals.Research limitations/implicationsThis study implies that inbound tourism demand in India can be augmented by improving infrastructure, governance quality and ICT penetration. For an emerging country like India, this may have far-reaching implications for sustaining and improving tourism sector growth.Originality/valueThis paper is the first of its kind to empirically examine the impact of ICT, infrastructure and governance quality in India using modern econometric techniques. Inbound tourism demand research aids government and policymakers in developing effective public policies that would reposition India to gain from a highly competitive global tourism industry.

COVID-19 pandemic and the exchange rate movements: evidence from six major COVID-19 hot spots

The study’s primary objective is to unravel the nexus between the COVID-19 crisis and the exchange rate movements in the six major COVID-19 hot spots—Brazil, China, India, Italy, Turkey, and the United Kingdom. The impact of the COVID-19 deaths on the Rupee/USD, Pound/USD, Yuan/USD, Real/USD, Lira/USD, and Euro/USD exchange rates is analyzed by using the panel ARDL model. The COVID-19 deaths are used as a proxy for market expectations. The panel ARDL model showed a unidirectional long-run causality running from the COVID-19 deaths to the exchange rate. In fact, the coefficient of COVID-19 deaths is positive and significant in explaining the exchange rate(s) in the long run. This result meets the a-priori expectation that a rise in COVID-19 deaths can depreciate the sample countries’ exchange rates. The reason being, the ongoing COVID-19 pandemic has changed the market expectations of the financial market participants about the future value of exchange rate(s) in the major COVID-19 hot spots. Therefore, countries experiencing a sharp daily rise in COVID-19 deaths typically saw their currencies weaken.

Investigating the Interactive Role of Demand Side Factors Potentially Responsible for Energy Crisis in Pakistan

This paper attempts to investigate the dynamic relationship among Energy Consumption (E), Financial System Development (F), Industrailization (I), Agriculture Development (A) and Economic Growth (Y) in case of Pakistan for the period 1971-2018 by using cointegration approach. After confirming the level of stationarity, the presence of long run relationship among the series was tested through newly developed combined cointegration approach in addition to ARDL bound testing with structural break dummy. The short run and long run parameter coefficients were estimated by unrestricted error correction model (UECM) because all the series are found stationary at 1st difference I(1) and sufficient evidence of cointegration. Finally, the direction of causality among the considered variables was achieved through Granger causality test within the framework of VECM. The long run parameter coefficient estimates by UECM indicate that financial development, industrialization, economic growth and decrease in agricultural contribution to GDP induce electricity consumption in Pakistan. We also found that a long-run unidirectional causality is running from the economic growth to electricity consumption which favors the electricity conservation hypothesis in case of Pakistan. The causality running from the electricity consumption to agriculture output coupled with negative parameter coefficient value suggests that electric power deficit is responsible for hampering the agricultural growth in Pakistan. The study suggests that electricity conservation policy in addition to prudent rationing of electric power among the various sectors may greatly contribute to minimize the adverse effects of energy crisis in Pakistan.

Testing for the Bidirectional Relationship Between FDI in Services and Trade in Services: Evidence from Emerging Economies

We examine the two-way links between foreign direct investments (FDI) in services and trade in services for 26 emerging economies from 2003 to 2015 using sectoral and sectoral disaggregated FDI data. Within a multivariate framework, we use panel unit root tests, recently developed heterogeneous panel cointegration and panel vector error correction model (VECM). Our results confirmed the cointegrating relationship between trade in services, FDI in services, financial services FDI and nonfinancial services FDI. We find the existence of long-run unidirectional causality from trade in services to FDI in services. However, the disaggregated analysis shows a bidirectional link between nonfinancial services FDI and trade in services in the short run. Still, there is no causality between financial services FDI and trade in services both in the short run and long run. The result also shows the evidence of unidirectional causality running from trade in services to nonfinancial services FDI in the long run. It implies that sectoral decomposition matters in the FDI–trade nexus in emerging economies. JEL Codes: G20, F14, G20, F23

A Correlative Study of Modern Logistics Industry in Developing Economy and Carbon Emission Using ARDL: A Case of Pakistan

The modern logistics industry in relation to economic growth and carbon emission has opened new strategic perspectives. Recent research work have analyzed such complex interference from a broad perspective. However, analyzing this overlap needs comprehensive insight into the logistics industry while simultaneously estimating its short-run and long-run effects from regional aspects due to continue-evolving factors and their impact on it. This paper competently analyzes logistics industry components in connection with economic prosperity, energy consumption, trade development, and carbon emission from a more specific regional perspective of a developing country. Methodologically, an autoregressive distributive lag model (ARDL) is employed using correlative evaluation of the dynamic factors and their interactive impact in short and long run on this relation, based on time-series data of Pakistan from 1990 to 2019. The study results endorse the previous studies’ outcomes by recognizing that an increase in carbon emission depends on trade development, energy usage, economic development, and the logistics industry’s various components except for air logistics. However, study results show a unidirectional long-run causality directing from economic development, logistics industry, energy utilization, and trade development to carbon emission. Moreover, these results reveal that this emission is the leading factor to introduce stringent emission standards that further overlap with regional demographics trends, i.e., carbon emission implications. These findings imply that economic development applies a substantial demand-pull impact on national logistics, i.e., regional economic development directs to the growth of the logistics industry in the corresponding region. Consequently, high-income geographical regions have higher long-run risk concerning contemporary developmental activities of the logistics industry when adhering to carbon emission standards. Particularly, the influence of upcoming emission standards must be prioritized when planning the future returns of contemporary research and development activities of the logistics industry in a given geographic area, such as CPEC. Given Pakistan’s perspective, the proposed empirical analysis can be exampled to other developing countries. This analysis may facilitate the design and development of strategies for upcoming financial funding in the modern logistics industry to seek its sustainable development-goals in developing economies.

Empirical analysis of the relationship among urbanization, economic growth and ecological footprint: evidence from Eastern Europe.

In recent environmental sustainability literature, ecological footprint is largely seen as the most appropriate indicator of environmental destruction. However, due to lack of clarity in its relationship with economic growth, ecosystem services, biodiversity and human well-being, serious academic and political attention on environmental sustainability has not really reflected on ecological footprint. Using CADF unit root test, Westerlund cointegration test, common correlated effects and Dumitrescu Hurlin causality approaches, we conduct empirical analysis of the relationship among urbanization, economic growth and ecological footprint: evidence from Eastern Europe between 1998Q4 and 2017Q4. We address the following protracted questions in the literature: (1) Can we find a relationship between ecological footprint, urbanization and growth? (2) What explains the relationship, if any? The outcomes of the Westerlund cointegration test reveal cointegration among the variables, (ii) the outcome of the Dumitrescu Hurlin causality test indicates that there is a long-run unidirectional causality running from growth to the ecological footprint and (iii) urbanization does not homogeneously cause ecological footprint. The study has implications for regional policy actions that could support the reduction of ecological deficits through growth and urbanization policies towards improving regional environmental quality.

Does the Number of Hajj Pilgrims Boost Economic Growth in Saudi Arabia?

This paper uses the multivariate Johansen cointegration approach and Granger causality tests to study the causal relationship between the number of pilgrims and the non-oil GDP growth in Saudi Arabia over the period 1980–2016 by integrating the real effective exchange rate index as an additional variable. Our findings indicate that there is only one long-run relationship between the three variables when the non-oil GDP growth is the dependent variable. There is a unidirectional long-run causality from the number of pilgrims to non-oil GDP growth. Besides, we find no short-run causal relationships between the three variables. Therefore, an important policy implication resulting from this study is that pilgrims can be a led growth factor to economic growth in Saudi Arabia in the long run. The pilgrimage event can, therefore, be an excellent opportunity for Saudi Arabia to boost its economic activity as stated by its 2030 vision.

How Does Innovation Affect Economic Growth? Evidence from G20 Countries

We study the interactions between innovation and economic growth in G20 countries over 1961–2019. We establish whether there is a temporal causality between these two variables. Employing the autoregressive distributive lag framework, our results expose a grid of short-run and long-run causal relationships between innovation and growth, including long-run unidirectional causality from innovation to economic growth. Overall, our findings shed light on the real effects of innovation on economic growth. JEL Codes: O38, O31, O32

The effect of ICT development on innovation: evidence from G-20 countries

We study the interactions between information and communication technology (ICT) development and innovation in G-20 countries over 1961–2019. We establish whether there is temporal causality between these two variables. Employing the vector error correction modelling (VECM) framework, our findings render a grid of short-run and long-run causal relationships between ICT development and innovation, including long-run unidirectional causality from innovation to ICT development.

DYNAMIC EFFECTS OF MALAYSIA'S GOVERNMENT SPENDING ON ENVIRONMENT QUALITY: BRIDGING STIRPAT AND EKC HYPOTHESIS

This paper investigates how government spending (GSE) affects the environmental quality proxy by CO2 emissions in Malaysia over the 1978–2020 period. For that purpose, the STIRPAT model in the EKC framework are applied. The F-bounds test is applied to assess the cointegration relationship's existence. The ARDL model is used to measure the short-run and long-run environmental elasticities, and the VECM Granger causality is used to estimate the direction of the causality relationship. Empirical results show a cointegration relationship among environmental quality, GDP, population, and Malaysia's GSE. The findings provide strong support for Malaysia's EKC presence, and the GSE significantly contributes to reducing environmental sustainability. The results show the short-run unidirectional Granger causality running from CO2 emissions, GDP, and population to GSE at the 1 percent significance levels. Also, this study reveals the long-run unidirectional Granger causality running from CO2 emissions and population to GSE and GDP at least at 10 percent significance level; and the bidirectional causality between GSE and GDP at least at 10 percent significance level as well. The result implies that the increasing demand for regulatory and protective functions represented by GSE are needed to sustain the increasing level of economic wealth, environment, and communities.Keywords: Environmental Sustainability, EKC, Government Spending, Dynamic Relationship, Causality, MalaysiaJEL Classifications: O1, O2, Q5DOI: https://doi.org/10.32479/ijeep.11273

Stock Market Development and Economic Growth: Empirical Evidence from Nepal

This study examines the relationship between stock market development and economic growth in Nepal by employing autoregressive distributed lag (ARDL) model with bound testing procedures. The study period covers annual time series data from 1994 to 2019. Indicators of the stock market development used are size, depth and efficiency represented by market capitalization as a percentage of gross domestic product (GDP), total value of shares traded as a percentage of GDP and total shares traded as a percentage of market capitalization, respectively. Following high correlations among these indicators, an aggregated index is constructed and used in the study. Real GDP per capita growth is taken as an economic growth indicator. The results suggest that there exists a long-run uni-directional causality relationship running from stock market development index to economic growth. Stock market size and liquidity are significant contributors, showing that stock market is able to mobilize capital and diversify risks with increased easiness in trading of stocks. The control variable market inflation shows no significant impact on either of the examined primary variables.

Energy consumption, tourism, economic growth and CO2 emissions nexus in India

India is one of the fastest growing nations in the world with ample scope for renewable energy. Nevertheless, challenges in expansion of renewable energy consumption have resulted in pollutant emissions continuing to be a noteworthy environmental concern in India. This paper investigates the relationship between energy consumption, CO2 emissions, Gross Domestic Product (GDP), and international tourist arrivals in India during 1991-2018, using the Autoregressive Distributed Lag and Vector Error Correction Model frameworks. This study extends the Indian literature on economic growth, energy consumption, and pollutant emissions nexus by including tourism, an energy-intensive industry in the model specification. Results reveal that energy consumption and tourism positively contribute to CO2 emissions. A long-run unidirectional causality running from energy consumption, GDP, GDP2, and tourist arrivals towards CO2 emissions is observed. Our results suggest that sustainable tourism, energy consumption, and economic growth should be at the forefront of the economic development agenda of India.

Long-Run Nexus of Tourism and Economic Growth in Sri Lanka: Empirical Evidence Using Cointegration Analysis

This study investigates the association between economic growth and tourism in Sri Lanka using cointegration analysis for the period 1980 to 2019. The analysis was performed using the Augmented Dickey-Fuller test, Phillips-Perron test, Engle-Granger cointegration, and Granger causality tests. The results revealed a long-run equilibrium relationship among variables while there is a disequilibrium in the short run. The estimated error correction term is theoretically acceptable and approximately 5 per cent yearly correction of its disequilibrium in the short run was found. Granger causality test presented a long-run unidirectional causality which is running from tourism to economic growth and thus findings confirm the tourism-led growth hypothesis in Sri Lanka tourism and development spectrum. Therefore, tourism has a significant positive impact on economic activities in the long run. Findings further emphasize that benefits of the economic development must be transferred to the further development of tourism to maintain a bilateral causality which is an important concept in this regard. It provides the rationale for the further development of productive policy strategies to attract more tourists to the country and upsurge visitor expenditures during their stay in Sri Lanka since Sri Lanka has significantly developed its accommodation capacities. Findings further reveal that the tourism sector must be developed parallel to the economic development to boost the growth through tourism. Therefore, all sectors, the government, private bodies, and voluntary organizations must become active partners in this endeavour, and policy implications need the focus of every aspect of enhancing tourism as a growth engine.

Examining the Impact of Coronavirus on Stock Markets: Investigating the Cointegration and Transmission of Shocks between China and World Largest Stock Markets

This study's focal point is to access the financial aspects of coronavirus on China and the world's largest stock markets by analysing the cointegration and the transmission of shocks from the Chinese stock market to the whole world. This study employs unit root test, Johansen cointegration test, vector error correction model, Granger causality test, variance decomposition and impulse response function test, to find the long-run and short-run relationship and transmission of shocks for the period from January 2012 to March 2020. Findings of the study observe the long-run relationship between stock markets. The short-run results reveal that the previous day's stock prices of Hong Kong and the US stock market show a positive relationship with China stock market. Granger causality results show only unidirectional long-run causality running from the UK, Hong Kong and Japan. Short-run causality results indicate the bidirectional causality among China and other major stock markets.

Growth in Foreign Trade in Liberalized India: The Relevance of FDI

Driven by the need of an economic model that can explain the foreign direct investment (FDI)–export relationship, especially in post-liberalized context, we make a special inquiry on whether FDI has a significant export-promoting impact in India under a time-varying parameter model with vector autoregressive specification. The Johansen’s co-integration test suggests a significant and positive long-run co-movement between FDI and export. The vector error correction model (VECM) confirms a unidirectional long-run causality from export to FDI. However, the Granger causality test establishes a bi-directional causal relationship between these variables in short run. Further, the foreign trade (FT) is found to be a strongly exogenous variable as per the variance decomposition analysis. Again, the impulse response function analysis suggests that the responses generated from a positive shock of FT to FDI and vice versa are small and initially negative, afterward remain steadily positive at a constant level. The study finally recommends the policymakers to channelize the inward-FDI into tradable goods industries rather than only linking it to service sector growth to reap the long-term benefit. In this regard, China’s effort to channelize inward-FDI into manufacturing sectors and the resultant momentous success in export performance can be taken as a classic example for FDI-led foreign trade promotion.