Negative Long-run Relationship Research Articles

The influence of climate change on the sesame yield in North Gondar, North Ethiopia: Application Autoregressive Distributed Lag (ARDL) time series model

Sesame is a major annual oil crop that is grown practically everywhere in tropical and subtropical Asia, as well as Africa, for its very nutritious and tasty seeds. Rising temperatures, droughts, floods, desertification, and weather all have a significant impact on agricultural production, particularly in developing countries like Ethiopia. Therefore, the main objective of this study is to examine the influence of climate change on the sesame yield in North Gondar, North Ethiopia, by using the autoregressive distributed Lag (ARDL) time series model. This study employed climate data from the Bahirdar Agrometeorological Center and secondary data on sesame production from the Ethiopian Statistical Service, spanning 36 years, from 1987 to 2023. Autoregressive Distributed LAG (ARDL) includes diagnostic tests for both short- and long-term autoregressive models. The results for the long-run and short-run elastic coefficients show a significant positive association between temperatures and sesame yield. Sesame yield and rainfall have a significant negative long-run and short-run relationship in North Gondar, North Ethiopia. ARDL results confirm that temperature and rainfall have significant effects on sesame productivity. Temperature had a considerable favorable effect on sesamen production, but rainfall had a negative effect in North Gondar, Ethiopia. Based on the evidence acquired from our study, we made several policy recommendations and suggestions to government officials, policymakers, new technologies, researchers, policy development planners, and other stakeholders in order to develop or implement new technology to halt its production and direct adaptation measures in light of the certainty of global warming and the characteristics of climate-dependent agricultural production.

The relationship between foreign direct investment and trade openness: Evidence from six developed economies

Abstract Subject and purpose of work In recent years, the competition for economic dominance globally has led developed economies increasingly to focus on outward foreign direct investment (FDI) and exports to other developing nations. However, there has been a notable research gap, with most studies concentrating on assessing the significance of FDI and trade openness in developing countries, while less attention has been paid to developed countries. This study explores the relationship between FDI and trade openness with economic growth in six developed economies. Material and methods Utilising annual data spanning from 1990 to 2022 from the World Bank, the study employs the panel Autoregressive Distributed Lag (ARDL) method for analysis. Results The estimated results indicate a negative long-run relationship and a positive short-run effect of FDI in the selected economies. Furthermore, the findings reveal a positive long-run association and a negative short-run impact of trade openness. The causality test indicated a bidirectional relationship between trade openness and economic growth. Conclusions The study suggests that various governments should enhance their investment environments to leverage the benefits of FDI inflows.

The Impact of Remittances on Renewable and Non-renewable Energy Consumption in Jamaica

Using annual data from 1980 to 2019, we explore the impact of remittance inflows (remittances) on renewable and non-renewable energy consumption in Jamaica. We apply statistically adequate vector error correction and vector autoregression models. There are two primary findings. First, we find that an increase in remittances is associated with a decrease in renewable energy consumption within an error correction model, which suggests a long-run negative relationship between remittances and renewable energy consumption. Second, an increase in remittances is associated with an increase in non-renewable energy consumption in the short run; no cointegrating relationship is detected. One implication of our finding is that Jamaica could strengthen policies that encourage the consumption of renewables while discouraging the consumption of non-renewables. These policies should apply to not only remittance-receiving households but also energy consumers in general to enhance the uptake of renewable energy.

Impact of Technological Innovations on Bank Performance in Selected West African Countries (1997-2020)

Purpose: Technological innovations are understood as new or improved processes, products or services, the technical characteristics of which are significantly different from the previous ones. Technological innovations in the banking sector have undoubtedly improved the functionality and performance of banks across the globe including West African countries such as Nigeria, Ghana and Coted’Ivoire. It has redefined the way and regime in banking operation in West Africa. It enables banks to improve the quality of service delivery to their numerous customers and makes it easy for customers to access banking services at the lowest cost possible. This study, therefore, focused on examining the impact of technological innovations on bank performance in West Africa. Method: A set of annual time series covering the period 1997 to 2020 and a multiple regression analysis including an autoregressive distributed lag (ARDL) model, a fully modified OLS (FMOLS) model and a dynamic OLS (DOLS) model were used. Bank performance was measured using bank return on assets (ROA) and bank return on equity (ROE), while technological innovation was measured using indicators such as Internet Banking (INB), Automated Teller Machines (ATM), Mobile Banking (MBN) and Point of Sale (POS) whose control variables are inflation rate (INFR) and exchange rate (EXR). Results and conclusion: Findings from the ARDL panel results show that both positive and negative long-term relationships exist between technological innovation and bank performance in West Africa. We thoroughly verified the results from the ARDL model with FMOLS and DOLS and the findings show that technological innovation has a positive and negative long-run relationship with bank performance in West Africa and the results were the same for Nigeria, Ghana and Ivory Coast. Originality/Value: This study, therefore, recommends that improving the quality of technologically innovative tools of banks such as internet banking, ATMs, POS and mobile banking with quality apparatus can lead to improved bank performance. Banks should also invest in cyber security to ensure funds deposited in banks are safe which will boost investor and customer confidence, acceptance and lead to increased bank performance.

The Causal Relation between Energy Consumption, Carbon Dioxide Emissions, and Macroeconomic Variables in Somalia

This study investigated the relationship between energy consumption, carbon dioxide emissions, and macroeconomic variables in Somalia with data spanning from 1990 to 2019 using ARDL model. The study found a negative long-run relationship between carbon dioxide emissions and energy consumption in Somalia, suggesting that improving access to clean energy can reduce the gradual rise of carbon dioxide emissions. The study also found that rising industrial value-added had a significant positive impact on energy consumption. Furthermore, findings from Cholesky's variance decomposition showed that 13.13% of future fluctuations in energy consumption are due to shocks in carbon dioxide emission, 33.63% of future fluctuations in carbon dioxide emissions are due to shocks in energy consumption, 40.63% of future fluctuations in industrialization are due to shocks in energy consumption and 41.23% of future fluctuations in population are due to shocks in energy consumption. There was evidence of a bidirectional causality between: energy consumption and population. The study suggests adding renewable energy technologies to the energy portfolio. This would help reduce reliance on unstable energy sources and reduce the chance that changes in commodity prices will interrupt the energy supply, which eventually would help reduce the effects of climate change.

DIGITAL FINANCE AND FINANCIAL INCLUSION IN NIGERIA: ARE THEY SIAMESE TWINS?

The link between Financial inclusion (FIN ) and digital finance(DF) is the primary subject of this research. Digital finance and inclusive financial though have been adjudged to be related; there are quite a plethora of issues that are still unclear concerning the nature and type of their relationship. Why are they related and at what point are they related? Short or long-run relationship? To clarify these issues, the study applied the Auto regressive Distributed Lag (ARDL) long-run cointegrating technique to explicate our econometric models. Our data is time series in nature and is for Nigeria. The study established that, internet-powered electronic device users, a proxy for digital finance has a positive long-run relationship with FIN while Automated Teller machine (ATM) ownership and usage has a negative long-run relationship with FIN. The study recommended that internet service providers (ISPs) be integrated into the Nigerian FIN paradigm to enhance the accuracy and viability of financial service provision, leading to a decline in the unbanked population.
 Keywords: Digital finance, FIN, financial services, ARDL Bounds Test, Nigeria.

Validity of the Phillips curve in the Agricultural Sector: The Case of Turkey

Agriculture, which has historically been the main employment generating sector, is still very important in newly industrializing countries such as Turkey. Theoretically, it is thought that its share in GNP will decrease over time, but the depth of the decrease will depend on the economic impact of agriculture. One way to measure this effect is to adapt the Phillips curve for the agricultural sector. Therefore, the aim of this study is to analyse the validity of the Phillips curve in the Turkish agricultural sector. The study is conducted by the Augmented Dickey Fuller, Phillips Perron and Zivot-Anders Unit Root Tests as well as Nonlinear Autoregressive Distributed Lag and Autoregressive Distributed Lag tests via TURKSTAT 2014Q1-2020Q3 dataset. Reviewing these test, we find that the cointegration coefficient calculated by the NARDL model is negative, yet statistically significant. Accordingly, the short-term imbalances are eliminated in the long-run and the system converges to the long-run equilibrium values. Nonetheless, since the coefficient is greater than one, it is a sign of significant fluctuations in the convergence of the system to the long-term equilibrium. Additionally, the long-run negative cointegrated relationship of unemployment and inflation indicates that the Phillips Curve is valid in Turkish agricultural sector.

Spatiotemporal changes of agricultural water footprint and its driving factors using the ARDL model in the Hexi corridor, China

The water footprint theory was used to analyze the agricultural water footprint (AWF) and its spatiotemporal characteristics in the Hexi corridor, Northwest of China from 2002 to 2017. The AWF increased during 2002–2017. Meanwhile, the water footprint of cash crops rapidly increased from 10.08 billion m3 to 100.94 billion m3; however, the water footprint of grain production increased slowly and remained relatively stable. There were great differences in the water footprint of various agricultural products in twenty counties in the Hexi corridor. Furthermore, this study explored the equilibrium relationship between the gross domestic product (GDP), population, grain yield, fertilization, urbanization rate, and AWF using the Panel Pool Mean Group and autoregressive distributive lag (PMG/ARDL) model. Our findings demonstrated that economic growth, grain yield, and fertilization had a significant positive relationship with AWF, and population and the urbanization rate had a negative long-run but non-significant relationship with AWF. The panel causality analysis showed a one-way causal relationship between the AWF with population and urbanization rate. The grain yield, the rate of urbanization, and fertilization in the Hexi corridor need further improvements to ensure the sustainable development of water resources.

Does Foreign Interest Rate Determine Islamic Stock Prices?

Does Foreign Interest Rate Determine Islamic Stock Prices?

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.

Global Geopolitical Risk and the Long- and Short-Run Impacts on the Returns and Volatilities of US Treasuries

ABSTRACT We examine the impact of global geopolitical risk (GPR) measures on US Treasuries’ returns and volatilities, differentiating between long- and short-run investment behaviours among an array of time-to-maturities ranging from 1 month to 30 years, taking into account various economic and financial factors. Using monthly data and a panel autoregressive distributed lag (ARDL) model, the results indicate a negative long-run relationship between US Treasuries’ returns and the global GPR index. These results generally hold when we consider geopolitical threats and geopolitical acts, although they exhibit some discrepancies between these two components and across the yield curve. Further results show a positive and strong long-run relationship between the US Treasuries’ realized volatilities and the various geopolitical risk measures. The evidence holds true when we disentangle ‘bad’ from ‘good’ realized volatilities, although the impact of bad volatility is stronger than that of good volatility, which points to an asymmetric effect of realized volatility in US Treasuries. A sub-sample analysis suggests the robustness of the main results. Our analyses provide the first empirical evidence of the information content of GPR for US Treasury securities’ returns and volatilities, which matters to fixed-income investors and decision-makers at the Federal Reserve.

Unemployment and Foreign Direct Investment Nexus: Empirical Evidence from Ghana

Purpose: The paper examines the effect of foreign direct investment on unemployment in Ghana. Design/methodology/approach: The paper uses annual data spanning from 1990 to 2020 and employed the Autoregressive Distributed Lag (ARDL) estimation technique. Findings: The paper found that unemployment has a long-run relationship with foreign direct investment, gross domestic product, export and gross capital formation. Foreign direct investment and GDP has a negative long-run relationship with unemployment. On the contrary, export of goods and services positively relate to unemployment in the long-run devoid of gender. Lastly, we also found a mediating effect of GDP on FDI in reducing unemployment rate in Ghana. Research limitations/implications: The finding that export of goods and services relate positively with unemployment in the long run does not necessarily imply that Ghana should stop exporting goods and services in order to solve unemployment challenges in the country. Rather we should adopt the attitude of adding value to our raw products before exporting. And to reduce unemployment in the country, government should adopt incentivized tax policies to foreign investors to attract more FDI inflows into the economy. Originality/value: Not only does the present paper extend to more recent data, but it is also the first of its kind to the best of our knowledge in studying the nexus between FDI and unemployment rate in Ghana and also bringing to bear the gender dynamics of such relationship.

Evolution of energy mix in emerging countries: Modern renewable energy, traditional renewable energy, and non-renewable energy

Recent global environmental concerns have called for efforts to promote the transition of energy sources toward renewable energy, particularly in emerging countries that prioritize high economic growth. One missing aspect in environmental studies is that renewable energy is composed of traditional and modern ones, where the former could induce environmental and health problems, and the latter could solve them. Accounting for different types of renewable energy, this study evaluates the energy mix evolution in relation to a country's development level (proxied by real GDP per capita) for 23 emerging countries from 1990 to 2016. By applying the pooled mean group autoregressive distributed lag (PMG-ARDL) model, we examine the short- and long-run linkages of a country's income level with the energy mix. To capture the energy mix, we use three variables of energy sources, (i) non-renewable, (ii) traditional renewable, and (iii) modern renewable energy. Our results show that the income level has a long-run positive relationship with non-renewable and modern renewable energy but a long-run negative relationship with traditional renewable energy. Our findings shed light on the importance of implementing policies targeting the shift from non-renewable energy toward modern renewable energy by the policymakers concerned in emerging countries.

FINANCIAL DEVELOPMENT, FINANCIAL INCLUSION AND INFORMALITY: NEW INTERNATIONAL EVIDENCE

This paper explores the empirical relationship between informality and several indicators of financial development (FD) and financial inclusion (FI). We exploit a panel of 152 countries with annual information between 1991 and 2017. Using panel cointegration techniques, we find evidence of a negative long-run relationship between informality and FD/FI for different groups of countries. Moreover, exogeneity tests indicate that some FD/FI indicators cause less informality. Specifically, we find that in developing countries FD reduces informality when measured as “financial credit” and “bank credit”, whereas FI reduces informality when measured as “number of bank accounts”. These results suggest that higher credit and more bank accounts have contributed to reducing informality in developing countries in the long run. Additionally, we find evidence of double causality between informality and other FD/FI indicators in developing and Latin American countries.

The relationship between staple food crops consumption and its impact on total factor productivity: does green economy matter?

The agriculture sector is a key driver of economic growth and provides employment opportunities across the globe generally. However, in today’s world, agricultural product demand is more influenced by taste, prices, and nutritional value due to climatic variation. The study has analyzed the current situation grain productivity by using the data of farm inputs and major grain crops of Pakistan from (1960–2020). The study consists of a two-stage analysis in the first stage, the total factor productivity (TFP) variable is obtained by using the parametric Tornqvisit-Theil index output-input-aggregation method separately for each crop; rice, maize, and wheat. After that, the unit root test is used to check the stationarity and trend of the variables in the long run. Subsequently, the autoregressive distributed lag (ARDL) model is applied to check the existence of cointegration in the long run and short run among the variables. The results of the study disclosed that the consumption of rice has a positive relationship with its total factor productivity, but, wheat and maize have a negative long-run cointegration relationship with the respective productivities. The study results have shown that the consumption pattern of staple crops has substantially changed, due to climatic variation, and the current food consumption trend is revealing new dimensions and trends owing to variation in climate change and anthropogenic pressure which demands to adapt climate resilient farm practices.

The COVID-19, power generation and economy – Case study of a developing country

The global COVID-19 pandemic created profound impact on every nation’s economy, education, healthcare, social and cultural life, domestic and international mobility at an unprecedented level. Since the start of the COVID-19 pandemic in early 2020, most nations are undergoing through frequent full or partial lockdowns, resulting in significant economic losses, and unprecedented suffering of hundreds of millions of people worldwide. Given the crucial role of electric power in economic activities, the purpose of this study is to investigate the impact of COVID-19 pandemic on power sector and economy in a developing/emerging country as a case study. The study examined electric power generation and consumption, GDP growth, export, import, remittances, and various government measures undertaken during the COVID-19 pandemic in Bangladesh. Autoregressive distributed lag (ARDL) model was used to investigate correlation between COVID-19 cases and power consumption during full and partial lockdowns. The research revealed a long-run negative relationship between COVID-19 cases and power consumption during partial lockdowns. The study also revealed that the targeted and partial lockdowns accompanied by nation-wide mass vaccination programme can steer the economy along the power sector with minimal or no impact during the COVID-19 pandemic.

The Impact of Non-performing Loans on Nigerian Economic Growth, 2011-2020

This paper examined the impact of rising non-performing loans (NPL) on Nigeria's economic growth using time series data from 2011 – to 2020. In analyzing this relationship, the co-integrated autoregressive distributed lag (ARDL) model was employed, and the study revealed a long-run negative relationship between NPL and economic growth. This suggests that a higher NPL may have reduced the banks' loan disbursement capacity or made the banks reluctant to give out more loans to the productive sector, adversely affecting the economy. This research also supports the long-standing results of a positive relationship between money supply and economic growth. It further revealed a positive relationship between government expenditure and economic growth in Nigeria. Therefore, the study recommended that Nigeria's financial management team activities include a dedicated watch on the rising NPL in the banking industry. Furthermore, monitoring NPL should no longer be viewed as the sole responsibility of the CBN but that of all managers of the Nigerian economy.

Dynamic Link Between Stock Market Size and Stock Market Investment Returns In Nigeria

Purpose—This study examines the dynamic link between stock market size and investment returns in Nigeria. Design/Methodology: Based on an ex post facto research design, the Autoregressive Distributed Lag (ARDL) technique was applied to the annual time series data obtained from the Central Bank of Nigeria’s statistical bulletin for the period 1985 to 2019. Findings-- Findings indicate a negative, weak, and significant correlation and a long-run relationship between stock market size and stock market returns in Nigeria. Furthermore, this study confirmed that in the long run, the stock market size negatively and significantly affects stock market returns in Nigeria. However, in the short run, the effect of stock market size on returns is positive and statistically significant. Practical Implications--It is imperative that the government vigorously pursue capital market policies directed at expanding the market size in close partnership with the organized private sector. In contrast, the long-run negative effect of stock market size on stock market investors should be mitigated by improving the financial market environment in the areas of law and policy framework, professionalism and ethical operations, infrastructural improvements, etc. Original Value—This study posits that there is a significant negative long-run relationship between size and investment returns in the Nigerian Stock Exchange, and this relationship has long-term policy implications for the economy. Keywords-- All-share index, Autoregressive Distributed Lag, Investments, Market capitalization, Stock market size, Stock returns. Paper Type—Research paper

NEXUS BETWEEN UNEMPLOYMENT, INFLATION AND ECONOMIC GROWTH IN NIGERIA

Unemployment and inflation are twin evils that are bedeviling economies of the world and have continuously attracted the concern of economists. Most developing countries Nigeria in particular is battling with these problems. This study examines the nexus between unemployment, inflation and economic growth in Nigeria from 1981 to 2020. Diagnostic test was conducted to ascertain the behavior of the series. The Augmented Dickey Fuller (ADF) and Philips Perron (PP) test results are reported. Based on the test, the variables in the model are of mixed order of integration i.e., two of the variables are I(1) and one is I(0) . The Autoregressive distributed lag (ARDL) bound co-integration test was conducted to check for possible long run relationship. It was found that there is a long-run relationship in the model. Thus, the ARDL ECM was used for the estimation. Results from the ARDL estimation reveal that the Error Correction Mechanism (ECM) has the expected negative sign with a high speed of adjustment of 71% back to equilibrium; there is a long-run negative relationship between unemployment and economic growth in Nigeria over the period of study; there is a long-run negative relationship between inflation and economic growth in Nigeria over the period of study. Based on these findings, this paper recommended that the government of Nigeria should spend more money on training and skill acquisition in order to combat unemployment. More so, excessive and galloping rise on the prices of goods and services in Nigeria should be control.