Long-run Results Research Articles

A Study of Long-Run Equilibrium Relationship Between Foreign Direct Investment and Its Key Determinants in Malaysia

This study investigates the long-run equilibrium relationship between foreign direct investment (FDI) and its key determinants in Malaysia. Employing the Autoregressive Distributed Lag (ARDL) model on annual data between 1971 and 2021. The key findings confirm a long-run equilibrium relationship between FDI and the selected macroeconomic variables as a group. However, the individual impact of gross domestic product, inflation, exchange rate, and trade openness on FDI is not statistically significant when analyzed separately. Specifically, the long-run results suggest that the determinants do not have significant effects on FDI. Meanwhile, the short-run relationship between FDI and its determinants in Malaysia reveals a complex interplay of factors. Inflation and exchange rates play significant roles, with inflation generally encouraging FDI and exchange rate volatility creating mixed effects. Trade openness on the other hand shows some short-run significance but it is not consistently impactful. The error correction (ECM) model also confirms the existence of a long-run relationship. It highlights that while short-term fluctuations can occur, FDI tends to move towards a long-term equilibrium influenced by a relatively moderate speed of adjustment. The key conclusion implies that FDI is influenced by the combined effect of these variables in the longer term, but the individual contribution of each variable is not strong enough to stand out statistically. This research contributes to the understanding of FDI dynamics in Malaysia by providing insights, thereby informing policymakers and investors about effective strategies to attract and leverage FDI for sustainable development.

Income inequality-renewable energy demand nexus in emerging Asian economies: does asymmetry matter?

Several efforts have been made to explore the income inequality influence on environmental degradation, but the query regarding the nexus of income inequality and renewable energy consumption (REC) is still unanswered. This vacuum in existing literature has raised the need to inspect the relationship between income inequality and REC. Thus, this study purposes to investigate the asymmetric effect of income inequality on REC for emerging Asian economies over the period 1990-2019 by adopting the nonlinear autoregressive distributed lag (NARDL) approach. The panel-wise long-run results infer that positive shock in income inequality exerts a significant negative effect on REC, while negative shock in income inequality has an insignificant effect on REC. Likewise, economy-wise long-run findings reveal that a positive shock in income inequality brings a negative and statistically significant influence on REC in the case of China, India, and Iran, while a negative shock in income inequality brings a positive influence on REC only in case of Russia.

Human capital investments and income inequality in Nigeria: Does institutional quality matter?

The study examines the impact of human capital and institutional quality on income inequality from 1990 to 2021. This study adopts the Kuznets model as its theoretical framework. The unit root test revealed a mixed stationary in the variables which prompts the choice of Autoregressive Distributed Lag of which its bound test result shows that there is a cointegration in the variables. The long-run results show that government expenditure on education, government expenditure on health, government effectiveness, and domestic credit to the private sector have a positive but not significant effect on income inequality while in the short-run, government effectiveness and domestic credit to the private sector have a positive but not significant impact on income inequality. Moreover, only government expenditure on education affects income inequality in the Nigerian economy positively and significantly. Based on the findings revealed, the study recommends that the government should by all means and economic resources increase the budget of human capital to enhance the reduction of income inequality in the country and place more emphasis on providing education grants and incentives that encourage the reduction of brain drain.

The impact of taxation, technological innovation and trade openness on renewable energy investment: Evidence from the top renewable energy producing countries

In the context of contemporary global warming, transitioning from traditional fossil energy to renewable energy sources emerges as a crucial strategy to reduce carbon emissions and achieve the 7th sustainable development goal (SDG). Tax policy significantly shapes the investment landscape, influencing all factors concerning the transition to renewable energy, such as technological innovation and trade openness. However, no empirical studies have examined the direct and moderating role of taxation on renewable energy investment, mainly due to the scarcity of tax data. Therefore, this paper utilizes the recently released Government Revenue Dataset (2023) to explore the complex link between taxation, technological innovation, trade openness, and renewable energy investment for a sample of the top 37 renewable energy-producing countries during the period (1996–2021). The results of the cross-section ARDL (CS-ARDL) and the pooled mean group ARDL (PMG-ARDL) models indicate that taxation has a negative and significant influence on renewable energy investment across all model specifications, both in the short and long run. Conversely, innovation and trade openness exhibit a positive and significant influence on clean energy investment. Regarding the moderating influence of taxation, the results revealed that tax revenues depress the positive impact exerted by technological innovation and international trade. Furthermore, the fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models affirm the robustness of the long-run results obtained from CS-ARDL and PMG-ARDL models. The study's findings offer significant insights into how countries engaged in renewable energy production can enhance their taxation framework to leverage trade and innovation to promote renewable energy investment.

Investigating the Nexus between Inward Foreign Direct Investment and Capital Goods Imports: Empirical Evidence from Pakistan

This research found the empirical analysis between capital goods imports and inward foreign direct investment (FDI) of Pakistan by applying the annual time series data from 1975 to 2020. The importance of this area of research arises from its role in the balance of payments by incorporating foreign direct investment in the capital goods import demand model. The autoregressive distributed lag (ARDL) technique is used to estimate the long run relationship between dependent and independent variables. Furthermore, fully modified least square (FMOLS) and Dynamic ordinary least square (DOLS) techniques are also applied to check the robustness of the estimated long-run results. The findings indicate that capital goods import is positively influenced by foreign direction in the case of Pakistan. Moreover, domestic income, and relative price both have theoretically correct signs. On the other hand, the coefficient of export is negatively associated with import demand, which means that capital goods imports are not used in the promotion of export growth in Pakistan. We recommend that an import substitution policy should be encouraged to divert FDI toward the promotion of export growth and hence reduce the trade deficit in Pakistan.

Interconnections between Remittances, Inflation, and Poverty in Pakistan and India

The study aims to explore the interconnection between remittances, inflation, and poverty in Pakistan and India. The study employed an Autoregressive Distributed Lag model to estimate the short-run and long-run results from 1972 to 2020. The study uses the poverty headcount ratio (as a dependent variable while the variables remittances, GDP deflator, Gini Index, foreign direct investment, tax revenue, unemployment rate, and Urbanisation are used as explanatory variables. The study has also used Granger Causality analysis. The findings of the study indicate that remittances and foreign direct investment has a negative impact on poverty. On the other hand, poverty is positively impacted by the GDP deflator, Gini Index, tax revenue, unemployment rate, and Urbanisation in both Pakistan and India. The result also shows that in both Pakistan and inida, remittances do not Granger cause poverty, and poverty Granger causes remittances. GDP deflator does not Granger cause poverty and poverty does not Granger cause GDP deflator. Policymakers should make policies to improve the remittances in both Pakistan and India. The planners should also make and implement policies that reduce the inflation rate in both Pakistan and India to reduce poverty.

Examining the impact of geopolitical risk on foreign remittances: evidence from top remittances receiving countries

Purpose This study investigates the impact of geopolitical risk (GPR) on foreign remittances (FRs) for the top remittance-receiving countries.Design/methodology/approach The sample includes Mexico, France, Egypt, China, the Philippines, India, Vietnam, Ukraine, Germany and Belgium for the annual period of 1998–2022 using the nonlinear panel autoregressive distributed lag (ARDL) model to determine the asymmetry in the relationship.Findings The results suggest that, in the short term, positive GPR shocks have a positive and significant impact on FRs received. On the other hand, the long-run results suggest that adverse GPR shocks negatively affect FRs received in the sampled countries. Additionally, the study confirms the asymmetric impact of GPR on top remittances received in countries.Research limitations/implications The policymakers, migrants and recipients should consider the asymmetric nature of GPR while making decisions regarding policies and the transfer of remittances. This information can be used to create more effective policies for controlling and reducing the effects of GPR on overseas remittances, such as assisting migrant workers and developing methods to lessen the volatility of these flows.Originality/value Acknowledging the potential fluctuations and uncertainties associated with GPR is crucial to make informed choices regarding remittance-related matters.

A Study of Pakistan’s Fiscal Landscape: Examining the Influence of Institutional Quality and Tax Policy Transformation

Tax collection is the fundamental pillar of financing public services such as education, healthcare, social welfare programs, and infrastructure, and ensuring economic stability. A high share in tax to GDP shows showing greater capacity of a government to provide a high living standard. Maintaining a high tax-to-GDP ratio is important to reveal the ability of the government to generate revenue mobilization. The main drive of the paper is to scrutinize the tax reform influence on the tax-to-GDP ratio for the data period covering from 1996 to 2022 in Pakistan. The study employs the ARDL estimation method, which is suggested by the unit root test. Notably, the long-run results show that regulatory quality and government effectiveness depicted a positive influence on the tax to GDP share, suggesting that improvements in these areas can significantly increase revenue collection. Similarly, political stability and the rule of law also play a positive and significant impact on tax to GDP shares, highlighting their vital roles in increasing revenue mobilization and tax voluntary tax compliance. In contrast, inflation appears negative association with tax to GDP ratio, indicating a substantial decline in the revenue mobilization in the total revenue collection. Findings recommend that the government have to focus on enhancing controlling quality, political stability, government efficiency, and the law and order to boost voluntary tax compliance. Additionally, strengthening institutions is vitally important for enforcing tax laws, and guaranteeing a fair and transparent tax mechanism further boosts revenue collection efforts.

Metallic minerals production and environmental sustainability in China: Insights using ARDL bounds testing and wavelet coherence approaches

China plays a prominent role in the production and consumption of metallic minerals. However, the mining and smelting processes associated with these minerals contribute significantly to the release of CO2 emissions. This study examines the long-run and causal effects of metallic minerals production, renewable energy consumption, GDP growth, financial development, and urbanization on CO2 emissions in China for the period 1977–2021, using the IPAT framework. This study utilizes various econometric methods, including the Bounds test of co-integration, autoregressive distribution lag (ARDL), wavelet coherence test (WTC), and gradual shift causality tests, to analyze the relationship between the variables. The bounds test demonstrates the cointegration among the variables. The long-run results indicate that metallic minerals production, GDP growth, and urbanization have a positive effect on CO2 emissions, while renewable energy consumption and financial development have a negative effect on CO2 emissions. Further, WTC indicates a significant relationship between CO2 emissions and independent variables. Moreover, causality tests indicate a one-way causal relationship between metallic minerals production, GDP growth, financial development, and urbanization with CO2 emissions. In addition, there is a two-way causal relationship between CO2 emissions and renewable energy consumption. To address the environmental consequences of CO2 emissions, China should implement measures such as metal recycling and the adoption of low-carbon and energy-efficient technologies in the mining and production of metals.

Understanding Global Commodity Price Shocks on Exchange Rates and Inflation in Emerging Economies: ARDL Perspective

Aims: To analyze the changing relationship between commodity prices (cocoa, diesel, gold, oil, petrol) and macroeconomic factors (exchange rate and inflation) in Ghana and differentiate between long-term and short-term effects.
 Study Design: Quantitative Design with Time series analysis using the Autoregressive Distributed Lag (ARDL) technique.
 Methodology: The study utilized cointegration and Error Correction Model in econometric estimation. Time series data for commodity prices and macroeconomic factors were collected for the period 2003M01 to 2023M10. The ARDL technique was applied to differentiate between long-term and short-term effects of inflation and exchange rates.
 Results: The short-run and long-run results indicate a positive relationship between commodity prices and inflation and exchange rates. A 1% increase in diesel prices is associated with a 0.23% appreciation in Ghana's currency in the short run (p=0.019) and a 1.76% rise in inflation in the long run (p=0.012). Past inflation has a dominant influence on current inflation, with a 1 percentage point increase in the previous year's inflation leading to a 0.45 percentage point increase in the current inflation rate.
 Conclusion: Policymakers should prioritize stabilizing diesel prices, invest in storage facilities, promote alternative energy sources, strengthen domestic production and distribution of essential commodities, and adopt targeted monetary and fiscal policies to anchor inflationary expectations and address inflation inertia in Ghana.

How does hydrogen energy technology help to achieve carbon neutrality targets?

In recent times, the role of hydrogen technology has become more important in decarbonizing society and achieving carbon neutrality targets. However, the nexus between hydrogen technology and carbon neutrality has not received attention from the empirics. Therefore, this analysis is an effort to plug this gap in the literature by examining the role of hydrogen technology in achieving carbon neutrality targets in six top hydrogen technologies innovative and polluting economies from 1995 to 2021. This study employs the CS-ARDL to obtain the short and long-run results. According to the long-run outcomes, hydrogen technology, green ICT, and financial development cause carbon emissions to fall. In contrast, the GDP boosts the carbon emissions. On the other hand, the short-run estimates don't show any significant relationship with the carbon emissions. These results highlight the significance of hydrogen technology and suggest that policymakers should increase the role of hydrogen technology in energy and related sectors in top polluted economies to help them achieve zero-emission targets.

Short Run and Long Run Effects of Corruption on Economic Growth: Evidence from Balkan Countries

One of the factors that characterize the different countries of the Balkan area is the level of corruption which, as often stressed by scholars, may significantly influence the economic growth of its countries. However, there is still no agreement on the sign of this effect: there are theoretical arguments and empirical results in favor of a positive correlation between corruption and growth, and there are also theoretical arguments and empirical results that support the opposite view. Comparing the short-term and long-term impacts can help to explain this contradiction. In this perspective, we propose an auto-regressive distributed lag (ARDL) methodology. This approach gives both short-run and long-run results simultaneously and it is robust with small samples. The results are not homogeneous for the eight countries covered by our study (Bulgaria, Croatia, Greece, North Macedonia, Romania, Serbia, Slovenia, and Turkey), but the following theoretical intuition is confirmed: although corruption could be seen as a factor that helps economic growth by speeding up the bureaucratic processing in the short run, conversely, in the long run, the social costs associated with corruption are considerable, making it difficult to sustain the political, economic, and social burdens, thus leading to a higher levels of corruption that negatively affect the economic growth. These results confirm certain aspects of Albert Hirschman’s ideas regarding private interests and public action.

Drivers of Carbon Emissions in Kenya: The Perspective of Technology

The empirical studies have portrayed from a different perspective that technology, foreign direct investment (FDI), and economic growth have diverse outcomes on carbon dioxide (CO2) emissions. African economies specifically Kenya are currently threatened with more CO2 emissions for which proper strategies need to be adopted to reduce and mitigate this situation. To address this issue, the Autoregressive Distributed Lag (ARDL) technique was utilized, differentiating between the long-term and short-term effects of drivers of CO2. Granger causality was applied to analyze the causality between the series. The study uses time series data for Kenya from 1990 to 2022. The short-run and long-run results indicate a negative relationship between technology and carbon emissions. Specifically, an increase in technology reduces carbon emissions while an increase in economic growth and FDI inflow increases carbon emissions. The study has identified the negative nexus between technology and carbon emissions in Kenya. This means that technological innovation can increase labour productivity and utilization of resources, thereby reducing carbon emissions. Therefore, Kenya should increase research and utilization of low and efficient carbon technologies to decouple economic growth from environmental pollution. Based on the result, various strategies have been proposed, including using different clean technologies to produce renewable fuels. FDI that complies with environmental regulations, and the use of advanced green and clean technologies can help mitigate the negative impact of technological progress on the environment. Additionally, technological progress, particularly in information and communication technology, will reduce greenhouse gas emissions and improve environmental quality.

Green logistics and circular economy in alleviating CO2 emissions: Does waste generation and GDP growth matter in EU countries?

The integration of Green Logistics (GL) and Circular Economy (CE) have been recognized as critical concepts for achieving sustainable economic and environmental performance. However, there is a lack of understanding on the combine impacts of CE and GL in alleviating CO2 emissions in pioneering nations relying on these concepts. This study examines the role of CE and GL sustainable in curbing CO2 emissions of 13 developed European Union (EU) countries from 2000 to 2020. The neoclassical growth and IPAT models, including the pool mean autoregressive distributed lags (PMG-ARDL) and the vector error correction model (VECM) are employed to estimate the short- and long-run effects and heterogeneous causal relationships. The long-run results reveal that CE and GL can mitigate CO2 (carbon dioxide) emissions, while the generation of municipal waste (GMW) has negative impact on the environment. Moreover, the long-run relationship between economic growth, CE, GL, and GMW validates the Environmental Kuznets Curve (EKC) hypothesis. The study also confirms a bidirectional causality between CE, GL, and CO2 emissions over the long run. This study proposes a model for assessing the impact of CE and GL initiatives on environmental performance and sustainability in both pioneering developed regions and emerging economies yet to embrace green growth concepts.

Linking per capita income, renewable energy, natural resources, trade, and Urbanisation to material footprint: insights from Saudi Arabia

In view of growing greenhouse gases and climate change, this paper investigates the effect of per capita income, renewable energy, natural resources, trade, and urbanisation on the material footprint of Saudi Arabia. This study uses data from 1990 to 2019. Autoregressive Distributed Lag, Fully Modified Ordinary Least Squares, Dynamic Ordinary Least Squares, and Canonical Cointegrating Regression are used as estimation techniques. The result hints that per capita income, renewable energy, natural resources, trade, and urbanisation are determinants of material footprint in Saudi Arabia. Furthermore, the short- and long-run results show that per capita income, trade, and urbanisation increase material footprint, contributing significantly to Saudi Arabia's ecological damage. However, renewable energy and total natural resources rent reduce the material footprint in both periods. Other cointegration techniques also support the long-run estimates. The implications of the result for a sustainable environment were discussed.

Asymmetric effects of economic policy uncertainty on demand for money in developed countries

This paper examines the asymmetric effects of economic policy uncertainty (EPU) on the demand for money in Canada, Japan, the United Kingdom, and the United States. We use linear and nonlinear ARDL models with monthly data over the period 1985–2022 to conduct the analysis. Results from the linear ARDL model show that changes in EPU have no short-run or long-run effect on money demand in any country, except in the US, where changes in EPU have a positive short-run effect. However, with the nonlinear ARDL model, we find evidence of short-run and long-run effects across all four countries. Both increases and decreases in EPU have negative long-run effects on Canadian and UK money demand, but a positive effect on US money demand. For Japan, rising EPU has a positive effect on money demand, whereas falling EPU is insignificant. The long-run results are consistent in each country over time. The recent COVID-19 period had a short-run impact across countries and a long-run effect on the relationship between EPU and money demand in Canada and the UK. In contrast, the Brexit period had no differential long-run impact on money demand across countries, and a short run impact was only observed in the UK. Our results highlight the importance of adopting nonlinear ARDL models instead of linear models to analyze money demand and the need to examine countries separately since the long-run effects of EPU on money demand vary across countries.

The Asymmetric Effects of Exchange Rate Volatility on Domestic Investment in Asia

ABSTRACT: Exchange rate volatility is said to affect domestic investment in either direction. An increase in exchange rate volatility can affect domestic investment negatively since risks are higher, mostly due to volatile prices that are the results of exchange rate volatility. Most previous studies assumed that the response is symmetric. However, one study recently demonstrated that the effects of exchange rate volatility on domestic investment could be asymmetric. We add to this new asymmetry literature by assessing the short-run and long-run effects of exchange rate volatility on domestic investment in eight Asian countries. The linear Autoregressive Distributed Lag (ARDL) approach of Pesaran et al. (2001) is used to estimate the symmetric effects of exchange rate volatility on investment. We then follow Shin et al.’s (2014) approach of asymmetric cointegration and error-correction modelling to estimate asymmetric effects of exchange rate volatility on investment. The advantage of using both the approaches is that the variables could be a combination of I(0) and I(1), ruling out pre-unit root testing since these are the properties of almost all macroeconomic variables. Another advantage is that both approaches yield short-run and long-run results in one step. These advanced methods are applied to data from Hong Kong, Indonesia, Japan, South Korea, Malaysia, the Philippines, Singapore, and Thailand. We find that when a traditional linear and symmetric ARDL investment model was estimated for each of the eight countries in our sample, exchange rate volatility had a significant short-run effects on domestic investment in six countries. The short-run effects lasted into significant long-run effects only in the cases for Malaysia and Thailand. However, when a nonlinear model was estimated, the short-run asymmetric effects of volatility were found in all the eight countries. The short-run effects lasted into the long run only for Hong Kong, Indonesia, and Thailand. Clearly, more significant effects of exchange rate volatility were established by estimating a nonlinear model which must be attributed to the nonlinear adjustment of exchange rate volatility. These findings provide policy guidelines to investors in these countries as to how and in which direction exchange rate uncertainty will affect their investment decisions. They can then hedge against uncertain exchange rate volatility and maintain a stable investment environment.

Investigating the role of energy consumption, ecological innovations, institutional quality and economic growth on ecological sustainability: a study from UAE

In the contemporary world, the issue of a sustainable environment is under significant attention by researchers and policymakers. However, the role of energy sources, both in terms of renewable and non-renewable, cannot be ignored in determining environmental pollution and related issues. This study aims to examine the trends in environmental sustainability as measured through carbon dioxide emissions while considering the role of renewable energy, non-renewable energy, ecological innovation, institutional quality, and economic growth in the United Arab Emirates (UAE). The time period of the study consists of 1995-2020 with yearly observations. For the purpose of literature discussion, both theoretical and empirical studies have been covered through critical analysis.Furthermore, this study considers novel approaches entitled auto-regressive distributed lag (ARDL) in order to estimate the relationships between the variables. The initial results confirm the presence of stationarity properties and the cointegrated association between the variables of interest. On the other side, the long-run results through ARDL show that renewable energy, ecological innovations, institutional quality, and square of economic growth are playing their significant and productive role in reducing carbon emissions. On the other side, non-renewable energy sources and economic growth are causing more carbon emissions, hence confirming the presence of the Environmental Kuznets Curve (EKC). Based on such findings, several policy suggestions have been provided along with limitations and future directions

Discoid LaterL Meniscus: A Concise Literature Update.

Discoid lateral meniscus (DLM) is the most frequent congenital variant of the lateral meniscus, which is prone to degeneration and tears, and frequently causes knee osteoarthritis. The purpose of this article has been to analyze the publications made during 2023 on DLM. The main conclusions of the analysis were as follows: MRI assessment might be helpful to diagnose DLM and detect the presence of instability: two main factors in the decision to perform surgery. Arthroscopic assessment should be utilized in conjunction with MRI findings for complete DLM diagnosis. Restoring the normal shape, retaining adequate width and thickness, and ensuring the stability of the remnant DLM is essential to sustaining the physiological function of the meniscus and preserving the knee. Partial meniscectomy with or without repair should be the first-line treatment when feasible, given that the clinical and radiological long-run results of total or subtotal meniscectomy are worse.

Public Debt and Infrastructural Development in Nigeria; An Empirical Investigation

This study examines the impact of public debt on infrastructural development in Nigeria from 1990-2022, as debt load has become one of the most critical impediments limiting recovery and growth on the continent, but if these debts both internally and externally sourced are being channelled and utilized effectively to improvement of public infrastructure might influences level of the economy, hence contentious in macroeconomics theories. Relying on data from the World Bank Development Indicators and the outcome of various pre-estimation tests ; the Augmented Dickey Fuller and Phillip Peron method were employed to determine the stationarity trend in the data, the correlation analysis to test the relationship between the variables, the study adopted the Auto Regressive Distributive Lag Model (ARDL) estimation technique to determine the relationship between public debt (proxied by domestic debt and external debt) and capital expenditure a proxy for public infrastructure in Nigeria. The long-run results revealed that external debt and internal debt is insignificant but have positive impact of capital expenditure in Nigeria, which implies the misallocation of funds to the development of infrastructures in the country. The study further revealed that the debt service payment and Inflation rate has negative impact of the capital expenditure at the current Lag but has positive association at Lag 1 and not statistically significant at both Lag. The study conclude that public debt positively impact infrastructural development in Nigeria. The research recommend that government should ensure that debts incurred are channel towards the specific and identified infrastructural productive projects and not just for solving short run problems