Dynamic Lag Research Articles

On the conflict of natural resources hypothesis in Pakistan

Being a resource-based nation, Pakistan has been riddled with economic inadequacy attributable to its reliance on the resource industry. The conformity of natural resources to a curse or blessing cannot be ascertained merely from the perceptive of the influences of resource endowments on economic and social development, as the focus of previous studies proposed. This inquiry intentions are to scrutinize the nature of natural resources, government debt, trade globalization, government stability, and renewable energy consumption, as well as their implications for human development in Pakistan from 1990 to 2021, applying the novel dynamic autoregressive distributed lag (D-ARDL) simulations method and the frequency-domain causality (FDC) test to scrutinize long-, medium-, and short-run relationships. The observed results proposed that natural resource undesirably impact human development, confirming the existence of a resource curse effect. Simultaneously, government debt and government stability worsen, whilst renewables and trade globalization stimulate human development in long and short term. In addition, the FDC validates long, medium and short run causation hypotheses. The findings indicate an appropriate practice for the optimal use of resource rents in conjunction with lower public debt and a stable government system would culminate in human development and inclusive growth.

Role of energy mix and eco-innovation in achieving environmental sustainability in the USA using the dynamic ARDL approach: Accounting the supply side of the ecosystem

The United Nations Framework Convention on Climate Change (UNFCCC) partners agreed with a landmark decision on environmental concerns at the COP26 in Glasgow, outlining future attempts and measures to ensure a secure environment. In this regard, several prior studies have looked at environmental issues using carbon dioxide emissions, or ecological footprint. However, considering these variables may cause the supply side of environmental quality to be overlooked. To make up for this shortcoming, this study examines the effect of energy mix (fossil fuels, nuclear, and renewables), economic growth, and eco-innovation on the load capacity factor, which emphasizes both the demand and supply side of the ecosystem since it takes biocapacity and ecological footprint into account. Hence, this study differs from previous research in that it takes a broader view of environmental sustainability. In this milieu, the current research employs a recently developed dynamic autoregressive distributed lag (DARDL) simulation model for the United States of America (USA), harnessing data from 1990 to 2018. The findings unveil that nuclear and renewable energy consumption and eco-innovation all positively impress the load capacity factor, meaning that these variables help the USA maintain its environmental sustainability. On the other side, fossil fuel usage and economic expansion curbs environmental sustainability. Furthermore, since the short-run income elasticity is larger than the long-run elasticity, the environmental Kuznets curve hypothesis is legitimate for the USA. These findings also validated by the frequency domain causality test. Based on the findings, specific policy proposals are given to assist the USA in improving its environmental quality and achieving the UN Sustainable Development Goals (SDGs) 7 (clean energy) and 13 (climate change mitigation).

Understanding the Relationship Between Foreign Direct Investment and Economic Growth in BRICS: Panel ARDL Approach

Foreign direct investment (FDI) has gained prominence in international economics over the past three decades. Primarily, the belief that FDI influences economic growth of the host country, set the stage for the empirical research focused on the FDI–growth nexus. The growth literature, however, reveals mixed evidence regarding the role of FDI in promoting growth. Despite the conflicting evidence, developed and developing economies have attached immense economic and political importance to FDI. It is noteworthy that BRICS (Brazil, Russia, India, China and South Africa) economies are representative developing economies and have emerged as significant FDI destinations, having witnessed an immense surge in inward FDI over the past few decades. It is against this backdrop that the present study attempts to assess the impact of FDI inflows and select macroeconomic variables, namely macroeconomic stability, human capital, financial development and trade openness (TO), on the economic growth of developing BRICS economies. The study examines both short-run and long-run relationships between FDI inflows, select macroeconomic variables and economic growth by employing the dynamic panel autoregressive distributed lag (ARDL) model, unlike most of the previous studies. For this study, secondary data covering a reference period of 32 years (1987–2018) were used. The data on GDP growth (GDPG), FDI inflows, inflation (INF), human capital, private sector bank credit (proxy for financial development) and TO have been collected from the World Investment Reports published annually by United Nations Conference on Trade and Development (UNCTAD) and World Bank (World Development Indicators). The findings revealed a long-run cointegration among FDI, host country characteristics (TO, human capital, financial development and macroeconomic stability) and economic growth in BRICS.

Effect of bilateral and multilateral concessional debts on public investment in Africa: A contingency analysis

AbstractThe purpose of this paper is to evaluate the relative influence of bilateral and multilateral concessional debts on public investment in 32 sub‐Saharan African countries over the period 1985–2020. Dynamic panel autoregressive distributed lag models comprising the mean group, pooled mean group and dynamic fixed effect estimators were employed in our model estimations. The results revealed that bilateral and multilateral concessional debts had a long‐run positive and significant effect on public investment. The findings indicated that a 1% change in bilateral and multilateral concessional debt was associated with 8.6 and 11.3% increases in public investment, respectively. While the short‐run influence of bilateral concessional debts was significantly positive, multilateral concessional debts had a short‐run positive but insignificant effect on public investment. It is discovered that institutional quality is associated with declines in public investment. The contingency analysis shows that institutional quality explains a lot about how well bilateral and multilateral concessional debts drive public investment. The evidence suggests that poor institutional quality is more likely to undermine the effectiveness of bilateral concessional debts on productive investment than multilateral concessional debts.

Nexus between economic growth, external debt, oil price, and remittances in India: New insight from novel DARDL simulations

This study aims to give empirical insights into how the linkages between external debt, crude oil price, and personal remittances affect economic growth in India. This research stands out from the rest because it makes use of the newly established unique dynamic autoregressive distributed lag (DARDL) simulations framework to evaluate long- and short-run cointegration among chosen variables, as well as the impact of negative and positive changes in the regressor on the regressand using annual data from 1990 to 2020. For India, the key findings are as follows: (i) external debt contributes to lower economic growth in the long run as well as the short run; (ii) oil price influences economic growth positively in both the long and short run, and (iii) personal remittance negatively affect economic growth in the long run. Considering empirical facts, this article proposes that the Indian government and policymakers formulate policies that could reduce external debt and improve the nation's economy to reap the potential gain from remittances, which might spur economic development.

Transition towards sustainable energy: The role of economic complexity, financial liberalization and natural resources management in China

China's sustainable development heavily depends on the nation's capacity to shift from fossil fuel to renewable energy, which can aid in meeting the country's target of attaining carbon neutrality by 2060. Currently, China is a global leader in renewable energy capacity; there is a need to understand the role of some major determinants of renewable energy usage. In this research, we consider it essential to investigate how financial globalization, economic complexity, and natural resources impact China's renewable energy usage, while considering crucial factors such as economic growth and environmental degradation. Annual dataset spanning from 1980 to 2019 and the dynamic autoregressive distributed lag approach for empirical investigation. The empirical outcome suggests that renewable energy is positively influenced by economic complexity, natural resources and economic growth. Furthermore, these results highlight the neutral impact of financial globalization and economic growth on renewable energy in the long run. However, financial globalization negatively impacts renewable energy in the short run. The frequency domain approach was used for the causal interaction test, which established the evidence of causality interaction between renewable energy and its determinants at various time horizons. As a result, policymakers should prioritize product specialization and diversification while pursuing more sophisticated exports.

The role of technological innovation in fostering environmental quality in South Africa: Fresh evidence from the novel dynamic ARDL simulations approach

This study revisits the role technological innovation plays in fostering environmental quality in South Africa over the period 1960-2020. Unlike the previous studies, the work employs the novel dynamic autoregressive distributed lag (ARDL) simulations framework to assess the positive and negative changes in technological innovation, scale effect, technique effect, for- eign direct investment, energy consumption, urbanization, industrial growth, and trade open- ness on CO2 emissions. Second, the paper uses the Squalli &Wilson (2011)'s innovative meas- ure of trade openness to overcome the limitations associated with the conventional trade in- tensity. Third, the study uses the frequency domain causality (FDC) approach developed by Breitung & Candelon (2006) to robustly capture permanent causality for long, short, and me- dium-term associations among the variables examined. Fourth, the paper employs the second- generation econometric procedures, which take into account the multiple structural breaks considerably overlooked by previous works. For South Africa, our empirical results reveal that: (i) technological innovation contributes to lower CO2 emissions in the short- and long run; (ii) while technique effect improves environmental quality, the scale effect largely con- tributes to escalate CO2 emissions, thus confirming that the environmental Kuznets curve (EKC) hypothesis holds; (iii) urbanization, industrial value-added, foreign direct investment and energy consumption increase CO2 emissions; (iv) trade openness contributes to worsen environmental degradation in the long run; (v) scale effect, technique effect, technological innovation, energy consumption, foreign direct investment, trade openness, urbanization, and industrial growth Granger-cause CO2 emissions in the short, medium and long run showing that these variables are fundamental to determine environmental quality. In light of our em- pirical evidence, this paper suggests that South Africa's government and policymakers could consider the role of technological innovation as a clean source of technology in achieving energy security and fostering environmental quality in the country.

Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach.

Given a new perspective on the environmental hypothesis, this paper systematically investigates the validity of the environmental Kuznets curve (EKC), pollution haven, and pollution halo hypotheses using carbon efficiency as the dependent variable. Applying the dynamic autoregressive distributed lag simulations based on the annual time series data over the period 1990-2019, the study found that real GDP per capita has negative effects on China's environmental quality both in the short and long run, whereas the square of real GDP per capita has positive impacts. This validates the EKC hypothesis for China. Furthermore, foreign direct investment has negative effects on environmental quality in China, implying that the case of China exemplifies the pollution haven hypothesis and not the pollution halo hypothesis. The empirical results also demonstrate that energy efficiency and trade openness improve China's environmental quality both in the short run and long run. These findings, therefore, provide insights into achieving the ambitious climate goals in China by 2050.

The Impact of Institutional Quality on Sectoral Foreign Direct Investment in Pakistan: A Dynamic Simulated ARDL Approach

Capital is needed to accelerate the development process, but developing nations struggle with minimum resources. Since foreign direct investment (FDI) is essential to solve the funding shortage, developing nations make every effort to attract FDI to their countries. This study was conducted to explore the impact of institutional quality on sectoral FDI in Pakistan using time series data for the period from 1986 to 2019. To create a solid foundation for policy formulation, this study developed a single measure of institutional quality by utilizing a wide range of institutional indicators. It evaluates the impact of overall institution quality on sector-level FDI and examines the causal relationship between institutions and sectoral FDI with a clear focus on a single-country analysis. The dynamic simulated autoregressive distributed lag technique was employed to explore the impact of institutional quality and other factors on FDI. The results of the study explained that institutional quality and TO have a positive and significant effect on the FDI of the primary FDI sector at 5%, while in the case of the secondary sector, the effect of institutional quality, HDI and GDP on FDI inflow is significant at 10% and TO has a significant effect on secondary sector FDI at 5%. In addition, institutional quality and GDP have a positive relationship with tertiary sector FDI at 5%. The empirical findings show that higher institutional quality in emerging economies such as Pakistan encourages large transfers of technological advances through FDI, increasing the overall performance of the economy. This study found that institutional quality significantly increases sectoral FDI in Pakistan. Finally, this study prescribes some policy measures to increase FDI based on the findings.

Dynamic moisture sorption and humidity response inside the wooden space to cyclical changing external relative humidity

ABSTRACT Wood is usually processed into various spaces and used in buildings, packaging and furniture. Dynamic moisture sorption and humidity response inside wooden space to sinusoidally changing external relative humidity (RH) were demonstrated by using a self-assembly device, which simultaneously recorded moisture content (MC) and RH changes. Wood has hierarchical structures, which provided the basis of moisture sorption and further influenced RH inside. Internal RH changed sinusoidally, similar to external RH and MC. During internal and external moisture exchange, water molecules experienced dynamic compound actions, including moisture gradient pressure, the attraction of sorption sites and water molecules and diffusing hindrance. Consequently, MC and internal RH exhibited dynamic phase lag of over 0.39 radian. Meanwhile, moisture sorption was higher for thinner wood, especially in a longer cyclic period since more water molecules interacted with sorption sites with less diffusing hindrance. Correspondingly, the humidity change was lower inside thicker wooden spaces in a shorter period. The average internal RH and amplitude decreased by 5% and 83.7%, respectively. Dynamic humidity change hysteresis existed and showed positive relation to the cyclic period but inversely with wood thickness. The study helped better understand dynamic moisture sorption and humidity change in wooden space and facilitated the better application of wood in human life.

Time-Varying linkages among financial development, natural resources utility, and globalization for economic recovery in China

The relationship between the availability of natural resources and environmental degradation give rise to significant ecological effects. Recognizing the importance of natural resources, urbanization, and human capital is essential for rapid economic growth. Therefore, it is crucial to consider the factors which contribute to environmental sustainability, by examining the connections between China's total natural resources, gross domestic product (GDP), urbanization, and economic recovery from 1980 to 2018. In this study, the dynamic autoregressive distributed lag (ARDL) model was used. These findings demonstrate that an increase in natural resources negatively impacts economic development in the long run. However, long-term gains in financial development and natural resources have led to higher economic recovery. Finally, urbanization has a significant and negative long-term effect on green economic growth. This study recommends management strategies for increasing urbanization and reducing the associated urban, environmental, and economic difficulties for policymakers and government authorities.

Impact of digital financial innovation on financial system development in Common Market for Eastern and Southern Africa (COMESA) countries

PurposeThis paper aims to assess the impact of digital financial innovation on financial system development in Common Market for eastern and Southern Africa (COMESA). This paper evaluates the dynamic relationship between digital financial innovation measures and financial system development using time series data from COMESA countries for the period 1997–2019.Design/methodology/approachA dynamic autoregressive distributed lag model (ARDL) was adopted and the mean group (MG), pooled mean group (PMG) and dynamic fixed effect (DFE) of the model were estimated to evaluate the short- and long-run impact. In addition, the dynamic generalized method of moments (DGMM) was adopted for a robustness check. The Hausman test results show PMG to be the most consistent and efficient estimator, while the coefficient of lagged dependent variable of different GMM is less than the fixed effect coefficient, and, as such, suggests system GMM is the most suitable estimator. Data for the study were sourced from World Bank Development Indicator (WDI, 2020), World Governance Indicator (WGI, 2020) and World Bank Global Financial Development Database (GFD, 2020).FindingsThe result shows that digital financial innovation significantly impacts financial system development in the long run. As such, the evidence revealed that automated teller machines (ATMs), point of sale (POS), mobile payments (MP) and mobile banking are significant and contribute positively to financial system development in the long run, while mobile money (MM) and Internet banking (INB) are insignificant but exhibit positive and inverse relationship with financial development respectively. Further investigation revealed that institutional quality and a stable macroeconomic environment including their interactive term are significantly imperative in predicting financial system development in the COMESA region.Practical implicationsResearchers recommend a cohesive and conscious policy that would checkmate the divergence in the short run and suggest a common regional innovative financial strategy that could be pursued to incentivize technology transfer needed to promote financial system development in the long run. More so, plausible product and process innovations may be adapted to complement innovative institutions in the different components of the COMESA financial system.Social implicationsDigital financial innovation services if well managed increase the inherent benefits in financial system development.Originality/valueTo the best of the authors’ knowledge, this paper presents new background information on digital financial innovation that may stimulate the development of the financial system, particularly in the COMESA region. It also exposes the relevance of digital financial innovation, institutional quality and stable macroeconomic environment as well as their interactive effect on COMESA financial system development.

Re-visiting resource curse hypothesis in China through the lens of human capital and globalization

The resource curse hypothesis has recently become an important research topic in environmental economics. However, there still needs to be consensus in the literature on whether natural resource rents (NRRs) support economic growth. Previous studies on China have mainly analyzed the resource curse hypothesis based on local or regional data. However, this study examines the issue based on national-level data using globalization and human capital as control variables. The dynamic Auto-Regressive Distributive Lag (DARDL) Simulations and the Kernel-based Regularized Least Squares (KRLS) techniques are employed for policy formulation for 1980–2019. The empirical assessments indicate that NRRs escalate economic growth, i.e., China's resource curse hypothesis is invalid. Further, empirical outcomes reveal that human capital and globalization encourage China's economic growth. The KRLS, a machine learning algorithm, also supports the findings of the DARDL approach. Finally, based on the empirical outcomes, several policy recommendations can be developed, such as more investment in the education sector and the use of NRRs for productive sectors of the economy.

Foreign Debt, Exchange Rate, Inflation and Economic Growth: A Co-integration and Causality Analysis

Pakistan is grappling with a significant debt crisis and seeking assistance from the IMF and allied nations to alleviate the situation. This has aroused the interest of the academic community to understand the intricacies of the debt trap and explore potential solutions. This study examines how foreign debt affects the economic growth of Pakistan by analyzing selected macroeconomic variables for the period 1990-2020. The results of dynamic autoregressive distributed lag models show that Pakistan's economic growth performance is significantly and adversely impacted by debt servicing and exchange rate fluctuations. From the Granger causality results, it is evident that there is a neither unidirectional nor bidirectional causal relationship between GDP and foreign debt. This rejects the notion of a direct relationship between the two, as proposed by previous studies. The study also finds that foreign debt negatively affects the economic performance of Pakistan’s economy via its effects on inflation, exchange rate and debt servicing. The paper offers useful policy recommendations.

Effects of possible changes in natural gas, nuclear, and coal energy consumption on CO2 emissions: Evidence from France under Russia’s gas supply cuts by dynamic ARDL simulations approach

The study explores the influences of potential changes in energy consumption on carbon dioxide (CO2) emissions, focusing on disaggregated energy consumption sources. In this manner, the study considers France as the leading nuclear energy-consuming country in Europe, includes yearly data between 1970 and 2021, and performs the dynamic autoregressive distributed lag (DYNARDL) model. In addition, the Kernel-based regularized least squares (KRLS) is used for robustness check. The results reveal that (i) cointegration exists between the disaggregated energy consumption indicators and CO2 emissions; (ii) nuclear, natural gas, oil, and coal energy have a statistically significant effect on CO2 emissions, while renewable energy is not statistically significant; (iii) nuclear power has a decreasing effect on CO2 emissions; (iv) positive (i.e., increasing) shocks to nuclear reduce CO2 emissions, even if they are 300 % in the case of counterfactual shocks; (v) any positive (i.e., increasing) shocks to coal have a drastically increasing effect on CO2 emissions, even if they are 25 % in the case of counterfactual shocks; (vi) the KRLS approach confirms the robustness of the results. Thus, this study suggests that France should continue to rely on nuclear power for electricity generation and that French policymakers should reduce electricity exports to European Union countries to provide an alternative against the Russian natural gas shock by preventing a reduction in energy supply.

Analyzing the role of green innovation and public-private partnerships in achieving sustainable development goals: a novel policy framework.

The environment's quality is the cornerstone for every country's long-term growth. Pakistan, like other countries, is embracing modern, efficient technologies to build a sustainable environment following the SDGs. In this situation, policymakers and experts have emphasized more on environmental factors. To do this, the study explores the impact of green innovation (GI), public-private partnerships in energy (PPP), energy use (EU), economic development (ED), and power prices (PP) on CO2 emissions in Pakistan from 1980 to 2019. The research uses a novel econometric technique for estimating environmental factors, notably the dynamic autoregressive distributed lag simulations (ARDLS) model and spectral frequency domain causality (SFDC), to examine positive and negative shocks for the prediction of the short-, medium-, and long-run impact of selected determinants, respectively. Additionally, robustness checks were performed using the fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical cointegrating regression (CCR) estimations. The short and long-term empirical findings indicate that GI lowers emissions; nevertheless, PPP, EU, and ED have a significant impact on emissions in the short run, while the EU increases emissions in the long run. PP, on the other hand, reduces emissions both short and long-term. The FMOLS, DOLS, and CCR estimations indicate significant discoveries. Additionally, the SFDC finding supports the long, medium, and short-term causation theories. This research advocates green innovation for a greener manufacturing process and PPP investment in renewable energy. In addition, the Pakistani government considers these variables while designing a comprehensive protracted environmental plan to meet SDGs 7 and 13.

Moving towards sustainability: how do low-carbon energy, current account balance, and reserves induce environmental deterioration in the Big 3?

Promoting financial sustainability is the focus of current state policies while addressing the concerns of environmental pollution. The alarming impacts of climate change on economies motivate us to revisit an intensive empirical study to explore the dynamic relationships of low-carbon energy, current account balance, and reserves with carbon dioxide (CO2)emissions in the most polluted countries across the globe for the years 1981-2020. We applied the dynamic autoregressive distributive lag (D-ARDL) simulation model to investigate the short and long-run connection. The empirical outcomes of the study uncover that in the short run, a 1% increase in renewable energy reduces CO2-based emissions by 0.417%, 0.169%, and 0.619% in China, the USA, and India, respectively. We further explored that China's and the USA's economic growth causes environmental deterioration. In contrast, a 1% increase in current account balances improves the environmental quality of China and India by 0.3% and 0.6%, respectively. This research concludes that model variables significantly impact the environment. Therefore, it is necessary to draw policy implications to increase the consumption of low-carbon energy to sustain economic growth by limiting the adverse impacts of economic activities.

Greening human capital towards environmental quality in Ghana: Insight from the novel dynamic ARDL simulation approach

Numerous studies on the factors influencing Ghana's environmental quality have been undertaken. However, to the best of our knowledge, no study has been conducted on the relationship between green human capital and environmental quality in Ghana. This study aims to address this knowledge gap by exploring the influence of green human capital on environmental quality in Ghana within the environmental Kuznets curve (EKC) framework. Modern econometric techniques are employed for accurate and trustworthy analyses based on data collected from Ghana from 1990 to 2019. The results reveal that all the study variables are first differenced stationary and co-integrated in the long run. Therefore, the novel dynamic autoregressive distributed lag (ARDL) simulation is adopted to examine the connections between the variables. The findings demonstrate that increasing green human capital degrades environmental quality in the short term while green human capital benefits environmental quality in the long term. Further, the investigation validates the EKC hypothesis in Ghana. It is recommended that stronger initiatives and policies be established to address the detrimental consequences of environmental deterioration caused by incompetent human capital, and that life-long green education be continuously reinforced so that human knowledge and skills keep updated with zero-emission milestones.

An empirical approach to the nexus between natural resources and environmental pollution: Do economic policy and environmental-related technologies make any difference?

The outlooks for the interactions between natural resource rent, economic growth, and environmental pollution are widely debated in the literature but not well understood in the context of policy uncertainty and environmental technologies. Therefore, this study empirically explores nexus between natural resource rent, economic policy uncertainty, economic growth, globalization, environmental-related technologies, and CO2 emissions in the United States between 1985 and 2020. The study employed dynamic Auto-Regressive Distributive Lag (ARDL) simulation and Kernel-based Regularized Least Squares (KRLS) techniques. The long-run regression outputs validate that environmental-related technologies are helpful in pollution reduction and improve environmental quality significantly. However, the increase in globalization tends to lead to environmental degradation. Furthermore, results reveal that the rise of natural resource rent contributes to carbon emissions, suggesting that an excessive dependency on natural resource rent disturbs ecological sustainability in the United States. Results indicate that environmental-related technologies should be encouraged, and more stability in economic policies can be suitable choices in fighting against climate change. New policy insights are further discussed in the paper.

Relationship between unemployment and policy uncertainty in Nigeria: ARDL evidence from 1990 to 2020

PurposeApart from providing theoretical clarity, the present research aims to validate empirically that the EPU will be adversely affecting these key macroeconomic variables and that managing EPU matters for economic policymaking in Nigeria.Design/methodology/approachA dynamic autoregressive distributed lag regression model is employed to analyse the relationship from 1990 to 2020. Based on the theory of multiplier effect, the analysis could examine the positive and negative changes in policy uncertainty, as well as the reliability in macroeconomic activities such as unemployment, infrastructure development and foreign direct investment inflows.FindingsThe findings revealed EPU is cointegrated with the key economic variables in focus. Further, the negative impact of EPU on corporate investment in FDI and positive impact of EPU on unemployment confirm for both short and long-run. However, the impact of EPU on government investment in infrastructure development is found to be positive which does not confirm the expected hypothesis.Practical implicationsDynamic relationship between policy uncertainty and macroeconomic activities in Nigeria seems to exist. Taking risky decisions has impact and causing a high unemployment rate, poor infrastructural development and lower foreign direct investment inflows in the country.Originality/valuePolicy uncertainty in Nigeria is determining. Despite that, very little research found that rising uncertainty issues may significantly affect unemployment, investment in infrastructure and foreign direct investment inflows adversely. Therefore, policy uncertainty is an open space for economic activities to thrive in Nigeria, especially unemployment.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2022-0555