Fully Modified Ordinary Least Squares Research Articles

Foreign Direct Investment Inflow Dynamics: The Case of Central and Eastern Europe

This study investigates the dynamics of foreign direct investment (FDI) inflows into Central and Eastern European countries (CEECs) using panel data (1994–2020) analysis methods such as fixed effects, fully modified ordinary least squares (FMOLS) and random effects. Specifically, the study examined what factors could account for the mixed pattern of FDI inflows into CEECs. The mixed results from the existing empirical literature on FDI inflow dynamics triggered the undertaking of this study to contribute to the ongoing debate on the subject. The study notes that infrastructural development, economic growth and domestic investment had a significant positive influence on FDI across all three panel data analysis methods. Other variables that were found to have had a significant positive effect on FDI include (1) complementarity between infrastructural and financial development (fixed effects, random effects), (2) trade openness (fixed effects) and (3) savings (random effects, FMOLS). A significant negative impact of the exchange rate on FDI was observed under the FMOLS. CEECs are therefore urged to implement policies to increase infrastructural development, financial development, trade openness and savings to enhance the inflow of FDI. Future studies should investigate the minimum threshold levels of the explanatory variables of FDI.

Modeling Linkages among Urban Agglomeration, Construction Industry, Non-Renewable Energy, and Zero-Carbon Future

On the one hand, the twin perspectives of the construction industry and urban agglomeration proliferate economic prosperity. However, on the other hand, construction activities and increased population density give rise to environmental challenges. This study is an initial attempt to explore links between the construction industry, urban agglomeration, non-renewable energy utilization, carbon dioxide emissions (CO2e), and economic output within a system of simultaneous equation modeling. This study develops modeling specifications to include the construction industry as a shifting factor and CO2e as a determinant of technical efficiency. A heterogeneous fully modified ordinary least squares (FMOLS) technique, capable of providing concrete empirical outcomes even in the presence of modern panel-data econometric issues, is utilized for the data of China’s 30 provincial/ city divisions during the 2003–2019 period. It has been revealed that: (i) the influence of urban agglomeration on the economic output was heterogeneous, with an adverse link for China’s western part, neutrality connection for the central part, and favorable for China’s eastern part; and (ii) shifting from China’s western to eastern parts, the expansion of the construction industry has a significant impact on economic output, and, hence, has been described as “the Economic Effects of Urban agglomeration” for the Chinese economy. The policies of this study have crucial lessons for global economies.

Impacts of health expenditures and environmental degradation on health status-Disability-adjusted life years and infant mortality.

Human health and well-being are intimately related to environmental quality. In this respect, the present study contributes to the existing health economic literature by examining whether public and private health expenditures (PPHE) moderate the incidences of environmental degradation on the health status in Saudi Arabia, particularly disability-adjusted life years (DALYs) and infant mortality. Using the fully modified ordinary least squares (FMOLS) method. The empirical results revealed that (i) unconditional positive impacts of CO2 emissions on increasing DALYs and infant mortality; (ii) conditional negative impacts of public health expenditures on DALYs and infant mortality in all the estimated models, whereas global and private expenditure contribute only on reducing infant mortality; (iii) public health expenditure is more effective than private health expenditure in reducing infant mortality; (iv) the effects of the interactions between the indicators of both health expenditures and CO2 emissions on DALYs and infant mortality are negative and significant only for the specifications relating to public health expenditures, indicating that this later could be employed as a policy or conditional variable that moderates the adverse impacts of carbon emissions on the population's health status. Generally, the study presents an overview of environmental health change's effects and examine how these effects may be reduced through increasing health spending. The study provides recommendations for addressing health status, health expenditures, and carbon emissions, all of which are directly or indirectly linked to the study.

Financialisation and income inequality: An investigation of the financial Kuznets curve hypothesis among developed and developing countries

The Financial Kuznets Curve (FKC) is a variant of the renowned Kuznets Curve and a counterpart to the Environmental Kuznets Curve. In this paper, we examine the financial Kuznets curve hypothesis—based on annual data for 20 developed and developing countries—using the Phillips and Hansen (1990) fully modified ordinary least square (FMOLS) and the unobserved components model (UCM). The results correspond to the current divergence in the empirical literature and show support for the inverted U-shaped curve as well as the U-shaped curve, in more than half of the sample countries. The estimated turning points differ significantly across countries and depending on the measure of financialisation used. Overall, the findings of this research suggest that there is no uniform effect of financialisation on income inequality. The results vary according to the level of economic development, financial structure, and potentially other factors that have not been considered in the empirical analysis provided in this paper.

How Oil Price Changes Affect Inflation in an Oil-Exporting Country: Evidence from Azerbaijan

This research study aims to explore the inflationary effects of oil price rises in the case of Azerbaijan. The study covers 1997–2021 yearly data to estimate long- and short-term impacts while considering “oil price—money supply” interactions. Autoregressive Distributed Lag Bounds testing (ARDLBT), Fully Modified Ordinary Least Squares (FMOLS), and Canonical Cointegration Regression (CCR) cointegration methods are applied simultaneously. The research findings are: (1) oil price is a significant long-term determinant of inflation in Azerbaijan, affecting overall prices directly and indirectly via the money supply; (2) the effect is statistically significant in the short-term and happens indirectly, moderated by the money supply; and (3) oil price moderates the impact of the money supply over inflation in the short-term. A major limitation of the current study is that it omits the possible moderation impact of oil prices over inflation in Azerbaijan through the resulting inflationary pressure due to oil price rises in trade-partner countries and the government’s fiscal policy. Research findings require the Central Bank to consider indirect effects of oil price changes, especially due to money supply changes, when targeting inflation and addressing policy sustainability in Azerbaijan.

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.

Natural Resources Curse in Indonesia

The purpose of this study is to find out whether there is a curse or blessing of Indonesia's natural resources and to find out how the long-term influence of natural resource rents, foreign direct investment, inflation, and the Covid-19 pandemic on economic growth. Based on the purpose of the study, the method used is a Fully Modified Ordinary Least Square (FMOLS). The results show that Indonesia is free from the curse of natural resources, meaning that Indonesia's natural resources have blessings for economic growth. In addition, based on the FMOLS test, it is known that foreign direct investment has not influenced economic development. Meanwhile, inflation and Covid-19 have a negative and significant influence on Indonesia's economic growth.

Does foreign direct investment affect poverty in BRICS?

This study examined the influence of foreign direct investment (FDI) on poverty alleviation in BRICS countries (Brazil, Russia, India, China, and South Africa) using panel methods of econometric estimation, namely pooled ordinary least squares (OLS), fixed effects and fully modified ordinary least squares (FMOLS). Data from 1989 to 2020 was used in this study. The majority of research on FDI-led poverty has ignored the omitted variable bias. Economic growth as a channel in the FDI–poverty nexus was also explored. The relationship between FDI and poverty has so far produced mixed results with no general consensus, hence triggering the undertaking of this study in the context of BRICS. Except for mortality rate, poverty alleviation triggered by FDI was achieved in BRICS (model 1 under fixed effects; model 2 under pooled ordinary least squares (OLS). Economic growth-led poverty reduction was observed across all the three panel methods. The interaction variable (FDI x economic growth) significantly enhanced poverty reduction in model 1 and model 3 across the three panel data methods employed. Similar results were observed in model 2 under the pooled OLS methodology. Policies geared at promoting FDI to reduce poverty should be implemented by BRICS authorities. Further research should explore the minimum threshold levels of FDI necessary to significantly reduce poverty in BRICS as such a study would be more useful and relevant for policymaking decisions relating to poverty reduction.

SMEs and carbon neutrality in ASEAN: the need to revisit sustainability policies

Most rules and regulations for protecting the environment and reducing greenhouse gas emissions target large enterprises. Although small and medium-sized enterprises (SMEs) have major shares in most Asian economies, they remain outside the purview of most environmental rules and regulations. The primary purpose of this study is to assess the association between SMEs’ activities and carbon emissions in the Association of Southeast Asian Nations (ASEAN) countries from 2010 to 2020. To this end, a fully modified ordinary least squares (FMOLS) model was developed. The results show that SMEs’ activities do not align with environmental protection goals and sustainable development, as the estimation results revealed their significant contributions to CO2 emissions. Other practical implications of this study for carbon-neutral SMEs are introducing green finance policies, revisiting the environmental and carbon reduction rules and regulations that cover SMEs, and changing banks’ lending mechanisms based on SMEs’ green economic performance.

Foreign Direct Investment-Growth Nexus in BRICS: How Relevant are the Absorption Capacities?

This study examined the impact of foreign direct investment on economic growth in BRICS using fixed effects, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS). Panel data ranging from 1991 to 2019 was used for the purposes of this study. The same study also explored whether financial sector and human capital development are necessary absorption capacities that enhance economic growth in BRICS. To a larger extent, foreign direct investment had a negative impact on economic growth in BRICS, consistent with the dependency theory. Financial development was also found to be the channel through which economic growth is enhanced by foreign direct investment. Although the influence was observed to be non-significantly negative, human capital development improved the influence of foreign direct investment on economic growth. BRICS authorities are therefore urged to implement human capital and financial development enhancement policies to ensure significant foreign direct investment’s positive influence on economic growth.

Analysis and Projection of Transport Sector Demand for Energy and Carbon Emission: An Application of the Grey Model in Pakistan

The incredible increase in carbon emissions is a major global concern. Thus, academicians and policymakers at COP26 are continuously urging to devise strategies to reduce carbon and other greenhouse gas emissions. The transportation sector is a major contributor to greenhouse gas emissions in developing countries. Therefore, this study projected an increase in fossil fuel demand for transportation and corresponding carbon dioxide emission in Pakistan from 2018 to 2030 by employing the Grey model and using annual data from 2010 to 2018. Furthermore, the determinant of fossil fuel demand is modeled using an environmental sustainability model such as stochastic regression IPAT that links environmental impact as a product of population, affluence, and technology on annual time series data spanning from 1990 to 2019. The projected values of oil demand and carbon emissions reveal an increasing trend, with average annual growth rates of 12.68% and 11.45%, respectively. The fully modified ordinary least squares (FM-OLS) findings confirmed the environmental Kuznets hypothesis. The increase in population growth emerged as the major driver for oil demand and carbon dioxide emissions, while technological advancement can reduce oil demand and corresponding carbon emissions. This study urges Pakistan to switch from oil to gas and other green energies by encouraging hybrid vehicles, as the number of vehicles on the road positively impacts the transport sector’s oil demand. Moreover, increasing economic growth and controlling the population growth rate by discouraging more children can be a valid policy for reducing oil demand and corresponding carbon emissions.

Environmental impacts of energy indicators on ecological footprints of oil-exporting African countries: Perspectives on fossil resources abundance amidst sustainable development quests

In the wake of the ongoing debate on global energy dynamics and environmental concerns, the calls for collective action for environmental protection have intensified even as the quest for sustainable economic growth continues to shape the decisions of policymakers and authorities among nations. As such, this study examines the environmental impacts of energy indicators on the ecological footprint of mainly oil-exporting African economies from the perspective of the interaction between fossil energy resource rents and its consumption, while controlling for the roles of urbanization and globalization among the countries for the period between 1990 and 2016. The adopted Augmented Mean Group (AMG) estimator produced very insightful information in the study and offers the additional advantage of exploring country-specific outcomes in the empirical analyses that were subsequently corroborated by the Dynamic Ordinary Least Square (DOLS) and Fully Modified Ordinary Least Square (FMOLS) approaches. Firstly, fossil energy resource rents and their consumption significantly contribute to environmental deterioration through rising ecological footprint among the countries. Secondly, economic growth and globalization also aggravate the pressure exerted on the environment alongside the observed undesirable environmental impacts of rapid urbanization among the countries. Thirdly, the inverted U-shape income-footprint relationship depicting the environmental Kuznets curve (EKC) hypothesis was rejected for the panel of all countries, while minimal evidence of its validity was only upheld for Egypt and Nigeria on a country-specific basis, thereby reflecting the roles of individual country's specific differences. Hence, strategic energy transition plans, economic diversification policies, green technology investments, and improved environmental regulations were recommended as necessary ingredients for policy directions toward achieving environmental sustainability alongside relevant development goals (SDGs-8, 11, & 13) in the understudied economies.

Determinants of FDI inflows: Aggregate versus country-specific evidence from ASEAN-6

This paper seeks to explore the determinants of foreign direct investment (FDI) inflows into six countries of the Association of Southeast Asian Nations (ASEAN), namely Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam, from 1995 to 2019. Estimations for the aggregate model are conducted with the Driscoll–Kraay standard errors panel regression approach, while the country-specific analyses are based on the fully modified ordinary least squares (FMOLS) approach. At the aggregate level, gross domestic product (GDP) growth, trade openness, unemployment, working-age population and interest rate spread are the main drivers of FDI inflows into the ASEAN-6, while per capita GDP, real interest rate and the global financial crisis have no significant impact. The empirical analysis for the specific-country cases yields mixed results, implying that international corporations may have various criteria to evaluate before making investment decisions depending on the development stage of the host country. Our research findings offer several implications for policymakers to attract quality FDI: (i) fostering trade and investment liberalization through taking down trade barriers and tariffs across nations; (ii) enhancing the quality and capacity of the labor force through management policy renovations; (iii) stabilizing interest rates through monetary policy management to ensure macroeconomic stability.

Panel cointegrating polynomial regressions: group-mean fully modified OLS estimation and inference

We develop group-mean fully modified OLS (FM-OLS) estimation and inference for panels of cointegrating polynomial regressions, i.e., regressions that include an integrated process and its powers as explanatory variables. The stationary errors are allowed to be serially correlated, the integrated regressors – allowed to contain drifts – to be endogenous and, as usual in the panel literature, we include individual-specific fixed effects and also allow for individual-specific time trends. We consider a fixed cross-section dimension and asymptotics in the time dimension only. Within this setting, we develop cross-section dependence robust inference for the group-mean estimator. In both the simulations and an illustrative application estimating environmental Kuznets curves (EKCs) for carbon dioxide emissions we compare our group-mean FM-OLS approach with a recently proposed pooled FM-OLS approach of de Jong and Wagner.

Agricultural Economic Growth, Renewable Energy Supply and CO2 Emissions Nexus

International trade has created more economic growth opportunities in the agriculture sector. The agricultural sector remains key to the South African economy, with a vibrant international market becoming available as the country’s agriculture exports grow. However, the impacts of human-caused global warming have intensified as a result of increased greenhouse gas emissions, notably carbon dioxide (CO2), which negatively affects agricultural productivity and the economy. Considering the future energy resource demands for agricultural productivity due to the expected population growth and the emphasis on environmental remedial actions, the following question presents itself: what impact will a clean energy supply have on the agricultural economy and the environment, notwithstanding that agriculture, as a sector, also has a huge potential to contribute to renewable energy production? This study examines the effect of the nexus of South Africa’s renewable energy supply, CO2 emissions and trade openness on agricultural economic growth from 1990 to 2021. The nexus provides crucial insights into policies targeted at promoting renewable energy in the agricultural sector by isolating key areas of priority. An autoregressive distributed lag (ARDL) bounds test, fully modified ordinary least square (FMOLS) test, a dynamic ordinary least square (DOLS) test and a canonical cointegrating regression (CCR) econometric analysis were used to estimate the nexus. The results showed that growth in the agricultural sector leads to deterioration in the environment, while international trade benefits the sector. The scale of renewable energy supply slowed down the agricultural economy. The study makes a new contribution in providing empirical evidence for the links between renewable energy supply and agricultural GDP, which can drive policy on renewable energy use in the agricultural sector in South Africa. The paper recommends intentional renewable energy production research and development (R&D) finance focusing on renewable energy human development planning and investments in vocational programmes in higher learning institutes, agricultural renewable energy policy and the creation of green incentive schemes for feedstock producers, especially in rural areas in the agricultural sector.

How do carbon emissions, economic growth, population growth, trade openness and employment influence food security? Recent evidence from the East Africa.

East Africa has a substantially greater rate of food insecurity than other regions of the world. Scenarios of climate change and other macroeconomic variables are important contributors to food insecurity in East Africa. Using data spanning from 1990 to 2020, this study looked into the influence of carbon dioxide (CO2) emissions, economic growth, population growth, trade openness, and agricultural employment on food security in the East Africa. The fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models were used in this study. The heterogeneous panel cointegration test's findings indicated that the study variables have an equilibrium long-term connections. The estimation findings from the FMOLS and DOLS models showed that an increase in CO2 emissions increases food security in the East Africa over the long term. According to other findings, long-term food security is positively impacted by economic expansion, population growth, trade openness, and employment in agriculture. However, trade openness has a detrimental long-lasting effect on food security. Future research directions, research limitations, and policy implications are discussed.

Toward sustainable and green development in Chile: Dynamic influences of carbon emission reduction variables

This study investigated the dynamic effects of economic growth, renewable energy consumption, urbanization, industrialization, tourism, agricultural productivity, and forest area on carbon dioxide (CO2) emissions in Chile. Using the dynamic ordinary least squares (DOLS) approach, time series data from 1990 to 2020 were analyzed. A 1% increase in economic growth, urbanization, industrialization, and tourism will increase Chile's CO2 emissions by 0.62%, 0.24%, 0.15%, and 0.1%, respectively. Additionally, a 1% increase in renewable energy consumption, agricultural production, and forest area may lead to CO2 emission reductions of 0.55%, 0.20%, and 0.98%, respectively. The estimated outcomes are insensitive to alternative estimators such as fully modified ordinary least squares (FMOLS) and canonical cointegrating regression (CCR). In order to ensure environmental sustainability through emission reductions, this article recommends policies on low-carbon economies, renewable energy consumption, sustainable urbanization, green industrialization, eco-friendly tourism, climate-smart agriculture, and sustainable forest management.

Board Characteristics and Corporate Sustainability Reporting: Evidence from Chinese Listed Companies

This paper investigates the impact of board characteristics (such as board size, board independence, CEO Duality, board meetings, and committee) on corporate sustainability reporting (CSR) in China. Unlike previous studies, we examine this relationship in light of the three pillars of corporate sustainability reporting: economic, environmental, and social. Using both the Fully Modified Ordinary Least Square (FMOLS) and Dynamics Ordinary Least Square (DOLS) empirical models, our data, which comprises 9842 firm-year observations from both the Shanghai and Shenzhen stock exchanges covering the 2006–2019 fiscal periods, reveals that board independence, a larger board size, and a board sustainability committee promote CSR in the three CSR pillars. However, the study shows that CEO duality is more likely to impede CSR. While the current study seems to provide some understanding regarding the relationship between board characteristics and corporate sustainability reporting to corporate boards, regulators, and practitioners interested in advancing the course of CSR, some significant knowledge gaps still need to be explored in future studies. Future research may consider other board characteristics as well as explore other CSR indices like integrated reporting and triple-bottom-line approaches.

Fiscal capacity and public health expenditure in Zimbabwe

Public healthcare financing is important for achieving one of the 2030 Sustainable Development Goals (SDGs), the goal of healthy living and well-being (SDG3). Understanding the impact of fiscal capacity on public healthcare financing helps in assessing the government’s commitment towards attaining SDG3. The study sought to investigate the relationship between fiscal capacity and public health expenditure in Zimbabwe. An Autoregressive Distributed Lag (ARDL) model was estimated using annual time series data for the period 1980–2017. The results of the ARDL model were validated using the Fully Modified Ordinary Least Squares (FMOLS) and Canonical Cointegrating Regression (CCR) methods. The study found that fiscal capacity (measured as the ratio of tax revenue to GDP) impacted positively on public health expenditure. The results suggest that following an improvement in resources, the government prioritised the health sector. The study recommends that the government continues to prioritise health in the national budget to enhance the country’s achievement of SDG3.

To what extent does renewable energy deployment reduce pollution indicators? the moderating role of research and development expenditure: Evidence from the top three ranked countries

Climate change, pollution, drought, and rising seas impede the achievement of the seventh sustainable development goal SDG#7 “affordable and clean energies”. To counter these threats, the use of Renewable Energy (RE) as an alternative to conventional energy plays an important role in sustainable development. In this context, the purpose of our paper is to investigate the effect of Renewable Energy deployment on environmental protection in China, The United States of America (USA), and Germany: the top three ranked countries in terms of REs production, according to RENEWABLE 2021 GLOBAL STATUSREPORT. To achieve this objective, the paper adopts a Panel fully modified OLS (FMOLS) method. Results declare that renewable energy significantly reduce pollution indicators; furthermore, we find that Research and development fully moderate this relationship. The findings of this study emphasize the importance of increasing spending on Research and development activities in the RE sector. In addition, the countries studied and countries around the world should pay greater attention to investment in research and development to support the long-term plan for advancing sustainable energy sources for feasible energy and economic development.