Dynamic OLS Research Articles

Nexus between profitability, firm size and leverage and tax avoidance: evidence from an emerging economy

PurposeThis study examines the impact of profitability, firm size and leverage on corporate tax avoidance in Bangladesh, an emerging South Asian economy.Design/methodology/approachA balanced panel data of 62 firms from Dhaka and Chittagong stock exchanges in Bangladesh from 2009 to 2020 were used to run the regression. This study employed the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) to examine the hypotheses.FindingsThe findings show that large firms positively impact corporate tax avoidance. Similarly, profitability and leverage are positively associated with tax avoidance, and the results are significant. Furthermore, the study conducts robustness tests that confirm the findings.Research limitations/implicationsThe use of cash effective tax rate (ETR) to investigate firms’ tax avoidance practices poses some limitations, and the results should be interpreted cautiously.Practical implicationsThe current study may help policymakers better enhance tax collection from business firms. The findings could serve as a valuable input for effectively monitoring tax collection from large profit-earning firms.Originality/valueTo the authors' best knowledge, this is the first historical attempt in Bangladesh to use panel data to examine the relationship between the firm’s level characteristics and corporate tax avoidance. Panel data often provides greater flexibility with large data, simplifying calculation and statistical analysis.

FDI-growth and trade-growth relationships during crises: evidence from Bangladesh

This study examines foreign direct investment (FDI)-growth and trade-growth relationships in Bangladesh during three major crises: the economic crisis of 2007–2008, the commodity crisis of 2016, and the coronavirus (COVID-19) pandemic of 2020. The augmented autoregressive distributed lag (AARDL) bounds testing approach and Bayer and Hanck cointegration are employed on time-series data spanning the period 1974–2020. The results suggest that exports have positive effects on economic growth, while imports have insignificant effects in both the short run and long run. Total trade (the sum of exports and imports) has a positive but weakly significant effect on economic growth only in the long run, whereas FDI exhibits a positive effect in both the short run and long run. Although the crises are not found to affect economic growth directly or through trade (i.e., no dampening effect on trade-led growth), they are found to distort FDI-led growth in both the short run and long run. As robustness tests for long-run elasticities, the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) cointegration techniques are implemented, yielding results similar to those obtained with the AARDL.

Determinants of Life Insurance Consumption in OECD Countries Using FMOLS and DOLS Techniques

This paper aims to examine the determinants of life insurance consumption in 30 OECD countries using panel data from 1996 to 2020. This study uses GDP per capita, Life expectancy, Urbanization, School education, and Health expenditure as the determinants to measure the OECD countries’ life insurance consumption. Insurance density is used as a proxy for life insurance consumption. Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and causality tests are applied in this study. Our empirical results revealed that the variables urbanization, school education, and GDP per capita significantly impact life insurance consumption, whereas life expectancy and health expenditure were found to have an insignificant relationship in estimating life insurance consumption. These findings will help all insurance industry stakeholders in OECD countries in policy formulation and decision making.

Statistical Models to Measure the Impact of Intellectual Property Rights Protection on Foreign Trade in Egypt

This study aims to estimate the relationship between the Protection of intellectual property rights indices and the foreign trade index in Egypt from 1995 to 2022. The comparison has been made between many models such as full modified ordinary least squares (FMOLS) model, dynamic ordinary least squares (DOLS) model , canonical co-integration regression (CCR) model and autoregressive distributed lag (ARDL) model. The results of the study showed that the best model was the ARDL model to increase its interpretive capacity. The study also showed that the most important property rights protection indicators affecting the foreign trade index are the number of applications and registrations of brands, the number of patents registered and granted, the number of applications and registrations of industrial designs, and the proportion of expenditure on research and development as a proportion of gross domestic product (GDP). The estimated model also passed all diagnostic tests and showed that there was no autocorrelation, no Heteroskedasticity. In addition, it was found to follow a normal distribution and to be stable.

Taking flight: Exploring the relationship between air transport and Malaysian economic growth

All facets of the tourism business, especially air travel, have been affected by the COVID-19 pandemic. The aviation industry continues to contribute to international economic expansion significantly. The article aims to identify the impact of the development of air transport on the economic development of the Malaysian economy. Therefore, the air-transportation-led growth hypothesis (ALGH) was investigated by examining whether airline travel boosts the Malaysian economy. The effects of air passengers (a stand-in for tourism) on Malaysia's GDP were examined in the long and short term. This study analyzed Data for Malaysia using an autoregressive distributed lag (ARDL) technique. The time covered was from 1970 to 2020. Certain control variables (i.e., energy consumption, financial development, social globalization, and urbanization) were also analyzed to see how they influenced economic expansion. Statistically significant effects of air travel on GDP were found in both the short and long term of this study, suggesting that this mode of transportation contributes to the sustained expansion of Malaysia's economy. Several methods, including Canonical Cointegration Regression (CCR), Dynamic Ordinary Least Squares (DOLS), and Fully Modified Ordinary Least Squares (FMOLS), were used to verify the results independently. The article offers legislative suggestions for improving the aviation industry's productivity, security, and bottom line.

Exploring asymmetric influence of R&D expenditures on CO2 emissions in China: evidence from nonlinear ARDL model.

R&D spending upsurges technological advancement and innovation which results in lowering energy consumption and environmental degradation. The current study investigates the asymmetrical impact of R&D spending on CO2 emissions in China via employing annual data from 1980 to 2021 and the NARDL model for empirical analysis. The estimated results of the NARDL model confirmed that there are asymmetries in positive and negative coefficients of R&D spending in China. The results depict that the positive shock in R&D spending exerts a negative and statistically significant impact on CO2 emissions in both runs implying that an increase in R&D spending lowers CO2 emissions. However, the negative coefficient of R&D spending yields a positive and statistically significant impact on CO2 emissions revealing the fact that a negative shock in R&D spending results in the upsurge of CO2 emissions in China. According to these findings, the impact of positive and negative shocks in R&D spending on CO2 emissions is asymmetric. The findings also show that the impact of a negative shock in R&D spending is greater than the impact of a positive shock on CO2 emissions. In addition to the negative shock in R&D spending, increases in energy consumption, economic growth, and FDI inflows also contribute to an upsurge in CO2 emissions in China. The robustness of the estimated results is assessed using standard fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models. The FMOLS and DOLS results have been confirmed to be sound and consistent with the results of the NARDL model. The study suggests that the economic strategies should aim at investing in R&D spending to foster environment-friendly technological innovations and to lower environmental degradation in China.

From brown to green: are Asian economies on the right path? Assessing the role of green innovations and geopolitical risk on environmental quality.

Preserving the sustainability of the natural environment has emerged as a critical focus on policy agendas worldwide. Therefore, this study examines the relationship between environmental quality and key determinants, focusing on geopolitical risk (GPR), green innovations (GI), economic growth, FDI, renewable energy consumption, and urbanization. Dataset is used for the time period of 1990-2020 across selected Asian economies including China, India, Japan, Malaysia, and South Korea. Using load capacity factor (LCF) as a comprehensive proxy for environmental quality, the research utilizes panel quantile regression (QR) to provide empirical outcomes. Results of panel QR method reveal a negative impact of economic growth and GPR on LCF. On the other hand, green innovation, FDI, and renewable energy are found as supportive factors to boost environmental quality. In addition, urbanization also shows positive linkage with LCF. The application of Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) further validates the robustness of the findings. Adoption of green innovations, practicing sustainable growth patterns, transition toward cleaner energy practices, and integrated urban planning are advocated to enhance environmental quality among Asian nations. Based on empirical findings study suggests comprehensive policy measures that can help in achieving sustainable development goals (SDGs) including SDG-7 (energy efficiency), SDG-8 (sustainable economic growth), SDG-11 (sustainable cities), and SDG-13 (climate action) among Asian countries.

Achieving Carbon-Neutrality in MENA Countries: Does Financial Inclusion Matter?

This study examines the relationship between financial inclusion, renewable energy, and CO2 emissions using data from 11 Middle East and North Africa (MENA) countries from 2004 to 2019. Evidence from fixed effects-ordinary least squares (FE-OLS), dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), and canonical correlation regression (CRR) showed that financial inclusion contributes significantly to decarbonization. Country-specific analysis indicated that financial inclusion is associated with mitigating CO2 emissions in Egypt, Israel, Qatar, and Tunisia while significantly spurring CO2 emissions in Algeria, Lebanon, and Saudi Arabia. In addition, renewable energy contributes significantly to decarbonization in MENA, especially in Algeria, Lebanon, Tunisia, and Turkey. We recommend that policies promoting financial inclusion and renewable energy usage would contribute to the attainment of the carbon-neutrality goal by MENA countries.

Natural resource sustainability and green recovery: Insights from carbon emission reduction in China

China's exponential economic expansion over the past thirty years has been accompanied by environmental hurdles, notably a surge in carbon emissions. This study investigates the effects of measures aimed at reducing carbon emissions on the sustainability of natural resources and their contribution to promoting an environmentally friendly economic recovery in China between 1990 and 2020. The analysis employs Dynamic Ordinary Least Squares (DOLS) regression analysis. Implementing carbon emission reduction measures resulted in a substantial initial decrease in emissions. These initiatives have fostered advancements and monetary allocations towards environmentally friendly technologies and sustainable methods in various industries, bolstering efforts to reduce carbon emissions and improve economic stability.The results illustrate that an effectively planned carbon emission reduction system has the potential to generate significant financial resources for environmentally friendly initiatives and promote sustainable economic revitalization. We advise policymakers to persist in investigating and improving these strategies to ensure the long-term viability of natural resources and promote an environmentally friendly economic recovery.

Balancing Progress and Preservation: The Complex Interplay of Economic Growth and Forest Conservation in Nepal’s Carbon Dioxide Emissions

The intricate relationship between economic growth, environmental quality, and energy consumption has been extensively debated and studied on a global scale. The impacts of ecological quality on economic growth have been observed to be both positive and negative, particularly about human health as a result of pollutant emissions. It is essential to examine the compatibility between economic growth and environmental improvement, particularly through the reduction of emissions. This study aimed to investigate the connection between economic growth in forested areas and the corresponding impact on carbon dioxide (CO2) emissions in Nepal (Rose and Fisher, 1970). The analysis utilized time series data from 1990 to 2020, employing the dynamic ordinary least squares (DOLS) method. The DOLS results demonstrated a positive and statistically significant relationship between economic growth and CO2 emissions (Shafik and Bandyopadhyay, 1992). Specifically, an increase of Rs. 10 million in gross domestic product (GDP) corresponded to a 0.6112 kiloton increase in CO2 emissions. In contrast, the long‐term coefficient for forested areas exhibited a substantial association, indicating that a reduction of one square kilometer of forested area (deforestation) resulted in an increase of 68.37 kilotons in CO2 emissions in Nepal. These findings accentuate the divergent effects of economic progress and deforestation on carbon emissions in Nepal, with GDP growth contributing to a greater increase in emissions. Therefore, the implementation of effective strategies and economic measures, such as afforestation and reforestation, forest protection, sustainable forest management, and mechanisms like REDD+ (reducing emissions from deforestation and forest degradation plus), can play a vital role in mitigating carbon emissions while simultaneously addressing deforestation and ensuring long‐term economic progress in Nepal.

Exploring the impact of economic growth and energy consumption on SO2 emissions in China based on the Environmental Kuznets Curve hypothesis

This study aims to analysis the influence of economic growth (EG) and energy consumption (EC) on sulfur dioxide emissions (SE) in China. Accordingly, this study explores the link between EG, EC, and SE for 30 provinces in China over the span of 2000–2019. This study also analyzes cross-sectional dependence tests, panel unit root tests, Westerlund panel cointegration tests, Dumitrescu-Hurlin (D-H) causality tests. According to the test results, there is an inverted U-shaped association between EG and SE, and the assumption of the Environmental Kuznets Curve (EKC) is verified. The signs of EG and EC in the fixed effect (FE) and random effect (RE) methods are in line with those in the dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS) and autoregressive distributed lag (ARDL) estimators. Moreover, the results verified that EC can obviously positive impact the SE. To reduce SE in China, government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency. This requires the comprehensive use of policies, regulations, economic incentives, and public participation to promote sustainable development.

Institutional quality and economic growth: Evidence from developing countries

This research aims to study the role of institutions in promoting employment and economic growth for a sample of eight Balkan countries over the period 2000–2022. Based on the cointegration technique by Pedroni (2004), fully modified ordinary least squares (FMOLS) and the dynamic ordinary least squares (DOLS) method by Kao and Chiang (2001) determined the potential long-run relationship between variables. The results suggest the existence of a positive and significant relationship between institutions and economic growth. We also found that education supported growth, and unemployment has restricted growth. The conclusion is that further improving institutional quality and education is necessary for supporting growth and employment.

Does the Quality of ICT have an Effect on Tax Revenue Collection in Africa?

This article examines the effect of the quality of information and communication technologies (ICT) on tax revenue collection in Africa. Starting with a sample of 48 countries, observed over the period 1986 – 2017, we use a cointegration model in panel data using fully modified ordinary least squares (FMOLS) technique for the basic analysis. To check robustness, we use dynamic ordinary least squares (DOLS) and canonical cointegration regression (CCR). The results show that the quality of ICT measured in terms of its bandwidth in kilobits per second, contributes positively and significantly to the collection of tax revenues. The findings suggest that development policies should be geared towards fostering both more and better ICTs. In this sense, African states should invest massively in high-speed fiber optic networks, serving the entire extent of their countries to allow tax administrations use of more advanced technologies.

Analysis of the Impact of Exchange Rate on Price Level in Nigeria

The study focus on Analysis of the Impact of Exchange Rate on Price Level in Nigeria from 1988 to 2016 with variables as Inflation, exchange rate, tariff rate, import and interest rate. The research employed the Dynamic Ordinary Least Square (DOLS) regression method with the pre-test of Augmented Dickey Fuller (ADF) unit root test. The regression result showed a negative and insignificant relationship between exchange rate and inflation, tariff rate was negative and significant in relationship with inflation, while import was positively and insignificantly related to inflation, interest rate was having a positive but not significant relationship with inflation. We recommend that moderate or realistic tariff rate be negotiated among trading partners. Also local production of goods for export that will counter the negative impact of import to avoid imported inflation and strict monitoring of the activity of CBN and commercial banks in exchange rate dealing to avoid unnecessary and unproductive use of dollars.

ENERGY SUBSIDY REFORMS, SOCIAL CONTRACT AND POVERTY REDUCTION IN NIGERIA

The study examined the relation among energy subsidy, social contract and poverty in Nigeria covering the period 1999-2022. The study used autoregressive distributed lag (ARDL) model, dynamic ordinary least square (DOLS), and fully modified ordinary least square (FMOLS) approaches to determine the outcome of long-term estimates of the ARDL robustness. The unit root tests shows that the series were stationary at levels I(0) and first difference I(1). Cointegration was established with 2 optimal lag. The results of DOLS and FMOLS show that energy reforms of petrol motor spirit, automobile gas oil, dual purpose kerosene and electricity tariffs have impacted on high level of poverty in Nigeria. The reforms have also affected control variables like inflation and per capital income as inflation erodes the purchasing power of economic agents. The study suggests the need to deepen and implement short-to medium term fuel subsidy removal using market-based pricing as a necessity to protect the poor. This should be complemented by conversion plan from petroleum to natural gas (CNG) vehicles. Strategic policies to strengthen the voice and accountability by the citizens are required. It is essential to trust between government and citizens to strengthen social contract in a manner that improves service delivery, reduce corruption and strengthen institutions which will enhance subsidy reforms more feasible.

The influence of unemployment and labor force participation rates on economic development in GCC countries: A cointegration approach

This study explores the relationship between GDP growth, unemployment rate, and labor force participation rate in the Gulf Cooperation Council (GCC) countries from 1990 to 2018. Furthermore, the study incorporates control factors such as government spending, trade openness, and energy use into the regression equation. We used panel dynamic ordinary least squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS) estimators to investigate the relationships between variables in this investigation. The econometric technique accounts for nonstationary, endogeneity bias and cross-sectional dependencies between country-year observations. Cointegration was found among GDP growth, unemployment rate, and labor force participation. Long-term, the unemployment rate has a statistically significant negative effect on economic growth in the GCC nations. Meanwhile, the labor force participation rate significantly influences economic expansion in the long term. The expansion of government expenditures and international trade reduces economic growth. Alternatively, it is discovered that energy consumption has a substantial and positive effect on economic expansion. Okun’s rule and the unidirectional causality from economic growth to unemployment indicate that the primary cause of unemployment in GCC nations is a failure to adequately expand their economies. When developing economic strategies to reduce unemployment, policymakers are particularly interested in determining whether or not economic development and the unemployment rate are cointegrated.

Examining the consumption of oil on total factor productivity and CO2 emissions: an analysis of highly oil-consuming countries

Purpose This study aims to examine the impact of oil consumption on carbon dioxide (CO2) emissions and total factor productivity (TFP) in highly oil-consuming countries of the world from 1995 to 2019. Design/methodology/approach For this purpose, fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are applied. Findings FMOLS and DOLS models reveal that oil consumption, human capital, population, trade openness and nonrenewable energy have a significant positive effect on CO2 emissions. While information and communication technology (ICT), as proxied by mobile and natural resources, has a significant negative effect on CO2 emissions. In the case of TFP, oil consumption, ICT and natural resources have a significant positive effect on the TFP. On the other hand, trade openness, population, human capital and nonrenewable energy have a significant negative effect on TFP. The results of this study can help to provide policy recommendations to reduce CO2 emissions in studied highly oil-consuming countries of the world. Originality/value Due to the threat to sustainable development, climate change has become a major topic for debate around the world. The influence of oil consumption on CO2 emission and TFP is less known in the available literature. Another significance of this study is that many researchers considered aggregate energy consumption to study this relationship, but the authors have studied the effect of energy consumption, particularly from oil in the top oil-consuming countries, which is a significant shortcoming of the present research.

Do tourism and CO2 emission predict technological innovation in developing countries: Examining Porter and innovative Claudia curve hypothesis

The accelerating concentration of CO2 emissions is attributed to human activities worldwide, leading to increased greenhouse gas emissions. There is an outcry for innovations to combat the environmental threat to even the existence of the human race. From this perspective, the current study aims to analyze the significance of technological innovation, tourism development, economic growth, and human development from the environmental perspective under the idea of carbon neutrality from 1996 to 2019. The study utilized dynamic ordinary least squares (DOLS) to estimate the relationship between the study variables and the panel vector error correction model to showcase the variables’ short and long-run connections. Results reveal that CO2 emissions positively affect technological innovations, which is evidence of the Porter hypothesis. The study showed that the gross domestic product, tourism, and human development index are good innovation indicators and supported the growth-led innovation hypothesis. This study supports the innovative Claudia curve theory between technology and CO2 emissions. Moreover, the study also investigated the Environmental Kuznets Curve (EKC) hypothesis during the study period. The causality analysis also supports the long-run results of DOLS. Based on the results, the study has implications for future researchers, policymakers, and regulatory bodies in developing countries to achieve carbon neutrality and Agenda 2030.

An empirical assessment of the effect of natural resources and financial technologies on sustainable development in resource abundant developing countries: Evidence using MMQR estimation

The present study aims to estimate the role of natural resources and financial technologies in sustainable development under the STIRPAT framework in seven resource abundant developing countries (Brazil, China, Russia, Saudi Arabia, Botswana, Morocco, and Turkey) over 2000 to 2020 period. To conduct empirical analysis, the study applies Fully Modified OLS (FMOLS), Dynamic OLS (DOLS) and Method of Moments Quantile Regression (MMQR). The findings of FMOLS and DOLS indicate the significant positive effect of natural resources and financial technologies on sustainable development in selected countries. These findings are robust in MMQR estimation (with significance of the coefficients varying at different quantiles). Based on these findings, the study recommends the policy makers and governments in these countries to implement effective policies aimed at the continual use and diffusion of financial technologies and efficient extraction and consumption of natural resources.

Dynamics of Digitalisation and its Implications on the Nigerian Financial System Performance

This paper examines the impact of digitalisation on the performance of Deposit Money Banks (DMBs) in Nigeria. Using the Dynamic Ordinary Least Squares (DOLS) method, the results revealed that Web pay, and the Nigeria Inter-Bank Settlement System (NIBSS), Instant Payment (NIP) transactions, have a significant and positive impact on the Capital Adequacy Ratio expressed as a percentage of risk-weighted credit of banks’ exposure. However, Point of Sale (PoS) and Web payments (Web pay) transactions showed a positive, but insignificant impact on the Liquidity Ratio of banks for the period, indicating that both are sources of liquidity in the financial system, but not significant. Also, NIP showed a positive, but not significant impact on the Asset Quality of banks. Further, an insignificant negative effect of PoS transactions and NIP on the profitability of banks in Nigeria was also established. Importantly, mobile payment transactions exerted a positive, significant impact on banks’ profitability during the study period. These findings presuppose those technological innovations in the banking sector of Nigeria’s economy are key to the profitability of banks. Therefore, DMBs in Nigeria should continue to leverage technological innovations, using the various digital banking channels, especially, Web pay, NIP, and mobile payments to boost their performance.