Autoregressive Distributed Lag Estimation Research Articles

Exploring the influence of sustainable regional planning on green economic growth: Evidence from Guangdong-Hong Kong- Macao Greater Bay Area and ASEAN+6

This study explores the influence of mining waste production on green economic growth in the ASEAN+6 and Guangdong-Hong Kong- Macao Greater Bay Area region spanning from 2000 to 2020. Employing ARDL (Autoregressive Distributed Lag) estimation and a comprehensive panel framework, the research reveals a notable adverse correlation: a 1% escalation in mining waste results in a 0.65% decline in green economic growth. Inefficient utilization of resources and inadequate waste management within the mining sector contribute to environmental deterioration, posing challenges to the sustainability of green industries. Furthermore, significant energy consumption from non-renewable sources during mining exacerbates the carbon footprint, obstructing advancements in green energy initiatives. The study also brings attention to a negative association between a 1% rise in inward Foreign Direct Investment (FDI) volume and a 0.39% decrease in green economic growth. To mitigate these unfavorable impacts, the research advocates for the promotion of sustainable FDI, the incentivization of green investments, and the implementation of rigorous environmental regulations.

The impact of personal remittance and RMG export income on income inequality in Bangladesh: evidence from an ARDL approach

PurposePersonal remittance and ready-made garments (RMG) export incomes have emerged as the largest source of foreign income for Bangladesh's economy. The study investigates their impact on income inequality and gross domestic product (GDP) as a control variable, using time-series yearly data from 1983 to 2018.Design/methodology/approachIt employs the Autoregressive Distributed Lag (ARDL) estimation and the Toda-Yamamoto (T-Y) causality approach. The ARDL estimation outcomes confirm a long-run association among the above variables and validate the autoregressive characteristic of the model.FindingsPersonal remittances positively contribute to reducing the income gap among the people of the society and declining income inequality. In contrast, RMG export income and economic growth contribute to further income inequality. The T-Y causality analysis follows the ARDL estimation outcomes and authenticates their robustness. It reveals a feedback relationship between remittance inflow and the Gini coefficient, unidirectional causalities from RMG export income to income inequality and economic growth to income inequality.Research limitations/implicationsThe finding has important policy implications to limit the income gaps between low and high-income groups by channeling incremental income to the lower-income group people. The policymakers may facilitate further international migration to attract further remittances and may upgrade the minimum wage of the RMG workers.Originality/valueThe study is original. As far as the authors' knowledge goes, this is a maiden attempt to investigate the impact of personal remittances and RMG export income on income disparity in the case of Bangladesh.

Energy consumption and innovation-environmental degradation nexus in BRICS countries: new evidence from NARDL approach using carbon dioxide and nitrous oxide emissions.

The BRICS nations-Brazil, Russia, India, China, and South Africa-have grown significantly in importance over the past few decades, playing a vital role in the development and growth of the global economy. This expansion has not been without cost, either, since these countries' concern over environmental deterioration has risen sharply. Both researchers and decision-makers have focused a lot of attention on the connection between economic growth and ecological sustainability. By using nonlinear autoregressive distributed lag (NARDL) approach, the complex relationships were analyzed between important economic indicators-such as gross domestic product (GDP), ecological innovations (EI), energy consumption (ENC), institutional performance (IP), and trade openness (TOP)-and their effect on carbon emissions and nitrous oxide emissions in the BRICS countries from 1990 to 2021, this study seeks to contribute to this important dialog. Principal component analysis is formed for technological innovations and institutional performance using six (ICT service exports as a percentage of service exports, computer communications as a percentage of commercial service exports, fixed telephone subscriptions per 100 people, internet users as a percentage of the population, number of patent applications, and R&D expenditures as a percentage of GDP) and twelve (government stability, investment profile, socioeconomic conditions, internal conflict, external conflict, military in politics, control of corruption, religious tensions, ethnic tensions, law and order, bureaucracy quality, and democratic accountability) distinct indicators, respectively. The results of nonlinear autoregressive distributed lag estimation show that increase in economic growth would increase carbon dioxide and nitrous oxide emissions. The positive and negative shocks in trade openness have positive and significant impact on carbon dioxide and nitrous oxide emissions in BRICS countries. Furthermore, the positive shock energy consumptions have positive and significant effect on Brazil and India when carbon dioxide and nitrous oxide emissions are used. However, EKC exists in BRICS countries when carbon dioxide and nitrous oxide emissions are used. According to long-term estimation, energy consumption and technological innovations in the BRICS countries show a strong and adverse link with nitrous oxide and a favorable relationship with carbon dioxide emissions. In the long run, environmental indicators are seen to have a major and unfavorable impact in BRICS nations. Finally, it is proposed that BRICS nations can assure environmental sustainability if they support creative activities, enhance their institutions, and support free trade policies.

Credit Financing and Agricultural Development in Nigeria

This study investigates the short-run dynamics and long-run link between credit financing offered by Deposit Money Banks (DMBs) and agricultural development in Nigeria for a period of 1981 to 2020. A quantitative ex-post facto research design was employed to analyze bank credit impact on agricultural advancement at both aggregate and sub-sectoral agricultural production. The research strategy utilized allows the use of economic series obtained from Central Bank of Nigeria Statistical Bulletin (2021) and World Bank Development Indicators (2021) to be analyzed by Autoregressive Distributed Lag (ARDL) estimation technique. From ARDL estimations, it is indicated that DMBs loans and advances have significantly negative short-run impacts on agricultural development in Nigeria at both aggregate and sub-sector levels. However, Bounds Testing analysis shows that the impacts of DMBs financing on Nigeria agriculture sector and labour employment in the sector become positively significant over a long period at aggregate level and for crop production only as a sub-sector. But the observed positive long-run impact of DMBs lending to agriculture was not significant for advancement of other sub-sectors (livestock, fishing and forestry). Hence, the study affirms that in the short run DMBs lending significantly slow down agricultural development in Nigeria but increases it significantly in the long run. The study recommends that there is need for agricultural policy makers and governments in Nigeria to develop appropriate specific agricultural financing mechanism that can aid performance of agricultural sector in the short-run and maintain long-run positive gains in the sector.

Catalysts of Economic Welfare in Africa: A Cross-Sectional Autoregressive Distributed Lag Approach

Abstract This study provides empirical perspectives on the catalysts of economic welfare in Africa, drawing inference from macroeconomic and non-macroeconomic factors. Leveraging a sample of a balanced panel dataset of 35 countries across Africa, this study provides novel applications of the cross-sectional autoregressive distributed lag methodology to economic welfare analysis in Africa. Issues of cross-sectional dependence and slope homogeneity were accounted for whilst establishing causal relationships between economic welfare proxied by the Human Development Index and macroeconomic and non-macroeconomic drivers of welfare. Based on cross-sectional autoregressive distributed lag estimation results, a 1% increase in economic growth was shown to account for a 0.233 percent and 0.253 percent increase in economic welfare in the long run and short run respectively. In addition, technology accounted for a 1.81 percent increase in economic welfare in the long run. The outcome of the Dumitrescu–Hurlin causality test demonstrated causality between trade openness, government effectiveness, economic growth, and economic welfare.

The impact of green quality of the energy consumption on carbon emissions in the United States

This paper investigates the impact of energy consumption’s Green Quality Index (GQI) on carbon dioxide (CO2) emissions in the United States from 1970 to 2021. At this point, the estimated models control for the effects of gross domestic product (GDP) per capita, urban population, and globalization on CO2 emissions. The Autoregressive Distributed Lag estimations demonstrate that GQI and globalization reduce CO2 emissions in the short- and long run. However, GDP per capita and urban population are positively related to CO2 emissions in the short- and long-run. Different estimation techniques confirm the long-run baseline findings. Potential policy implications for reducing CO2 emissions in the United States are also provided.

Estimating the health production function for Pakistan: Do environmental factors matter?

AbstractIt is essential for sustainable economic development to comprehend how environmental factors impact public health. This study analyses this relationship in the context of Pakistan using long‐term data. This study aims to determine how environmental factors influence health production function in Pakistan to enlighten policy decisions that can improve human life and advance the cause of sustainable development. We hypothesize, based on prior research, that urbanization and rainfall will increase life expectancy in Pakistan, while deforestation, temperature, and CO2 emissions will decrease it. To verify our theory, we use the autoregressive distributed lag (ARDL) method to calculate the long‐run association between the variables, as well as the Zivot–Andrews and Lee–Strazicich unit root tests to identify structural breaks. Utilizing the bound and Gregory–Hansen co‐integration tests, co‐integration is confirmed. According to ARDL estimates, there are statistically significant correlations between factors that affect Pakistan's life expectancy, such as deforestation, temperature, and CO2 emissions, as well as rainfall and urbanization. The findings of this study underscore the importance of addressing environmental degradation and deforestation in Pakistan. For enhancing human life and achieving sustainable development objectives in the nation, it is essential to modernize forest laws and regulations and adopt eco‐friendly technologies.

Renewable energy deployment in Europe: Do politics matter?

AbstractThis study analyzes non-hydroelectric renewable capacity across 27 European countries from 2000 to 2020, using advanced econometric techniques like the Dumitrescu and Hurlin panel Granger non-causality method, Panel Autoregressive Distributed Lag and Panel Quantile Autoregressive Distributed Lag estimations. This investigation reveals complex relationships extending beyond immediate variables. These relationships, rooted in pairwise causalities and broader interactions, underpin observed phenomena. Causality tests show that achieving non-hydroelectric renewable capacity is a long-term endeavor, emphasizing persistent policy approaches for effective energy transition. Three key variables emerge as potent policy drivers: maintaining an environment conducive to economic freedom, fostering financial development, and driving non-hydroelectric renewable patents’ research and development. These variables play a pivotal role in capacity expansion. Additionally, the findings of this empirical investigation spotlight the role of political orientations. Leftist governments have lagged in prioritizing energy transition, prompting questions about neglecting environmental concerns and necessitating comprehensive policy reform. In essence, this study offers novel insights into non-hydroelectric renewable energy deployment. By unraveling complex relationships, emphasizing persistent policies, and identifying key variables, this investigation provides a nuanced perspective in line with sustainable energy transition urgency. As global ecological imperatives heighten, our work guides informed policy decisions for a greener future.

THE EFFECT OF INFORMAL ECONOMY ON HUMAN CAPITAL DEVELOPMENT

This study investigated the effect of the informal economy on human capital development and the direction of causality between informal economy and human capital development in Nigeria from 1970 to 2019. The study objectives were achieved by analysing annual time series data sourced from the World Development Indicators and Central Bank of Nigeria using the autoregressive distributed lag estimation technique and the Toda-Yamamoto causality test. Findings from the study showed positive long-run effect of informal economy on human capital development. The result from this study also revealed unidirectional causality flowing from informal economy to human capital development. Consequently, this study concluded that engagement in informal economic activities is beneficial to human capital development in Nigeria. Following these findings, Nigerian policy makers aiming to achieve human capital development should implement comprehensive policies which facilitate the competitiveness and growth of informal economic activities.

Financial technology development: Implications for traditional banks in Africa

The speed of financial technology (Fintech) adoption in delivering financial services has raised concerns among researchers on the future of traditional banks, especially as authors believe that Fintech comes with both prospects and problems. This study therefore aims to examine the growth, measurements, and the impact of Fintech on traditional banks in a panel of sixteen African countries for the period 1800–2020. These periods were divided into three phases: the analogue (1800–1967), the digital (1967–2008), and the modern phases (2008–2020). The autoregressive distributed lag (ARDL) and descriptive analyses methods were used to investigate the study’s objectives. It found that the analogue era witnessed the birth of Fintech ideas, while the digital era witnessed structural changes within the financial system. Results from the pooled mean group ARDL estimation technique based on the third/modern era reveal that, on average, a unit increase in Fintech adoption significantly reduces bank profitability (ROA) by 12.6%. Hence, although early Fintech adoption poses no threat to bank profitability; however, beyond certain threshold, its continuous adoption reduces profitability. Again, the speed of adjustment at 90.9% per annum is an indication that short-run Fintech disruptive impact/disequilibrium is corrected within one year and one month. The Principal Component Analysis used to generate Fintech index shows that African Fintech’s operation is more susceptible to changes in mobile banking. The study concludes that too much Fintech adoption is unhealthy for traditional banks in Africa and therefore it recommends that Fintech should collaborate with banks to correct for its disruptive impacts.

Testing the effects of banking development, economic growth and foreign direct investment on renewable energy in South Africa

AbstractThe world's climate‐related policies need to be revised to combat environmental issues. Therefore, adopting renewable energy technologies in conjunction with energy efficiency measures are needed to make safe pathways to reduce over 90% of energy related CO2. In this context, this study intends to assess the influence of foreign direct investment (FDI), economic growth, and banking and development on renewable energy consumption in South Africa from 1970 to 2020. The study uses a novel ‘bootstrap Autoregressive Distributed Lag (ARDL)’ testing to empirically analyse the short and long links among the tested variables. The ARDL estimations demonstrate a FDI and economic growth have positive effect on renewable energy consumption. Furthermore, the outcomes reveal that banking sector development affects positively renewable energy use in long run. Therefore, it is suggested that government and playmakers of South Africa must make more efforts to link the economic and baking development with renewable energy by investing capital and funds in renewable energy infrastructure. It will not only boost the economy of the country but also provide an opportunity to clean and green the environment with decreasing rate of greenhouse gases emission like carbon dioxide.

Understanding Short-Term and Long-Term Price Fluctuations of Main Staple Food Commodities in Aceh Province, Indonesia: An ARDL Investigation

Aceh Province still relies on external sources from other regions for its main staple food commodities, resulting in unpredictable price fluctuations. To address this issue, it is essential to identify the key determinants responsible for these fluctuations and implement suitable preventive measures and policies. Utilizing monthly time-series data from January 2016 to December 2020 and employing the Autoregressive Distributed Lag (ARDL) approach, we investigate the short-term and long-term impact of variables like raw material prices, rainfall, and price index received by farmers on the price fluctuations. The results of the ARDL estimation reveal that all selected independent variables play a crucial role and significant in influencing the price fluctuations of main staple food commodities. Armed with these findings, we suggest that policymakers can provide necessary resources to farmers, strengthen weather monitoring systems, and enhance market transparency, thus better controlling future price fluctuations of regional staple food commodities.

Modeling The Effects of Climate Change on Food Production in Ivory Coast: Evidence from ARDL Approach

There is a direct link between global warming and hunger in emerging West African nations like Ivory Coast, where the population is overgrowing, and food insecurity is rising. This work aims to examine and explore climate change's effects on agriculture production in Ivory Coast from 1990 to 2019. Various stationarity tests, including the Phillips-Perron (PP) and the Augmented Dickey-Fuller (ADF), are applied to determine the variables' order of integration. The autoregressive distributed lag (ARDL) approach is employed to model the long- and short-run relationships between temperature, rainfall, carbon dioxide emissions, domestic credit, gross capital formation, and agriculture sector and subsectors. The present study uses the Johansen cointegration test to verify the long-run cointegration of the ARDL estimation. The findings reveal that all the variables are integrated into order zero or one. Cointegration tests demonstrate a valid long-term association between the variables. Agriculture and related subsectors in Ivory Coast were found to benefit from increasing temperature over the long run, except for the fishery subsector, where the impact is negligible. In the short run, temperature’s effect is positive on aggregate agriculture, although it is not statistically significant. Its effect is beneficial to agriculture's subsectors, except for fishery production. In both runs, Ivory Coast’s aggregate agriculture sector and fishery subsector are negatively affected by rainfall. An insignificant favorable effect of rainfall is found on crop production in both runs. The estimated results indicated that the role of CO2 is positive on agriculture and crop production in both run estimations. However, CO2 does not impact livestock production. It has a long-term positive influence on fishery production but no effect in the short run. Domestic credit is found to have a beneficial influence on agriculture and its subsectors in both runs, except for crop and livestock production, where the effect is negative and insignificant in the short run. Gross capital formation negatively impacts agriculture and its subsectors in Ivory Coast, except crop production, where it only has an insignificant beneficial effect in the short run. The same is true for fishery production, which only had a significant favourable impact effect in the short run. For the government and policymakers, the findings guide the formulation of suitable policies to address global warming's effects on agriculture and guarantee sustainable food production for the increasing population.

Analysis of Trade Openness and Macroeconomic Variables on Foreign Direct Investment in Indonesia for the Period 1980-2022

This study analyzes trade openness and macroeconomic variables on foreign investment in Indonesia. This study uses Indonesian time series data from 1980 to 2022. The data analysis technique uses the Autoregressive Distributed Lag (ARDL) method. Data were analyzed using data stationarity test, optimal lag test, CUSUM test, classical assumption test, cointegration test and ARDL estimation processed with Eviews 10. The results showed that indirect trade openness has a positive and significant effect on Foreign Direct Investment (FDI) in the short term and long term. The exchange rate (IDR to USD) has a negative and significant effect on Foreign Direct Investment (FDI) in the short and long term. Inflation rate in the short term has a positive and significant effect but in the long term has a negative and insignificant effect on Foreign Direct Investment (FDI). GDP has a negative and significant effect in the short term but in the long term has a significant positive effect on Foreign Direct Investment (FDI).

Energy productivity and environmental degradation in the Netherlands: evidence from the novel Fourier-based estimators.

Due to the incessant quest for economic growth, global energy demand has increased to a level that requires urgent rethinking. The Netherlands depends heavily on traditional energy sources, which are finite and equally emit a lot of greenhouse gasses, causing further environmental destruction. To sustain economic growth and protect the ecosystem, it is crucial for the Netherlands to consume energy efficiently. Given that policy directions are required, this paper investigates the effect of energy productivity on environmental degradation in the Netherlands between 1990Q1 and 2019Q4, using the Fourier ARDL (autoregressive distributed lag) and Fourier Toda-Yamamoto causality approaches. The Fourier ADL estimates indicate that all variables are cointegrated. Additionally, the long-run Fourier ARDL estimates indicate that investments in energy productivity could help reduce carbon dioxide emissions in the Netherlands. Furthermore, the Fourier Toda-Yamamoto causality outcomes suggest that energy productivity, economic growth, and renewable energy consumption have a unidirectional causal effect on CO2 emissions. These revealing outcomes provide significant policy insights for the Netherlands' energy productivity objectives in their new energy policy proposed in 2022. The government could, through the new energy policy, increase investment in smart meters and review existing fossil fuel subsidies and energy trade taxes. Additionally, the government could consider reviewing the Netherlands' economic structure by increasing the share of the primary and tertiary sectors to the rising economic growth to reduce energy consumption.

An Investigation of Tourism, Economic Growth, CO2 Emissions, Trade Openness and Energy Intensity Index Nexus: Evidence for the European Union

Tourism has become one of the most important sectors in many countries, significantly contributing to their economic growth and development. However, the expansion of tourism has also brought about various environmental and social challenges. The relationship between tourism, economic growth, trade openness, and the environment is diverse and complex. The objective of this paper is to investigate the relationship between the international tourism development index, GDP per capita, CO2 emissions, trade openness index as well as the energy intensity index in EU 27, over the 1995–2019 period. A composite index for international tourism was developed using the Principal Component Analysis (PCA). Panel Autoregressive distributed lag (ARDL) approach is used to reveal the long- and short-run impact of GDP per capita, CO2 emissions, trade openness index as well as the energy intensity index on the tourism development index. Panel ARDL estimates confirm some of our research hypotheses: at the level of EU countries, there is a short-run relationship between tourism and GDP per capita, but only in a few EU countries, trade openness influences tourism development index. Dumitrescu-Hurlin causality test confirms long-run feedback relationship between tourism development index and trade openness, between tourism development index and CO2 emissions, and between tourism development index and GDP and unilateral causality running from tourism development index towards energy efficiency.

Digitalization of logistics for transition to a resource-efficient and circular economy

In this research, employing the ARDL (Autoregressive Distributed Lag) estimation technique, the impacts of the digitalization of logistics on the efficiency of natural resource deployment and depletion are measured for the case of China from 1990 to 2021. The results confirmed that in the short term, the enterprise digital transformation index does not have significant coefficients, and the total factor productivity of logistics accelerates the effectiveness of natural resource consumption in China. In the long term, the enterprise digital transformation index and the total factor productivity of logistics have positive and significant coefficients. The role of the information technology factor as a mediating variable on natural resource utilization efficiency is positive in China. The paper brings new insights with various policy implications like establishing a regional digital logistics network, expanding digital green financing markets, and planning to make balanced digitalization of logistics throughout China for scholars and policymakers.

Impact of Entrepreneurship and International Trade on Economic Growth and Development in Nigeria

This study empirically investigates the impact of entrepreneurship and international trade on economic growth and development in Nigeria from 1990 to 2022. Domestic credit to private sector (DCPS), Exchange rate (EXR), Self-employment (SEEM), Total exports ((TEX), Total imports (TIM) and inflation rate (INFR)were used as dimensions of the independent variable while Real gross domestic product (RGDP) as the dependent variable. Annual time series data were obtained from secondary sources including the CBN annual statistical bulletin, World Bank development indicators. The Eview9 Statistical Software was employed to analyze the data empirically. The Unit root test shows that real gross domestic product, domestic credit to private sector, exchange rate, self-employment, total exports and total imports are all stationary after first difference I(1) while inflation rate was stationary at level I(0). The data were analyzed using the Autoregressive distributed lag (ARDL). The results of the ARDL estimates indicate that in the long run self-employment and total exports coefficients were positively signed and statistically significant which means that increase in self-employment and total exports in Nigeria will increase real gross domestic product (Economic growth) while total imports turned up with a negative sign and also statistically significant. It portends that total import has a negative impact on economic growth and development in Nigeria in the long run. The study recommends amongst others that government should promote entrepreneurship by providing credit and grants to encourage self-employment. Government should also encourage import substitution, promote exportation of locally made goods as this has positive impact on economic growth and development in Nigeria.

Effects of developmental and non-developmental expenditure on economics growth of India: An error correction model approach

In this article attempt is made to establish the relationship between the developmental and non-developmental expenditure in India and its influence over the economic growth. For this, secondary data are used for the period of 1991-2021 and sourced from various state finance reports, Ministry of Statistics and Programme Implementation, and World Bank, Indian Public Finance Statistics, and annual budget allocation. To check the long-run and short-run relationship among the variables Autoregressive Distributed Lag (ARDL) model, Bound Test and Error Correction Model techniques have been used. The ARDL estimates indicate that in the long-run development expenditure having positive impact over the economic growth, however, it is statistically insignificant. While population growth rate having negative impact over the economic growth. Further, Error Correction Model (ECM) estimates revealed that there is an existence of short-run relationship among the variables too and it is very sensitive, its adjustment rate is about 80 percent and statistically significant at 5 percent level. Therefore, it is suggested to the government to focus more on the short-run goals rather long-run issues because if the problems are address immediately at the time when it arises then it would also assist to achieve the long-run sustainable economic growth.

The Growth Effect of Government Expenditure in Jammu & Kashmir

Purpose : The paper examined the growth impact of aggregate government expenditure and its various components in Jammu & Kashmir using time series data from 1981–2020. At the disintegrated level, the study assessed the growth impact of government expenditure on three different types of services, namely, economic, social, and general. Methodology : The autoregressive distributed lag (ARDL) or bounds cointegration technique was used to explore the long-run relationship (cointegration) between total government expenditure and economic growth. The growth impact of government expenditure on economic, social, and general services was investigated using the regression model. Findings : The study found a cointegrating relationship between aggregate government expenditure and economic growth in the erstwhile state of Jammu & Kashmir. The ARDL estimates showed that total government expenditure impacted Jammu & Kashmir’s economic growth positively and significantly in the short and long run. Furthermore, the estimated regression coefficients revealed that government expenditure on social services impacted economic growth positively and significantly. In contrast, government expenditure on economic and general services had a negative but insignificant growth impact. Practical Implications : The study’s findings would assist the policymakers in prioritizing Jammu & Kashmir’s limited resources for developing sectors with the potential to raise economic growth. The study recommended that government expenditure on social services should be increased to enhance growth in the erstwhile state of Jammu & Kashmir. A compositional change in government expenditure favoring social services from general and economic services would stimulate economic growth in the former state of Jammu & Kashmir. The study’s main limitation is that the other potential growth determinants were not considered explanatory/control variables. Originality : The study provided empirical evidence of the growth effect of total government expenditure and its various types in one of India’s least developed, slow-growing, and resource-deficit states (now Union Territory). To the best of my knowledge, the growth impact of government expenditure on three different types of services (economic, social, and general) were not investigated empirically in Jammu & Kashmir for the period from 1981–2020. The study contributed to the scant empirical literature on the growth impact of government expenditure at the sub-national (state level).