Autoregressive Distributed Lag Model Research Articles

Embracing Technological Advancement: Assessing the Impact of Innovation on Sectorial Employment in Tanzania

Technological innovation is one of the most rapidly advancing and dynamic sector today. It drives growth across all sectors of the economy. However, this rapid growth presents both opportunities and challenges. Taking innovation into account, this study aims to assess the impact of technological innovation on three sectors which are agriculture, industrial, and service sectors. The study employed the autoregressive distributed lag model (ARDL), with data from 2000 to 2022 obtained from the World Bank (WB) and the World Intellectual Property Organization (WIPO). Three ARDL models were used to estimate employment in the agriculture sector, employment in the industrial sector and employment in the service sector with inflation (CPI) and interest rate (INT) as the control variables. The ADF (Augmented Dickey-Fuller) test, PP(Philip-Perron) test, Serial Correlation LM test, BG Heteroscedasticity, and Jarque Bera Normality test were utilized to ensure robust estimates of the models. The findings revealed that innovation has a significant positive influence on employment in the agriculture sector and service sector whereas the industrial sector is negatively influenced by innovation. Nevertheless, inflation has a significant positive effect on employment in the agriculture and service sectors but negatively affects employment in the industrial sector, where a lag in interest rate influence negatively employment in the agricultural sector. Relying on these findings, the study recommends an increase in expenditure on research and development, formulation of policies that will mainstream innovation in all sectors of the economy, and investing more in education and skills development

Impact of Tax-based Revenue on Economic Development in Nigeria, 1999 to 2023

This research measures the contributory impact of Tax-based revenue on economic development in Nigeria, 1999 to 2023, with a specific focus on the nuanced dynamics of oil-based tax (OBT), non-oil-based tax (NOBT), and aggregate tax revenue (ATR). Leveraging comprehensive data extracted from the Central Bank of Nigeria's Statistical Bulletin and Federal Inland Revenue Service (FIRS) database, the study employs the Autoregressive Distributed Lag Model (ARDL) with Gross Domestic Product Growth Per Capital (GDPPC) as the outcome variable. The empirical analysis supports a significant and positive impact of non-oil-based tax revenue on GDPG while the oil-based tax shares no significant impact on economic development. Also, aggregate tax revenue (ATR) was found to negatively but significantly impact on economic development. The study recommends the adjustment of the tax system to address the developmental constraint on investment and consumption posed by taxation while optimizing the benefits that accrue from an efficient and good tax system.

Trade Outwardness and International Financial Flows in Nigeria

This study used the Autoregressive Distributed Lag model to investigate the impact of international financial flows on trade outwardness in Nigeria. With dataset covering the period 1999 – 2023 drawn from the World Development Indicator, which is a repository of the World Bank, official development assistance (ODA), Foreign portfolio investment (FPI) and foreign direct investment (FDI) were used as proxies for international financial flows. The quotient of the sum of export and import over gross domestic product represented trade outward which found to positively and significantly respond to changes in ODA and FPI and insignificantly and negative respond to FDI. It is recommended that trade outwardness should be tailored in the direction of international financial flows while harnessing the benefits of trade and mitigating the adverse effects of trade relations. This can be done through protective import strategies and export promotion methods.

An Exploration of the Relative Influence of the Determinants of the Mexican Peso - U.S. Dollar Exchange Rate

This article examines the impact over time of the government’s primary balance, remittances, foreign direct investment expectations, and real interest rates on the Mexican peso to US dollar exchange rate between 2003 and 2023, using monthly and quarterly data. An autoregressive distributed lag model with bounds testing and a Granger non-causality test are employed. The results indicate that, although the significance of all variables changes over time, foreign direct investment expectations and the government’s primary balance influence the exchange rate throughout the entire period. Foreign direct investment expectations and remittances exert the most persistent long- and short-run influence, respectively. The evolving significance across time of these determinants implies the need of a dynamic and adaptable policy framework to currency stability in Mexico.

Assessing effects of agriculture and industry on CO2 emissions in Bangladesh

Climate change is a critical global issue, driven primarily by the continuous rise in carbon dioxide (CO2) levels. Addressing this challenge requires innovative solutions and proactive measures to mitigate its impact. This study investigates the impact of Bangladesh’s industrialization, agriculture, and imports on CO2 emissions, exploring both linear and asymmetric relationships to inform sustainable development strategies. Advanced modeling techniques, namely autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL) models are used to evaluate the impact of Bangladesh’s agricultural and industrial sectors on CO2 emissions. Time-series data ranging from 1990 to 2022 are analyzed to ensure data stationarity, employing the augmented Dickey-Fuller (ADF) test. Subsequently, the existence of non-linear associations is validated using the Brock-Dechert-Scheinkman (BDS) test, with further confirmation through bounds testing to establish both symmetric and asymmetric long-run cointegrating relationships. Long and short-run coefficients are assessed using linear and asymmetry ARDL models, revealing that industrialization contributes to increased carbon emissions in Bangladesh. While the ARDL model reports that the effect of agriculturalization on CO2 emissions is insignificant in the long-run, the asymmetry ARDL model suggests a rapid reduction in carbon emissions due to agriculturalization, observed both in the long and short-run. Additionally, imports have considerable impact on carbon emissions. Diagnostic tests have confirmed the adequacy of the model, while stability tests have validated the estimated parameters’ stability. Finally, the direction of association between variables is determined by applying linear and nonlinear Granger causality tests. This study underscores the importance of promoting sustainable industrial practices, enhancing agricultural efficiency, and regulating imports as pivotal strategies for mitigating CO2 emissions and achieving enduring environmental sustainability in Bangladesh.

Impact of Environmental Degradation on Economic Growth: Testing the Environmental

Looking at the contribution of economic activity in the country, it is seen to add robustness to growth and development, but in contrast give birth to greenhouse gases (GHGs), such as CO2 CO2 which is also called carbon dioxid, CH4 which is also called methane, and N2O represent nitrous oxide. The factors influencing Greenhouse gas emissions include rising of population, upward movement of per capita output and consumption, infrastructural development made about infrastructures, human character, and innovation. However, if mitigation efforts are not enough, climate change would most likely lead to a slowdown the upward movement. Thus, the study examined the relationship between economic growth and environmental degradation using the Autoregressive Distributed Lag model and examined the impact of environmental degradation on economic growth in Nigeria from 1990 to 2022 using that lens. Based on the estimated ARDL regression result, environmental degradation as determined by carbon dioxide emissions (kt) and economic growth are negatively correlated. The negative indication indicated that economic growth will decline by roughly -0.455% and -0.893% over the medium and long terms, respectively, as carbon emissions rise. The findings indicated that there is validity to Nigeria’s Environmental Kuznets Curve, which demonstrates how environmental deterioration impedes economic progress. Similarly, a positive indication indicating a one-period lag in carbon emissions showed that, in the short term, economic growth increases by around 0.948% in tandem with rising carbon emissions. Thus, the paper illustrated an inverse U-shaped interaction between environmental degradation and economic growth, with healthy economy initially related with increased emissions. However, the majority of the control variable estimates deviate from theoretical expectations. On the other hand, a positive and statistically significant one-period lagged coefficient of trade openness suggests that trade openness looks to support and encourage economic growth in the short run. Similarly, during the period under consideration in Nigeria, the short-run economic growth is positively and strongly correlated with the one-period lagged coefficient of gross fixed capital formation. The report suggested boosting energy efficiency in the world’s energy mix in order to lower greenhouse gas emissions, which are the main contributors to climate change. Therefore, in order to prevent the development of closed-form relationships that could result in a slowdown in economic growth, Nigerian government agencies that are responsible for implementing national and international environmental rules should proceed with caution.

The legal foundations and specifics of exercising corporate rights by individuals authorized to perform local self-government

Financial liberalization is a widely adopted policy for countries to enhance growth. Financial liberalization enables financial institutions to proceed with innovative activities by familiarizing themselves with fewer mortgage loans in the financial market. Financial liberalization is a widely adopted policy for countries to enhance growth; however, it is a complex and controversial issue, with different studies providing contrasting perspectives. Financial liberalization is considered an efficient way to measure and change the financial market and structure in order to reach a position to get financial liberalized markets under an efficient and effective guideline. In the case of Vietnam, very few scholars have investigated the issue of financial liberalization-led growth. This endeavor examines the effects of financial liberalization on economic growth in the presence of control variables for Vietnam over the period of 1990 to 2021. This study uses the Autoregressive Distributive Lag Model approach due to its several advantages. The results show that financial liberalization enhances economic growth, which implies that more liberalization results in enhanced growth in Vietnam. Improved access to credit is another positive outcome of financial liberalization, as it can result in greater access to credit for individuals and businesses, enabling them to make investments and expand their operations. Hence, the results support the neo-liberal view of liberalization.

The Impact of Climate Change on Zero Hunger in South Asia

Climate change has raised ample concerns about achieving zero hunger. The goal of the study is to investigate the link between climate change and eradicating hunger in Asian nations. The data span is from 2001 to 2020 from World Bank and KOF. The effect was investigated using the Pool Mean Grouped/Panel Autoregressive Distributed Lag Model which shows that climate change, both in the short-run and long-run, hinders progress toward achieving zero hunger. The conclusion shows that in the long run, a rise in per capita income, globalization, and labor force participation boosts the progress towards achieving zero hunger but, in the short run, per capita income has a significant effect, and globalization and labor force participation have an insignificant effect on zero hunger. Finally, this study offers some recommendations to achieve zero hunger.

The influence of climate change on crop production: Evidence from Somalia

The study examines the effect of climate change on crop production in Somalia for the period 1990 to 2022 obtained from the World Bank and FAOSTAT. Initial assessments were conducted on the data using various techniques, including the Correlation Matrix, Augmented Dickey-Fuller test, and Phillips-Perron unit root test. The findings from both the Bounds test and Johansen test demonstrate the existence of cointegration within the model. To estimate the parameter values of the regression model, three methods were employed: the Autoregressive Distributed Lagged (ARDL) model, Dynamic Ordinary Least Squares (DOLS), and Fully Modified Least Squares (FMOLS). The study's results demonstrate a positive and significant influence of foreign direct investment (FDI) on crop production. Specifically, the impact of FDI is found to be more pronounced in the long term compared to the short term. Similarly, the study finds that the harvested area and labor force have substantial positive impacts on crop production, both in the short run and long run. Based on the ARDL model results, the study finds that rainfall and temperature do not have a beneficial influence on crop production in both the short run and long run. This is becuase, Somalia is considered as one of the most susceptible countries to the effects of climate change globally. The paper advises Somalia's government to focus on developing heat-resistant crops to counter the opposing effects of temperature on crop production and ensure food security. It also requires a comprehensive agriculture funding-framework including emergency assistance.

Vietnam's exports to Korea and the real exchange rate: Post-crisis evidence from the multiple threshold nonlinear autoregressive distributed lag model

In this study, the asymmetric effects of the real exchange rate on Vietnam's exports to Korea were investigated using the multiple threshold nonlinear autoregressive distributed lag (MTNARDL) model. As a result, the MTNARDL model exhibited enhanced estimation accuracy compared to the single-threshold nonlinear autoregressive distributed lag (NARDL) model. Furthermore, the aggregate bias problem was solved using individual export data for 16 major industries instead of relying on the overall export value data. The results revealed the substantial asymmetric impact of real exchange rate fluctuations in the short and long run. Fluctuations in the real exchange rate boosted Vietnam's exports to the Republic of Korea in the long run, with minimal negative influence. This indicates that the depreciation of the Vietnamese dong against the United States (US) dollar encouraged exports in some industries but limited exports in others. However, the short-term effect of the real exchange rate remains uncertain, as it could be either negative or positive depending on the industry and threshold level. The diverse impacts of the real exchange rate fluctuations on exports across industries were attributed to factors such as the capacity to absorb foreign exchange risks, product heterogeneity, and the ease of adjusting inputs and production for each sector. Therefore, these findings may help policymakers develop Vietnam-specific policies to address long- and short-term changes in the threshold levels of real exchange rate fluctuations.

Financial inclusion in Morocco: the impact of financial development, financial innovation and economic growth

The relationship between financial inclusion, social development, particularly poverty reduction, financial innovation and economic growth has been endorsed by a number of studies. Indeed, the development policies pursued by countries such as Morocco often define financial inclusion, growth, financial development, financial innovation, monetary policy and investment as fields of action for economic and social development. The aim of this study is to assess this choice by examining the short- and long-term relationship between financial inclusion, financial development, financial innovation, growth, inflation and the interest rate. Using the ARDL (AutoRegressive Distributed Lag) model and the Granger causality test, the results show the positive short- and long-term effect of financial development and financial innovation on financial inclusion, and the positive short- and negative long-term effect of economic growth on financial inclusion. The inflation and the interest rate that represents monetary policy influence financial inclusion in the short and long term positively and negatively respectively. In terms of causality, the granger test shows that economic growth has an effect on inclusion in only one direction and that financial inclusion has an effect on financial development in only one direction. On the other hand, innovation, inflation and the interest rate have a bidirectional relationship with financial inclusion.

The Impact of Climate Change on Rice Production in Punjab: An Auto Regression Distributed Lag Model

The Impact of Climate Change on Rice Production in Punjab: An Auto Regression Distributed Lag Model

Interplay of Foreign Direct Investment, Remittances, and Economic Growth: Insights from SAARC Countries

The current study focuses on finding and analyzing the nexus between remittances, foreign direct investment, and economic growth in SAARC countries. This study uses secondary balanced data of selected SAARC countries for the years 2000 to 2019. This study uses gross domestic product i.e., GDP, which serves as the proxy of economic growth, as the dependent variable. The core independent variables of this study include (FDI) foreign direct investment and remittances (RMTN). Additionally, gross capital formation (GCF) and carbon dioxide emissions (CO2) are the other two independent variables in this study. For the proxy for environmental degradation the study uses data of CO2 emissions. The data is collected from the world development indicators, WDI. The study focuses on how all the independent variables affect the growth of economy in selected SAARC countries which include Pakistan, India, Bangladesh, Sri Lanka, and Nepal. The study applies cross sectional dependence test, panel cointegration test, unit root tests, and PARDL (panel auto regressive distributed lag model), also called pooled mean group methodology, to obtain empirical estimates. The results of PARDL show that FDI, RMTN, and GCF are all positively and significantly related to GDP. This means that GDP or alternatively economic growth, is improving with rise in FDI, RMTN, and GCF in selected SAARC countries. The results show that CO2 emissions have a negative significant impact on GDP i.e., increase in pollution levels is harmful for the growth of the selected economies.

Can environmental taxes and green technological investment ease environmental pollution in China?

This study examines the complex relationship between environmental taxation, green technology, green investment, real GDP, and environmental pollution by employing the Nonlinear autoregressive distributive lag model for China. The findings indicate that environmental tax policies have significant short- and long-term effects, with positive shocks leading to pollution reductions. The positive and negative shocks to green investment increase pollution levels in the long run. Moreover, the real GDP displays pollution reductions in the short run. The results provide valuable insights into China's environmental and economic situation and offer policy recommendations. These findings were confirmed using the Wald test. The findings emphasize China's need for stronger environmental taxes, green technology adoption, evaluated green investments, and sustainable economic growth to achieve cleaner production and environmental sustainability.

COVID-19 and Uncertainty Effects on Tunisian Stock Market Volatility: Insights from GJR-GARCH, Wavelet Coherence, and ARDL

This study rigorously investigates the impact of COVID-19 on Tunisian stock market volatility. The investigation spans from January 2020 to December 2022, employing a GJR-GARCH model, bias-corrected wavelet analysis, and an ARDL approach. Specific variables related to health measures and government interventions are incorporated. The findings highlight that confirmed and death cases contribute significantly to the escalation in TUNINDEX volatility when using both the conditional variance and the realized volatility. Interestingly, aggregate indices related to government interventions exhibit substantial impacts on the realized volatility, indicating a relative resilience of the Tunisian stock market amidst the challenges posed by COVID-19. However, the application of the bias-corrected wavelet analysis yields more subtle outcomes in terms of the correlations of both measures of volatility to the same metrics. Our econometric implications bear on the application of such a technique, as well as on the use of the realized volatility as an accurate measure of the “true” value of volatility. Nevertheless, the measures and actions undertaken by the authorities do not exclude fear and insecurity from investors due to another virus or any other crisis. The positive and long-term impact on the volatility of US equity market uncertainty, VIX, economic policy uncertainty (EPU), and the infectious disease EMV tracker (IDEMV) is obvious through the autoregressive distributed lag model (ARDL). A potential vulnerability of the Tunisian stock market to future shocks is not excluded. Government and stock market authorities should grapple with economic and financial fallout and always instill investor confidence. Importantly, our results put mechanisms such as overreaction to public news and (in)efficient use of information under test. Questioning the accuracy of announcements is then recommended.

Exploring the impact of oil revenue on Nigeria's economic growth: A non‐linear autoregressive distributed lag model

AbstractThe influence of oil proceeds on an economy remains a subject of debate among scholars. Most scholars agree that income from oil has direct effect on economic expansion. We explore the impact of revenue from oil on economic growth in Nigeria from 1986 to 2016. Data were collected from the Nigerian Central Bank and the World Data Indicators. We employed a non‐linear autoregressive distributive lag approach to analyse the data. The outcome exposes a direct and significant association between revenue from oil and GDP both in the short and long term. Trade openness exhibits a significant negative effect on GDP from both short‐ and long‐term perspectives. Gross capital formation directly influences GDP in the short and long run, with significant impacts primarily in the long term. The study suggests that revenue from oil has a direct and significant impact on the Nigerian economy during the period from 1981 to 2016. We recommend that the Nigerian government create a conducive environment for private investment to thrive, thereby sustaining the nation's growth potential. Additionally, the government should wisely utilise revenue from oil to revitalise non‐booming productive sectors in the economy, thus diversifying revenue sources.

An Analysis of the Impact of Seaport Efficiency on Nigeria’s Economic Growth.

This research is driven by the objective to assess the impact of the seaport efficiency on Nigeria’s economic growth. The western ports of Lagos are selected as the Decision-Making Units (DMU) for this study covering the period of 2000 to 2020. Two stage estimation process is employed. Data Envelopment Analysis (DEA) was deployed in the first stage to generate the efficiency index required to test the relationships. In the second stage, the efficiency index so generated is introduced as one of the independent variables in a multiple regression model, using Autoregressive Distributed Lag Model (ARDL). The finding shows that seaport efficiency has a negative but significant relationship with economic growth in both the long run and short run. The study concludes that seaport efficiency has an inverse relationship with Nigeria’s economic growth. The result of this study suggests that reforms may not have deepened the level of efficiency in the Nigerian seaport to drive positive economic growth, hence the recommendation for further investment in the terminal operational equipment and technological infrastructure to drive further efficiency in the sector.

Investigating Factors Affecting Renewable and Nonrenewable Electricity Generation in Iran

This study identifies key elements that facilitate the transition of power generation from non-renewable to renewable sources. Annual data from 1977 to 2018 and an autoregressive distributed lag model are used in the study. The gross domestic product, industrialization, urbanization, fuel, and power prices, as well as the dollar exchange rate, are employed as independent variables. The study takes the Iran-Iraq War and nuclear sanctions into account. The findings show that, in the short run, all variables—aside from the exchange rate—have an impact on the generation of electricity from renewable sources. Only natural gas prices, industrialization, and gross domestic product are effective in the short run, for power generation from non-renewable energies. In the long run, all variables, with the exception of electricity price, are effective in producing power from renewable sources, and all variables, with the exception of fuel prices and industrialization, are effective in producing electricity from non-renewable sources. The findings also indicate that nuclear sanctions have a detrimental impact on the production of electricity from renewable sources and a beneficial impact on the production of electricity from non-renewable sources.

The Relationship between Geopolitical Events and the Crude Oil Prices: An Application of ARDL Model

This paper aims to explore the short-run and long-run relationship between geopolitical events and crude oil prices for the period 2000-2023. In addition to geopolitical events, we included the market factors whose data were available in the right part of the equation. To investigate long-run cointegration, this paper used quarterly data and employed the Autoregressive distributed lagged (ARDL) bounds testing approach developed by (Pesaran et al., 2001). Study findings from the ARDL bound testing approach confirm the existence of a long-run and short-run association between geopolitical events and crude oil prices. Furthermore, the findings from the ARDL model revealed that, among others, world crude oil production; OECD’s crude oil stocks, and OECD economic growth have a significant effect on the dependent variable (crude oil prices) both in the long run and short run.

Globalization, Migration, and Economic Growth in Nigeria

The study aimed to empirically examine the effect of globalization and migration on Nigeria's economic growth. The study covered the period 33 years (1990 – 2022). The variables used in the study are foreign direct investment, trade openness, foreign exchange rate, remittances, and gross domestic product. The ARDL (autoregressive distributed lag) model was employed for the study and a long-run relationship was established. Findings revealed that remittance had a significantly positive effect on Nigeria's economic growth in the long run. The finding of the error correction mechanism revealed a speed of adjustment to equilibrium of 31.1%. The study suggested that the government, as a key player, should take immediate action to formulate policies that bolster and optimize the advantages of remittance inflows. This is crucial as remittances have been found to positively and significantly affect economic growth in the short and long run. These measures may encompass reducing transaction expenses, improving financial literacy among recipients, and encouraging investments to amplify the developmental effects of remittances.