Bounds Testing Approach Research Articles

Relevance of oil price, military expenditure and exports to achieve the Saudi Arabian sustainable economic and environmental objectives: a non-linear ARDL approach.

This study investigates the economic and environmental issues of Saudi Arabia, a net exporter of crude oil mainly relying on oil exports, which faces economic crises due to the decline in oil prices. For this purpose, we highlighted the main challenges of the Saudi economy, such as oil price shocks and a significant increase in military expenditures. The economic and environmental issues are vital for the country's development and sustainability. Saudi Arabia is a major exporter of fossil fuels, which threatens its long-term economic growth due to the global transition towards renewables. Also, heavy dependence on fossil fuels is deteriorating the environment as well. On account of this, we extended the Solow growth model by augmenting oil prices, military expenditure, and exports. Similarly, the autoregressive distributed lag (ARDL) bound testing approach is used to find the long-term as well as the short-term nexus between variables. The study provides innovative findings regarding the country's role in oil price fluctuations, exports, and heavy military expenditures. In the short run, higher oil prices are increasing the economic process. In the long run, higher oil prices have a significant and negative impact. Military expenditure and exports have a significant and positive relationship with economic growth in the case of long-run analysis. For carbon emissions, the rise in oil prices helps reduce carbon emissions. In comparison, higher exports are also responsible for carbon emissions. The study proposes innovative and fruitful policies regarding the economic prosperity of Saudi Arabia, such as increasing the military expenditure to maintain peace in the region and increasing the exports of oil products, as well as non-oil products, to have shelter from oil price shocks.

Does external debt drive inflation in Sudan: evidence from symmetric and asymmetric ARDL approaches

PurposeThis study aims to examine the symmetric and asymmetric impact of external debt on inflation in Sudan from 1970 to 2020 within a multivariate framework by including money supply and the nominal effective exchange rate as additional inflation determinants.Design/methodology/approachThe authors utilize an Auto Regressive Distributed Lag (ARDL) model to examine the symmetric impact of external debt on inflation, while the asymmetric impact is examined using a Nonlinear ARDL (NARDL) model. The existence of a long-run relationship between inflation and external debt is tested using the bounds-testing approach to cointegration, and a vector error-correction model is estimated to determine the short parameters of equilibrium dynamics.FindingsThe linear ARDL model results show that external debt has no statistically significant impact on inflation in the long run. On the contrary, the results of the NARDL model show that positive and negative external debt shocks statistically affect inflation in the long run. The estimated long-run elasticity coefficients of the linear and nonlinear ARDL models reveal that the domestic money supply has a statistically significant positive impact on inflation. In contrast, the nominal effective exchange rate has a statistically significant negative impact on inflation.Practical implicationsThe reliance on symmetric analysis may not be sufficient to uncover the existence of a linkage between external debt and inflation. Proper external debt management is crucial to control inflation rates in Sudan.Originality/valueTo date, no empirical study has assessed the external debt-inflation nexus and its potential asymmetry in Sudan, and the current study aims to fill this gap in the literature.

The impact of remittances on economic growth in Ghana: An ARDL bound test approach

The impact of remittances on economic growth in Ghana: An ARDL bound test approach

Effect Of Financial Technology On Cash Holding In Indonesia Using Autoregressive Distributed Lag (ARDL)

The rapid proliferation of financial technology (Fintech) has revolutionized the landscape of financial services globally, presenting digital alternatives to conventional banking and payment methods. Indonesia has emerged as a noteworthy adopter of Fintech, driven by the widespread usage of smartphones and government initiatives to foster financial inclusion. Nonetheless, the empirical research concerning the association between Fintech adoption and cash-holding behaviour in Indonesia remains limited. This study explores Fintech's influence on individuals' cash holding patterns in the country, considering direct indicators such as debit cards, credit cards, electronic money, mobile banking, and internet banking. A time-series analysis covering the period from M5 2013 to M3 2023, based on secondary data from the Bank Indonesia Statistic Database, is employed to achieve this research objective. The analytical framework utilizes the Autoregressive Distributed Lag (ARDL) bounds testing approach, accounting for the explanatory variables' concurrent and lagged effects. The empirical findings reveal a significant positive relationship between debit cards, mobile banking, and internet banking usage in short-term cash-holding behaviour. In contrast, credit card usage exhibits a negative and statistically significant association with long-term cash holding. These results contribute to a comprehensive understanding of how Fintech adoption shapes cash-holding behaviour in Indonesia and provide valuable insights into the country's transition toward a cashless society.

Does the Income from Tourism and Remittances Really Matter for Economic Growth? Evidence from the Nepalese Economy

This study investigates the effects of tourism and remittances on Nepal's Gross Domestic Product (GDP). It is based on secondary information acquired from Nepal's several economic surveys and publications from the Nepal Rastra Bank. It spans 34 fiscal years, from 1987/88 through 2020/21. The study employs descriptive and exploratory research designs.Descriptive statistics, unit root testing, Augmented Dickey-Fuller test, ARDL bound testing approach, heteroscedasticity test, serial correlation test, and CUSUM and CUSUM squares test of stability analysis are some econometrics instruments utilized.The GDP, remittances, and income from tourism are found to be correlated over the long term. In the long run, remittances and tourism revenue increase Nepal's GDP, but there is no discernible effect in the short run. The GDP increased by 0.794 and 0.157 percent for every one percent increase in tourist and remittance income. Therefore, the impact of tourism income is more significant than the impact of remittance income on GDP. Therefore, policymakers can employ tourism to promote Nepal's long-term economic growth.

Developing nexus between economic opening-up, environmental regulations, rent of natural resources, green innovation, and environmental upgrading of China - empirical analysis using ARDL bound-testing approach

With increasing demand for green growth globally, the escalating economic growth of China is also needed to be accompanied with environmental protection. From an environmental upgrading perspective, current study developed a nexus amid Green Total Factor Energy Productivity (GTFEP), Economic Opening-up (EOU), Environmental Regulations (ER), Rent of Natural Resources (RNR) and Green Innovation (GI) of China. Using annual data from 1990 to 2020 and applying a bound testing approach for Auto-regressive Distributed Lag model (ARDL) along with an error correction model, current study investigated short and long run dynamics amid variables of concern. The results confirmed cointegration between GTFEP and all other variables, and Granger causality analysis revealed uni-directional causality, running from independent variables towards GTFEP. Concluding the results, both long and short-run findings suggested effectiveness of EOU, ER, RNR and GI on GTFEP of China, and the results are statistically significant. Thus, the policies should be aimed to improve opening-up, environmental regulations and green innovation.

The determinants of oil consumption in Tunisia: Fresh evidence from NARDL approach and asymmetric causality test

This paper examines the asymmetric impact of oil price, economic growth, financial development, and industrialization on oil consumption in Tunisia, using the Nonlinear Autoregressive Distributed Lag (NARDL) model over the period 1980–2020. The NARDL bound testing approach confirms the presence of a cointegrating relationship between oil demand and its determinants. The results show that oil demand is income elastic and price inelastic. In the long run, the impact of increased and decreased financial development on oil consumption is found positive and negative, respectively. The findings also highlight that a positive (negative) shock to industrialization decreases (increases) energy consumption. The study of symmetrical causality supports the feedback hypothesis between growth and consumption. However, the asymmetric causality analysis shows that only negative shocks to economic growth have impacts on oil demand. The Tunisian economic model could be oriented in such a way as to support economic activity and implement energy saving policies. Finally, the implications of the different findings are discussed and key recommendations for policymakers are also provided.

Climate change and agriculture nexus in Bangladesh: Evidence from ARDL and ECM techniques

The erratic weather puts farming households of Bangladesh at high production risk with significant consequences on food production, income, and livelihood. This study attempts to find the effect of various climate change indicators on agriculture in Bangladesh over the period 1980–2014. The study used the ARDL bounds testing approach to assess the long-run associations and the Granger causality test to determine the causal relationships between the regressors and dependent variables. The outcomes revealed that the first lag of agricultural value-added, second lag of carbon emissions, and average rainfall have a positive impact while the first lag of carbon has negative and significant impacts on agricultural production in the long run; in the short run-past realizations of carbon emission have a negative and significant impact on agricultural value-added. Additionally, the results show a unidirectional causality from carbon emission to agricultural output, agricultural output to average rainfall, and agricultural output to energy consumption. The study fills the gap in the climate change literature by applying the ARDL method to establish the nexus between climate change and agricultural output in Bangladesh.

Analysing Factors Affecting the Industrial Production Sector in Malaysia: Evidence From the Bounds Testing Approach of Cointegration

Analysing Factors Affecting the Industrial Production Sector in Malaysia: Evidence From the Bounds Testing Approach of Cointegration

Financialization and growth nexus in the EU new member states (NMS): an ARDL bounds testing approach and Granger causality analysis

PurposeThis study aims to explore the short-run and long-run relationships and causality between economic growth and financialization in the new member states (NMS-11) and to provide some policy implications drawn from the empirical findings.Design/methodology/approachThe autoregressive distributed lag (ARDL) bounds test approach to cointegration with the vector error correction model and the cumulative sum of squares (CUSUMQ) test for stability of functions is used between 1995q1 and 2021q4 to examine the existence of cointegration, relationships and causality between economic growth and financialization.FindingsThe findings of the ARDL bounds test demonstrate that the variables included in the models are bound together in the long run, as confirmed by the associated equilibrium correction. The estimated models indicate that the association between selected variables and economic growth is stronger and more statistically significant in the short run compared with the long run. Also, for NMS-11 understudied countries, short-run causality prevails over long-run causality. The changes in the level of financialization have a significant negative effect on the growth rates in the short run, which aligns with findings from previous empirical studies.Originality/valueThis study extends the existing very limited literature about short-run and long-run relationships and causality among economic growth and financialization, including inflation and unemployment variables, to determine their link in the NMS-11. Specifically, the present study reveals that the current level of financialization hampers economic growth and promoting such economic policies further can have adverse effects on the overall economic growth.

Investigating the Dynamic Relationship between Exchange Rate and Trade Balance in Egypt: ARDL Bounds Testing Approach

Exchange rate policies are among the most important economic tools in the country for their impact on the balance of payments in general and the balance of trade. This study used the autoregressive distributed lag (ARDL) model to estimate the long-term relationship between the exchange rate and the trade balance deficit while clarifying the impact of potential determinants during the period 1990 to 2021 in Egypt. The data for trade balance and its economic determinants (exchange rate, foreign direct investment, and money supply) was obtained from the World Bank. The results indicated that the best model was ARDL (2,1,2,3). The exchange rate is found to have a significant negative effect on the trade balance, confirming the perceptions of the economic theory. The money supply is positively and significantly related to the trade balance while there is no significant effect of foreign direct investment in the long term on the trade balance deficit. Economic adjustments between the four variables occur in the short run (after about 14 months only). The study recommends continuing the policy of liberalizing the exchange rate while working on expanding the production base to increase exports.

Economic growth, inflation and unemployment in Africa: an autoregressive distributed lag bounds testing approach, 1991–2019

PurposeUnemployment is one of the major challenges facing most countries, including Africa as a continent. Seeking how to reduce unemployment, debt, inflation and increase gross domestic product (GDP), foreign direct investment (FDI) and gross capital formation in the continent has been an agenda of governments, policy makers and economists to. This study examines the relationship between economic growth, inflation, debt, FDI, gross capital formation, labor force, population and unemployment in Africa.Design/methodology/approachAn updated panel dataset of 29 African countries was selected from different regions from 1991 to 2019. These countries were selected based on their unemployment, population growth and inflation rates. The Pesaran cross-sectional dependence and panel unit root test (the Dickey–Fuller cross-sectional supplemented and the Im-Pesaran-Shin cross-sectional) were applied. Further, the panel Autoregressive Distributed Lag (ARDL) model (Bounds test) and pooled mean group (PMG) estimator were utilized in this work.FindingsThis shows that economic growth, debt, labor force and population have a positive relationship with unemployment in the long run. Therefore, an increase in these variables generates an increase in the selected African countries' unemployment growth. In contrast, inflation, FDI and gross capital formation have a negative relationship with unemployment in the long run, which implies that an increase in these variables reduces unemployment in the selected African countries.Research limitations/implicationsThis study has potential limitations because some data from the countries are not up to date and some years are missing from the data.Practical implicationsThis study contributes to understanding unemployment and Okun's law in the African economy. This study shows that an increase in economic growth leads to a rise in unemployment, while an increase in inflation leads to a decrease in unemployment.Originality/valueThis paper provides an insight into the major factors that increase and reduces unemployment for government and policy marker to take the adequate measure.

From pollution to progress: Exploring the role of cleaner technology, energy efficiency and sustainable production in reducing PM2.5 levels in China

AbstractAir pollution, particularly particulate matter (PM2.5) levels, was a significant focus at the COP26 summit. Rampant production practices and changing lifestyles contribute to the issue globally. China's rapid urbanization and reliance on fossil fuels significantly threaten global health sustainability. This study aims to evaluate China's environmental agenda and offer policy recommendations for achieving a green and clean environment. To accomplish this, the study assesses the crucial factors contributing to China's air pollution levels, focusing specifically on fine PM2.5 from 1975 to 2020. By implementing the ARDL bounds testing approach, the study confirmed a non‐linear relationship between per capita income and PM2.5, demonstrating an inverted U‐shaped curve with a turning point observed at a per capita income level of US$3030 in the short run. Furthermore, a positive correlation between these variables was detected in the long run. The study also revealed that rapid urbanization initially leads to increased PM2.5 concentrations, whereas it has a decreasing effect in the long term. To progress towards sustainable production and consumption, China has embraced efficient environmental technologies and increasing clean energy sources in its production mix. Leveraging these strategies, the country strives to achieve its decarbonization agenda and ensure a cleaner future. By conducting an ex ante analysis, this study identified ecological technologies, renewable energy demand and oil resource rents as critical influencers on China's air pollution levels over the next decade. The findings underscore the pressing need to embrace alternative energy sources, eco‐friendly technologies and resource conservation to tackle air pollution effectively and accomplish China's decarbonization objectives. It is imperative to prioritize adopting sustainable practices, ensuring a cleaner environment for current and future generations.

Investigating the Dynamic Association Among CO2 Emission, Energy Use, and Economic Growth: Evidence From China

Environmental pollution and climatic variations are due to CO2 emissions and considered an important global issue. The key aim of this study was to investigate the dynamic association among CO2 emission, energy use, and economic growth in China. Secondary data was used in this study ranging from 1971 to 2014, and data stationarity was verified by applying the Augmented Dickey-Fuller unit root test. The autoregressive distributed lag (ARDL) bounds testing approach and Granger causality test with vector error correction model was used to check the causal connection amid the study variables. Outcomes expose that energy use, economic growth and gross domestic product has positive coefficients through long-run analysis with p-values (.062), (.000), and (.100), respectively, that validate the significant association with CO2 emission. Furthermore, the outcomes of short-run analysis also uncover that energy use, economic growth, and gross domestic product have a significant association with CO2 emission in China. Potential conservative policies are needed from the Chinese government to reduce CO2 emissions and resources to resolve the problem without impacting the economic progress.

Investigating the relationship between market value added (MVA) and economic value-added momentum (EVAM): empirical evidence from Turkiye

Purpose- This study aims to investigate the possible relationship between market value added (MVA) and economic value-added momentum (EVAM). Besides, any possible linkage between leverage (in terms of the degree of combined leverage) and market value added is also tested. Methodology- This study conducts a time series analysis to the quarterly data of manufacturing industry, comprising Borsa Istanbul (BIST) listed manufacturing firms for the period of 2001.q2-2022.q4 to test MVA-EVAM relationship. It employs autoregressive distributed lag (ARDL) bounds testing approach, developed firstly by Pesaran and Shin (1999) and further revised by Pesaran, Smith and Shin (2001). The stationarity of the series is tested by the Augmented Dickey-Fuller (ADF) and Phillips and Perron (PP) unit root tests. Findings- Empirical findings from ARDL bounds testing approach refers the existence of long-run relationships between market value added and economic value added momentum; and market value added and degree of total leverage. The coefficients of the long-run form of ARDL model reveal that both economic value-added momentum and degree of combined leverage have statistically significant and negative effects on market value added. The estimated short-run coefficients indicate that economic value added momentum has significantly negative effect on market value added created as similar to the long-run finding. Another finding is that though leverage has significantly positive effect on market value added in the short-run, this positive effect turns out to be negative in lag one period. Conclusion- This study contributes to the literature on MVA-EVA relationship by employing autoregressive ARDL bounds testing approach to manufacturing industry comprising Borsa Istanbul (BIST) listed manufacturing firms of Turkey as an emerging market. Besides, the research model includes EVAM -as an independent variable- that is so rarely considered in existing literature. Keywords: Market value-added, economic value-added momentum, leverage, time series analysis, ARDL bounds testing approach. JEL Codes: G32, C32, C58

The role of agriculture, industry and the service sector in economic growth: The case of Mozambique

This study evaluated the effect of agriculture, industry, manufacturing and the service sector on economic growth for the period 1991 to 2020 using the autoregressive distributed lag stationarity (ARDL) bounds-testing approach. The empirical results of this study show that, in the long run, the industry sector and exports are positive and significant determinants; the manufacturing sector is a negative significant determinant of economic growth; while agriculture and the service sector were found to be insignificant. However, it was found that, in the short run, agriculture has a significant positive effect on economic growth, along with the manufacturing sector. The service sector was found to have no significant effect on economic growth in the short run. Therefore, in the long run, policy should focus on enhancing the industrial sector and promoting exports. In the short run, policy should focus on agriculture enhancement so as to boost economic growth positively.

Analyzing the volatility spillover and cointegration relationship between daily spot West Texas intermediate crude oil price and US dollar

In the study, it is aimed to analyze the diffusion and cointegration relationship between WTI and US Dollar in the period of 2016-2021. In the study, after a comprehensive literature review of the theoretical review, the econometric analysis section was started. In the first part of the analysis, the short and long-term relationships between the variables were examined with the autoregressive distributed lag methodology and the existence of a cointegration relationship was reached. According to the findings, the effect of WTI on foreign exchange volatility in the long run is statistically significant and negative. In the short-term evaluation, ECT is negative and significant within expectations. In this context, the changes between the variables approach the long-term equilibrium level. According to the results obtained in the causality and variance causality analyzes applied in the last part of the analysis, it is understood that there is a volatility spillover effect from WTI to foreign currency.

Impact of Climate Change on Total Factor Productivity of Agriculture in District Multan

Agriculture is particularly vulnerable to climate change because it faces open weather conditions. In uncontrolled open weather circumstances, it's difficult to attain better total factor productivity (TFP), which characterizes agriculture growth in an economy. The study estimated the TFP growth of Pakistan’s agriculture in first step by employing the Tornqvist- Theil index number approach for the period 1990-2019. The time series data for thirteen crops and four livestock categories from 1990 to 2019 were collected from different sources to estimate the TFP. The average annual TFP growth of agriculture was estimated to be 2.14 percent for the study period, and it contributed about 56 percent to total agricultural output growth. The results also indicated that TFP growth in agriculture sector was highest (0.05 percent) during the 1990-2000, while lowest (-2.14 percent) during the last decade. After, TFP index that was calculated in first step was used as dependent variable in second step of analysis. Then we estimated the impact of climate change on TFP in agriculture sector in Multan district. For this first we used ARDL bound test approach for estimation of long run impact of climatic variables. The results showed that there are positive effects of both minimum and maximum temperature on TFP in the study area. The drought and floods have negative impact on TFP but in first lag their effects became positive on TFP. One of the important variables of climate is rain that had positive impact on the TFP growth, with 1% increase in rainfall there was 0.22% increase in TFP at first lag. Improving the adaptation and mitigation practices related to floods and droughts would be required for sustainable growth in TFP in agriculture sector in Multan District.

ANALYSIS OF THE SOCIAL SECURITY INSTITUTION’S HEALTH SPENDING: AN ARDL BOUNDS TEST APPROACH

ANALYSIS OF THE SOCIAL SECURITY INSTITUTION’S HEALTH SPENDING: AN ARDL BOUNDS TEST APPROACH
 Yunus Emre KARATAŞ, Metin DİNÇER 
 
 With the health transformation program, universal health insurance was introduced. Thus, it became the most significant health service purchaser social security institution. The services provided by hospitals began to occupy an important place in the expenditures of the social security institution. Thus, the study aims to predict and model the effect of functional characteristics of health facilities on Social Security Institution (SSI) health expenditures in Turkey. While collecting the data used in the study, the hospital’s service levels as functional characteristics were considered, and the data between 01/2009 and 05/2020 were analyzed. Auto-Regressive Distributed Lag Model (ARDL) bounds test was used to analyze the presence of cointegration between variables in the short and long run. Long-run predictions show that while the secondary-level state hospitals reduce the health expenditure of the SSI, the tertiary-level state, university, and secondary-level private hospitals increase the SSI health expenditure. Measuring the services provided by hospitals and the benefits they provide to patients according to objective criteria will be the most significant indicator of the appropriateness of health expenditures.
 Keywords: ARDL Bounds Test, Reimbursement, Health Spending, Health Insurance, Social Security Institution
 Jel Codes: C32, G22, G28, H51, I13

Fiscal Decentralization and access to Social Services in Pakistan: Exploring the Role of Corruption

The present study looks at how accessibility to water and sanitation (social services) are affected by fiscal decentralization during the years 1980–2020 by incorporating the role of corruption in Pakistan using an ARDL Bounds testing approach. Two indicators, including revenue and expenditure decentralization, are employed to precisely capture the essence of fiscal decentralization. The Corruption Perception Index is used to quantify corruption. The empirical results indicate that decentralization of revenue and expenditures has a growing impact on social service access. The study offers proof that corruption not only impairs access to social services but also lessens the benefits of fiscal decentralization on that access. To achieve the desired effects of fiscal decentralization, the policy framework needs to take particular actions, such as increasing accountability and transparency to reduce corruption and enhance the quality of institutions.