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This 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.

The 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.

The 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.

The 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.

To 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 purpose of this paper is to assess both short and long-term influences of public investment on economic growth and test the hypothesis that whether public investment promotes or demotes private investment in Vietnam.

The authors use the approach of autoregressive distributed lag model and Vietnam’s macro data in the period of 1990-2016, to evaluate the short and long-term effects of public investment on economic growth and private investment. The model evaluates the impact of public investment on economic growth and private investment based on the neoclassical theories. The public investment which strongly affects economic growth is also reflected by aggregate supply and demand. Public investment directly impacts aggregate demand as a government expenditure and aggregate supply as a production function (capital factor).

The results from this research indicate that public investment in Vietnam in the past period does affect economic growth in the pattern of an inverted-U shape as of Barro (1990), with positive effects mostly occurring from the second year and negative effects of constraining long-term growth. Meanwhile, investment from the private sector, state-owned enterprises, and FDI has positive effects on short-term economic growth and state-owned capital stock has positive impacts on economic growth in both the short and long run. The estimated influence of public investment on private investment also shows a similar inverted-U shape in which public investment have crowding-in private investment short-term but crowding-out in the long run.

The empirical findings in this study can be used for conducting a more efficient policy in restructuring the state sector investment in Vietnam.

The main contributions in this study are: to evaluate the impacts of public investment on economic growth and private investment, the authors extracted public investment in infrastructure from aggregate investment of state sector (as previous studies used); the authors also uses state-owned capital stock variable including cumulative public investment and state-owned enterprises investment suggesting that this could control for the different orders of integration between the stock and flow variable and improve the experimental characteristics of the equation to a higher degree.

This paper investigates the relationship between domestic gold prices and inflation in Vietnam based on the monthly series of the gold price index and consumer price index over the period of December 2001–July 2020.

The co-integration between the domestic gold price and inflation is examined within the autoregressive distributed lag-error correction (ARDL bounds testing) framework. This paper also applies the vector error correction model (VECM) and impulse response function analysis to explore the causal relationship between these two variables. Moreover, since both gold and inflation series are likely to have structural changes over time, a unit root test controlling for significant breaks is employed in this paper.

Findings from the ARDL bounds testing model suggest the presence of a co-integration between the underlying variables. The VECM indicates that shocks in inflation lead to a negative response to gold prices in the long run. In the short term, only fluctuations in gold prices impact inflation, and this causality is unidirectional.

Gold is regarded as a critical financial asset to preserve wealth from inflation pressure in the case of Vietnam. These findings propose implications for both investors and policymakers.

Empirical results suggest that inflation has a long-term impact on gold prices in the Vietnamese market. In the existence of a permanent inflationary shock, domestic prices of gold respond negatively to this shock; hence, gold can act as a good hedge against inflation in Vietnam.

This paper aims to explain real exchange rate fluctuations by means of a model including both standard fundamentals and two alternative measures of inflation expectations for five inflation targeting countries (the UK, Canada, Australia, New Zealand and Sweden) over the period January 1993–July 2019.

Both a benchmark linear autoregressive distributed lag (ARDL) model and a nonlinear autoregressive distributed lag (NARDL) specification are considered.

The results suggest that the nonlinear framework is more appropriate to capture the behaviour of real exchange rates given the presence of asymmetries both in the long and short run. In particular, the speed of adjustment towards the purchasing power parity (PPP) implied long-run equilibrium is three times faster in a nonlinear framework, which provides much stronger evidence in support of PPP. Moreover, inflation expectations play an important role, with survey-based ones having a more sizable effect than market-based ones.

The focus on linearities and the estimation of a NARDL model, which is shown to outperform the linear ARDL model both within sample and out of sample, is an important contribution to the existing literature which has rarely applied this type of framework; the choice of an appropriate econometric method also makes the policy implications of the analysis more reliable; in particular, monetary authorities should aim to achieve a high degree of credibility to manage them and thus currency fluctuations effectively; the inflation targeting framework might be especially appropriate for this purpose.

This paper aims to assess the impact of digital financial innovation on financial system development in Common Market for eastern and Southern Africa (COMESA). This paper evaluates the dynamic relationship between digital financial innovation measures and financial system development using time series data from COMESA countries for the period 1997–2019.

A dynamic autoregressive distributed lag model (ARDL) was adopted and the mean group (MG), pooled mean group (PMG) and dynamic fixed effect (DFE) of the model were estimated to evaluate the short- and long-run impact. In addition, the dynamic generalized method of moments (DGMM) was adopted for a robustness check. The Hausman test results show PMG to be the most consistent and efficient estimator, while the coefficient of lagged dependent variable of different GMM is less than the fixed effect coefficient, and, as such, suggests system GMM is the most suitable estimator. Data for the study were sourced from World Bank Development Indicator (WDI, 2020), World Governance Indicator (WGI, 2020) and World Bank Global Financial Development Database (GFD, 2020).

The result shows that digital financial innovation significantly impacts financial system development in the long run. As such, the evidence revealed that automated teller machines (ATMs), point of sale (POS), mobile payments (MP) and mobile banking are significant and contribute positively to financial system development in the long run, while mobile money (MM) and Internet banking (INB) are insignificant but exhibit positive and inverse relationship with financial development respectively. Further investigation revealed that institutional quality and a stable macroeconomic environment including their interactive term are significantly imperative in predicting financial system development in the COMESA region.

Researchers recommend a cohesive and conscious policy that would checkmate the divergence in the short run and suggest a common regional innovative financial strategy that could be pursued to incentivize technology transfer needed to promote financial system development in the long run. More so, plausible product and process innovations may be adapted to complement innovative institutions in the different components of the COMESA financial system.

Digital financial innovation services if well managed increase the inherent benefits in financial system development.

To the best of the authors’ knowledge, this paper presents new background information on digital financial innovation that may stimulate the development of the financial system, particularly in the COMESA region. It also exposes the relevance of digital financial innovation, institutional quality and stable macroeconomic environment as well as their interactive effect on COMESA financial system development.

The environmental deterioration has become one of the most economically consequential and charged topics. Numerous scholars have examined the driving factors failing to consider the structural breaks. This study aims to explore sustainability using the per capita ecological footprints (EF) as an indicator of environmental adversities and controlling the resources rent [(natural resources (NR)], labor capital (LC), urbanization (UR) and per capita economic growth [gross domestic product (GDP)] of China.

Through the analysis of the long- and short-run effects with an autoregressive distributed lag model (ARDL), structural break based on BP test and Granger causality test based on vector error correction model (VECM), empirical evidence is provided for the policies formulation of sustainable development.

The long-run equilibrium between the EF and GDP, NR, UR and LC is proved. In the long run, an environmental Kuznets curve (EKC) relationship existed, but China is still in the rising stage of the curve; there is a positive relationship between the EF and NR, indicating a resource curse; the UR is also unsustainable. The LC is the most favorable factor for sustainable development. In the short term, only the lagged GDP has an inhibitory effect on the EF. Besides, all explanatory variables are Granger causes of the EF.

A novel attempt is made to examine the long-term equilibrium and short-term dynamics under the prerequisites that the structural break points with its time and frequencies were examined by BP test and ARDL and VECM framework and the validity of the EKC hypothesis is tested.

Based on the hypothesis of the environmental Kuznets curve (EKC), the purpose of this study is to investigate the relationship between environmental pollutants (as measured by CO₂ emissions) and GDP for India, over the period 1980–2012. The presence of an inverted “U” shape relationship is examined while controlling for factors such as the degree of trade openness, foreign direct investment, oil prices, the legal system and industrialization.

To verify whether the EKC follows a linear, quadratic or polynomial form, autoregressive distributed lag (ARDL) bounds testing approach for cointegration with structural breaks is adopted. The annual time series data for carbon emissions (CO₂), economic growth (GDP), industrial development (industrialization), foreign direct investment and trade openness have been obtained from World Development Indicators online database. Crude oil price (international price index) for the period is collected from the International Monetary Fund. Data for total petroleum consumption are collected from the US Energy Information Agency. Data for economic freedom variables are from the Fraser Institute's Economic Freedom Index's online database.

The findings support the existence of inverted U-shaped EKC in the short-run, but not in the long-run. A linear monotonic relationship has also been estimated in select model specifications. Additionally, trade openness has been estimated to reduce emissions in models, which incorporate FDI. Else, where significant, its impact on carbon emissions is adverse. A rise in fuel price leads to reduction in carbon emissions across model specifications. Further, the lower size of government degrades the environment both in the long-run and short-run.

Given the existence of the pollution haven hypothesis, wherein more trade and foreign direct investments cause environmental degradation, the paper proposes formulation of appropriate regulatory mechanisms that are environmentally friendly. Additionally, India's new economic policies, favoring liberalization, privatization and globalization, reinforces the need to strengthen environmental regulations.

Incorporation of economic freedom as measured by the “Size of Government” in the EKC model is unique. “Size of Government” deserves a special mention. The rationale for including this explanatory variable is to understand whether countries with lower government size are more polluting. After all, theory does suggest that goods and services, which have higher social cost vis-à-vis private cost, shall be overproduced in economies that adopt more market-friendly policies, necessitating government intervention. In the study, size of government is measured as per the definition and methodology adopted by Fraser Institute's Economic Freedom of the World Index.

The aims of the paper are to investigate IT software and service export function for India. First, cointegration tests have been used to investigate the long-run equilibrium relationship of the given variables. Second, long-run coefficients and associated error correction mechanism are estimated.

Annual time series data on IT software and service exports, human capital, exchange rate, investment in IT, external demand and openness index have been used for the present study during the period 1980–2017. The data are collected from the National Association of Software and Service Companies (NASSCOM), Planning Commission of India, University Grants Commission (UGC) of India, real effective exchange rate (REER) database and World Bank development indicators. Auto regressive distributed lag (ARDL) model is used to analyze both short-run and long-run dynamic behaviour of economic variables with appropriate asymptotic inferences.

Results of the analysis show the stable long-run equilibrium relationship among the given variables. It is found that external demand, exchange rate, human capital and openness index have a substantial long-run impact on the IT software and service exports. We also found that the coefficient of error correction term is negative and significant at 1% of the level of significance, which confirms the existence of stable long-run relationship which means adjustment will take place when there is a short-run deviation to its long-run equilibrium after a shock.

There may be other determinants of software and service exports apart from those considered by the present study. Due to the non-availability of data, the study considers only important determinants that determine the software and service exports in India. The IT exports are an emerging and dynamic field of economic activity and the rate of change is so rapid that the relevance of individual factors may change over time. The study period is also limited to available data.

The paper has implications for achieving sustainability in IT software and service exports growth. It is recommended that policies directed at improving the performance of IT software and service exports should largely consider the long-run behaviour of these variables.

This paper focuses on originality in the analysis of the relationship among the given variables including IT software and service exports, human capital, exchange rate, investment in IT, external demand and openness index in India. All the work has been done in original by the authors, and the work used has been acknowledged properly.

This paper aims to investigate simultaneously the causality and the dynamic links between exchange rates and stock market indices. It attempts to identify the short- and long-term effect of the US dollar on major stock market indices of Brazil, Russia, India, China and South-Africa (BRICS) nations.

This paper applies a new methodology combining the panel generalized method of moments model and the panel auto-regressive distributed lag (ARDL) method to investigate the existence of a causal short-/long-run relationships and dynamic dependence among all stock market returns and exchanges rates changes of BRICS countries.

Results show that exchange rate changes have a significant effect on the past and the current volatility of the BRICS stock indices. Besides, ARDL estimations reveal that exchange rate movements have a significant effect on short- and long-term stocks market indices of all BRICS countries

The findings have implications for policymakers and market participants who try to manage the exchange rate will have a different dose of intervention if they know that the effects of currency depreciation are different than appreciation. These results have important implications that investors should take into account in frequency-varying exchange rates and stock returns and regulators should consider developing sound policy measures to prevent financial risk.

Globalization occupies a central research activity and remains an increasingly controversial phenomenon in economics. This phenomenon corresponds to a subject that can be criticized through its impact on national economies. On the other hand, the world economy is evolving in a liberalized environment in which foreign direct investment plays a fundamental role in the economic development of each country. The advent of financial flows – foreign direct investment, remittances and official development assistance – can be a key factor in the development of the economy. The purpose of this study is to analyze the effect of financial flows on economic growth in developing countries. Empirically, different approaches have been used. As part of this study, an attempt was made to use a combined autoregressive distributed lag (ARDL) panel approach to study the short-term and long-run effects of financial flows on economic growth. The results indicate ambiguous effects. Economically, the effect of financial flows on economic growth depends on the investor’s expectations.

To study the short-run and long-run effects of financial flows on economic growth, this paper considers an empirical approach based on the panel ARDL. This model makes it possible to distinguish between the short-run effect and the long-run one. This type of model is based on three estimators, namely, mean group, pooled mean group (PMG) and dynamic fixed effect.

Results confirm the existence of a long-run relationship because the adjustment coefficient (error correction parameter) is negative and statistically significant. This paper finds that the PMG estimator is more consistent and more efficient. In the short-run, foreign direct investment do negatively affect economic growth, the effect is no significant in the long-run. On the other hand, the effect of remittances on economic growth is significant in the short-run. However, it is no significant in the long-run. Finally, the results suggest that the effect of official development assistance on economic growth is insignificant; both in the long-run and in the short-run.

To study the interaction between financial flows and economic growth, some empirical methodology are used such as the dynamic panel data and the autoregressive vector (VAR) model. In this study, we apply the panel ARDL model to analyze the short-run and the long-run effect for each financial flow on economic growth. The objective is to study the heterogeneity on dynamic adjustment in the short-term and long-term.