Net‐zero policy and forward default risk in the energy sector: Evidence of corporate environmentalism using (a)symmetric models

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.

Examining the relationship between default risk and efficiency in Islamic and conventional banks

Recent events have highlighted the potential importance of nonlinear efiects of flscal variables (notably debt and deflcits) on interest rates: While in times when government solvency is not a concern the standard crowding-out efiects are of moderate magnitude, in times when default risk becomes an issue the interest rate efiects can become very large. This paper provides new evidence on the magnitude of these efiects. For the case when default risk is not a concern, it uses an arbitrage-free term structure model to estimate the dynamic efiects of flscal policy shocks on interest rates along the entire maturity spectrum. For the case when default risk becomes a concern (thereby violating a central assumption of the term structure model), I present evidence based on EMU government bond spread regressions on time-varying efiects of national flscal policies on spreads as well as the time-varying sensitivity of yield spreads to international risk aversion as a function of the state of flscal policy. JEL classiflcation: E6, H6.

The relationship between energy use and industrial sector output can play a vital role in adjusting policies regarding energy sector. This paper investigates the causal relation between energy consumption and industrial sector performance in 14 selected countries of world by utilizing panel data from 1993 to 2017. these 14 countries are divided into two groups: high income group and upper middle income group countries. The Auto Regressive Distributed Lag (ARDL) test is used to check the impact of energy consumption in both long-term and short-term. The results of ARDL indicate the presence of long run and short run relationship among the variables. It also reveals that aggregated and disaggregated energy components (ELE, HYD and OIL) have a favorable and significant impact on industrial performance. Oil has more significant impact on industrial sector as compare to other energy sources in both income groups. Labor and capital in both models have remarkable impact on output as per Neo classical output theory, in our aggregated energy consumption model. These results describe the fact that industrial sector of these two income groups needs a great deal of energy. The present study is fairly significant for academic perspective and policy makers as it shows a strong relationship between energy consumption and industrial sector output. According to the findings, improvement of energy sector in said countries will boost the industrial sector's performance. Keywords: Energy consumption; Industrial output; Auto Regressive Distributed Lag Model. F bound test.

Purpose This study examines the complex relationship between income inequality and the ecological footprint in South Africa, emphasizing its implications for more inclusive environmental policies. Design/methodology/approach The result offers social, economic and environmental perspectives by employing both the autoregressive distributed lag model (ARDL) and the nonlinear autoregressive distributed lag (NARDL) models for data from 1980 to 2017. Findings The ARDL findings indicate that income inequality does not significantly influence the ecological footprint. However, while financial development negatively affects the ecological footprint, factors such as energy consumption, economic growth and trade openness positively influence it in both the short and long term. In contrast, the NARDL model reveals a hidden nexus in which reductions in income inequality significantly decrease the ecological footprint, highlighting the importance of decomposing variables into their + and – components to uncover hidden dynamics. These results highlight the potential oversight of critical relationships using traditional models and emphasize the value of disaggregated data to provide deeper insights into the interactions between economic variables and environmental outcomes. In addition, other findings from the NARDL model align with those obtained from the ARDL model, reinforcing the robustness of our analysis. Originality/value Unlike prior research, this study reveals the asymmetric impacts of income inequality on ecological outcomes, offering a fresh perspective on integrating economic disparities into sustainable development strategies.

The present study made an attempt to investigate the fiscal deficit–economic growth nexus in India during 1980–1981 to 2016–2017 in the presence of gross domestic capital formation (GDCF), exchange rate, and total revenue. For empirical investigation, the study has employed auto-regressive distributed lag (ARDL) model. The empirical findings of the ARDL model provide evidence that the linear model for India’s fiscal deficit, capital formation, and economic growth dynamics would be misspecification of the model. Therefore, this study has used nonlinear auto-regressive distributed lag (NARDL) bounds testing of cointegration proposed by Shin et al. (in: Festschrift in honor of Peter Schmidt, Springer, New York, 2014) to investigate the long-run and short-run interactions between the variables. The NARDL results found the evidence of asymmetric association between fiscal deficit and GDP and GDCF and GDP in the long-term and short-term time sphere. The obtained results indicate that fiscal deficit has adverse impact on GDP, whereas GDCF has positive influence on GDP in India. This finding supports neoclassical theory regarding the nexus between fiscal deficit and economic growth. The study has suggested that, as per the “golden rule” of public finance, the amount of the fiscal deficit should be spent on capital formation in order to have a long-term multiplier effect on growth.

This paper examines the economic impacts of climate change on agriculture in Bhutan. It focuses on the significance of the agriculture sector in Bhutan and analyzes the economic effects of climate change using the Autoregressive Distributed Lag (ARDL) model. The dependent variable used in the ARDL model is agriculture GDP, while the independent variables are temperature and rainfall. The ARDL model is employed to assess the short-run and long-run economic impacts of climate change on agriculture. The results of the study indicate that the agriculture sector has consistently contributed the highest GDP from 2009 to 2020 in Bhutan. Additionally, it has provided the most significant employment opportunities compared to other sectors between 2009 and 2019. The ARDL model results demonstrate that in the short run, the coefficient for temperature is positive at 0.16, and the coefficient for rainfall is 0.5, indicating that climate change has a positive impact on agriculture GDP. However, in the long run, the ARDL model reveals a negative impact of climate change on agriculture GDP. The coefficient for temperature is -11.2, and for rainfall, it is -1.13. These findings underscore the urgent need for measures to address the challenges posed by climate change. The paper recommends raising awareness about climate-smart initiatives and programs among stakeholders. Additionally, training and the adoption of climate-resilient seeds and techniques are necessary to mitigate the adverse effects of climate change on the agriculture sector.

In this study, we explored the influence of trade diversification and financial sector development on economic growth of ten West African countries for the period 2007 to 2020. The study employed the panel autoregressive distributed lag (ARDL) model since some of the variables were stationary at level while others were stationary at first difference, fully modified ordinary least squares approach of estimation, and Granger causality test. The findings of the study from the ARDL model indicated that export diversification exerts a negative effect on economic growth both in the short-run and in the long-run, though such effect were insignificant. The effect of financial sector development on growth is observed to be positive and significant in the short-run, and negative and significant in the long-run. From the robustness check, the FMOLS result indicated that export diversification exerted a negative and significant effect on growth; while the effect of financial development is positive but insignificant. The Granger causality test revealed that a unidirectional causality flow between export diversification and economic growth, with the former causing the latter. The implication of this findings is that countries within the West African region should specialize in some export products in order to boost efficiency in production and the resultant effect on greater export and export earnings.

This paper contributes to the burgeoning literature on the so-called “risk-taking channel” of monetary policy by constructing a partial equilibrium model of the commercial loan market, where conventional monetary policy influences bank lending standards and, by extension, the risk of bank default. In the model, borrower heterogeneity in terms of entrepreneurial abilities and project revenue results in optimal commercial bank lending standards. These standards take the form of a minimum ability requirement: only borrowers with abilities greater than or equal to the minimum threshold receive a loan; the rest are completely excluded from the loan market. After loans are made, a negative aggregate shock that lowers all borrowers’ project revenue results in unexpected loan losses for the bank that may push it into default. In the baseline model, lending standards loosen and the probability of bank default rises when the central bank’s policy rate falls, a result that suggests that asset quality and lending standards may play an important role in shaping the risk-taking channel of monetary policy. However, the relationship between bank default and the policy rate is sensitive to the extent of bank capitalization. While default risk and the policy rate are negatively correlated at relatively strongly capitalized banks, the risk of default at more weakly capitalized banks increases with the policy rate. Additionally, default risk at strongly capitalized banks is more responsive to changes in the policy rate than at weakly capitalized banks. This paper contributes to the literature on the risk-taking channel of monetary policy. First, the model enables analysis of the impact of monetary policy on risk-taking in a setting where both bank asset quality and leverage play a role in shaping the risk of bank default. Second, the model’s results on the role of bank capitalization imply that the tradeoff between financial stability and monetary policy depends crucially on bank capital ratios. This suggests that recent changes to bank capital requirements embodied in new post-2008 financial crisis regulations may impact the nature and size of the risk-taking channel.

The growing significance of consumer confidence and the explanation of the factors influencing this confidence is an important issue worthy of study. This study aims to examine the effects of election periods and consumer expectations on the Consumer Confidence Index (CCI) in Turkey. To this end, the Autoregressive Distributed Lag (ARDL) and Quantile Autoregressive Distributed Lag (QARDL) models will be employed. Data on the variables in question were collected on a monthly basis from Turkish Statistical Institute (TUIK) over the period spanning 2012:1 to 2024:3. The ARDL model findings indicate that election periods exert a positive and significant influence on the TGE, both in the short run and in the long run. The intention to buy or have a house built and the intention to save have positive and significant effects on the TGE in both the short and long run. Conversely, the intention to buy a car and the cost of living index have a positive and significant effects on the TGE in the short run, but no significant effect was found in the long run. The QARDL model reveals that asymmetry is present, with all variables exhibiting disparate effects across different quartiles. The findings of this study indicate that in order to enhance consumer confidence and guarantee economic stability, it is essential to prioritise the housing market, savings patterns and reducing the cost of living. The development of policies that ensure the sustainability of the confidence and stability created during election periods is crucial. The research offers invaluable insights into ARDL and QARDL models that can inform Turkey's economic policies.

This paper explores the transformative role of fiscal policy in driving economic prosperity in Nigeria covering 1985 to 2022. By examining how federal government domestic debt, external debt, capital expenditure, recurrent expenditure, oil revenue and non-oil revenue as a proxy for fiscal policy correlate with gross domestic product per capita as a proxy for economic growth. Data for the study were obtained from Central Bank of Nigeria (CBN) Statistical Bulletin 2022. The Augmented Dickey Fuller (ADF) method was used to conduct a unit root test on the developed model. The variables were found to be of mixed order I(0) and I (1) according to the results of the Augmented Dickey Fuller unit root test. In order to determine whether fiscal policy and economic growth have a long-run connection, the research used the Auto-regressive Distributive Lag (ARDL) model and conducted a bound test. Results from the regression analysis showed that federal government domestic debt had a negative relationship with gross domestic product per capita in the short-run, while federal government external debt reported a negative but significant impact on gross domestic product per capita in the long-run. The Auto-regressive Distributive Lag (ARDL) bound test showed that fiscal policy and economic growth are correlated in the long run. The impact on gross domestic product per capita was positive and statistically significant for federal government recurrent spending and oil and non-oil income, while it was negligible for federal government capital expenditure. Hence, it was concluded that fiscal policy leads to economic prosperity significantly. It was therefore recommended amongst other that the federal ministry of finance should prioritize improving debt management practices to reduce the reliance on domestic debt. This includes developing strategies for refinancing existing high interest debt with lower cost options and integrating debt reduction into fiscal planning.

Exploring the asymmetric effect of remittance inflows on gold import demand: Evidence from a large gold-consuming and remittance-receiving country

PurposeThis empirical study explores the role of tourism development (TD) in India's environmental degradation. Since sustainable eco-tourism is essential for India, whose long-term economic prosperity also depends on robust tourism growth. Hence, this study offers specific policy proposals for sustainable tourism based on the simulated outcomes.Design/methodology/approachThe study employed the quarterly data from 1995Q1–2018Q4 for empirical validation. Moreover, the autoregressive distributed lag (ARDL) approach, Toda and Yamamoto (TY) causality model and wavelet coherence are also used to analyse the role of TD in India's environmental degradation.FindingsThe ARDL bounds test confirms the long-run relationship between the series. The long-run results from the ARDL model also indicate the driving role of TD in India's environmental degradation. In addition, the usage of the wavelet coherence method confirms the changes in TD that leads to changes in India's pollution level at different frequencies and periods, especially in the long run.Research limitations/implicationsSince this analysis is India-specific, these findings may lack generalizability to other developing economies. Therefore, researchers are encouraged to examine the impact of tourism growth on the natural environment in other countries either in a panel or time-series framework.Practical implicationsThis study suggests crucial implications for checking the pollution sands from TD without sacrificing tourism-led economic growth. This would be possible if the usage of green energy in India's transport sector is promoted.Originality/valueThis is the first study that analyzes the impact of TD on environmental degradation in the ARDL, wavelet coherence, TY frameworks for enabling the Indian economy for a sustainable tourism practice.

An axiomatic approach to default risk and model uncertainty in rating systems

PurposeThe main aim of this paper is to examine the mechanism of determining the exchange rate of the US dollar against the Indonesian rupiah (USD/IDR) by market players to manage the USD/IDR exchange rate stability. Thus, this study is expected to provide a better understanding of the determinants of the USD/IDR, given that the data set completely encompasses all the USD/IDR transactions in the Indonesian foreign exchange market. Order flow data used in this study cover all transactions on the USD/IDR conducted by domestic residents including both individuals and corporations and foreign investors in the Indonesian foreign exchange market.Design/methodology/approachThis study covers the data set over the period January 3, 2011 to December 31, 2015, and the vector autoregression and autoregressive distributed lag models are used in examining the research questions. More particularly, in this study, the author examines whether the net total domestic individual transactions (DOVA), net total domestic corporation transactions (KOVA), net total foreign investor transactions (IOVA), Asian Dollar Index (ADXY), non-deliverable forward (NDF) for USD/IDR and Volatility Index (VIX) are statistically significant determinants of the USD/IDR exchange rate.FindingsOverall, this study suggests that in the short run, lag of the USD/IDR exchange rate or inertia level, lag of the IOVA, lag of the NDF of the USD/IDR exchange rate and lag of the ADXY are statistically significant determinants of the USD/IDR. On the other hand, in the long run, DOVA, NDF and ADXY are found to be statistically significant determinants of USD/IDR. This study also found that there is a market leader and asymmetric information among market players in the Indonesian foreign exchange market, and their USD/IDR exchange rate level becomes a reference for other market players when conducting transactions with each other.Originality/valueThe paper is original along two lines. First, the data set used in this study is unique. It encompasses all the USD/IDR transactions in the Indonesian foreign exchange market. The order flow data used in this study cover all transactions on the USD/IDR conducted by domestic residents (includes both individuals and corporations) and foreign investors in the Indonesian foreign exchange market. Such an approach has not been used previously to study the exchange rate behavior in an emerging market. Second, there is limited knowledge on Indonesia’s exchange rate dynamics. This study fills this gap.