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The study aims to find the synchronization between foreign agriculture investment (FAI) and Sustainable Development Goals (SDGs) related to agriculture as classified by the Food and Agriculture Organization (FAO). The study tries to find such an association in India over 2 decades from 2001.

The Toda-Yamamoto Granger using the M-Wald test for the non-causality procedure is applied to find the synchronization. Stationarity is tested using the Augmented Dickey-Fuller, Phillips-Perron and Kwiatkowski, Phillips, Schmidt and Shin (KPSS) tests. The Johanson methodology with MacKinnon-Haug-Michelis P-value is employed for the Cointegration test.

The empirical results indicate that the FAI Granger cause SDG2 “Zero hunger” and “Overall sustainability”, but SDG13 “Climate Change”, SDG6 “Clean water and sanitation”, SDG12 “Responsible production and consumption” and SDG15 “Life on Land” granger cause global investments. Notwithstanding, SDG5 “Gender equality” and SDG14 “Life below water” found no-way causality with FAI.

Host governments should prioritize sector-level sustainable development, notably agricultural SDGs, to attract global investments. Foreign agriculture investment is influenced differently by various SDGs; thus, policymakers should concentrate on specific agricultural SDGs to enhance the flow of capital into the agriculture sector. Global investors should take sustainability into account while framing foreign investment plans, and the supra-national organization may consider global agricultural investments while addressing the problems related to global food security.

The distinguishing feature of the study is that SDGs classified by the FAO from a global investment perspective have not been studied so far.

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

This paper documents a robust empirical regularity: higher trade openness is associated with a lower unemployment rate. This paper also examines whether or not the effects of trade liberalisation depend on countries' income levels. Further, the dynamic causation between trade openness and unemployment is also examined.

In order to obtain insight into the openness–unemployment nexus, following empirical methods were utilised - static panel models, dynamic panel models and a novel panel Granger causality approach proposed by Juodis et al. (2021).

Results suggest that openness negatively affects unemployment; the extent to which trade liberalisation affects unemployment depends on the income level of each country. The Juodis, Karavias, and Sarafidis (JKS) test confirmed that the past values of trade openness, inflation, foreign direct investment and gross domestic product per capita contain information that helps to predict unemployment in a more robust manner. To simply put, opening upto trade may eventually become a requirement for creating more job opportunities, but this alone may not be enough. The extent to which nations benefit from trade liberalisation is largely dependent on the overall economic conditions and their capability to move up the income scale.

A major difference between this study and those performed previously is that this study does not only examine the impact of trade openness on unemployment, but also investigates whether the unemployment effect of liberalisation is affected by countries' income levels – an issue that has received little attention in the past. Additionally, the unique panel non-causality approach put forth by Juodis et al. (2021) is used in the first instance to look into the causal link between trade openness and unemployment. This method has advantages in that the method enables capturing Granger-causality in homogeneous or heterogeneous panels amongst multiple variables.

The purpose of this paper is to analyse the influence of economic growth, digitalisation, eco-innovation, energy consumption and patents on environmental technologies on the volume of greenhouse gas emissions (GHG) recorded in European countries for a period of nine years (2010–2018).

Two empirical methods were integrated into the theoretical approach developed based on the analysis of the current scientific framework. Multiple linear regression, an extended version of the OLS model, and a non-causal analysis as a robustness method, Dumitrescu–Hurlin, were used to achieve the proposed research objective.

Digitalisation described by the number of individual Internet users and patents on environmental technologies determines the amount of GHG in Europe, and economic growth continues to have a significant effect on the amount of emissions, as well as the consumption of renewable energy. European countries are not framed in well-established patterns, but the economic growth, digitalisation, eco-innovation and renewable energy have an impact on the amount of GHG in one way or another. In many European countries, the amount of GHGs is decreasing as a result of economic growth, changes in the energy field and digitalisation. The positive influence of economic growth on climate neutrality depends on its degree of sustainability, while patents have the same conditional effect of their translation into environmentally efficient technologies.

This study has a number of limitations which derive, first of all, from the lack of digitalisation indicators. The missing data restricted the inclusion in the analysis of variables relevant to the description of the European digitalisation process, also obtaining conclusive results on the effects of digitalisation on GHG emissions.

A similar analysis of the relationship among the amount of greenhouse gas emissions and economic growth, digitalisation, eco-innovation and renewable energy is less common in the literature. Also, the results can be inspirational in the sphere of macroeconomic policy.

This study examines the influence of the global geopolitical risk (GPR) on the relationship between oil prices and domestic food prices under the augmented Phillips curve framework.

Using monthly data on Nigeria from January 1995 to December 2021, the authors accommodate symmetry and asymmetry by adopting the linear and nonlinear autoregressive distributed lag, linear and nonlinear Granger causality tests.

The study establishes the positive and significant effects of both oil prices and GPR on food prices in the long and short run, though with a small magnitude in the short run. The asymmetric model shows that, while oil price shocks (positive and negative) exert a positive influence on food prices in the long-run, the effects of oil price shocks differ when accounting for GPR in the short-run. The coefficients of the interactive term, being the moderator of GPR between oil-food prices, are positively significant across models, suggesting that they jointly influence food prices when assuming linearity. The nonlinear model shows that the positive and negative components of interactive terms exert a positively significant influence on food prices, even though food prices tend to be more reactive to positive oil price shocks. The robustness checks show a unidirectional causal flow from oil prices and GPR to food prices under the linear and nonlinear models.

The authors examine the moderating effect of the newly developed global GPR index of Caldara and Iacoviello (2022) on the oil–food inflation relationship in Nigeria by applying the symmetric and asymmetric approaches.

This study aims to examine the value relevance of earnings in terms of predicting the value variables such as cash flow, capital investment (CI), dividend and stock return under the Indian institutional settings.

The study used panel Granger causality tests to examine causality relationships among variables and panel data regression models to check the statistical associations between earnings and value variables.

Based on a data set of 7,280 Bombay Stock Exchange-listed firm-years spanning over ten years from March 2009 to March 2018, the results show higher sensitivity of earnings toward cash flows, CI, divided and stock return and vice-versa. Further, the findings deduced from the empirical results demonstrate that earnings are positively related to value variables. Overall, the results established that earnings are value-relevant and have predictive ability to forecast the value variables that facilitate investors in portfolio valuation. The results are consistent with the predictive view of the value relevance of earnings. Several robustness checks confirm these results.

This study brings new empirical evidence from a distinct capital market, India, and provides a new facet to the value relevance debate in terms of its prediction view. The study is among earlier attempts that jointly measure the ability of earnings in forecasting different value variables by taking a uniform sample of firms at the same period. Hence, the study provides a comprehensive view of the predictive ability of reported earnings.

Achieving sustainable development goals (SDGs) demands mobilising finance and aligning it with elements of sustainability. This study, thus, aims to investigate the impact of financial development of an economy on the achievement of SDGs.

The authors analyse a sample of 35 Asian countries based on their SDG trends and representative SDG indicators. An ordered probit model is employed for analysing the impact of financial development on the SDG trend. Subsequently, pairwise Granger causality test is employed for investigating the causality between the SDG and the financial development.

The findings indicate that financial development positively impacts the progress towards SDG achievement in the areas: (1) gender equality, (2) economic growth, (3) industry, innovation and infrastructure and (4) sustainable cities and communities; and adversely impacts the climate action. The causality test indicates a bidirectional causality for financial development and industry, infrastructure and innovation, financial development and sustainable cities and communities and financial development and climate action, and unidirectional causality from gender equality to financial development.

The findings have implications for the government of a nation as well as the private businesses. The goals allow businesses to implement well-articulated strategies which pay attention to the SDGs.

The novelty of the paper is that the authors provide evidence supporting the view that focusing on building a resilient and robust financial system is of importance for the achievement of SDGs.

Might the impact of the financial stress on exchange markets be asymmetric and exposed to regime changes? Departing from the existing literature, highlighting that the domestic and foreign financial stress in terms of money market have substantial effects on exchange market, this paper aims to investigate the impacts of the bond yield spreads of three emerging countries (Mexico, Russia, and South Korea) on their exchange market pressure indices using monthly observations for the period 2010:01–2019:12. Additionally, the paper analyses the impact of bond yield spread of the US on the exchange market pressure indices of the three mentioned emerging countries. The authors hypothesized whether the negative and positive changes in the bond yield spreads have varying effects on exchange market pressure indices.

To address the research question, we measure the bond yield spread of the selected countries by using the interest rate spread between 10-year and 3-month treasury bills. At the same time, the exchange market pressure index is proxied by the index introduced by Desai et al. (2017). We base the empirical analysis on nonlinear vector autoregression (VAR) models and an asymmetric quantile-based approach.

The results of the impulse response functions indicate that increases/decreases in the bond yield spreads of Mexico, Russia and South Korea raise/lower their exchange market pressure, and the effects of shocks in the bond yield spreads of the US also lead to depreciation/appreciation pressures in the local currencies of the emerging countries. The quantile connectedness analysis, which allows for the role of regimes, reveals that the weights of the domestic and foreign bond yield spread in explaining variations of exchange market pressure indices are higher when exchange market pressure indices are not in a normal regime, indicating the role of extreme development conditions in the exchange market. The quantile regression model underlines that an increase in the domestic bond yield spread leads to a rise in its exchange market pressure index during all exchange market pressure periods in Mexico, and the relevant effects are valid during periods of high exchange market pressure in Russia. Our results also show that Russia differs from Mexico and South Korea in terms of the factors influencing the demand for domestic currency, and we have demonstrated the role of domestic macroeconomic and financial conditions in surpassing the effects of US financial stress. More specifically, the impacts of the domestic and foreign financial stress vary across regimes and are asymmetric.

This study enriches the literature on factors affecting the exchange market pressure of emerging countries. The results have significant economic implications for policymakers, indicating that the exchange market pressure index may trigger a financial crisis and economic recession.

The main purpose of this study is to investigate the agriculture-induced environmental Kuznets curve (EKC) hypothesis in South Asian economies (SAE).

This study employs econometric techniques, including Westerlund cointegration tests, cross-sectional augmented distributive lag model (CS-ARDL) and Dumitrescu and Hurlin (DH) causality tests to investigate the relationship between renewable and non-renewable energy consumption, agriculture, economic growth, financial development and carbon emissions in SAE from 1990 to 2019.

The CS-ARDL test outcome supports the presence of the agriculture-induced EKC hypothesis in SAE. Additionally, through the application of the DH causality test, the study confirms a unidirectional causality running from renewable energy consumption (REC), fossil fuel consumption (FFC), economic growth (GDP) and squared economic growth (GDP²) to carbon dioxide (CO₂) emissions.

This study proposes that future research should extend comparisons to worldwide intergovernmental bodies, use advanced econometric methodologies for accurate estimates, and investigate incorporating the service or primary sector into the EKC. Such multidimensional studies can inform various methods for mitigating global climate change and ensuring ecological sustainability.

Environmental degradation has been extensively studied in different regions and countries, but SAE face significant constraints in addressing this issue, and comprehensive studies in this area are scarce. This research is pioneering as it is the first study to investigate the applicability of the agriculture-induced EKC in the South Asian region. By filling this gap in the current literature, the study provides valuable insights into major SAE and their environmental challenges.

This paper aims to empirically examine the impact of economic development and energy consumption in Saudi Arabia (the leading OPEC giant and the Arab energy icon country) between 1971 and 2015, whilst incorporating globalization, financial development and capital accumulation.

This study uses econometric tools and the analytical framework based on the autoregressive distributed lag (ARDL) model.

The study found that, unlike economic development, globalization and financial development increased energy consumption. Also, capital accumulation created a boost in the country’s energy consumption. Results of variance decomposition indicate that the innovative shocks in globalization and financial development affected energy consumption at the rates of 15.28% and 28.98%, respectively, over 15 years’ period, while shocks in capital accumulation affected energy consumption at a rate of only about 1.24%. In addition, the results of impulse response function show that globalization and economic development were highly responsive to shocks in financial development, and capital accumulation greatly spurred financial development.

The findings of this study have implication for promoting an efficient and sustainable energy systems that enhance sustainable development based on the accrued benefits of globalization, financial development and capital accumulation.

Given the increasing level of globalization, financial development and energy consumption, our study uses econometric tools and the analytical framework based on the ARDL model to revisit how energy consumption is influenced by economic development in Saudi Arabia by incorporating other determinants of energy consumption such as globalization, financial development and capital accumulation. The results were validated based on the innovative accounting.