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This study aims to examine the impact of external debt on economic growth in Bangladesh within a broader macroeconomic scenario.

In the process of doing so, it assesses the empirical cointegration, long-run and short-run dynamics of the concerned variables for the period of 1980–2017 applying the autoregressive distributed lag (ARDL) bounds testing approach to cointegration. First, debt-gross domestic product linkage explores the impact of external debt impact on economic growth using a set of macro and country risk variables, and then this linkage is also analyzed along with a newly formed macroeconomic policy (MEP) variable using principal component analysis.

The study results reveal the negative impact of external debt on GDP growth, but the larger positive impact of MEP index indicates that this adverse effect of debt can be mitigated or even nullified by sound MEP and appropriate human resource policy.

The dynamic effects of different shocks (external debt and macro policy variable) on economic growth by vector autoregression impulse response function also confirm our ARDL findings.

The authors test the effect of expenditure decentralization and fiscal equalization on short- and long-run economic growth and estimate two-step generalized method of moment (GMM) simultaneous equations models, using panel data for China and India for the period 1985 to 2005. The authors estimate two simultaneous equations: a growth equation and equalization equation and find that expenditure decentralization has a negative and statistically significant effect at conventional levels on short-run economic growth for both China and India. However, the authors also find that this result is sensitive to the set of included explanatory variables. This leads the authors to conclude that expenditure decentralization has no effect on short-run economic growth for either country. The authors also find that expenditure decentralization has a positive and statistically significant effect on fiscal equalization for both countries but find no evidence that fiscal equalization affects short-run economic growth for either China or India. In contrast, the authors find that expenditure decentralization has a positive effect on long-run economic growth in the case of India, but not in the case of China. Finally, the authors report evidence that fiscal equalization has no effect on long-run economic growth in the case of China; however, the authors find that equalization has a positive and statistically significant at conventional levels effect on long-run economic growth in India.

The authors estimate two-step GMM simultaneous equations models, using panel data for China and India for the period 1985 to 2005. To examine the effect of fiscal decentralization (FD) policies on economic growth in China and India, the authors estimate two equations: a growth equation and an equalization equation. For the growth equation, the authors adopt a production-function-based model that is widely used in the empirical literature on growth; however, the authors do make some compromises with this specification due to the unavailability of certain data. For the equalization equation, the authors include variables that economic theory and empirical evidence suggest influence fiscal disparities among subnational governments which in turn influence the demand for horizontal fiscal equalization (HFE). To the extent possible, the authors employ the same econometric specification, variable constructions and sample periods for both China and India. The authors believe this strategy provides a more rigorous test of the FD hypothesis.

The authors find that expenditure decentralization has a negative and statistically significant effect at conventional levels on short-run economic growth for both China and India. However, the authors also find that this result is sensitive to the set of included explanatory variables. This leads to conclude that expenditure decentralization has no effect on short-run economic growth for either country. The authors also find that expenditure decentralization has a positive and statistically significant effect on fiscal equalization for both countries but find no evidence that fiscal equalization affects short-run economic growth for either China or India. In contrast, the authors find that expenditure decentralization has a positive effect on long-run economic growth in the case of India, but not in the case of China. Finally, the authors report evidence that fiscal equalization has no effect on long-run economic growth in the case of China; however, the authors find that equalization has a positive and statistically significant at conventional levels effect on long-run economic growth in India.

Due to the importance of FD policies, especially to many developing countries that are currently pursuing decentralization reforms, future research should examine the effect of FD on economic growth for other countries. Furthermore, although it would be difficult to do so, future research should examine whether FD promotes political stability on ethnically diverse countries.

To the best of the authors’ knowledge, no one has examined the effect of FD policies on India's growth experience. What is more is that this is also the first of its kind to have a comprehensive empirical investigation into these two major developing countries with very interesting similarities and differences in FD policies. It is thus of great importance to examine the effect of expenditure decentralization and HFE on economic growth in China and India.

Economic literature highlights both positive and negative impact of FDI on economic growth. The purpose of this study is to confirm the relationship between various economic factors and FDI equity inflows and find out deviations, if any. This is investigated using standard time-series econometric models. The long and short run relationship is inquired with respect to market size, inflation rate, level of infrastructure, domestic investment and openness to trade. The choice of variables for Indian economy is purely based on empirical observations obtained from scientific literature review.

The study involves application of autoregressive distributive lag (ARDL) model to investigate the relationship. The long run co-integration between FDI and economic growth is tested by Pesaran ARDL model. The stationarity of data is tested by augmented Dickey Fuller test and Phillip–Perron unit root test. Error correction model is applied to study the short run relationship using Johansen’s vector error correction model method besides other tests.

The results show that the domestic investment, inflation rate, level of infrastructure and trade openness influence inward FDI flows. These factors have both long and short-term relationship with FDI inflows. However, market size is insignificant in influencing the foreign investments inflows. There lies an inverse relation between FDI and inflation rate.

To the best of the authors’ knowledge, the study is original. The methodology and interpretation of results are distinct and different from other similar studies.

This study aims to investigate whether the characteristics of the chief financial officer (CFO) have an impact on the intensity of the corporate research and development (R&D) investment.

Based on hand-collected data for the CFOs of a sample of the largest European listed companies for the period 2013–2016, this study uses regression analyses to test empirically the association of CFO education, CFO gender and CFO age with R&D investment intensity.

The presence of female CFOs, CFOs with a Master of Business Administration (MBA) or Doctor of Philosophy (PhD) degree and older CFOs is positively associated with the intensity of R&D investment.

This study relies on some observable characteristics of CFOs and focuses on large listed companies.

The results of this study may help investors, stakeholders and practitioners to understand better which type of CFO characteristics are more likely to result in higher firm-level R&D investment intensity.

This study offers the first insights into the impact of CFOs, as the most prominent C-suite executives, on the level of corporate investments in R&D activity.

The impact of debt on economic growth has attracted immense economic research necessitated by ballooning public debt stock among countries and most of the literature presume a symmetric relationship between debt and economic growth. However, this study contemplates an asymmetric relationship and thus relies on annual series from 1970 to 2019 to examine the asymmetric effects of public debt on economic growth in Ghana.

The nonlinear autoregressive distributed lag (NARDL) bounds approach was employed. Gross domestic product (GDP) growth is the dependent variable while public debt and other control variables each decomposed into their positive and negative shocks constitute the independent variables.

The results reveal that a positive shock to public debt insignificantly impacts the growth of the economy in the short and long runs. Also, a negative shock to public debt exerts significant short-run negative and insignificant long-run positive effects on the growth of the economy. The divergence in the short- and long-run effects on growth of a negative shock to public debt and the general insignificant effects of a positive shock to the same is a glitch that is attributed to overcapitalized loans and poor utilization of credit facilities.

The study recommends “inter alia” that the government of Ghana strengthens the short to medium-term debt management strategies achievable through the enforcement of the Public Financial Management Act (PFMA) Act-921 and the Public Procurement Act (PPA) Act-914 to deal with any adverse effects of debt on the growth of the economy.

The novelty of the current study lies not only in the fact that it captures recent public debt dynamics at a time Ghana faces extreme fiscal constraints and escalating cost of debt servicing but it also does so in an asymmetric environment which is unprecedented an assumption in the analysis of Ghana's public debt–economic growth nexus.

The climate change effects on agricultural output in different regions of the world and have been debated in the literature of emerging economies. Recently, the agriculture sector has influenced globally through climate change and also hurts all sectors of economies. This study aims to examine and explore the impact of global climate change on agricultural output in China over the period of 1982-2014.

Different unit root tests including augmented Dickey–Fuller, Phillips–Perron and Kwiatkowski, Phillips, Schmidt and Shin are used to check the order of integration among the study variables. The autoregressive distributed lag (ARDL) bounds testing approach to cointegration and the Johansen cointegration test are applied to assess the association among the study variables with the evidence of long-run and short-run analysis.

Unit root test estimations confirm that all variables are stationary at the combination of I(0) and I(1). The results show that CO₂ emissions have a significant effect on agricultural output in both long-run and short-run analyses, while temperature and rainfall have a negative effect on agricultural output in the long-run. Among other determinants, the land area under cereal crops, fertilizer consumption, and energy consumption have a positive and significant association with agricultural output in both long-run and short-run analysis. The estimated coefficient of the error correction term is also highly significant.

China’s population is multiplying, and in the coming decades, the country will face food safety and security challenges. Possible initiatives are needed to configure the Chinese Government to cope with the adverse effects of climate change on agriculture and ensure adequate food for the growing population. In concise, the analysis specifies that legislators and policy experts should spot that the climate change would transmute the total output factors, accordingly a county or regional specific and crop-specific total factor of production pattern adaptation is indorsed.

The present empirical study is the first, to the best of the authors’ knowledge, to investigate the impact of global climate change on agricultural output in China by using ARDL bounds testing approach to cointegration and Johansen cointegration test.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

Utilising a database that distinctly classifies firm-level ESG (environmental, social and governance) news sentiment as positive or negative, the authors examine the information flow between the two types of ESG news sentiment and stock returns for 20 companies listed on the Johannesburg Stock Exchange between 2015 and 2021.

The authors use Shannonian transfer entropy to examine whether information significantly flows from ESG news sentiment to stock returns and a modified event study analysis to establish how stock prices react to changes in the two types of ESG sentiment.

Using Shannonian transfer entropy, the authors find that for the majority of the companies studied, information flows from the positive ESG news sentiment to stock returns while only a minority of the companies exhibit significant information flow from negative ESG news sentiment to returns. Furthermore, the study’s findings show significantly positive (negative) abnormal returns on the event date and beyond for both upgrades and downgrades in positive ESG news sentiment.

This study is among the first in an African context to investigate the impact of ESG news sentiment on stock market returns at high frequencies.

The purpose of this paper is to examine key macroeconomic determinants on Cameroon's economic growth from 1970 to 2018.

Data were obtained from the World Development Indicators and applied on time series data econometric techniques. The auto-regressive distributed lag (ARDL) bounds model analyzed the data since the variables had different order of integration.

The results showed long and short runs’ positive and significant connection between economic growth in Cameroon and government expenditure; trade openness, gross capital formation and exchange rate. Human capital development, foreign aid, money supply, inflation and foreign direct investment negatively and significantly affected economic growth in the short and long-runs. Hence, the macroeconomic indicators are not death.

The present research paper has tried to capture the impact of nine macroeconomic determinants on economic growth such as the government expenditure (LNGOVEXP), human capital development (LNHCD), foreign aids (AID), trade openness (LNTOP), foreign direct investment (LNFDI), gross capital formation (INVEST), broad money (LNM2), official exchange rate (LNEXHRATE) and Inflation (LNINFLA). However, these variables have the tendency to affect each other in a unidirectional or bidirectional manner. Further, the present research paper is unable to capture the impact of other macroeconomic variable due to the unavailability of data.

The study recommends that Cameroon should use proper planning and strategic policy interventions to achieve higher sustainable economic growth with human capital development, foreign aid, money supply, foreign direct investment and moderate inflation.

Macroeconomic indicators, if managed well, increase economic growth.

This paper to the best of the researcher's knowledge presents new background information to both policymakers and researchers on the main macroeconomic determinants using econometric analysis.

Investor risk perception is a personalized judgement on the uncertainty of returns pertaining to a financial instrument. This study identifies key psychological and demographic factors that influence risk perception. It also unravels the complex relationship between demographic attributes and investor's risk attitude towards equity investment.

Exploratory factor analysis is used to identify factors that define investor risk perception. Multiple regression is used to assess the relationship between demographic traits and factor groups. Kruskal–Wallis test is used to ascertain whether the factors extracted differ across demographic categories. A risk perception framework based on these findings is developed to provide deeper insight.

There is evidence of the relationship and influence of demographic factors on risk propensity and behavioural bias. From this study, it is apparent that return expectation, time horizon and loss aversion, which define the risk propensity construct, vary significantly based on demographic traits. Familiarity, overconfidence, anchoring and experiential biases which define the behavioural bias construct differ across demographic categories. These factors influence the risk perception of an individual with respect to equity investments.

The reference for the framework of this study is limited as there has been no precedence of similar work in academia.

This paper establishes that information seekers make rational decisions. The paper iterates the need for portfolio managers to develop and align investment strategies after evaluation of investors' risk by including these behavioural factors, this can particularly be advantageous during extreme volatility in markets that concedes the possibility of irrational decision making.

This study highlights that regulators need to acknowledge the investor's affective, cognitive and demographic impact on equity markets and align risk control measures that are conducive to market evolution. It also creates awareness among market participants that psychological factors and behavioural biases can have an impact on investment decisions.

This is the only study that looks at a three-dimensional perspective of the investor risk perception framework. The study presents the relationship between risk propensity, behavioural bias and demographic factors in the backdrop of “information” being the mediating variable. This paper covers five characteristics of risk propensity and eight behavioural biases, such a vast coverage has not been attempted within the academic realm earlier with the aforesaid perspective.