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This study aims to examine the linear and nonlinear remittance–institutional quality link in developing countries.

This study investigates the nonlinear relationship between remittance and political institutional quality in a panel of 97 developing countries using annual data of over nine years from 2009 to 2017. The estimated model uses system generalized method of moments for three political institutions indicators, namely, democracy, political stability and civil liberties.

The results revealed that remittance has a significant inverted U-shape impact on political institution’s indicators. Therefore, before the turning point, remittance is associated with high level of democracy, more stable political system and more civil freedom. While moving after the turning point indicates low level of political institution in the country.

The authors certify that this is the original paper. It has not been previously published and is not currently under submission or in press elsewhere.

This study aims to investigate the contingent roles real effective exchange rates (REERs) play in mediating the effects of oil revenue on the agriculture sector value-added in 25 major and minor oil-exporting (MIOEC) countries during the period of 1975–2014.

The panel autoregressive distributed lag (ARDL) estimator proposed by Pesaran et al. (1999) was relied upon to achieve the objectives of the study. This estimator involves a pool of small cross-sectional units over a long-time span that covers for 25 oil-exporting countries over 39 years (1975–2014).

This paper reveals the following findings. Firstly, oil revenue has a direct negative effect on agricultural value-added in the short- and long-term. This finding holds for full sample and subsamples of major oil-exporting (MAOEC) and MIOEC countries. Further assessment reveals that the magnitude of the impact is larger for MAOEC than that of the MIOEC. Secondly, the finding for the long-run effect shows that the contingent effect of real exchange rate on the nexus between oil revenue and agricultural value-added is negative and statistically significant at the conventional level for the full sample. This suggests that, in the long-run, the appreciation in real exchange rates exacerbate the negative marginal effects of oil revenue on agricultural value-added in all oil-exporting countries. However, when sub-samples of MAOEC and MIOEC are considered, the contingent effect disappeared (become insignificant) in MAOEC while it is positive and statistically significant in MIOEC. Thus, in the long-run, the appreciation in real exchange rates diminishes the negative marginal effects of oil revenue on agricultural value-added in MIOEC. While oil revenue has a direct negative effect, its effect is also moderated by the variations in REERs in MIOEC in the long-run. Finally, in the short-run, fluctuations in the real exchange rate do not matter for the nexus of oil revenue and agriculture sector in these countries whether minor or MAOEC countries.

This study contributes to the debate in the empirical literature on the Dutch disease effect and “oil curse”. Using the appropriate panel ARDL empirical framework, it provides evidence on how exchange rate variations in the oil-exporting countries influence the nature of the effects of the oil revenue on agricultural sectors in the long-run but not in the short-run. Contingent effects of REERs only appear to exist in MIOEC in the long-run.

The purpose of this study is to investigate the effect of government expenditure on economic growth in 15 Economic Community of West African States (ECOWAS) countries over the period of 2005–2017. More precisely, this paper investigates whether institutional environment influences the effect of government spending on economic growth.

This study adopts the generalized method of moments-system method of estimation to address the problem of dynamic endogeneity inherent in the relationship. Similarly, unlike previous studies which assume that the disturbances of a panel model are cross-sectionally independent, we account for cross-section dependency and cross-country heterogeneity inherent in empirical modeling using Driscoll and Kraay's nonparametric covariance matrix estimator, adjusted for use with both balanced and unbalanced panels along with Monte Carlo simulations.

The authors find that though, government spending has a positive impact on economic growth but the level of institutional quality adversely affect that positive impact. This suggests that the institutional environment in ECOWAS countries is a drag and not a push factor for government fiscal operations and/policies. Thus, the results provide empirical evidence that there is a conditional relationship between government spending and economic growth in African countries. That is, the effect of government spending on economic growth is dependent on the quality of institutions. Lastly, these findings suggest that in order for government spending to contribute to economic growth, African countries must develop a strong institutional environment.

Unlike previous time series studies for African countries which concentrated on the two variable case, we include institutional quality as a third variable to underline the potential importance of institutional quality for economic growth in ECOWAS countries.

This study aims to comprehend the application of analytics in the supply chain during the ongoing COVID-19 crisis and identify the emerging themes.

The author downloaded a list of research articles on the application of analytics to the supply chain from SCOPUS, conducted a systematic literature review for exploratory analysis and proposed a framework. Notably, the author used the topic modeling technique to identify research themes published during the ongoing COVID-19 crisis and thereby underscore some future research directions.

The author found that artificial intelligence, machine learning, internet of thing and blockchain are trending topics. Additionally, the author identified five themes by topic modeling, including the theme “Social Media information in Supply chain.”

The results were derived from a data set extracted from SCOPUS. Thus, the author excluded all studies not listed in SCOPUS from the analysis. Future research with articles indexed in other databases should be investigated to get a more holistic perspective of specific themes.

This study provides a deeper understanding and proposes a framework for applications of analytics in the supply chain that researchers could use for future research and industry practitioners to implement in their organizations to make a more sustainable and resilient supply chain.

This study provides exploratory information from published articles on the use of analytics in the supply chain during the COVID-19 crisis and generates themes that help understand the emerging and underpinned area of research.