This paper investigates the effect of financial inclusiveness on economic growth in selected developed and developing countries (63 countries) for the years of 2014 and 2017. The level of financial inclusiveness for each country is calculated using a new construction of the financial inclusion index. The role of financial inclusiveness on economic growth is subsequently estimated using a cross-sectional threshold regression technique. The main findings revealed that there is a threshold effect of the financial inclusiveness-growth nexus, which means that financial inclusiveness exhibits a non-monotonic positive relation with economic growth. The positive effect is more pronounced at a high level than in the low level of financial inclusion index. These new findings should motivate policymakers and the banking sector in each country to exert greater effort in raising the level of financial inclusion in stimulating sustainable economic growth.

This paper attempts to provide a probable answer to a longstanding resource curse puzzle; i.e., why resource-rich nations grow at a slower rate compared to less fortunate ones. Using an innovative threshold estimation technique, the empirical results reveal that there is a threshold effect in the natural resources – economic growth relationship. We find that the impact of natural resources is meaningful to economic growth only after a certain threshold point of institutional quality has been attained. The results also shed light on the fact that the nations that have low institutional quality depend heavily on natural resources while countries with high quality institutions are relatively less dependent on natural resources to generate growth.

This study aims to investigate the influence of the volatility of exchange rates on manufacturing commodity exports in the ASEAN-5 (Indonesia, Singapore, Thailand, Malaysia, and the Philippines). The study used the ARCH/GARCH, ARDL, and Nonlinear ARDL to determine the symmetrical and asymmetrical influence of the volatility of the exchange rate on manufacturing exports in both the short run and long run. Five leading commodity exports for each of the ASEAN-5 countries were used and analyzed over the period January 2007-March 2019. Our strategy using the ARDL approach revealed that volatility has a significant influence on 13 commodity exports in the short term. While the Nonlinear ARDL approach revealed that volatility influenced 19 commodity exports. Additionally, in the long run, finding from ARDL and Nonlinear ARDL also indicates risk-averse behaviour by exporters. However, in the long run, the nonlinear model demonstrates that volatility asserts an asymmetric influence on nearly all commodity exports. With this, therefore, there is the need for policymakers to uphold steadiness in the exchange rate via the use of adequate foreign reserves and amplified the level of investment.

The main objective of this paper is to reinvestigate the impacts of non-tariff measures (NTMs) on bilateral exports among Regional Comprehensive Economic Partnership (RCEP) countries. The study adds to the literature in two areas. First, we calculate coverage ratios for NTMs related to specific sustainable development goals (SDGs) imposed on bilateral trade between RCEP member countries. Second, to avoid aggregation bias, the analysis covers four major sectors, namely agrifood, health, logistics, and other manufacturing. The results of a Poisson pseudo maximum likelihood (PPML) regression in a gravity model, using average import data from 2016 to 2018 at the Harmonized Commodity Description and Coding Systems (HS) two-digit level (97 subsectors), show that the effects of SDG-related NTMs vary by sector. NTMs related to SDG 3 (good health and well-being) distort trade in health but enhance trade in logistics. NTMs related to SDG 12 (responsible consumption and production) have a negative impact on logistics but a positive impact on other manufacturing exports. The findings provide new perspectives on the varying impacts of SDG-related NTMs on trade. Interestingly, the study finds that NTMs addressing SDGs 3 and 12 have positive trade impacts. Policymakers should, however, regulate NTM implementation, to minimize negative impacts and ensure that domestic firms comply to promote sustainable production.

Purpose: The purpose of this paper is to investigate the nonlinear relationship between shadow economy and income inequality and determine whether the size of shadow economy can influence the level of income inequality.Design/methodology/approach: Both parametric (panel OLS) and nonparametric/semiparametric regression suggested by Robinson (1988) will be used to capture the dynamic nonlinear relationship between these variables using unbalanced panel data of 154 countries from 2000 to 2007. Additionally, the relationship between income inequality and shadow economy on both developed and developing countries will be analyzed and compared.Findings: First, semiparametric analysis and nonparametric analysis are significantly different than parametric analysis and better in nonlinear analysis between income inequality and shadow economy. Second, income inequality and shadow economy resemble an inverted-N relationship. Third, the relationship between income inequality and shadow economy is different in developed countries (OECD countries) and developing countries, where OECD countries have similar inverted-N relationship as before. However, for developing countries, income inequality and shadow economy show an inverted-U relationship, similar to the original Kuznets hypothesis.Practical implications: This study suggests that there is a possible trade-off between income inequality and shadow economy and helps policy makers in solving both problems effectively.Originality/value: Despite the growing importance of income inequality and shadow economy, literature linking the two variables is scarce. To the best of the authors’ knowledge, there is no literature that nonlinearly links these two variables. Furthermore, the dynamics of the relationship between these two variables in developed countries and developing countries will be explored as well.