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The purpose of this study is to investigate long-run and short-run relationships between trade diversification, financial system development, capital formation and economic growth.

ARDL estimation approach is applied to analyze long-run and short-run relationships between the financial system development, capital formation, economic growth and trade diversification in case of the Sultanate of Oman over the period 39 years starting from 1979 till 2017.

The results show that financial system development and economic growth has a positive impact on trade diversification in the short-run and long-run. However, capital formation has a negative impact on trade diversification in the short run and long run. The negative relationship between trade diversification and capital formation implies that over the period of study, the investment in capital goods was made to enhance the production capacity of the oil sector to maximize revenue.

This research is limited to analyze long-run and short-run relationship between the financial system development, capital formation and economic growth and trade diversification in case of Sultanate of Oman.

To achieve the diversification goal, the policymakers need to formulate policies to strengthen the financial system and invest in infrastructure development to promote the non-oil sector. The research findings of this study will provide insights to the policymakers to formulate an effective diversification policy.

This research contributes to the existing literature by providing empirical evidence of the short-run and long-run analysis of the selected variables in the context of an oil-dependent country.

The international trade literature has established that export product diversification lowers export product revenue instability. The current analysis investigates whether this finding carries over services exports.

The empirical analysis covers a sample of 152 countries over the period 1980–2014 and employs the two-step system generalized method of moments (GMM) approach.

The empirical findings indicate that services export diversification reduces services export revenue instability both over the full sample as well as over sub-samples of high-income countries (HICs), least developed countries (LDCs) as well as developing countries (i.e. non-HICs) that are not LDCs. HICs appear to experience a higher positive effect of services export diversification on services export revenue instability than in developing countries. The analysis also shows that countries that further open-up to international trade enjoy a greater reducing effect of services export diversification on the instability of services export revenue.

This analysis, therefore, adds to the existing studies on the relationship between export product diversification and the instability of revenue derived from goods exports by focusing on the services export side. An important message from the analysis is that countries that diversify their services export basket enjoy lower services export revenue instability when they further integrate into the world trade market.

This study highlights the importance of services export diversification, including for stabilizing services export revenue to services traders. Diversifying services export items, including across traditional and modern services sectors involves the implementation of a wide range of policies and measures, of which the liberalization of the services sectors through reduction and eventually the elimination of services trade barriers; the improvement of the business environment and the development of domestic financial markets (see for example, Hoekman, 2017). It could be interesting that another study consider policies and measures that could promote services export diversification.

To the best of the authors’ knowledge, this is the first time this topic is being addressed, including empirically.

This paper attempts to investigate through empirical exercise how the chances of female employment opportunities rise in a developing country like India, against the backdrop of changes in institutions that are associated with globalization.

The paper develops a simultaneous equation model through a growth equation, gender equation and globalization equation to identify the factors impacting female labor market opportunities in India, based on annual time series data 1991–2019.

The major results of this study are as follows: (1) It is social globalization that positively impacts gender equality in employment opportunities apart from economic growth and trade diversification; (2) Evidence of “feminization of labor force” in the context of trade diversification is found; and (3) Equal gender opportunities reflect in equalizing outcomes in the labor market.

Growth strategies need to be constructed in such a way in India that it has redistributive implications and benefits women. The state agency needs to optimize the productive base of human resources and increase women's empowering capability through social and legal sanctions.

The uniqueness of the present paper lies in contributing to the existing literature on how gender inequality impacts trade diversification and how trade diversification impacts gender.

Personal remittance and ready-made garments (RMG) export incomes have emerged as the largest source of foreign income for Bangladesh's economy. The study investigates their impact on income inequality and gross domestic product (GDP) as a control variable, using time-series yearly data from 1983 to 2018.

It employs the Autoregressive Distributed Lag (ARDL) estimation and the Toda-Yamamoto (T-Y) causality approach. The ARDL estimation outcomes confirm a long-run association among the above variables and validate the autoregressive characteristic of the model.

Personal remittances positively contribute to reducing the income gap among the people of the society and declining income inequality. In contrast, RMG export income and economic growth contribute to further income inequality. The T-Y causality analysis follows the ARDL estimation outcomes and authenticates their robustness. It reveals a feedback relationship between remittance inflow and the Gini coefficient, unidirectional causalities from RMG export income to income inequality and economic growth to income inequality.

The finding has important policy implications to limit the income gaps between low and high-income groups by channeling incremental income to the lower-income group people. The policymakers may facilitate further international migration to attract further remittances and may upgrade the minimum wage of the RMG workers.

The study is original. As far as the authors' knowledge goes, this is a maiden attempt to investigate the impact of personal remittances and RMG export income on income disparity in the case of Bangladesh.

This paper investigates the dynamic patterns of Vietnam’s comparative advantage in the context of ASEAN. Using the Galtonian regression method and the Markov transition probability matrices for data from 1997 to 2008, we find the following: Firstly, commodity groups with a weak comparative advantage improved their competitiveness, whereas those groups with a strong comparative advantage saw it decline, indicating a convergence of their comparative advantages. Secondly, in terms of intra-distribution dynamics, industries with no initial comparative advantage (Class a) and those with a strong initial comparative advantage (Class d) showed a high degree of persistence, suggesting a low degree of mobility in the trade patterns for Classes a and d. Thirdly, mineral resource-intensive products showed a high degree of export specialization, whereas other product categories showed a high degree of export diversification. Fourthly, all commodity groups showed a downward trend in the degree of specialization. Finally, Vietnam’s exports were dominated by unskilled labor-intensive products and agricultural resource-intensive products, reflecting the validity of Heckscher-Ohlin model. As a result of the country’s trade liberalization, the patterns of Vietnam’s comparative advantage have come to reflect its factor endowment. These results suggest that Vietnam could better diversify its export structures and shift to exports based on human capital and technology by further liberalizing its trade policies, fostering human capital formation, and facilitating the transfer of technology.

This study aims to propose a comprehensive greenfield foreign direct investment (FDI) attractiveness index using exploratory factor analysis and automated machine learning (AML). We offer offer a robust empirical measurement of location-choice factors identified in the FDI literature through a novel method and provide a tool for assessing the countries' investment potential.

Based on five conceptual key sub-domains of FDI, We collected quantitative indicators in several databases with annual data ranging from 2006 to 2019. This study first run a factor analysis to identify the most important features. It then uses AML to assess the relative importance of each resultant factor and generate a calibrated index. AML computational algorithms minimize predictive errors, explore patterns in the data and make predictions in an empirically robust way.

Openness conditions and economic growth are the most relevant factors to attract FDI identified in the study. Luxembourg, Hong Kong, Singapore, Malta and Ireland are the top five countries with the highest overall greenfield attractiveness index. This study also presents specific indices for the three sectors: energy, financial services, information and communication technology (ICT) and electronics.

Existent indexes present deficiencies in conceptualization and measurement, lacking theoretical foundation, arbitrary selection of factors and use of limited linear models. This study’s index is developed in a robust three-stage process. The use of AML configures an advantage compared to traditional linear and additive models, as it selects the best model considering the predictive capacity of many models simultaneously.

The purpose of this study is to empirically analyze the impact of logistics efficiency on trade volume growth, and to examine the effects of lower tariffs resulting from free trade agreements. In order to measure the impact of logistics efficiency on trade volume growth, the export and import trade volume among 53 countries was introduced as the dependent variable. Macroeconomic indicators including annual average tariff rate, logistics efficiency indicators for port, air, railroad, road and container vessel connectivity, as well as dummy variables such as whether a free trade agreement was signed, were introduced as the explanatory variables. Bilateral panel data between trading nations was used to estimate the gravity panel model, and analysis followed the categorization: 1) separate inputs of the five logistics efficiency variables and 2) one aggregated input of the five variables as a single indicator. The analysis found that logistics efficiency had a statistically significant impact on bilateral trade volume growth, while the impact of lowering tariff rates on increasing trade was insignificant. In addition, logistics efficiency was found to have a greater impact on increasing trade volume than free trade agreements. These results imply that trade can be promoted more effectively by establishing and efficiently operating logistics-related infrastructure rather than traditional methods of reducing trade barriers such as lowering tariffs and signing free trade agreements.

The purpose of this study is to look at the United Arab Emirates’ (UAE's) progress toward economic diversification and becoming a knowledge-based economy.

The World Development Indicators (WDI) and GlobalEconomy websites provided all secondary data for this paper. The data are largely used to highlight the UAE's current level of diversification and, consequently, the atmosphere for a knowledge economy transition necessary for sustainable development. Additionally, the study conducts a nonparametric estimation using DEA to identify the condition of four variables pertaining to the UAE's knowledge economy. The Herfindahl-Hirschman index (HHI) was utilized empirically in this study to determine the current state of diversity.

According to this research, the UAE economy was reasonably diverse until recently. The number of patents and journal papers published per resident both add to the UAE's GDP. Furthermore, the UAE's information and communication technology (ICT) exports are inconsistent; a declining trend in the number of researchers and the education sector's continuous struggles are major concerns. Furthermore, Figure 1 in the introduction reinforces this conclusion by noting that construction and building remained the greatest employer of labor throughout the time period. This is a significant finding because, as illustrated in this research, low labor force participation in the education sector, combined with lower citizen participation in advanced education in the UAE, results in low scientific research and publications, with low knowledge output as patent applications. In general, the majority of the UAE's population is expat, and the extent to which locals and expats contribute to the overall advancement of education remains an open question. According to the data envelopment analysis (DEA) model, three variables in the knowledge economy are productive, and they are economic incentive and institutional regime, innovation systems and ICT. The findings of this article will aid policymakers in the UAE, and more generally in the Gulf Cooperation Council (GCC) region, in developing more successful policies that help in the growth of a knowledge- and innovation-based economy.

This study is appropriate for UAE economic policymakers to monitor the state and policies required for the UAE's transition to a knowledge economy.

This issue has rarely been addressed by the use of robust parametric and nonparametric processes, as well as robust data visualization tools.

Food and beverage (F&B) small and medium-sized enterprises (SMEs) must diversify their markets and obtain predictable sources of revenues to withstand difficult and volatile periods such as the post-pandemic geopolitical scenario, recently burdened by the Russian-Ukrainian conflict. On the other hand, another strand of the literature suggests that public procurement could be considered a great source of income, enabling solid contracts, revenues and cash-flow stability. Therefore, this paper aims to explore the role of public procurement, the adoption of e-commerce platforms and their interactions in affecting the exporting performances of SMEs operating in the F&B sector.

The study retrieves data from 2,186 Italian F&B manufacturing SMEs relying on Margò by Cribis database. Therefore, it conducts a structured equational model (SEM) to test the developed hypotheses empirically.

The findings reveal that digital selling platforms positively affect exports, whereas public procurement negatively affects F&B SMEs exports. Nonetheless, findings underline that the interaction between public procurement and the adoption of digital selling platforms dampens public procurement's negative effects on exports.

This study brings an original contribution to the F&B literature by conducting empirical research on an extensive sample of firms from one of the most influential countries in the F&B vertical, Italy, with officially registered data. More importantly, to the best of the authors' knowledge, this study pioneers the investigation of the relationship between public procurement and e-commerce platforms in affecting F&B SMEs' export performances.

The purpose of this paper is to investigate both long-run and short-run dynamics among the software and services export, investment in information technology (IT) and GDP in India and to investigate the direction of the relationship among the given three macro-economic variables.

The time series data have been taken to investigate the long-run relationship exists among the variables. Annual data were collected from the NASSCOM Annual Reports, Planning Commission of India and Reserve Bank of India during the period 1980–2016. Cointegration and vector error correction model have been used for analyzing the causal relationship among investment in IT, software exports and GDP in India.

Cointegration results confirm that software and services export, investment in IT and GDP are cointegrated, implying that there exists the long-run equilibrium relationship among the given three macro-economic variables. Similarly, vector error correction mechanism Granger causality results hold that there is uni-directional long-run causality running from software and services export and investment in IT to GDP, implying that software and services export is an important determinant of economic growth in India.

The limitations of the paper are generalization of the results and proxy variable for IT investments.

The paper has implications for the expansion of market concentration, diversification of software and service exports, and investments in R&D for increasing competitiveness of the industry in the global market.

This paper focuses on originality in the analysis of the relationship among the given variables software exports, investment in the IT sector and GDP in India. All the work has been done in original by the authors and the work used have been acknowledged properly.