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The European Union (EU) has notified its revised Generalized System of Preference (GSP) on 31 October, 2012 which will come into effect from 1 January, 2014. The EU is also in the process of, or contemplating, to sign Free Trade Agreements (FTAs) with many developing countries. Recently, EU has officially announced initiation of FTA negotiations with USA. Such preferential tariff arrangements could lead to significant erosion of preferences enjoyed currently by the Least Developed Countries (LDCs). In this backdrop, the main objective of the present study is to investigate the economic impacts originating from preference erosion in the EU market which could potentially affect LDCs in general, Bangladesh in particular. In this context, a dynamic computable general equilibrium (CGE) analysis has been developed by using the Global Trade Analysis Project (GTAP) model and database to explore the aggregate impact of the preferential erosion as well as sectoral implications for which different partial equilibrium analyses were used. The analysis evince that if the EU eliminates all tariffs for Pakistan, India and Vietnam, Bangladesh's real GDP could decrease by 0.27 percent whilst welfare loss could be to the tune of US$ 54 million. Total exports to the EU will be reduced by 0.18 percent; consequently, Bangladesh’s terms of trade and exports of textiles and clothing could be fall by about 1 percent. The product level disaggregated analysis using RCA and unit price of major items also indicate that a number of products including textiles and clothing will be confronted with formidable market access difficulties in the EU.

The purpose of this study is to evaluate the effect of some internal features that influence the efficiency of non-bank financial institutions (NBFIs) in Bangladesh.

The study selected the top 15 Dhaka Stock Exchange (DSE)-listed NBFIs according to purposive sampling. The study period was from 2016 to 2020. Secondary data were collected from annual reports. The cost-to-income ratio was a dependent variable that was used as a proxy of operational efficiency. The ordinary least square regression technique was applied to measure the impact of firm-specific factors on efficiency.

Results showed that number of employees, branch number, firm size and deposit ratio have a significant effect on efficiency at 5% level. The number of branches and employees showed a negative impact, whereas firm size and deposit ratio showed a positive effect on the firms' efficiency. The deposit ratio is negatively related because deposit interest expenses were more than offset by interest income generation through the conversion of deposits into loans.

The study has practical and policy implications on NBFIs' managers, employees, shareholders, depositors, clients, regulatory authorities and government as efficiency enhancement would bring financial soundness.

This study shed light on some firm-specific factors that can be changed to increase operational efficiency or reduce the cost-to-income ratio. The novelty of the study is that it identified some significant associations between firm-specific factors and the operational efficiency of NBFIs.

This paper aims to investigate the effects of economic growth, population density and international trade on energy consumption and environmental quality in India.

Taking annual data of 1971-2011, autoregressive distributed lag bounds testing technique is applied to explore the long run link between the series. The Granger causality test is used to determine the direction of causality between the variables.

The obtained results confirm the cointegration of variables, and economic growth and population density are found to have significant positive effects on energy consumption in both the short and long runs. CO₂ emissions are also positively and significantly affected by population density and energy consumption, and negatively affected by economic growth.

The paper is original and valuable in the sense that it has considered two relevant additional explanatory variables, namely, population density and trade openness, which got little attention in the past. This research is an improvement over the previous studies because it has looked at the separate effects of explanatory variables on energy consumption, in addition to the effects on carbon emissions. Therefore, the findings of this research are more reliable because this adopted methodology is better and extensive, and the authors have properly addressed the issue of omitted variable bias.

The purpose of this study is to investigate the relationship between natural gas consumption and economic growth of France.

To analyze the relationship, an extended Cobb–Douglas production function is used. The auto-regressive distributive lag bounds testing approach is applied to test the existence of the long-run relationship between the series. The vector error correction model Granger causality approach is implemented to detect the direction of causal relation between the variables.

The results show that variables are cointegrated for the long-run relationship. They also indicate that natural gas consumption, exports, capital and labor are the contributing factors to economic growth in France. The causality analysis indicates that feedback hypothesis is validated between gas consumption and economic growth. The bidirectional causality is also found between exports and economic growth, gas consumption and exports and capital and gas consumption.

The feedback hypothesis between gas consumption and economic growth implies that adoption of energy conservation policies should be discouraged; rather, gas consumption and economic growth policies should be jointly implemented.

This study is an original work for France and shows the results of the relationship between natural gas consumption and economic growth. In line with the results of this study, new direction for policy makers is opened up to formulate a comprehensive energy policy to sustain long-term economic growth in France.

The purpose of this paper is to explore the drivers of economic growth in South Asia region for the period of 1975–2016 using the World Bank data.

Panel corrected standard error (static estimation) approach and one-step system generalised method of moments (dynamic estimation) approach are used.

Both the static and dynamic estimations indicate that energy use, gross capital formation and remittances are the main drivers of economic growth in South Asian countries. The effects of all these variables are positive and significant. The extent of the effect of energy use is much higher than that of other two variables on the economic growth. A 1 per cent increase in the growth of energy consumption can expedite the gross domestic product growth by approximately 3 per cent in South Asia. However, the key variables, such as trade, government expenditure and foreign direct investment demonstrate no significant effect.

The current research is original in the sense that it investigated the issue with a new data set using improved econometric techniques. Moreover, in South Asia as a whole, this kind of study is totally absent, particularly with panel data of a large number of years. Furthermore, this study has taken into account the problem of heterogeneity and the biases created by cross-section dependence, which were mostly absent in previous studies. Therefore, the findings of this research are new contributions to the existing literature.

This paper examined the volatility models for exchange rate return, including Random Walk model, AR model, GARCH model and extensive GARCH model, with Normal and Student-t distribution assumption as well as nonparametric specification test of these models. We fit these models to Bangladesh foreign exchange rate index from January 1999 to December 31, 2012. The return series of Bangladesh foreign exchange rate are leptokurtic, significant skewness, deviation from normality as well as the returns series are volatility clustering as well. We found that student t distribution into GARCH model improves the better performance to forecast the volatility for Bangladesh foreign exchange market. The traditional likelihood comparison showed that the importance of GARCH model in modeling of Bangladesh foreign market, but the modern nonparametric specification test found that RW, AR and the model with GARCH effect are still grossly mis-specified. All these imply that there is still a long way before we reach the adequate specification for Bangladesh exchange rate dynamics.

The purpose of this paper is to analyze the rationale for using social engineering as a tool to impact the nationalization of workforce in the United Arab Emirates (UAE).

Interpretative and exploratory approaches have been employed for this research. Accordingly, the study has extensively reviewed government documents, reports of international organizations and relevant academic literature, including journal articles, conference papers and unpublished dissertations.

The findings show that the UAE Government has initiated multiple policies and programs to enhance participation of indigenous Emiratis in the burgeoning labor market which has been hitherto dominated by the expatriates. However, while the Emiratization programs are on the verge of fulfilling the targets in the public sector job market, significant gaps exist between the targets and accomplishments in the private sector, causing policy concern.

This paper links theoretical insights from the social engineering model used in the social sciences research to analyze the dynamics of workforce nationalization. The study will be helpful to inform further empirical research in this area.

The purpose of this research is to investigate the millennial consumers’ purchasing behavior of fashion clothing brands in the spectrum of brand awareness, brand schematicity with brand consciousness and brand nationality. This study mainly considered the millennial consumers as they are the most dynamic and discerning segment when choosing a distinct fashion brand.

The study uses a well-structured questionnaire developed and distributed to 266 millennial respondents using shoping malls and university campus intercept methods. Data were analyzed by applying the structural equation modeling.

The results show that brand awareness has a mediating effect on the millennials’ purchasing behavior toward fashion clothing brands. The study also confirms the active moderation role of brand schematicity on the purchasing behavior toward fashion clothing brands.

Based on these findings, the fashion clothing retailers should aim to maximize their sales from the millennial segments by enhancing brand awareness. The schematic consumers are more engaged in the numbers of quality hints to make their choice on the fashion clothing brands. Therefore, the practitioners must consider such information, and that should be available in the fashion clothing retail outlets.

The study contributes to the existing literature of the millennials’ purchasing behavior toward the fashion clothing brands. Moreover, research on this segment related to brand awareness and brand schematicity is insufficient, and the current study may add significant value.

The purpose of this paper is to explore the effects of population growth (PG), environmental quality and trade openness on economic growth of major developed and developing countries.

The authors have used the panel unit root and panel co-integration tests over the period 1960-2013. Granger causality test is used to find out the direction of causality between the variables.

There is a bi-directional relationship between economic growth and trade openness, and a unidirectional relation, running from trade openness to CO₂ emissions in the three developed countries. PG has a positive effect on economic growth in three developing countries and there exists a bidirectional relationships between CO₂ emissions and PG and a unidirectional relationship from PG to economic growth and from trade openness to economic growth. Furthermore, there is a unidirectional relationship from PG to economic growth and bidirectional relationships between trade openness and economic growth for the six selected countries.

This is the first comprehensive research that combined the selected three major developed and three major emerging countries of the world to explore the effects of three important variables on economic growth. The authors’ findings will help the policy makers as well as the people of these six countries. this study has shown the aggregate and disaggregate results, so a comparison between the groups of countries is possible. Therefore, this research has significant contributions.

Social media brand pages have become instrumental in enabling customers to voluntarily participate in providing feedback/ideas for improvement and collaboration with others that contribute to the innovation effort of brands. However, research on mechanisms which harness these specific customer engagement behaviours (CEB) in branded social media platforms is limited. Based on the stimulus–organism–response paradigm, this study investigates how specific online-service design characteristics in social media brand pages induce customer-perceived value perceptions, which in turn, stimulate feedback and collaboration intentions with customers.

Data collected from 654 US consumers of brand pages on Facebook were used to empirically test the proposed framework via structural equation modelling.

The theoretical framework found support for most hypothesized relationships showing how online-service design characteristics induce an identified set of customer value perceptions that influence customer feedback and collaboration intentions.

The sample is restricted to customer evaluations of brand pages on Facebook in the USA. Practitioners are advised to maximize online-service design characteristics of content quality, brand page interactivity, sociability and customer contact quality as stimulants that induce brand learning value, entitativity value and hedonic value. This then translates to customer feedback and collaboration intentions towards the brand page.

The findings have important implications for the design and optimization of online services in the customer engagement-innovation interface to harness CEBs for innovation performance.