ENTREPRENEURIAL ECOSYSTEM AS A CATALYST FOR ECONOMIC GROWTH: A GLOBAL EMPIRICAL EVIDENCE USING A NOVEL COMPOSITE INDEX

Comprehensive performance evaluation of banking branches: A three-stage slacks-based measure (SBM) data envelopment analysis

The high tech industry has played a critical role in the economic growth of Taiwan over the past two decades. The main success factor in the high tech industry is posited to be improving R&D efficiency and performance. This study utilizes an empirical study to provide valuable managerial insights when measuring the impact of R&D activities and performance representation in the Taiwanese high tech industry. The multi factor R&D performance model is determined to provide improved performance measures within the framework of the developed model, and is adopted to further examine the R&D performance of high tech firms and industries. The few studies dealing with devising the influence of environmental factors on efficiency measures do not consider that inefficiency results partly from exogenous circumstances. This study develops a two-stage sequential technique for incorporating environmental effects into a method for evaluating R&D performance based data envelopment analysis (DEA) and ordinary least squares (OLS) regression with panel data to obtain an efficiency measurement. The study data comprised 194 high tech firms analyzed from a multi-source database. The empirical results demonstrate that the average pure technical efficiency, overall technical efficiency, and scale efficiency scores across all 194 firms are 0.535, 0.424, and 0.791, respectively. Based on those efficiency scores and two-stage DEA empirical, suggestions regarding resource allocation for inefficient firms are explored and can be used to monitor R&D performance and as a basis for making subsequent innovation activities improvements. Key words: High tech industry, performance, R&D productivity, two-stage data envelopment analysis, OLS regression.

Is economic growth less welfare enhancing in Africa? Evidence from the last forty years

Net trade and Foreign Direct Investment (FDI) are both important factors of economic growth and development in Sub Saharan African (SSA) region. Many different studies have shown the impact of trade and FDI in economy growth in SSA countries. However, few is known about the effect in SSA region in overall. To use these factors in policy making and development planning, the following questions need to be addressed. As both factors impact the economy growth, can net trade (NT) historical performance be used to forecast FDI? Is there any short-run or long-run relationship effect among GDP growth, FDI and net trade? This paper has implemented the cointegration methodology to analyze the impact of net trade and FDI on GDP growth, used the Vector Error Correction Model (VECM) for long-run and short-run relationship effect, an Ordinary Least Square (OLS) regression to determine the significant impact of FDI and net trade on GDP growth and finally the granger causality test. This study shows a positive long-run relationship effect of FDI on GDP. The positive short-run effect of both FDI and net trade is also detected on GDP growth. The regression result shows that net trade has a significant impact on GDP growth and finally from the Granger causality test, the study shows that net trade Grangercause FDI.

Net trade and Foreign Direct Investment (FDI) are both important factors of economic growth and development in Sub Saharan African (SSA) region. Many different studies have shown the impact of trade and FDI in economy growth in SSA countries. However, few is known about the effect in SSA region in overall. To use these factors in policy making and development planning, the following questions need to be addressed. As both factors impact the economy growth, can net trade (NT) historical performance be used to forecast FDI? Is there any short-run or long-run relationship effect among GDP growth, FDI and net trade? This paper has implemented the cointegration methodology to analyze the impact of net trade and FDI on GDP growth, used the Vector Error Correction Model (VECM) for long-run and short-run relationship effect, an Ordinary Least Square (OLS) regression to determine the significant impact of FDI and net trade on GDP growth and finally the granger causality test. This study shows a positive long-run relationship effect of FDI on GDP. The positive short-run effect of both FDI and net trade is also detected on GDP growth. The regression result shows that net trade has a significant impact on GDP growth and finally from the Granger causality test, the study shows that net trade Grangercause FDI.

Relationship between economic growth and mismanaged e-waste: Panel data evidence from 27 EU countries analyzed under the Kuznets curve hypothesis

Using a panel of 113 countries over the period from 1990 to 2013, this paper provides new empirical evidence to the intensive debate of whether financial structure is relevant for economic growth. Specifically, we evaluate the role of political risk, development stage and their interactions with the structure of the financial system. We find that on average a more market-based financial system is associated with a higher level of economic growth. This impact varies with different levels of political risk and different stages of economic development. Specifically, the comparative development of equity markets compared with banks appear to promote more economic growth in countries with lower political risk and at a better stage of economic development. Moreover, banks are more important to economic growth in over-market-based financial systems, whilst equity markets are more sensitive to economic growth in over-bank-based financial systems. Our paper provides new insights into the real effects of the mixture of banks and markets on the economy.

Our pioneer study is aimed at investigating the role of the service sector in affecting sustainable environment in Pakistan. Using time series data over 1971–2014 and applying an autoregressive distributive lag (ARDL) model with structural break analysis, we establish a long-term equilibrium relationship of carbon dioxide (CO2) emissions with energy consumption, income level, services and trade openness. Our findings support a service-induced environmental Kuznets curve (EKC) hypothesis in Pakistan. The income level sharply raises environmental degradation at the early stage; however, after reaching a certain threshold, it improves environmental quality but at a lower rate. There exists an inverted U-shaped nexus between services and CO2 emissions, which implies that the service sector is less energy-intensive in terms of mitigating pollution in Pakistan. Moreover, the energy consumption has an inverted U-shaped effect on carbon emissions, which implies energy efficiencies and adoption of renewable energy has reduced pollution in the long run. The trade openness increases CO2 emissions in both the short term and long term. The quadratic term of income level has a negatively inelastic impact on CO2 emissions, which implies a very slow rate of improvement in environmental quality. On the other hand, the quadratic term of services shows a highly elastic impact on pollution, which induces the EKC hypothesis. Our robustness checks such as fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (OLS), and Toda and Yamamoto (TY) causality tests further confirm the existence of the service-induced EKC hypothesis in Pakistan. Moreover, there exists a unidirectional causality from energy consumption to CO2 emissions, a bidirectional causal relationship between economic growth and CO2 emissions, and a unidirectional causal linkage between services and CO2 emissions. Lastly, we discuss certain policy implications for designing appropriate environmental and energy policies to mitigate the pollution in Pakistan.

Renewable energy, CO2 emissions and economic growth in sub-Saharan Africa: Does institutional quality matter?

A study of the impact of military expenditures on economic growth and development examines the differences in the results of previous studies which led to contradictory conclusions. The authors find that these differences are due to sample variations, specificational choices, and the different time periods examined. The data indicate that there is no consistent, statistically significant connection between military spending and economic growth. Augmentation of the models suggests that military expenditures neither help nor hurt economic growth to any significant extent. 2 tables.

Publisher Summary This chapter discusses the financial development and economic growth in underdeveloped countries. An observed characteristic of the process of economic development over time, in a market-oriented economy using the price mechanism to allocate resources, is an increase in the number and variety of financial institutions and a substantial rise in the proportion not only of money but also of the total of all financial assets relative to GNP and to tangible wealth. Typical statements indicate that the financial system somehow accommodates—or, to the extent that it malfunctions, it restricts—growth of real per capita output. Such an approach places emphasis on the demand side for financial services; as the economy grows it generates additional and new demands for these services, which bring about a supply response in the growth of the financial system. In this view, the lack of financial institutions in underdeveloped countries is simply an indication of the lack of demand for their services.

ABSTRACTSub-Sahara Africa has over the years been exposed to diverse arguments and agitations about the provision of employment to alleviate poverty in the sub region with the aim of achieving full employment. Whereas some economists and bibliographers believe of the significant impact that employment and unemployment have on annual percentage change in GDP growth, some do not. The main objective of the study is to access the impact that employment and unemployment have on annual percentage change in GDP growth in Sub-Saharan African countries. World Development Indicator (WDI) data was collected from the World Bank from the year 2000 to 2014 for the purpose of the study. A sample of 12 sub-Saharan African countries were randomly selected using a random number generator and variables taken. Two statistical models were used; the Pooled Ordinary Least Square (OLS) regression model and the Least Square Dummy Variable (LSDV) regression model with fixed effect was used to empirically access impact that employment and unemployment have on annual percentage change in GDP growth. Both the Pooled Ordinary Least Square regression model and the Least Square Dummy Variable regression model tested to be statistically significant but LSDV regression model explained a greater percentage of the variability of the model than the Pooled OLS for employment on GDP growth rate. The pooled OLS regression model was not statistically significant at 5% level of significance in assessing the impact that unemployment has on annual percentage change in GDP growth. Further empirical analysis of the study also revealed a positive relationship between annual percentage change in GDP growth and employment for the female population (Empl15+Female), employment rate for the male population (Empl15+Male) and employment rate for the Total Youth population (Empl15-24 total). Also, an inverse relationship existed between unemployment male youth population (15-24years), and female youth population (15-24years) on annual percentage change in GDP growth. The study can be improved by considering other factors that impact GDP growth other than employment and unemployment.Keywords: Employment, Unemployment, GDP growth rate, Pooled OLS, LSDV

Russell Graph efficiency measures in Data Envelopment Analysis: The multiplicative approach

The relationship between financial sector development and economic growth is a crucial issue for both developing and developed nations. To keep up with the changing world economy, there is need for developing countries like Kenya to develop their financial sectors. Kenya’s financial sector development has had a major role in its economic growth and this study provides a selected review of the literature and the relationship between Kenya’s financial sector and its economic growth. Numerous studies have been done on the effect of the financial sector on economic growth and the general conclusion is that the financial sector plays a central role in economic development and growth of the country. However, there is a limitation of empirical and theoretical work supporting the concept in developing countries. Most of the studies done focus on the direction of causality between finance development and economic growth and their relationship. For this reason, the study set out to analyze the influence of financial sector development on Kenya’s economic growth. The Neo-classical theory of growth was used to inform the study variables; banking sector, export market and economic growth. The study adopted an ex-post facto research design with Ordinary Least Square (OLS) method. The data used was secondary in nature obtained from the Kenya National Bureau of Statistics from the period 2010-2019. The findings revealed that there was a positive influence of financial sector development on economic growth. This implies that financial sector development promotes economic growth in Kenya. In policy terms, the findings, imply that Kenya can accelerate economic growth by improving the financial sector since financial development can be an engine of growth in this country. The study recommended that other major components of the financial sector development apart from the two studied; banking sector and export market, in this paper should be studied and put up in place well -structured policies that will support them and further develop the financial sector with the aspirations under the Kenya Vision 2030. Keywords : Financial sector development, Economic growth DOI: 10.7176/RJFA/12-2-01 Publication date: January 31 st 2021

Slacks-based measurement (SBM), as an important branch of data envelopment analysis (DEA) for evaluating the efficiency of decision making units (DMUs) was firstly proposed by Tone and has been well developed in different directions. Many models based on SBM have been built, such as SBM of super efficiency, SBM of network DEA, SBM of the worst-practise DEA and dynamic SBM. In this paper, we extend the SBM models in different returns to scale (RTS) and build a comprehensive SBM model. Based on the SBM models above, a new approach for estimating returns to scale of DMUs is proposed. This approach has a specific advantage that it can gain projection of inefficient observations from input-output orientation. At last, a numerical example demonstrates the process of estimating returns to scale.