The role of human capital and financial development in boosting FDI in emerging economies

This study aims to investigate the relationships between economic development and environmental degradation regarding the emissions of CO₂ and SO₂ in Southeast Asia (SEA). The pooling data consist of 10 countries, Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Singapore, the Philippines, Thailand, and Vietnam, in the period 2003-2012. Furthermore, income elasticity of CO₂ and SO₂ emissions is computed for each country to observe the sensitivity of environmental degradation through the emissions of CO₂ and SO₂ brought by economic development.
The results indicate that CO₂ displays an inverted U-shape pattern, whereas SO₂ has decreased at an increasing rate since 2003. It is expected that SO₂ will increase as the SEA economies further develop. The turning points for both CO₂ and SO₂, indicate that the current SEA income level has not reached the turning point. The income elasticities show that income elasticities for CO₂ are positive for all 10 countries. Both Singapore and Malaysia are classified as countries with high income. However, Singapore, with 0.64%, has the highest income elasticity, and Malaysia, with 0.15%, has the second lowest. There is no indication that wealthy countries have a significant impact on CO₂ through economic development. Income elasticities for SO₂ of each country are all negative. This suggests that SO₂ is an inferior good. Brunei, with 8.41%, has the most sensitivity toward change in SO₂ emissions, whereas Myanmar, with only 0.58%, is the least sensitive to SO₂ emissions.

This paper examines the economic relationships between oil price volatility and socially-economic development of 14 Organization of the Petroleum Exporting Countries (OPEC) using the annual panel data for the period 1990–2014 obtained from the World Bank (WB) statistical data sets. Hausman specification test has been performed to choose the method of panel data analysis, and the results were in favor of fixed effects estimation. The main findings indicate the direct relationship between economic growth and oil price volatility. The research supports the hypothesis that an increase in crude oil prices is positively related to GDP, and a 10% increase in oil prices correlates with 0.6-4% GDP improvements. Structural changes in employment in favor of service sector are negatively correlated with GDP per capita. Changes in GDP structure in favor of oil rents on 10% lead to the shrinking of GDP on 1%. Life expectancy at birth, as an indirect indicator of health, positively influences the economic growth indicators and an improvement in life expectancy on one percentage leads on average to 1% growth in GDP and 0.5-1.33% growth in GDP per capita. Energy efficiency improvements are positive drivers of GDP values at OPEC, and our findings suggest that a 10% increase at GDP per unit of energy use leads to 3% increase of GDP itself. The study recommends investing in energy efficiency, human capital, and capital formation to guarantee long-run economic development and prosperity of OPEC counties.

The Working Capital Management (WCM) has an important role for the firm’s success or failure, because it directly affects the overall business health of the firm. This study examined the impact of WCM on profitability and shareholders’ wealth using 50 companies listed in different sectors on the Colombo Stock Exchange (CSE) for the period from 2010 to 2015. This sample represents 47% of the selected sectors of CSE. The profitability of the company is measured using gross operating profit (GOP) and shareholders wealth measured by Tobin’s Q (TQ) ratio. The WCM is measured using five independent variables namely stock holding period (SHP), debtors’ collection period (DCP), creditors’ settlement period (CSP), cash conversion circle (CCC) and current assets ratio (CAR). Further, three additional variables such as firm size (SIZE), leverage (LEV) and earning yield (EY) are employed as controlling variables to capture the impact of other performance of the companies.
The data were analyzed using ordinary least square (OLS) and panel data regression models. These regression models reveal that there is a significant negative relationship between CCC and dependent variables (GOP & TQ). Further, this relationship has been confirmed by the major components of CCC such as SHP, DCP. Firm size also positively and significantly effects on the firm GOP while negatively effects on the TQ. Further, they revealed that there is a significant positive relationship between LEV and TQ. The study finds that the shareholders’ wealth and profitability can be increased through the efficiency of WCM.