The rapid rise in climate and ecological challenges have allowed policymakers to introduce stringent environmental policies. In addition, financial limitations may pose challenges for countries looking to green energy investments as energy transition is associated with geopolitical risks that could create uncertainty and dissuade green energy investments. The current study uses PTR and PSTR as econometric strategy to investigate how geopolitical risks and financial development indicators influence energy transition in selected industrial economies. Our findings indicate a non-linear DCPB-RE relationship with a threshold equal to 39.361 in PTR model and 35.605 and 122.35 in PSTR model. Additionally, when the threshold was estimated above, financial development indicators and geopolitical risk positively impacts renewable energy. This confirms that these economies operate within a geopolitical context, with the objective of investing more in clean energy. We report novel policy suggestion to encourage policymakers promoting energy transition and advance the sustainable financing development and ecological sustainability.
The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.
Private hospitals are expanding in Latin America, but the industry is less developed in this region than in some other emerging markets. Groups of hospitals are emerging in countries such as Brazil, Mexico, Colombia and Peru. However, they haven't reached the size of hospital groups in Malaysia, India and South Africa. They also remain domestically focused, while companies from the aforementioned three emerging markets outside Latin America have expanded to multiple other countries and have listed on stock exchanges to access more capital to finance their expansion. It is very likely that these trends seen in other emerging markets will manifest in Latin America as it continues to develop.
To boost the stability of economic and financial aspects along with the apprehensions for sustainability, it is important to promote the development of clean energy stocks around the globe. In the current research, the researchers have examined the impact of oil prices, coal prices, natural gas prices, and gold prices on clean energy stock using the autoregressive distribution lag (ARDL) approach from the year 2011 to the year 2020. The result of daily data analysis specifies that in the long as well as in the short run, gold prices, oil prices, and coal prices have a positive and significant effect on clean energy stock. On the other side, natural gas prices in the long as well as in the short run have a negative and significant effect on clean energy stock. So, the empirical analysis of our study is of interest to investors at an institutional level who aim at detecting the risk associated with the clean energy market through proper financial modeling. Besides, this study opens up a new domain to sustain financial as well as economic prospects by protecting the environment through clean energy stock as the investment in clean energy stocks results in producing a substantial effect on the economy and the environment as well.
Preventive maintenance (PM) planning becomes a crucial issue in the real world of the manufacturing process. It is important in the manufacturing industry to maintain the optimum level of production and minimize its investments. Thus, this paper focuses on multiple jobs with a single production line by considering stochastic machine breakdown time. The aim of this paper is to propose a good integration of production and PM schedule that will minimize total completion time. In this study, a hybrid method, which is a genetic algorithm (GA), is used with the Monte Carlo simulation (MCS) technique to deal with the uncertain behavior of machine breakdown time. A deterministic model is adopted and tested under different levels of complexity. Its performance is evaluated based on the value of average completion time. The result clearly shows that the proposed integrated production with PM schedule can reduce the average completion time by 11.68% compared to the production scheduling with machine breakdown time.
The emergence of mega vessels is not a new event in container shipping industry. Containerization has caused a spectacular growth in maritime transportation and brought significant developments to the industry, ranging from operation systems to seaport infrastructure expansion. Container vessels have gotten larger, with some having the capacity of 18,000 TEUs (Triple E Class), to cope with the demand for economies of scale (EOS). Mega vessels can influence the strategic planning of seaport operators for massive infrastructure development and investment on existing terminals at the seaports. The objective ofthis research is to identify and measure the requirements for seaport expansion that need to be prioritized by seaport operators to accommodate mega vessels. Additionally, this research aims to determine the challenges faced by seaport operator to meet the seaport infrastructure expansion requirements. Two mathematical methods were employed, namely Analytical Hierarchy Process (AHP) and Evidential Reasoning (ER). The results showed that the most important requirement for seaport expansion is navigation aspect followed by berth expansion, terminal, yard and gate operations. This research is expected to assist seaport operator in making a decision on prioritizing t requirements for expansion. Furthermore, this research aims to measure the readiness of seaports to serve mega vessels in global shipping industry in order to achieve competitive advantages.
In general, the nature of gold that acts as a hedge against inflation and its stable price over the course of the financial crisis has made it a unique commodity. Priceforecasts are a must for gold producers, investors and central bank to know the current trends in gold prices. Forecasting the future value of a variableis often done with time series analysis method. This study was conducted to determine the best model for forecasting gold commodity prices as well as forecasting world gold commodity prices in 2018 using Box-Jenkins approach. The data used in this study wasobtained from Investing.Com from 2015 until 2017. Thisstudy shows that ARIMA (1,1,1) is the best model to predict gold commodity prices based on Mean Absolute Percentage Error (MAPE). MAPE value for ARIMA (1,1,1) is 0.02%, where this value proves that forecasting using ARIMA (1,1,1) is the best forecasting becauseMAPE value is less than 10%.
This paper aims at solving an optimization problem in the presence of heavy tail behavior of financial assets. The question of minimizing risk subjected to a certain expected return or maximizing return fora given expected risk are two objective functions to be solved using Markowitz model. The Markowitz based strategies namely the mean variance portfolio, minimum variance portfolio and equally weighted portfolio are proposed in conjunction with mean and variance analysis of the portfolio. The historical prices of stocks traded at Bursa Malaysia are used for empirical analysis. We employed CAPM in order to investigate the performance of the Markowitz model which was benchmarked with risk adjusted KLSE Composite Index. We performed a backtesting study of portfolio optimization techniques defined under modern portfolio theory in order to find the optimal portfolio. Our findings showthat the mean variance portfolio outperformed the other two strategies in termsof performance of investment for heavy tailed assets.
Malaysia is also affected by the economic crisis as it applies the door-to-door policy economy even though the crisis has started on a global platform. Therefore, the objective of this study is to see how far economic recession affects development expenditure, domestic investment, and foreign direct investment in Malaysia. Using secondary data from 1980 to 2015, unit root tests, Johansen co-integration test, Vector Error Correction Model (VECM), and Granger-causality test were carried out. The findings showed that there was a long run relationship between the economic recession and at least one independent variable while there was no short run relationship between the variables. For causal relationships, the economic recession was the cause of domestic development and investment expenditure while foreign direct investment was the cause of the recession, domestic development, and investment spending. Hence, the government must ensure economic stability by implementing various policies.
Gold is a valuable asset to a country because of itsliquidity.Gold reserve can stabilize the currency in a country.The objectiveof this paper is to identify the factors contributingto the volatility of gold prices, such as Real Malaysia GDP, inflation rates, crude oil pricesand exchange rates. The data was analysed using Autoregressive Distributed Lag (ARDL) approachwith time series data, with 30-year coverage from 1987 to 2016. Findings showed that only Real Malaysia GDP and crudeoil priceswere significantly relatedto gold prices. As a conclusion, this study can beusedas reference byother investors.The author suggests toother researchers to further improve upon this study by adding more variables or diversifying the variables that relate to volatility of gold prices
This study examines the issues of winner's curse, size effect and bandwagon effect in explaining the under-pricing phenomenon of Malaysian IPOs, for the period from January 2001 to December 2008. The average initial return for the Malaysian private placement IPOs (a proxy for informed investors) is significantly lower than that of the non-private placement IPOs (a proxy for uninformed investors), which gives support to the winner's curse hypothesis, where uninformed investors demand a higher initial return in the absence of informed investors. Using listing board as proxy for size of companies, we find that the smaller the company, the higher the average initial return, thus giving support to size effect, where investors usually demand higher initial return for smaller companies due to their higher perceived risk. The study also finds that the presence of a large number of informed investors as compared to uninformed investors in an IPO exercise will result in an increase in demand for that particular stock in the secondary market, which gives support to the bandwagon effect.
"Smart cities" have become the development direction pursued by city leaders to address challenges related to rapid growth in urban areas. The sustainable development of the logistics sector has important practical significance for the evolution of smart cities. This study assessed the inefficiency rate and total factor productivity (TFP) of logistics in 36 Chinese cities from 2006 to 2015. The directional distance function (DDF) and Luenberger productivity index analytical approaches were used to assess the relevant parameters. The results revealed that the logistics system inefficiency rate of the eastern region was much higher than that of the central and western regions, while that of the western region was slightly higher than that of the central region. This study identified the main constraints of the logistics TFP in different regions in China. This finding is used to promote policy-making and investment planning to improve China's competitive advantage. The results documented that the central region of China needs to accelerate logistics reforms and use its location advantage of its location to form an organic connection with the eastern and western regions. Countries can use such metrics to take actions to improve their logistics performance, as such an improvement has a causal relationship with economic development.
Consumer interest in privately managed urban transport services in Indonesia are showing a declining trend. On the other hand, the presence of Transportation on Demand (ToD) based on Internet of Things (IoT) has attracted the majority of conventional fleet customers which contribute to the declining trend of occupancy. Therefore, this study aims to present a feasibility study of a small car RE60 Three Passenger and One Driver (3P+1D) four-wheeler as an alternative to replace conventional fleets. The Break-Even Point (BEP), Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP) are analyzed based on vehicle operating data. The analysis shows that there is an additional monthly income flow of IDR 1,533,122 and IDR 2,536,946 from RE60 operations compared to the high and low consumption of fuel from existing fleets, respectively. In conclusion, it is feasible to invest in small car RE60 as a replacement for the existing fleets since the fundamental indicators (BEP, NPV, IRR, and PP) showed positive results before the specified instalment period. Sensitivity analysis also shows good results, NPV shows positive results (>0) although the input conditions are made pessimistic to -30% from NPV base case. The BEP of RE60 will cut distance travelled at 190,670 km and 115,225 km, respectively. NPV of IDR 33,088,000 and IDR 80,841,000 will be obtained at the 60th month after the operation and IRR also enabled good scores, at 2.24% and 4.17%.
Studies have shown that factors like trade, urbanization, and economic growth may increase the ecological footprint (EFP) since ecological distortions are mainly human-induced. Therefore, this study explores the effect of economic growth and urbanization on the EFP, accounting for foreign direct investment and trade in Nigeria, using data from 1977 to 2016. This study used the EFP variable as against the CO2 emissions used in the previous studies since the former is a more comprehensive and extensive measure of environmental quality. We apply the novel dynamic autoregressive distributed lag (ARDL) simulations for model estimation, the Bayer and Hanck J Time Ser Anal 34: 83-95, (2013) combined cointegration, and the ARDL bounds test for cointegration. Although the results affirmed the presence of long-run relationship among the variables, economic growth deteriorates the environment in the short run, while urbanization exacts no harmful impact. In the long run, FDI and trade deteriorate the environment while economic growth adds to environmental quality. It is recommended that policymakers strengthen the existing environmental regulations to curtail harmful trade and provide rural infrastructures to abate urban anomaly.
The Belt and Road Initiative (BRI) is an ambitious development project initiated by the Chinese government to foster economic progress worldwide. In this regard, this study aims to investigate the dynamics of energy, economy, and environment among 42 BRI developing countries using an annual frequency panel dataset from 1995 to 2019. The major findings from the econometric analyses revealed that higher levels of energy consumption, economic growth, population growth rate, and FDI inflows exhibit adverse environmental consequences by boosting the CO2 emission figures of the selected developing BRI member nations. However, it is interesting to observe that exploiting renewable energy sources, which are relatively cleaner compared to the traditionally-consumed fossil fuels, and fostering agricultural sector development can significantly improve environmental well-being by curbing the emission levels further. On the other hand, financial development is found to be ineffective in explaining the variations in the CO2 emission figures of the selected countries. Besides, the causality analysis shows that higher energy consumption, FDI inflows, and agricultural development cause environmental pollution by boosting CO2 emissions. However, economic growth, technology development, financial progress, and renewable energy consumption are evidenced to exhibit bidirectional causal associations with CO2 emissions. In line with these findings, several relevant policies can be recommended for the BRI to be environmentally sustainable.
This study examined the influence of tail risks on global financial markets, which aids in better understanding of the emergence of COVID-19. This study looks at the global and Vietnamese stock markets impacted by the COVID-19 pandemic to identify systemic emergencies. Risk dependent value (CoVaR) and Delta link VaR are two important tail-related risk indicators used in Conditional Bivariate Dynamic Correlation (DCC) (CoVaR). The empirical findings demonstrate that when COVID-19's worldwide spread widens, the volatility transmission of systemic risks across the global stock market and multiple exchanges shifts and becomes more relevant over time. At the time of COVID-19, the world industrial market was larger than the Vietnamese stock market, and the Vietnamese stock market posed a lesser danger to the global market. A closer examination of the link between the Vietnam value-at-risk (VaR) range index sample and the world stock index indicates a significant degree of downside risk integration in key monetary systems, particularly during the COVID-19 era. Our study findings may help regulators, politicians, and portfolio risk managers in Vietnam and worldwide during the unique moment of uncertainty created by the COVID-19 epidemic.
Sustainable crowdfunding has emerged as a significant factor in the quest for alternative funding streams in recent times. The process has entailed the removal of financial obstacles and intermediaries, facilitating proximity between entrepreneurs' initiatives and fund providers, thereby initiating modifications in conventional investment and profitability criteria. The correlation between corporate social responsibility (CSR) and sustainable business returns is a significant metric that may enhance funding costs. CSR initiatives and crowdfunding possess the potential for mutually beneficial outcomes in terms of fundraising. However, fundraisers encounter obstacles and competition in their efforts to attain their donation objectives. As an illustration, CSR endeavors may provide a chance to raise capital via crowdfunding. Conversely, crowdfunding has the potential to serve as a means of micro-funding various social initiatives that align with a corporation's corporate social responsibility objectives. The present research investigates the correlation between efficacious donation fundraising campaigns in the context of crowdfunding endeavors that hold the possibility of transforming into corporate social responsibility initiatives. The present study investigates the correlation between the initial amount of funds raised on the first day of a fundraising campaign and the target amount of funds sought by the fundraiser, as well as the type of activities involved. The present study utilizes data derived from crowdfunding endeavors in Southeast Asian nations to scrutinize the funds amassed through donations by juxtaposing trends, cultures, and characteristics of fundraisers employing donation-based crowdfunding. The present investigation employs data collected between the period spanning from the beginning of September 2021 to the end of September 2021 in the economies of Southeast Asia, including Singapore, Indonesia, Malaysia, Thailand, and the Philippines. The present investigation utilizes the partial least squares structural equation modeling (PLS-SEM) approach for the estimation of the variables. The findings of the hypothesis indicate that there exists a positive correlation between crowdfunding, environmental nonprofit organizations, organizational profitability, and CSR.
The foremost purpose of the study is to establish a point that an economy of G-7 countries has an abundance of resources to tackle the environmental changes that occur in the world, but these countries are still behind the line because in this modern era, environmental performance changes their shape, dimension, and nature very frequently and create a huge impact on globalization of world economy. To fill this gap, we use green investment, institutional quality, and economic growth on environmental performance for this, we use four proxies for green investment and three proxies for greenhouse gas, and we also use six proxies of institutional quality to do this using period of 1997 to 2021. Moreover, we have used the panel nonlinear autoregressive distributed lag method to evaluate the long-run and short-run asymmetric effects of green investment, institutional quality, and economic growth on greenhouse gas emissions. The findings of the study affirm that the positive change of green investment has a positive and significant relationship with environmental performance, while the negative change of green investment has a significant and positive influence with environmental performance in the long run. Furthermore, the outcomes demonstrate that the positive shock of institutional quality has a positive and significant relationship with environmental performance, while the negative shock of intuitional quality has a significant and positive association with environmental performance in the long run, whereas positive change in economic growth has a positive and significant with the environmental performance, while the negative change of economic growth has a positive effect with environmental performance in the long run. This study finds future precautions that institutional quality has to perform exceptionally and shows results very rapidly, while green investment with economic growth has also made a deadly combination to control greenhouse gas emission, so the role of G-7 countries is pretty clear and straight. Furthermore, it is suggested that governments and policymakers take a proactive stance to promote resource acquisition and investment across all industries. To reduce gas emissions, public interest might also be complementary to private ones. So, economic policymakers, specifically in G-7 countries, should consider strategies that support sustainable economic growth.
Global economies have recently been concerned about sustainable environmental management by reducing emissions and tackling ecological footprints. The rapid economic expansion and investment in traditional manufacturing further raises environmental degradation. China surpasses other emerging economies in the economic growth race yet has remained the top pollution-emitting economy for the last few decades, necessitating scholarly attention. This study examines the influencing factors of ecological footprints in China from the perspective of COP27. Using the extended dataset from 1988 to 2021, this study uses several time series diagnostic tests and verifies the existence of the long-run association between the study variables. Consequently, the non-linear scattered data leads to non-parametric (method of moment quantile regression) adoption. The empirical results indicate that only economic growth is a significant factor in environmental quality degradation in China. However, improving renewable energy usage, research and development, and foreign direct investment reduces the country's ecological footprint. Hence, the latter variables substantially lead to environmental sustainability. The robustness of the results is confirmed via a robust non-parametric estimator and causality test. Based on the empirical results, this study recommends increased investment in research and development, renewable production, and foreign direct investment enhancement.
Carbon emission trading is an important environmental policy tool to promote carbon emission reduction. With the panel data of carbon emissions trading (CET) pilots, this paper used the spatial difference-in-difference model (SDID) to test whether CET can affect the enterprise environmental responsibility and the spatial spillover effect of carbon emissions trading. The study found that CET can significantly improve the environmental responsibility level of enterprises in pilot areas. The environmental responsibility level of enterprises in surrounding areas are also improved driven by CET. In the time dimension, the role of CET in improving the enterprise environmental responsibility is gradually increasing. The impact of CET on enterprise environmental responsibility has significant heterogeneity in the dimension of ownership attributes and environmental regulation. Promoting corporate environmental protection investment is the main path for CET to improve the enterprise environmental responsibility.