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Coal’s rising prominence in the power industry has raised concerns about future CO2 emissions and energy reliability. As of 2017, it is estimated that Malaysia’s existing natural gas production can only be maintained for another 40 years. Consequently, the carbon intensity of electricity production has increased due to the increasing share of coal-fired plants and electricity infrastructure inefficiencies. To summarise, energy industries have been the highest emitters of CO2 emissions, with a 54-percent share. In response to these challenges, the government implemented a series of renewable energy (RE) policy measures. Whether these policies are sufficient in driving Malaysian energy decarbonisation is yet to be seen. In this study, we simulated different scenarios from 2015 to 2050 with an agent-based model to explore the roles of renewable energy policies towards emission reduction in the energy sector. The simulation results reveal that when all renewables initiatives were implemented, the share of RE increased to 16 percent, and emissions intensity fell by 26 percent relative to its level in 2005, albeit with increasing absolute carbon emissions. This milestone is still far below the government’s 45 percent reduction target. The simulation results demonstrate that renewable energy policies are less effective in driving Malaysian electricity towards desired low-carbon pathways. Furthermore, it is evidenced that no single approach can achieve the emission reduction target. Therefore, a combination of energy efficiency and renewable energy policy measures is unavoidable to decarbonise the electricity sector in Malaysia.

Advanced digitalization and financial technology have of recent times become among the most crucial tools. Data mining and sentiment analysis have revealed the importance of digitalization in modern times. This study examines the influence of Google search activity on the volatility of digital assets. We analyzed six digital asset prices for Bitcoin, Bitcoin Cash, Ethereum, Ethereum Classic, Litecoin, and Ripple from the Coinmarketcap database. We used tweets on Twitter to survey users’ sentiment by using the Twitter search Application Programming Interface and Google trend search from web searches, news searches, and YouTube searches data using RStudio software. The study spanned 1 September 2019 to 31 January 2020 and employed the Vector Autoregression (VAR) approach for analysis. The VAR estimation revealed that Google search variables have significantly influenced the volatility of Bitcoin, Ethereum, Litecoin, and Ripple, as supported by the Granger causality test and impulse response function. The results of this study could be useful for investors and policymakers in drawing up strategies to reduce market volatility. These results should thus be useful to investors in developing profitable investment strategies to mitigate the impact of market turbulence.

Wind is a renewable energy source. Overall, using wind to produce energy has fewer effects on the environment than many other energy sources. Wind and solar energy provide public health and environmental benefits to the social. Wind turbines may also reduce the amount of electricity generation from fossil fuels, which results in lower total air pollution and carbon dioxide emissions. In order to better optimize the effect of social energy economic management and facilitate the multiobjective decision making of coordinated development of energy and socioeconomic environment, a modeling and analysis method of economic benefits of wind power generation based on deep learning is proposed. In this paper, based on the principle of deep learning, the evaluation indicators of wind power economic benefits are excavated, a scientific and reasonable economic benefit evaluation system is constructed, a wind power economic benefit analysis model supported by public management is constructed, and the steps of wind power economic benefit analysis are simplified. It is concluded that the modeling and analysis method of wind power economic benefits based on deep learning has high practicability in the actual application process, which is convenient for the prediction and analysis of energy demand for social and economic development.

This study provides new evidence regarding the nonlinear relationship between energy consumption and economic growth in the Middle East and North Africa (MENA) region for the 1990–2014 period. The empirical estimation is conducted using a dynamic panel threshold model. We found one threshold in the relationship between energy consumption and economic growth and one threshold in the relationship between carbon dioxide (CO2) emissions and economic growth. The results indicate that energy consumption positively and significantly affects economic growth in the low energy consumption regime. In contrast, it has a negative and significant impact on economic growth in the high energy consumption regime. Moreover, CO2 emissions are positively and significantly related to economic growth in the low regime of CO2 emissions. Nevertheless, the relationship between CO2 emissions and economic growth in the high CO2 emissions regime is negative and significant. Therefore, policymakers should implement other effective energy policies, such as stricter regulations on CO2 emissions, increase energy efficiency, and replace fossil fuels with cleaner energy sources to avoid unnecessary CO2 emissions and combat global warming. Future studies should identify the root causes of failures and issues in real time for inflation and link the energy–growth nexus to achieving the 2030 Sustainable Development Goals (SDGs) Agenda, Goal 7: Affordable and Clean Energy.

A ban on palm oil imports by the European Union has become a problematic issue, especially for palm oil producers' countries. Oil palm has been widely used in many sub-sectors, and any changes in the production side may affect many sectors that use oil palm as an input factor in their productions. This study explores the chain of the oil palm sector on the other sub-sectors in Malaysia by using a value-added multiplier method and network modeling. The study focuses on the specific oil palm sub-sector and oils and fats sub-sector in the Malaysian economic structure based on the Malaysian Input-Output 2015 Table. Network visualization and all the analyses involving network methods were developed and performed using UCINET and GEPHI software. The value-added multiplier results explained that the net value between output multiplier and import multiplier is vital to depict the real impact of net resources used as an input factor in the oils and fats and oil palm sub-sectors. The high-density value level shows that the Malaysian oil palm sector has high connectivity in the economic system. From the network visualization analysis, the oils and fats sub-sector has a high level of integration with other sectors within the network. Meanwhile, the oil palm sub-sector categorized in the periphery structure group has a low level of integration in the input-output network. This is due to the high value-added demand for oil palm in the oils and fats sub-sector in the manufacturing sector. Overall, most of the sub-sectors in Malaysia are highly interconnected due to the high clustering ratio. Therefore, ensuring sufficient oil palm production is vital for sustainable production of other sub-sectors.

This article is particularly concentrated on measuring systemic risk based on network topology of bilateral exposures and obligations specifically for the sectoral level of global banking systems in 2010. Financial network models based on financial exposures are models that aim to depict causal chains of exposures and obligations of counterparties rather than rely solely on statistical correlations on market price-based data for financial institutions. Our starting point is the bilateral claims of the ultimate risk of the main institutional sectors that include banks, non-bank private sectors and non-allocated sectors of the 10 reporting countries that consist of Belgium, France, Germany, Italy, Japan, Spain, Switzerland, Turkey, the United Kingdom and the United States of America. The other non-reporting countries will be merged into one group. The results show that banking systems in countries such as the United States and the United Kingdom in particular are making vast amounts of foreign investments, implying that they constitute a central hub in the core. The results in the contagion effect show that all of the other countries are collapsed after a shock from a core country such as the United Kingdom in both rates of loss given defaults of 100 and 60 %.

The effects of climate change are diverse and impact several aspects of the environment, coastal activities, social dynamics, economic factors, and drivers of growth. This paper investigates the vulnerability assessment caused by climate change in one of Malaysia's coastal areas. We analyze the relationships between indicators of vulnerability by correlating the perceptions of a community characterised by both identified and anticipated climate change situations, whereby we develop a risk perception index that comprises cognitive, contextual, and affective factors as one of the indicators under exposure indices. The Composite Vulnerability Index (CVI) methodology was used to provide a comprehensive assessment of the community's vulnerability to climate change in Kuala Gula. The area is very vulnerable to dwindling fresh water supplies, changing climate, and poor socioeconomic resources of the local population. Data on three components of CVI (exposure, sensitivity, and adaptive capacity) were collected from household members using a close-ended questionnaire-based survey. Our analysis demonstrates that these coastal communities are prone to vulnerability and greater consequences regarding threats associated with climate change, as the CVI of Kuala Gula was considerably high. In addition, the results indicated that the exposure index was high, while the sensitivity and adaptive capacity indices were at moderate levels. From the statistical analysis of the exposure and perceptions indices, we found that an increased level of vulnerability to the impacts of climate change led to greater perceptions among Kuala Gula coastline communities regarding climate change. Furthermore, a lack of financial capital and low-income households has a detrimental impact on the overall adaptive ability of the local community. As a result, the methodology may assist local policymakers in integrating and enhancing local multi-hazard knowledge in relation to the concepts of exposure, sensitivity, and adaptive ability, as well as in making information usable for mitigation and adaptation of climate change within these communities.

Purpose The purpose of this paper is to investigate the nonlinear relationship between shadow economy and income inequality and determine whether the size of shadow economy can influence the level of income inequality. Design/methodology/approach Both parametric (panel OLS) and nonparametric/semiparametric regression suggested by Robinson (1988) will be used to capture the dynamic nonlinear relationship between these variables using unbalanced panel data of 154 countries from 2000 to 2007. Additionally, the relationship between income inequality and shadow economy on both developed and developing countries will be analyzed and compared. Findings First, semiparametric analysis and nonparametric analysis are significantly different than parametric analysis and better in nonlinear analysis between income inequality and shadow economy. Second, income inequality and shadow economy resemble an inverted-N relationship. Third, the relationship between income inequality and shadow economy is different in developed countries (OECD countries) and developing countries, where OECD countries have similar inverted-N relationship as before. However, for developing countries, income inequality and shadow economy show an inverted-U relationship, similar to the original Kuznets hypothesis. Practical implications This study suggests that there is a possible trade-off between income inequality and shadow economy and helps policy makers in solving both problems effectively. Originality/value Despite the growing importance of income inequality and shadow economy, literature linking the two variables is scarce. To the best of the authors’ knowledge, there is no literature that nonlinearly links these two variables. Furthermore, the dynamics of the relationship between these two variables in developed countries and developing countries will be explored as well.

Purpose-this study aims to investigate Malaysian stock market efficiency from the view of shariah compliant and conventional stocks based on the effectiveness of technical trading strategies. design/methodology/approach-this study uses unconventional trading strategies that mix buy recommendations of bursa Malaysia analysts with sell signals generated from 10 selected technical trading strategies (simple moving average, moving average envelopes, Bollinger bands, momentum, commodity channel index, relative strength index, stochastic, Williams percentage range, moving average convergence divergence oscillator and shooting star) that are detected using chartnexus. the period from 1 January 2013 until 31 December 2015 produces a total sample consisting of 1,265 buy recommendations of 125 shariah compliant stocks and 400 buy recommendations of conventional stocks. the study period is extended until 31 march 2016 to provide an ample time for detecting the sell signal especially for buy recommendations that are released towards the end of 2015. findings – the resulting Jensen's alpha show 8 out of 10 strategies are effective in generating abnormal returns in shariah-compliant samples while only 3 out of 10 strategies are effective in conventional samples. prominent effectiveness of technical trading strategies in shariah-compliant stocks implies clear inefficiency in that stock market segment as opposed to those of the conventional stocks. originality/value-the results based on unconventional trading strategies provide new insights of Malaysian stock market efficiency especially in shariah-compliant and conventional stocks. the paper provides more robust findings on market efficiency as firms’ equity level data were focussed together with analysts’ buy recommendations from bursa Malaysia.

The aim of this paper is to analyse the role of banks in the transmission of monetary policy and business cycle. This paper attempts to look into the assets side as a monetary policy channel to influence economic activities. Changes in the monetary policy channel give an idea to regulate and strengthen the banking industry. The different views raise the following questions: how do changes in the monetary policy transmission affect commercial banks portfolio? If bank lending plays as a monetary policy channel, does it affect the other portfolios? Do the current regulations (such as capital requirement) affect the bank portfolio behaviour? Furthermore, Generalise Least Squares method was used to estimate the monetary changes toward commercial banks portfolio. Annual data was compiled from the year 1994 until 2004. The number of observations was based on the combination of time series and crosssectional data, which is known as pooled data. In addition, an unbalanced bank-level panel data set for commercial banks was used. Finally, our results found that there exists a bank-lending channel in the case of Malaysia. JEL Classification numbers: E51; E52; E58.