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Smart meter datasets have recently transitioned from monthly intervals to one-second granularity, yielding invaluable insights for diverse metering functions. Clustering analysis, a fundamental data mining technique, is extensively applied to discern unique energy consumption patterns. However, the advent of high-resolution smart meter data brings forth formidable challenges, including non-Gaussian data distributions, unknown cluster counts, and varying feature importance within high-dimensional spaces. This article introduces an innovative learning framework integrating the expectation-maximization algorithm with the minimum message length criterion. This unified approach enables concurrent feature and model selection, finely tuned for the proposed bounded asymmetric generalized Gaussian mixture model with feature saliency. Our experiments aim to replicate an efficient smart meter data analysis scenario by incorporating three distinct feature extraction methods. We rigorously validate the clustering efficacy of our proposed algorithm against several state-of-the-art approaches, employing diverse performance metrics across synthetic and real smart meter datasets. The clusters that we identify effectively highlight variations in residential energy consumption, furnishing utility companies with actionable insights for targeted demand reduction efforts. Moreover, we demonstrate our method's robustness and real-world applicability by harnessing Concordia's High-Performance Computing infrastructure. This facilitates efficient energy pattern characterization, particularly within smart meter environments involving edge cloud computing. Finally, we emphasize that our proposed mixture model outperforms three other models in this paper's comparative study. We achieve superior performance compared to the non-bounded variant of the proposed mixture model by an average percentage improvement of 7.828%. [ABSTRACT FROM AUTHOR]

This study examines the impact of energy consumption, urbanization, and globalization on environmental degradation proxied by carbon emissions (CO2) in the South Asian Association for Regional Cooperation (SAARC) countries, namely Sri Lanka, Pakistan, Maldives, Nepal, Bhutan, Bangladesh, and India using data over the period 1990–2018. The cross-sectional autoregressive distributed lag (CS-ARDL), pooled mean group (PMG), and Dumitrescu and Hurlin (D-H) Granger causality techniques are employed for the empirical analysis. First and second-generation panel unit root tests are used to determine the stationary level of all data series which reveals mixed order of integration. The empirical findings show that urbanization, gross domestic product (GDP) per capita income, energy consumption, industrial growth, globalization, and financial development cause CO2 emissions, while the other variables, namely arable land and innovation, put negative effects on CO2 emissions. Moreover, the D-H heterogeneous test results exhibit that bi-directional relationship exists between CO2 and arable land, urbanization, industrial growth, and financial development, while a unidirectional causality exists between CO2 emissions and GDP per head income. These findings suggest that planned urbanization, investment in renewable energy sources, and effective strategies regarding the economic and financial integration with the global economies are required for a clean and green environment. [ABSTRACT FROM AUTHOR]

Achieving sustainable development is the prime objective of every government. Based on Solow's theoretical proposition, this study attempts to explore empirically the linkages between tourism, energy consumption, and economic growth, for the top nine Asian travel and tourism countries including Indonesia between 1995 and 2018. The fully modified ordinary least squares method and Granger's causality approaches are implemented for empirical analysis. The empirical result reveals that tourism has a statistically positive impact on economic growth in Asia's top nine travel and tourist countries. Moreover, energy consumption, exports, and savings have also a positive and statistically significant impact on economic growth. The results of panel Granger causality tests demonstrate that there is a mutual interdependence between tourism, energy consumption, and economic growth in the selected panel country group. The empirical finding indicates the positive influences of tourism on economic growth; therefore, the government must strive to formulate a policy that would help to build infrastructural adequacy and promote tourism development in Asian countries. [ABSTRACT FROM AUTHOR]

We examine the relative performance of the industry, services, and agriculture sectors in energy conservation and reduction in CO2 emissions in Pakistan using the "spatial-temporal decomposition" method by taken data from 2006 to 2016. An efficient way to achieve low-carbon economy targets is to decompose different factors contributing to CO2 emissions, including structure effect, intensity effect, GDP gap effect, energy use efficiency effect, and economic efficiency. We classify economic sectors into three groups based on performance, i.e., sectors performing below, average, and above-average performing. Our results indicate that the economic efficiency and energy use efficiency effects in the industry sector have remained above average. In contrast, the GDP gap effect has remained below average. In the case of structure effect and intensity effect, the agriculture sector has performed on average. In contrast, the service sector has shown mixed results in all factors. The government should pay special attention to energy use structure and innovation to improve desirable output technical efficiency to achieve the target carbon emission level. [ABSTRACT FROM AUTHOR]

The pivotal role of energy in the progression of economic growth cannot be overlooked. Given its importance to policymakers, the influence of energy use on economic growth is undeniably crucial and thus should be explored meticulously. This study empirically examines the impact of energy on economic growth within the production function framework of a panel of 10 developing Asian economies from 1990Q1 to 2014Q4. The pooled mean group, fully modified ordinary least squares, and dynamic ordinary least squares methods are implemented. Empirical results reveal that energy has a significant positive impact on economic growth, thereby suggesting that energy is an important factor of production in addition to human and physical capital. The implication of the finding suggests that all 10 Asian economies are energy dependent and thus can propel economic growth by sustaining energy supply, which can largely improve social welfare. [ABSTRACT FROM AUTHOR]

The role of energy cannot be passed over in the process of economic growth and development in any economy. China consumes colossal quantity of energy; thus, the central objectives of this study is to empirically evaluate the linkages among energy use, environment by CO2 emissions, human health by health expenditures, Foreign Direct Investment (FDI) inflows, and real GDP per capita used for economic growth over the period of 1995–2016 for China. The nature of the data directed to employ the Canonical cointegrating regression (CCR) method for unknown parameter estimation. Four equations have estimated namely for FDI, health, environment, and economic growth. The result for China during the period under the study reveals that energy consumption has significant positive impact on FDI, health, environment, and economic growth. The study results suggest that policy makers need to chalk out effective policy for effective utilization of energy so as to encourage permissible economic growth and development in China. [ABSTRACT FROM AUTHOR]

An increasing number of studies reveal that tourism industry makes a substantial contribution towards socioeconomic growth and development of tourism led economies. However, tourism steered economic growth and development is achieved at the cost of environmental pollution and degradation. The main objective of this study is to examine the effect of tourists’ arrivals on environmental pollution caused by Carbon Dioxide emissions in Malaysia, Thailand and Singapore over the period of 1990–2014. Some other regressors namely energy consumption and income are also used in the multivariate model. The Zivot–Andrews test is employed to determine unit-root and presence of structural break in the data. Fully Modified Ordinary Least Squares estimator is used as an analytical technique for unknown parameters estimation. The empirical results reveal that tourism has a significant positive effect on environmental pollution in Malaysia. However, an inverse relationship between tourism and environmental pollution is observed in Thailand and Singapore. Empirical findings suggest that sustainable economic growth and development should be ensured by implementing prudent public policy where host governments must strive to promote socially and environmentally responsible tourism industries in their respective countries. [ABSTRACT FROM AUTHOR]

The current study investigates the dynamic relationship between structural changes, real GDP per capita, energy consumption, trade openness, population density, and carbon dioxide (CO) emissions within the EKC framework over a period 1971-2013. The study used the autoregressive distributed lagged (ARDL) approach to investigate the long-run relationship between the selected variables. The study also employed the dynamic ordinary least squared (DOLS) technique to obtain the robust long-run estimates. Moreover, the causal relationship between the variables is explored using the VECM Granger causality test. Empirical results reveal a negative relationship between structural change and CO emissions in the long run. The results indicate a positive relationship between energy consumption, trade openness, and CO emissions. The study applied the turning point formula of Itkonen (2012) rather than the conventional formula of the turning point. The empirical estimates of the study do not support the presence of the EKC relationship between income and CO emissions. The Granger causality test indicates the presence of long-run bidirectional causality between energy consumption, structural change, and CO emissions in the long run. Economic growth, openness to trade, and population density unidirectionally cause CO emissions. These results suggest that the government should focus more on information-based services rather than energy-intensive manufacturing activities. The feedback relationship between energy consumption and CO emissions suggests that there is an ominous need to refurbish the energy-related policy reforms to ensure the installations of some energy-efficient modern technologies. [ABSTRACT FROM AUTHOR]

The objective of the study is to empirically examine the effects of urbanization, energy consumption, and per capita GDP on CO2 emissions for all member countries from BRICS. Panel data over the period 1990-2014 and the STRIPAT model are used. After panel unit root tests, the method of fully modified Ordinary Least Squares (FMOLS) is applied as an analytical technique. Empirical results reveal that urbanization has a positive and significant relationship with CO2 emissions in all BRICS countries with the exception of Russia. Results also show that GDP per capita in cases of Brazil, Russia, and South Africa will help to mitigate CO2 emissions, while the results are opposite in the cases of India and China. Likewise, energy consumption is positively and significantly causing CO2 emissions in cases of Brazil, India, and China, whereas, it is helping to reduce CO2 emission in Russia, while energy consumption has no impact in the case of South Africa. The findings of the study suggest important policy implications. This study recommends introducing less pollution emission of transport, and constructing long-term and effective system in renewable energy development in order to mitigate side effects of urbanization on the environment. © 2016 American Institute of Chemical Engineers Environ Prog, 36: 523-531, 2017 [ABSTRACT FROM AUTHOR]

The basic objective of this study is to empirically estimate the Environmental Kuznets Curve ( EKC) hypothesis for four countries from low income, lower middle income, upper middle income and high income countries namely Tanzania, Guatemala, China and the USA, respectively. For the empirical investigation an econometric model consists of Carbon Dioxide (CO 2 ) emissions used a proxy for environmental degradation as a response variable, while, income, income square, energy consumption, urbanization growth rate, and trade openness are as regressors. Annual time series data covering the time period 1975–2014 are used for the empirical investigation. Results of Johansen co-integration test indicate that there exists one co-integrating relationship among the variables in the case of the USA and China, while in the case of Tanzania and Guatemala, there exist two co-integrating linkages. Similarly, the Pearson correlation result among the five variables shows that energy consumption has a significant positive relationship with trade openness and CO 2 emissions in Tanzania, the USA, Guatemala and China, whereas, a significant negative relationship with economic growth in all these countries has been observed. The empirical results also reveal that in the case of Tanzania and China, trade openness has a significant positive relationship with environmental degradation, while in case of the USA and Guatemala, the correlation with urbanization growth rate is found significant with a negative sign. The ordinary least square result supports an EKC hypothesis for low and lower middle income countries. However, the study fails to find any support for the validity of an EKC hypothesis for upper middle income and high income countries during the period under the study. [ABSTRACT FROM AUTHOR]

This study aims to investigate the causal nexus between energy consumption and economic growth for 119 countries from all over the world having at-least 30 years of available data on candidate variables, including 30 high income OECD, 13 high income non-OECD, 65 middle income and 11 low income countries. The study employs Granger-causality in the frequency domain context for empirical analysis, which allows one to examine the causal nexus over different frequencies and thus provides relatively a better picture of the causal nexus between the candidate variables. In particular, we examine the temporary (short-run) as well as at permanent (long-run) causal nexus between energy consumption and economic growth. The empirical results suggest that 18 countries (including 5 high income OECD, 2 high income Non-OECD, 10 middle income and 1 low income) confirm the existence of feedback hypothesis, 25 countries (including 4 high income OECD, 3 high income non-OECD, 14 middle income and 4 low income) confirm growth hypothesis out of total 119 countries. Similarly, 40 countries (including 6 high income OECD, 6 high income non-OECD, 27 middle income and 1 low income) suggest conservation hypothesis, while, 36 countries (comprising of 15 high income OECD, 2 high income non-OECD, 14 middle income and 5 low income) hold neutrality hypothesis between energy consumption and economic growth out of 119 countries. The findings of the study suggest that an appropriate and effective public policy is required for all sample countries both in the short and long-term, while considering sustainable economic growth and development. [ABSTRACT FROM AUTHOR]

The objective of the study is to examine the relationship between military expenditures and unemployment rate in the panel of selected SAARC countries namely India, Nepal, Pakistan and Sri Lanka over the period ranging from 1990 to 2013. In particular, the study used multivariate framework to examine the long-run relationship between military expenditures and unemployment rate by taking into account the effect of macroeconomic variables namely energy consumption, GDP per capita, Foreign Direct Investment (FDI) net inflows and population growth rate. The empirical results show that all the variables exhibit non-stationary behavior and have long-run relationships between them. The results of panel DOLS show that military expenditures favor the employment rate in the SAARC region, as the estimated coefficient of military expenditure has a negative and more elastic relationship with the unemployment rate. Other factors i.e., energy consumption, GDP per capita and incoming FDI significantly decreases the unemployment rate in the SAARC region. However, population growth rate does not exhibit significant association with the unemployment rate during the period under the study. In a second regression apparatus, energy consumption, and GDP per capita significantly decrease the military spending, however, population growth rate significantly increases the military expenditures in the region. The results of causality indicate that there is an inverse causality between energy consumption, GDP per capita and population growth rate with the unemployment rate, while there is no significant causation between military spending and the rest of the variables in the short-run. In the long-run, there is a significant causation between the variables with the exception of population growth rate in SAARC region. These results are valuable both for policy makers and government officials to formulate their strategic polices for SAARC countries. [ABSTRACT FROM AUTHOR]

The present study identifies and evaluates the macroeconomic factors that determine energy consumption in Greece. This study is based on annual time series data covering the period ranging from 1975–2013. The Augmented Dickey Fuller (ADF) test and KPSS test are employed in order to test stationarity of the data, confirming that all the variables are I(1). Within the next step of the methodology we employed a VECM model in order to detect causality among the variables through the Granger causality test. Similarly, the impulse response analysis provides that urbanization, infrastructure, trade, income, population growth, and foreign direct investment are the main determinants of energy consumption in Greece during the period surveyed. The findings suggest that in order to fulfill the energy demand in the country, the decision-makers need to formulate energy policy in favor of enlarging the supply of energy and especially renewable energy to foster the process of economic growth and development. Especially, in the times of crisis the particular determinants are a necessity to initiate economic growth. [ABSTRACT FROM AUTHOR]

The main purpose of this work is to analyze the impact of environmental degradation proxied by CO emissions per capita along with some other explanatory variables namely energy use, trade, and human capital on economic growth in selected higher CO emissions economies namely China, the USA, India, and Japan. For empirical analysis, annual data over the period spanning between 1971 and 2013 are used. After using relevant and suitable tests for checking data properties, the panel fully modified ordinary least squares (FMOLS) method is employed as an analytical technique for parameter estimation. The panel group FMOLS results reveal that almost all variables are statistically significant, whereby test rejects the null hypotheses of non cointegration, demonstrating that all variables play an important role in affecting the economic growth role across countries. Where two regressors namely CO emissions and energy use show significantly negative impacts on economic growth, for trade and human capital, they tend to show the significantly positive impact on economic growth. However, for the individual analysis across countries, the panel estimate suggests that CO emissions have a significant positive relationship with economic growth for China, Japan, and the USA, while it is found significantly negative in case of India. The empirical findings of the study suggest that appropriate and prudent policies are required in order to control pollution emerging from areas other than liquefied fuel consumption. The ultimate impact of shrinking pollution will help in supporting sustainable economic growth and maturation as well as largely improve society welfare. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between energy consumption and carbon dioxide emission in the causal framework, as the direction of causality remains has a significant policy implication for developed and developing countries. The study employed maximum entropy bootstrap (Meboot) approach to examine the causal nexus between energy consumption and carbon dioxide emission using bivariate as well as multivariate framework for Malaysia, over a period of 1975-2013. This is a unified approach without requiring the use of conventional techniques based on asymptotical theory such as testing for possible unit root and cointegration. In addition, it can be applied in the presence of non-stationary of any type including structural breaks without any type of data transformation to achieve stationary. Thus, it provides more reliable and robust inferences which are insensitive to time span as well as lag length used. The empirical results show that there is a unidirectional causality running from energy consumption to carbon emission both in the bivariate model and multivariate framework, while controlling for broad money supply and population density. The results indicate that Malaysia is an energy-dependent country and hence energy is stimulus to carbon emissions. [ABSTRACT FROM AUTHOR]

The objective of this study is to examine the causal relationship between energy consumption and economic growth for ASEAN-5 countries which includes Indonesia, Malaysia, Thailand, Singapore, and the Philippines. For empirical examination annual time series data in the period of 1980–2012 are used. The results of Johansen co-integration test reveal that there exists one co-integrating relationship among the variables in case of Indonesia, Malaysia, the Philippines and Singapore. The results uncover the existence of two co-integrating associations among the variables for Thailand. The Granger causality test suggests that there is no unilateral causality for Indonesia as in all the three cases. In case of Malaysia the economic growth caused energy consumption, however, no evidence is found for causality either from exports or from gross fixed capital formation to energy consumption. While, in the cases of Thailand and the Philippines the direction of causality runs from gross fixed capital formation to energy consumption. For Singapore, energy consumption runs from two sides i.e. one from exports side and the other from gross fixed capital formation side. The findings exhibit that energy consumption has significant and long run relationship to economic growth for almost all ASEAN-5 countries. The findings suggest that policy makers need to formulate policies conducive to the energy development which will consequently accelerate sustainable economic growth in ASEAN countries. Energy development should be based on the existing condition of each country. A comprehensive investment framework for renewable energy should also be developed besides maintaining adequate energy inventory. The ASEAN countries should strengthen their institutions and capacity as well as cooperation in energy management and development. [ABSTRACT FROM AUTHOR]

The aim of this study is to verify empirically the impact of various factors on energy consumption in three ASEAN countries namely Indonesia, Malaysia and Thailand over the period 1980 to 2012. After using sundry appropriate diagnostic tests for checking time series data, the method of least square as an analytical technique is used for parameters estimation. The findings validate that FDI inflows, economic growth, trade openness and human development index have positive and statistically significant impacts on energy consumption. The other variable urbanization has positive and statistically significant impacts on energy consumption for Thailand and Indonesia only. While, the empirical results reveals that population growth rate has a positive and statistically significant relationship with energy consumption only in the case of Malaysia. So, in the light of determinations of the study, the policy implication is that energy policy needs to be orientated in favor of expanding the supply of energy to reach an enhanced degree of sustainable economic growth and development. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the impacts of some central explanatory variables namely Foreign Direct Investment (FDI), infrastructure facility, saving, inflation, income and energy use on Romanian's stock market development measured by market capitalization. For empirical examination, this study used annual time series data over the period of 1990 to 2013. The study employs various diagnostic tests including normality test, Pearson correlation test, Park test and DW- test, which shows that there is no problem of skewness and kurtosis, no problem of heteroscedasticity and no problem of autocorrelation in the model of market capitalization used for Romania. The Johanson co-integration results indicates that there exists three cointegrating relationship among the variables. Further, least squares estimate indicates incoming FDI, infrastructure, saving, energy usage and income are important determinants of Romanian's stock market in selected macroeconomic variables used in the study. The empirical findings suggests that management authorities of Romania needs to formulate prudent macroeconomic stabilization policy in order to encourage incoming FDI, facilitate physical infrastructure, encourage saving, maintain sustainable energy use. Thus, all these measures will further develop largely Romanian's stock market. [ABSTRACT FROM AUTHOR]