Reducing carbon dioxide (CO2) emissions has become a global consensus in response to global warming and climate change, especially to China, the largest CO2 emitter in the world. Most studies have focused on CO2 emissions from the production sector, however, the household sector plays an important role in the total energy-related CO2 emissions. This study formulates an integrated model based on...

In a comprehensive LMDI-STIRPAT-ARDL framework, this research investigates the residential electricity consumption (REC)-income nexus in Morocco for period 1990 to 2018. The logarithmic mean Divisia index (LMDI) results show that economic activity and intensity are leading drivers of Morocco’s REC, followed by population structure. And then, LMDI analysis was combined with stochastic impacts re...

This study investigates ways to effectively reduce carbon dioxide (CO2) emissions in Indonesia’s manufacturing industry, by firm characteristics. It is important determine the characters that have greatest potential decrease CO2 emissions. The Logarithmic Mean Divisia Index (LMDI) method used decompose into key factors influencing changes emissions, such as economic activity, industrial structu...

Previous work has used neural networks to predict the rate of inflation in Taiwan using four measures of ‘money’ (simple sum and three divisia measures). In this work we develop a new approach that uses an evolutionary strategy as a predictive tool. This approach is simple to implement yet produces results that are favourable with the neural network predictions. Computational results are given.

Electricity substitution is an effective measure for reducing pollutant emissions and promoting the consumption of renewable energy. The current research lacks a quantitative analysis method factors affecting regional electricity substitution. This article proposes decomposition model based on Logarithmic Mean Divisia Index to expand depth breadth Results show that: (1) Macro-level in Guangdong...

As a less-developed province that has been chosen to be part of a low-carbon pilot project, Yunnan faces the challenge of maintaining rapid economic growth while reducing CO2 emissions. Understanding the drivers behind CO2 emission changes can help decouple economic growth from CO2 emissions. However, previous studies on the drivers of CO2 emissions in less-developed regions that focus on both ...

Xinjiang's agricultural carbon emissions showed three stages of change, i.e., continued to rise, declined and continued to rise, during 1991-2014. The agriculture belonged to the "low emissions and high efficiency" agriculture category, with a lower agricultural carbon emission intensity. By using the logarithmic mean divisia index decomposition method, agricultural carbon emissions were decomp...

This study analyzes carbon emission trends and drivers in 40 major economies using the WIOD database, a harmonized and consistent dataset of input-output table time series accompanied by environmental satellite data. We use logarithmic mean Divisia index decomposition to (1) study trends in global carbon emissions between 1995 and 2009, (2) attribute changes in carbon emissions to either influe...

The United States of America is not only an important energy consuming country, but also in the dominant position of energy for many years. As one of the two largest emitters, the US has always been trying to register a decline in energy-related CO2. In order to make a further analysis of the phenomenon, we choose a new decoupling analysis with the multilevel logarithmic mean Divisia index (LMD...

BACKGROUND Body mass index (BMI) tends to be higher among shorter adults, especially women. The dependence of BMI-height correlation on age and calendar time may inform us about temporal determinants of BMI. METHODS Series of cross-sectional surveys: Health Survey for England, 1992-2011. We study the Benn Index, which is the coefficient in a regression of log(weight) on log(height). This is a...