A general equilibrium model of macroeconomic rebound effect: A broader view

Rocha, Felipe Freitas da; Almeida, Edmar Luiz Fagundes de

doi:10.1016/j.eneco.2021.105232

Cited by 7 publications

(3 citation statements)

References 42 publications

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“…where µ jt represents the inefficiency of energy use, which follows N + 0, σ 2 µ . Considering the stochastic frontier analysis (SFA) has obvious advantages in dealing with statistical noise and the heterogeneity of the reaction technology, we adopted the SFA method to estimate Equation (13). According to the parameter estimation results of Equation ( 13), we can estimate the static energy efficiency of each DMU j using the following equation:…”

Section: Measurement Procedures For Energy Efficiencymentioning

confidence: 99%

“…In Section 4, we present an econometric model to explore the potential impacts of the RE on CO2 emissions; the data sources of all In recent years, estimating the magnitude of the RE has become the focus of this research. Many scholars have evaluated the RE based on various approaches [9][10][11][12]; however, there is still a debate about its magnitude due to the lack of unified evaluation mechanisms both in theory and practice [13,14]. Furthermore, to date, much research has been undertaken to detect the potential drivers of CO 2 emissions in terms of various aspects [15,16]; however, the potential impacts of RE on CO 2 emissions have rarely been systematically investigated, especially for the case of China.…”

Section: Introductionmentioning

confidence: 99%

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CO2 Emissions in China: Does the Energy Rebound Matter?

et al. 2022

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Enhancing energy efficiency is globally regarded as an effective way to reduce carbon emissions. In recent years, the energy efficiency of China has gradually improved; however, energy consumption and CO2 emissions are still increasing. To better understand the reasons for this, we evaluated the energy rebound effect (RE) of 30 provinces in China over the period 2001–2017 by employing stochastic frontier analysis (SFA) and the system generalized method of moments (system-GMM) approach, and explored the extent to which the RE affects CO2 emissions. Asymmetric and regional heterogeneity analyses were also conducted. The results indicate that the national average RE was 90.47% in the short run, and 78.17% in the long run, during the sample period. Most of the provinces experienced a partial RE, with a backfire effect occurring in some provinces such as Guangxi and Henan. The RE was associated with significant increases in CO2 emissions; specifically, a 1% increase in the short-run RE led to an increase in CO2 emissions of approximately 0.818%, and a 1% increase in the long-run RE resulted in an increase in CO2 emissions of approximately 0.695%. Moreover, significant regional differences existed in the impact of the RE on CO2 emissions; in regions with high emissions and a high RE, the CO2 reduction effect from the marginal decline in the RE was much more pronounced than that in other regions.

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Section: Measurement Procedures For Energy Efficiencymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

CO2 Emissions in China: Does the Energy Rebound Matter?

et al. 2022

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“…At present, many researchers have studied the regional economy. Rocha et al analyzed the rebound effect in macroeconomics [12]. This method focused on the long-term and short-term impact of energy services and non-energy inputs on the economy, put forward the impact of technological changes in energy on energy consumption, and introduced the productivity parameters of non-energy inputs.…”

Section: Introductionmentioning

confidence: 99%

Study on the Influence of Macro-control of Regional Economic Development on Resource Allocation in Capital Market

2023

HBEM

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The influence of macro-control of regional economic development on resource allocation in capital market is studied in order to optimize capital market resource allocation and promote regional economic development. The efficiency of capital market resource allocation is taken as the dependent variable, and macroeconomic regulation indicators such as monetary policy, fiscal policy, and tax policy are selected as independent variables. A multiple regression analysis model is constructed to analyze the impact of macroeconomic regulation on capital market resource allocation. The economic data of 28 provinces in eastern, central, and western China, as well as the data on capital market resource allocation, are selected for empirical analysis. The results of the empirical analysis show that significant impacts on economic growth in the eastern region are exerted by monetary policy, fiscal policy, and tax policy. Economic growth in the central region is positively influenced by monetary policy. Guidance mechanisms, information transmission mechanisms, and competition and incentive mechanisms play a significant promoting role in the allocation of capital market resources in the western region. Based on the empirical analysis results, suggestions are made for optimizing capital market resource allocation to provide reference for promoting regional economic growth.

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