The demand for natural gas in the Northeastern United States

Gautam, Tej K.; Paudel, Krishna P.

doi:10.1016/j.energy.2018.06.092

Cited by 25 publications

(11 citation statements)

References 45 publications

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“…In 2016, Burke and Yang [14] estimated the long-run price and income elasticities of the aggregate natural gas consumption in 44 countries by using national data, Sun and Ouyang [48] investigated the price and income elasticities of the consumption of natural gas, electricity and transport fuels in the household sector inside China. In 2018, Ota et al [49] studied empirically the demographic impacts on electricity and natural gas consumption in the residential sector in 45 prefectures in Japan between 1990 and 2010, Gautam and Paudel [50] Zhang et al [16] analyzed the demand for natural gas by investigating the long-run price and income elasticities in various sectors in China using an Autoregressive Distributed Lag (ARDL) model. Chai et al [51] performed a met-regression analysis on previous studies on estimating price elasticities of natural gas to set up a benchmark value of elasticities, Zeng et al [52] investigated the response of natural gas consumption to a price change in the household sector and analyzed the mean factors impacting the demand for natural gas in China.…”

Section: Overview Of the Literaturementioning

confidence: 99%

Economic, environment and demographic elasticities of natural gas demand: A review

Malzi

2024

RMd

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This paper conducts a comprehensive review of various estimates for natural gas demand responses. We consider a stream of empirical studies that have been conducted after 1950. The purpose of this paper is to provide the full image, synthesize and analyze the published studies in this field from the first experimental study to the beginning of 2019. In this study, we discuss the methods and techniques used, the application area, the variables, and data sources and data size. Most studies have investigated price and income elasticities; many fewer have focused upon demographic variables. This work will be of significant importance for future researchers aiming to analyze the demand for natural gas.

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Section: Overview Of the Literaturementioning

confidence: 99%

Economic, environment and demographic elasticities of natural gas demand: A review

Malzi

2024

RMd

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“…In previous energy research [1][2][3][4][5], demographic factors such as the elderly, population density, and urbanization have received little attention, despite the fact that they influence household natural gas consumption explicitly or implicitly. Furthermore, with the exception of Gautam et al [5], the majority of these research are based on data from before 2010, and it is critical to update studies, especially in this economic field where inputs are rapidly changing.…”

Section: Figurementioning

confidence: 99%

The Dynamic of Residential Energy Demand Function: Evidence from Natural Gas

Malzi¹

2022

Natural Gas - New Perspectives and Future Developments [Working Title]

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This analysis uses annual data on residential gas use for 29 Organization for Economic Cooperation and Development nations from 2005 to 2016 to look at per capita energy demand. The effect of price and income on natural gas demand elasticities has been studied in the past, but most research have ignored demographic aspects. The goal of this study is to incorporate these characteristics into natural gas demand modeling. A dynamic panel system dubbed the Generalized Method of Moments (GMM) estimator was used to address the endogeneity issue. The following are the study’s main findings: First, the residential sector consumes more natural gas per capita as the population grows. Second, the consumption of per capita residential natural gas in Organization for Economic Cooperation and Development countries is decreasing as the population ages. Finally, as the population density rises, so does per capita gas consumption.

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“…The basic logic in this method is to test for cointegration by determining whether there are error corrections for individual panel members or for the entire panel. This method is one of the most suitable cointegration test methods that can be used in case of unit root and cross-sectional dependence (Gautam and Paudel, 2018). Error correction based cointegration tests are very flexible and allow heterogeneous determination of both long-and short-term specifications of the error correction model (Westerlund, 2007).…”

Section: Econometric Modelling and Estimation Strategymentioning

confidence: 99%

The Nexus of Economic Growth, Trade Openness and Banking Sector Depth In OIC: An Application of Panel Data Analysis

Durak

Eroğlu

2019

Alphanumeric Journal

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This article is investigated the connections between economic growth, trade openness and banking sector depth, using a panel data set including seventeen countries in the Islamic Cooperation Organization (OIC), where participation and conventional banking co-exist, for the period 1990-2016. Using a multivariate framework, it is primarily found that all the variables are not integrated of order one (I). Since the series are not stationary, cross-dependence tests and Westerlund (2007) cointegration analysis are performed to the series and it is determined that the series are cross-dependent and cointegrated. Then, the models are estimated with three estimators by writing the panel as panel ARDL model to determine the long-term and short-term relations. The results of the study indicate a general long-run equilibrium connection between economic growth, trade openness and banking sector depth as well as a short-run connection among these variables. Policy suggestions include those that will increase greater banking sector depth as well as promoted trade openness.

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The demand for natural gas in the Northeastern United States

Cited by 25 publications

References 45 publications

Economic, environment and demographic elasticities of natural gas demand: A review

Economic, environment and demographic elasticities of natural gas demand: A review

The Dynamic of Residential Energy Demand Function: Evidence from Natural Gas

The Nexus of Economic Growth, Trade Openness and Banking Sector Depth In OIC: An Application of Panel Data Analysis

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