The demand for residential, industrial and total electricity, 1973-1998

By D. Kamerschen, David V. Porter. 2004

238 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/5e1625eab6af5575147645abaa7e984a63fad7d0

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In Electrical and Electronic Engineering

In Renewable Energy, Sustainability and the Environment

Citations in the corpus

A Partial Adjustment Model of U.S. Electricity Demand by Region, Season, and Sector (2009, background): “Because of this problem, some researchers have promoted simultaneous equation approaches over partial adjustment models (Kamerschen and Porter 2004).”
Expecting the Unexpected: Emissions Uncertainty and Environmental Market Design (2019, background): “Kamerschen and Porter (2004) estimates a long-run industrial price elasticity of demand of -0.35 when controlling for heating and cooling degreedays.”
Response of residential electricity demand to price: The effect of measurement error (2011, background): “The majority of these studies have used panel data and a dynamic adjustment approach (Halvorsen, 1975; Houthakker, 1980; Baltagi et al., 2002; Kamerschen and Porter, 2004; Bernstein and Griffin, 2005 and Paul et al., 2009).”
Estimation of Elasticity Price of Electricity with Incomplete Information (2012, background): “Kamerschen and Porter (2004) analyze industrial, residential and aggregate demand, and Bose and Shukla (1999) estimate residential, industrial, agricultural and commercial demand.”
The Long-Run Dynamics of Electricity Demand: Evidence from Municipal Aggregation (2020, background): “The long-run elasticity estimates vary widely, from −0.3 to about −1.1 (e.g., Kamerschen and Porter, 2004; Dergiades and Tsoulfidis, 2008; Alberini and Filippini, 2011), and none of these estimates is based on quasi-experimental variation.3 Consistency in these models generally requires strong…”
Aggregate electricity demand in South Africa: Conditional forecasts to 2030 (2010, background): “Additionally, some researchers have tried to combine numerous different variables to explain electricity use [17,22,23].”
Modelling aggregate domestic electricity demand in Ghana: An autoregressive distributed lag bounds cointegration approach (2012, methodology): “The ARDL Bounds cointegration test first developed by Pesaran and Shin (1999) and later extended by Pesaran et al.”
Estimating Residential Demand for Electricity in the United States, 1965-2006 (2008, background): “Moreover, Pesaran and Pesaran (1997) argued that it is extremely important to ascertain the constancy of the long-run multipliers by testing the above error-correction model for the stability of its parameters.”
Short- and long-run electricity demand elasticities at the subsectoral level: A cointegration analysis for German manufacturing industries (2015, methodology): “Instead of taking first differences of the data, which was the common prior solution but leads to a loss of long-run 4 Also, other studies (see Kamerschen & Porter, 2004) have found that weather variables tend to be insignificant in…”
Sensitivity of Price Elasticity of Demand to Aggregation, Unobserved Heterogeneity, Price Trends, and Price Endogeneity: Evidence from U.S. Data (2016, unknown): “From Table 1, we note that with a few exceptions (e.g. Kamerschen and Porter, 2004), studies with highly aggregated data appear to produce lower price elasticity estimates than their disaggregated counterparts.”
Price Knowledge in Household Demand for Utility Services (2005, background): “…of the price variable have statistically significant effects on estimated price elasticities (e.g., Espey, Espey, and Shaw 1997; Hanemann 1998; Renzetti 2002; Arbues, Garcia-Valinas, and Martinez- Espineira 2003; Dalhuisen et al. 2003; Espey and Espey 2004; Kamerschen and Porter 2004).”