An almost ideal supply system estimate of US energy substitution

Alexi Thompson

Energy Economics, 2013, vol. 40, issue C, 813-818

Abstract: This paper introduces a Linear Almost Ideal Supply System (LAISS) model to examine aggregate US energy demand. Based on the Almost Ideal Demand System (AIDS) model, the LAISS model is a flexible functional form for imposing and testing properties of demand for the inputs of production. Own and cross price elasticities are derived for aggregate capital, labor, and energy, and compared to the translog cost function. Both models reduce to estimating a system of input share equations on input prices and output, with output normalized by the Stone's input price index in the LAISS model. Results indicate that all inputs are substitutes in both models, but elasticities differ. A log likelihood dominance criterion shows that the LAISS model dominates the translog cost function for this dataset. Results suggest that inputs are substitutes, and that an energy import tariff would increase demand for labor and capital.

Keywords: Almost ideal supply system; Energy substitution; Translog cost function (search for similar items in EconPapers)
JEL-codes: L50 L60 O13 Q40 Q43 Q48 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S014098831300220X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:40:y:2013:i:c:p:813-818

DOI: 10.1016/j.eneco.2013.09.025

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().