Demand Estimation Model Research Articles

The Demand for Electricity and Natural Gas in the Northeastern United States

The demand for natural gas and electricity for the residential, commercial and industrial sectors was estimated using a combination of the error-components model and seemingly unrelated regressions. The estimated demand models showed both natural gas and electricity to be price-elastic in the long run and price-inelastic in the short run in all sectors except the commercial sector in which electricity demand is unresponsive to its own price. Natural gas had negligible income elasticities in the residential and commercial sectors, and a long-run income elasticity of 2.86 in the industrial sector. Electricity had an insignificant income effect in all sectors but the industrial, where its long-run elasticity was unitary. Only in the residential demand for natural gas is the cross price elasticity substantial with the price of electricity having a long-run cross elasticity of 1.70. Fuel oil prices generally had a negative impact probably indicating a large income effect. The elasticities of adjustment were higher for natural gas than electricity, indicating a faster adjustment to change, either in response to greater instability in energy availability or reflecting more alternative fuels or both. 16 references, 4 tables.

Estimation of implicit utility models

We explore the possibility of estimating demand models derived from implicit function representations of preferences. We find that the use of standard FIML estimation methods and computer codes results in unusually troublesome methodological problems. We propose an alternative non-standard iterative algorithm for computing the FIML estimates. In any case, this class of models is very difficult to estimate

A recreation site demand and benefit estimation model

Cesario F. J. and Knetsch J. L. (1976) A recreation site demand and benefit estimation model, Reg. Studies 10, 97–104. A model useful for estimating both the numbers of visits per unit time attracted to recreation sites in a region and the primary social benefits associated with these sites is developed. The visitor component of the model predicts use as a function of the characteristics of population centers, recreation sites and spatial separation. The benefits component of the model estimates aggregate willingness to pay using an extension of the familiar Clawson-Knetsch travel cost technique. Novel features of the model include incorporation of a way to capture substitution effects of price changes and inclusion of a measure of time cost as well as money cost in the analysis. An application is provided.

Realization Of An IT Strategy For Planning ARailway Sector Under Transformation

Realization Of An IT Strategy For Planning ARailway Sector Under Transformation