Short-Run Crude Oil Price and Surplus Production Capacity

Abstract

Crude Oil Price, Petroleum Inventory, Surplus Production Capacity, Q40,

A Short-Run Crude Oil Price Forecast Model with Ratchet Effect

“…Meanwhile, recent OPEC policy of not accommodating this increased demand with higher crude oil production and increased investment in larger production capacity resulted in little excess production capacity since the middle of 2004, and along with market fears of supply shortages, created significant upward pressures on crude oil prices. 13 See Ye et al (2006). 12 Dynamic forecast refers to a multi-step forecast using actual values of the exogenous variables, but using model predicted values for the endogenous variable.…”

“…However, as world demand grew, this excess capacity diminished, reducing the perceived ability of producers to meet demand increases in the short term. Improvements in forecasting capabilities were seen when an excess production capacity variable was added as an additional predictor in the forecast model (see, for example, Ye et al 2006). However, since early 2004, estimated inventories and excess production capacity significantly under-predict WTI prices, even with shift factors added to the model to reflect possible structural changes.…”

Methodology for examining the relationship between oil rent and crude oil production: Evidence from Cameroon

“…In addition, the price of crude oil influences the production of crude oil [ 39 , 1 ] and production influences the price of crude oil [ 40 , 41 ] . If the price remains high in a context where the oil fields are located either in a hostile environment or in difficult exploitation conditions, then the oil producing multinationals will be very cautious.…”

A New Theory to Forecast the Price of Nonrenewable Energy Resources with Mass and Energy-Capital Conservation Equations

“…Sadorsky [69] used several different univariate and multivariate statistical models to estimate forecasts of daily volatility in petroleum future price returns. Ye et al [70] showed the effect that surplus crude oil production capacity has on short-term crude oil prices. Moshiri and Foroutan [71] modelled and forecasted daily crude oil future prices from 1983 to 2003, listed in NYMEX, applying ARIMA and GARCH models, tested for chaos using embedding dimension, BDS(L), Lyapunov exponent, and neural networks tests, and set up a nonlinear and flexible ANN model to forecast the series.…”