Supply, demand and drilling and exploration elasticities in natural gas: An empirical estimation framework.

摘要

Chapters 1 and 2 estimate short-run supply and demand, and drilling and exploration elasticities in U.S. natural gas. The modeling framework presented here is the first to utilize weather-related instruments to identify both demand and supply-side parameters in natural gas. Weather shocks in the current month shift demand, permitting identification of short-run supply and drilling and exploration curves. Lagged, weather-induced storage shocks shift supply, permitting identification of the short-run demand curve.;Preferred estimates of aggregate demand range from (-0.14) to (-0.19). Elasticity varies by consumer type with industrial users the most inelastic at (-0.20) and residential utilities the most relatively elastic at (-0.46). Electricity generators exhibit elasticity of (-0.21). Estimates of supply elasticity range from (0.98) to (1.28). OLS regressions show that uninstrumented estimates are significantly downward biased.;Estimates of drilling and exploration activity first show a statistically significant increase five to six months after a price shock. This is the first study to examine the price response dynamics of drilling activity on a time scale shorter than one year. Maximum elasticity for the exploratory wells is (1.0), for developmental wells is (1.24), and for the number of active rotary rigs is (0.57). Again, OLS regressions reveal that uninstrumented estimates are significantly downward biased.;Chapter 3 examines the effect of entry on incumbent airline price dispersion. Three econometric methods are employed; a long-range event study, a control function and 2SLS regression. The primary hypothesis tested, is that dominant capacity share at the origin airport provides proportionately more protection for an incumbent's premium fares. There is some evidence that this occurs. Airlines with greater than 50% or 75% share are found to decrease base fares more than premium fares in response to competitor entry, although the effects are not statistically significant.;The 2SLS regression finds that entry on a route by a low cost airline decreases incumbent price dispersion 26% and average fare by 68%. Entry by a legacy airline decreases incumbent price dispersion by 18% and average fare by 10%. Additionally, similar to other recent works incumbents are found to consistently decrease fares several quarters before entry actually occurs.