Economic Elasticity of Tactical Missile Costs
Models and Methods Track
Economic elasticity is defined as the ratio of the percent change in one variable to the percent change in another variable. In missile production, it is hypothesized that two forms of elasticity dominate: price elasticity of demand and production cost improvement. The former implies prices and demand are inversely proportional, meaning if like goods (e.g., missiles) are cheaper, we tend to buy more of them. Production cost improvement is defined simply as the reduction of costs of successive units. Cost improvement curve theories, such as unit learning, explain the converse effect: “If we can buy a greater quantity of an item, its relative cost decreases between successive units.”
In this presentation, the author answers the question: “Which theory dominates in weapons system markets such as missiles?” In the case of missiles, one way to sort out which of the two effects (i.e., price elasticity of demand and production cost improvement) dominate is to examine the lot quantity purchases of different lots for the same missiles. Since the lot average unit cost of successive lots are presumably cheaper due to production cost improvement, we should see a trend towards greater lot buys of successive lots. If this effect is not evident (i.e., we buy consistently the same number of missiles or fewer in successive lots), then the cost improvement paradigm should dominate since we are still on the “learning curve.”
Raymond P. Covert
Mr. Covert is a Technical Director at MCR, LLC and the Chief Practitioner for Cost and Schedule Analysis. He has been involved with cost and schedule analysis for space systems for the past eighteen years. In his twenty-six years in DoD weapon system and aerospace engineering he has also been employed at The Aerospace Corporation, Tecolote Research, Inc., LTV Corporation and several divisions of Northrop Grumman Corporation in the United States and the United Kingdom. He has specific experience in systems analysis, systems integration, parametric analysis, risk analysis, digital filtering, algorithm development, and simulation.