Modelling the long term prices for crude oil and natural gas has been a critical undertaking of many governments, companies, and analysts. The most important goal of this exercise is to effectively project the price of crude oil and natural gas to inform and shape today’s decisions. Most long-run energy models in use today are unable to quantify properly a factor for supply growth due to technical change – a component that has played a significant role in the provision of access to newer streams of crude oil and natural gas - because the measurement of productivity and technical change at the oil and gas industry aggregate level are limited to a small set of studies for few countries.

This thesis attempts to measure the rate of change in technical change for the oil and gas industry using data from private and national major companies. Publicly available financial data are aggregated from eight major producers over a time period of at least fifteen years for the national oil companies and forty five years for the private oil companies. The time period chosen effectively covers three distinct periods of different crude oil price behavior.

Three productivity measurement methods are applied - the growth accounting, index number theory, and regression method – to measure for the rate of change in productivity and technical change for the private and national oil companies, and for the aggregate that allows to infer the rates for the entire industry. The thesis concludes that the rate of technical change for the industry can be assessed and it proposes a reasonably estimated range (1.4-1.7 per cent per year) that can be incorporated into long-run energy models. The thesis also presents insights to the drivers that influence the rate of growth. Finally, the thesis provides a dataset containing the information about output and labor and capital inputs for major oil and gas companies that can be used by researchers to enhance studies on the rate of technical change in the oil and gas industry.