Private and Social Learning in Oil and Gas Extraction
Saturday, Jan. 4, 2020 8:00 AM - 10:00 AM (PDT)
- Chair: Mark Agerton, University of California-Davis
Well Confidentiality Laws and Oil and Gas Investment
AbstractUncertain investment opportunities, like oil and gas exploration, often have information externalities. If realized investment outcomes are correlated across opportunities (i.e. wells) and observable, a social planner will often be able to invest more efficiently than uncoordinated competing firms can (Hendricks and Kovenock (1989)). While concentrated ownership of drilling rights solves this problem, the decentralized nature of mineral leasing markets makes split ownership quite common. In response, many states impose a period of “well confidentiality,” during which an investing firm can maintain secrecy about the outcomes of its exploration activities. While secrecy mitigates some free-riding concerns, it may also exacerbate coordination issues. Moreover, by changing the nature of payoffs in the investment stage, well confidentiality policies may in turn affect firms’ incentives to acquire concentrated drilling right positions in the first place. Thus, the net effect of laws which affect the information firms have about their competitors’ investments is theoretically ambiguous.
This paper empirically measures the net effect of well confidentiality laws on the efficiency of the oil and gas drilling rights and exploration markets by exploiting a natural experiment that occurred in Appalachian shale basins during the recent fracking boom. Midway through the formative period of these newly economical formations, Pennsylvania repealed its 5 year secrecy period, while shorter secrecy laws in neighboring West Virginia and Ohio remained constant. Using administrative data on drilling rights, well permitting, and production outcomes, we measure the effect of secrecy on investment, exploratory effort, and production. Based on these estimates, we compute the costs, benefits and distributional consequences (land owners vs. oil and gas companies) of well confidentiality laws.
Industry Dynamics with Social Learning: Evidence from Hydraulic Fracturing
AbstractI model the interaction between dynamic decision making and social learning about new technologies in driving industry takeoff and productivity growth. Learning about the use of new technologies is an important factor in economic growth, but I demonstrate that anticipated social learning can lead to a free-riding dynamic in scenarios with high uncertainty. I consider the empirical setting of hydraulic fracturing in North Dakota, where firms learn about the optimal use of fracturing technology, in part due to detailed data published by regulators. The cumulative value of this learning process is a ceteris paribus 40% increase in expected profitability. I model the impact of learning externalities on agents’ decisions to drill shale oil wells, an optimal stopping problem. My estimates suggest that the social learning externality is too small to affect investment as the industry develops and uncertainty is reduced. Conversely, I demonstrate that under higher uncertainty, anticipated social learning can lead to significantly lower industry investment and learning rates. Under this scenario, I also demonstrate the potential for public tests of the technology to enhance welfare by leading to more investment and a higher learning rate.
Information Externalities, Free Riding, and Optimal Exploration in the UK Oil Industry
AbstractInformation spillovers between firms can reduce the incentive to invest in R&D if property rights do not prevent firms from free riding on competitors' innovations. Conversely, strong property rights over innovations can impede cumulative research and lead to inefficient duplication of effort. These effects are particularly acute in natural resource exploration, where discoveries are spatially correlated and property rights over neighboring regions are allocated to competing firms. I use data from offshore oil exploration in the UK to quantify the effects of information externalities on the speed and efficiency of exploration by estimating a dynamic structural model of the firm's exploration problem. Firms drill exploration wells to learn about the spatial distribution of oil and face a trade-off between drilling now and delaying exploration to learn from other firms' wells. I show that removing the incentive to free ride brings exploration forward by about 1 year and increases industry surplus by 31%. Allowing perfect information flow between firms raises industry surplus by a further 38%. Counterfactual policy simulations highlight the tradeoff between discouraging free riding and encouraging cumulative research - stronger property rights over exploration well data increase the rate of exploration, while weaker property rights increase the efficiency and speed of learning but reduce the rate of exploration. Spatial clustering of each firm's drilling licenses both reduces the incentive to free ride and increases the speed of learning.
Learning Where to Drill: Drilling Decisions and Geological Quality in the Haynesville Shale
AbstractWe often attribute the increasing productivity of U.S. shale oil and gas wells to firms learning how to drill better. Firms may instead be changing where they drill based on the information they learn about geology and the mineral lease contracts that determine their incentives to drill. To identify how learning and contracts affect average well productivity over time, I estimate an internally consistent dynamic discrete choice model of royalty-rates, drilling decisions, and production outcomes in Louisiana's Haynesville shale. I find that the correlation of firms' priors with actual geological quality is 74%. Learning has implied mild increases in output per well over time of around 0.1%. Distortionary contracts are a much more important driver of increases in aggregate output per well. Once we control for these economic factors, residual trends in output per well that we might normally attribute to technological progress disappear.
- Q4 - Energy
- O3 - Innovation; Research and Development; Technological Change; Intellectual Property Rights