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| Content Provider | Springer Nature Link |
|---|---|
| Author | Balthrop, Andrew |
| Copyright Year | 2016 |
| Abstract | Power-law distributions can be generated by a variety of theoretical processes and have been found in many areas of economics and finance. This paper demonstrates that the distribution of cumulative oil and gas recovery in Texas is best described by a power-law distribution, with exponent approximately equal to 1.1 for oil production and 1.6 for gas production. Estimation is carried out using lease and well-level data from a cross section of over 600,000 observations gathered by DrillingInfo. The goodness of fit of the hypothesized power law is verified with regression-based and likelihood ratio tests, as well as nested and composite hypotheses. Results are significant because they show that production data are heavy tailed, that empirical variance estimates do not converge, and that 1 % of oil leases are responsible for 70 % of cumulative recovery. The distribution has consequences for efficient management and implications about peak oil because wells close to the mean account for so little of the cumulative distribution of recovery. |
| Starting Page | 1521 |
| Ending Page | 1539 |
| Page Count | 19 |
| File Format | |
| ISSN | 03777332 |
| Journal | Empirical Economics |
| Volume Number | 51 |
| Issue Number | 4 |
| e-ISSN | 14358921 |
| Language | English |
| Publisher | Springer Berlin Heidelberg |
| Publisher Date | 2016-01-02 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Hydrocarbons Oil Natural gas Power law Pareto distribution Scaling distribution Fractal Econometrics Statistics for Business/Economics/Mathematical Finance/Insurance Economic Theory/Quantitative Economics/Mathematical Methods |
| Content Type | Text |
| Resource Type | Article |
| Subject | Statistics and Probability Social Sciences Economics and Econometrics |
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