The analysis in this section is based on the IMPLAN model as described at the beginning of the Socioeconomic Resources section. IMPLAN focuses on employment and labor earnings and does not explicitly address non-labor income such as transfer payments (e.g., Social Security), investment earnings, or rent. As a result, the focus of this analysis is limited to the segment of the economy that is based on work-related income. The effects of non-labor income should be considered when interpreting the results of the IMPLAN model as substantial portions of income in some locations in the Planning Area come from non-labor income (e.g., Park County where nearly 40 percent of personal income is from non-labor income).
Assumptions used in this analysis include the following:
Employment, earnings, and output are indicators of economic and population change.
BLM-influenced activities alter economic conditions. Economic benefits to the Planning Area accrue from BLM-influenced activities, such as oil and natural gas development, livestock grazing, and recreation. Economic benefits to the Planning Area also accrue from wildlife grazing, to the extent that wildlife grazing contributes to the availability of and demand for recreational activities. Conversely, the possibility of economic losses to the Planning Area due to BLM-influenced activities is recognized and evaluated.
Indirect and induced benefits due to minerals, livestock grazing, and recreation can reasonably be estimated by the IMPLAN model. (The IMPLAN production coefficients were modified to reflect the interaction of producing sectors in the Planning Area.)
Recreation-related expenditures by residents occur in the region, but do not represent new money coming into the Planning Area; therefore, the analysis of economic impacts from recreation considers only recreation expenditures of nonresidents in the four-county Planning Area. In other words, there is a multiplier effect associated with nonresident recreation-related spending because it results in an input of new money into the Planning Area. By comparison, it is assumed that recreation-related expenditures of people who live within the Planning Area would generally be spent within the area (although not necessarily on the same activities), given the set of possible management actions represented by the range of alternatives analyzed.
The analysis of direct and indirect impacts associated with oil and gas activity considers only activities on BLM-administered surface and federal mineral estate. The cumulative analysis considers activities on state and fee land and mineral estate.
For livestock grazing, the analysis reflects a “worst-case” assumption that all acres impacted by surface-disturbing actions (from all the sources listed in Appendix T) are lands currently permitted for grazing; thus, the number of acres available for grazing in 2027 is the number of acres available under each alternative, minus acres that are affected in the long term by surface-disturbing actions (and withdrawals). In addition, the analysis of grazing reflects the assumption that surface-disturbing actions occur at a constant rate over time.
For livestock grazing, the analysis of baseline AUMs available and reductions in AUMs is adjusted for the ratio of authorized use to active use, which is calculated based on the long-term average of authorized and active AUMs for the Planning Area from 1988 to 2009. This long-term average is 64.21 percent. Appendix X contains additional details regarding this adjustment.
The pace and timing of economic development in the Planning Area depends on many factors beyond BLM management. These include national and international energy demand, supply, and prices; operator business strategies; production conditions within the Planning Area; and demand and supply for agricultural products. Because the future pace of development in the Planning Area is unknown, this analysis assumes a relatively constant rate of development. Therefore, actual impacts may differ if the rate of development changes substantially (e.g., there may be boom and bust type short-term impacts that would differ from long-term impacts).
The IMPLAN production coefficients were modified to reflect the interaction of producing sectors in the Planning Area. As a result, the calibrated model does a better job of generating multipliers and the subsequent impacts that reflect the interaction between and among the sectors in the Planning Area, compared to a model using unadjusted national coefficients. Specifically, worker productivity in oil and gas production is higher in Wyoming and more of the hay used for livestock feed is produced within the region, compared with national averages. Key variables used in the IMPLAN model were filled in using data specific to Wyoming, including employment estimates, labor earnings, and total industry output.
Appendix X describes the economic analysis method in more detail, along with detailed assumptions and factors for the analysis.