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APPENDIX G

SOCIOECONOMICS

G.1 REGIONAL ECONOMIC MODELING

The IMPLAN (Impact analysis for Planning) regional economic modeling system was used to construct a baseline economic model for the region-of-interest, and to measure the possible impacts of EIS alternatives on regional employment, labor income, and output of goods and services (MIG, Inc. 1993). The stock regional IMPLAN model uses Standard Industrial Classification (SIC) information provided by the Bureau of Economic Analysis (BEA) on employment, income, and production activities within the region-of-interest, which in this case is Los Alamos, Santa Fe, and Rio Arriba counties of north-central New Mexico.

IMPLAN employs a static, non-survey, input-output model which uses a 528-sector adaptation of the 538-sector BEA national input-output transactions table otherwise known as the "national table." This table was derived by BEA based on information from its national income and product accounts (NIPA accounts) covering the production and sales of all commodities. The most recent national table was released by BEA in 1994 and represents the industrial technologies in place in 1987. These values have been price-updated to 1994 constant dollars. IMPLAN provides the flexibility to update the 1987-level technology of any industry, as represented in the national table, to an improved representation of the technology currently being employed. IMPLAN also performs adjustments to the national table to permit regional tables to be constructed for application to any region of the country.

Among the more important considerations in applying the stock IMPLAN model are that: 1) the model is static in the sense of reflecting economic conditions and production technologies in place at a given point in time, with no allowance for technological changes; 2) the model uses exogenous estimates of "regional repurchasing coefficients," (RPCs) critical parameters reflecting the locally produced portion of goods or services used by industry in the region-of-interest; 3) the model characterizes all industrial production processes as requiring fixed proportional use of factors of production, making no allowances for input substitutions due to relative-price changes.

This stock IMPLAN model was modified to reflect 1993 levels of economic activity specific to the tri-county area based on two additional data files: 1) ES-202 employment data obtained from New Mexico Department of Labor, which covers 1993 annualized employment levels at the two-digit SIC level; and 2) published information on regional consumption expenditures made by LANL during FY 1992, as described in a DOE-funded study (Lansford et al. 1993). The modified IMPLAN model of the region-of-interest reflects these additional county-level data files and, correspondingly, the recent experience underlying employment and expenditures within the tri-county region.

The stock IMPLAN model was also adjusted to better approximate the local economic impacts of incremental construction and operations expenditures under each EIS alternative. These adjustments bear on the accuracy of IMPLAN's RPCs for heavy construction (SIC 16) and facility operations (SIC 28). Based on DARHT's local construction expenditures during FY 1993, IMPLAN's RPC for heavy construction was adjusted downward to 0.15 to reflect the fact that most of the value of Heavy Construction services is being procured from outside the region of influence, and in fact, from outside thestate. This parameter adjustment provides a more realistic estimate of the RPC for heavy construction in the region-of-interest. On the contrary, IMPLAN's RPC for industrial facility operations was adjusted upward to 0.80. This upward adjustment reflects the understanding that most of PHERMEX's local expenditures are on specialized equipment made onsite at other LANL defense production facilities.

Given the above adjustments, the modified IMPLAN model was run with alternative expenditure scenarios in order to estimate the consequential impacts of the various EIS alternatives on regional employment, labor income, and output of goods and services. These alternative data sets reflect the following expenditures information provided by LANL: 1) annual capital and operating expenditures for the DARHT and PHERMEX facilities under each EIS alternative (tables G-1Table G-1.-Capital-funded Construction Costs by Alternative (in millions of 1995 dollars)

Table G-2.-Operations and Maintenance Costs by Alternative (in millions of 1995 dollars)

and G-2) and 2) estimated duration of construction and timing of operations for the DARHT and PHERMEX facilities under each EIS alternative. Upon applying a DOE price escalation index for general construction and defense programs to these alternative expenditure projections, IMPLAN was run to estimate the consequential impacts of each DARHT alternative on employment, labor income, and output of goods and services in the region-of-interest for each year in the 1995 to 2002 period. These impacts are reported by year for that period (see table G-3Table G-3.-Summary of Economic Impacts by Alternative (FY 1996 to FY 2002)

).

Sums and products of numbers in this appendix may not appear consistent due to rounding.

G.2 ENVIRONMENTAL JUSTICE ANALYSIS

The geographic region underlying the analysis of environmental justice encompasses various Census tracts spanning four county boundaries, i.e., Los Alamos, Santa Fe, Rio Arriba, and Sandoval counties. Census tract boundaries within these counties are derived from a coverage of census block group boundaries provided by Geographic Data Technology, Lebanon, New Hampshire. This coverage was derived from the TIGER/Line Files of 1990 census geography provided by the U.S. Bureau of Census. In addition, the geographic region underlying the analysis of environmental justice encompasses the Native American reservations of the Cochiti, Santa Clara, Jemez, and San Ildefonso DOE/LANL accord tribes. The geographic boundaries of these reservations were derived from digital data provided by the Bureau of Indian Affairs.

Note that the scope of coverage used in the analysis excludes boundaries or locations of several categories of lands that are generally associated with tribal lands: 1) ceded lands (lands ceded to the U.S. Government to which some tribes retain treaty-protected rights); 2) possessory and usage areas that were established, in some cases, in the course of U.S. Land Claims Commission hearings; and 3) in-holdings within the tribal reservation boundaries. Such in-holdings are lands not held in trust for tribes. These may include fee lands owned by non-Indians, or public domain lands withdrawn from their former trust status (e.g., for National Park Service management or interstate highway rights-of-way).

Given the geographic coverage described above, the following demographic data were used to measure minority and low-income populations: total persons (100 percent count), total households, persons by race, persons by Race and Hispanic Origin, and household counts by income class. The data were extracted from Summary Tape File 3A of the 1990 decennial census, provided by the U.S. Bureau of Census for census block groups. Each block group is identified by its unique block group identifier and the FederalInformation Procedures System (FIPS) identifier for American Indian and Alaska Native Area (AIANAFP). The block group data were then aggregated by tracts generally, and by tracts for the Cochiti, Jemez, San Ildefonso, and Santa Clara Reservation populations only.

Minority population distributions were derived using census tract data on race and Hispanic origin. The size of the minority population within a specific scope of coverage [10, 30, or 50 mi (16, 48, or 80 km)] was measured as the difference between the general population and the white Non-Hispanic subgroup of the general population. The ratio between the derived minority subgroup and the general population constitutes the percentage of "minority population" residing within the various scopes of coverage. This percentage is greater than one half in both the 30- (48-) and 50-mi (80-km) radius, reflecting the large number of Hispanic and Native American persons residing in the region-of-interest.

Similarly, the low-income population distribution was derived using census tract data on household income. Household income data reflects wages and salaries earned by persons of 15 years of age and beyond who reside in the same household. For the region-of-interest the income class of $15,000 or lesswas chosen as the poverty threshold measure for the low-income population. This income level is the reported 1990 poverty threshold for the average-sized household in the region-of-interest. The ratio between these households and the total number of households in a specific scope of coverage [10, 30 or 50 mi (16, 48, or 80 km)] constitutes the percentage of the "low-income" households in the region-of-interest.

Finally, the presentation of both the minority and low-income distributions of the population can take a variety of forms. In the present analysis, maps and tables were constructed taking into consideration that census tracts (or block) areas tend to sprawl across the varying scopes of coverage, e.g. certain census tracts tend to lie on both sides of the 10-, 30-, and 50-mi radius (16-, 48-, and 80-km). In these instances, a detailed atlas was used to apportion persons and households situated in these census tracts to one or the other side of the boundary.

G.3 REFERENCES CITED IN APPENDIX G

Burns, M.J., 1995a, Response to Initial DARHT EIS Data Request, LANL Memorandum No. DX-DO:DARHT-95-16, January 30, Los Alamos National Laboratory, Los Alamos, New Mexico.

Burns, M.J., 1995b, Revised Cost Estimates and Suggested Text Revisions for the Final DARHT EIS, LANL Memorandum No. DX-DO: DARHT-95-100, August 16, Los Alamos National Laboratory, Los Alamos, New Mexico.

Lansford, R.R., et al., 1993, The Economic Impact of Los Alamos National Laboratory on North Central New Mexico and the State of New Mexico, Fiscal Year 1992, August, U.S. Department of Energy, Albuquerque Operations Office, Los Alamos, New Mexico.

MIG, Inc., 1993, Micro IMPLAN Users Guide, Version 91-F, January, Minnesota IMPLAN Group, St. Paul, Minnesota.

Pearman Jr., D.W., 1994, Economic Escalation Indices for Department of Energy (DOE) Construction, Environmental Restoration and Waste Management Projects, February 27, U.S. Department of Energy internal memorandum to distribution, February 27, U.S. Department of Energy, Washington, D.C.

containment G-3

decommissioning G-3

decontamination G-3

employment G-1, G-2, G-3

environmental justice G-2

Hispanic G-2, G-4

low-income G-2, G-4, G-5

plutonium G-3

primary G-3

waste management G-5