May 20, 2025

Executive Summary

Impacts Assessment For The National Ignition Facility (NIF), a December, 1996 report by Bay Area Economics/M. Cubed is a fatally flawed document that relies, in an uncritical manner, on similarly flawed socioeconomic analyses contained in Argonne National Laboratory’s report Technical Documentation in Support of the Draft-Specific Analysis For Construction and Operation of the National Ignition Facility. The flaws in the Argonne National Laboratory report are related both to economic impact calculations that inflate regional employment and earnings and to arbitrary and nonsensical economic impact regions that appear to be designed to exaggerate NIF’s regional economic impact on California and to depress the same impacts in New Mexico, two of the proposed sites considered for the NIF.

The methodologies leading to this faulty analysis are relatively transparent in the Argonne report, and the report is careful to note that there is a significant difference between its ‘economic study regions’ and the ‘region of influence’ (ROI) used in conventional economic analysis to determine regional employment and income effects. Unfortunately, the Argonne report uses both measures very selectively-- ‘economic study regions’ are used to inflate employment and income effects of the NIF while ROI measures are used to minimize growth and immigration problems associated with the project.

The Bay Area Economics/M. Cubed study not only fails to acknowledge the many problems with the Argonne report, it actively misrepresents the inflated Argonne National Laboratory employment and earnings results as being the economic impact of NIF on the San Francisco Bay Area. In one sense, it is to be expected that the Bay Area Economic Report, which was paid for by Lawrence Livermore National Laboratory (LLNL), would overstate the economic impacts of building and operating the NIF. At the time the report was released, local media noted that individuals close to the project felt LLNL had influenced the outcome. However, the methodology employed by Argonne National Laboratory in the socioeconomic portion of its report also calls into question the validity of the Final Programmatic Environmental Impact Statement for Stockpile Stewardship and Management that was also based, in part, on the Argonne analysis. This is especially troubling given that the EIS is supposed to provide information, in an unbiased manner, for decisions about publicly funded projects. In the case of the NIF, the EIS process may have been compromised, essentially "fixing" the outcome without benefit of a truly neutral analysis. Because of the key role played by the socioeconomic section of Argonne National Laboratory report in this lineage of problems, it will be critiqued first in this paper. Following this critique, the claims in the Bay Area Economics report will be investigated.

Employment Impacts of the NIF on the Bay Area

Annual Construction Employment

Both NIF Construction Scenarios

Because neither the Argonne National Laboratory report nor the Bay area Economics/M. Cubed report measures the potential economic impact of the NIF on the actual San Francisco Bay Area ROI, the figures in Table 1, which are based on the RIMS II model and two different construction scenarios are provided for reference. These figures are based on the 1994 Conceptual Design Report and they consider two scenarios: (1) The LLNL Estimate assumes that the construction phase of the NIF peaks in FY1999. (2) The Alternative Forecast is based on the assumption that the peak will occur one year later--a scenario deemed more likely by several of the NIF planners in 1994 but, for budgeting considerations, one that was not pursued. Depending on which scenario one chooses to follow, direct employment in the San Francisco Bay Area will vary between 22 and 600 over the life of the project and the total employment in the region will range from about 64 to 1775. The reader will note that while the direct employment figures in these estimates vary somewhat from those contained in the Argonne and Bay Area Economics reports, the total employment figures vary significantly.

The authors of the Argonne National Laboratory report committed three major errors in their analysis--each of which inflated the regional and national employment and earnings impacts of the NIF. First, they used total NIF budget amounts without removing those moneys that will be spent outside the US. Second, they invented new, larger economic impact ‘regions’ that have no discernible relationships to the actual Region of Impact. And third, they used erroneous figures for the direct employment associated with the NIF and they further inflated economic impacts through uses of questionable ‘induced employment’ methodologies.

1. Budget Amounts

The Argonne report states that "it was assumed that all final demand changes resulting from NIF procurement would occur within the US economy (i.e., no leakage to foreign markets for importing goods or services)." However, the Argonne report was calculated based on the data contained in the NIF Conceptual Design Report (CDR) and the CDR states clearly that one-fourth of the NIF project costs are scheduled to go to foreign industry. This means that the Argonne report initially overstates the economic spending from NIF in the United States and its regions by 25%. Since the total employment and earnings impacts of the project are based on these economic spending totals, job creation and income effects are also inflated by 25%.

2. Impact Areas

The Argonne National Laboratory report created a new regional entity called an ‘economic study area’. According to the report,

The fact that an ‘economic study area’ is coincident with areas defined by the BEA means nothing. The BEA generally recognizes either counties or metropolitan statistical areas (that may be composed of several counties) in every state in the union. This ‘definition’ has no significance in determining how the Bay Area is affected by spending for the NIF--the ostensible focus of the Argonne report. The Argonne report further defines a Region of Influence (ROI) in the following manner:

This definition is also flawed. The issue in regional economics is whether a a region’s economy is significantly affected by some kind of spending, it is not whether a certain proportion of spending is put into a region. For example, spending for NIF has a minimal effect on the San Francisco Bay Area where the NIF would increase the baseline economic growth rate by only .002 percentage points. On the other hand, a very small proportion of the spending on NIF would have a major effect on Sandoval County in New Mexico because the county is poor and lacks other employment. Again, this is an important distinction since both Los Alamos National Laboratory and Sandia National Laboratory in New Mexico were proposed sites for the NIF. Thus, the relative effects of the project on Sandoval County are not simply theoretical.

Source: Technical Documentation, Argonne National Laboratory, p.3-2.

Figure 1

Argonne National Lab’s Designation of Region of Impact

and Economic Study Region for California

Argonne’s apparent attempt to use these two types of economic regions to define a local area that maximized the economic impact in California leads to a convoluted and nonsensical approach for both California and New Mexico. As the map in Figure 1 demonstrates, the Region of Impact for the San Francisco Bay Area is, not surprisingly, located around the San Francisco Bay Area. Using this region of impact leads one to forecast total regional employment levels in the ranges in Table 1 of this paper.

However, Argonne defined a new ‘economic study area’ (the hash-marked area in Figure 1) that covers half the coastal area of the state of California and it based its employment calculations on this area. In any regional employment calculations, the larger the region, the more people who are likely to be employed by the economic effects of any given project. However, the region chosen should have some discernible relationship to the site where the project is being constructed. Argonne has clearly not achieved such a relationship with its California ‘economic study area’ nor was it similarly generous in the allocation of ‘economic study areas’ in other states considered as sites for the NIF. For example, take the case of federal employment in New Mexico.

Figure 2

Federal Civil and Military Government

Net Flow of Workers Between Counties--1990

Figure 2 shows the relationship between Los Alamos National Laboratory (LANL) and the counties that surround it. Federal jobs at LANL and also those within the counties themselves (shown as circled arrows) are very important to poorer counties like Sandoval County, which borders LANL on the north, the south and the west. Yet, when Argonne established its regions of influence for LANL and for Sandia, the two proposed NIF sites in New Mexico, it did not use the generous methods it employed in California. As Figure 3 shows, Sandoval County was included not in the ROI with LANL, which it essentially surrounds, but instead, in the Sandia ROI. Further, the most obvious and most significant economic axis in the state, the Santa Fe-Albuquerque link (among a myriad of things, Santa Fe bases its economy on tourism and Albuquerque has the airport) was broken by Argonne’s attempt to gerrymander two rather unlikely ROI’s accompanied by two even more unlikely ‘economic study areas’. The end result of this unnatural assignment was that NIF employment effects in both ROI’s were shown to be significantly less than those in California. Unfortunately, none of the effects reported in the Argonne report remotely resemble the actual regional impacts that would be experienced if the NIF was built in either location.

The importance of this maneuvering by Argonne can best be understood by referring to Table 3.5 in the Argonne report. Direct and indirect employment totals for all regions under consideration for the NIF site are essentially identical if the region’s employment is added to the US residual employment (employment occurring outside the region). Differences in amounts of regional employment are directly related to how each region is defined and the figures cited for the ‘Bay Area" are, in reality, the figures for the California ‘economic study region’--an area that comprises half the California coastline. Further, the figures for the Sandia and LANL options both omit important areas that would have increased local employment and earnings impacts. Thus, the EIS that was based on Argonne's study did not have full, accurate, unbiased information with respect to economic impacts.

3. Employment Calculations

The Argonne report calculated direct employment impacts

Including workers in a regional economic impact model who do not live in the ROI is a fundamental error that leads to inflated direct and total employment impacts. Even if workers from other labs were assigned on a temporary basis to the NIF construction site, they would still spend their pay at their home sites where their families were located and hence, would still contribute little or no direct on-site impacts.

Argonne’s analysis also included induced impacts. These are employment changes caused by the greater general spending created by the direct and indirect impacts. Induced impacts are far more problematic than the direct and indirect impacts that result from the use of the generally accepted RIMS II model, and one usually sees induced effects estimated only in areas where large federal projects are being sold. In the Argonne report, the induced effects contributed significantly to the highly inflated estimates of total employment contained in the report--it is interesting to note that total employment estimates using the Argonne induced impact methodology are roughly twice the level that the RIMS II model would call for. As a further problem, the induced estimates were not reported separately by Argonne, and were included instead as part of indirect employment effects. This leads the reader to erroneously conclude that the Argonne estimates resulted from accepted regional economic practice and from the use of an accepted regional model (RIMS II).

In sum, the overall effect of the various errors committed by Argonne in calculating employment effects from the NIF has consistently been to inflate the potential economic and employment effects of the proposed project. Even the Bay Area Economics/M. Cubed report was nervous about Argonne’s handling of its employment calculations, stating that "It should be noted that Argonne’s definition of direct and indirect effects is different than that used for other I/O models."

Given the multiple layers of critical problems associated with the Argonne report, it is sufficient to note that the Bay Area Economics/M. Cubed report uses the Argonne results and suffers from the same errors and the same inflated forecasts. However, it is significant that Bay Area Economics/M. Cubed not only embraced the Argonne report, they created a further layer of misunderstanding by continually referring to employment calculations based on the Argonne ‘economic study area’ as the employment effects in the San Francisco Bay Area. The following quotes from the Bay Area Economics/M. Cubed report are representative:

Perhaps the most interesting attribute of the Bay Area Economics/M. Cubed report is its heavily caveated results--particularly in the discussion of benefits from spin-offs. This is most likely due to an attempt by the report’s reviewers from the University of California, Berkeley, to ‘detune’ a report whose flaws must have been abundantly obvious to at least the reviewers who were economists. The following sections discuss the Bay Area Economics/M. Cubed report’s statements concerning the value of technological innovations, the need for industry involvement and commercialization of results, the allocation of NIF funds to various spending categories, and the need for and alternatives to the NIF.

1. The ‘value’ of technological innovations

Throughout the Bay Area Economics/M. Cubed report, caveat after caveat states clearly that no calculations of the spin-off effects of the NIF can be made. Some examples:

Given what the authors of the Bay Area Economics/M. Cubed study had to work with in terms of successful spin-off projects from the NIF’s predecessor, the Nova Laser, an ICF program, the need for these caveats is clear. For example, consider the following statement from their report:

The two, cited projects were chosen from eight technologies that evolved from LLNL’s existing laser program and they are based on past research--the ICF has been funded since 1970. According to the Bay area Economics/M. Cubed report, "these particular technologies were examined because of their potential for commercial success, and are used to illustrate the potential for any one technology to result in significant economic benefits." In other words, the authors chose only to investigate ‘successful’ projects and not all attempts to commercialize ICF technology. The uses of only favorable outcomes to predict the likely effect of the NIF obviously biases the outcome of the Bay Area Economics/M. Cubed report.

However, only two of the eight technologies "offer[ed] a clear set of commercial opportunities." One can assume, given the eagerness of the report’s authors to demonstrate that valuable spin-offs will result from the NIF, that if more promising projects had been available the authors would have used them. Thus, it appears that after 26 years of funding, the Bay Area Economics/M. Cubed report could only find two products with ‘potential’ and that even those projects have neither been integrated into commercial industry nor do they have a discernible relationship to the NIF. The strained attempt to associate these two projects with ten percent of the gross domestic product is simply disingenuous and the fallacy of this argument is so apparent that it requires no further comment in this paper.

The real problem in trying to use spin-offs as justification for the NIF is alluded to by the Bay Area Economics/M. Cubed report when it notes that "Technological innovations emerging from the NIF are likely to be unique compared to innovations developed by other public or private research institutions in the US." This is exactly the point. The valuable innovations adopted by US industry generally arise from investments made by US industries. The fact that the NIF innovations may be unique (as is research into biological weapons or poison gas) does not indicate that these innovations would either be valuable or adaptable to commercial industry. In fact, the idea that they are unique suggests that no one else has found it worth while to invest in or work on them.

A large part of the Bay Area Economics/M. Cubed report is devoted to the need for private industry involvement and commercialization of laboratory projects. While this has little to do with the NIF, it is an important goal for the general operation of the national labs. As the report notes:

These statements rely heavily on the use of CRADAs to achieve the desired integration of laboratory research and commercial enterprises. Unfortunately, as of 1996 the CRADA program is essentially dead at the DOE labs, and if the Bay Area Economics/M. Cubed means, as it implies, that projects such as the NIF are feasible only if their benefits to industry are commercialized, the general malaise in the DOE labs in this area calls into question any rationale for the NIF that is based on either spin-offs or the commercialization of technologies.

3. Allocation of NIF funds to various spending categories

According to the Bay Area Economics/M. Cubed report, "approximately 75 percent of NIF’s $1.1 billion budget will pass directly to industry, injecting funds into the economy in a range of technical categories." The 75% figure comes from page 3-7 of the Argonne study which claims that 25% of the construction budget goes to households (i.e., wages). This 75% figure is questionable for several reasons. First, only 36% of NIF’s spending is for laboratory and optical instruments and the rest is for things that are not obviously technical in nature--architects, surveyors, fabricated plate work, construction, etc. And second, one page later, the Bay Area Economics/M. Cubed report contradicts its own 75% figure, claiming that

It is important to note that both these figures are based on total US spending, not regional spending. When one considers the actual spending in either the Bay Area ROI or in the expanded ‘economic study area’ used in the both the Argonne and the Bay Area Economics/M. Cubed reports, the amounts of regional spending are significantly reduced below the lower US spending figure. For example, the Bay Area Economics/M. Cubed report claims that

Table 2

The Declining Percentage of Local Purchases

During Construction of the NIF

This shift in spending away from the region of impact is clearly shown by the data in the Bay Area Economics/M. Cubed report. As Table 2 shows, starting in FY1998, and using the ‘economic study area’ that contains half the California coast, the percentage of work performed in the area still declines throughout the period of the project. It appears that after rough construction of the NIF is completed, less and less local content is used during the phase in which technological equipment is purchased and installed. This directly contradicts the claims of the report that technological purchases are directed toward the California region in which the NIF is located.

4. The need for and alternatives to the NIF

The Bay Area Economics/M. Cubed report is full of statements about the need for the NIF. While it is obvious that the authors of this report are not qualified to make such an assessment, it is curious that as economists they chose not investigate any alternatives to this expensive program even though acceptable alternatives appear to exist within DOE. For example, an existing facility at Sandia National Laboratory appears to already be capable of studying much of what NIF is designed to do, and at a much lower cost.

The Particle Beam Fusion Accelerator Z-pinch configuration (PBFA-Z) at Sandia National Laboratory produced 1.8 megajoules of energy during a November, 1996 test. This is the same energy level NIF is designed to produce. According to an article in Sandia's newsletter, "The powerful 'shots' provide data for computer simulations used to predict the physics within, and effects of, a nuclear blast. Scientists hope to substitute this laboratory data for some of that obtained from underground nuclear explosions, which have been halted." This is the same mission NIF is designed to fill.

Although the PBFA-Z facility uses different technology, it is funded through the same DOE functional division--the Defense Programs Inertial Confinement Fusion (ICF) program budget. According to an official at Sandia, information gleaned from experiments conducted on the current PBFA-Z machine overlap from 50 to 75% with those planned for NIF. With an investment on the order of a few hundred million dollars, a large pulse-power machine could conduct up to 90% of the work NIF is designed to do.

However, there are some important economic differences between the machines. NIF is officially projected to cost about $1.2 billion to build and $115 million to operate each year. PBFA-Z cost about $40 million to build in 1985, and it operates for around $20 to $30 million annually. Further, the PBFA-Z machine uses far less energy to operate than the NIF because it stores electrical energy over time and then releases it all at once, only using about a dollar's worth of electricity each time. To produce the same 1.8 megajoules of energy, NIF must start out with several hundred megajoules since it is only about .01% to .5% efficient. Thus, PBFA-Z is both cheaper and more efficient than NIF. In fact, scientists at Sandia claim that a pulse-power machine with more capacity could achieve thermonuclear ignition--the chief justification for NIF--at about one tenth the price of NIF construction.

As an official from DOE's Sandia National Lab recently wrote: "Our fundamental concern is that the National Ignition Facility will drain resources from many other programs because the annual operating budget for NIF will exceed $150 million and in an era of limited resources this will have to come out of existing programs. This is not even addressing the source of the true construction costs which are projected to exceed $2 billion." If the Sandia figures are correct, the total costs of NIF may exceed $6.5 billion over the 30 year life cycle of the project--about $2 billion more than the official estimates. Decontamination and Decommissioning costs are not included in any of these estimates.

Conclusion

The fact that the two studies analyzed here contain serious flaws that lead to inaccurate conclusions is enough to invalidate their respective findings. At a minimum, new analysis should be carried out using accepted economic models and defensible regional defintions. But beyond the flaws in the studies themselves, the public policy implications are more troublesome. The EIS produced by the DOE for NIF and its associated facilities relied on flawed and biased studies. This undermines the validity of the entire decision-making process for the NIF. Furthermore, the fact that the EIS's key economic document was produced by Argonne National Lab--an entity of DOE--further strains the credibility of this process.

The errors contained in the Argonne/M. Cubed Bay Area Studies served not only to shed an unwarranted positive economic light on the NIF project and forced the siting decision toward Lawrence Livermore National Laboratory. This not only subverted the decision process, it betrayed the spirit and letter of the law that mandates environmental impact studies.

Finally, it may be the case that from a purely economic perspective, an existing facility--the PBFA-Z at Sandia--could carry out much of the mission claimed for NIF at far lower costs. Are the excessive additional costs for the marginal gain in capability at NIF really worth the expenditure of national resources? This question has not been answered, nor has a sound economic analysis been produced for the NIF itself. Neither good economics and nor sound public process has been served by using such fatally flawed studies.