Import vulnerability of defense-related industries: An empirical model

NORTH-HOLLAND

Import Vulnerability of Defense-Related Industries: An Empirical Modal Mitchell Kellman, City College of New York, Yochanan Shachmurove, University of Pennsylvania,

and

Tarek Saadawi, City College of New York This paper provides an examination of the concept of "foreign dependency," with focus on defense-industry usage. The topic has taken on a new urgency as of late when it has been noted that the very hi-tech weapons, generally given credit in Desert Storm, consist of critical components and subsystems that are not, and perhaps cannot be produced in the United States. The problem is a relevant one across the technological spectrum. Thus, it may be as difficult for the United States to assure an adequate supply of chemically treated boots, as to provide the latest microchip sensors. We develop an empirical methodology that allows for a quantitative determination, resulting in a ranking of import dependence or vulnerability of products. This method takes into account most existing industrial plants, import surges, and the relative weight of defense usage in total national apparent consumption, It yields unique dependence profiles, identifying bottlenecks along the breakdown analysis dimension (i.e., subassemblies, components down to raw materials). The method is demonstrated in several applications across the technological spectrum.

1. INTRODUCTION This paper provides a systematic examination of the concept of "foreign dependency." It examines the problem from a theoretical viewpoint and, in light of the theoretical conceptual framework, develops a methodology that allows for an actual determination and measurement of product-specific "Import Vulnerability Indices" (IVIs). These, in turn allow for comparisons and rankings according to alternative criteria of foreign dependency associated with defense-related systems and subsystems. Address correspondence to Prof. Yochanan Shachmurove, Department of Economics, University of Pennsylvania, 3718 Locust Walk, Philadelphia, PA 19104-6297. Received December 1994; final draft accepted May 1995.

Journal of Policy Modeling 18(1):87-107 (1996) © Society for Policy Modeling, 1996

0161-8938/96/$15.00 SSDI 0161-8938(95)00077-7

88

M. Kellman, Y. Shachmurove, and T. Saadawi

The motivation behind this study is the fear of Department of Defense (DOD) dependence on foreign suppliers for critical systems or inputs for such systems. The issue of foreign dependency of defense-related industries has a venerable history and may be summarized succinctly as follows: "the pattern of declining U.S. competitiveness will undoubtedly impinge upon American defense capabilities".~ There have been those who have explained the very essence of the industrialization process as an attempt to develop or maintain defense-related capabilities. "Industrialization in most major countries has been rooted, historically, in the attempt to acquire a military capability". 2 In the literature, import dependence has been discussed in the contexts of different, often specific commodities and different countries. Herrmann (1989) investigates the dependence on imported wheat in a pooled cross-country analysis for the years 1968-80. Clark (1990), Craig (1984), Kautmann (1991), and Yucel and Dahl (1990) study the issue of import dependency on energy. Mikesell (1987) studies the issue in the context of non-fuel minerals, and Lindsey (1989) studies the non-renewable resources in general. Leela (1980) studies the import dependence on non-ferrous metals in India. Parley (1978) examines the Irish economy's dependence on foreign imports during the 1960s. Chu (1988) studies the Taiwanese dependence, while Zimbalist and Brundenius (1989) study the Cuban economy; Chaudhary (1988), the Pakistan case; Baark (1991), the case of Ghana; and Andrae and Beckman (1987), the Nigerian dependence problem. As is clear from the above citations, the preponderance of work in this area deals with import vulnerability on fuels, raw materials, and other primary commodities. Very little work focuses on manufactured products, notable exceptions are Clark, Kaserman, and Mayo (1990), and Koekkoek (1987). Our paper develops a methodology that may be applied to both commodities and manufactures, including high-tech. It allows for explicit consideration of vulnerabilities at the component and subassembly, as well as lower (e.g., raw materials) levels in the production process. The issue takes on new poignancy today, as it has been widely observed that on the one hand, the United States' military success t Bruce Brunton, "National Security and International Competitiveness," IIEC Proceedings, April 30, 1988, 154-162. 2For example, Guatam Sen, The Military Origins of Industrialization and International Trade Rivalry. New York: St. Martin's Press, 1984.

IMPORT VULNERABILITY

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in Desert Storm was largely a function of our "high-tech" weaponry, and on the other, that these "American" weapons are as international as the Ford World Car. Regarding the Sparrow missile, a Congressional study found that "the guidance system had circuits from Japan, a critical memory chip made in Thailand, and other essential parts bore the West German stamp. ''3 The article cites Robert Costello, currently of the Hudson Institute, formerly DOD procurement chief, who argues that the likely effect of commercial electronic and other high-tech emigration from our shores is a loss of research and engineering potential, which will lead to our possessing "outdated weapons produced at vast expense." Again it should be noted that the problem was considered of growing criticality well before the current situation. Indicative is an article in Science, "American Weapons, Alien Parts," which documented the problem over five years ago, 4 which noted that "certain electronic components used in Army systems are supplied exclusively by foreign sources i n c l u d i n g . . , electronic countermeasure tubes, liquid crystal and electroluminescent video displays, magnetic bubble memories, and certain raw materials." To date, many studies have attempted to pinpoint the exact nature of the threat presented by "import dependence," and to gauge its quantitative dimensions. 5 A seminal work is that of Costello (1988), which suggests that current data deficiencies prevent effective monitoring by DOD of domestic production capacity and technologies in "subtier" and basic industries. A study closely related to our effort here is by Belch et al. (1986). Utilizing information on DOD purchases plus an input-output model of the United States, they define industries potentially critical to DOD (belonging to the Defense Industrial Base) as those industries for which the defense procurement ratio exceeds the overall share of GNP purchased by DOD (directly or indirectly). Another (commissioned) relevant study is Peterson, Schacht, and McClenon (1987). Although the 3"American Smart Bombs, Foreign Brains," Business Week, March 4, 1991, p. 18. 4Eliot Marshal, "American Weapons, Alien Parts," Science, October I0, 1986, pp. 141143. See also T. Moran, "International Economics and National Security," Foreign Affairs Vol. 69(5), Winter 1990-91, pp. 74-90. For a useful study and summary of recent relevant work, see Ratner, J., and Thomas, C. (1990) The Defense Industrial Base and Foreign Supply of Defence Goods, Defense Economics 2:57-68. Another recent study is by Hartley, K., and Martin, S. (1993) Evaluating Collaborative Programs, Defense Economics 4(2): 195-211. For a European study, see Walker, W., and Willett, S. (1993) Restructuring the European Defence Industrial Base, Defence Economics 4(2): 141-160.

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M. Kellman, Y. S h a c h m u r o v e , a n d T. Saadawi

study states that no single criteria should or could be used to determine the adequacy of the defense industrial base, their empirical analysis relies primarily on a single criteria: comparing the performance of defense industries with the manufacturing sector as a whole. In short all of these studies attempt to evaluate the issue of the defense sector's capabilities (where "defense sector" is variously defined) against DOD needs (again variously defined). It is obvious that like any other issue, an extreme emphasis of this issue may lead to abuses (such as the bill that has been proposed by Representative Oakar that would have required all weapon systems, parts, and components to be manufactured domestically). Each of the works cited above suffers from a conceptual weakness that limits its operational applicability. Each studies the problem in terms of either a one-dimensional objective function, or a set of mutually unrelated targets. However, in practice the critical issue facing policymakers often involves assessing trade-offs in the context of multi-dimensional goals. No coherent methodology has to date been formalized in this area that would allow for an explicit weighing of alternative policy goals. This paper develops an integrated model that, utilizing costeffective and relatively available databases, allows for both subjective and objective weighing of alternative criteria trade-offs. Lately, much has been written suggesting full "self-sufficiency" in U.S. defense-production capability as a desirable and perhaps even feasible goal.4 Many such efforts have foundered on the shoals of cost and technical feasibility. 7 It is not our intention to present a full-blown economic analysis of alternative self-sufficiency scenarios. However, it is clear that any such attempt would be facilitated by, if not require, a practical model that would allow for explicit trade-off analysis in a multi-goal environment. At an operational level, it is typically recognized that the pursuance of such a goal requires sophisticated and expensive new databases. Recently, there has surfaced a new suggestion that a very large scale data management system be developed, the so-called integrated weapons database (IWDB). Such a database would have all the information about various weapons, from manufacturing 6For example, the three main recommendations of the BAST study cited in the abovementioned Science article are that we should "stimulate whole new technologies," and "begin far-reaching programs that will rebuild U.S. self-sufficiency in key areas". 7For example, Questek's DINET, or Defense Security Agency's SOCRATES.

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91

plans to maintenance diagrams, in one vast database created by linking the Pentagon's computers with those of thousands of suppliers. If all suppliers and components of the data network utilized the same classification standards, the Pentagon would be in position to plug into the totally automated and electronic business environment. Perhaps one may view such a development as a first-best solution to the DOD acquisition function in the next decade. However, it is not likely that such a universal homogeneity of product standards and codes will be soon or easily (or perhaps ever) attainable. In the United States many critical data systems, especially those needed to track production levels and potential, rely on (constantly revised) various industry-based codes (e.g., SIC or ISIC). Other data systems, especially those needed to track international trade, rely on product- (rather than industry-) based codes and standards. Though there is a movement to the use of trade codes more closely homogenized with one another (e.g., H S, replacing both Sched B and TSUSA), and with European codes (e.g., BTN), these two general databases are conceptually different and do not easily speak to each other (allow for cross-concordance walk-through). Further, codes routinely used within DOD, such as Federal Supply Codes (FSC), are only vaguely concordable with generally used codes such as ISIC. We are not aware even of attempts to concord more detailed classifications, such as NSN, with either product- or industry-based codes used by the Department of Commerce. The problem is compounded when one considers the difficulty in cross-walking from Customs detailed codes to DOD codes (such as FSC and NSN). There are those who believe the problems of creating a single unified product-industry code is not intractable, and just recently a computerized attempt to relate fourdigit FSC codes to four-digit SIC codes has been made. Since any automated DOD acquisition s y s t e m - w h e t h e r of a broad conception, such as IWDB, or a more limited o n e - u t i l i z e d by DLA to help develop systematic acquisition and stockpiling priority criteria would clearly require the capability to match product classifications across several product-classification schemes, it is unlikely to be either cheap or available in the reasonably near future. In this study we propose an alternative (or perhaps complementary) approach to the development of super-comprehensive (and super-expensive) databases for the purpose at hand. Rather we go

92

M. Kellman, Y. S h a c h m u r o v e , a n d T. Saadawi

the "indicator" route, focusing on flexibility, ease of use, operational usefulness, and maximum reliability of existing publicly and inexpensively available databases. 2. T H E D A T A 8 2A. Database Considerations

The criterion for the selection of databases to accompany the proposed methodology is theoretical relevance. In addition the selection takes into account ready availability, cost effectiveness, and ease for user-friendly interaction. Production databases rely on Department of Commerce Census of Manufacturers data. Import and export data rely on OECD statistics. Defense procurement data utilize a DRI proprietary database: FSC-DIFS. Working with these data bases, tests were carried out using the Work Breakdown System 9 to study a number of cases of potential foreign dependence. The results demonstrate the methodology developed in this study to be flexible and practical. While examining the potential usefulness of many alternative databases, we focused primarily on non-classified, and easily available, and hence practical and inexpensive databases. Naturally, the minimal and optimal data requirements are and must be dependent on, and functions of, the theoretical considerations. While the theoretical basis for the practical, empirical Import Vulnerability Index (IVI) is presented below, the minimal data requirements include observations on domestic production, imports (both total and classified by supplier country), exports, DOD demand, and some "surge" m e a s u r e - in our case chosen to be the growth in the share of (respective product) imports of our domestic market. Furthermore, observations for each of these must be available not only for the product, or system as a whole, but also for earlier stages in its Work Breakdown System (WBS), that is, the subsystems, components, and so forth. Our final choice of useful databases, used in the demonstration described below, utilized three different databases, and hence required concordance between three different classification schemes - t h e DOD's Federal Supply Code (FSC), the U.S. Department of Commerce's Standard Industrial Classification (SIC), and the SSee Ahmed, Kellman, and Saadawi (1991) for a schematic summary of the data and databases explored, with a brief description of various conceptual problems encountered. 9For a full description of the Work Breakdown System, see Frisch (1990).

IMPORT VULNERABILITY

93

O.E.C.D.'s Standard International Trade Classification (SITC). These three codes were arrived at as the optimal and minimum number of codes needed to develop the Import Vulnerability Indices, having considered and experimented with many other possibilities (including DOD's NSN's, TSUSA, SCHED B., and HS). Incidentally, the use of the SITC was chosen, in part, because it is widely used by other, including European, countries, and thus should prove useful when tying-in European-vendor (or customer) data into this proposed database.'° 3. METHODOLOGY: DERIVATION OF INDICES

The methodology chosen emphasizes several principles. First, it must enable the construction of Import Dependence Indices with an intuitive explanation, clearly derivable from generally acceptable principles. Second, they should utilize only generally (and inexpensively) available data. Third, a fairly wide degree of flexibility should be allowed the user of the methodology. This last point is important, because the methodology is designed to allow these IVIs to conceptually apply to a broad range of products, both "hi-tech," and "nuts-and-bolts." That is, it allows the user to insert his or her subjective judgment at various points in the calculation, and then allows the user to observe the resultant alternative indices. This demonstrates four different, alternative Import Vulnerability Indices (IVIs). IVI1 is the "Import Ratio" (1R). It is calculated as the imports divided by the difference between domestic production (PRO) (or shipments) and exports (X): IM 11111 = ), • ( P R O - X )

(1)

where gamma is a scaler. 11112is a two-dimensional index that takes into account both the import ratio and the proportion of domestic production purchased by DOD. Both of these factors are positively associated with import vulnerability. It is possible that two products have the same import ratio (IR), but that defense use is only one percent of total domestic production, whereas it constitutes 80 percent of total domestic production for the other. Clearly the first is less vulnerable to import '°For a detailed description of the various databases examined, see Ahmed et ai. (1991).

94

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Figure 1.

•

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Iso-vulnerability contours.

cutoffs. This can be clearly seen using Iso-Vulnerability contours in Figure 1. IVI2 is calculated using the following formula: 11/12 = ~2 * I R '~ * D P R O R

w h e r e tt + 13 = 1

I~

(2)

where DPROR is the Defense procurement ratio, defense procurement divided by domestic production. The user may choose alternative values for alpha and beta. If only IR is to be considered (back to IVI1), then alpha will be assigned a value of unity. If on the other hand, it is believed that in the case of a particular product group, a heavy weighing should be given the proportion of production already utilized by the defense establishment, alpha may be assigned a value of, say 0.1. In the demonstration below, we arbitrarily assign alpha and beta equal weights (0.5 each). IVI3 is a three-dimensional index of vulnerability. It adds to the two variables considered in IVI2 a third consideration: the nature of the s o u r c e - (supplying) country of the U.S. imports of the product. This is done by accessing a subroutine (or module) which g i v e s for each p r o d u c t - the distribution by country of the imports, and multiplies each percentage by a Country Risk index (CRNDX).

IMPORT VULNERABILITY

95

This CRNDXis calculated as a Weighted Country Score (WCS)" and requires expert judgment inputs from sources such as specialized Country Risk specialists from the State Department or elsewhere. The trade data required to construct such an index is readily available. For the demonstration, we utilize a set of illustrative sourcing distribution ratios for each of the components. These ratios remain identical for 1982 and for 1987, and the only thing varied in this case is the index, CRNDX (or the specific Factors used in the calculation of the Weighted Country Scores). This allows us to observe how changes in the (perhaps highly subjectively determined) index may affect the Import Vulnerability Index, and its rankings. IVI3 is calculated as follows: IVI3

= Y3 * I R a * D P R O R

wherea+13+8=

~ * CRNDX

6

1

(3)

Finally, it might be argued that the rapidity by which the import ratio (IR) has grown in a recent period is an important indication of p o t e n t i a l - future import vulnerability. That is, although today the indices calculated above may not indicate a certain product or component is "import vulnerable," the trend may be such that in a short while, the United States (and DOD) may become quite dependent on foreign sourcing. In fact, the explicit introduction of this surge factor introduces a dynamic element into the calculation. This may be considered in some applications of the methodology as a critical input, because it introduces a capability for projection of trends into the near future. This allows one to interpret the Import Vulnerability Indices not solely as snapshots of the (recent) past, but also as indicators of future or potential foreign dependence. To take this factor into account, we calculate the percentage growth of the import ratio (IR) from 1982 to 1987 (for each product and component) as a separate variable, and introduce it (multiplicatively), creating our final index, IVI4: IVI4

= Y4 * 1 R ~ * D P R O R

wherea+f~+6+E=

~ * crndx s * GRIN

1

~

(4)

"For a description and derivation of the Weighted Country Score, see Ahmed et al. (1992).

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M. Kellman, Y. Shachmurove, and T. Saadawi

Again, because the user may determine the values of the exponents (subject to the constraint that they add up to one), a reasonable degree of flexibility is available. Thus, if the user does not believe that recent import-proportion growth is really indicative of any import vulnerability, then he or she may assign a low value, say 0.1, to epsilon. Note that IVI1, IVI2, and IVI3 may be considered as limited, or special-case, versions of IVI4, calculated by assigning zero values to selected exponents in the latter formulation. 4. CASE STUDY: C O M P U T E R S The demonstrations detailed below indicate the type of analysis, and the type o f output that the user may obtain from any product, using the automated set of programs available. The first program, SCREEN-FLOW, is described in A h m e d et al. ( 1991). That application allows the user to determine which, of a large initial group of products, are "import-dependent." Then using the COUNTRY SCORE program (see Ahmed et al. (1991)), the user may calculate weighted country scores for each product of interest (selected perhaps as a result of the previous program's run). Finally, the user may calculate actual Import Vulnerability Indices (IVIs) for the products of interest. As illustrated below, the calculation takes into account not only the product (or system), but also its subsystems and components. The first demonstration of this will be "computers." Using the on-screen interactive program SCREEN-FLOW, the user will have noted whether the system is import-dependent. As is detailed in the following section, SCREEN-FLOW allows for a rapid and economical screening of the system and its Work Breakdown System, applying a nested design of three simple yet critical criteria (e.g., does Defense demand of the product, or of any of its subsystems or components, exceed total or some pre-set fraction of total domestic production, and does the decision change if known convertibility or expandibility potentials are exploited). This procedure will allow the user to focus the analysis, as described in this section, only on those systems that (directly or indirectly) are deemed to be foreigndependent (to some degree). SCREEN-FLOW will also allow the user to scan and identify the key Work Breakdown Analysis subsystems. Once the Import Vulnerability Indices (IVIs) have been calculated for the chosen System, (and its component subsystem down to the required level or tier), the user will clearly be able to note

IMPORT VULNERABILITY

97

the Work Breakdown level at which the key dependency or vulnerability is found. Thus, this will allow the user to identify the bottleneck level. In addition, the user will be able to identify the key underlying nature of the foreign dependency. By either experimenting with the various parameters (as explained below) or alternatively by comparing the Vulnerability Profiles (across Work Breakdown categories), the user will be able to determine whether the dependency reflects primarily a large import share of the domestic market, or a large portion of the domestic market utilized for Defense (or essential civilian) purposes, or a dangerous concentration of imports from unreliable foreign sources, or the presence of a relatively sharp import (share) surge in the particular product (or any of its subsystems and components). As noted, the user (e.g., program manager) will then be in position to rank subassemblies and components of the desired system by degrees of foreign dependence. This may be an important input into management decisions dealing with stockpiling or inventory policy in the face of some, or alternative, scenarios. A different use that may be made of the Import Vulnerability Indices is to compare levels of foreign dependence across systems. This would allow the program manager, or user, to gain important perspective by comparing and ranking the relative degrees of Import Vulnerability not of various subassemblies (as above), but rather of whole systems compared with other whole systems (e.g., electronics, machine tooling, transportation equipment, clothing, rations, or medical). Again, this may be a useful management tool for acquisition or stockpiling functions at a broader (or higher) level of decision making. Both usages of the indices will be illustrated below. Table 1 summarizes the basic statistics utilized for the computation of IVIs for computers. Table 2 presents the basic ratios that underlie the vulnerability indices described below. The only other basic measure that enters as an integral component of the import vulnerability indices is the Country Weighted Score (CWS) (see Table 3). Note that Table 3 assumes that in 1982, of the five countries, the United Kingdom and Germany were considered to be the most reliable potential suppliers, hence their low Country Factors. France (not a formal member of NATO, with a history of independent and apparently idiosyncratic policies) is ranked as considerably less reliable. China and Thailand are considered the least stable and reliable as potential sources of critical products or components.

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M. Kellman, Y. S h a c h m u r o v e , a n d T. Saadawi

T a b l e 1: I m p o r t Vulnerability Indices: C o m p u t e r s , Basic Statistics a Level

Computer 1982 I 1987 I Storage devices 1982 II 1987 Capacitors 1982 III 1987 Diodes, transistors, semi-conductors 1982 1987 Printed circuit boards 1982 1987

Production b

Imports c

Exports a

Defense"

$13,457 $26,624

$ 1,713 $11,671

$ 966 $2,270

$ 81 $ 89

$ 3,490 $ 6,905

$ 444 $ 1,656

$ 251 $2,347

$121 $220

$ 1,207 $ 1,307

$ $

296 461

$ 261 $ 339

$ 42 $ 42

$11,215 $17,929

$ $

477 724

$ 216 $ 353

$ 10 $ 17

$ 2,289 $ 4,814

$ $

225 532

$ 132 $ 550

$ 31 $ 44

aAll units in thousands of SU.S. The source for the production data is the U.S. Department of Commerce, Industry Census 198Z The import and export data, are from the O.E.C.D. Series C, Trade by Commodities. The Defense procurement figures are from DRI/McGraw Hill, FSC Series. bThe production data are shipments from the Survey of Industry of the U.S. Department of Commerce. The products are classified in terms of Standard Industrial Classification (SIC). ¢The import data are classified according to the Standard International Trade Classification (SITC Rev 2). They are from the Organization for Economic Cooperation and Development (OECD), Trade by Commodity, Series C. d The exports are from the same source and classification as the imports. The exports are used in this study solely to derive "Apparent consumption" figures: production plus imports minus exports. ' The defense use refers to calendar-year annual usage. The data are from Data Resources, Inc., McGraw Hill FSC-DIFS databank.

The resultant Country Weighted Scores are given in Table 4. They are gotten by weighing each country's Country Factor by the proportion of each product supplied to the U.S. market by that respective country. By way of illustration, we note that the Weighted Country Score (WCS) for Storage Devices increased significantly, while that for capacitors decreased. An examination of the distribution of U.S. imports of each item, by supplying country, and of the Country Factors in Table 3 and in its related footnote reveals the reasons for

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Table 2: Import Vulnerability Indices: Computers, a Basic Ratios

Level

Imports/ production

Imports/ supply b

Defense/ production ~

Import growth a

12.7 43.8

13.7 47.9

0.61 0.33

46.8

12.7 24.0

13.7 36.3

3.5 3.2

30.1

24.5 35.2

31.3 47.6

3.5 3.2

9.2

4.3 4.0

4.3 4.1

0.1 0.1

8.7

9.8 11.0

10.4 12.5

1.4 0.9

18.8

Computer 1982 1987

[

Storage devices 1982 1987

II

Capacitors 1982 1987

III

Diodes, transistors, semi-conductors 1982 1987

III

Printed circuit boards 1982 1987

III

aThe following details the product categories used to identify the computer items: SIC

SITC

FSC

Computers (CPUs)

3571

Storage devices Capacitors Diodes, etc. Printed circuits

3572 3675 3674 3672

7521 7522 7524 77884 7763 7762

7021 7022 7025 7025 5961 5962

bSupply here refers to "Apparent Consumption," calculated as production plus imports minus exports. CThis is the proportion of annual produciton that is utilized for defense purposes. dAverage annual rate of growth, 1982-87.

these changes. According to Table 3, a relatively large proportion (60%) of Storage Devices is sourced from Germany. By the late 1980s, Germany's move to unification cast doubts on its political orientation in the case of any future conflict, and therefore its Country Factor was increased from 0.2 in 1982 to 0.5 in 1987. This explains the increased "riskiness" associated with Storage Devices, as its Weighted Country Score increased from 0.32 to 0.50 between these two years. On the other hand, Capacitors enjoyed a downgrading of the CWS measure of country-related riskiness: from 0.62 to 0.55. The

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M. Kellman, Y. S h a c h m u r o v e , a n d T. Saadawi

Table 3: D e m o n s t r a t i o n o f Calculation of H y p o t h e t i c a l C o u n t r y W e i g h t e d Scores, 1982 Country:

UK

Germany

France

Thailand

China

Country factor a Proportion of U.S. imports b Computers Storage devices Capacitors Diodes, etc. Printed circuits

0.2

0.2

0.4

0.8

0.6

0.5 0.1 0.1 0.2 0.1

0.1 0.6 0.1 0.2 0.1

0.2 0.1 0.1 0.2 0.2

0.1 0.1 0.6 0.2 0.4

0.1 0.1 0.1 0.2 0.2

aSee Ahmed et al. (1991) for a discussion of Country Factors. The higher the number, the more "risky" or "unreliable" is the country as a potential supplier of defense-related products for possible mobilization periods. bThese are hypothetical values meant merely for demonstration purposes.

reason for this may be seen by noting that a high proportion of this product (60%) originates from Thailand. In the early 1980s, Thailand was considered a high-risk supplier for many political and economic reasons. By the late 1980s, it became clear that its economy was "taking off," and that its Western orientation was being cemented by a growing volume of private investment projects in that country. Hence, by 1987, its Country Factor was upgraded from 0.8 to 0.6. This in turn resulted in a less risky CWF for Capacitors. These Weighted Country Scores, together with the ratios in Table 2, constitute the building blocks of which are composed the Import Vulnerability Indices (IVIs) (Table 5). Table 5 is arranged in four columns, each presenting values of the respective Import Vulnerability Indices, IVI1 to 11:14. In turn, values are presented for each system, subsystem, and component for each of two industry census years, 1982 and 1987. Focusing first on the first index, 1I:11, because the index is composed of a single (import-supply) ratio, it is denominated in terms of a cardinal, or ratio, scale. Therefore, one may impute meaning, or "semantic content" not only to the rankings, but also the relative sizes- both between products at different levels of the Work Breakdown Process and between the two years. It is first noted that the indices here demonstrate a relatively large range. The maximum is 47.9 percent, for computers (or CPUs) in 1987, while the minimum is as low as 4.1 percent for the category including diodes, transistors, and semi-conductors. Thus, for some of the products

IMPORT VULNERABILITY

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Table 4: Weighted C o u n t r y Scores

Computers Storage devices Capacitors Diodes, etc. Printed circuits

1982"

1987b

0.34 0.32 0.62 0.44 0.56

0.36 0.50 0.55 0.50 0.55

aThis column was obtained by multiplying the country factors in Table 3 by the respective country-source ratio, also in Table 3. bThe figures in this column were obtained by applying different Country Factors to the same distribution of country sourcing as in Table 3. The new Country Factors are: United Kingdom, 0.2; Germany, 0.5; France, 0.3; Thailand, 0.6; China, 0.9. Note that the main differences between these and the 1982 CFs are that Germany and China were judged to be significantly less reliable as potential suppliers and France somewhat more reliable than they had in 1982.

(computers and capacitors), close to half of the supply, or apparent consumption in the United States in the late 1980s came from imported sources, while for others, such as the diodes and transistors, domestic usage was supplied predominantly from domestic sources. The existence of such a wide range for the index is a strong argument

Table 5: I m p o r t Vulnerability Indices: C o m p u t e r s

Computers 1982 1987 Storage devices 1982 1987 Capacitors 1982 1987 Diodes, transistors, semi-conductors 1982 1987 Printed circuit boards 1982 1987

IVI1

IVI2

IVI3

IV14

13.7 47.9

2.9 4.0

6.7 8.2

12.8

13.7 36.3

6.9 10.8

9.5 16.1

13.7

31.3 47.6

10.4 12.3

17.6 18.5

17.0

4.3 4.1

0.6 0.6

2.3 2.4

2.9

10.4 12.5

3.8 3.4

8.5 7.9

9.6

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Figure 2. Import VulnerabilityIndex 1, computers 1987. in its favor, because it allows for clear distinctions between "import dependent" and "non-import dependent" categories of products. Examining the profile of 11/11 in 1982, across products (system and subsystems), we note that the pattern suggests that in the early 1980s, computers were relatively endangered by "import dependence" not at the final, system level (where IVI1 equaled only 13.7%), but rather at the component (Level 3), where capacitors registered an IVI1 of 31.3 percent, close to three times higher. Presumably, were IVI1 being utilized as the relevant criteria for assigning import vulnerability priority for purposes of stockpiling, the focus at that time would have been more on the upstream components and less on the final downstream system. Shifting attention to changes over time, one notices that relative changes in import dependence were not uniform across the Work Breakdown pattern. Roughly speaking, the further system and subsystems furthest downstream (Levels 1 and 2) experienced the largest relative slides into foreign dependence (of roughly 300% or more). At the component level (Level 3), the degree of foreign dependence increased only moderately in most cases, and even decreasing in one case (the diodes and transistors). By 1987, the profile one obtains from IVI1 is quite different. It is now more evenly distributed across the Work Breakdown categories. This profile is illustrated in Figure 2. It is clear from the profile in Figure 2 that the degree of Import Dependence or Import Vulnerability in 1987, as depicted by IVI1

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is relatively "front loaded." That is, the highest degree of vulnerability is present in the final system and subsystem levels, while most of the component (Level 3) items are hardly affected by import vulnerability. Shifting our attention now to IVI2, we focus on the differences between the pattern of foreign dependence emerging from this index as compared to the previous one. It might be recalled that this index incorporates the same factors present in 1VI1, but adds to them the proportion of defense usage as a proportion of domestic production.12 Because the portion of domestic product assigned for defense use for this particular system tends to be lower than the import ratios, the sizes of the index tend to be lower than are those of IVI1. Because IVI2, like IVI1, is composed of "objective" ratios (combined subjectively), the fact that they tend to be smaller than IVI1 may indeed be interpreted to indicate that use of IVI2 suggests an overall lesser degree and urgency to foreign dependence for this particular system and its subcomponents. The relative rankings of import vulnerability also differ from that obtained from the previous index. We see this in Figure 3. Clearly, the "front-loaded" pattern described by the profile of IVI1 is no longer descriptive of the pattern of import dependence Pin the case illustrated in the text, one-half weight is assigned to the import ratio and one-half to the defense-use ratio. This was an arbitrary choice, chosen for demonstration purposes. The program is arranged so that the user may assign his or her relative weights to each of the factors. This is generally true for IVI3 and IVI4 as well.

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Figure 4. Import Vulnerability Index 3, computers 1987. when IVI2 is utilized as the relevant criteria. Now the second-level subsystem (second from the left) is found to be at a higher level of risk with respect to import vulnerability than is the final system product (first on the left), and the third item from the right, a component belonging to Level 3 on the Work Breakdown scheme, registers the highest level of potential vulnerability. Figure 4 illustrates the vulnerability profile for computers in 1987, when the Weighted Country Scale is added as an additional factor in the index. Because a non-parametric factor, composed of a somewhat arbitrarily chosen scale, is now incorporated into the index, the interpretation of the actual values becomes more problematic. However, some insight into how explicit consideration of relative country "riskiness factors" may affect the pattern of import vulnerability of a product or system may be attained by comparing the profile obtained using this IVI3 (Figure 4) with the previous ones. In the particular case of computers, it is found that the profile of relative vulnerabilities depicted with the use of IVI3 is practically identical with that given by IVI2. This is an important reminder that certain patterns may not be "index sensitive," but may rather present a relatively robust pattern. A finding such as above would indicate a situation in which the "objective" relative rankings illustrated in Figure 3 with IVI2 is not contradicted or reversed, or indeed even substantially changed, when "subjective" country risk assessments are introduced into the picture. This is but one illustration of the analytical use and flexibility that this approach affords the analyst and user of this approach.

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A different situation is illustrated when we introduce the surge factor, as embodied in IVI4 (Figure 5). When the change from 1982 to 1987 o f the import share (the surge factor) is taken into account as incorporated in IVI4, the relative import dependence or potential vulnerability of the Level 1 system (first on the left) increases relative to that of the subsystem in Level 2 (second from the left). Thus, here is an illustration of a case where the choice of the relevant index may in fact affect the relative potential import-vulnerabilities. 5. SUMMARY

This paper provides a computationally feasible methodology that, in the context o f a theoretically consistent model, allows for numerical and quantitative measurements and rankings of various indicators of "foreign dependency," with focus on defense-industry usage. The topic has taken on a new urgency as of late when it has been noted that the very hi-tech weapons, generally given credit in Desert Storm, consist of critical components and subsystems that are not, and perhaps cannot be produced in the United States. The problem is a relevant one across the technological spectrum. Thus, it may be as difficult for the United States to assure an adequate supply of chemically treated boots as to provide the latest microchip sensors.

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We develop a methodology that results in a quantitative determination that allows for a ranking of import dependence or vulnerability of products. This method takes into account most existing industrial plants, import surges, and the relative weight of defense usage in total national apparent consumption. It yields unique dependence profiles, identifying bottlenecks along the Breakdown Analysis dimension (i.e., subassemblies, components down to raw materials). The method is demonstrated in several applications across the technological spectrum.

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