examine the market structure of the US manufacturing sector of the provided article provided below.

How Competitive is the US Manufacturing Sector? Fatma Abdel-Raouf Department of Economics and Finance, Goldey-Beacom College, 4701 Limestone Road, Wilmington, DE 19808, USA. E-mail: raouff@ghc.edu This paper assesses the market structure of the US manufacturing sector using a corrected four-rm concentration ratio. The correction is done to the published 1997 CR, using the North American Industry Classication System, and addresses four areas: overaggregation, underaggregation, market locality, and international trade. The paper finds the US manufacturing sector to be fairly competitive with 58.0 percent of its industries operate in competitive markets, 17.5 percent operate in loose oligopoly, 24.5 percent operate in tight oligopoly, and none operates in monopoly markets. Equally important, this research nds international trade to have an important impact on the level of competition in the manufacturing sector. Eastern Economic Journal (2009) 35, 5270. doi:10.1057fpalgrave.eej.9050043 Keywords: concentration ratio; market structure; manufacturing sector; NAICS JEL: L11; L60 INTRODUCTION In 1982, William Shepherd examined the market structure of the US economy, including the manufacturing sector, where he found that in 1980, 69 percent of the manufacturing sector operated in effective competition (loose oligopoly, perfect competition, and monopolistic competition), 27.08 percent operated in tight oligopoly, 3.92 percent operated in dominant firm markets, and none operated in monopoly. Moreover, Shepherd compares the market structure of the US economy over different years: 1939, 1958, and 1980. Shepherd fmds that the US manufacturing sector became more competitive over the aforementioned periods of time, with most of the changes happening between 1958 and 1980. In particular, Shepherd finds that the monopoly's share of the US manufacturing sector decreased from 0.75 percent in 1939 to 0.35 percent in 1958 and to zero in 1980. The tight oligopoly's share increased slightly from 36.4 percent in 1939 to 37.46 percent in 1958 then decreased to 27.08 percent in 1980. The dominant firm's share witnessed the largest decrease over the same period from 11.35 percent in 1939 to 6.29 percent in 1958 and to 3.92 percent in 1980. Over the ensuing decades, the manufacturing sector has witnessed some changes: Its share of GDP, employment, and employees\" compensation decreased from 19.66, 20.75, and 26.37 percent, respectively, in 1980 to 15.41t, 14.43, and 16.76 percent, respectively, in 1997.1 In addition, the 1980s and 1990s witnessed two movements, the large merger movement of the 1980s2 and the increase in imports. The former increased concentration, while the latter decreased it.3 Furthermore, there were large cutbacks in antitrust activities and increases in deregulation during the 1980s, especially during the Reagan administration. The antitrust activities increased slightly during the 1990s but were still considered weak. As such, an update of Shepherd's work is needed, and that is the intention of this paper. Doing so enables us to see whether the US manufacturing sector has become more or less competitive4 than it was in 1980. Note, however, that this research uses 199'? data, which is organized and classified by the North American Industry Classication System (NAICS). This system was first introduced in 1997. Earlier data (1992 and prior years) are organized and classied by the Standard Industry Classification (SIC) system. In assessing the structure of the US manufacturing sector, I am going to use the 199'? four-firm concentration ratio. Knowing its shortcomings as a measure of market structure, correction methods will be used to remedy these shortcomings. Four corrections are used to address overaggregation, underaggregation, market locality, and international trade. The modified concentration ratio in conjunction with other criteria will be used to analyze the structure of the US manufacturing sector. In addition, a comparison will be made between the published and corrected concentration ratio to see how closely the former substitutes for the latter. Comparing the result of this research to that of Shepherd's in 1982, I find that the US manufacturing sector has become slightly more competitive than it was in 1980. In particular, I find that 58 percent of the manufacturing sector operate in competitive markets, 17.5 percent operate in loose oligopoly, and 24.5 percent operate in tight oligopoly markets. Moreover, confirming Shepherd's results, none of the manufacturing sector industries in 199'1'r operates in a monopoly market. Furthermore, agreeing with Shepherd's findings in 1982, international trade plays an important role in keeping the US markets competitive. International trade increases the percentage of the manufacturing sector operating in competitive markets by 31.6 percent, while decreasing the percentage of the manufacturing sector operating in loose and tight oligopoly markets by 35.2 percent and 15.3 percent, respectively. The paper proceeds as follows: The next section shows the importance of concentration and market structure. Then the further section introduces the reader to the new industry classication system NAICS. The subsequent section discusses the concentration ratio, its shortcomings, and the methodology used to correct for these shortcomings. The penultimate section presents the results. The last section concludes the research. IMPORTANCE OF CONCENTRATION AND MARKET STRUCTURE Assessing the structure of the manufacturing sector is important as it relates to its performance through the traditional structureconductperformance paradigm,5 which was originally introduced by E. Mason of Harvard during the 1930s and elaborated on by many economists subsequently.6 In addition, structure is affected by economies of scale. Empirical resultsT nd that, in most of the US industries, minimum efficient scale (MES) is a small percentage of the total industry output, cost gradients are small, multiplant economies of scale are slight or absent, and excess market shares market shares that exceed the MES extensively exist [Shepherd and Shepherd 2004]. Note that these results indicate competitive structure. Concentration plays an important role in antitrust policy. The Department of Justice (DoJ) uses concentration as measured by the HerfindahlHirschman Index (HHI) in judging horizontal merger acquisitions. If the HHI exceeds 1,800, the DoJ considers this market to be highly concentrated and tightly scrutinizes any merger EasternFconomicJoumalZMSS 54 acquisition in that market. If the HHI is between 1,000 and 1,800, the DoJ considers this market to be moderately concentrated, while if the HHI is less than 1,000, the market is considered unconcentrated. Moreover, concentration might affect innovation. Following the "creative destruction" of Schumpeter [cited in Gopinath et al. 2004] concentration can increase innovation, which in turn increases productivity, decreasing the social welfare loss associated with concentration. Gopinath et al. [2004] examine the effect of concentration on productivity growth in the US manufacturing sector. Consistent with previous research, they find an "inverted-U relationship" between concentra- tion and productivity. As concentration increases, so does productivity up to certain level. Beyond that level, increased concentration reduces productivity. They estimate this concentration growth rate to be 23 percent, beyond which concentration growth will have a negative effect on productivity growth. At this peak level of concentration growth rate, productivity increases by approximately 1.7 percent. They also find that concentration growth contributes an average of 10 percent of the productivity growth in the US manufacturing sector. Furthermore, research - while not confirmed by all research - has found that market structure is related to human capital, workers' quality, workers' wages, and firm's systematic risk and cost of capital. Belman and Heywood [1990] address the first two factors. They find that the capital-to-labor ratio is positively related to concentration in the non-union sector, while it is unrelated to concentration in the union sector. Belman and Heywood also find that concentrated industries hire more qualified workers (in terms of the educational background of workers). When including a measure of research and development, Belman and Heywood find that more qualified workers are not more likely to work in concentrated industries. They find that more qualified workers are associated with industries that have large R&D budgets that happen to be concentrated. The relationship between concentration and workers' wage is controversial. Some [Dalton and Ford 1977; Kwoka 1983; Long and Link 1983; Mellow 1983; Heywood 1986; and Belman and Weiss 1989, cited in Belman and Heywood 1990] believe that concentrated industries pay their workers higher wages, generating another source of inefficiency associated with concentration, while others [Rapping 1967; Pugel 1980; and Freeman and Medoff 1981, cited in Belman and Heywood 1990] have not confirmed this relationship. In addition, Belman and Weiss [1989] find that the higher wage paid by concentrated industries is partly direct effect (i.e., because of concentration), and the majority of it is indirect effect through unionization. Regarding the relationship between concentration and a firm's systematic risk and cost of capital, we tend to believe that concentrated industries reduce the systematic risk for its constituent firms, research has not unanimously confirmed this relation- ship." Sullivan [1982] cited in Sudarsanam [1992] finds that a firm's systematic risk, measured by beta, decreases with concentration [Fabozzi, Garlick, Ghosh, and Kislowski [1986] cited in Sudarsanam [1992] find a weak negative impact of concen- tration on systematic risk]. On the other hand, Curley et al. [1982]cited in Sudarsanam [1992] find that concentration has no effect on the firm's systematic risk. NORTH AMERICAN INDUSTRY CLASSIFICATION SYSTEM In 1997, the NAICS replaced the SIC system. The NAICS is a combined effort of the US [Bureau of Economic Analysis (BEA), Bureau of Labor Statistics (BLS), andthe Census Bureau], Canada, and Mexico. This provides comparable statistics among the three NAFTA trading partners. The NAICS implemented profound structural improvements over the SIC system and identified 358 new industries for the whole economy. Some of the major changes introduced by the NAICS are [Zeisset and Wallace 2003]: 1. The NAICS doubles the number of sectors in the economy from 10 in the SIC system to 20. In manufacturing, the NAICS reorganizes the manufacturing sector; recognizing 79 new industries, revising 186 other industries, creating the Computer and Electronic Product manufacturing subsector, moving out many important activities, and moving in other activities, to mention a few. In addition, the NAICS moves information to a separate sector. 2. The NAICS introduces a new numbering system. NAICS industries are identified by a 6-digit code, compared to a four-digit SIC code. The longer code allows for more flexibility in defining subsectors and industries. The international NAICS code identifies only the first five digits of the code, leaving the sixth digit for an individual country's use. Therefore, the six-digit NAICS codes in the US may not be the same as their counterparts in Canada or Mexico, while the five-digit codes are the same among the three countries. The structure of the NAICS in the manufacturing sector is as follows: . 21 subsectors, three-digit code (NAICS 311-339) . 89 industry groups, four-digit code (NAICS 3111-3399) . 183 industries, five-digit code (NAICS 31111-33999) . 474 US industries, six-digit code (NAICS 311111-339999). 3. The NAICS introduces a different classification principle than that used by the SIC system. SIC classification is based on the primary type of activity undertaken by the firm and all units of the firm are classified under the same industry. NAICS, however, is based on the production process or the supply function of the firm. Therefore, different units of the same firm may be classified under different industries. In addition, if an establishment produces products classified in more than one industry, the establishment is classified in the industry with the largest product value. One type of establishment that is significantly affected by this classification is the auxiliary establishments. Auxiliary establishments are those that produce support services to other establishments of the enterprise. These services are not intended for use outside the enterprise. For example, an establishment providing data processing service (or research) for an automobile-making enterprise will be classified under data processing services (the research unit will be classified under professional, scientific, and technical services) using the NAICS while it is classified under automobile manufacturing using the SIC system [NAICS Association 2003]. That causes significant changes in the published data. For example, in the state of Delaware, MBNA is no longer the largest bank in the state, although it is still the state's largest private employer, as the majority of its employment is now classified under the Management of Companies and Enterprises sector. In addition, chemical manufacturing in the state of Delaware has some of its units - which all used to be classified under chemical manufacturing in the SIC system - being classified under other sectors in the NAICS: Professional, Scientific, and Technical Services; Management of Companies and Enterprises; Administrative Support and Waste Management and Remediation Services, and others. This caused Delaware'sFatma Abdel-Raoul" How Competitive is the US Manufacturing Sector? 56 Table 1 Correspondence between the 199? NAICS and the 1987 SIC industries for the manufacturing (mfg) sector NAICS code Exact match Combinations Subsets Total Number % Number "/6 Number % 311 Food mfg 12 25 24 5D 12 25 48 312 Beverage and tobacco product mfg 2 22 3 33 4 44 9 313 Textile mills 2 I? 10 83 0 12 314 Textile product mills 4 50 4 5D 0 8 315 Apparel mfg 0 2D 83 4 1T 24 316 Leather and allied product mfg 8 BO 2 20 0 10 321 Wood product mfg 6 43 4 29 4 29 14 322 Paper mfg 7 35 s 40 5 2s 20 323 Printing and related support activities 2 l? 8 67 2 1T 12 324 Petroleum and coal products mfg 4 80 l 20 0 5 325 Chemical mfg 18 53 10 29 6 18 34 326 Plastic and rubber products mfg T 41 4 24 6 35 1? 327 Nonmetallic mineral product mfg 15 63 4 1'? 5 21 24 331 Primary metal mfg 15 58 7 27 4 15 26 332 Fabricated metal product mfg 1'! 40 15 35 ll 26 43 333 Machinery mfg 25 51 13 2'? 11 22 49 334 Computer and electronic product mfg 15 50 10 33 5 1T 30 335 Electrical equipment, appliance and component mfg 11 50 7 32 4 18 22 336 Transportation equipment mfg 5 1'.-' 10 33 15 50 30 337 Furniture and related product mfg 5 3B 5 38 3 23 13 339I Miscellaneous mfg 9 38 13 54 2 8 24 Total 189 40 182 38 103 22 474 employment in the chemical manufacturing industry to decrease from 20,600 in 2001 (using SIC) to 4,?00 in 2002 (using NAICS) [Sharpley G Undated] With these changes, the NAICS is still comparable to the SIC system. In the manufacturing sector, 40 percent of the NAICS industries exactly match the SIC, 38 percent are combinations of two or more SIC industries, and 22 percent are subsets of the SIC industries. Table 1 shows the correspondence between the NAICS and the SIC industries for different subsectors in the manufacturing sector. Looking at Table 1, we see that some subsectors such as leather and allied product manufacturing and petroleum and coal products manufacturing have the majority of their industries exactly match their SIC counterparts while the apparel subsector has none of its industries exactly match the SIC industries. METHODOLOGY FOR CORRECTING THE CONCENTRATION RATIO In assessing the structure of the US manufacturing sector, I use the four-firm concentration ratio (hereafter CR4).10 The concentration ratio is calculated from the value of shipments by domestic producers. As such, it has some limitations: 1. Over-aggregation: Some industries are broadly defined, as they include non- competing products. For example, the pharmaceutical companies sell different drugs (such as AIDS medication, anti-depressant drugs, and vaccines, etc.). These drugs EasternEconomicJournalZMSS do not compete with each other. Pharmaceutical companies have a very high concentration in the individual drug markets. In 1997, the CR4 for the pharma- ceuticalsndustry was 35.6 percent; correcting it for overaggregation increases it to 59.08 percent. Similarly, aircraft manufacturing; motorcycle, bicycle, and parts manufacturing; " and many others are broadly defined. The improvements in industry classification introduced in the NAICS did not eliminate all the overaggregation industry definition problems, albeit reducing them. For example, 311422, specialty canning is broadly defined - this industry was broadly defined under the SIC system as well - as it includes non-competing products like, 3114221, canned baby food; 3114224, canned soups and stews; 3114227, canned dry beans, and other canned specialties. To adjust for overaggregation, I will use the weighted average four-firm concentration ratio with the value of shipment as weight. The weighted average CR4 is based on the products' (seven-digit NAICS) CR4s and their value of shipment. Data for the products' value of shipment are obtained from the 1997 census industry series publications. The Census Bureau publishes an industry series publication for each six-digit NAICS industry. These industry series publications contain detailed statistics regarding different products produced by the industry. Eighty-three industries have been modified for this shortcoming. The technical appendix contains more details about calculating the modified CR4. 2. Underaggregation: Since the boundaries of an industry are not well defined, we might find competition between two products in different industries, such as in the copper and aluminum industries. The copper industry is highly concentrated (in 1997, it had a CR4 of 94.5 percent), but since aluminum competes with copper in many applications, this reduces the concentration in the copper industry (in 1997, its corrected CRac was 77.11 percent). Another example is the wood and non-wood office furniture industries. The non-wood office furniture industry is concentrated (CR4 of 64.7 percent in 1997), but since wood office furniture competes with non- wood office furniture, this reduces its concentration to 56.8 percent in the non-wood office furniture industry. The NAICS classification is broadly defined in some cases, while narrowly defined in others. As with overaggregation, NAICS makes some improvement over the SIC system regarding the underaggregation problem but does not completely eliminate it. To adjust for underaggregation, I will use a combined four-firm concentration ratio [Weiss and Pascoe 1986]. To calculate the combined CR4, I divide the summation of the value of shipments by the largest four companies in the two (or more) affected industries by the total value of shipments in these industries. Thirty-two industries have been modified for this shortcoming and combined into 14 industries. 3. Geographical coverage of the market: The concentration ratio pertains to the nation as a whole. Some markets are highly localized, such as ready-mix concrete with a CR4 of 7 percent in 1997, suggesting a very competitive market. However, because of its high transportation cost, a local market exists, and it is highly concentrated. Cement is another example; Scherer and Ross [1990] mention that it costs approximately 45 cents to ship one dollar's worth of cement 350 miles. That is why, according to Scherer, in 1977, 83 percent of all cement was shipped 200 miles or less. In 1997, the CR4 for cement was 33.5 percent; adjusting for market locality increases it to 53.75 percent. Products with high transaction cost usually have local or regional markets, and for them, the published concentration ratios tend to understate the actual concentration. Eastern Economic Journal 2009 3558 The modication for market locality is based on the distance shipped13 for most of the shipment.14 Assessing the distance shipped is based on data from the 199'? Commodity Flow Survey (CFS) published by the Department of Transportation. CFS uses the Standard Classication of Transportation Goods (SCTG) coding system. Therefore, each SCTG commodity is matched to its NAICS code for consistency. The optimal correction for regional and local markets is the weighted averages of local or regional four-firm concentration ratios [Weiss and Pascoe 1986; Schwartz- man and Bodoff 1971]. To do so, we need the local or regional concentration ratios for the affected industries. However, the Census Bureau no longer publishes this information. The last year for which the Census Bureau published the aforemen- tioned data is 1963. To that end, an alternative method is used. Following Weiss [1991],15 I correct for the market locality using a constant factor explained in the technical appendix derived from the average CR4 of local, regional, and national industries. 4. Internationat' trade: Imports: The concentration ratio accounts for the domestic production. This causes an upward bias of concentration in the US markets as it does not account for imports. In general, imports increase sales and consequently lower the concentration ratio. Exports: The value of the US exports is calculated in the producer concentration ratio but they do not reach US consumers. If large producers export more of their output than small producers which seems to be the case then this causes an upward bias in the producer concentration ratio. In general, exports reduce domestic sales and consequently increase concentration ratio. The automobile industry is a good example here. In 199?, CR4 for automobile manufacturing in the US was 79.5 percent. Taking international trade into consideration reduces it to 41.41 percent.16 Data for exports and imports are obtained as a special tabulation from the US Department of Commerce. Since there is no published data about the 199? US exports and imports by 6-digit NAICS industries, a special tabulation has to be made. Different modications have been used in the literature to adjust the concentration ratio for international trade.\" In this paper, I will use the following:18 S4 CR4 CR4T (S+MX 100 where 3,; is the value of shipment for the four largest firms in the industry,\" S the total value of shipments in the industry, X the value of exports, and M is the value of imports. Coughlin and Watkins [1985] nd that in the majority of industries, international trade adjustments, both intra-rm trade by the leading rms and foreign trade in general, has a small effect on concentration. Only in 20 industries were the modifications important. However, as the role of international trade increases over time, we expect the international trade modication to be more important. Dealing with undisclosed data For some industries, the Census Bureau withholds the concentration ratio to prevent disclosure of data for specic companies. In manufacturing, only two industries\" had their four-rm CRs suppressed. In both cases, the eight-rm CRs are 100 EasternEeonomicJoumalMSS 59 percent and the number of firms in the industry is less than 10 (8 and 5 to be exact). In both cases, a CR4 of 90 percent is used. Procedures for concentration ratio adjustments In adjusting the manufacturing concentration ratios, I will proceed as follows: 1. Estimate the withheld concentration ratios. 2. Adjust the CR4 to reflect industry definition problems, when applicable. 3. Adjust the CR, to reflect the market locality problem, when applicable. 4. Adjust all CR4s for exports and imports. Correlation coefficient between the published and the corrected CR4s Because of its use in many industrial organization studies to assess the market structure, I examine how closely the published CR4s relate to the corrected CRAS. The published and corrected CR4s are strongly correlated. The correlation coefficient between them is 0.8043. Furthermore, for some subsectors the published CR4s and the corrected ones have even stronger correlation. These subsectors are textile product mills, with a correlation coefficient of 0.9895; wood product manufacturing, with a correlation coefficient of 0.9336; printing and related support activities manufacturing, with a correlation coefficient of 0.9531; plastic and rubber products manufacturing, with a correlation coefficient of 0.9130; and fabricated metal product manufacturing, with a correlation coefficient of 0.9654. On the other side, for other subsectors the correlation coefficient between the published and the corrected CR4s are not as strong. These subsectors are computer and electronic product manufacturing, with a correlation coefficient of 0.6775; paper manufacturing, with a correlation coefficient of 0.6913; and primary metal manufacturing, with a correlation coefficient of 0.6277. The aforementioned correlation coefficients are all statistically significant. The calculated t-values are 29.4063, 16.7697, 9.0258, 9.9571, 8.6676, 23.9921, 4.8742, 4.059, and 3.9502, respectively. RESULTS The corrected CR4 (hereafter CR4c) is used to assess the market structure as follows:2 . Competitive:"If CRac 60 percent, the leading firms have significant market power and high barriers to entry. . Monopoly: If CRac is very close to 100 percent, entry to the market is blockaded, and there is evidence of monopoly power. Eastern Economic Journal 2009 35Fatma Abdel-Raouf How Competitive is the US Manufacturing Sector? 60 Table 2 Market structure of the US manufacturing sector in 1997 Competitive Loose oligopoly Tight oligopoly Monopoly Number of industries 275 83 116 % of all industries 58.0 17.5 24.5 The results show that the US manufacturing sector has become slightly more competitive in 1997 than it was in 1980.2 Table 2 shows the structure of the manufacturing sector in 1997. Three results merit mentioning: The first result shows the majority of the US manufacturing industries are competitive: 58 percent of the manufacturing industries operate in competitive markets, 17.5 percent operate in loose oligopoly, and 24.5 percent operate in tight oligopoly markets. In classifying the market structure, CRac is mainly used as a criterion. Four groups are analyzed: . Industries with CRac 60 percent are all examined to see if any do not belong to the tight oligopoly market structure. All of them, with no exception, have a CR4 or CRAc > 60 percent and fit in the tight oligopoly structure. . Industries with CR4 or CRAc of 95 percent or more have been scrutinized to assess whether they can be categorized as monopoly or not (these industries are carbon black manufacturing, undisclosed CR4; alumina refining, undisclosed CR4; cellulosic organic fiber manufacturing, CR4=100; light truck and utility vehicle manufacturing, CR4c=99.3; flavoring syrup and concentrate manufacturing, CRAC=97.8; and Cane sugar refining, CR4=98.7). In doing so, I examine the number of firms, price-cost margin (PCM), "barriers to entry, the market share of each firm, and the same industry information mentioned above. Using this information, I find that none of these industries is concentrated enough to be classified as a monopoly. The second result finds that none of the manufacturing industries is concentrated enough to be classified as monopoly. This result agrees with Shepherd's result in 1982. Eastern Economic Journal 2009 35Shepherd's 1980 classication of the manufacturing sector is 69 percent competitive and 31 percent tight oligopoly. The percentage of the manufacturing industries operating in tight oligopoly decreased from 31 percent in 1980 to 24.5 percent in 199?. Some of the concentrated industries in 1980 have become less so in 199?. Examples of these industries include power-driven hand tool manufacturing; rolling mill machinery and equipment manufacturing; ball and roller bearing manufacturing; motor and generator manufacturing; storage battery manufactur- ing; rubber and plastic hoses and belting manufacturing; scale and balance manufacturing; fastener, button, needle, and pin manufacturing; optical instrument and lens manufacturing; and game, toy, and children's vehicle manufacturing. On the contrary, some of the competitive industries in 1980 have become concentrated in 199?. Examplm of these industries include animal (except poultry) slaughtering, meat processed from carcasses; Nitrogenous fertilizer manufacturing; phosphatic fertilizer manufacturing; glass container manufacturing; mattress manu- facturing, cellulosic organic ber manufacturing, crown and closure manufacturing, cutlery and atware (except precious) manufacturing, and house slipper manufacturing. Comparing the classification of industriesz8 in the manufacturing sector between 199? and 1980, I find that the majority of the manufacturing sector industries stay within the same classification as in 1980. In particular, 82.9 percent of industries in the manufacturing sector have the same classification as in 1980 while 1?.1 percent of industries have different classications in 199? than in 1980. Table 3 shows a comparison between the classications in 199? and 1980. A closer examination at the market structure of the manufacturing sector between 199? and 1980 reveals that some subsectors have seen small changes to their market structures in 199? compared with 1980, while others have seen larger changes. Some of the subsectors that have seen minor changes in their structures between 199? and 1980 are beverage manufacturing; textile mills; textile product mills; apparel manufacturing; leather and allied product manufacturing; wood product manu- facturing; paper manufacturing; plastic and rubber products manufacturing; and furniture and related product manufacturing. Examples of the subsectors that have seen considerable change to their structures are chemical manufacturing; non- metallic mineral product manufacturing; primary metal manufacturing; electrical equipment, appliance and component manufacturing; and transportation equipment manufacturing. The third remit indicates the important role international trade plays in keeping the US manufacturing markets competitive. International trade increases the competitive share of the manufacturing sector by 14 percentage points, decreases the loose oligopoly share by 9.5 percentage points, and decreases the tight oligopoly share by 4.4 percentage points (see Table 4). Some industries are affected more by international trade than others. Five subsectors are heavily affected by international trade. These subsectors are apparel manufacturing and leather and allied product manufacturing (NAICS 315 and 316), Table 3 Comparison between 199'?Ir and 1980 classification 1980 Clarication 1997 Clarication CompetitivefLO (%) TO {'%) T0 9.5 l 5.6 Competitive 6?.3 7.6 EasternEennnmianumalm 35 Patina Abdel-Raouf How Competitive is the US Manufacturing Sector? 62 machinery manufacturing (NAICS 333), computer and electronic product manu- facturing (N AICS 334), and transportation equipment manufacturing (NAICS 336). The apparel and the leather industries have become very competitive as a result of international trade. Table Szgshows the published and trade corrected CR4s for these subsectors. From Table 5, we see that the international trade corrected CR4 decreases by as much as 83.65 percent for men's and boys\" cut and sew work clothing manufacturing in the apparel subsector and 93.9 percent for fur and leather apparel manufacturing in the leather subsector. Moreover, 17 out of those 26 industries have CR4s in excess of 40 percent according to the published CR4s. After correcting for international trade, only two industries remain with CR4s in excess of 40 percent. Table 4 Role of international trade on manufacturing industries in 199'? Corrected CR (CRm) All corrections but international trade Number % Number % Competitive 2'15 58 209 44.1 Loose oligopoly 83 17.5 128 2'! Tight oligopoly 116 24.5 13? 28.9 Table 5 Published and international trade corrected CR4s for the apparel and leather industries 199? Industry Published CR4- corrected NAICS CR (CR4) for international code trade 315221 Men's and boys' out and sew underwear and nightwear 67.5 44 manufacturing (mfg) 315222 Men's and boys' out and sew suit, coat, and overcoat mfg 42 18.52 315223 Men's and boys' out and sew shirt (exc work shirt) mfg 42.9 35.99 315224 Men's and boys' out and sew trouser, slack, and jean mfg 68.9 32.14 315225 Men's and boys' out and sew work clothing mfg 46.6 1.62 315228 Men's and boys' out and sew other outerwear mfg 20.3 4.96 315231 Women's and girls' cutfsew lingerie and nightwear mfg 42.8 21.26 315232 Women's and girls' cut and sew blouse and shirt mfg 12.6 4.74 315234 Women's and girls' cut and sew suit, coat, skirt mfg 31.9 16.83 315239 Women's and girls' cut and sew other outerwear mfg 22.3 9.72 315291 Infants' cut and sew apparel mfg 60.9 24.36 315292 Fur and leather apparel mfg 22.6 1.38 315991 Hat, cap, and millinery mfg 36 20.62 315992 Glove and mitten mfg 63.8 31.44 315993 Men's and boys' neckwear mfg 48.2 3611'' 315999 Other apparel accessories and other apparel mfg 19 7.38 316110 leather and hide tanning and nishing 49.1 30.5 316211 Rubber and plastic footwear 54.6 26.68 316212 House slipper mfg 82.5 55.03 316213 Men's footwear (except athletic) mfg 49.7 18.34 316214 Women's footwear (except athletic) mfg 49.5 5 316219 Other footwear mfg 32.6 0.11 316991 Luggage mfg 51.9 11.24 316992 Women's handbag and purse 58.6 10.48 316993 Personal leather good (except women's handbag and purse) mfg 42.2 19.02 316999 All other leather good mfg 24.9 10.66 EastemEeommieJourleISS The machinery industries have become very competitive as a result of international trade as well. Table 6 shows the published and trade corrected CR4s for this subsector. From Table 6, we see that the international trade corrected CR4 decreases by as much as 80.11 percent for oil and gas eld machinery and equipment manufacturing. Moreover, 10 out of those 18 industries have CR4s in excess of 40 percent according to the published CR4s. After correcting for international trade, only two industries remain with CR4s in excess of 40 percent. The computer and electronic product industries are no different than the previous three subsectors. Table 7 shows the published and trade corrected CR4s for this subsector. From Table 7, we see that international trade corrected CR4 decreases by as much as 83.58 percent for watch, clock, and part manufacturing. Moreover, eight out of those 14 industries have CR4s in excess of 40 percent according to the published CR4s. After correcting for international trade, only one industry remains with a CR4 in excess of 40 percent. Being highly concentrated industries, the effect of international trade on transportation equipment industries, while substantial, is not as large as its effect on the aforementioned industries. Table 8 shows the published and trade corrected CR4s for this subsector. From Table 8, we see that international trade corrected CR4 decreases by as much as 70.94 percent for heavy duty truck manufacturing. In addition, six out of those nine industries have CR4s in excess of 60 percent according to the published CR4s. After correcting for international trade, only one industry remains with a CR4 in excess of 60 percent. In addition, many other industries in other subsectors are heavily affected by international trade. Some of these industries are game, toy, and children's vehicle manufacturing; doll and stuffed toy manufacturing; vitreous china, fine earthenware and other pottery product manufacturing; seafood canning; spring (heavy gauge) manufacturing; storage battery manufacturing; and primary battery manufacturing. Table 6 Published and international trade corrected CR4s for the machinery industries 1997' NA ICS Industry Published CR corrected code CR (CR4) for international trade 333120 Construction machinery manufacturing (mfg) 49.6 34.7 333131 Mining machinery and equipment mfg 36.4 26.88 333132 Oil and gas eld machinery and equipment mfg 44.3'1 8.81 333210 Sawmill and woodworking machinery mfg 30 17.91 333220 Plastics and rubber industry machinery mfg 30.2 16.85 333291 Paper industry machinery mfg 37.2 25.43 333292 Textile machinery mfg 24.4 9.24 333295 Semiconductor machinery mfg 43.5 31.35 333315 Photographic and photocopying equipment mfg 80.9 38.81 333516 Rolling mill machinery and equipment mfg 53 35.78 333611 Turbine and turbine generator set unit mfg 78.2 50.91 333612 Speed changer, industrial high-speed drive, and gear mfg 29 17.3 333613 Mechanical power transmission equipment mfg 26.1 19.96 333924 Industrial truck, tractor, trailer, and stacker machinery mfg 38.5 29.91 333991 Power-driven handtool mfg 47 31.21 333992 Welding and soldering equipment mfg 53.4 41.87 333995 Fluid power cylinder and actuator mfg 44.2 38.2 333997 Scale and balance (except laboratory) mfg 57.2 39.62 I"This is CR auna Abdel-MOI.\" How Competitive is the US Manufacturing Sector? 64 Table '7 Published and international trade corrected CR45 for computer and electronic product industries 799? lndtutry Published CR corrected NAICS CR (CR4) for international code trade 334112 Computer storage device manufacturing (mfg) 53.1 17.23 334310 Audio and video equipment mfg 36.8\" 4.96 334413 Semiconductor and related device mfg 52.5 27.13 334414 Electronic capacitor mfg 61.1 24.47 334415 Electronic resistor mfg 42.6 20.47 334416 Electronic coil, transformer, and other inductor mfg 13.5 6.61 334417 Electronic connector mfg 50.7 29.02 334418 printed circuit assembly (electronic assembly) mfg 40.6 25.09 334419 Other electronic component mfg 7.8 3.07 334513 Industrial process control instrument mfg 30.8 16.34 334516 Analytical laboratory instrument mfg 33.6 24.6 334517 Irradiation apparatus mfg 53.3 39.62 334518 Watch, clock, and part mfg 43.1 7.9 334613 Magnetic and optical recording media mfg 37.9 18.04 I"This is CR1\local CRs, which are no longer published by the Census Bureau. Likewise, to correct for overaggregation, we need the product CRs, which again are no longer published by the Census Bureau. This scarcity of research on this topic is what motivated me to undertake this research and examine how competitive the US manufacturing sector is. In assessing the market structure of the US manufacturing sector, I use a corrected CR4. The correction to the published CR4 is based on four elements overaggregation, underaggregation, market locality, and international trade. To correct for overaggregation, I use a weighted average CR4, where the weight used is the value of shipment. To correct for underaggregation, I use a combined four-firm CR. To correct for market locality, I use a constant factor approach. After these three corrections are completed, all concentration ratios are then corrected for international trade. The data used are the 1997 NAICS. The 1997 NAICS identies 474 industries within the manufacturing sector. In correcting the published concentration ratio for these industries, I modied 83 industries for overaggregation, 32 industries for underaggregation, 35 industries were classified as regional industries, and 12 industries were classied as local industries. The corrected CR4s are then used in conjunction with other criteria to assess the market structure of the US manufacturing sector. I nd 58 percent of all US manufacturing industries are competitive, 17.5 percent are loose oligopoly, and 24.5 percent are tight oligopoly. None of the US manufacturing industries operates in a monopoly market. Comparing this result with Shepherd's [1982], I fmd that the US manufacturing sector has become more competitive in 1997 than it was in 1982. In particular, the competitive structure of the manufacturing sector increased from 69 percent in 1980 to 75.5 percent in 1997 while the tight oligopoly decreased from 31 percent to 24.5 percent. Confirming Shepherd's result, none of the manufacturing sector in 1997 operated in a monopoly structure. The author also nds international trade to play an important role in keeping the US manufacturing industries competitive. Correcting the CR4 for international trade increases the share of the manufacturing competitiveness from 44.1 to 58 percent while it decreases the shares of loose and tight oligopoly from 27 and 28.9 percent to 17.5 and 24.5 percent, respectively. Furthermore, ve subsectors (apparel manufacturing, leather and allied product manufacturing, machinery manufactur- ing, computer and electronic product manufacturing, and transportation equipment manufacturing) are more influenced by international trade than the remaining subsectors. Finally, the author acknowledges that while the corrections to the CR4 used in this paper are not optimal, due to lack of data, they lead to better assessment of the market structure than the published CR4s