Mobility Barriers and Profitability of Multinational and Local Enterprises in IndianManufacturingAuthor(s): Nagesh KumarSource: The Journal of Industrial Economics, Vol. 38, No. 4 (Jun., 1990), pp. 449-463Published by: Blackwell PublishingStable URL: http://www.jstor.org/stable/2098350Accessed: 05/12/2008 06:29

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THE JOURNAL OF INDUSTRIAL ECONOMICS 0022-1821 $2.00 Volume XXXVIII June 1990 No. 4

MOBILITY BARRIERS AND PROFITABILITY OF MULTINATIONAL AND LOCAL ENTERPRISES IN

INDIAN MANUFACTURING*

NAGESH KUMAR

This paper examines the determinants of profit margins of affiliates of multinational enterprises (MNEs) and local firms (LCEs) in 43 Indian manufacturing industries to seek explanations of the superior perform- ance of the former. The empirical analysis finds support for the pro- position that MNEs and LCEs constitute different strategic groups in an industry and that the former as a group enjoys greater protection from mobility barriers. MNEs appear to enjoy persistent advantage over their local counterparts especially in knowledge (both technology and human skill) intensive industries. Residual ability differences are not statistically significant in explaining profitability differences between MNEs and LCEs.

I. INTRODUCTION

THE CONVENTIONAL market structure-conduct-performance (SCP) paradigm (a' la Bain [1956]) relates profitability to the degree of seller concentration and the height of entry barriers. The entry barriers are industry specific and are expected to protect all firms in the industry. However, systematic differences in profit margins of affiliates (or subsidiaries) of Western multinational enterprises (hereafter MNEs)l and local enterprises (LCEs) were observed in 43 (three digit) Indian manufacturing industries where they co-existed. Average profit margins of MNEs in 1980-81 were higher than those of their local counterparts in all but eight of the 43 industries (see Appendix for the details of coverage of the sample). For the overall sample, the profit margin of MNEs was 9.6 per cent compared to 5 per cent for LCEs and the difference was statistically significant in terms of Wilcoxon's Paired Match Test. Previous work has shown that this difference persists even when other variables distinguishing MNEs from LCEs, such as firm size, growth, R & D

intensity, degree of vertical integration, and financial characteristics, were

* This paper is based on a part of the author's doctoral dissertation submitted to the Delhi School of Economics, Delhi. I am indebted to N. S. Siddharthan, K. L. Krishna, V. R. Panchamukhi, Pulin Nayak, and two anonymous referees of this journal for their comments. The author alone is responsible for the remaining errors and the views expressed.

' By MNEs in this paper, we refer to those Indian affiliates of Western multinational enterprises in which they retain a controlling interest. A rule of thumb of at least 25 per cent of foreign equity ownership has been used to identify such affiliates in tune with Reserve Bank of India's definition of Foreign Controlled Rupee Company.

449

450 NAGESH KUMAR

controlled for in a multivariate (discriminant analysis) context.2 Because of their high profitability MNEs accounted for 36.5 per cent of the profits of large private companies in India compared to their 24.4 per cent share of sales in 1980-81 (Kumar [1988]).

What explains such profitability differences in firms grouped on the basis of nationality of control? One possible source could be the probably superior ability or entrepreneurship of MNEs. Another possibility is that MNEs and LCEs are constituents of different 'strategic groups' of the type discussed by Caves and Porter [1977]. If the latter is the case then entry barriers may not protect MNEs and LCEs equally and the differential protection enjoyed by them may explain the differences in performance.

This paper analyses the determinants of profit margins of MNEs and LCEs to examine what explains the superior performance of the former. The plan of the paper is as follows: section II formulates testable hypotheses by examining the relevance of different theoretical paradigms for explaining intra-industry profitability differences in the present context. Section III presents the empirical results, and section IV summarises the findings.

II. INTRA-INDUSTRY PROFITABILITY DIFFERENCES: HYPOTHESES

11(i). The theory

As observed above, the original SCP paradigm provided no explanation of intra-industry profitability differences. Subsequent empirical studies attempted to explain inter-firm differences in profitability in terms of their market share and/or size (Shepherd [1972]; Gale [1972]). Mancke [1974] questioned the convention of drawing inferences from possible correlations between profitability, market share, firm size and growth because all these parameters are influenced by the magnitude of success of past investments. According to Demsetz [1973], superior ability or entrepreneurship is the source of inter-firm differences in profitability. This explanation may fit in the present context if MNEs demonstrate superior ability or their operations are more efficient than those of their local counterparts.

An extension of the SCP paradigm provides an explanation for sustained inter-group differences in profitability in terms of strategic heterogeneity of firms (Caves and Porter [1977]; Newman [1978]; Porter [1979]). This hypothesis recognises that there are alternative ways of doing business and that the strategy of firms in a particular industry differs in respect of variables besides scale, such as mode of competitive rivalry, degree of vertical inte- gration, geographical extent of markets served, nature of distribution

2 The exercise covered in all fifteen discriminating characteristics. The step-wise discriminant analysis selected these five (plus price-cost margins) to be significant discriminants. See Kumar [1990], Chapter 4, for details.

MOBILITY BARRIERS AND PROFITABILITY OF MULTINATIONALS 451

channels employed, breadth of product line, etc. (Porter [1979; Oster [1982]). An industry, therefore, is composed of groups of firms, and firms in a group are similar to each other in terms of competitive strategy. One implication of the segmentation of industry into strategic groups is that entry barriers are partly specific to the strategic groups and partly to the industry (Porter [1979]). The entry barriers not only impede fresh entry to the industry but also restrict inter-strategic group mobility of the existing firms, and hence are more generally referred to as 'mobility barriers'. Thus, firms in a particular strategic group may not only enjoy protection from new entrants to the industry but also from existing firms belonging to other strategic groups in the same industry. The mobility barriers could be a source of persistent advantage and hence might explain higher profit margins enjoyed by some firms in an industry. It is possible that MNEs and LCEs in Indian industries constitute different strategic groups and that explains the profitability differences.

11(ii). MNEs and LCEs as two strategic groups

The strategic differences between firms are, among other factors, reflections of their tangible and intangible assets (Porter [1979]). In these respects, MNEs clearly stand out as being very different from their local rivals. Being part of established global enterprises, MNEs enjoy ownership of intangible assets lending them special advantages over purely national firms, such as brand goodwill, proprietary technology, captive access to parent's research laboratories, reservoirs of organisational and managerial skills, and inter- national marketing and information networks. Besides, the centralised decision making aimed at global optimisation of resources/opportunities in the case of MNEs could also lead to strategic differences. These differences are reflected in terms of their significantly larger scales of operation, tendency to employ qualitatively superior manpower, higher degree of vertical integration and higher level of liquidity compared to their local counterparts observed in Indian manufacturing (Kumar [1990] Chapter 4). Caves et al. [1980] have found support for the hypothesis of strategic differences between MNEs and local firms in Canadian manufacturing industries. Thus there appears to be a reasonable case for treating MNEs as belonging to a different strategic group than their local counterparts in respective industries.

II(iii). Hypotheses

The proposition that differential protection enjoyed from entry or mobility barriers is the source of higher profitability of MNEs can be tested by analysing the determinants of profitability in the two groups of firms. If entry barriers protect MNEs and local firms differently, the relationship between

452 NAGESH KUMAR

profitability and market structural variables will be different for the two groups. In what follows we specify the profit functions of MNEs and LCEs which will then be estimated. In addition to the differential protection from entry barriers, a part of the higher profit margins of MNEs may be due to their superior ability. That is, other things being the same, MNEs still earn higher profits. The influence of superior ability, if any, can be detected by examining the intercept terms of the respective profit functions.

If PCMM and PCML represent, respectively, average profit margins for MNEs and LCEs, we could write their profit functions as

(1) PCMM = al+ blX + clZ

(2) PCML = a2+ b2X + c2Z

where X is a vector of exogenous variables capturing the strategic group specific entry barriers which are expected to protect MNEs and LCEs differently; and Z is the vector of industry specific factors that affect profita- bility of the two groups of firms similarly. Hence, as per our hypothesis

a, 0 a2: if there is an ability differential between MNEs and LCEs, and,

b, # b2: if the entry or mobility barriers protect MNEs and LCEs differently.

There is no theoretical reason to expect differences between cl and c2.

II(iv). Explanatory variables and predictions

In what follows we attempt to identify variables capturing the different elements of structure that determine PCM. Following Bain [1956], Caves [1964] and the subsequent empirical literature, and in view of the availability of statistics for India, the following variables are identified.

(a) Entry Barriers: Entry barriers give to the existing firms an absolute cost advantage over the new entrants. Here five sources of entry barriers are identified as follows:

(i) Advertisement intensity (ADS) to capture the extent of product differentiation and goodwill. Product differentiation through advertisement is effective mainly in the case of consumer goods industries. This heterogeneity is controlled for through use of a slope dummy variable ADCON, following the common practice (Caves, et al. [1980]);

(ii) Technology Intensity (TECH) to capture intensity of R & D and licensing (process or product technology) inputs;

(iii) Skill Intensity (SKIL) capturing the intensity of the industry in organ- isational, managerial and technical skills;

MOBILITY BARRIERS AND PROFITABILITY OF MULTINATIONALS 453

(iv) Value added to sales ratio (VAS) to capture the length of production process or the degree of vertical integration necessary for running business in an industry; and

(v) Average Capital Requirements (AKR) to proxy high initial capital requirements for setting up an average (in the absence of information on minimum efficient size) plant.

(b) Four firm concentration ratio (CR4) to proxy the degree of seller concentration;

(c) Growth rate of industry sales (GROW) to proxy for the rate of growth of industry demand;

(d) Average Firm Size (SIZEM and SIZEL respectively) to control for possible effect of differential firm size on profitability;

(e) Effective rates of protection (ERP) to capture the protection from external competition, following Hitiris [1978] and Katrak [1980]; and

(f) Capital Output ratio (COR) to control for the opportunity cost of capital (as our dependent variable is the price-cost margin and not the rate of return).

All these variables, except SIZE, are expected to favourably affect the profitability of firms. The SIZE and profitability relationship is determined by two counteracting influences. Large firms may be able to reap scale economies in production, advertising, marketing, and R & D. On the other hand a too large organisation could suffer from scale diseconomies and X- inefficiency. Hence, the relationship will depend upon the net outcome of these influences. In the light of the strategic groups hypothesis, some of the entry barriers are posited to influence the profitability of the two groups of firms differently.

II(v). Diferential protection of MNEs and LCEs

Of the five sources of entry barriers identified above, three viz. ADS, TECH, SKIL are expected to protect MNEs and LCEs differently and hence act as mobility barriers. In view of their possession of brand names enjoying consumer loyalty, MNEs can be expected to pursue competitive strategies based on non-price competition through product differentiation. A new entrant, or even an existing local firm, will need to undertake substantial advertising to match the brand goodwill enjoyed by MNEs cultivated through the past and current advertisements by them and their associates in India and elsewhere. MNEs, therefore, are expected to enjoy protection from the product differentiation entry barrier. Hence a positive and significant relationship between PCMM and ADS is predicted. The relationship between PCML and ADS, however, is not so clear. This is because among LCEs there could be firms also pursuing strategies dominated by product differentiation (e.g. the larger ones or those affiliated with local conglomerate business

454 NAGESH KUMAR

houses), while there may be others concentrating on price-competition. The product differentiation mobility barrier may create an umbrella for local firms as argued by Porter [1979] in his leader-follower-firms analogy. The net effect of ADS on PCML may, therefore, depend upon intra-strategic group structure and on the viability of non-advertisement intensive strategies (Caves and Pugel [1980]). Hence, no precise prediction regarding the relationship between the advertising intensity and PCML can be made.

MNEs enjoy captive access to the laboratories of the global enterprise. Local firms with no such captive sources will have to either set up in-house research facilities to get technological inputs or depend continuously on external sources (mainly foreign, in developing countries like India). Otherwise firms run the risk of facing technological obsolescence. The inter- national technology markets are characterised by imperfections. Therefore, technology intensity (TECH) is likely to prove to be a formidable entry and mobility barrier protecting only MNEs.

Similarly, MNEs enjoy captive access to the reservoir of skills cultivated through their experience of operating similar plants in different countries. A local firm must be prepared to pay high salaries to attract and retain specialised and experienced personnel. Therefore, skill intensity (SKIL) is also likely to act as a potent mobility barrier protecting only MNEs.

Thus, ADS, TECH and SKIL are predicted to affect the profit margins of MNEs (viz. PCMM) positively. Their influence on PCML is expected to be different if MNEs and LCEs indeed belong to different strategic groups. In terms of the notation of equations (1) and (2) above, variables ADS, TECH and SKIL belong to vector X; variables VAS, AKR, CR4, GROW, SIZEi, ERP and COR are elements of vector Z. Equations (1) and (2) can be written as:

(3) PCMM = a, +b11ADS+bl2TECH+bl3SKIL+c11VAS +Cl2AKR + Cl3CR4 + C14GROW + cl5SIZEM +C16ERP+c17COR

(4) PCML = a2 + b2lADS+ b22TECH+ b23SKIL+ c21 VAS + C22AKR + c23CR4 + C24GROW+ C25SIZEL + c26ERP + c27COR

In the empirical analysis, a test of heterogeneity of intercepts and slopes of estimated profit functions of MNEs and LCEs will be conducted to examine whether intergroup differences in ability and/or differential protection by mobility barriers do explain profitability differences.

III. EMPIRICAL ANALYSIS

To test the hypotheses formulated above, equations (3) and (4) are fitted for a sample of 43 Indian manufacturing industries. The central hypothesis to be

MOBILITY BARRIERS AND PROFITABILITY OF MULTINATIONALS 455

TABLE I

UNRESTRICTED PROFIT FUNCTIONS OF MULTINATIONAL AND LOCAL FIRMS

Dependent Variables

PCMM PCML

Independent Variables 1 2 3 4

1. ADS 0.0016 0.015 -0.189 -0.181 (0.041) (0.376) (0.882) (0.875)

2. ADCON 0.070 0.139 1.467 1.250 (0.307) (0.545) (1.226) (1.004)

3. TECH 0.030c 0.038b -0.070 -0.062 (1.967) (2.432) (0.790) (0.750)

4. SKILl 0.577c 1.092 (1.879) (0.719)

5. SKIL2 0.648a 0.574 (2.933) (0.574)

6. VAS 0.628c 0.623c 4.587b 4.648b (1.962) (1.806) (2.413) (2.497)

7. AKR 0.146 0.170 - 1.848a - 1.734a (1.228) (1.323) (2.648) (2.762)

8. SIZEi - 0.268a -0.234a 2.945a 2.838a (2.672) (2.202) (4.284) (4.428)

9. Intercept 2.680 1.812 -2.335 -4.664 R - 2 0.588 0.534 0.437 0.442 F 7.138a 5.727a 3.88a 3.957a Sum of Squared Residuals 5.789 6.552 177.609 176.098 N 43 43 43 43

Note: Figures in parentheses are t-values. Superscripts indicate levels of significance as follows:

1 per cent; b 5 per cent; and c 10 per cent (two-tailed test).

tested here is that certain entry barriers or industry characteristics affect the profit margins of the two groups of firms differently. Hence, all the variables, except for SIZE, were measured at thcB industry level. This enables us to test the differential protection hypothesis and is consistent with the procedure adopted by Porter [1979]. The average firm size has been measured for the two groups separately (viz. SIZEM and SIZEL respectively).

Definitions of variables and data sources are given in the Appendix. The regressions are fitted in both original form as well on the logarithmic transformations of data. For the reason of goodness of fit, only results pertaining to logarithmic transformation are presented.3

The estimated regression equations explaining industry variation in PCMM and PCML are presented in Table I. As two alternative proxies of

3This, however, necessitated adding trivial values to a few observations having zero or negative values. Our results are not sensitive to these additions.

456 NAGESH KUMAR

SKIL are used, two versions of each equation are presented. Since variables CR4, GROW, COR and ERP were significant for neither PCMM nor PCML, they were excluded from the equations presented in the Table. CR4 and GROW have also been insignificant in a number of previous studies such as Comanor and Wilson [1974], and Siddharthan and Dasgupta [1983]. Another explanation for the insignificance of CR4 and ERP might be that their positive effect on profits is cancelled by the operational inefficiency resulting from the lack of competition.

From Table I the intercept and slope coefficients for a number of variables appear to be quite different for the two groups of firms. Howeverl these differences need to be evaluated for their statistical significance. We first analyse the performance of individual variables in explaining the profitability of the two groups of firms and then conduct tests of heterogeneity of these profit functions.

III(i). Mobility barriers

The coefficient of advertisement intensity barrier is significant in neither case. One possible explanation of this finding can be that in a country like India where the government policy has restricted both internal as well as external competition and where firms, particularly up to 1980 (which, in fact, is our reference period) enjoyed a seller's market, advertising does not have the role in influencing profit margins that it has in more competitive settings in industrialised countries. It might also indicate the viability of non-advertising intensive strategies that has been noted in Canada's case by Caves and Pugel [1980]. Also the measurement of advertisement intensity has well known limitations in reflecting either the economies of scale in advertisement (Comanor and Wilson [1974]), or capitalised value of past advertisement expenditures.

TECH, as well as SKILl and SKIL2 (the alternative proxies of industry's intensity in human skills), are consistently significant with positive sign in explaining variation in PCMM. In the PCML equations, however, they are not significant (and TECH has a negative sign). This finding suggests that knowledge (skill and technology) intensity entry barriers protect only MNEs from competition by both new entrants and existing local firms. The know- ledge intensive industries are usually producer goods industries. Market transactions of products of these industries get influenced by not only the technical specification of the individual product concerned but also other factors such as width of the product range offered by the particular supplier, his reputation and overall technological strength etc. MNEs represent their respective global enterprises and their technological competence and experience the world over. Most MNE affiliates in India, particularly in the early post-Independence period, were set up in response to the import- substitution drive (Kumar [1987]). Most of them had been serving the Indian

MOBILITY BARRIERS AND PROFITABILITY OF MULTINATIONALS 457

market through exports before starting local production. Hence, they inherited a built up clientele and goodwill. In comparison, local firms in the business, offering even equally good products based on technology obtained on licensing or on their own R & D, suffer from several disadvantages. They do not enjoy a ready market acceptance and must develop markets from scratch. Being new to business, the range of the products/associated services offered by them is unlikely to be as wide as that of MNEs. It appears, therefore, that MNEs and LCEs serve different segments of markets. MNEs might be serving the top-end consisting of discriminating buyers who can accept higher prices while LCEs concentrate on the price competitive lower end.

II(ii). Other variables

VAS, the proxy of degree of vertical integration, has a positive and significant coefficient in explaining the variation of both PCMM and PCML. As an industry specific entry barrier, the length of production process gives an edge to all existing firms-multinational or local-over their potential rivals and hence has a favourable effect on their profit margins. Elsewhere, we have found evidence of a significantly higher degree of vertical integration of operations of MNEs than their local counterparts in Indian manufacturing even after controlling for other factors (Kumar [1990], chapter 4). This may explain a part of the higher profit margins of MNEs.

The performance of AKR, which is never significant with the hypothesised positive sign (even in the absence of SIZE with which it is collinear), suggests that a large capital requirement is no more an effective entry barrier in the Indian case. This may be due to easy availability of long term capital from public financial institutions and the development of capital markets in the country. In the case of local firms, AKR is in fact significant with a negative sign indicating their disadvantage in large capital requiring industries. This finding needs an explanation which seems to be in the rampant under- utilisation of capacities that characterises the Indian industries.4

The firm size variable is significant in both the cases, but with different signs. For profit margins of MNEs, it has a negative sign and a positive sign in the case of PCML. This result has to be interpreted in the light of evidence on relative sizes reported by us elsewhere (Kumar [1990], chapter 4). MNEs had been found to be of considerably larger size on average than their local counterparts. The relationship between firm size and profitability has been hypothesised to be of inverted-U shape i.e. profitability rises with size to a certain extent and declines afterwards when X-inefficiencies start operating. It appears that MNEs are in the second half of the inverted-U because of their larger size while the local firms are still in the first half. Connor and Mueller

4 See DGTD [1984], for recent evidence on underutilisation of capacity.

458 NAGESH KUMAR

[1982] have also reported a negative relationship in the case of affiliates of US MNEs in Mexico and Brazil.

III(iii). Tests of heterogeneity of profit functions

To examine the statistical significance of the observed heterogeneity of intercepts and slopes of the profit functions of MNEs and LCEs, we made use of Covariance Analysis. This procedure involves contrasting (using an F-Test) the residual sums of squares in the restricted model in which hypothetical equality of coefficients is imposed, with those of the unrestricted models where intercepts, slopes, and both are allowed to vary across MNEs and LCEs (see, for example, Johnston [1972], Chapter 6). In addition to the unrestricted profit functions of MNEs and LCEs, as presented in Table I, we needed to fit restricted profit functions. The following two profit functions (corresponding to equations (1) and (3) in Table I) were fitted on 86 obser- vations pooled across MNEs and LCEs. Equation (5) below assumes the restriction of complete similarity of the profit functions of MNEs and LCEs.

(5) PCMi = ot + JI1ADS + /2ADCON + f3 TECH + f4SKIL2

+ f5 VAS + J6AKR + /7SIZEi

Equation (6) allows intercepts for the two groups to vary by introducing an intercept dummy variable (DMNE), taking value one for MNEs and zero otherwise:

(6) PCMi = oco + #ODMNE + l1 ADS + JI2ADCON + /B3 TECH

+ IJ4SKIL2 + fl5 VAS + JI6AKR + /7SIZEi

The estimated versions of these equations are reported in Table II. The MNE dummy DMNE has a positive coefficient which is statistically sig- nificant at the 10 per cent level using a t-test. Table III summarises the covariance analysis based on results reported in Table I (equations (1) and (3)) and Table II. The F-tests suggest that differences in the intercepts of the profit functions of MNEs and LCEs are not statistically significant at the 5 per cent level (Fl). This finding, therefore, limits the role of inter-group ability differences as the source of superior profit margins of MNEs to effects captured by the independent variables (e.g. perhaps a more efficient manage- ment of capital). Differences in the slope vectors as well as the overall profit functions, however, are significant at the one per cent level of confidence (F2 and F3 respectively). At first sight, the differential slope vectors seem to uphold the proposition that MNEs and LCEs in Indian manufacturing constitute different strategic groups and enjoy differential protection from mobility barriers.

However, this conclusion is subject to an important reservation. The covariance analysis presented above indicates statistical significance of the

MOBILITY BARRIERS AND PROFITABILITY OF MULTINATIONALS 459

TABLE II RESTRICTED PROFIT FUNCTIONS OF MULTINATIONAL AND LOCAL FIRMS

Dependent Variable: PCMi

Independent Completely restricted Partially restricted Variables Model Model

1 2

1. ADS -0.0902 -0.76 (0.727) (0.680)

2. ADCON 1.523b 1.448b

(2.177) (2.094) 3. TECH 0.060 0.061

(1.280) (1.313) 4. SKIL2 -0.463 -0.454

(0.685) (0.680) 5. VAS - 1.937c - 1.775c

(1.848) (1.711) 6. AKR 0.824b 0.620a

(2.357) (1.705) 7. SIZEi 1.220a 0.970a

(4.357) (3.121) 8. DMNE - 0.784c

(1.762) 9. Intercept 2.489 2.177

R 2 0.276 0.304 F 4.257 4.213 Sum of Squared Residuals 269.78 259.330 N 86 86

Note: Figures in parentheses are t-values. Superscripts indicate levels of significance as follows:

a 1 per cent; b 5 per cent; and 1 10 per cent (two tailed test).

heterogeneity of the overall slope vectors of the profit functions of MNEs and LCEs. Which of the individual regression coefficients are significantly different is not clear from this analysis. The only way of finding it out is to fit additional models with slope dummy variables capturing differential slopes for individual explanatory variables and subsets of them for a pooled sample. An attempt of this type proved futile because of severe multicollinearity among different dummy variables that landed us in the Dummy Variable Trap. Therefore, given the data and analytical tools available for the present exercise, it is only possible to say that the slopes of profit functions of MNEs and LCEs are statistically different. It has not been possible to formally identify the specific entry barriers contributing to the observed heterogeneity of the slopes of profit functions. However, it is clear from Table I that the Z vector variables of VAS, AKR and SIZE will have made a significant contribution to the F-tests, which cannot therefore be interpreted as straight- forward tests of the strategic groups hypothesis.

460 NAGESH KUMAR

TABLE III TESTS OF HETEROGENEITY OF PROFIT FUNCTIONS (COVARIANCE ANALYSIS)

Sum of Squared Degrees of Mean Squares F-Test Model Residuals Freedom (col. 2/3) (degrees offreedom)

1 2 3 4 5

Restricted (Equation (1) SO = 269.78 78 Mo = 3.46 in Table II)

Partially Test of differential restricted Sl = 259.33 77 M1 = 3.37 intercepts: (Equation (2) Fl = M21M in Table II) = 3.10

(1,77) Incremental (differential S2 = SO-SI 1 M2 = 10.45 intercepts) = 10.45

Unrestricted Test of differential (Equations (1) S3 = 5.79 + 177.61 70 M3 = 2.62 slope Vectors: and (3) in = 183.40 F2 = M41M3 Table I) = 4.14*

(7,70) Incremental (differential S4 = Sl -S3 7 M4 = 10.85 slope vectors) = 75.93

Total S5 = S2+S4 7 M5 = 12.20 Test of Overall Incremental = 85.38 Heterogeneity:

F3 = M5/M3 = 4.65* (7,70)

* Indicates significant at 1 per cent level.

Nevertheless the performance of the explanatory variables, in terms of their statistical significance and the proportion of explained variation, differs greatly between the unrestricted and restricted profits functions (see Tables I and II). This suggests that intra-industry structure is an important aspect of industrial organisation, and needs to be taken care of by future market structure-performance studies.

IV. CONCLUSION

This paper examined the determinants of profit margins of MNEs and LCEs in 43 Indian manufacturing industries to seek explanations of the superior performance of the former. At the outset a set of hypotheses pertaining to the likely determinants was formulated. Two theoretical possibilities were considered for explaining superior profit margins of MNEs. One paradigm was that MNEs and LCEs perhaps constituted different strategic groups and that entry barriers protected them differently. Another possible explanation

MOBILITY BARRIERS AND PROFITABILITY OF MULTINATIONALS 461

lay in the probably superior ability or entrepreneurship of MNEs. The empirical analysis finds some support for the proposition that MNEs and LCEs belong to different strategic groups in an industry and that MNEs as a group are protected by entry barriers more than their local counterparts. Residual ability differences are not statistically significant in explaining the profitability difference.

MNEs are found to enjoy persistent advantages over their local counter- parts mainly in the knowledge (both technology and human skills) intensive industries. This is because in these industries the overall technological strength and reputation of an enterprise, and width of product range and associated services, play a crucial role in market transactions. Being part of global enterprises, affiliates of MNEs enjoy a formidable edge over their local counterparts in all these respects. The two groups of firms, therefore, appear to be serving different market segments, with MNEs capturing the quality conscious upper end of the market that can accept higher prices and LCEs concentrating on the price competitive lower end. These advantages of MNEs over local counterparts arise from their accumulated learning and tech- nological activities. Therefore, the higher profit margins of MNEs in technology and skill intensive industries could alternatively be interpreted to represent rents for their globally accumulated learning and experience, and returns on their past investments in R & D.

The degree of seller concentration and protection from imports accorded to the local industry are not found to be related to profitability in India's case. Perhaps the operational inefficiency resulting from the lack of competition nullifies the favourable effect which these two factors might have had on profitability. In Indian manufacturing industries the advertising intensity also does not appear to be playing the role it does in more competitive settings. Finally, the wide divergence between the restricted and unrestricted profit functions suggests that the intra-industry structure is an important aspect of industrial organisation and needs to be captured in further market structure- performance studies.

NAGESH KUMAR, ACCEPTED DECEMBER 1989

Research and Information System for the Non-Aligned and Other Developing Countries, 40-B Lodhi Estate, New Delhi-110003, India.

APPENDIX

Data and Measurement of Variables

The comparison of profit margins of MNEs and LCEs, as well as further empirical analysis, have drawn for data requirements from an unpublished data base compiled by the Reserve Bank of India. This data base includes financial statistics in respect of 1720 select non-Government, non-financial public limited companies for the years

462 NAGESH KUMAR

1976-77 to 1980-81. The sample companies accounted for 86 per cent of paid-up capital of all public limited companies in the private sector in 1979-80. Out of these 1720 companies, 1334 were in the manufacturing sector. The present study is confined to these manufacturing companies. Each one of these companies had been classified into a three digit industry on the basis of the manufacturing activity accounting for at least one half of its turnover. In all there were 62 industry classes. However, certain refinement of the industry classification was found to be necessary which yielded 54 industries. The sample for the present study included 43 of these 54 industries, leaving aside the single company industries, miscellaneous industries, and those without representation of MNEs. These industries covered 1143 companies in all, 252 of which were MNEs. Industry aggregates were generated by adding up respective values for all the companies included in the industry group (in the sample) and variables were computed as per their definitions given below. Unless otherwise indicated all the variables have been derived from the above database.

ADS: Proportion of advertisement expenditure in net industry sales, averaged over 1978-79 to 1980-81.

ADCON: ADS * DCON. AKR: Average capital employed per firm, averaged over 1978-79 to 1980-81. COR: Total capital employed as a proportion of net industry sales, averaged over

1978-79 to 1980-81. CR4: Share of top four firms in industry (sample) sales, averaged over 1978-79 to

1980-81. DCON: A dummy variable, taking value one if the industry is supplying consumer

goods (both durables and non-durables), and zero otherwise. ERP: Effective rates of protection for 1979-80 (Cordon Method). Source:

National Council of Applied Economic Research, New Delhi. GROW: Proportionate change in net industry sales over 1978-79 to 1980-8 1. PCMi: Profit before tax of ith group of firms as a proportion of their sales,

averaged over 1978-79 to 1980-81. SKILl: Proportion of non-production workers in total work force in 1978-79,

computed from the Annual Survey of Industries: Census Sector Summary Results, 1978-79, Central Statistical Organisation, Govt. of India.

SKIL2: Percentage share of earnings of employees drawing Rs.3000/- per month or more in total wages and salaries bill, averaged over 1978-79 to 1980-8 1.

TECH: Proportion of in-house R & D expenditure and remittances on account of royalty and technical fees in net sales, averaged over 1978-79 to 1980-81.

VAS: Proportion of value-added in net sales in 1980-8 1. SIZEi: Average net sales per firm in the ith group.

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