Are multinationality and diversification complementary or substitute strategies?

International Journal of Industrial Organization 19 (2001) 1315–1346 www.elsevier.com / locate / econbase

Are multinationality and diversification complementary or substitute strategies? An empirical analysis on European leading firms Stephen W. Davies a , *, Laura Rondi b , Alessandro Sembenelli b,c a School of Economic and Social Studies, University of East Anglia, Norwich NR4 7 TJ, UK CERIS-CNR, Economic Research Institute on Firms and Growth, Via Avogadro 8, 10121 Torino, Italy c Dipartimento ‘‘ G. Prato’’, Universita’ di Torino, Corso Unione Sovietica, 218 bis, 10134 Torino, Italy

b

Received 1 August 1997; received in revised form 27 September 1999; accepted 8 February 2000

Abstract This paper models the multinationality and diversification of firms jointly. It applies a new typology, distinguishing diversification at home and abroad (multinationality in primary / secondary industries), to the corporate structures of a sample of leading EU manufacturing firms. This provides the framework for a sequential stochastic model of firms’ decision making. Results suggest that multinationality and diversification are, in general, complementary strategies. In differentiated-product industries, this implies that proprietary assets are a public good within the firm. In homogeneous-product industries, however, there is some evidence of substitutability, in that the two strategies may be alternative routes for escaping constraints on growth.  2001 Elsevier Science B.V. All rights reserved. JEL classification: L1; L2 Keywords: Multinationals; Diversification; Corporate structure; Proprietary assets

* Corresponding author. Tel.: 1 44-160-359-2715; fax: 1 44-160-345-6259. E-mail address: [email protected] (S.W. Davies). 0167-7187 / 01 / $ – see front matter  2001 Elsevier Science B.V. All rights reserved. PII: S0167-7187( 00 )00063-1

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1. Introduction Prevailing explanations of firm diversification and multinationality display striking similarities, both pointing to proprietary assets and firm size / growth, as the driving causal forces. Yet, in spite of this commonality, the empirical literatures have remained largely independent. This paper examines these two dimensions of corporate structure jointly for a sample of 277 leading manufacturing firms in the European Union. On a descriptive level, the objective is to provide a concise, but informative, picture of these features of the EU’s leading firms. To do this, we introduce a new typology for describing corporate structure. Analytically, we address two main questions. First, ‘are diversification and multinationality substitute, or complementary, strategies?’ Second, ‘what are the causal underpinnings of the relationship to (firm) size, and do they differ between the two strategies?’ Following a brief summary in Section 2 of the previous literature, Section 3 introduces a typology of corporate structure which distinguishes between a firm’s foreign production in its primary and secondary industries (or, equivalently, its diversification at home and abroad). This is applied to provide the descriptive picture for this sample of leading EU firms in Section 4. Building on the insights provided, Section 5 presents a theoretical model, based on a simple formulation of the firm’s decision of whether or not to diversify and go multinational. The model is tested in Section 6 using probit / logit analysis. Section 7 concludes.

2. Brief review of the literature The conventional theoretical literatures on why firms choose to be multinational or diversified are sufficiently well known as to require only a brief rehearsal here 1 . The multinational firm is often viewed as having some proprietary (specific) asset which is commonly associated with product differentiation and / or technological know-how; and because of high transaction and agency costs, this is often best exploited in foreign markets by local production rather than by exporting or licensing (e.g. Dunning, 1981; Caves, 1996). Another pervasive theme concerns the role to firm size. Within the Industrial Organisation literature, this flows most obviously from modelling the firm’s choice on how best to service a foreign market. Local (i.e. multinational) production reduces marginal costs (by avoiding transport costs and tariffs), but only at the expense of incurring the additional fixed costs of setting up the foreign plant. It follows that multinationality is more likely the larger are the firm’s planned foreign sales, and, ceteris paribus, the larger the

1

Two recent survey papers provide succinct summaries: Markusen (1995) on multinationality, and Montgomery (1994) on diversification.

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size of the foreign market, relative to the efficient scale of production (e.g. Smith, 1987, Markusen and Venables, 1998). In another part of the literature, deriving from the theory of the firm tradition, multinationality is viewed as one route for escaping constraints on growth in the firm’s domestic market. In that case, high domestic market share is the more relevant trigger for multinationality. Within the empirical literature, Horst’s (1972) early study established a key role for size – he found that the firm’s size in its domestic market (market share) was the only significant discriminant between multinational and non-multinational firms. Caves interpreted this (Caves, 1996, p.59), as ‘‘supporting the hypothesis that the firm runs through its opportunities in the domestic market before incurring the transactions costs of going abroad’’. Subsequent studies have provided widespread empirical support for both the size and proprietary asset hypotheses, usually in the form of positive correlation and regression coefficients between various indices of multinationality and a variety of measures of firm size, advertising and R&D expenditures (the empirical literature is well surveyed by Caves, 1996, pp.7–13 and 59–60). Very similar themes are also evident in the diversification literature. Technological spillovers and exploitation of brand names and advertising goodwill in adjacent markets are cited as major reasons for the multimarket firm (e.g. Scott, 1993). The role of firm size is even more firmly entrenched in this literature (originating from Penrose, 1959), although here the emphasis is more on diversification as a strategy pursued by growth-oriented managers faced with limits to growth in their primary industry. Again, many empirical studies confirm positive statistical associations between diversification and firm size, R&D and advertising 2 . As with multinationality, size is sometimes measured in absolute terms, and sometimes as market shares – the former capturing sheer scale factors, such as economies of scope and demand externalities, whilst the latter are more obviously relevant to the constraints to growth motive. Of course, it is unsurprising that the two literatures are parallel, since multinational operations may be seen merely as geographical diversification. What is more interesting is whether a joint analysis offers any additional insights. If both diversification and multinationality are driven by the same intangible asset story, can we explain why some firms are multinational without being diversified, and vice-versa? Why do some firms diversify (go multinational) only in their country of origin (core industry), while others are also diversified (multinational) in other countries (industries)? Underpinning these questions, is the proprietary asset a ‘public good’ within the firm, or is it in finite supply? Similarly, if multinationality and diversification are both strategies associated with larger size and growth, are they seen as alternatives, or are they typically pursued simultaneously or sequentially? 2

Markides (1995) and Pearce (1993) are recent examples of cross-section firm level studies in this tradition.

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Relatively few studies have explicitly considered questions such as these: theoretical modelling is rare, and there is only a handful of empirical studies. Caves, again, (Caves, 1996, pp. 21–2 and 59–60) summarises the latter, concluding that some studies point to a short-run trade-off, but that in the longer-run, firms appear able to pursue both strategies: ‘‘studies that compare product-market and geographic (international) diversification (across) firms of varying sizes and maturities, usually find positive correlations: given time and resources, a firm can exploit opportunities for diversifying in both directions, and the sorts of proprietary assets that support foreign investment are the same ones associated with ‘related’ diversification’’. However, some studies appear to be unaware of the potential danger of imputing causality to statistical associations which may merely reflect underlying arithmetic near-identities. This problem is most acute when working with purely crosssection data, and since this is the type of data which we shall employ here, a brief elaboration is helpful. Consider first the relationship between diversification (multinationality) and the firm’s aggregate size. If firms use diversification (multinationality) to overcome limits to growth in their primary industry (home country), then this is best thought of as a route to growth–the means by which larger size is attained–and it is misleading to impute a causal interpretation, flowing from large size to diversification (multinationality.) Indeed, unless diversification (multinationality) is a perfect substitute for core industry (home country) operations, it must necessarily imply an increase in the firm’s aggregate firm size. This argument is formalised in Appendix A. Measuring diversification by Berry’s (1975) traditional Herfindahl-based D index [Eq. (A.1)], it is shown that aggregate firm size can be decomposed in product space into three component parts: (i) typical market share, (ii) the typical size of market in which it operates, and (iii) the number of equivalent industries across which it is diversified. Holding the first two constant, firm size rises proportionately with D. A similar decomposition is derived in geographic space, confirming that aggregate firm size also rises proportionately with an analogous M index [Eq. (A.2)] of multinationality across countries. To disentangle the relationship between diversification and multinationality, a distinction should be made between the firm’s aggregate diversification and its diversification within individual countries. (The relevance of this distinction can be seen by considering a firm which is a vertically integrated multinational, which locates its entire output in industry A in country 1, and its entire output in industry B in country 2. Such a firm is both multinational and diversified 3 in aggregate, but it is completely specialised within each country, and uninational in each industry). 3

Throughout this paper ‘diversified’ refers to multi-industry operations and will therefore include vertical operations.

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Making this distinction, it can be seen that acts of diversification will typically also affect the firm’s index of overall multinationality (M). This is most obvious where the firm diversifies abroad – simultaneously affecting both M and D. But even diversification at home will raise the proportion of the firm’s aggregate output produced at home, and thereby depress its aggregate multinationality. In Appendix A, it is shown that the aggregate diversification index depends not only on the firm’s (weighted) average diversification within individual countries, but also on the precise pattern of its multinationality across countries. The upshot is that care is required when exploring the nexus of firm size / multinationality / diversification. Underlying any causal relationships which may exist, there are some clear algebraic accounting identities which need to be controlled for 4 . This has not always happened in previous studies, especially those based on cross-sections and using simple measures of aggregate firm size as an explanatory variable.

3. A typology for corporate structure If indices of multinationality and diversification are jointly determined along with the firm’s aggregate size, then it is clear that some sort of disaggregation is necessary if we are to disentangle causal relationships. For the purposes of the present paper, a simple, but as far as we know novel, device is sufficient. This entails first identifying, for a given firm, its primary industry and its home country, and then distinguishing the eight broad classes of corporate structure depicted in the 2 3 2 matrices shown in Fig. 1 5 . The first three depict firms which are not both multinational and diversified: Class I Class II Class III

Specialist (i.e. non-diversified) uninational firms Specialised multinationals Diversified uninationals

The other five classes depict different types of diversified–multinational firms

Class IV

Specialised at home, uninational in the primary industry, but operating in a secondary industry abroad (e.g. a purely vertical multinational)

4 This is not to deny that some studies avoid this potential tautology by considering a time interval (i.e. investigating the impact of initial firm size on subsequent multinational expansion), e.g. Pearce (1990), or by exploring the effect of domestic size on the extent of multinationality, e.g. Swedenborg (1979). 5 It has been pointed out to us that this matrix is reminiscent of the Ansoff (1965) matrix which may be familiar to readers conversant with the corporate strategy literature. As far as we know, that matrix has never been used in empirical applications such as this.

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Fig. 1. A typology of corporate structures.

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Class V Class VI Class VII

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Multinational, but only in the primary industry, and diversified, but only in the home country Specialised at home, but multinational only in secondary industries Diversified at home and abroad, i.e. multinational in both primary and secondary industries

4. Applying the typology to the sample of leading EU firms This typology is applied to a sample of 277 leading firms in the European Union (EU) for 1987. Initially, in this section, the statistics are deliberately confined to a descriptive purpose. This helps to establish a background for the more formal disaggregated modelling of the next two sections. In addition, because the sample and the typology itself are both novel, a brief exploratory factual examination may be of some interest in its own right. The sample is drawn from a database first assembled as part of a wider study on the competitive process and structure of industries and firms in EU manufacturing (Davies et al., 1996). The database includes information, for each firm, on its sales 6 in each of up to 100 industries defined at the (NACE Rev. 0 classification) 3-digit level, across the same 11 member states (i.e. EU12, with Belgium and Luxembourg consolidated). More precisely, the sample comprises all ‘leading’ EU manufacturing firms, where a firm is defined as a ‘leader’ if it is amongst the five largest producers (at the EU level) in at least one 3-digit manufacturing industry. For any firm meeting this criterion, data have been collected on its EU sales in all industries in which it operates (including those in which it is not a leader). In turn, its total EU sales in each industry are also disaggregated into separate figures for each member state 7 . Thus, for each firm, we observe a matrix, in which x jk refers to the firm’s sales in industry j ( 5 1 . . . 100) in country k ( 5 1 . . . 11). Two important features of this database should be highlighted. First, the sample is obviously targeted towards firms which are mostly very large in absolute terms

6 Throughout, the term ‘sales’ is used as shorthand for ‘sales by country of origin’, that is, sales of goods produced in that country. Thus, apart from changes in stocks of finished products, we might equally refer to this as ‘‘production’’ in each country. Either way, this measure of size should not be confused with ‘‘sales by country of destination’’, which would also include sales in a given country sourced from production in other countries. That would give quite inappropriate measures of multinational production. 7 The main source of information was company reports, supplemented by business directories and national production censuses. Considerable care, based on the knowledge of economists from the relevant country, was taken in grouping together all firms under the same ultimate ownership (the accounts of all subsidiaries and associates in which share ownership was at least 50% were consolidated).

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– it includes nearly all of the EU’s very largest manufacturers (97 of the top 100, according to our calculations), and all the firms play a leading role within their own individual industries. This is not necessarily a drawback, so long as this property is borne in mind throughout. Second, all data are confined to sales within manufacturing and sourced from within the EU. This is both a strength and a weakness. It has the important advantage that firm structures can be compared on a completely standardised basis (i.e. the same 11 countries, the same 100 industries, and the same level of aggregation). On the other hand, it is a major limitation on the scope of the study, since it abstracts from both diversification outside manufacturing and multinationality outside the EU. Having said this, for most of the sample firms, non-manufacturing activities are relatively minor, since the criterion for inclusion in the sample is based on large size in manufacturing. The omission of operations outside the EU is probably the more telling limitation. In an attempt to constrain it, we have excluded 36 firms from the original database which are, in fact, subsidiaries of non-EU owned parents. For these firms in particular, non-EU operations are clearly of central importance to their corporate structures. Nevertheless, non-EU non-manufacturing operations are undoubtedly significant for a number of the EU-owned firms remaining in our sample, and the omission of these activities from the database means that the results in Table 1 should be viewed as describing a lower threshold to the true diversification and multinational activities of the firms. Unfortunately, the task of extending the scope outside EU manufacturing would be enormous at the level of disaggregation used here, and beyond our current research capacity. For each firm, aggregate indices of diversification and multinationality have been estimated using Berry’s D and the equivalent M index (as described above and defined in Appendix A)8 . Using these indices, firms were allocated according to the eight classes. We first note the following general features of the sample: (i) Only about one-quarter of the firms are neither diversified nor multinational 9 (Class I), 8

These indices have familiar properties: a firm specialized in a single industry scores D50, while one spreading its output equally across N industries records D 5 (N 2 1) /N, tending to unity as N becomes large. Similarly, a firm which operates in a single country records M50, while one having equal sized operations in S countries records M 5 (S 2 1) /S. 9 In allocating firms to classes, we have defined a firm as diversified (multinational) only if its D(M) value exceeds 0.095. We introduce this filter to cut out cases where there are ‘trivially small’ amounts of diversification / multinationality which may, in fact, be the result of measurement error. Company reports (our main source) are not always careful, when describing smaller subsidiaries, to define industry of production precisely, or to distinguish foreign production from merely selling operations. In spite of devoting considerable effort to data collection, we can not be sure that all such errors of classification have been removed – especially in the marginal cases. This cut-off value is applied in the interests of caution, but, in any event, it is not very exclusive: it excludes fewer than 10 firms in both cases, and 0.095 corresponds to a hypothetical firm operating in two industries (countries), of which the main industry (country) accounts for 95% of the total.

Table 1 The typology applied to leading EU firms a ( i) Frequencies of classes by firm size Class

(specialised uninational) (specialised multinational) (diversified uninational) (diversified multinational)

Mean size

Mean size

Sample means

firms

in HC-PI

(mn.ecus)

M

D

DH

D,DH

80 14 79 104

564 2253 1038 1406

570 2642 1846 3671

0.00 0.34 0.00 0.35

0.00 0.00 0.52 0.57

0.00 0.00 0.52 0.57

n.a. n.a. 0 65

1 48 1 9 45

667 1634 1875 834 1283

771 2981 4724 1849 4812

0.23 0.28 0.75 0.24 0.44

0.18 0.45 0.68 0.69 0.69

0.00 0.49 0.00 0.63 0.67

0 48 0 0 17

277

1101

2203

0.15

0.37

0.37

65

GER

FRA

UK

IT

NL b

BL

29 5 19

15 3 13

Breakdown of diversified multinational IV V VI VII VIII All Firms

( ii) Frequencies of classes by country of origin Class

Total

I II III IV V VI VII VIII Total

80 14 79 1 48 1 9 45 277

a

c

–

– 12

–

4 2 24 –

14 –

19 3 18 –

12 –

2 8 75

3 10 58

4 19 65

75 2962 1565

58 2451 1294

65 1657 878

2 1 1

– 4 1 2 1

– 6

– –

2 – –

3 49

5 11

49 1483 702

11 4434 893

SP 4

– – 12 12 1058 583

7 – – – – – – – 7 7 598 598

A firm is considered to be diversified at home only if DH .0.095; multinational in its primary industry only if MP .0.095; and diversified abroad only if its non-primary foreign operations account for at least 5% of total sales (see footnote 8). b It includes two anglo / dutch firms (Unilever and Royal Dutch Shell). c GER5Germany, FRA5France, UK5United Kingdom, IT5Italy, NL5Netherlands, SP5Spain (5) and Portugal (2), BL5Belgium / Luxembourg.

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Number of firms Firm aggregate size Firm size in HC-PI

No. with

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I II III IV–VIII

No. of

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(ii) Diversification is more common: two-thirds of firms are diversified (Classes III–VIII), while only two-fifths are multinational (II, IV–VIII), (iii) There are no obvious signs from these crude statistics that the two strategies are either substitutes or complementary. The number of firms that are both diversified and multinational (104 in IV–VIII) is almost identical to the number opting for only one of the two strategies (93 in II and III). Moreover, amongst diversified firms, there is no significant difference in the mean value of D between those which are also multinational (IV–VIII) and those which are not (III), i.e. 0.57 and 0.52 respectively. Similarly, amongst multinational firms, mean M does not differ significantly between those which are, and are not, also diversified (0.35 for IV–VIII and 0.34 for II). However, these preliminary statistics 10 have so far ignored differences within the set of diversified multinationals. Focusing attention on the lower part of Table 1(i), three more points are noteworthy: (iv) Only two of the diversified-multinational classes, V and VIII, are significantly populated in this particular sample 11 . There are only 11 firms in the remaining three classes IV, VI and VII, and inspection of these firms suggests that, for some at least, there may be classification ambiguities 12 . (v) The typology sheds further light on the ‘‘accounting relationship’’ between multinationality and diversification. One way of quantifying the ‘‘influence’’ of multinationality on diversification (or vice versa) is to examine how multinationality affects the firm’s aggregate diversification (D) relative to diversification in its home country (DH ). In the simple 2 3 2 case, it is easily shown arithmetically that multinationality must reduce D below DH , if confined to a primary industry (Class V), but increase it if confined to a secondary industry (IV, VI, VII); the effect may go either way when multinationality occurs in both primary and secondary industries (VIII) – depending on the relative magnitudes of the four cells in the matrix. In fact, in this particular sample, the deflationary effect

10

One other descriptive statistic of some interest is that there is a positive correlation (r50.32) between D and M. We also find the conventional positive statistical associations between firm size and multinationality (0.28) and diversification (0.27). 11 This is not to deny that, say, vertical MNEs might be a more common occurrence were we to widen our canvas to include operations outside the EU, notably the developing world. 12 Classes IV and VI each include a single Belgian firm, and since both firms have significant foreign operations in immediately adjacent member states, the notion of a home country is less meaningful in these cases. The nine firms in Class VII are very heterogeneous and some could easily switch to other mainstream Classes with only marginal changes in structure. For instance, there are two conglomerates with large non-manufacturing operations, and another is a UK firm with traditionally strong interests in Ireland (Guinness): for these three, arguably, the classification scheme is too simplistic. Three of the other firms have only small foreign sales (5–9%), and are near to being Class III.

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dominates in terms of numbers of firms – 65 of the 104 diversified–multinationals have DH . D (see the last columns of the table). This reflects the balance of two counteracting forces: Class V is far more frequent than Classes IV, VI and VII, but, within Class VIII, more often than not, multinationality tends to increase aggregate diversification. However, when judged by sample means, the two effects exactly balance: mean D and DH are both 0.57 for the 104 firms, and this is because many Class V firms are only moderately multinational in their primary industry. We conclude that, although there are purely arithmetic forces at work which might give an impression of substitute or complementary strategies, in this particular sample, they are largely offsetting. (vi) Abstracting from the three sparsely populated classes (IV, VI and VII), the mean size of firm increases as we move up through the 5 remaining classes: both class II and class III firms are larger, on average, than class I, class V are larger than either class II or class III, and class VIII are larger on average than class VIII. This is consistent with a stylised dynamic story, in which the growing firm first either diversifies at home (moving from I to III), or goes multinational in its primary industry (I to II), then moves to both diversification at home and multinationality in primary industry (II or III to V), before finally diversifying abroad (V to VIII). Each step increases the firm’s aggregate size, and this gives rise to positive correlations between M, D and aggregate firm size. (vii) Finally, part (ii) to the Table disaggregates according to the firms’ home countries. As can be seen, all but 30 of the sample firms originate from the four largest member states (Germany, France, UK and Italy). Amongst these countries, there is broad similarity – both in the distribution of firms across classes and in the ratio of firm size in home country primary industry (HC-PI) to aggregate firm size (roughly 50%). However, the UK firms have a greater tendency towards Classes III and VIII, with very few specialised Class I firms. Amongst the smaller member states, it is noticeable that all seven Spanish firms are specialised uninationals, while Dutch firms (notably, Unilever, Shell, Philips) are more likely to be Class VIII. In the econometrics which follow, we investigate whether there is a discernible ‘country effect’, once industry size is controlled for. To anticipate, there is little evidence of such an effect (see also footnote 16).

5. A simple model Armed with this descriptive background, we now turn to a formal theoretical model which is capable of generating testable predictions for a cross-section database as just described. In order to side-step the arithmetic accounting relationships between aggregate firm size and D and M, the model makes a crucial distinction between diversification at home and abroad. Whilst the solely crosssection nature of the data means there is little scope for explicitly modelling the dynamics of decision-making, we are able to introduce sequentiality in a

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circumspect way. We know from the previous section that certain types of corporate structure (Classes IV, VI and VII) occur only rarely in practice. This suggests that, without too much loss of generality, we can assume that firms do not choose to diversify abroad before diversifying at home, or go multinational in secondary, before primary, industries. This considerably simplifies the sequence of decisions, which are modelled as follows. We first describe the firm’s two decisions on whether to diversify at home and whether to go multinational in the primary industry. Initially these are presented as independent decisions, but we then consider the nature of their independence. Finally, we assume that foreign diversification can only occur when and if the firm is already both multinational in its primary industry, and diversified at home.

5.1. Home diversification and primary multinationality Consider first the firm’s decision on whether or not to diversify at home. Suppose initially that it chooses to diversify once its primary industry market share exceeds some threshold value, say l%. This would be consistent, for example, with a Penrose view of diversification as a strategy designed to escape limits to further growth in the primary industry. This can be translated into a cross-section setting as follows. Denote the firm’s size in its home primary industry by SPH and the total size of that industry by ISPH , then the probability that a firm will be observed to be diversified at home is given by: PhDH . 0j 5 PhSPH . l(ISPH )j

(1)

If l is constant across firms, this probability curve would be a simple step function (Fig. 2). More generally, however, threshold market share may vary between firms, depending on various firm-specific factors, such as the motives of managers. Furthermore, as discussed earlier, the size effect need not be confined exclusively to market shares. If the firm’s absolute size in the market is important, for example, in determining the gains from diversification due to economies of scope and demand spillovers, then a more general form is more appropriate: PhDH . 0j 5 PhSPH . SD j

(2)

where SD denotes some critical absolute size in the market, which will vary across firms according to a vector of firm-level characteristics, including industry size: SD 5 (IS) bPH ? e

(3)

where e is defined as a random variable, representing all other non-size influences. The magnitude of b reflects the relative strength of market share, as opposed to absolute size: if the decision depends only on market share, then b 51, whilst b 50 if only absolute size matters. We shall assume that the logarithm of e is normally distributed with mean mD and variance s 2D . Although there is no

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Fig. 2. Probability of multinationality / diversification as a function of firm size.

theoretical necessity for introducing this particular distributional assumption at this stage, the model will be tested below using probit analysis, which implies lognormality. In any event, the lognormal is a very plausible candidate: critical size is a non-negative variate, and if it is the product of a large number of independent influences, the multiplicative form of the central limit theorem offers a reasonable genesis for the lognormal. In this more general form, the step function generalises to the dotted sigmoid curve shown in Fig. 2, which is merely the cumulated SD (lognormal) distribution. To see the implications, note first that because e is lognormal, so too is SD . Using the notation of Aitchison and Brown (1957), if e is Lh mD , s D2 j, then SD is Lh mD 1 b ln (IS) PH , s D2 j

(4)

and PhDH . 0j 5 L hln SPH u ( mD 1 b ln (IS) PH ), s 2D j 5 N h(ln SPH 2 b ln (IS) PH 2 mD ) /sD u0, 1j

(5)

It follows that there is a linear relation between the normal equivalent deviate (probit) of the probability and ln SPH and ln ISPH , as in a standard probit model. Thus, the probability will rise according to a cumulative normal curve when plotted against the logarithm of SPH . The exact shape of the curve depends on the magnitudes of (IS) PH and the parameters, mD and s 2D : it will be higher the smaller are mD and (IS) PH (for b .0), and shallower, the larger is s 2D . Small mD implies

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that threshold market share is low and that other factors are conducive to diversification, large s 2D implies that the dominant influences on diversification are non-size related. Conversely, where other factors have only marginal influence, the variance is low, and the curve is steep. The decision whether to go multinational in primary industry is modelled similarly: PhMP . 0j 5 PhSPH . SM j

(6)

where SM is another ‘critical’ size, defined by: b

SM 5 (IS) PH ? e

(7)

2 where e is also lognormally distributed, with mean mm and variance s m . Again, the relative strength of other (as yet unspecified) determinants of multinationality 2 will determine the magnitudes of mm and s m . Using identical algebra to (4)–(6), one can derive an analogous linear relation between the probit of the probability of multinationality and the logarithms of firm and industry size, in which the coefficients are determined by b and the parameters of the critical size distribution. In this case, however, the role of size requires further deliberation. As explained in the earlier literature survey, the same arguments on the firm’s absolute size in the market, and its market share have been applied to multinationality as to diversification. In addition, however, the firm’s choice between multinationality and exporting points also to the relevance of the size of the foreign market. If so, we should expect the firm’s critical size to be inversely related to the size of the foreign market (relative to minimum efficient scale). However, to anticipate a data issue, in this particular sample, we are unable to satisfactorily distinguish between the size of the foreign and domestic industries. This is because, within the four largest member states, most industries are of broadly similar size. This means that, when comparing, across firms and industries, home and foreign industry size are very strongly correlated 13 , especially amongst firms from those four largest countries. In effect, severe multicollinearity will make it impracticable to disentangle the two separate effects. For this reason, we shall include only one measure of industry size in the econometrics below, accepting that it will capture the net result of two potentially opposite effects. The discussion has been couched so far for a within-industry context. When applied, as below, to a pooled sample of firms across industries, inter-industry determinants also become important, and all parameters will now reflect vectors of industry-level, as well as firm-level variables. Crucially, for present purposes, firms’ proprietary assets will be one such variable. Where diversification (mul-

13

The simple correlation coefficient between home and EU wide (excluding home) industry size relative to setup costs in the sample below is 0.94.

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tinationality) is driven more by proprietary assets than size factors, the mean and variance of critical size will be lower and (probably) higher respectively. Thus, probability curves will be higher and (probably) flatter in industries characterised by these assets.

5.2. Interdependence between the two decisions So far, these two decisions have been modelled independently of each other, i.e. ignoring the possibility that the two strategies may be complementary or substitutes. In principle, this might arise in two ways. First, there may be a causal effect. This happens where the nature of the diversification (multinational) decision is changed if the firm is already multinational (diversified). For example, if the firm is already multinational, a large domestic primary industry market share may be less of a trigger for diversification, since expansion abroad is now another option. Similarly, if the proprietary asset is in fixed supply within the firm, prior multinationality will reduce the gains to be had from subsequent diversification. Alternatively, the inter-relationship may not be directly causal, it may merely be that a firm has similar ‘‘tastes’’ for multinationality and diversification. For example, managers with preferences for empire building and growth maximising may see both strategies as potential (not mutually exclusive) avenues for securing these objectives. Similarly (and perhaps more interestingly), the firm may possess a proprietary asset which can be exploited equally in both geographic and product spaces – the public good argument. Of course, in a time series application, one might hope to distinguish between the these hypotheses, but, given our database, there is little scope for identifying the historical sequence of decisions for individual firms. Therefore, the conclusion we carry forward is more limited: the two critical sizes, SD and SM , will be positively correlated if multinationality and diversification are complements, but negatively related if they are substitutes 14 .

5.3. Foreign diversification Finally, foreign diversification (secondary multinationality) is modelled quite simply in terms of the conditional probability that a firm will be diversified abroad, given that it is already diversified at home and multinational in its primary industry. In this case, however, (IS) PH might not be expected to play a prominent role since a high home primary industry market share is unlikely to constitute an important constraint on growth for a firm already diversified at home and multinational in its primary industry. Similarly, SPH is no longer an appropriate

14

In fact, as will be seen, there is some scope, empirically, for synthesising the inter-temporal dimension even without time series data.

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measure of firm size. Instead, we posit that the conditional probability is given by the probability that SP&H , the firm’ s total output in its primary industry and its home country, is greater than some critical value. The latter is again assumed to be a random variable, reflecting a variety of unspecified determinants, including the existence of firm-specific proprietary assets.

6. Econometric results The results of testing the model econometrically on the current sample 15 are reported as four steps in Tables 2–5. We start with the basic model, first examining home diversification and primary multinationality in terms of just size. This is then extended to include the effects of proprietary assets and by exploring the interrelationship between the two strategies. Finally, Section 6.4 turns to foreign diversification (secondary multinationality).

6.1. Basic model: effects of size on home diversification and primary multinationality Following Eq. (5), the empirical counterpart to the theoretical model is a probit model, in which the probability of being diversified (multinational) is a linear function of the logarithms of SPH and ISPH – respectively, the production by the firm in its primary industry in its home country, and the total size of that industry’s production. In order to normalise for differences in the minimum efficient scale Table 2 Bivariate probit analysis of the probability of diversification / multinationality: basic model a,b

PhDH . 0j

PhMP . 0j

Variable

Coefficient

Std. Error

Const. SPH ISPH Const. SPH ISPH RHO(1,2) LOG-L n. obs.

20.541 0.249 20.107 21.921 0.279 20.002 0.541 2307.0 266

(0.482) (0.057) (0.042) (0.489) (0.063) (0.040) (0.085)

*** ** *** *** ***

a

Significance levels: * 10%, ** 5%, *** 1%. Test statistics for Univariate Probit Models: Eq. (1): Log-L5 2153.3, Log-L0 5 2172.8, x 2 [2]539.0; Eq. (2): Log-L5 2167.7, Log-L0 5 2179.3, x 2 [2]523.1. b

15

Firms in the anomalous classes (IV, VI and VII) are excluded throughout this section since, by assumption, the theoretical model rules out such structures.

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Table 3 Bivariate probit analysis of the probability of diversification / multinationality extended model with product differentiation dummy a,b,c

PhDH . 0j

PhMP . 0j

Variable

Coefficient

Const. SPH ISPH Const.?DIFF SPH ?DIFF ISPH ?DIFF Const. SPH ISPH Const.?DIFF SPH ?DIFF ISPH ?DIFF RHO (1,2) LOG-L n. obs.

( I) 21.033 0.380 20.146 0.272 20.219 0.230 22.239 0.293 0.009 0.930 20.111 0.053 0.524 2297.3 266

Std. Error

(0.681) (0.101) (0.050) (1.093) (0.136) (0.107) (0.746) (0.109) (0.048) (1.112) (0.143) (0.101) (0.090)

Coefficient

*** *** * ** *** ***

***

( II) 20.885 0.354 20.147 – 20.170 0.222 21.903 0.229 0.015 0.488 – – 0.523 2298.1 266

Std. Error

(0.511) (0.079) (0.046) – (0.061) (0.073) (0.504) (0.067) (0.042) (0.175) – – (0.089)

* *** *** *** *** *** *** ***

***

a

Significance levels: * 10%, ** 5%, *** 1%. Test statistics for Univariate Probit Models in (I). Eq. (1): Log-L5 2147.1, Log-L0 5 2172.8, x 2 [5]551.4; Eq. (2): Log-L5 2162.9, Log-L0 5 2179.3, x 2 [5]532.8. c Test statistics for Univariate Probit Models in (II). Eq. (1): Log-L5 2147.1, Log-L0 5 2172.8, x 2 [4]551.3; Eq. (2): Log-L5 2163.6, Log-L0 5 2179.3, x 2 [3]531.4. b

across industries, ISPH is deflated by a variable reflecting setup costs. (Appendix B provides more detail on measurement and sources). The equation in Table 2 applies a bivariate probit model, with two zero-one dependent variables, indicating whether or not the firm is diversified at home and Table 4 Multinomial logit analysis of the probability of diversification / multinationality a Class II

Class III

Class V and VIII

Variable

Coefficient

Std. Error

Coefficient

Std. Error

Coefficient

Std. Error

Const. SPH ISPH Const.?DIFF SPH ?DIFF ISPH ?DIFF LOG-L LOG-L0 x 2 [15] n. obs.

25.088 0.740 20.117 0.616 20.416 0.367 2292.7 2331.0 76.6 266

(2.526) ** (0.372) ** (0.168) (4.002) (0.512) (0.363)

21.780 0.718 20.366 20.219 20.514 0.556

(1.366) (0.212) *** (0.103) *** (2.282) (0.302) * (0.231) **

24.215 0.948 20.216 1.689 20.546 0.407

(1.535) *** (0.233) *** (0.105) ** (2.240) (0.301) * (0.210) **

a

Significance levels: * 10%, ** 5%, *** 1%. Degrees of freedom in squared brackets.

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Table 5 Wald tests on equality of coefficients in Table 4 a Null hypothesis

Class II5Class III Class II5Class V/ VIII Class III5Class V/ VIII a

Non-diff.

Diff.

x2

[d.f.]

x2

[d.f.]

23.8*** 15.7*** 5.2

[3] [3] [3]

9.8*** 26.4*** 11.4***

[3] [3] [3]

Significance levels: * 10%, ** 5%, *** 1%.

multinational in primary industry, regressed against the logarithms of SPH and ISPH . The equations are estimated without restrictions on the coefficients of the two size variables, to allow for the possibility that there is an absolute firm size, as well as a market share, effect. Bivariate probit analysis is appropriate in that it acknowledges that SD and SM may be correlated across firms. If so, it will offer an efficiency gain over estimating the two equations separately. The equation confirms a significantly positive influence of firm size, SPH , for both diversification and multinationality. However, the results on industry size, ISPH , differ. For diversification, it attracts the expected negative coefficient, which is significant. We can also just reject the restriction (at the 5% level) that it is of equal size, but of opposite sign, to the coefficient of SPH . This indicates that, controlling for the market share effect, there is also an absolute size effect – a firm is more likely to be diversified in its home country, the larger is its market share and the scale of its operations in its home primary industry. On the other hand, in the multinational equation, ISPH is insignificant: here, it is the firm’s absolute size alone which matters. However, we can not rule out the possibility that this lack of significance for industry size reflects the cancelling out of the two opposite effects mentioned in Section 5.2: both home market share and the size of the foreign market may have positive influences, implying, respectively, negative and positive influences for ‘‘industry’’ size. Comparing the two equations, Wald tests show that the slope coefficient (on SPH ) does not differ significantly between multinationality and diversification, but the intercept does. This implies that the mean of the critical size distribution is lower for diversification than for multinationality, but we can not reject the hypothesis that the variances are identical. This is depicted graphically in Fig. 3, in which the probability of home diversification, plotted against SPH (evaluated at sample mean ISPH ) is always higher for home diversification than for primary multinationality. This sharpens up the finding from the descriptive statistics in Section 4 that diversification is the more common strategy. Finally, the estimated correlation between the error terms of the two equations, rho, is 10.542, and is statistically significant. Thus, the preliminary conclusions are that size ‘‘matters’’ for both strategies: for diversification, this has both market share and absolute size dimensions, but, for

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Fig. 3. Probability of multinationality (MP ) and diversification (DH ) amongst Europe’s leading firms.

multinationality, there is only evidence at this stage of an absolute size effect. The positive correlation between the two critical sizes suggests that the two strategies are complementary in a sense to be explored below 16 .

6.2. Introducing proprietary assets Table 3 reports the result of re-estimating the bivariate model, but now distinguishing two broad groups of firms, depending on whether the firm’s primary industry is characterised by ‘‘high’’ or ‘‘low’’ product differentiation. This simple binary distinction is based on industry-level data on typical advertising and R&D expenditures (see Appendix B for more detail), and should be interpreted as an indicator of the intrinsic nature of the firm’s main industry, rather than as a proxy for how much the firm itself spends. Nevertheless, the implication is that leaders in DIFF industries must typically possess some specific asset. This is an admittedly indirect way of proceeding, but it is arguably the best available alternative, given

16 In addition to the equations reported in the tables, we have also experimented with additional equations including country dummies (by the country of each firm’s origin). This is to recognize that firms from certain member states may be intrinsically more likely to be more multinational / diversified than firms from others. However, the empirical findings show that, after we control for domestic market size, national differences do not persist (with the exception of Holland which attracts a coefficient which is weakly positively significant at the 10% level in some cases). For similar evidence see Davies et al. (1996), Ch. 11 and 12. For instance, we find there that econometric analysis of multinationality rejects the hypothesis that German firms are less multinational than UK firms, once we control for national size and firm’s country share.

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that comparable firm-level data on these and other variables are currently unavailable 17 . It should be also noted that this specification ignores any proprietary assets which are not associated with product differentiation, the most obvious example would be some specific managerial expertise, which can clearly occur in non-differentiated product industries. The coefficient estimates shown with a DIFF flag thus refer to intercept and slope dummy variables for the high differentiation group, the low group (NONDIFF) being the default. The log-likelihood is reduced from 307 to 297.3, and Wald tests show that we can reject the hypothesis that the coefficients are the same for DIFF and NON-DIFF firms. This is true for both for the equation as a whole ( x 2 519.1 [6]), and for the diversification and multinational components individually ( x 2 510.6 [3] and 9.1 [3] respectively). Turning to the coefficients on individual variables, the Table also points to the sources of these DIFF / NON-DIFF differences. For diversification, the previous results are qualitatively unchanged (in terms of signs and significance levels) for the (default) NON-DIFF firms, but significant differences now appear between the two groups on both size variables (although the difference on firm size is only significant at the 10% level.) The net effect for the DIFF group (derived by summing the coefficients on the default and interactive forms of each variable), is that the impact of firm size is dampened, whilst that on industry size is removed altogether. In other words, diversification is driven more by a desire to exploit a specific asset and less by the desire to break free from constraints to growth in the firm’s primary market. This is shown in Fig. 4, which is plotted using the parsimonious form of the equation (II), evaluated at sample mean values for industry size. As can be seen, where product differentiation is present, diversification is generally more likely at any given firm size, but it is less sensitive to size; indeed, at large firm sizes, the two curves intersect, indicating a very high probability of diversification in both types of industry. For multinationality, there are no significant differences between the two groups in the individual coefficients shown in equation I. Superficially, this is inconsistent with the finding of a significant difference between the two groups for the equation taken as a whole. However, further experimentation to establish the parsimonious forms of both equations, shown as equation II in the table, helps to identify where the differences reside. Once the two insignificant interacted size variables are

17 One positive by-product of using industry data in this categorical way (rather than firm-specific variables) is that it minimises the likelihood of simultaneity between R&D and advertising and diversification and multinationality. For practical purposes, we do not treat R&D and advertising separately. This is because: i) many firms in the differentiated product sub-sample are both research and advertising intensive; ii) some firms with a research intensive primary industry are in fact diversified in advertising intensive industries (and vice-versa), iii) separating the differentiated subsample would further decrease the degrees of freedom at the expense of the precision of the estimates.

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Fig. 4. Probability of multinationality (MP ) and diversification (DH ) for homogeneous and differentiated product firms.

excluded from the multinational equation, there is a strongly significant difference in the intercept. Whilst there is evident instability of coefficients in this equation, the parsimonious form does suggest that mean critical size is significantly lower for DIFF firms. In other words, as expected, multinationality is more likely, at any given firm size, for firms in industries characterised by product differentiation (Fig. 4). Thus, our interim conclusion is that product differentiation tends to make both strategies more likely. For multinationality, this is in addition to the absolute firm size effect identified in the previous sub-section; but, for diversification, this it is at the expense of the industry size effect.

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6.3. Complements or substitutes? As can be seen from the significant rho values in Table 3, the positive relation between the errors of the diversification and multinational equations remains significant even after we have allowed for the DIFF / NON-DIFF distinction. In this sub-section we explore the interdependence further. In terms of the typology, Tables 2 and 3 have so far compared Classes I and II against Classes III,V and VIII in the diversification equation, and Classes I and III against Classes II,V and VIII in the multinationality equation. We now wish to isolate those firms which are both multinational and diversified (V and VIII) from those that are only diversified (III) or only multinational (II) respectively. In other words, we wish to explore the differences between the conditional probabilities of being diversified, given multinationality and given not-multinationality (and symmetrically for multinationality). The relevant equation has then been estimated as a four choices (I, II, III, V/ VIII) multinomial logit with Class I as default 18 . Estimated coefficients are presented in Table 4. As in Section 6.2, we allow for differences between the high and the low differentiation groups by interacting all regressors with a dummy variable, DIFF which is equal to 1 if the firm belongs to the high differentiation group and 0 otherwise. Interpretation of the results is also aided by referring to the Wald tests on the equality of coefficients amongst classes in Table 5, and by the graphical representations in Fig. 5. Each curve is derived from the estimated coefficients in Table 4, and therefore refers to a bilateral comparison between the relevant class and the default (evaluated at mean values of ISPH ). Thus: (i) Curve II compares firms that are solely multinational with those that are neither multinational nor diversified. It therefore portrays the probability of being multinational, conditional on not being diversified. 18 Ideally, the equation would have been estimated using a multivariate probit estimator, but this is impossible given the absence of any available computer programme. As Greene (1993, p.663) explains, ‘The practical obstacle to such an extension is the evaluation of higher order multivariate normal integrals’. Multinomial logit is a good second best, given the close similarity of the logistic and normal distributions. However, multinomial logit limitations in accounting for differential substitutability among alternatives (the so-called Independence of Irrelevant Alternatives property) are well known. Testing procedures have been suggested based on eliminating one or more alternatives from the choice set to see whether coefficient estimates are affected. Missing suggestions from theory, in this paper we have applied the test proposed by Hausman and MacFadden (1984) to all possible combinations of restricted sets (I–II, I–III, I–V/ VIII, II–III, II–V/ VIII, III–V/ VIII, I–II–III, I–II–V/ VIII, II–III–V/ VIII). The null hypothesis of Independence of Irrelevant Alternatives is never rejected. However, in 4 out of 10 cases the test generates small negative values. As pointed out by Small and Hsiao (1985), this depends on the fact that the proposed test requires the inversion of the difference between two closely related matrices, which may be non-positive definite or nearly singular and thus cause computational and inference problems.

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Fig. 5. Probability of diversification / multinationality for homogeneous and differentiated product firms – distinguishing classes.

(ii) Curve III compares firms that are solely diversified with those that are neither multinational nor diversified. It therefore portrays the probability of being diversified, conditional on not being multinational. (iii) Curve V/ VIII compares firms that are both multinational and diversified with those that are neither. In this case, the interest lies not so much in the straight comparison with the default, but more in comparisons with the two other curves. Thus: (iiia) Curve V/ VIII relative to Curve II compares firms that are multinational and diversified with those that are solely multinational. This reveals the difference

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between the probability of being multinational, conditional on being diversified and conditional on not being diversified. (iiib) Curve V/ VIII relative to Curve III similarly reveals the difference between the probability of being diversified, conditional on being multinational and conditional on not being multinational. For DIFF firms, the Wald tests reported in Table 5 indicate that the three curves differ significantly from each other. Also, as shown by the figure, the probabilities of being solely diversified or solely multinational (particularly the latter) are typically quite low for DIFF firms. Comparing V/ VIII with II and III, the conditional probability of being multinational is higher for diversified firms than for non-diversified firms, and the conditional probability of being diversified is higher for multinational firms than for non-multinationals (except at extremely small firm sizes). In other words, where proprietary assets are likely to be important, if firms are multinational then they are also probably diversified, and vice-versa. This is obviously consistent with complementarity. For NON-DIFF firms, visual comparison of the II and V/ VIII curves shows that the conditional probability of being multinational is also higher for diversified firms than for non-diversified firms, and the appropriate Wald test confirms that the difference is strongly significant. On the other hand, comparison of III with V/ VIII suggests that the conditional probability of being diversified is lower for multinationals than for non-multinationals (except at extremely large firm sizes). Although the Wald test shows the difference to be only weakly significant, at slightly less than the 10% level, there would appear to be a paradox: for the (default) NON-DIFF firms, the two strategies are complements looked at from one direction, but not from the other (indeed, if anything, the weak evidence is that they are substitutes). In fact, although there is an asymmetry, there is no paradox. We believe the explanation lies in the different size-motives for multinationality and diversification. Whilst diversification removes a constraint on growth otherwise imposed by a large primary industry market share, for multinationality, it is absolute size which matters – once the firm achieves a certain home country size, multinationality becomes a viable alternative to exporting. If this is so, it follows that the growth incentive for diversification will be reduced if the multinationality option has already been taken, since expansion can now be effected geographically without recourse to diversification. On the other hand, the incentive for multinationality remains unchanged, whether or not the firm is diversified – the advantage of foreign production over exporting in the primary industry is unaltered by diversification into other industries at home.

6.4. Foreign diversification Finally, Table 6 relates to the ‘‘last’’ decision – will a firm which is diversified at home and multinational in its primary industry also opt for diversification

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Table 6 Univariate probit analysis of the probability of diversification abroad a Variable Const. SP&H LOG-L LOG-L0 x 2 [1] n. obs.

Coefficient 22.188 0.288

Std. Error

(0.871) *** (0.115) ***

261.1 264.4 6.5 93

a

SP&H 5Firm’s total output in its primary industry and its home country. Significance levels: * 10%, ** 5%, *** 1%. Degrees of freedom in squared brackets.

abroad? In terms of the typology, this is a comparison between Class V and Class VIII (which have so far been consolidated throughout this section). Again, this is modelled simply using univariate probit, allowing the parameters to differ between DIFF and NON-DIFF. Here, we find no significant evidence of a difference in the equation between DIFF and NON-DIFF firms, and the equation is confined merely to the size variable (defined as the firm’s size at home and in its primary industry), which is positively significant 19 . It appears that foreign diversification can be explained as an alternative avenue for expansion, once firms have diversified at home and gone multinational in their primary industry. However, we are reluctant to conclude that specific assets have no role to play in this ‘final’ stage, since the majority of firms in both Classes V and VIII originate from DIFF industries, rendering this distinction imprecise in this stage.

6.5. Adjusting size for exports Finally, we should acknowledge a potential limitation on the above results which derives from an inevitable imprecision in recording the firm’s size in its primary industry. As explained already, both firm and industry size have been measured in the above econometrics using the size of production in a home country. Measured size therefore includes production for exports as well as production for domestic consumption. However, much of the theoretical motivation for including size in the model reflects the constraints on domestic growth hypothesis, i.e. as domestic primary market share increases, both diversification and multinationality become more attractive. As such, the ideal test of the hypothesis will involve measuring firm size by production for domestic consumption, i.e. size net of exports. 19 We also experimented with three other size measures: SPH ; firm size in its primary industry across all countries; and its total home country firm size. None achieved the same significance level as SP&H ; indeed, each attracted a negative sign when included alongside SP&H .

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Unfortunately, in many company accounts (our primary data-source) this disaggregation is not reported for individual countries. This means that, in effect, exports have been included in our observations on SPH and ISPH for all firms, leading to probable over-estimates of the domestic market share of any that are significantly engaged in exporting. While it is difficult to assess the extent of any consequent bias from a priori reasoning, we have undertaken a sensitivity test by re-estimating all of the above equations having adjusted both SPH and ISPH using industry-level data on trade. More specifically, SPH has been multiplied, for each firm, by the ratio of production for domestic consumption to total production (i.e. the complement of the exports to production ratio) as recorded at the industry-level for the firm’s primary industry in its home country. This adjustment assumes that the firm’s propensity to export is identical to that for the industry as a whole in its home country. Similarly, ISPH has been recomputed as apparent consumption for the industry as a whole, by subtracting exports and adding imports from the previously used observations on production. Reassuringly, the results are remarkably robust to this revision. Of course, even this adjustment will not have eradicated all measurement errors, especially if, as seems likely, the sample firms have a greater propensity to export than do other (smaller) firms in their home industries. However, this particular sensitivity test is probably as far as we can pursue this potential bias, given the present data available to us. Provisionally, at least, it does not suggest that our inability to net out exports has imparted a serious bias to our results 20 .

7. Implications and conclusions As explained in the introduction, this paper has some objectives which are largely descriptive, and some which are more analytical. On a descriptive level, we have reported some evidence on the extent of diversification and multinationality (within the EU) for a set of the EU’s largest manufacturing firms. Both structures are common amongst these firms, but with diversification being the more common. We went on to suggest a typology for describing the corporate structures of such firms in these two dimensions. This depends on whether firms are diversified at home and / or abroad (or, equivalently, multinational in their primary and secondary industries.) According to this typology, eight alternative structures are possible in principle. In this particular sample, however, only five of the types are observed with any frequency. Future research will reveal whether this is the norm, or whether it is peculiar to this particular sample.

20

A version of Tables 2–5, using these revised size measures is available on request from the authors.

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On a more analytical level, we have examined two relationships which have been prevalent in the previous separate literatures on diversification and multinationality: it is usually found that both strategies are more common in larger firms, and where proprietary assets are likely to be more important. Our results tend to confirm these ‘stylised facts’, but with important qualifications and extensions. First, we suggested that simple positive correlation / regression coefficients between aggregate firm size and diversification or multinationality are not conclusive. Rather, they are open to purely identity-type explanations – unless expansion via multinationality and diversification is a perfect substitute for home country operations in the core industry, it must necessarily increase the firm’s aggregate size. For this reason, we have modelled the decision-making process as sequential, distinguishing home from foreign diversification, and primary from secondary multinationality. This leads to finer formulations of the size hypothesis: e.g. is home diversification related to the size of the firm in its home primary industry? Generally, the significance of size remains robust to this sort of disaggregation, but some important qualifications now emerge (see below). We also find that size continues to be important for foreign diversification (i.e. secondary industry multinationality), but, in this case, it is the firm’s size aggregated across its primary industry in all countries and across all industries in its home country. This is consistent with the hypothesis that foreign diversification is viewed as a further potential source of expansion. Proprietary assets also have an important role. More precisely, we find that both home diversification and primary multinationality are generally more likely when firms originate from an industry characterised by high advertising and / or R&D. Our interpretation is that leading firms in these industries almost inevitably possess specific assets associated with product differentiation. In these cases, the coefficient on firm size is much reduced, suggesting that the two strategies are motivated more by exploitation of a specific asset than by expansion. Our most novel results concern the interplay between the two strategies. Where firms originate from differentiated product industries, home diversification and primary multinationality are found to be complementary, in the sense that firms which are multinational in their core industry are also more likely to be diversified at home, and vice-versa. The implication is that proprietary assets are typically a public good within the firm: if they can be exploited across countries, they can also typically support expansion in product space. However, a second theme in our results suggests that there is a sense in which the two strategies may sometimes be viewed as substitutes or alternatives. Thus, there is evidence that diversification is more likely, when the firm operates in a smaller non-differentiated industry, in which the opportunity for growth may be constrained. However, this tendency is only apparent amongst firms which are not also multinational. The implication is that this motive for diversification is reduced where multinationality offers an alternative option. Interestingly, the reverse is not observed. In other words the likelihood of being multinational is not smaller for

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firms which have already taken the diversification option. In the paper we offer a possible explanation for this asymmetry based on the different motivations underlying the two choices. We should close, however, with an important qualification. Throughout, our analysis has been constrained by the cross-section nature of our data. Especially (but not only) when examining the issues raised in the previous paragraph, time series data on the evolution of corporate structures would offer better prospects of more refined testing. Nevertheless, pending that future work, we believe that the results of the present study provide a useful starting point.

Acknowledgements We are grateful for comments to three referees of this journal, and to participants at seminars given at CERIS-CNR, EARIE 95, IGIER-Bocconi University, Sheffield University, UEA and University of Leicester. Steve Davies would like to thank CERIS-CNR for hosting his stay in Torino, during which much of this research was undertaken.

Appendix A. Identity relationships between firm size, multinationality and diversification Let SIZE i be the firm’s size aggregated across all industries ( j) and countries (k), and define its overall diversification and multinationality using the following Herfindahl-type indices: Di 5 1 2 Sj (x ij )2 /(x i )2

(A.1)

Mi 5 1 2 Sk (x ik )2 /(x i )2

(A.2)

(i) Decomposition of firm size in product space Denote the i-th firm’s market share in industry j by MSij 5 x ij /x j , where x j denotes the aggregate size of industry j, and substitute into (A.1): Di 5 1 2 S j (MSij )2 (x j )2 /(x i )2 .

(A.3)

Next define its ‘typical’ market share as the weighted average market share across industries:

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MSi 5 S j MSij (x ij /x i )

(A.4)

and combine (A.3) and (A.4) to give MSi (1 2 Di )21 5 x i [S j MSij x ij ] / [S j MSij (x ij ) (x j )] Next define an index of the typical size of industry as:

(A.5) 21

in which the firm operates

ISi 5 S j (w ij .x j )

(A.6)

where w ij 5 (x ij MSij ) / S(x ij MSij )

(A.7)

ISi 5 S i x j x ij MSij / S(x ij MSij ) 5 S j x 2j MS 2ij / S(x ij MSij )

(A.8)

then

Substituting (A.8) into (A.5) and rearranging, it follows that: SIZE i 5 x i 5 MS *i IS *i (1 2 Di )21

(A.9)

(ii) Decomposition of firm size in geographic space The analogous decomposition across countries follows identically, merely replacing market share and industry size for industry j with country share (CSi ) and country size (NATSi ) for country k: SIZEi 5 x i 5 CS *i NATS i* (1 2 Mi )21

(A.10)

(iii) Relationship between multinationality and diversification Denote the firm’s diversification within country k by Dk 5 1 2 S j (x jk )2 /(x k )2 and the ‘typical’ (weighted average) value of this across countries as d 5 S k vk Dk where vk 5 x 2k / Sx 2k

(A.11) 22

(A.12)

21 Some comment is needed in interpreting the IS index. For firm i, it is the weighted average size of all industries in which it operates. As the weights depend on the size of the firm’s presence in the industry times its market share, the index is firm specific: industry j is given more weight if the firm’s operations in j are both important to the firm and significant in the industry. 22 The unusual weighting structure in defining ‘typical’ is dictated by the nature of Herfindahl type. The weights, so defined, sum to unity and attach relatively more importance to the larger industries (countries).

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Similarly, denote multinationality in industry j by: Mj 5 1 2 S k (x jk )2 /(x j )2

(A.13)

and typical multinationality as: m 5 S j w j Mj where w j 5 x j2 / Sx j2

(A.14)

Substituting (A.11) into (A.12) and (A.13) and (A.14) and equating the two expressions yields: (1 2 m) S j x 2j 5 (1 2 d)S k x 2k

(A.15)

Then substituting in (A.1) and (A.2) gives: (1 2 m)(1 2 D) 5 (1 2 d)(1 2 M)

(A.16)

Finally, simple manipulation gives: D 5 d 1 h(1 2 d) ? (M 2 m) /(1 2 m)j

(A.17)

Appendix B SPH 5the firm’s sales of goods produced in its primary industry in its home country. Primary industry refers to the 3-digit NACE Rev. 0 industry accounting for the largest proportion of the firm’s total EU sales. For 194 firms this proportion exceeds 50%, but it is only 25–50% for 74 firms, and only 15–25% for 9. In some cases then, the classification is ambiguous – a matter we address in Section 4. Home country is always identified as the firm’s country of origin: all but 11 firms produce at least half of their EU total in their home country. The source is the EU Market Share Matrix for 1987 (see Davies et al., 1996, Appendix 3). The primary sources are mainly company reports and business directories (see footnote 7). ISPH 5the size of the firm’s primary industry in its home country, relative to setup costs entailed by efficient scale (i.e. the product of minimum efficient scale and the industry’s capital output ratio), see Davies et al. (1996, Appendix 3). The primary sources for industry size: Published 3-digit EUROSTAT data (Structure and Activity of Industry, 1987). These figures were grossed up to take account of production of smaller firms with less than employees (Enterprises in Europe, Second Report, EUROSTAT, 1992 for 2-digit level data and unpublished EUROSTAT 3-digit level data). The engineering estimates of minimum efficient size are taken from Pratten (1987), The Cost of Non-Europe supplemented by additional estimates of MES and capital intensity kindly provided by Bruce Lyons (UEA); based on data from the UK Census of Production and Business Monitors. DIFF 5an industry dummy variable which takes the value of unity if the firm’s primary industry is either advertising- or R&D-intensive (or both). Again, this is as described in Davies et al. (1996); (Appendix 3). Their primary sources were: (i)

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comprehensive advertising data in the EU are only available for the UK (MEAL advertising data on the advertising expenditures of the top 250 advertisers in the UK). These figures are expressed relative to UK apparent consumption: the industry is advertising-intensive if this ratio.1%. Data on the R&D to sales ratios are available for the UK (Business Monitor, MO14, CSO, 1989), and Italy (ISTAT, Statistiche della Ricerca Scientifica, 1990). The industry is R&Dintensive if this ratio.1%. For practical purposes, we do not treat R&D and advertising separately. This is because: (i) many firms in the differentiated product sub-sample are both research and advertising intensive; (ii) some firms with a research intensive primary industry are in fact diversified in advertising intensive industries (and vice-versa), (iii) separating the differentiated sub-sample would further decrease the degrees of freedom at the expense of the precision of the estimates. The TRADE data used to estimate the firm’s export intensity in its primary industry and the apparent consumption in the firm’s primary industry (see Section 6.5) are taken from unpublished EUROSTAT country data at the 3-digit industry level (NACE Rev. 0).

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