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Multinational involvement and risk
261
Economics Letters 19 (1985) 261-265 North-Holland
MULTINATIONAL Mark HIRSCHEY
INVOLVEMENT
AND RISK
*
Uniuersity of Colorado, Denuer. CO 80202, USA Received
18 April 1985
This study reveals that foreign sales, profit and asset percentage data all relate to the same underlying multinational involvement phenomena, and finds no inverse relation between two common measures of risk and multinational involvement. These results suggest the multinational phenomena must be rationalized on the basis of imperfections in input and output markets, rather than on the basis of imperfections in international capital markets.
1. Introduction Hughes, Logue and Sweeney (1975) for example, found support for a risk reduction motive to multinational involvement, in that they found both systematic and unsystematic risk to be lower for multinational as opposed to uninational firms. This contrast with an alternate view of multinational involvement as a means by which firms exploit economic rent opportunities caused by imperfections in real input and output markets. Baldwin (1979) and La11 (1980) for example, found support for the hypothesis that foreign markets are sought in order more completely to exploit Ricardian rent opportunities. Whereas the financial diversification hypothesis implies a negative marginal effect of multinational involvement on risk, no such relation is inherent in the industrial organization hypothesis. By explicitly considering the relation between multinational involvement and risk a direct test of the financial diversification hypothesis becomes possible. Little or no relation would be inconsistent with the financial diversification hypothesis, and suggest the industrial organization hypothesis as a seemingly attractive alternate explanation of the multinational phenomena.
2. Factor analysis 2.1. Sources of risk Several important sources of risk have been proposed, beyond those relating to multinational involvement. Ben-Zion and Shalit (1975) argue that leverage is an important determinant of equity risk since senior securities have priority over common stock in the distribution of a firm’s income as well as in the distribution of its assets in the case of bankruptcy. They also argue that firm size is an important determinant of risk, where large firms are presumed less risky due to greater diversifica* I wish to thank Lemma W. Senbet, Howard E. Thompson and Dean W. Wichern for valuable comments Scott S. Scheffler provided able research assistance. Of course, I alone am responsible for any errors.
0165-1765/85/$3.30
0 1985, Elsevier Science Publishers
B.V. (North-Holland)
on an earlier draft.
262
M. Hirschey
/ Multinutionul
rnuolwment
and risk
tion, typically long records of successful performance, and assets which tend to be more marketable than those of smaller companies. A more controversial potential determinant of risk is relative firm size. Subrahmanyam and Thomadakis (1980) have developed a model of the firm under uncertainty which predicts a negative relation between market share and risk. Sullivan (1978) observed a generally significant negative relation between four-firm concentration and risk, implying leading firms have greater price stability in the secondary capital market with correspondingly lower capital costs. Curley, Hexter and Choi (1982) dispute this finding, citing flaws in the Sullivan analysis. After correction, they find little support for the Sullivan hypothesis. Thus, the relation between relative firm size and risk remains unsettled. Senbet and Thompson (1982) argue that risk will tend to increase with growth because managers of rapidly growing firms must devote substantial effort to project search. Given finite managerial capabilities, these managers will have less time to devote to project return and risk analysis, and an increased variability of project returns will result. And finally, risk may be affected by firm operating characteristics such as capital intensity [Subrahmanyam and Thomadakis (1980)], as well as by the intangible nature of investment expenditures. Comanor and Wilson (1967) for example, have suggested that advertising investment in market penetration will involve a particularly risky use of funds since it does not generally create tangible assets which can be resold in the event of failure. A similar argument can be made in terms of research and development ( R&D) expenditures, with the result being the anticipation of a positive correlation between risk and capital intensity, R&z D and advertising intensity. And finally, the measurement of multinational involvement is itself a subject of some dispute. Agmon and Lessard (1977) argue that the proportion of the market value of the firm which represents foreign as opposed to domestic operations is an ideal index. Despite its attractiveness on a theoretical level, market value indices would involve complicated calculations of the value of tangible and intangible assets which are not presently available [see Hirschey (1982b)]. On a second-best criteria, foreign sales, asset and profit percentages have been offered as attractive indices of multinational involvement. However, it is uncertain whether or not these data convey equivalent risk information. For example, expropriation risk would seem closely related to the foreign asset percentage, but may bear little or no relation to the foreign sales percentage. Furthermore, as Errunza and Senbet (1981) argue, foreign asset and profit figures are the outcome of both home and host country accounting conventions, translation procedures and intracompany allocations. Thus, these figures may show little consistency across firms. On an a priori basis, it is not clear whether the ten variables discussed above constitute unique sources of risk, or instead relate to a fewer number of underlying but unobservable factors. To investigate this issue, a factor analysis of the ten potential determinants of risk is appropriate [see Johnson and Wichern (1982)]. 2.2. Data Data were obtained on a 1978 sample of n = 92 industrials from the Forbes annual survey of the largest U.S. based multinationals. Firms engaged in banking (e.g., Citicorp, Bankamerica, etc.) and retailing (e.g., Sears, F.W. Woolworth, etc.) were omitted in order that a more homogenous sample might be analyzed. The foreign sales percentage (FSP), foreign profit percentage (FPP) and foreign asset percentage (FAP) data are all defined as the proportion of foreign to foreign plus domestic totals, and were obtained from Forbes. The book values of total assets, stockholder’s equity and sales were obtained from Fortune. Leverage (LEV) is measured by the debt to stockholder’s equity ratio. Firm size is measured by sales (S) in billions of dollars. Concentration (CR) in percent is analyzed using primary product industry concentration data at the four-digit level from the 1977 Census of Manufacturers.
M. Hirschey / Multinatu_mzl involvement and risk Table
263
1
Rotated
estimates of factor loadings. Principal component
Variable
FSP FPP FAP LEV S CR CR K/S R&D/S A D/S
Maximum
likelihood
Estimated factor
Specific
Estimated factor
Specific
loadings
variances
loadings
variances
F4
‘&,=1-R;
F,
- 0.202
0.100
0.952
0.110
0.075
0.241
0.744
- 0.017
0.134
0.934
0.100
0.305
0.017
F2
F,
4
0.918
0.067
0.861
- 0.045
0.103
0.921
0.024
- 0.035
- 0.078
- 0.203
-0.112
0.107
-0.122 0.797
F2
-0.150
F3 0.022 0.000
F4
‘@,=1-h;
-0.119
0.045
0.088
0.460
-0.116
- 0.038
0.158
-0.196
0.896
0.162
0.018
0.810
- 0.325
0.165
0.210
0.047
0.820
- 0.198
0.014
0.308
- 0.282
0.203
- 0.410
- 0.202
0.671
- 0.153
0.090
- 0.085
0.003
0.953
0.777
0.491
0.112
0.095
0.419
0.017
0.003
0.907
0.251
- 0.019
0.114
0.012
0.013
- 0.024
0.803
0.022
0.354
0.029
0.069
0.475
0.682
- 0.373
0.166
- 0.011
0.071
- 0.270
- 0.329
- 0.738
0.297
0.036
0.254
0.437
0.599
0.744
-0.113 0.197 -0.136
0.963
0.810
-0.138
0.000
- 0.094
- 0.376
0.813
0.521
0.621
Cumulative proportion of total variance explained
0.236
0.376
Growth (GR) in percent is measured as the average annual rate of growth in firm sales between 1973 K/S, is measured by the total asset to and 1978 where GR = ( S1978/S1973)“5 - 1. Capital intensity, sales ratio. Similarly, R&D intensity (R&D/S) and advertising intensity (A D/S) are measured by the ratios of R&D and advertising expeditures to sales, respectively. R&D expenditure data were obtained from Business Week, while advertising expenditures had Leading National Advertisers as its source. In addition to these ten potential sources of risk, two measures of risk are included in the regression analysis described below. First, stock price betas calculated using 60 observations of monthly data obtained from Value Line are considered. Second, Standard and Poor’s (S&P) ranking of earnings and dividend stability is considered as an alternate risk measure. Following Ben-Zion and Shalit (1975) letter rankings of common stock (A+, A , . . . , C, NR) were translated into a numerical scale ranging from 1 to 8. These rankings were obtained from Standard and Poor’s Security Owners’ Stock Guide, 2.3. Estimation
results
Rotated estimates of factor loadings based upon the sample correlation matrix using both principal component and maximum likelihood methods of estimation are presented in table 1. Using a criterion of eigenvalues greater than one, an m = 4 factor solution was suggested from the principal component perspective, and m = 3 from the maximum likelihood perspective. A subsequent interpretation of the factor loadings reinforces the choice of m = 4. Specific variances, @ = 1 - hf represent the share of variation in a variable which cannot be explained in terms of a few underlying factors. Here hf is described as the communality of a variable, or its squared multiple correlation with the m = 4 factors. The cumulative proportion of total variance explained shows the share of variation in all the x ‘s which is captured through adding each additional factor. It is obvious from table 1 that a firm’s percentage of foreign sales, profits and assets all related to a single latent underlying unobservable variable, here F,, which can be called multinational involve-
264
M. Hwschqv / Multincriional inrwlwnrent und risk
ment. With respect to multinational involvement, a simple structure is suggested in that the high factor loadings of foreign sales, profit and asset percentages are accompanied by low factor loadings for alternate potential determinants of risk. Moreover, this finding is robust in that it emerges in both principal component and maximum likelihood estimates. Thus, the data have the potential to provide evidence on the risk implications of multinational involvement which is distinct from the effects of other important influences. Less striking, but still fairly unique and consistent, characterizations of each remaining factor can also be provided. F, relates to the ‘investment options’ of the firm as captured by sales and growth data. c? seems closely related to the capital and R&D intensity or ‘investment risk’ of the firm. though this factor also reflects the effects of growth to a more limited degree. And finally. F4 is clearly related to leverage. These results imply that, in addition to multinational involvement, the effects of investment options, investment risk and leverage must also be considered as potential causes of firm risk.
3. Regression
analysis
A regression analysis using two alternate measures of risk, y variables, is now conducted to learn the risk implications, if any, of multinational involvement and other potentially important factors. Stock price betas will be considered as the most widely accepted measure of systematic risk. In addition, Ben-Zion and Shalit (1975) propose the S&P ranking of earnings and dividend stability be considered as a second alternate risk measure reflecting risk assessments by investment agencies and other practitioners operating in the stock market. In their analysis, Ben-Zion and Shalit found that betas and the S&P rank capture different aspects of risk, with some overlap. As a practical implication of their findings, it is desirable to consider more than a single measure in empirical studies of risk.
Table 2 Estimation
results
for sources
of two common
measures
Dependent
of risk (/-statistics
variable S&P rank
Beta
Constant F,(Multinational
involvement)
PC factors
ML factors
1.048 0.017 (1.11)
F2 (Investment
options)
0.020 (1.33)
4 (Investment
risk)
0.054 (3.55) il
F4 (Leverage)
- 0.015 ( - 0.98)
R2 F * Indicates ’ Indicates
0.152 4.12 a significance significance
at the a = 0.01 level. at the a = 0.05 level.
in parentheses).
PC factors
ML factors
1.048 0.016 (1.02)
2.557 -0.106 ( - 0.73)
2.557 ~ 0.062 ( ~ 0.40)
~ 0.006 (-0.37)
- 0.024 (-0.17)
-0.191 (-1.21)
0.070 (4.65) * 0.014 (0.83) 0.217 6.37 ’
- 0.001
( ~ 0.01)
0.064 (0.43)
0.481 (3.29) ’
0.563 (3.44) A
0.110 2.69 h
0.126 3.14 h
h4. Hirschey / Multinational inooluement and mk
265
Table 2 shows OLS results for regressions of beta and S&P rank measures of risk on factor scores obtained through principal component (PC) and maximum likelihood (ML) estimation. Interestingly, the data fail to support the financial diversification hypothesis. No consistent risk-reducing effect of multinational involvement is noted. In fact, as in some related studies [e.g., Hirschey (1982a)], some evidence of a modest risk-increasing effect of multinational involvement is found in the beta regressions. However, such effects are quite modest, and on an overall basis one must conclude that no strong relation between either risk measure and multinational involvement is apparent. Beta seems to be most closely determined by investment risk, while the S&P ranking measure is closely related to leverage. The findings with respect to beta can be taken as support for Subrahmanyam and Thomakakis’ (1980) argument. concerning the importance of capital intensity as a basic determinant of systematic risk, and Comanor and Wilson’s (1967) suggestion that investments in intangible assets are risky. The findings with respect to the S&P ranking measure parallel Ben-Zion and Shalit’s (1975) results, and suggest that institutional assessments of risk are more heavily influenced by financial leverage than by other factors. 4. Summary These findings are inconsistent with any important inverse relation between multinational involvement and risk. Therefore, these results are inconsistent with explanation of multinational involvement as an efficient means of international diversification of firm investment porfolios, but are instead consistent with the notion of efficiency across international capital markets. Since the industrial organization hypothesis implies no necessary relation between multinational involvement and risk, this hypothesis would seemingly provide an attractive alternate explanation of the multinational phenomena. References Agmon, T. and D.R. Lessard, 1977, Investor recognition of corporate international diversification. Journal of Finance 32, Sept., 1049-1055. Baldwin. R.E., 1979, Determinants of trade and foreign investment: Further evidence, Review of Economics and Statistics 61, Feb., 40-48. Ben-Zion, U. and S.S. Shalit, 1975, Size, leverage, and divided record as determinants of equity risk, Journal of Finance 30, Sept., 1015-1026. Comanor, W.S. and T.A. Wilson, 1967. Advertising, market structure and performance, Review of Economics and Statistics 49, Nov., 4233440. Curley, A.J., J.L. Hexter and D. Choi, 1982, The cost of capital and the market power of firms: A comment. Review of Economics and Statistics 64, Aug., 519-523. Errunza, V.R. and L.W. Senbet, 1981, The effects of international operations on the market value of the firm: Theory and evidence, Journal of Finance (Proceedings) 36, May, 401-417. Hirschey, M., 1982a, Market power and foreign involvement by U.S. multinationals, Review of Economics and Statistics 64, May, 343-346. Hirschey, M., 1982b, Intangible capital aspects of advertising and R&D expenditures, Journal of Industrial Economics 30, June, 375-390. Hughes, J.S., D.E. Logue and R.J. Sweeney, 1975, Corporate international diversification and market assigned measures of risk and diversification, Journal of Financial and Quantitative Analysis 10, Nov., 627-637. Johnson, R.A. and D.W. Wichern. 1982, Applied multivariate statistical analysis (Prentice-Hall. Englewood Cliffs, NJ). Lall, S., 1980, Monopolistic advantages and foreign involvement by U.S. manufacturing industry, Oxford Economic Papers 32, March, 102-122. Senbet, L.W. and H.E. Thompson, 1982, Growth and risk, Journal of Financial and Quantitative Analysis 17, Sept.. 331-340. Subrahmanyam, M.G. and S.B. Thomadakis, 1980, Systematic risk and the theory of the firm, Quarterly Journal of Economics 97, May, 437-451. Sullivan, T.G., 1978, The cost of capital and the market power of firms, Review of Economics and Statistics 60, May, 209-217.
Economics Letters 19 (1985) 261-265 North-Holland
MULTINATIONAL Mark HIRSCHEY
INVOLVEMENT
AND RISK
*
Uniuersity of Colorado, Denuer. CO 80202, USA Received
18 April 1985
This study reveals that foreign sales, profit and asset percentage data all relate to the same underlying multinational involvement phenomena, and finds no inverse relation between two common measures of risk and multinational involvement. These results suggest the multinational phenomena must be rationalized on the basis of imperfections in input and output markets, rather than on the basis of imperfections in international capital markets.
1. Introduction Hughes, Logue and Sweeney (1975) for example, found support for a risk reduction motive to multinational involvement, in that they found both systematic and unsystematic risk to be lower for multinational as opposed to uninational firms. This contrast with an alternate view of multinational involvement as a means by which firms exploit economic rent opportunities caused by imperfections in real input and output markets. Baldwin (1979) and La11 (1980) for example, found support for the hypothesis that foreign markets are sought in order more completely to exploit Ricardian rent opportunities. Whereas the financial diversification hypothesis implies a negative marginal effect of multinational involvement on risk, no such relation is inherent in the industrial organization hypothesis. By explicitly considering the relation between multinational involvement and risk a direct test of the financial diversification hypothesis becomes possible. Little or no relation would be inconsistent with the financial diversification hypothesis, and suggest the industrial organization hypothesis as a seemingly attractive alternate explanation of the multinational phenomena.
2. Factor analysis 2.1. Sources of risk Several important sources of risk have been proposed, beyond those relating to multinational involvement. Ben-Zion and Shalit (1975) argue that leverage is an important determinant of equity risk since senior securities have priority over common stock in the distribution of a firm’s income as well as in the distribution of its assets in the case of bankruptcy. They also argue that firm size is an important determinant of risk, where large firms are presumed less risky due to greater diversifica* I wish to thank Lemma W. Senbet, Howard E. Thompson and Dean W. Wichern for valuable comments Scott S. Scheffler provided able research assistance. Of course, I alone am responsible for any errors.
0165-1765/85/$3.30
0 1985, Elsevier Science Publishers
B.V. (North-Holland)
on an earlier draft.
262
M. Hirschey
/ Multinutionul
rnuolwment
and risk
tion, typically long records of successful performance, and assets which tend to be more marketable than those of smaller companies. A more controversial potential determinant of risk is relative firm size. Subrahmanyam and Thomadakis (1980) have developed a model of the firm under uncertainty which predicts a negative relation between market share and risk. Sullivan (1978) observed a generally significant negative relation between four-firm concentration and risk, implying leading firms have greater price stability in the secondary capital market with correspondingly lower capital costs. Curley, Hexter and Choi (1982) dispute this finding, citing flaws in the Sullivan analysis. After correction, they find little support for the Sullivan hypothesis. Thus, the relation between relative firm size and risk remains unsettled. Senbet and Thompson (1982) argue that risk will tend to increase with growth because managers of rapidly growing firms must devote substantial effort to project search. Given finite managerial capabilities, these managers will have less time to devote to project return and risk analysis, and an increased variability of project returns will result. And finally, risk may be affected by firm operating characteristics such as capital intensity [Subrahmanyam and Thomadakis (1980)], as well as by the intangible nature of investment expenditures. Comanor and Wilson (1967) for example, have suggested that advertising investment in market penetration will involve a particularly risky use of funds since it does not generally create tangible assets which can be resold in the event of failure. A similar argument can be made in terms of research and development ( R&D) expenditures, with the result being the anticipation of a positive correlation between risk and capital intensity, R&z D and advertising intensity. And finally, the measurement of multinational involvement is itself a subject of some dispute. Agmon and Lessard (1977) argue that the proportion of the market value of the firm which represents foreign as opposed to domestic operations is an ideal index. Despite its attractiveness on a theoretical level, market value indices would involve complicated calculations of the value of tangible and intangible assets which are not presently available [see Hirschey (1982b)]. On a second-best criteria, foreign sales, asset and profit percentages have been offered as attractive indices of multinational involvement. However, it is uncertain whether or not these data convey equivalent risk information. For example, expropriation risk would seem closely related to the foreign asset percentage, but may bear little or no relation to the foreign sales percentage. Furthermore, as Errunza and Senbet (1981) argue, foreign asset and profit figures are the outcome of both home and host country accounting conventions, translation procedures and intracompany allocations. Thus, these figures may show little consistency across firms. On an a priori basis, it is not clear whether the ten variables discussed above constitute unique sources of risk, or instead relate to a fewer number of underlying but unobservable factors. To investigate this issue, a factor analysis of the ten potential determinants of risk is appropriate [see Johnson and Wichern (1982)]. 2.2. Data Data were obtained on a 1978 sample of n = 92 industrials from the Forbes annual survey of the largest U.S. based multinationals. Firms engaged in banking (e.g., Citicorp, Bankamerica, etc.) and retailing (e.g., Sears, F.W. Woolworth, etc.) were omitted in order that a more homogenous sample might be analyzed. The foreign sales percentage (FSP), foreign profit percentage (FPP) and foreign asset percentage (FAP) data are all defined as the proportion of foreign to foreign plus domestic totals, and were obtained from Forbes. The book values of total assets, stockholder’s equity and sales were obtained from Fortune. Leverage (LEV) is measured by the debt to stockholder’s equity ratio. Firm size is measured by sales (S) in billions of dollars. Concentration (CR) in percent is analyzed using primary product industry concentration data at the four-digit level from the 1977 Census of Manufacturers.
M. Hirschey / Multinatu_mzl involvement and risk Table
263
1
Rotated
estimates of factor loadings. Principal component
Variable
FSP FPP FAP LEV S CR CR K/S R&D/S A D/S
Maximum
likelihood
Estimated factor
Specific
Estimated factor
Specific
loadings
variances
loadings
variances
F4
‘&,=1-R;
F,
- 0.202
0.100
0.952
0.110
0.075
0.241
0.744
- 0.017
0.134
0.934
0.100
0.305
0.017
F2
F,
4
0.918
0.067
0.861
- 0.045
0.103
0.921
0.024
- 0.035
- 0.078
- 0.203
-0.112
0.107
-0.122 0.797
F2
-0.150
F3 0.022 0.000
F4
‘@,=1-h;
-0.119
0.045
0.088
0.460
-0.116
- 0.038
0.158
-0.196
0.896
0.162
0.018
0.810
- 0.325
0.165
0.210
0.047
0.820
- 0.198
0.014
0.308
- 0.282
0.203
- 0.410
- 0.202
0.671
- 0.153
0.090
- 0.085
0.003
0.953
0.777
0.491
0.112
0.095
0.419
0.017
0.003
0.907
0.251
- 0.019
0.114
0.012
0.013
- 0.024
0.803
0.022
0.354
0.029
0.069
0.475
0.682
- 0.373
0.166
- 0.011
0.071
- 0.270
- 0.329
- 0.738
0.297
0.036
0.254
0.437
0.599
0.744
-0.113 0.197 -0.136
0.963
0.810
-0.138
0.000
- 0.094
- 0.376
0.813
0.521
0.621
Cumulative proportion of total variance explained
0.236
0.376
Growth (GR) in percent is measured as the average annual rate of growth in firm sales between 1973 K/S, is measured by the total asset to and 1978 where GR = ( S1978/S1973)“5 - 1. Capital intensity, sales ratio. Similarly, R&D intensity (R&D/S) and advertising intensity (A D/S) are measured by the ratios of R&D and advertising expeditures to sales, respectively. R&D expenditure data were obtained from Business Week, while advertising expenditures had Leading National Advertisers as its source. In addition to these ten potential sources of risk, two measures of risk are included in the regression analysis described below. First, stock price betas calculated using 60 observations of monthly data obtained from Value Line are considered. Second, Standard and Poor’s (S&P) ranking of earnings and dividend stability is considered as an alternate risk measure. Following Ben-Zion and Shalit (1975) letter rankings of common stock (A+, A , . . . , C, NR) were translated into a numerical scale ranging from 1 to 8. These rankings were obtained from Standard and Poor’s Security Owners’ Stock Guide, 2.3. Estimation
results
Rotated estimates of factor loadings based upon the sample correlation matrix using both principal component and maximum likelihood methods of estimation are presented in table 1. Using a criterion of eigenvalues greater than one, an m = 4 factor solution was suggested from the principal component perspective, and m = 3 from the maximum likelihood perspective. A subsequent interpretation of the factor loadings reinforces the choice of m = 4. Specific variances, @ = 1 - hf represent the share of variation in a variable which cannot be explained in terms of a few underlying factors. Here hf is described as the communality of a variable, or its squared multiple correlation with the m = 4 factors. The cumulative proportion of total variance explained shows the share of variation in all the x ‘s which is captured through adding each additional factor. It is obvious from table 1 that a firm’s percentage of foreign sales, profits and assets all related to a single latent underlying unobservable variable, here F,, which can be called multinational involve-
264
M. Hwschqv / Multincriional inrwlwnrent und risk
ment. With respect to multinational involvement, a simple structure is suggested in that the high factor loadings of foreign sales, profit and asset percentages are accompanied by low factor loadings for alternate potential determinants of risk. Moreover, this finding is robust in that it emerges in both principal component and maximum likelihood estimates. Thus, the data have the potential to provide evidence on the risk implications of multinational involvement which is distinct from the effects of other important influences. Less striking, but still fairly unique and consistent, characterizations of each remaining factor can also be provided. F, relates to the ‘investment options’ of the firm as captured by sales and growth data. c? seems closely related to the capital and R&D intensity or ‘investment risk’ of the firm. though this factor also reflects the effects of growth to a more limited degree. And finally. F4 is clearly related to leverage. These results imply that, in addition to multinational involvement, the effects of investment options, investment risk and leverage must also be considered as potential causes of firm risk.
3. Regression
analysis
A regression analysis using two alternate measures of risk, y variables, is now conducted to learn the risk implications, if any, of multinational involvement and other potentially important factors. Stock price betas will be considered as the most widely accepted measure of systematic risk. In addition, Ben-Zion and Shalit (1975) propose the S&P ranking of earnings and dividend stability be considered as a second alternate risk measure reflecting risk assessments by investment agencies and other practitioners operating in the stock market. In their analysis, Ben-Zion and Shalit found that betas and the S&P rank capture different aspects of risk, with some overlap. As a practical implication of their findings, it is desirable to consider more than a single measure in empirical studies of risk.
Table 2 Estimation
results
for sources
of two common
measures
Dependent
of risk (/-statistics
variable S&P rank
Beta
Constant F,(Multinational
involvement)
PC factors
ML factors
1.048 0.017 (1.11)
F2 (Investment
options)
0.020 (1.33)
4 (Investment
risk)
0.054 (3.55) il
F4 (Leverage)
- 0.015 ( - 0.98)
R2 F * Indicates ’ Indicates
0.152 4.12 a significance significance
at the a = 0.01 level. at the a = 0.05 level.
in parentheses).
PC factors
ML factors
1.048 0.016 (1.02)
2.557 -0.106 ( - 0.73)
2.557 ~ 0.062 ( ~ 0.40)
~ 0.006 (-0.37)
- 0.024 (-0.17)
-0.191 (-1.21)
0.070 (4.65) * 0.014 (0.83) 0.217 6.37 ’
- 0.001
( ~ 0.01)
0.064 (0.43)
0.481 (3.29) ’
0.563 (3.44) A
0.110 2.69 h
0.126 3.14 h
h4. Hirschey / Multinational inooluement and mk
265
Table 2 shows OLS results for regressions of beta and S&P rank measures of risk on factor scores obtained through principal component (PC) and maximum likelihood (ML) estimation. Interestingly, the data fail to support the financial diversification hypothesis. No consistent risk-reducing effect of multinational involvement is noted. In fact, as in some related studies [e.g., Hirschey (1982a)], some evidence of a modest risk-increasing effect of multinational involvement is found in the beta regressions. However, such effects are quite modest, and on an overall basis one must conclude that no strong relation between either risk measure and multinational involvement is apparent. Beta seems to be most closely determined by investment risk, while the S&P ranking measure is closely related to leverage. The findings with respect to beta can be taken as support for Subrahmanyam and Thomakakis’ (1980) argument. concerning the importance of capital intensity as a basic determinant of systematic risk, and Comanor and Wilson’s (1967) suggestion that investments in intangible assets are risky. The findings with respect to the S&P ranking measure parallel Ben-Zion and Shalit’s (1975) results, and suggest that institutional assessments of risk are more heavily influenced by financial leverage than by other factors. 4. Summary These findings are inconsistent with any important inverse relation between multinational involvement and risk. Therefore, these results are inconsistent with explanation of multinational involvement as an efficient means of international diversification of firm investment porfolios, but are instead consistent with the notion of efficiency across international capital markets. Since the industrial organization hypothesis implies no necessary relation between multinational involvement and risk, this hypothesis would seemingly provide an attractive alternate explanation of the multinational phenomena. References Agmon, T. and D.R. Lessard, 1977, Investor recognition of corporate international diversification. Journal of Finance 32, Sept., 1049-1055. Baldwin. R.E., 1979, Determinants of trade and foreign investment: Further evidence, Review of Economics and Statistics 61, Feb., 40-48. Ben-Zion, U. and S.S. Shalit, 1975, Size, leverage, and divided record as determinants of equity risk, Journal of Finance 30, Sept., 1015-1026. Comanor, W.S. and T.A. Wilson, 1967. Advertising, market structure and performance, Review of Economics and Statistics 49, Nov., 4233440. Curley, A.J., J.L. Hexter and D. Choi, 1982, The cost of capital and the market power of firms: A comment. Review of Economics and Statistics 64, Aug., 519-523. Errunza, V.R. and L.W. Senbet, 1981, The effects of international operations on the market value of the firm: Theory and evidence, Journal of Finance (Proceedings) 36, May, 401-417. Hirschey, M., 1982a, Market power and foreign involvement by U.S. multinationals, Review of Economics and Statistics 64, May, 343-346. Hirschey, M., 1982b, Intangible capital aspects of advertising and R&D expenditures, Journal of Industrial Economics 30, June, 375-390. Hughes, J.S., D.E. Logue and R.J. Sweeney, 1975, Corporate international diversification and market assigned measures of risk and diversification, Journal of Financial and Quantitative Analysis 10, Nov., 627-637. Johnson, R.A. and D.W. Wichern. 1982, Applied multivariate statistical analysis (Prentice-Hall. Englewood Cliffs, NJ). Lall, S., 1980, Monopolistic advantages and foreign involvement by U.S. manufacturing industry, Oxford Economic Papers 32, March, 102-122. Senbet, L.W. and H.E. Thompson, 1982, Growth and risk, Journal of Financial and Quantitative Analysis 17, Sept.. 331-340. Subrahmanyam, M.G. and S.B. Thomadakis, 1980, Systematic risk and the theory of the firm, Quarterly Journal of Economics 97, May, 437-451. Sullivan, T.G., 1978, The cost of capital and the market power of firms, Review of Economics and Statistics 60, May, 209-217.