Firm Performance and Foreign Ownership in Africa: Evidence from

Regional Program on Enterprise Development

Discussion Papers

Firm Performance and Foreign Ownership in Africa: Evidence from Zimbabwe, Ghana and Kenya Vijaya Ramachandran and Manju Kedia Shah RPED Paper No. 81 August 1998

The views expressed in this paper are solely those of the authors. They do not necessarily represent the views of the World Bank or its member countries and should not be attributed to the World Bank or its affiliated organizations.

ABSTRACT This paper examines the effect of foreign ownership on value added of firms in sub-Saharan Africa, using firm-level data from the Regional Program on Enterprise Development at the World Bank. The econometric analysis shows that foreign ownership has a significant effect on value added only when it exceeds a majority share. The results for Africa are consistent with the existing literature on foreign investment which argues that majority ownership creates appropriate incentives and provides greater opportunity to raise firm-level value added.

1 SECTION I: THE ROLE OF FOREIGN INVESTMENT IN AFRICAN INDUSTRIAL DEVELOPMENT

There is probably no greater economic challenge than that of generating growth in sub-Saharan Africa. One of the key questions concerns the appropriate role for multinational corporations. Should they be allowed in? And on what terms? To answer these questions, we need to understand the relationship between foreign ownership and the value added in the manufacturing sector. Some of the literature on economic development in Africa argues that Africa does not have the initial conditions to ensure the success of foreign firms or even large local firms in the industrial sector (Stewart et al, 1992). In particular, foreign firms have been criticized for not making a significant contribution to economic development. In their book, Alternative Development Strategies in Sub-Saharan Africa, Stewart et al write: “...recent experience suggests that direct foreign investment cannot be relied on as a substantial support for the balance of payments, nor as a panacea for the efficiency problems of African industry. Prospects for increasing direct foreign investment in the current environment are also poor as investors switch to richer markets, with more advanced facilities and skills.” (Stewart et al, 1992, p.21)

Stewart et al conclude that “the main emphasis of an industrialization strategy should be on the development of industrial firms owned and managed by Africans” (p. 25).1

Another common criticism is that multinationals are too capital intensive. Our data, summarized in the table below, show capital-labor ratios for foreign and local firms in our sample:

1

Interestingly enough, Lall argues later in the book that “ownership patterns have been skewed to promote Africanisation faster than is economically efficient.”

2 Capital-labor ratios (capital measured in US$): Local firms

Firms with foreign equity

Ghana

5216.8

9958.8

Kenya

11269.7

17018.4

Zimbabwe

9110.2

19647.6

It is in fact clear that firms with foreign equity are more capital intensive than their local counterparts. However, it is not clear that greater capital intensity alone is grounds for dismissing multinationals from Africa. One critical question that needs to be answered concerns the performance of multinational firms vis a vis local firms. Also, we need to examine different types of foreign ownership (majority foreign ownership, minority foreign ownership and joint ventures) and their effect on value added in the industrial sector in sub-Saharan Africa.

SECTION II: FOREIGN OWNERSHIP AND VALUE ADDED

The literature on foreign ownership is extensive and presents many interesting testable hypotheses. Amongst these is the hypothesis that foreign ownership is positively correlated with value added of the firm.2 This hypothesis is based on the notion that foreign ownership

2

Value added is used instead of firm profitability because firms are much more reluctant to report profits than the value of sales and the costs of raw materials. Therefore, rather than rely on profit figures (which are missing in many cases), we construct net value added from the information provided on sales and costs of inputs.

3 brings in new technology, more productive techniques, better management skills, better training methodologies and various intangible benefits that raise value added (Dunning 1970; Caves 1974; Dunning and Pearce 1977; Globerman 1979; Blomstrom 1983, 1989; Kokko 1992; Biggs, Shah and Srivastava, 1995a; Harrison 1996).3 The argument here is that foreign firms have greater opportunity than local firms to make investments that raise value added. Thus, the first hypothesis we test in this paper is whether or not foreign ownership has a significant effect on value added. We test this hypothesis with two measures of foreign ownership--share of foreign equity in the firm, and a dummy that is set to 1 if the firm has any foreign equity.

The second set of hypotheses focuses on incentives generated by majority versus minority ownership. The literature in this area argues that share of ownership often determines the degree of control over firm profits (Telesio 1979; Benvignati 1983; Chen 1983; McMullen 1983; Davidson and McFetridge 1984; Mansfield 1984; McFetridge 1987; Pisano 1989; Blomstrom and Zejan 1989; Lee and Mansfield 1996). This is due to the fact that the rentextraction potential of the foreign parent may be directly related to how much equity it controls in the local firm.

3

The exact nature of the relationship between foreign ownership and firm profitability is very difficult to identify. Foreign ownership captures intangibles such as quality of management or worker training that can affect firm productivity. Many studies have found foreign ownership to be important in determining firm profits. One exception is the study by Vendrell-Alda (1978)--after controlling for many industrial and strategic factors affecting profitability, he finds that there is no significant residual productivity due to foreign ownership per se. Our study examines the effect of foreign ownership on value added, recognizing that value added reflects variation in both productivity and rents.

4 A corollary of this literature is that a greater share of ownership means greater control over profits which in turn implies greater incentives to invest in training, education, and technology to raise firm profits (Ramachandran, 1993). Thus, if the parent firm has the option to invest in partial ownership versus full ownership, it needs to consider the net benefit of each type of ownership. If the foreign firm has partial equity holdings and the firm is managed by a local owner, the foreign firm avoids the administrative and other costs of alien ownership and receives a share of the profits correlated with its share of equity. However, the local manager may have the opportunity to divert revenues due to the fact that the foreign shareholder does not have managerial control of the firm. This is particularly true when the foreign partner is the minority shareholder. The extent of this diversion is a function of the flows of information between the local subsidiary and its parent firm, the extent to which contracts between the two are enforceable, and whether the foreign parent is able to participate in firm decision making as a minority shareholder (often thousands of miles away). Thus, revenue diversion may lead to reduced incentives for the foreign firm to raise value added in firms which are partially foreignowned.

We can test the hypothesis that firms with a majority share of foreign ownership will exhibit higher value-added because there is both a greater opportunity to raise value added and greater incentive to raise value added.4 We test this hypothesis with several econometric specifications,

4

Presumably, local owners also have an incentive to maximize profits. However, we hypothesize that firms that are majority locally-owned generally do not have good access to technology, management skills and training in the countries under consideration, and may not be able to invest in productivity raising activities to the same extent as their foreign counterparts.

5 setting the foreign ownership dummy to 1 if foreign ownership exceeds 50 per cent, 55 per cent and 65 per cent. We also present results that include foreign ownership as a continuous variable, to see whether foreign ownership is correlated with value added.

The theoretical approach is straightforward. A standard Cobb-Douglas production function is used in the analysis. While we are aware that the Cobb-Douglas production function is a very special form with many limitations, it is arguably a good first approximation. Furthermore, the use of a production function of greater complexity makes unreasonable demands on these data.5

The traditional Cobb-Douglas production function is specified in the following manner: Q= AK a Lß

(1)

where Q is value added, K is the capital stock at replacement value, and L is the number of workers. The factors that contribute to productivity can be included in the A which is a parameter that measures productivity-enhancing investments. Therefore, A= f(X), where X is a vector of firm-specific factors including productivityenhancing measures such whether or not the firm has a worker training program, the education level of the general manager, and the amount of foreign equity in the firm.

5

The Cobb-Douglas production function represents a special case of Constant Elasticity of Production (CES) Production Functions where there is unit elasticity of substitution between labor and capital. Therefore, a strong assumption is imposed on the data. However, the Cobb-Douglas production function is probably the most appropriate specification for these data. Griliches and Ringstad (1971) found there was not much to be gained from moving to a more flexible form of the CES production function. Also, due to structural adjustment and economic liberalization, market structure is relatively competitive (or at least not as heavily rent-seeking and competition-constrained as it used to be).

6

The empirical estimation arising out of the theoretical model can be described in the following manner for firm j: ln(Qj ) = ln (Aj) + aln (Kj ) + ß ln (Lj ) + eQj

(3)

where Qj is the value added for firm j, Aj is the vector of productivity-enhancing measures, Kj is firm j’s replacement value of capital, Lj is the firm j’s employment level as measured by total number of workers, and eQj is the error term in the regression.

SECTION III: ECONOMETRIC MODELS AND RESULTS

The results of six regression models are presented in this section, along with some descriptive statistics to orient the reader to the data. Tables I-V describe various characteristics of firms in Zimbabwe, Ghana, and Kenya broken down by ownership category, as well as the results of the econometric estimations of firm-level value added.6 The data consist of 132 firms from Zimbabwe, 134 firms from Ghana, and 150 firms from Kenya drawn from four sectors--food processing, wood and furniture, textiles, and metalworking. Tables I-V present descriptive

6

Earlier studies have examined the determinants of productivity in Africa. Biggs, Shah and Srivastava (1995a) contains an in-depth analysis of technical efficiency, learning effects and technological capabilities of firms in Kenya, Zimbabwe and Ghana. Biggs and Raturi (1997) examine the determinants of competitiveness, focusing on the use of technical licenses, training and acquisition of know-how. Biggs, Shah and Srivastava (1995b) examine the returns to worker training that takes place within African firms. All these studies show that foreign ownership (measured as a continuous variable) is significant i.e. foreign firms are more productive and they invest more in worker training than their locally owned counterparts.

7 statistics from the first round of surveys in each of the above-mentioned countries.7 Table I describes value added per worker for each of five ownership categories (wholly locally owned, firms with 1-55 percent foreign equity, firms with greater than 55 percent foreign equity, firms with greater than 65 percent foreign equity and firms that are 100 percent foreign-owned). Table I shows that value added per worker increases with the share of foreign ownership in the firm. Firms with 100 percent foreign equity have the highest value added in Zimbabwe and Ghana. Kenyan firms that are 100 percent foreign owned have lower value added than those that are majority foreign-owned, but are significantly higher value added per worker than firms that are locally owned or minority foreign owned. These numbers are consistent with the theory that foreign ownership is correlated positively with value added per worker.8 Tables II shows that firms with foreign ownership are generally larger, which is not surprising. The total number of workers in the firm is used as the best available measure of firm size and the data indicate that there is a fairly large increase in firm size when foreign equity exceeds 50 per cent. Table III shows that foreign firms invest in worker training programs to a greater extent

7

The data for Ghana were collected in 1991. The data for Kenya and Zimbabwe were collected in 1992. (Two subsequent rounds of surveys have been completed, yielding panel data for use in future work). The original sample of firms consisted of 200 firms in each of the three countries, covering the entire size distribution of firms. More than 50 per cent of the firms that were dropped from the sample were dropped because of missing values on the variable that measures capital stock. Some of the dropped firms are micro-enterprises of less than 5 workers doing “batch jobs.” Other observations were dropped due to negative values of value added. Finally, a few extreme outliers with improbable values of capital and labor were discarded. 8 Foreign ownership in Africa is sometimes ambiguous. We define a firm to be foreign-owned according to the nationality of the owner. However, firms owned by Africans of Caucasian descent may possess many of the characteristics of multinational firms in that they may have better access to overseas credit, education, and technology. We have counted these firms as being locally owned because the nationality of the owner is African. This may weaken our results slightly by making the contrast between foreign and local firms seem less sharp. In the Kenyan case however, we control for

8 than locally owned firms, and that worker training programs are more prevalent in firms which have majority foreign ownership in Ghana and Zimbabwe. Kenyan firms do not show this result. Firms with foreign ownership tend to have better trained managers, as Table IV shows, although this difference is particularly noticeable between wholly locally-owned firms and firms with any degree of foreign ownership. Table V shows the distribution of firms by ownership category across the four major industry categories--food, wood and furniture, metal and textiles. While locally owned firms are concentrated in the textile and garment industry, firms with greater foreign equity are dispersed to a greater extent across food, metal and textiles. Each country has a small share of foreign ownership--30% of firms in Zimbabwe, 16.4% in Ghana, and 22% in Kenya have some share of foreign equity. Of the 104 foreign firms in the sample, 26% are in the food sector, 21% are in wood and furniture, 34% are in metal, and 19% are in textiles.

The econometric specifications tested in this analysis try to control for different factors that may determine value added.9 Controlling for worker training programs, industry specific effects, education level of the general manager, and quantity of labor and capital, we look at the correlation of foreign ownership with value added. Six econometric models are estimated to determine what kind of foreign ownership matters to firm-level value added.10 All models are estimated using the ordinary least squares regression method with log value added as the

Asian ownership by using a dummy variable set to 1 if firms are Asian-owned. 9 Value added is often treated as a rough measure of firm productivity, particularly when prices and quantities cannot be separated in the data. Our hypothesis is that value added is a measure of productivity and rents, reflecting both efficiency and market power of the firm.

9 dependent variable 11. In every model, the independent variables include the two main inputs, labor and capital (measured in log terms). The model also includes dummies to control for other variables that determine value added--whether the general manager has a graduate degree, whether the firm has a training program, and sector dummies for three of the four industry categories that are included to pick up industry-specific effects.12 The variables measuring education of the general manager and worker training are included to examine the correlation of human capital, both managerial and worker-level with value added.13 Foreign ownership is measured differently in each model to test the hypotheses generated by the literature discussed in Section II. Our aim is to see if foreign ownership is significant after controlling for investment in human capital and sector specific advantages.

In the first model described in Table VI, the foreign ownership dummy is set to 1 if the firm has any foreign equity. After controlling for investment in training, education of the General Manager, labor and capital inputs and sector-specific effects, we find the foreign ownership

10

The econometric estimations report standard errors that are corrected for heteroscedasticity. Value added is measured by subtracting both direct and indirect costs from sales. Indirect costs include energy and transportation costs. One issue to keep in mind is whether firms are sensitive to differential accounting practices in their response to survey questions. Specifically, locally-owned firms may report lower value added because they are taxed on their profits (correlated with value added). This may result in a downward bias in value added for local firms. 12 Capital is measured as the replacement cost of plant and equipment, as estimated by the firm manager. Labor is measured as the number of full-time equivalent workers in the firm. 13 Worker training is measured as a dummy variable which is set to 1 if the firm has invested in any type of worker training program. A more careful measure would enable us to relate worker training to the productivity of workers. We simply include worker training as a measure that enhances the overall productivity of the firm. 11

10 dummy to be insignificant for all three countries.14 In the second model, foreign ownership is treated as a continuous variable. This model also tests the first hypothesis discussed in Section II, namely that there is a positive correlation between foreign ownership and firm-level value added. The results of this model are presented in Table VII. They show that labor and capital are significant in determining value added. The education level of the general manager is not significant in any of the regressions. The training dummy is significant at the 1 percent level of confidence for Zimbabwe only. The sectoral dummies indicate that there is a comparative advantage for the food processing sector in all three countries (the coefficients are large in all three regressions and statistically significant at the 5 percent level for Zimbabwe and Ghana). Most interesting of all is the size and significance of the foreign ownership variable. Although the coefficients for Zimbabwe and Ghana are statistically significant, the size of the coefficient is very small for all three countries, indicating that foreign ownership, measured as a continuous variable, is not highly correlated with value added.

The third model presented in Table VIII tests the hypothesis that majority ownership is correlated with value added. In this model, the foreign ownership variable is transformed into two dummies that are set equal to one if foreign ownership is between 1-50 percent and greater than 50 percent respectively (zero denotes wholly local ownership). This model tests the hypothesis that majority foreign ownership is correlated with value added. Although the

14

A dummy which is set to 1 for firms which are Asian-owned is included in the regressions for Kenya. Based on the existing literature and our observations from field work, it is clear that Asianowned firms in Kenya are significantly different than non-Asian owned firms. These differences will be explored further in future work.

11 majority foreign ownership dummy is positive and has a fairly large coefficient compared with the foreign ownership coefficient in Tables VI and VII, the results are not overwhelming. Only the coefficient on the Ghana regression is statistically significant. These results do not allow us to confirm the hypothesis that a simple majority foreign ownership (as measured by foreign equity greater than 50 per cent) is correlated with value added.

The fourth model presented in Table IX disaggregates ownership differently to test for shifts in value added with different levels of foreign equity. The foreign ownership dummies are set to one over two possible ranges of foreign equity--1 to 55 percent, and greater than 55 percent. The excluded category is local ownership. These results reveal that a foreign ownership share of greater than 55 percent is correlated with higher value added. The coefficients on the ownership dummy that measures foreign equity of greater than 55 per cent is greater in magnitude than the foreign ownership dummy in the previous regression (measuring equity of greater than 50 per cent) and is statistically significant for all three countries at the 10 percent level of confidence.15

The fifth model presented in Table X tests yet another specification. One of the foreign ownership dummies is set to one if foreign equity is 65 percent or greater and is zero otherwise. The other is set to one if foreign equity is between 1 and 65 percent of the firm and the excluded category is wholly locally-owned firms. The coefficient on the ownership dummy

15

One interesting point is that foreign firms sometimes negotiate complete control over managerial decision making even if they do not have majority share in the local subsidiary. We do not

12 measuring greater than 65 percent foreign equity is significant at the 5 percent for all three countries, confirming that majority ownership of greater than 65 percent is significantly correlated with value added. Thus, there is an upward shift in value added due to the increase in share of foreign equity in the firm beyond 65 percent. The econometric results are very robust to minor variations in specification.

Table XI shows the results of the pooled regressions. Data from all three countries were pooled with dummies for Kenya and Ghana. The results are similar to those described in earlier tables; the coefficients on majority foreign ownership (at 55 percent and 65 percent) are large and significant while the coefficient on minority ownership is not. When foreign ownership is included as a continuous variable, it is significant but very small in size (0.004). Table XI also shows that value added in the food sector for all three countries is higher, and that the differential between Zimbabwe and the other two countries is positive and statistically significant at the 1 per cent level of confidence.16

Table XII shows that a 10 percent increase in capital inputs will result in an increase in value added of 2.7 to 4.0 percent for all firms in our sample. The increase is between 8.0 and 12.5 percent for firms with a foreign equity share of greater than 55 percent, and between 8.5 and

have the information to isolate these cases but acknowledge that they may be present in our data. 16 Two other specifications were run with the pooled data. The first specified dummies for foreign equity that were set to 1 for foreign equity less than 49 percent, 50 percent, and greater than 50 percent. The second specified dummies for foreign equity that were set to 1 for foreign equity less than 45 percent, 45-55 percent, and greater than 55 percent. In both cases, only the majority foreign equity dummy was significant at the 5 percent level of confidence.

13 16.5 percent if this share exceeds 65 percent. Similarly, an increase in labor by 10 percent will raise value added from 6.3 to 8.6 percent for all firms, while firms with a share of foreign equity greater than 55 percent see increases of 10.4 to 15 percent, and firms with greater than 65 percent foreign equity show increases of 10.9 percent to 19.3 percent.17

SECTION IV: CONCLUSION AND POLICY IMPLICATIONS

The results presented in the previous section indicate that foreign ownership does in fact affect the value added of the firm, but only beyond a certain level of ownership. They show that a majority of foreign ownership of greater than 55 percent does raise the value added of the firm; a lesser degree of participation is not significant in terms of its effect on value added. Interestingly, a 50-50 split in equity between local and foreign firm does not raise value added significantly. What seems to matter is majority ownership by the foreign owner. Majority ownership by local owners does not significantly contribute to the value added of the firm.18

17

It is interesting to note that the slope of the regression does not change when ownership increases beyond 55 percent. Econometric specifications not reported in the paper that include share of foreign equity as a continuous variable and interaction terms between share of foreign equity and a dummy set to 1 if the firm has greater than 55 percent and 65 foreign equity respectively, revealed that the magnitude of the coefficient does not increase when ownership exceeds 55 or 65 percent. Rather, majority ownership causes an upward shift in value added. 18 One interesting question is why the foreign ownership dummy does not become significant at 51 percent (i.e. when foreign ownership becomes a majority share). A possible explanation is simply that the data include measurement errors that give us an imprecise estimate. The pooled regressions do in fact show the foreign ownership variable to be significant at 51 per cent. Another explanation is that foreign owners need a clear majority (not just a 1 percent share) to invest in raising value added.

14 Why does majority foreign ownership matter? The econometric models presented in this paper control for many of the key inputs into the production process, namely the quantities of labor and capital in the production process, the level of education of the manager, worker training and various industry specific effects that determine variance in value added. Despite controlling for these factors, foreign ownership dummies measuring foreign equity greater than 55 percent and 65 percent are significant in the econometric specifications. There may be several explanations for this result. Foreign ownership may bring with it many benefits that local ownership cannot provide; examples include the “know-why” surrounding know-how, timely access to inputs, finance, maintenance personnel, and sources of information about technology and markets. Another explanation is that amongst these benefits are often intangible benefits relating to differences in the quality of labor and capital between local and foreign firms, as well as differences in the type of training received within these firms. These differences are very difficult to measure but are often highly correlated with ownership, and consequently with value added of the firm. This indicates not unsurprisingly, that even though locally-owned firms have control over profits, they may lack access to technology, skills and markets that would help them raise value added. A third possible explanation of our result is that foreign firms are able to exercise market power that results in a higher value of sales. It could be argued that multinational subsidiaries invest more in R&D, advertising, and other measures that raise barriers to entry. It is likely that our results reflect some combination of the differences in productivity and market power of foreign versus local firms. Further research needs to be done in this area, in order to understand the nature of competition in the private sector in Africa.

15 The results in this paper are consistent with the hypotheses generated by the literature on foreign ownership. The foreign ownership variable is insignificant when included as a dummy or as a measure of minority foreign ownership, and only weakly significant when measured as a continuous variable. However, it is significant for all three countries when measuring majority equity. This is an important result in that it indicates that simply entering into minority partnerships and joint ventures may not have much effect in raising value added.19 Rather, foreign firms which have a clear majority in terms of ownership appear to have greater opportunity and/or to be more motivated to transfer the sorts of skills and benefits--both tangible and intangible--discussed above.

We can reject the idea that “Africa is different,” at least where foreign firms are concerned. Rather, foreign firms appear to have greater opportunity and incentive to raise value added in the manner described by the existing literature in industrial organization. If higher value added is in fact driven by greater investment in resources and productivity-enhancing technology, it may be beneficial to pursue “open-door" policies that allow foreign investors to own majority shares or subsidiaries in the industrial sector in Africa.

19

However, it is important to keep in mind that minority foreign ownership may often be a politically palatable manner in which to open up a country to foreign investment. It may also be beneficial when it is linked to managerial control that is greater than that suggested by the share of equity owned by the foreign firm.

16 References

1. Benvignati, A.M. (1983). “International Technology Transfer Patterns in a Traditional Industry,” Journal of International Business Studies, 14 (Winter), 63-75. 2. Biggs, T., M. Shah and P. Srivastava (1995a). “Technological Capabilities and Learning in African Enterprises,” World Bank Technical Paper no.288, Africa Technical Department Series. 3. Biggs, T., M. Shah and P. Srivastava (1995b). “Training and Productivity in African Manufacturing Services,” RPED Discussion Papers, August 1995. 4. Biggs, T. and P. Srivastava (1996). “Structural Aspects of Manufacturing in Sub-Saharan Africa: Findings from a Seven Country Enterprise Survey,” World Bank Discussion Paper No. 346, Africa Technical Department Series. 5. Biggs, T. And M. Raturi (1997). “Productivity and Competitiveness in African Manufacturing,” RPED Discussion Papers, May 1997. 6. Blomstrom, M. (1983). “Foreign Investment, Technical Efficiency and Structural Change: Evidence from the Mexican Manufacturing Industry,” Ph.D. Dissertation, Gothenburg University. 7. Blomstrom, M. (1989). Foreign Investment and Spillovers. London: Routledge. 8. Blomstrom, M. And M. Zejan. (1989). “Why Do Multinational Firms Seek Out Joint Ventures?,” National Bureau of Economic Research Working Paper No. 2987. 9. Caves, R.E. (1974). “Multinational Firms, Competition, and Productivity in Host-Country Industries,” Economica, 41 (May), 176-93. 10. Chen, E.K.Y. (1983). Multinational Companies, Technology and Employment. New York: St. Martin’s Press. 11. Dunning, J.H. (1970). Studies in International Investment. London: Allen and Unwin. 12. Dunning, J. H. and R.D. Pearce (1977). U.S. Industry in Britain. Boulder: Westview Press. 13. Globerman, S. (1979). “Foreign Direct Investment and ‘Spillover’ Efficiency Benefits in Canadian Manufacturing,” Canadian Journal of Economics, 12(February), 42-56. 14. Griliches, Z. and V. Ringstad (1971). Economies of Scale and the Form of the Production Function: an econometric study of Norwegian manufacturing establishment data. Amsterdam: North-Holland Publishing Co. 15. Harrison, A. (1996). “Determinants and Effects of Direct Foreign Investment in Cote d’Ivoire, Morocco, and Venezuela,” in M.J. Roberts and J.R. Tybout (eds.), Industrial Evolution in Developing Countries, pp. 163-186. New York: Oxford University Press.

17 16. Lee, J.Y. and E. Mansfield (1996). “Intellectual Property Protection and U.S. Foreign Direct Investment,” Review of Economics and Statistics, 78,181-86. 17. McMullen, K.E. (1983). “Lags in Product and Process Innovation Adoption by Canadian Firms,” in A.M. Rugman (ed.), Multinationals and Technology Transfer: The Canadian Experience, pp. 50-72. New York: Praeger. 18. Pisano, G. (1989). “Using Equity Participation to Support Exchange: Evidence from the Biotechnology Industry,” Journal of Law, Economics, and Organization, Vol.5, no.1, pp.109-126. 19. Ramachandran, V. (1993). “Technology Transfer, Firm Ownership, and Investment in Human Capital,” Review of Economics and Statistics, 75 (November), 664-70. 20. Stewart, F., Lall, S., and S.M. Wangwe (1992). Alternative development strategies in sub-Saharan Africa. Basingstoke: Macmillan. 21. Telesio, P. (1979). Technology Licensing and Multinational Enterprises. New York: Praeger. 22. Vendrell-Alda, J.L.M. (1978). Comparing Foreign Subsidiaries and Domestic Firms: A Research Methodology Applied to Efficiency in Argentine Industry. NY: Garland.

18 Table I: Value Added Per Worker in US Dollars imbabwe

Ghana

Kenya Value Added in US Dollars*

Wholly locally-owned firms: (5551.6) (2278.1)

5854.9 1417.1 3145.4 (3292.2)

Firms with 1-55 percent foreign equity: 10094.0 3011.2 3959.5 (6445.8) (3051.6)

(2819.1)

Firms with >55 percent foreign equity: 14412.4 9433.1 5319.4 (8893.2) (13977.3) (4321.1) Firms with >65 percent foreign equity: 14362.9 (6380.08) (18525.7)

16306.6 (4706.4)

5340.8

Firms with 100 percent foreign equity: 16320.8 (10043.9) (22802.8)

21573.4 (4908.4)

4996.2

--------------------------------------------------------------------------------------------* Value added is measured as total annual sales minus the cost of raw materials, rent, electricity, solid fuel, and liquid fuel. All value added figures are measured in US dollars. The exchange rate used is taken from African Development Indicators published annually by the World Bank. For Ghana, the 1991 exchange rate of 367.8 cedi/USD is used because the firm survey was carried out in 1991. The 1992 exchange rates are used for Zimbabwe and Kenya; these rates are $Z5.1/USD and 32.2KSh/USD respectively.

19 Table II: Total Workers Per Firm

Zimbabwe

Total Workers Per Firm Ghana Kenya

184.5

34.0

108.3

Firms with 1-55 percent foreign equity: 467.7

94.9

104.0

Firms with >55 percent foreign equity: 535.9

228.2

697.0


120.0

541.3

Firms with 100 percent foreign equity: 201.3

146.0

597.9

Wholly locally-owned firms:

Table III: Firms with a Training Program for Workers


19.4

Percentage with a Training Program Zimbabwe Ghana Kenya 2.6 4.6

Firms with 1-55 percent foreign equity: 28.6

2.6

22.2


16.7

9.1


33.3

11.1

Firms with 100 percent foreign equity: 40.0

50.0

12.5

20 Table IV: Percentage of General Managers with graduate training

Zimbabwe

Ghana

Kenya


34.0

41.6

17.8

Firms with 1-55 percent foreign equity: Firms with >55 percent foreign equity:

57.0 68.8

70.0 100.0

57.1 70.0

Firms with >65 percent foreign equity:

60.0

100.0

63.5

Firms with 100 percent foreign equity:

70.0

100.0

58.1

21 Table V: Percentage Distribution of Firms by Industry Type, 1992 data (number of firms in each sector is in parentheses)

Zimbabwe: Ownership

Food

Wood

Metal

Textiles

0 foreign eq 1-55% foreign eq 56-100% foreign eq 65-100% foreign eq 100% foreign eq N

24.3(25) 16.5(17) 17.5(18) 50.0(7) 0(0) 21.4(3) 28.6(4) 25.0(4) 6.3(1) 43.8(7) 25.0(4) 25.0(1) 0(0) 25.0(1) 50.0(2) 20.0(2) 10.0(1) 50.0(5) 20.0(2) 39 19 34

41.7(43)

Ownership

Food

Textiles


19.7(23) 35.9(42) 25.6(30) 25.0(3) 8.3(1) 33.3(4) 33.3(4) 33.3(2) 16.7(1) 50.0(3) 0(0) 66.7(2) 33.3(1) 0(0) 0(0) 50.0(1) 50.0(1) 0(0) 0(0) 31 46 37

18.8(22)

Ownership

Food

Textiles


24.4(32) 27.5(36) 21.4(28) 22.2(2) 22.2(2) 22.2(2) 33.3(3) 9.1(1) 45.5(5) 36.4(4) 9.1(1) 11.1(1) 55.6(5) 33.3(3) 0(0) 12.5(1) 50.0(4) 37.5(3) 0(0) 37 52 40

55

Ghana: Wood

Metal

26

Kenya: Wood

Metal

26.7(35)

39

22 Table VI: OLS with Foreign Ownership Dummy Dependent Variable is Log Value Added Zimbabwe

Ghana

Kenya

Intercept

4.44*** (0.47)

3.28*** (0.41)

4.49*** (0.49)

Log (capital)

0.39*** (0.06)

0.35*** (0.06)

0.27*** (0.06)

Log (labor)

0.64*** (0.09)

0.63*** (0.12)

0.86*** (0.09)

Educ (GM)

0.16 (0.14)

0.35 (0.22)

-0.06 (0.18)

Training Dummy

0.59*** (0.16)

0.79* 0.10 (0.46) (0.20)

Food

0.43* (0.17)

0.89*** (0.32)

0.34 (0.23)

Wood

0.21 (0.33)

0.31 (0.27)

-0.34 (0.21)

Metal

0.18 (0.36)

0.79*** (0.30)

-0.002 (0.23)

Foreign Dummy

0.25 (0.17)

0.48 (0.30)

0.34 (0.24)

Asian Dummy

0.48*** (0.18)

N 132 134 R-squared 0.86 0.79 F 105.3 66.1 __________________________________________________ The foreign ownership dummy is set to 1 if the firm has any foreign equity. *** denotes significance at the 1 percent level of confidence ** denotes significance at the 5 percent level of confidence * denotes significance at the 10 percent level of confidence

150 0.87 114.1

23 Table VII: OLS with Foreign Ownership as a Continuous Variable Dependent Variable is Log Value Added Zimbabwe

Ghana

Kenya

Intercept

4.42*** (0.46)

3.30*** (0.41)

4.51*** (0.49)

Log (capital)

0.39*** (0.06)

0.35*** (0.06)

0.27*** (0.06)

Log (labor)

0.64*** (0.09)

0.62*** (0.12)

0.86*** (0.09)

Educ (GM)

0.16 (0.14)

0.35 (0.22)

-0.06 (0.18)

Training Dummy

0.58*** (0.16)

0.73 (0.46)

0.09 (0.20)

Food (0.17)

0.43** 0.89** 0.35 (0.23)

(0.32)

Wood

0.19 (0.21)

0.31 (0.27)

-0.34 (0.21)

Metal

0.16 (0.19)

0.80** 0.00 (0.29)

(0.23)

Foreign (Cont.)

0.004*

0.01** 0.005 (0.0022) (0.005) (0.003)

Asian Dummy

N R-squared F

0.48*** (0.18) 132 0.86 106.5

134 0.79 66.9

__________________________________________________ *** denotes significance at the 1 percent level of confidence ** denotes significance at the 5 percent level of confidence * denotes significance at the 10 percent level of confidence

150 0.87 116.32

24 Table VIII: OLS with Foreign Ownership Dummies Dependent Variable is Log Value Added Zimbabwe Ghana

Kenya

Intercept

4.42*** (0.47)

3.28*** (0.41)

4.52*** (0.49)

Log (capital)

0.39*** (0.06)

0.35*** (0.06)

0.27*** (0.06)

Log (labor)

0.64*** (0.09)

0.62*** (0.12)

0.86*** (0.09)

Educ (GM)

0.15 (0.14) 0.58*** (0.16)

0.35 (0.22) 0.83** 0.08 (0.46)

-0.06 (0.17)

Training Dummy

Food Wood Metal Foreign (1-50%)

Foreign (51-100%)

0.44** 0.91** 0.36 (0.16) (0.32) 0.20 0.32 (0.21) (0.28) 0.16 0.81** 0.02 (0.19) (0.29) 0.08 0.21 (0.24) (0.37) 0.37 (0.22)

0.83** 0.51 (0.42)

Asian Dummy

N 132 134 R-squared 0.86 0.79 F 93.8 59.13 *** denotes significance at the 1 percent level of confidence ** denotes significance at the 5 percent level of confidence * denotes significance at the 10 percent level of confidence

(0.21)

(0.23) -0.33 (0.21) (0.23) 0.12 (0.36)

(0.32)

0.53*** (0.19) 150 0.87 104.06

25 Table IX: OLS with Foreign Ownership Dummies Dependent Variable is Log Value Added Zimbabwe Ghana Intercept 4.40*** 3.28*** (0.47) (0.41)

Kenya 4.55*** (0.49)

Log (capital)

0.40*** (0.06)

0.36*** (0.06)

0.27*** (0.06)

Log (labor)

0.64*** (0.09)

0.61*** (0.12)

0.86*** (0.09)

Educ (GM)

0.15 (0.14)

0.32 (0.22)

-0.07 (0.17)

Training Dummy

0.57*** (0.16)

0.79* (0.46)

0.09 (0.20)

Food

0.45** (0.17)

0.88*** (0.32)

0.36 (0.23)

Wood

0.19 (0.21)

0.31 (0.28)

-0.34 (0.21)

Metal

0.16 (0.19)

0.78*** (0.29)

0.01 (0.23)

Foreign(1-55%)

0.06 (0.24)

0.30 (0.34)

0.06 (0.33)

Foreign(56-100%)

0.40* (0.22)

0.89*

0.62*

(0.48)

(0.34)

Asian Dummy

N R-squared F

0.57*** (0.19) 132 86.4 94.05

134 79.6 58.98

*** denotes significance at the 1 percent level of confidence ** denotes significance at the 5 percent level of confidence * denotes significance at the 10 percent level of confidence

150 87.2 103.17

26 Table X: OLS with Foreign Ownership Majority Dummy Dependent Variable is Log Value Added Zimbabwe Ghana

Kenya

Intercept

4.37*** (0.47)

3.29*** (0.41)

4.52*** (0.49)

Log (capital)

0.40*** (0.06)

0.35*** (0.06)

0.27*** (0.06)

Log (labor)

0.64*** (0.09)

0.63*** (0.11)

0.86*** (0.09)

Educ (GM)

0.15 (0.14)

0.33 (0.22)

-0.06 (0.18)

Training Dummy

0.58*** (0.16)

0.70 (0.46)

0.07 (0.20)

Food

0.46*** (0.17) 0.19 (0.21)

0.86** 0.33 (0.32) 0.31 (0.27)

(0.22) -0.36 (0.21)

Metal

0.15 (0.19)

0.83** -0.07 (0.30) (0.23)

Foreign (1-65%)

0.03 (0.23)

0.33 (0.32)

Foreign (66-100%)

0.45** (0.22)

Wood

1.30** 0.69** (0.65)

Asian Dummy

N 132 R-squared 0.86 F 94.6 *** denotes significance at the 1 percent level of confidence ** denotes significance at the 5 percent level of confidence * denotes significance at the 10 percent level of confidence

0.08 (0.30)

(0.35) 0.54*** (0.18)

134 0.79 59.4

150 0.87 103.5

27 Table XI: Pooled Estimations Dependent Variable is Log Value Added

Model 1 (Continuous) Intercept

4.21** (0.26) 0.39** (0.03) 0.71** (0.06) 0.11 (0.11)

Log (capital) Log (labor) Educ (GM) Dummy

0.05

Wood Metal

4.23**

4.22** (0.26)

0.39**

(0.26) 0.39**

(0.03) 0.71**

(0.03) 0.71**

(0.06) 0.10 (0.11)

(0.06) 0.10 (0.11) Training

0.04 (0.11) 0.46** (0.13) -0.08 (0.12) 0.21 (0.13)

Food

Model 2 Model 3 (Foreign>55) (Foreign>65)

0.04 (0.11)

0.46**

(0.11) 0.46**

(0.13) -0.08 (0.12) 0.20 (0.13)

(min)

0.22

(maj)

0.44**

(0.13) -0.08 (0.12) 0.20 (0.13) Foreign 0.21

(0.17)

(cont.) Ghana Kenya

N R-squared F

(0.16) Foreign 0.49**

(0.18)

(0.19) Foreign

-1.06*** (0.12) -0.56*** (0.11)

-1.05*** (0.12) -0.55*** (0.12)

420 0.89

420 0.89

0.004* (0.002) -1.06*** (0.12) -0.56*** (0.11) 420 0.89 326.59

296.97

*** denotes significance at the 1 percent level of confidence ** denotes significance at the 5 percent level of confidence * denotes significance at the 10 percent level of confidence

249.96

28 Table XII: Percentage Increase in Value Added with Foreign Ownership

With a 10 percent increase in capital: Zimbabwe

Ghana

Kenya

All firms

4.0

3.6

2.7

1-55 percent foreign

4.6

6.6

3.3

>55 percent foreign

8.0

12.5

8.9

>65 percent foreign

8.5

16.5

9.6

All firms

6.4

6.3

8.6

1-55 percent foreign

7.0

9.1

9.2

>55 percent foreign

10.4

15.0

14.8

>65 percent foreign

10.9

19.3

15.5

With a 10 percent increase in labor:

World Bank User L:\ENDATA\WORD\Electronic Papers\Foreign Ownership.doc 4/20/99 5:54 PM