Asia-Africa Trade and Investment Conference (AATIC)

Tokyo – November 1 & 2, 2004

Competitivenessand Private SectorDevelopment in AfricaCross Country Evidence from the World Bank’s Investment Climate Data

Benn EifertVijaya Ramachandran

October 2004

Headquarters1818 H Street, N.W.Washington, D.C. 20433, USA

Telephone: (202) 473-1000Facsimile: (202) 477-6391 RCA248423 WORLDDBK

European Office66, avenue d’Iéna75116 Paris, France

Telephone: (1)40.69.30.00Facsimile: (1)40.69.30.66Telex: 640661

Tokyo OfficeFukoku Seimei Building, 10th Floor2-2-2 Uchisaiwai-ChoChiyoda-Ku, Tokyo 100-0011 Japan

Telephone: (81-3)3597-6650Facsimile: (81-3)3597-6695Telex: 26838

WORLD BANK GROUPAFRICA REGION, PRIVATE SECTOR UNIT

0507090-TICAD Cover.qxd 10/15/04 11:01 AM Page 1

33665

Pub

lic D

iscl

osur

e A

utho

rized

Pub

lic D

iscl

osur

e A

utho

rized

Pub

lic D

iscl

osur

e A

utho

rized

Pub

lic D

iscl

osur

e A

utho

rized

Pub

lic D

iscl

osur

e A

utho

rized

Pub

lic D

iscl

osur

e A

utho

rized

Pub

lic D

iscl

osur

e A

utho

rized

Pub

lic D

iscl

osur

e A

utho

rized

Competitiveness and Private Sector Development in Africa:

Cross-Country Evidence from the World Bank’s Investment Climate Data

Benn Eifert Vijaya Ramachandran1

October 2004

1 Benn Eifert is a Junior Professional Associate at the World Bank. Vijaya Ramachandran is Assistant Professor of Public Policy at Georgetown University and a consultant at the World Bank. Data for this paper were generated by the Regional Program on Enterprise Development and the Develoment Economics Research Group of the World Bank. We would like to acknowledge the contributions of Linda Cotton, Jean Michel Marchat, James Habyarimana, and Manju Kedia Shah to the Africa Investment Climate Assessments, which we draw upon heavily in this analysis. We would also like to thank Alan Gelb for his extensive and very useful comments. The views presented in this paper are solely those of the authors.

2

Contents

1. Introduction 2. State of Manufacturing in Africa Competitiveness in Africa: Broad Benchmarks 3. Enabling Environment Access to and Cost of Finance in Africa Macroeconomic Policy and Instability Market Structure Infrastructure Labor Force Skills and Human Capital

Interaction with Public Sector: Taxation, Regulation, Judiciary, Governance, and Corruption

4. Overall Benchmarking: Comparison of a Simple IC Index and CPIA Ratings 5. Conclusion The findings, interpretations, and conclusions expressed herein are those of the author(s) and do not necessarily reflect the views of the Board of Executive Directors of the World Bank or the governments they represent.

3

Abstract Investment Climate Survey data are now available for several member countries of the World Bank, including eight in Sub-Saharan Africa. These reports and the surveys that underpin them have generated very large quantities of data on many dimensions of the business environment. This paper is an attempt to synthesize some of the key, commonly available indicators in a comparative framework, focusing on Africa and using countries such as China, India, Morocco, and Bolivia as international reference points. From indicators in the areas of macroeconomic stability, finance, market structure, infrastructure, skills, customs procedures, labor regulations, business regulations, corruption, and security, it is evident that most African business environments still have serious shortcomings compared with their international competitors. Although more analysis is needed to quantify the impact of different dimensions of the business environment on firm-level productivity, in some cases the direct costs of poor business environments to firms are quantifiable, and the results are striking. The results suggest that improved competitiveness in Africa will require lower costs of doing business and higher productivity, not lower real wages, which are not the main obstacle.

4

1. Introduction Over the past decade, analytic work carried out in the World Bank’s Africa Private Sector Group has emphasized the importance of microeconomic constraints to private sector development. Large, broad-based, competitive private sectors are still relatively rare in Sub-Saharan Africa, reflecting the pervasiveness of poor business climates and weak enabling environments that depress the productivity of existing enterprises and discourage the entry of new ones. Over the past three years, work on microeconomic constraints has also been conducted Bank-wide. The purpose of the main product of this work, the Investment Climate Assessment (ICA), is to look systematically across the dimensions of the business climate to identify and analyze key constraints on the ability of firms to produce, invest, and grow. ICAs have thus far focused on manufacturing sectors and related services, which historically have been at the core of successful industrialization and economic transformation (see box 1). A fair amount of research already exists on the African private sector. Bigsten et al. (2000) survey a number of explanations for African countries’ poor performance in fostering labor-intensive manufacturing and private sector development. The pessimists argue that Africa’s scant human capital and rich natural resource base ensure that manufactured exports will always be unprofitable.2 However, dynamic trade theory suggests that comparative advantage is partly endogenous, because a country’s production and trade are not limited by its endowed resources only but also by a process of searching and learning, stimulated by competition incentives in an appropriate institutional setting (Olofin 2002, Grossman and Helpman 1994) The policies, institutions, and infrastructure maintained by African governments—and the effects they have on transactions costs—are crucial in encouraging, or discouraging, firm-specific learning and the development of competitive advantage and export industries.3 Box 1: Manufacturing Growth and Economic Transformation in East Asia and Africa

2 See Wood (1994), Wood and Berge (1997), and Wood and Mayer (1998). However, if transport costs are high enough—and in Africa they are very high—this factor endowment is consistent with competitiveness in a wide variety of labor-intensive natural resource processing industries. 3 Collier and Gunning (1999).

From 1966 to 1988, the East Asian tigers registered rapid annual manufacturing growth rates: South Korea (16.0 percent), Taiwan (13.2 percent), Indonesia (12.1 percent), Singapore (11.1 percent), Malaysia (10.1 percent), andThailand (10.0 percent). China experienced 11.1 percent growth in manufacturing from 1980 to 2002. Overtwenty-two years, these growth rates imply eight-fold to twenty-six-fold increases in manufacturing output and rapid employment creation. The increases in human capital and major spillover effects associated with this rapidsustained growth in manufacturing eventually allowed the more advanced East Asian economies to transitioninto higher value-added products and skill- and technology-intensive industries. In contrast, Sub-Saharan Africa as a whole has averaged 1.9 percent annual growth in manufacturing between 1980 and 2002—increasing real output by half over a period in which population has nearly doubled. Manufacturing output per capita and formalsector employment has fallen, and most African economies have remained dependent on commodity exports andagriculture.

5

The completion of first-round ICAs for six countries in Sub-Saharan Africa—Eritrea, Ethiopia, Mozambique, Nigeria, Uganda, and Zambia—offers an opportunity to draw comparative lessons about the state of private sector development in Africa and the obstacles facing its acceleration. Competitiveness is a comparative concept by definition: The ability of African countries to develop competitive manufacturing sectors depends on the quality of African business environments and labor forces relative to those of the export powerhouses of the developing world. This paper presents the key findings of the ICAs in a comparative framework, bringing in data for countries such as Bolivia, China, India, and Morocco, as well as additional external and internal research to assess the strengths and weaknesses of African business climates in fostering growth and competitiveness. Although productivity analysis is needed to quantify the relative importance of different business climate factors, our preliminary sense from the ICAs is that the common major bottlenecks are macroeconomic instability, policy uncertainty, poor access to finance, and shoddy electricity service, with governance as a cross-cutting theme. African economies badly need rapid progress in these areas, and the contrast with China, India, Morocco, and even Bolivia is stark.4 On other dimensions of the business environment—such as market structure, transportation, telecom, tax administration, and regulatory quality—some countries have made real progress, while others have faltered. These bottlenecks, often along with adverse structural factors, have increased costs in African economies and hurt competitiveness. The available evidence—data on wages and indirect costs, as well as from comparisons of gross domestic product (GDP) at market prices and GDP in purchasing power parity measures—suggests that overall costs in African economies are very high, a point to which this paper will return at greater length. The Ethiopia ICA estimates that the potential gains to average firm total factor productivity (TFP)5 from improving selected investment climate indicators to the level of China are on the order of 180 percent.6 More extensive pooled productivity analysis is necessary to check the robustness of these estimates, but their magnitude is striking. Given constant returns to scale, if Ethiopia’s business climate looked more like that of China, Ethiopian firms would be able to produce the same number of goods at

4 Political instability is closely related to governance and is also a cross-cutting theme in investment climate issues, though not focused on in the ICAs. Fosu (2003) finds a substantial negative effect of elite political instability (in the form of coups, attempted coups, and coup plots) on export performance in Africa from 1967 to 1986. 5 TFP is calculated as the residual of a standardized sector production function in which value added is estimated as a function of capital and labor inputs and various business environment factors. TFP captures the efficiency of firms and the environment in which they operate, because value added is sales less materials costs and all indirect costs. 6 These estimates, which recur throughout the Ethiopia ICA, should be taken as ballpark figures, with the understanding that the left-hand-side variables (which are very specific) undoubtedly function as proxies for the broader issue areas. There may also be reverse causality issues in some areas.

6

close to a third of the inputs and costs.7 Given that Soderbom and Teal (2003) find that TFP is one of the best predictors of African firms’ propensity to invest and export, the corresponding increase in competitiveness would surely stimulate rapid growth of existing firms and entry of new firms, creating jobs and reducing poverty. This paper is a first attempt at pulling together some cross-country comparisons from the investment climate data for Africa. We have focused our efforts on quantitative comparisons of survey responses, with a view to carrying out more in-depth econometric work in future research. The paper is divided into three sections. The first section describes the state of the business climate in Africa from the perspective of broad benchmarks and indicators. The second discusses the data on the enabling environment. And the third introduces a comparative benchmarking exercise that ranks the various countries on different business climate issues.

7 This assumes constant returns to scale and should not be viewed as a precise estimate. Rather, it gives an idea of the importance of investment climate issues in competitiveness.

7

2. State of Manufacturing in Africa

Manufacturing sectors in most African countries remain small in absolute terms and as a share of GDP, particularly when compared with developing powerhouses like China and India. For the sample of Africa ICA countries, growth in manufacturing over the 2000–2002 period was in the 3–5 percent range annually, with the exception of Mozambique, which grew at over 9 percent. These current manufacturing growth rates—0–2 percent in per capita terms—are well below those observed historically in most developed countries during their early phases of economic transformation and are not high enough to drive substantial job creation and poverty reduction. In Mozambique, high growth rates can be attributed to mega-investments in capital-intensive projects (reflected in the high investment and foreign direct investment levels in table 1), which have produced few jobs at a relatively high cost and questionable in terms of sustainability and poverty impact.8

Table 1. Selected Economic Indicators, 2000–2002 GNI

per capita, $

Trade % GDP

Ag, % GDP

Investment (FDI*), %GDP*

Mfg, %GDP (growth*)

Mfg exports %GDP*

Mfg, % mrch exports*

Eritrea 160 111 21 39 (5.3) 7.5 (5.4) - - Ethiopia 100 49 52 18 (1.2) 7.0 (5.0) 0.5 9.8 Mozambique 210 79 23 40 (8.6) 13.0 (9.2) 1.1 7.5 Nigeria 290 81 35 20 (2.4) 4.1 (3.7) 0.2 0.2 Uganda 250 40 31 20 (2.6) 9.9 (2.9) 0.3 6.5 Zambia 330 75 22 18 (2.9) 11.0 (4.5) 3.7 17.0 Kenya 360 57 19 14 (0.4) 13.0 (1.0) 3.8 22.2 Botswana 2,980 126 2 27 (1.1) 4.6 (3.3) - - Mauritius 3,850 127 7 25 (2.5) 24.0 (5.6) 23.4 77.5 Madagascar 240 56 27 14 (1.3) 12.0 (-4.1) 8.0 49.8 China 940 52 15 37 (3.7) 38.0 (8.7) 19.3 88.4 India 480 31 23 22 (0.6) 15.0 (5.6) 6.7 76.5 Morocco 1,190 66 16 25 (4.2) 17.0 (4.0) 14.0 64.1 Bolivia 900 49 15 16 (9.3) 15.0 (1.9) 2.8 16.9** *Marked values are average 2000-2002; others are most recent data. **2002 value. This figure has fallen rapidly from 40% in 1999 due to oil/gas exports. Source: World Bank, World Development Indicators 2004 (Washington, DC: 2004).

8 Mozambique has a pipeline of mega-projects that may bring $10 billion in new investment between 2001 and 2010 but will only create 20,000 jobs (5,000 directly and 15,000 indirectly, at $500,000 per job). This is also true to some degree in Eritrea, where relatively strong numbers in investment and growth mask a reality of extremely high capital intensity of over $20,000 per worker and formal manufacturing employment of only 1.2 percent of the workforce.

8

Manufacturing sectors in surveyed countries also remain inward looking, with the exception of Mauritius and recently Madagascar. Few African firms export at least 20 percent of their sales, particularly given the small size of their domestic markets (see figure 1). Manufactures play a much smaller role in the merchandise exports of the African countries in the sample than in China, India, and Morocco. This suggests that opening to imports and integrating into primary export markets have not led systematically to increased competitiveness in African secondary sectors, despite some country-level and cross-country evidence for a positive relationship between liberalization and productivity growth.9 Although the opening process may have had some effect, it has not been sufficient in the broader context of the business environment to push African competitiveness past the threshold where firms can rapidly increase manufactured exports. This has serious implications for diversification and vulnerability to shocks because African countries still depend on a few primary commodity exports for foreign exchange. Figure 1. Percentage of Surveyed Firms Exporting at Least 20 Percent of Production

0

10

20

30

40

50

60

Eritrea

Ethiop

ia

Kenya

Mozam

bique

Nigeria

Ugand

a

Zambia

Bolivia

China

India

Morocc

o

Competitiveness in Africa: Broad Benchmarks Slow growth and low export levels in manufacturing imply that African firms are characterized by low (though varying) levels of competitiveness.10 This is borne out in the data on specific obstacles to firm development and is also illustrated by a number of broader benchmarks.

9 See Chete and Adeola (2002a, 2002b) on Nigeria, Onjala (2002) on Kenya, Chirwa (2000) on Malawi, and Soderbom and Teal (2003) with panel data on 93 countries for the 1970–2000 period. For a more pessimistic theoretical and empirical perspective, see Azam, Calmettte, Loustalan, and Maurel (2002). 10 For instance, a COMESA-FTA study found that 75 percent of Ethiopian products were uncompetitive on the basis of ex-factory cost versus CIF price comparison.

9

Value added per worker (Y:L), the traditional measure of labor productivity, is illustrated in table 2, and its overall median values by country range from around $1,000 to nearly $5,000 overall. Specific sectors report median values as low as $500 (small wood and wood processing firms in Ethiopia) and as high as $20,000 (large chemicals firms in Kenya). Several African countries (Eritrea, Kenya, Nigeria, and Zambia) have Y:L levels surpassing Bolivia and comparable to China, India, and Morocco. However, it must be emphasized that Y:L is not a measure of the intrinsic productivity of workers or a direct benchmark of success or efficiency; in part it reflects the level of capital intensity, as demonstrated by figure 2.11 Table 2. Value Added per Worker (US$) China India Morocco Bolivia Eritrea Ethiopia Kenya Moz. Nigeria Uganda ZambiaOverall 3,893 3,357 4,583 1,636 2,822 852 4,225 975 3,221 1,255 3,185 Small 3,718 2,982 9,461 1,265 3,066 858 3,920 706 2,192 1,043 3,185 Large 3,990 5,119 1,475 2,910 1,897 742 6,475 1,456 4,085 4,107 3,031 Table 3. Capital per Worker (US$) China India Morocco Bolivia Eritrea Ethiopia Kenya Moz. Nigeria Uganda ZambiaOverall 5,356 2,132 3,387 2,849 16,209 2,371 10,767 5,302 22,247 1,743 8,917 Small 22,770 2,082 4,591 2,365 13,204 2,654 10,602 15,532 1,573 8,917 Large 3,054 2,238 2,139 5,616 32,174 1,516 11,010 11,200 23,047 6,498 7,431 Figure 2. Simple Relationship, Y:L versus K:L, Entire Sample (Africa Region and comparators)

Capital intensity (as measured by the capital to labor ratio in table 3) measures the success of African countries in fostering labor-intensive manufacturing along the lines of their potential competitive advantage in low-cost labor.12 Firms in Eritrea, Kenya, Mozambique, Nigeria, and Zambia use very large quantities of capital per worker, 11 In general, Y:L is related to the overall characteristics of the firm and the supply chain and thus includes (but is much broader than) the intrinsic productivity of workers arising to their skill, education, work ethic, and so forth. For instance, in addition to the effect of capital intensity, high materials costs arising from poor transport systems and geographic sparseness reduce value added per worker. 12 The samples are fairly comparable across countries because the overlap of key sectors is quite large. In addition, the stratified random sample is drawn in exactly the same manner across countries.

10

given the level of development of those countries, with exceptionally high capital intensity in Eritrea ($16,209) and Nigeria ($22,247). Uganda ($1,743) and Ethiopia ($2,371) seem to have been more successful in fostering labor-intensive manufacturing. Partly as a result of this, employment in manufacturing firms represents 29 percent of formal sector employment in Uganda, but close to only 1 percent in Eritrea. Small and micro firms tend to be the least capital intensive across the sample, but this pattern is by no means uniform. Firms producing textiles, garments, and leather products tend to cluster at the lower end of capital intensity, whereas metal, food-beverage, and chemical industries cluster at the higher end. In addition, African firms’ large quantities of capital are used very inefficiently, as demonstrated by data on capacity utilization (figure 3). Several African countries operate in the range of 50 percent of capacity. Zambia, Kenya, and Uganda are closer to 60 percent, a more respectable level, but still well below the 70-80 percent range where successful manufacturing exporters and developed countries are clustered. Figure 3. Capacity Utilization in Manufacturing, Selected Countries

0102030405060708090

Cam

eroo

n ea

rly 1

990s

Ethi

opia

200

1

Moz

ambi

que

1999

Zam

bia

90s

Tanz

ania

ear

ly 1

990s

Nig

eria

199

9

Eritr

ea 2

001

Gha

na e

arly

199

0s

Boliv

ia 1

999

Tanz

ania

200

1

Uga

nda

2001

Keny

a 20

01

Zam

bia

2001

Zim

babw

e ea

rly19

90s

Keny

a ea

rly 1

990s

Mor

occo

199

9

Cot

e d’

Ivoi

re e

arly

199

0s

Uni

ted

Stat

es 2

002

Thai

land

late

199

0s

Chi

na 2

001

%

Sources: Lindauer and Velenchik (1994); and RPED Surveys (1991-2003). Labor costs are one candidate for the source of African firms’ lack of competitiveness, high capital intensity, and low efficiency. Unit labor costs (ULC) provide a lens of sorts (though imperfect, as described below) into the relative cost and productivity of labor. ULC measures the average cost of labor per unit of output, defined in U.S. dollars as

e1

QwL

where w is the manufacturing wage; L is the amount of labor employed;

11

Q is a physical measure of output; and e is the exchange rate defined as domestic currency per U.S. dollar.

Because it is very difficult to obtain comparable physical measures of output across different countries, we use an approximate measure of ULC, the ratio of wages to value added at the firm level. By definition, unit labor costs are high in countries that have high wages and low value added per worker. For a country to have a low (competitive) ULC, it has to do one of three things (or a combination thereof): (i) keep nominal wages low, (ii) keep its exchange rate competitive, or (iii) increase its labor productivity. Figure 4 provides aggregate data on ULC for several countries in Asia and Sub-Saharan Africa, and table 4 disaggregates the most recent wave of ULC data by sector. Figure 4. Wage Cost / Value Added (approximating unit labor costs)

Source: Lindauer and Velenchik (1994); and RPED Surveys (1991-2003). Table 4. Median ULC by Sector, Current Wave of Surveys Overall Chemicals,

paints Food, beverage

Metal, metal products

Textiles, garments, leather

Wood, wood products

China 0.29 0.27 0.39 India 0.26 0.28 Morocco 0.54 0.52* 0.45 0.54 Bolivia 0.48 Eritrea 0.21 0.09** 0.24* 0.18** 0.26** 0.37 Ethiopia 0.37 0.28 0.42 0.41 0.42 Kenya 0.31 0.17* 0.22 0.45 0.47 0.32* Nigeria 0.23 0.16 0.15 0.21 0.37 0.25** Uganda 0.40 0.38** 0.29 0.42* 0.32* 0.62 Zambia 0.39 0.33* 0.40 0.37* 0.32 0.23** *less than 20 firms with data **less than 10 firms with data Source: Investment Climate Survey Data

12

Figure 5. ULC versus Capital Intensity, Sector-Level Data*

*One observation per sector per country Source: Investment Climate Survey Data As with the previous caveat about labor productivity, ULC should be interpreted cautiously (particularly in the aggregate). Higher K:L pushes Y:L up and thus ULC down, artificially biasing the benchmark toward capital-intensive development.13 This relationship is illustrated in figure 5. Variation in median capital intensity explains roughly 25 percent of the variance in median ULC.14 This has two implications. On the one hand, because higher K:L pushes ULC down, ULC is not an ideal benchmark of competitiveness in (labor-intensive) manufacturing. On the other hand, there is considerable variance remaining that is independent from variance in K:L, variance that reflects sectoral characteristics as well as labor-cost competitiveness.15 On the first implication, it is evident that in Sub-Saharan Africa, some countries score very well on the ULC benchmark despite their lack of competitiveness and vice versa. For instance, Africa’s only long-term success story in labor-intensive manufacturing exports, Mauritius, shows a poor ULC of 0.50 for 1987. From two years before to two years after this observation (19851989), Mauritius averaged 7.4 percent real GDP growth 13 In models of perfect competition and price adjustment, ULC is fixed at a parameter (the labor share of production). This is clearly not realistic. Assuming more generally that wages are correlated with the marginal product of labor, but not perfectly so, then increases in Q:L resulting from increases in K:L will push down ULC. 14 The ULC / K:L relationship looks weaker than the Y:L / K:L relationship, in which almost every Y:L observation lies within two points of its predicted value on the log scale, but keep in mind that the difference between plus two points and minus two points on the log scale is equivalent to a one-hundred-fold difference in productivity. 15 Studying the residuals of this regression—an attempt at “correcting” ULC for capital intensity—is quite interesting. The residuals for overall ULC in China and India are negative and large (–0.05 to –0.15), as expected, whereas those for Morocco are positive and quite high (which makes sense given its very high labor costs). Oddly, Nigeria and Eritrea score well with this correction (though less so than China and India); Uganda and Ethiopia come in next, and Kenya, Mozambique, and Zambia have the highest “corrected” ULC. The fact that Nigeria and Eritrea score reasonably well is reason to worry about this benchmark as well; perhaps the correction is inadequate, or perhaps there are other factors biasing ULC.

13

and 13.3 percent real manufacturing growth. Uganda, a strong performer through the 1990s, shows a mediocre ULC (0.39) for that period, and a very poor ratio (0.52) for 2002. Meanwhile, Nigeria—by all accounts not a highly competitive country—registered the best ULC of any African country for 1983 (0.20) and 2001 (0.26), comparable to the East Asian tigers. Similarly, Eritrea registered 0.24 overall ULC, but exports very few manufactures. A large part of the explanation is that Mauritius, and more recently Uganda, has been known for labor-intensive manufacturing, whereas Nigerian and Eritrean enterprises tend to be very capital intensive. However, ULC comparisons between Asia and Africa are compelling; with a few exceptions with very high K:L ratios, Sub-Saharan Africa has higher ULC than Asia at roughly equivalent stages of development. This is almost certainly an indication of the relative lack of competitiveness of African countries; the Asian tigers fostered highly labor-intensive development through the 1960s and 1970s, so differences in capital intensity bias the imputed gap in competitiveness between most African and Asian countries downward. However, this does not imply that high real wages dominate business costs in Africa. Most African workers receive less compensation than their counterparts elsewhere (see table 5). Wages at the higher end of the African sample are comparable to Bolivia and India, but much lower than in China and particularly Morocco. In addition, the fact that costs are much higher in most African countries implies that the real incomes of African workers are even lower in comparison (see figure 6). A comparison of GDP at market prices to GDP in purchasing power parity indicates that aggregate costs across the continent (excluding South Africa) are 80 percent higher than they “should” be given per capita GDP. 16 Abnormally high costs across African economies imply that high labor costs for firms (in absolute terms or relative to productivity) are not inconsistent with very low real wage income for workers. Table 5. Median Value of Annual Wages and Benefits per Worker (US$) China India Morocco Bolivia Eritrea Ethiopia Kenya Mozambique Nigeria Uganda Zambia1170 850 2400 790 745 310 860 675 840 415 970 Table 6. Labor Costs as Share of Total Costs (%) China India Morocco Bolivia Eritrea Ethiopia Kenya Moz. Nigeria Uganda ZambiaSmall 0.15 0.13 0.28 0.24 0.20 0.12 0.13 0.27 0.12 Large 0.17 0.14 0.27 0.24 0.19 0.11 0.15 0.30 0.12 Overall 0.15 0.12 0.29 0.19 0.23 0.23 0.12 0.26 0.11 0.17 0.12

16 Based on nonlinear regressions of the regional ratio of market GDP to purchasing power parity GDP on the natural log of regional per capita income for AFR, MENA, LAC, SAR, EAP, ECA, and OECD. Log per capita income explains 92 percent of the variance in the GDP:PPP ratio in the regional data and 80 percent in the country-level data.

14

Figure 6. Cost Premiums in Africa Relative to Level Predicted by per Capita GDP

0

20

40

60

80

100

120

SSA lessSouth Africa

CPIA quintile 1poor countries

quintile 2 quintile 3 quintile 4 quintile 5

cost

pre

miu

m o

ver l

evel

s pr

edic

ted

by p

.c. G

DP, %

The issue of high aggregate costs is crucial to our discussion. Not only do high costs create a gap between effective wages paid and income received, but high costs also have major direct effects on firms, effects that are relatively large compared with labor costs alone (which account for a relatively small share of total firm costs; see table 6). This wave of data shows overall median labor costs as a share of total costs in Africa at 17 percent,17 which is consistent with the findings of previous surveys discussed in Gelb and Tidrick (2000). As such, the business environment factors that influence the other 83 percent of firm-level costs are crucial for competitiveness. From the discussion thus far, the following four stylized facts emerge:

• African firms face relatively high labor costs relative to productivity. • Aggregate costs across African economies are very high, pushing up firms’ costs

and pushing down workers’ real wage incomes. • African workers’ real wage incomes are in fact quite low. • Labor costs account for a relatively small share of the total costs of African firms.

The last three imply that wage levels per se are not the primary obstacle to African competitiveness. There is little potential for increasing competitiveness through wage reductions when workers’ real wage incomes are already very low and labor costs are a small share of total costs.18 Competitiveness must come from increased productivity and largely from lower non-labor costs and greater development of worker skills. Therefore, the emphasis on improving productivity must include the business environment factors that drive up non-labor costs and drive down productivity in Africa—factors associated with weak financial systems, macroeconomic instability, concentrated market structure, infrastructure and service deficiencies, overregulation, 17 Note that more capital-intensive countries have smaller labor costs as a share of total costs. 18 The possible exception is Mozambique, the one relatively higher-wage country where production is capital-intensive but labor costs are a significant share of total costs.

15

corruption, poor security, and so forth. For instance, figure 6 demonstrates that aggregate costs are much higher in African countries with poor policies and institutions, a point that bolsters the focus on business environments and governance. The various dimensions of the business environment are the subject of the remainder of this paper. In some cases their importance can be quantified relative to that of wage levels, and the results are striking. For instance, if Kenya’s poor electricity system were improved to the quality of China’s, the resulting cost savings and productivity increases for Kenyan firms would be financially equivalent to the near-total elimination of their labor costs.

16

3. Enabling Environment The evidence on high aggregate costs and low competitiveness suggests that inhospitable African business climates present major obstacles to economic growth. Their weaknesses are certainly influenced by geography—African economies are very sparse, with negative implications for economies of scale and transactions costs—but are in great part engendered by governments (Collier and Gunning 1999). Poor business climates are inseparable from the performance of African firms, a fact that is reinforced by the finding of Soderbom and Teal (2003) that total factor productivity levels (determined by the whole spectrum of cost-influencing factors) are the major determinant of firm investment and exports in Africa.19 This section discusses the different aspects of the enabling environment, including finance, macroeconomic stability, market structure, infrastructure, human capital, taxation, regulation, judicial systems, governance, corruption, and security. Access to and Cost of Finance in Africa One of the most important bottlenecks facing firms in Sub-Saharan Africa is access to reliable, inexpensive financing. But not all scholars agree on this. Bigsten et al. (1997) argues that financial constraints are not the most important bottleneck in their sample of African firms, in part based on the apparent coexistence of high profits and low investment.20 However, when firm managers were surveyed about the importance of different constraints on their ability to do business effectively, many described access to and the cost of finance as a major or severe obstacle (figure 7). By and large, managers’ perceptions are borne out by the objective data (see tables 7 and 8); when compared with China, Morocco, and India, African firms have less access to loans and overdrafts, use more internal funds and retained earnings to fund investments and operating costs, pay much higher interest rates, and are required to register many more assets as collateral. Market failures are rampant: Small firms are less likely to get a loan, controlling for variables typically assumed to explain why this is so; relationships and ethnic connections are very important in access to credit; and outstanding debt is positively related to obtaining future lending (Bigsten et al. 2000).Where data are available, it is evident that shortfalls in the quality of financial systems matter quite a bit for firm competitiveness; the Ethiopia ICA estimates that if the percentage of firms with access to overdrafts doubled from 26.6 percent to 53.2 percent, average firm-level TFP would increase by 31 percent.

19 Again, with value added as sales less materials and indirect costs, TFP captures the efficiency of firms and the environments in which they operate. 20 Their analysis was based on surveys of Cameroon (1992–1995), Ghana (1991–1993), Kenya (1992–1994), and Zimbabwe (1992–1994)

17

According to the investment climate data, Mozambican firms have the greatest problems with respect to finance; 75 percent rated access to finance as a major or severe obstacle, and 84 percent said the same about its cost. The Mozambican banking sector suffered from inadequate and poor supervision throughout the 1990s, leading to a number of major insolvencies and the loss of public confidence. Today, the ratio of M2/GDP is only 25 percent. The scarcity of finance has meant that only 7 percent of working capital and 10 percent of investments are financed from bank loans, which carry annual interest rates of nearly 30 percent (13-18 percent in real terms). Cash flow problems are enormous, as funds are tied up in raw materials, finished goods inventories, overdue payments, and refunds owed by the government.21 Given the weakness of the formal banking sector, supplier credit could play a potentially major role in facilitating business operations, but poor information and weak contract enforcement have led to a heavily cash-based environment, with only 0.5 percent of firms’ operating expenditures financed by trade credit. Only 40 percent of firms indicate the availability of supplier credit, and those provide credit on an average of 34 percent of their sales, compared with 75 percent in Nigeria. Problems accessing loans and supplier credit are particularly significant for smaller firms, due to high transactions costs related to problems of information, communication, and enforcement. Mozambican firms generally require long-established contracts and strong reputations to be able to obtain bank finance, generating major barriers to entry. Zambian firms also face a very difficult financial environment. Access to finance in Zambia is better than in Mozambique—31 percent and 47 percent of firms have loans and overdrafts, respectively—but excessive government borrowing (65-80 percent of all commercial borrowing in Zambia) has propelled interest rates to nearly 30 percent for bank loans and 45 percent for overdrafts. Supplier credit is more common in Zambia, and 12.4 percent of firms’ operating expenditures are financed in this way. Ugandan firms report serious difficulties with finance, although they are advantaged generally when compared with Mozambique and with respect to cost when compared with Zambia. The Ugandan financial sector is severely underdeveloped, providing only 12 percent of GDP in credit to the private sector, compared with 61 percent on average for developing countries. Imprudent banking practices and government borrowing from banking sector were a major problem in the 1990s, leading to the closing of four major banks in 1999. Portfolio quality is generally very poor, partially because of politically motivated lending. As a result of overall weaknesses in the sector, access to finance is relatively poor, with Ugandan firms only able to finance 7 percent of their working capital and 13 percent of their new investments with bank loans. Interest rates and collateral requirements are not excessive by African standards, at 17 percent per year and 116 percent of loan value respectively, although both are very high compared

21 For instance, the median value of back tax refunds owed to firms by government in Mozambique is 13 percent of sales.

18

with China. Trade credit is common, but the sums involved are usually small due to weak contract enforcement. Rural credit is particularly difficult to access, with no formal lending institutions operating in rural areas due to widespread customary land tenure and the associated lack of collateral. The Nigerian banking sector is larger and more developed than many in Africa, but even there firms still suffer from serious problems. Funds are generally available in the system, but information asymmetries and contract enforcement problems lead many banks to focus on consumer imports and speculation in foreign exchange markets rather than lending to the productive sector.22 Most large-scale enterprises in Nigeria have reduced their borrowings from banks due to high interest rates (around 23 percent per year) and the short-term nature of available loans. Less than 16 percent of the sample reported having loans of more than one year in term. Banks are particularly unwilling to lend to the small and medium enterprise (SME) sector because of its high perceived risks. Some 38.5 percent of Nigerian firms describe themselves as credit constrained, including 48 percent of microfirms and 25 percent of very large firms. Those same problems distort the use of trade credit; 75-80 percent of firms report giving or receiving trade credit, but many SMEs claim that larger companies use their leverage to extract trade credit from their smaller suppliers by not paying for goods for extended periods of time. However, between loans and overdrafts, over 80 percent of Nigerian firms have some form of formal access to finance, which is a strong point relative to other African countries—and even when compared with China. The Kenyan financial system is more developed than that of most African countries. Access is probably the best in the sample; only 20 percent of firms are credit constrained, and about the same number that do not have access to overdrafts. Interest rates are low for Africa at less than 15 percent. Almost three-quarters of Kenyan firms identify the cost of finance as a major or severe problem, but it is reasonable to assume that the more export-oriented Kenyan manufacturing firms have a more internationally oriented reference point; however, they are still disadvantaged relative to China and Morocco. Ethiopian firms seem to be in a reasonable situation with respect to finance, although almost 38 percent of firms consider access to finance to be a major or severe problem. Interest rates are low at just over 10 percent, and the majority of firms have either a bank loan or an overdraft. Collateral requirements are also more reasonable, at close to 120 percent of the value of the loan on average. However, many firms do not yet have a long-term relationship with their bank, and information asymmetries remain a problem obstructing the extension of finance to small and medium-sized firms. Interestingly, medium-sized firms are most likely to describe themselves as credit constrained (51

22 Many Nigerian banks are taking high forex risk, with 36 banks representing 52 percent of system assets holding net forex positions in excess of 50 percent of net wealth.

19

percent do so), with small firms also well above the average. In addition, the efficiency of payments systems is very low; it takes four times as long for a foreign wire to clear through Ethiopia as it does through China, with negative implications for cash flow. Eritrean firms appear to be the best-situated among the surveyed countries in terms of finance. Access levels are high—45 percent and 49 percent of firms have access to loans and overdrafts, respectively, and interest rates are low for Africa (9.8 percent). However, this masks major problems in the financial sector related to state ownership, lack of competition, and lack of risk accounting. Interest rates do not appear to account for the varying degrees of risk represented by the different firms in the sample. As a result, politically connected firms have access to very cheap credit, and the overall viability of the financial sector and the efficiency of resource allocation are low. Efficiency in payments systems is also low, with foreign wires taking three times longer to clear through Eritrea than through China. Although the solvency and financial depth of African banking systems have been strengthened, this has not yet translated into access to reliable, inexpensive financing on the level of successful exporters. China, India, and Morocco are clearly superior in terms of access to financial services: 72 percent of Indian firms have loans; 89 percent of Moroccan firms have overdraft accounts; and Chinese firms pay median interest rates of only 6 percent. Bolivia’s financial system is weaker, but loan access (46 percent) and interest rates (14 percent) are comparable to the best African performers. Figure 7. Percentage of Firms Rating Finance Constraints as Major or Severe

0102030405060708090

Eritrea Ethiopia Moz. Uganda Zambia Kenya China

%

Access to f inance

Cost of f inance

20

Table 7. Finance, Access, and Cost % firms credit

constrained % of firms with loan

Average cost of loan, %

% of firms with overdraft

Average cost of overdraft, %

Collateral as % of loan

Eritrea 28.0 44.9 9.8 48.5 168 Ethiopia 45.0 10.7 26.6 10.4 120 Mozambique 29.0 28.0 12.1 131 Nigeria 38.5 23.0 23.0 70.0 23.5 151 Uganda 26.7 32.3 16.7 17.2 116 Zambia 31.4 28.1 47.3 45.1 Kenya 20.4 40.0 14.8 79.1 16.7 170 India 72.0 12.3 China 46.0 5.9 22.0 87 Morocco 45.0 10.0 89.0 10.5 Bolivia 46.0 14.0 Table 7. Sources of Funds for Operations and Investment % of working capital financed from… % financing new investment from… Internal funds Loans, overdrafts Trade credits Internal funds Loans, overdrafts Eritrea 74 24 0.25 63 31 Ethiopia 64 24 4.0 51 16 Kenya 46 25 15.0 45 27 Mozambique 90 7 0.5 65 10 Nigeria 54 26 Uganda 80 7 5.0 71 13 Zambia 61 16 12.0 53 18 Morocco 62 20 8.0 China 52 29 3.3 52 21 India 30* 37* 30* 37* *India data come from general question about firm finances, not specific to investment or working capital Macroeconomic Policy and Instability Of all reform areas, it is often asserted that African countries have made the most progress in basic macroeconomic stabilization. However, the ICA data make clear that most have a long way to go in building macroeconomic environments conducive to private sector development. The uncertainty generated by rapid and variable inflation and exchange rate volatility increases transactions costs and hampers the abilities of firms to plan for the future; large and sustained fiscal and external deficits raise the ugly prospect of crisis. Even in more stable countries such as Uganda, nearly half of firms claim that macroeconomic instability remains a major or severe problem for their operations (see table 9), although part of this may be due to deterioration in Uganda’s terms of trade over the past decade. Conditions in Ethiopia and Eritrea are worse, having deteriorated sharply over the last few years in the midst of conflict. In the most

21

volatile cases, where inflation remains in the double digits and exchange rate variability is high, as many as 70-80 percent of firms list macroeconomic instability as a major or severe problem. In contrast, only 26 percent of firms make the same claim in China, where inflation and exchange rate volatility are low and external balances are stable. India, Morocco, and Bolivia also outperform the Africa ICA countries on macrostability, as do Botswana and Mauritius, the two Sub-Saharan Africa countries with a history of good governance and rapid growth. Institutional investor credit ratings for Sub-Saharan Africa also highlight international financial markets’ perceptions of the sustainability of country debt and macroeconomic policy. All the Africa ICA countries received scores of 15-20 on a scale of 0-100, implying that none have been able to establish a reputation for strong economic management. Some claim that these ratings are biased against African countries, but strong marks for Botswana and Mauritius suggest that financial markets respond positively to sustained periods of responsible management. Severe macroeconomic distortions are relatively uncommon among African ICA countries, but a few remain. Eritrea has a dual exchange rate regime through which it rations foreign exchange, subsidizing favored government-owned or -affiliated firms while forcing the remainder to buy foreign exchange on the unofficial market and to report import costs for tax purposes as if they bought at the official rate. Shortage of foreign exchange has resulted in low capacity utilization in non-state firms and is one of the largest obstacles to doing business in Eritrea, rating a 4.4 average response on a scale of 1-5, where 5 is a severe obstacle. Table 9. Macroeconomic Indicators Macroinstability major

/ severe problem, % firms

Inflation* Real exchange rate volatility**

Ext. balance, % of GDP**

Institutional Investor credit rating, Dec’03

Eritrea 80 11.4 2.4 -63.1 Ethiopia 51 -3.9 1.0 -16.5 16.0 Mozambique 63 12.1 2.3 -20.8 19.1 Madagascar 10.6 1.5 -5.4 Nigeria 13.7 1.9 4.8 17.6 Uganda 45 3.3 2.1 -14.3 20.0 Zambia 74 24.7 5.4 -12.1 15.8 Kenya 51 8.0 1.4 -8.1 22.9 Botswana 5.4 3.0 13.2 59.0 Mauritius 4.5 1.4 -0.3 53.5 China 26 0.0 1.0 2.2 59.9 (9/03 ) India 4.0 1.2 -0.8 45.3 Morocco 1.9 0.9 -5.8 45.6 Bolivia 2.9 0.5 -6.8 * Average 2000-02 ** Average absolute % change in average monthly nominal exchange rate relative to SDR, 2000-03

22

Market Structure Market competition is key in producing efficient outcomes and incentives for innovation, but African markets often remain highly concentrated. Privatization and commercialization of key state-owned enterprises (SOEs) in many countries have not proceeded very far; in others, the absent or corrupt regulatory processes of privatization have transferred inefficient monopolies into private hands without increasing competition. Table 10 provides a look at some indicators of market structure and competitiveness from the ICA surveys, and table 11 looks at state ownership. African markets tend toward more substantial state involvement and weaker competition than their comparators. SOEs do play a substantial role in China, but the incidence of monopoly and oligopoly are quite low, which indicates that Chinese SOEs have been subjected to substantial market discipline.23 Moroccan and Indian firms have median market shares of only 5-8 percent in their most important products, compared with 10-20 percent for most African countries. In Ethiopia, Eritrea, and Mozambique, firms with significant state ownership account for more than half of sales; competition is strong in Ethiopia, but very weak in the latter two countries, with monopolistic and oligopolistic firms accounting for over 60 percent of sales. Mozambique has privatized over 850 firms over the last decade, but large SOEs remain and dominate their respective markets, despite the higher productivity of privatized firms. Eritrea’s large SOEs also dominate their respective markets and receive preferential treatment. In Nigeria, public enterprises account for half of GDP, two-thirds of employment, and 57 percent of formal sector investment. The major producers are in petroleum industries, and most public enterprises do not appear to be in the manufacturing sector; only 7 percent of surveyed enterprises (accounting for 10 percent of the sample’s sales) have significant levels of state ownership. However, the manufacturing sector suffers greatly from inefficiencies in government-owned utility monopolies that provide poor services and required around US$30 billion in direct and indirect subsidies in 1998. In Zambia, most public enterprises have been sold, but the key utilities (telephone, electricity, railways) and the biggest commercial bank have remained in state hands following strong political resistance to reform. In addition, the lack of effective competition policy and the prevalence of nepotism in government contracting and the implementation of regulations have allowed private monopolies and oligopolies to dominate numerous sectors, as evidenced by high market concentration figures. In Ethiopia, the government still participates extensively in manufacturing, construction, transport, and infrastructure and monopolizes water and telecom; companies with at 23 In these data, firms are defined as oligopolistic when they have two or less competitors, so the numbers include monopolies as well.

23

least 50 percent public ownership account for 62 percent of sales. In Uganda, many large public enterprises remain engaged in the delivery of commercial services, impeding entry in tourism, agribusiness, and financial services and providing substandard quality on water, transport, telecom, and power. Trade openness, also a major determinant of competition, differs widely over the sample. Average tariff rates, shown in Figure 8, indicate that some African countries have moved further than others in import liberalization.24 Interestingly, six of the seven African countries sampled here have lower tariffs than India and Morocco, two highly successful manufacturing exporters. This does not tell the whole story, however, because African countries have often maintained high trade barriers in import-competing industries while allowing tariffs to fall on other products, and non-tariff barriers in Africa are often still high according to the International Monetary Fund’s trade openness index.25 In addition, the much larger size of the comparator economies (especially China and India) increases domestic competition and economies of scale, but the much smaller African economies can less afford such protectionist tendencies. The major laggard on trade openness among the African sample is Nigeria, where trade policy is still protectionist and largely used for conferring benefits. The overall effective rate of protection is 25 percent, dispersion of tariff rates is enormous, and trade policy implementation is inconsistent and opaque. Ethiopia also lags, with effective rates of protection at 26 percent, and sectoral policies clearly biased in favor of protecting manufacturing and against agriculture and mining. Uganda and Zambia are generally rated highly on openness, but they retain policies that impede trade, such as use of ad hoc tariffs for revenue purposes in Uganda and discretionary import bans in Zambia. Table 10. Market Structure Indicators % domestic

mkt share, firm mean (median)

Competitors (median)

Suppliers (median)

Monopoly (oligopoly), % firms

% industry sales, mon. (olig.) firms

Anticompetitive behavior as major / severe problem. %

Bolivia 26 (17) Morocco 12 (4) China 14 17 4.6 (6.5) 1.1 (8.2) India 18 (8) Eritrea 5 6.3 (16.5) 43.4 (20.5) 8 Ethiopia 15 (5) 24 6 5.5 (6.2) 0.9 (1.8) 30 Kenya 30 (20) 7 7 11.1 (12.3) 7.6 (19.7) 65 Moz. 24 (11) 5 5 20.0 (25.3) 51.2 (9.8) 60 Nigeria Uganda 23 (10) 8 4 8.0 (10.0) 2.4 (12.8) 31 Zambia 32 (20) 8 6 7.3 (11.5) 4.1 (25.0) 39 *Oligopoly here defined as firms with one or two competitors (so does not include monopolies)

24 Calculated as the total tax revenues from import taxes divided by the value of imports. 25 See Hinkle et al. (2003).

24

Table 11. State Ownership Indicators % firms with greater than 50%(10%)

state ownership Sales, firms with greater than 50% (10%) state ownership, % total sales of sample

Bolivia Morocco 0.1 (0.3) 0.0 (0.0) China 20.9 (24.7) 21.9 (25.2) India 2.1 (2.8) 0.9 (0.9) Eritrea 17.7 (20.3) 66.3 (67.4) Ethiopia 13.4 (13.6) 61.8 (61.8) Kenya 5.7 (7.2) 19.5 (28.2) Moz. 1.3 (4.0) 32.2 (26.9) Nigeria 3.1 (7.0) 0.7 (9.9) Uganda 2.3 (3.7) 4.9 (12.9) Zambia 2.9 (4.9) 3.0 (38.8) Figure 8. Average Tariff Rates

05

10152025303540

Eritrea

Ethiop

ia

Mozam

bique

Kenya

Nigeria

Ugand

a

Zambia

China

India

Morocc

oBoli

via

Source: World Development Indicators 2002 Infrastructure African countries exhibit generally poor, but quite varied, quality of infrastructure. Our data show that electricity, telecommunications, and transport are serious problems (figure 9), especially transportation. Economic sparseness is a considerable obstacle to the quality of infrastructure services on the continent, but it is clear that the quality of management of infrastructure systems makes a big difference as well. The efficiency of public sector enterprises is key; the relative quality of electricity, transportation, and telecom in the same country can be very different, as privatization or competition reforms in one sector move forward while those in another stall. The most recent progress has been made in telecom, where the successful incorporation of private providers of cellular infrastructure in Mozambique, Uganda, and Zambia has extended coverage and improved service

25

quality significantly. The least progress has been made in electricity, where effective reform of national companies has lagged, with severe consequences for firms. Conflict has particularly negative effects on infrastructure, as evidenced in Ethiopia and Eritrea over the last few years.26 In particular, comparisons between Africa and China—where relatively few firms point to infrastructure issues as important constraints and where the quality of electricity, transportation, and telecom is consistently good—illustrate the need for rapid progress. Figure 9. Percentage of Firms Citing Infrastructure as a Major or Severe Constraint

0

10

20

30

40

50

60

70

Eritrea

Ethiop

ia

Mozam

bique

Ugand

a

Zambia

Kenya

China

%

electricity

transportation

telecom

Note: 97 percent of Nigerian firms listed infrastructure as one of the top three constraints to their operations, with the most important issue being electricity supply; 74.2 percent reported power outages to be a major or severe constraint on capacity utilization. Electricity Access to reliable and cheap electricity is undoubtedly the most problematic of infrastructure issues in Africa (see figure 9 and table 12), and the major problems stem from government failures. State-owned power monopolies are common, and powerful interests protect them from restructuring. Simply getting connected to the power grid can take as long as 174 days on average (Zambia) compared with only 18.5 days in China. Power companies often do not inform firms of rolling blackouts, such as in Eritrea, or they demand large bribes and then still often fail to inform firms, such as in Nigeria. Despite monopoly positions and terrible service, national power companies often lose tremendous amounts of money; Zambia’s ZESCO registers non-technical losses on the order of 20 percent of turnover. In Nigeria, where the vast majority of firms cited electricity supply as a crucial bottleneck, firms must secure permission from the national power company to import generators; managers view this as a blatant mechanism for government officials to extract bribes.

26 Indeed, the Ethiopia ICA notes that deficient physical infrastructure may be the single largest bottleneck in the country’s investment climate.

26

Deficient electricity service severely hurts competitiveness. Power outages occur more than once a week in Eritrea and Mozambique, and not much less in other African countries, compared with a little over once a month in Morocco and a few times a year in China. Many firms have their own generators, but the cost of privately supplied power is two to three times as high as that from public grids. Bringing energy costs down to the level of China (1.4 percent of total costs) would be financially equivalent to wage bill reductions of 7 percent (Uganda), 10 percent (Ethiopia), 15 percent (Eritrea), 22 percent (Nigeria), 23 percent (Zambia), and 35 percent (Kenya).27 Over and above the cost of public and private power, production losses caused by power outages are 3 to 5 percent of sales—comparable to Bolivia and India but well above China (1 percent) and Morocco (2 percent). In some types of production, especially of continuous-process items like plastic and soap, the unexpected cessation of power can lead to weeks of lost production while machines are cleaned. The Ethiopia ICA estimates that if the percentage of output lost to power outages could be halved, firm-level productivity would rise by 37 percent. Table 12. Quality of Electricity Infrastructure Energy, % of

firm costs, average

% output lost to power outages, average

Power outages per year, median

% have own generator

Days for electricity connection, average (median)

Eritrea 5 5.5 60 43 99 (30) Ethiopia 3.3 5.6 36 17 116 (60) Mozambique 2.0 60 23 31.5 (20) Nigeria* 4.2 3.3 97 Uganda 3.3 6.3 20 35 38 (14) Zambia 4.2 4.5 15 38 174 (60) Kenya 5.6 9.3 24 70 65 (18) Morocco 2.1 12 17 China 1.4 2.0 2 30 18.5 (4.5) India 5.3 69 Bolivia 3.6 * 60 12 *Bolivian firms reported an average of 1 day of lost production per year due to power outages. Limited progress has been made thus far. Ethiopia has recently redesigned policies to allow some private participation in energy, but the effects have yet to be seen. Uganda has been moving forward with restructuring as well, and some progress has been made over the 2001–2003 period, but still only 5 percent of its population is connected to electricity. Elsewhere, particularly Nigeria and Zambia, resistance to privatization or commercialization has been intense and progress scant.

27 If country 1’s labor costs are X% of sales, country 1’s average electricity costs are Y1% of sales, and country 2’s electricity costs are Y2% of sales, and Y1>Y2, then the difference between the electricity costs of the two countries is financially equivalent to (Y1-Y2)/X as a share of labor costs.

27

Transportation Domestic transport costs are very high in Africa, and 20–30 percent of firms in most African countries cite transport issues as major or severe obstacles to doing business.28 High transport costs hurt exporters’ competitiveness the most but also provide some degree of trade protection to import-competing industries. This is supported by the fact that in Uganda and Zambia (both landlocked countries), 23 percent and 30 percent of non-exporting firms, respectively, cited transport as a major or severe obstacle, compared with 35 percent and 41 percent of exporters. Some structural factors play into high transport costs, as does the lack of adequate maintenance expenditures and quality control. Low road density is in part a structural result of low population density.29 However, as figure 10 shows, that relationship is not perfect across the African and comparator countries: Kenya and India have substantially larger road networks than their population densities predict, and the opposite is true for Ethiopia and Eritrea. African countries also tend to have far smaller shares of paved roads than their competitors. On this metric, as shown in table 13, Nigeria (at 31 percent) is the strongest performer of the African countries in this sample, compared with 56 percent (India, Morocco) and 88 percent (China). Low density can be offset by policies to encourage clusters and export processing zones, where low transport costs and economies of scale in infrastructure provision can take hold. However, African governments have generally been unsuccessful in creating the conditions necessary to develop efficient clusters, and export processing zones in Africa have had a very mixed record. Data on the cost of poor transport infrastructure are hard to find, but the surveys give some indications. Ugandan firms on average lost 1.8 percent of domestic sales and 1.1 percent of exports because of delays in transportation services. Zambia’s roads suffer from heavy industrial traffic resulting from the poor performance of the state-owned railway system; the average firm had production interrupted for 5.3 days in 2001 because of transport failures. In Ethiopia, the combination of direct government participation and a terrible road network pushes local transport costs to eight times Chinese levels, four times South African levels, and twice Kenyan levels.30 In Madagascar, the road network is congested and poorly laid out, and there is only one road leading to the port (Cadot and Nasir 2001). Nigeria is the outlier in terms of transportation infrastructure among the Africa ICA countries, although it has only half the percentage of paved roads as India and Morocco and a third the share of China. The

28 See Limao and Venables (2001) for some good, though slightly dated, evidence. 29 A more interesting measure than population per square kilometers would be a notion of density that captures the average distance between two people in a country, but to our knowledge these data are not readily available. 30 This estimate is from the Ethiopia ICA, although the manner of calculation is not clear.

28

direct transportation costs of Nigerian firms average 1.3 percent of sales (an interesting result but difficult to interpret with only one comparator, Eritrea, at 1.7 percent of sales). Trends in the quality of transport infrastructure are mixed, and in many cases difficult to discern. Eritrea and Ethiopia both have seen conflict-related deterioration of infrastructure, including of their road networks, which for Ethiopia in particular is thought to be the single most major investment climate bottleneck. On the upside, Mozambican transport costs are high but improving; firms used to send goods by sea from Beira to Maputo in 1998, but road quality has improved enough on that critical route that it is now cheaper to ship by land.31 Table 13. Quality of Transport Infrastructure Roads, km per

thousand km2 Paved roads, km per thousand km2

Paved roads as share of total

% of production lost in shipment, average

Population per km2

Eritrea 40 8.7 22 0.4 43 Ethiopia 32 3.8 12 1.0 67 Kenya 112 13.6 12 2.0 (dom.), 1.4 (int’l) 55 Mozambique 39 7.3 19 0.6 24 Nigeria 213 66.0 31 146 Uganda 137 9.2 7 2.4 119 Zambia 90 16.2 18 3.9 14 Mauritius 949 920.3 97 597 Morocco 129 72.9 56 66 China 150 33.7 88 1.2 137 India 1117 510.3 56 353 Bolivia 50 3.2 7 8 Figure 10. Population Density Versus Road Density (population and kilometers of road per square km)

3.03.54.04.55.05.56.06.57.07.5

2.0 3.0 4.0 5.0 6.0 7.0

ln (population density)

ln (r

oad

dens

ity)

Source: World Development Indicators 2002

31 This improvement is largely due to enormous inflows of foreign aid directed at infrastructure.

29

Telecommunications Arguably, more progress has been made in telecommunications, where new technologies have opened up opportunities for private participation in cellular phone and Internet communications. In Mozambique, for instance, the introduction of cellular service in 1998 and 1999 has brought regular cellular phone use to over 80 percent of sampled firms. In addition, over a third of Mozambican firms use e-mail, and 18 percent have web sites. In Uganda, very few firms cite major or severe problems with telecommunications, and the wait for telephone connections is short by African standards. Zambia has increased mobile phone use substantially, although the lack of a strong competition policy has kept prices relatively high. On the whole, the surveyed countries in Africa lag far behind China, India, and Morocco in terms of access to telecom services. In Ethiopia, there are less than five fixed and mobile lines per 1,000 people, it still takes nearly nine months on average to get a phone connection, and a meager 6 percent of firms are able to use the Internet in business communication. Eritrea is not much better, with poor connection times, very low phone density, and very little use of e-mail by firms. In Zambia, the failure to commercialize the national telecom company (ZAMTEL) keeps the quality of land line service down and the costs up. Kenya has better phone density, but very poor connection service and the highest median frequency of phone service interruptions of any country surveyed. Other research shows that in Madagascar, the cost of a 512-kilobyte Internet connection is $7,700 per month (compared with $20 per month in France), which severely impacts the viability of its nascent IT industry (Cadot and Nasir 2001). Telecom costs are often 5 percent of turnover in Madagascar’s enterprises, and high costs impede market information. The impact of poor telecommunications in the slow reformers is significant. The Ethiopia ICA estimates that if the number of days needed to get a telephone connection were halved, average firm-level productivity would rise by 20 percent. Although this sends a strong message regarding the weaker performers on telecom, a comparison of even the better performers (Uganda and Mozambique) with China and India suggests that there is still need for much improvement, particularly on telephone density and Internet usage.

30

Table 14. Quality of Telecom Infrastructure Fixed, mobile

lines per 1,000

Days for telephone connection, mean (median)

Phone service outages per year, mean (median)

Internet users per 1,000

% firms using e-mail

Eritrea 11.0 249 (65) 12.0 (0) 3.57 17 Ethiopia 4.8 255 (90) 28.0 (7.3)* 0.38 6 Mozambique 12.8 23 (10) 13.0 0.83 36 Nigeria 8.9 0.89 39 Uganda 17.2 33 (7) 17.9 (7) 2.63 39 Zambia 19.4 87 (30) 40.1 (3) 2.43 84 Kenya 29.6 124 (60) 35.8 (14) 16.30 81 Morocco 204.4 13.70 50 India 43.8 6.78 45 China 247.7 12 (7) 5.0 (2) 71.00 ** Bolivia 172.0 32.00 *The Ethiopia survey gave interruptions as percentage of usage: 7.3 (2); value in table is multiplied by 365 days. **21% of an average firm’s employees use the Internet regularly in China. Labor Force Skills and Human Capital The quality of labor force skills and the accumulation of human capital are just as relevant for competitiveness as is physical infrastructure.32 School enrollment rates (primary, secondary, and tertiary) are provided in table 15, and indicate that most African countries lag their competitors to a significant extent, and the quality of schooling is often quite low. In addition to low investment in human capital, many African countries have difficulty retaining highly educated workers or attracting skilled expatriates. Skill inflows are reduced by obstructive visa policies that make it very difficult to hire expatriates. Skill outflows are enormous; for instance, of African emigrants to the United States in 1991, 58 percent had doctorates or medical degrees, 19 percent had master’s degrees, and 15 percent had been university professors in their home countries. There were 95,000 highly educated Africans living in the United States in 1991. Firm perceptions data from the ICAs provide strong support for the importance of worker skills (figure 11). Many firms try to fill the gap left by poor secondary schooling. In Madagascar, for example, firms must provide very basic training; only 6 percent of students enrolling in the first year of primary school finish secondary school (Cadot and Nasir 2001). However, firm perceptions of the need for skills are not correlated with the incidence of training, suggesting that many firms that need better skills are not capable

32 Interestingly, studies typically find little effect of the observable component of skill – the education and training of the workforce—on exports, investment, and firm efficiency (Soderbom and Teal 2000). However, this should be regarded as an indication of the need for better measurements of human capital, rather than an argument that human capital does not matter.

31

of providing formal training. Only 30–40 percent of African firms provide training, compared with 72 percent of Chinese firms.33 Labor force skills interact with other issues as well. For instance, in Nigeria there is evidence that poor skills and training reduce the ability of the banking sector to discriminate between viable and non-viable firm investments. As a result, many banks avoid commercial loans. Table 15. Literacy and School Enrollment Rates (%)

Net Enrollment Net Enrollment Country Pr. Sec. Tert.*

Literacy

Country Pr. Sec. Tert.*

Literacy

Eritrea 41 22 1.7 Uganda 109 12 3 69 Ethiopia 47 13 1.6 42 Zambia 66 19 2.5 80 Kenya 69 23 3 84 Morocco 78 30 10.3 51 Madagascar 68 11 2.2 China 93 63* 7.5 90 Mozambique 54 9 0.6 46 India 102* 49* 10.5 62 Nigeria 82* 30* 4 67 Bolivia 94 67 39 87 *Gross rates used, as net rates not available. Historical data for Morocco, China, and India show that gross enrollment rates for primary and secondary school average one-fifth higher than net rates. In African countries, gross enrollment rates average nearly one-half higher than net rates. Figure 11. Firm Perceptions of Skills Shortages (% of firms offering formal training)

01020304050607080

Chi

na

Eritr

ea

Ethi

opia

Indi

a

Ken

ya

Mor

occo

Moz

ambi

que

Nig

eria

Uga

nda

Zam

bia

Bol

ivia

% offering training % citing worker skills as major or severe problem

Note: In Nigeria, 9% of Nigerian firms listed worker skills among the top three constraints on their business, and 7% said worker skills were a major or severe obstacle to capacity utilization.

33 The relationship between the perceived lack of labor force skills and the proportions of firms offering training is complex because causality can run in both directions; high-skill environments can be fostered by extensive training, but training is often also induced by low-skill environments.

32

Interaction with Public Sector: Taxation, Regulation, Judiciary, Governance, and Corruption

Every area of the investment climate discussed thus far has strong links to the quality of government policy and bureaucracy. Our data show that firms interact regularly with governments and their local representatives, particularly in the context of regulation and taxation. Taxation Domestic taxes in Africa ordinarily include a sales tax, a company tax or profit tax on formal sector enterprises, a local tax on informal sector firms, and sometimes a proportional duty on buildings and equipment. The data show that in some cases, inefficient or corrupt tax administration harms business operations and reduces revenue collection in Africa. The quintessential example is Nigeria, where multiple and often overlapping jurisdictions of federal, state, and local government bring down swarms of officials imposing arbitrary taxes, largely in efforts to extract money for their own personal use. In Mozambique, back tax refunds (particularly valued added tax) are 13 percent of annual sales, and recovering the refunds requires large bribes and long delays. In both Mozambique and Eritrea, many tax incentives exist in law that are almost never used by firms because of the hassles and corruption involved in accessing them. In Ethiopia, respondents emphasize the inconsistency and nontransparency in methods of sales tax and profits tax assessments. Tax administration seems to be somewhat less of a problem for Zambian firms, which complain more about high rates, but other evidence suggests that corruption is rampant in the Zambia Revenue Authority (ZRA).34 Evidence from other research suggests that implementation of tax laws, even those designed to provide investment incentives, is problematic in a number of African countries, reflecting weak governance and bureaucratic capacity.35 In terms of perceptions, firms in most African ICA countries view taxation as a bigger problem than do their counterparts in China, but as a smaller problem than firms in India (see figure 12).

34 See Transparency International (2003), Zambia report. 35 See, for instance, Marchat (1997) on Côte d’Ivoire.

33

Figure 12. Percentage of Firms Reporting Tax Issues as Major or Severe Obstacle

01020304050607080

Eritrea

Ethiop

iaMoz

.

Ugand

a

Zambia

Kenya

China

India

%

rates

administration

There is also some evidence to suggest that African governments lose substantial revenue due to tax evasion, as administrative hurdles and corruption drive firms to work hard to hide income. Firms in the survey were asked different versions of the following question: Acknowledging the difficulty of complying with regulations, what share of its income do you think a typical firm in your industry reports for tax purposes? They estimated the share of reported income to be 86 percent (Kenya), 84 percent (Eritrea), 84 percent (Zambia), 77 percent (Uganda), and 69 percent (Tanzania), compared with 98 percent (China). Regulations Turning to the quality of regulation, there are two major issues to keep in mind. The first is the nature of the rules themselves—how complex are they, how much of a burden do they put on enterprises, and so forth. The second is the implementation and enforcement of the rules—does the rule of law hold, or is bureaucratic discretion and corruption widespread? This section will discuss regulations and procedures related to customs, land, labor, and business operations. Customs Customs processes have improved in some African countries, but are still poor compared to international best practice (see table 16). In Morocco, exports usually clear in one day, and imports in two. Uganda and Zambia are the strongest performers, where imports clear in a relatively quick 4 and 5 days, respectively (exports clear in 3 days and 2 days). Nonetheless, over a quarter of firms in Uganda and nearly a third of firms in Zambia note that customs regulation is a major or severe obstacle to their operations. Eritrean ports are somewhat slower, taking 7 days to clear imports on average, and the process depends more on personal relationships than on formal rules. Ethiopia’s customs performance is very poor, and state-owned enterprises are privileged with expedited clearance times that are 25-50 percent faster than those for private sector firms. Mozambique is among the worse of the performers on customs; new procedures have recently been designed but are regularly ignored by customs

34

officials. Border regulations make the costs of shipping across the South African border by land utterly exorbitant; it costs 5.5 times as much to send goods to Durban by land as by sea, and trucks have to wait 5-7 days at the border for clearance. Mozambican firms report holding very large inventories of inputs because of the long clearance times. In Nigeria, complex and protectionist trade laws and a 100 percent inspection requirement at the port of Lagos combine with enormous corruption problems in the bureaucracy to result in inordinately large costs and delays associated with customs.36 The regulatory regime rewards firms that can sneak around the rules most effectively and produces rent-seeking opportunities for officials. The problems associated with customs have a significant detrimental effect on firm efficiency. The Ethiopia ICA estimates that if the number of days required to clear customs were halved, average firm-level productivity would increase by 18 percent. Given that Ethiopia is in the middle of the range for surveyed countries on customs issues, the returns to effective customs reform in a country like Nigeria would likely be enormous—an inference supported by analysis carried out in the Nigeria ICA. One garment exporter in Madagascar estimated that reducing port clearance times to one day would reduce his total costs by 3-5 percent; given that labor accounts for 14 percent of the direct costs of producing a men’s casual long-sleeved shirt in Madagascar, this reduction in clearance times would be financially equivalent to a 20-30 percent decrease in wage costs per shirt (Cadot and Nasir 2001). Table 16. Customs and Trade % firms reporting customs and

trade regulation as a major or severe obstacle

Days to clear imports, median

Days to clear exports, median

Eritrea 9 7 2 Ethiopia 28 14 4 Mozambique 45 12 17 Nigeria 18 7-10 Uganda 27 4 3 Zambia 32 5 2 Kenya 40 7 4 Morocco 2 1 China 21 5 3 India 49 7 3 Bolivia 7 2 Note: Nigerian exports are given as a range from the Nigeria ICA. Also, 29% 3%, and 25%) of Nigerian firms cited customs clearance for imports (customs clearance for exports, port operations, and administration, respectively) as a major or severe problem for firm operations and profitability.

36 Port costs at Lagos are $200 per container, three times those of other West African ports. Fraud, corruption, and poor security increase the cost of imports by approximately 45 percent. This is a good specific example of the high aggregate costs inferred by GDP(PPP) : GDP (market prices) comparisons.

35

Labor Restrictive labor regulations can distort flexibility and increase costs to the private sector. Table 17 compares some relevant data, including perceptions, flexibility of hiring, and retention of larger-than-optimal labor forces. Ethiopian and Eritrean firms seem to have relatively few problems with labor regulations, judging in particular from perceptions data and from overstaffing data in Ethiopia. Eritrean firms suffer badly from conflict-related labor shortages; a situation not uncommon in postconflict countries. In Nigeria, labor unions have gained strength after democratization and have succeeded in raising the minimum wage, thereby raising the unit cost of labor.37 In Zambia, the ICA reports inconsistency and instability in labor laws, in addition to their use as confiscatory instruments.38 However, relatively few Zambian firms (28 percent) report overstaffing, and the magnitude of the overstaffing that exists in those firms is small (18 percent). It is difficult to tell how Kenya fares, because Doing Business 2004 reports good flexibility in firing, but 41 percent of Kenyan firms report overstaffing, preferring to retain a median of only 62 percent of their current workforce, and perceptions data are in the middle of the pack.39 Ugandan firms may suffer from overstaffing (39 percent of firms, preferring to retain only 63 percent of their workforce), as well as rigidities in firing. However, the firm survey data reported in the Uganda ICA show that regulatory constraints are minimal, union membership is small, and workforce contracts tend to be flexible. Mozambican firms appear to face harsh constraints in terms of labor regulation. About 37 percent of firms retain extra workers because of regulation and would prefer to retain only 63 percent of their current work force. Privatized companies are 2.5 times more likely to retain extra workers, as they suffer from intense political pressure to avoid retrenchment. The legal system is so weak and costly that even workers dismissed for a just cause (such as stealing) are often paid hefty severance fees. Piece rate pay is illegal in Mozambique, further delinking productivity from pay in manufacturing.

37 This is partly because most firms do not actually pay minimum wage to their workers; the average wage is $46.50 per month, but the minimum wage is $50, with bonuses and allowances, bringing total compensation up to $83. 38 Immigration laws recently changed, requiring all non-Zambians to renew their unexpired work permits at prohibitive costs. 39 The Doing Business methodology relies on lawyers’ assessments of the laws governing regulatory frameworks, and so is generated in a very different manner than the ICA data. See World Bank (2004).

36

Table 17. Labor Regulations Labor regulations major or

severe obstacle, % firms % retaining extra workers (of these, % overstaffing)*

Flexibility-of-firing index, Doing Business 2004**

Eritrea 5 Ethiopia 4 26 (25) 29 Mozambique 38 37 (37) 64 Nigeria 11 36 Uganda 17 39 (37) 50 Zambia 19 28 (18) 40 Kenya 22 41 (38) 16 Morocco 63 25 33 China 21 54 (20) 57 India 47 (20) 45 Bolivia 45 *Looser wording of this question in some surveys may have distorted this result slightly, but there is no systematic pattern visible as such.lower score implies greater labor market flexibility. **Lower score implies greater labor market flexibility. Notes: 21% (4%) of Zambian (Chinese) firms also reported retaining a smaller-than-optimal workforce because of regulatory constraints, desiring a median increase of 20% (20%) in their labor force. Kenyan and Ugandan firms were asked a similar but less tightly worded question, which some firms may have interpreted more broadly and thus reported their ideal labor force size in terms of their visions of firm growth. For these countries, 37% and 35% of firms reported understaffing, with median desired increases of 48% and 43%. Land

Access to land is almost universally a problem in the countries we have surveyed thus far, although data are somewhat scarce because land is usually a one-time acquisition. Sole government ownership of land is common outside of Kenya, and although Uganda has allowed communities to opt into freehold and leasehold systems, their use is not yet widespread. Where data are available, accessing land takes around ten to twelve months and can be expensive (table 18). In Mozambique, firms pay an average of $18,000 in processing fees to obtain land. In Nigeria, large bribes are usually associated with the process of requesting access, and some firms waited up to ten years for land. Preferential treatment and rationing also arise from state ownership. For instance, in Eritrea the distribution of responses to the seriousness of problems related to land is strongly bimodal; well-connected firms get land easily, whereas others obtain land at great difficulty and expense. In Ethiopia, rent costs for private firms are as high as 16-25 percent of total sales, whereas government-owned firms only pay 2 percent of sales. In most of the surveyed countries, land is not a common form of collateral. This is usually due to lack of freehold tenure, or in Ethiopia’s case, because the government has first claim to the value of land in the event of firm closure. In Nigeria, firms must “re-register” land to be able to use it as collateral, a process that takes six months to two years and can cost 15 percent of the value of the land in official fees alone, plus bribes.

37

Africa is a very land-rich continent; the unsuitability of land as collateral vastly reduces the African economies’ stock of collateralizable assets and probably also drives up collateral requirements. In contrast, 90 percent of Bolivian firms reported that land is always accepted as collateral. Table 18. Access to Land Months to procure land, median

(mean) Access to land a major or severe problem, % firms

Eritrea 10.5 (6) 22 Ethiopia 11 (6) 15 Mozambique 12 27 Nigeria 6-120 (only a range provided) Uganda 12 17 Zambia 10 (6) 17 Kenya 24 China 19 Firm Entry and Operations Regulations related to the startup and operation of enterprises also have the potential to significantly impede the investment climate and have had a negative effect in several countries. A few indicators are shown in table 19. In terms of investment procedures, the surveyed countries have a ways to go before “one-stop investment shopping” is achieved and streamlined inspections become the norm. Eritrea is probably the strongest performer in this area; business licensing procedures are streamlined there and generally well implemented through the Business Licensing Office, although there is anecdotal evidence of potential investors being turned down for arbitrary reasons.40 In Mozambique, the new streamlined business regulations are of limited use because bureaucrats retain so much discretion in their implementation. Officials in Mozambique are almost universally unaware of laws or ignore them outright, and there is no legal recourse for managers. Entry into the market in that country is very time consuming and difficult, even with a consultant, and expensive; it takes between 3.5 and 5 months and $1,000-$1,500 for an experienced consulting firm to start a business. In Zambia, there has been a recent explosion of license-requiring agencies within the government; the Zambia ICA cites one company with eight subsidiaries that required 300 licenses, with accompanying bribes. The major problem is that there are many civil servants in Zambia whose power far exceeds their pay and who often parlay whatever power they have into personal income-generating opportunities. In Mozambique, starting a business takes 153 days on average; in Ethiopia, the up-front costs of starting a business amount to 422% of per capita GDP. not including additional time and

40 It is worth noting that by definition the surveys only capture the firms that were successful in obtaining licenses.

38

money to get licenses, investment permits, and import/export permits.41 These barriers to entry reduce competition and redirect investment to countries such as Morocco, where it takes 31 days and 19% of GDP to set up a business. In terms of day-to-day operations, the burden of inspections and regulatory visits varies substantially across the countries surveyed, although the more important issue is perhaps the nature of those visits. Managers in Eritrea and Ethiopia do not spend too much time dealing with regulation (although the number of inspection visits is high in Ethiopia) and petty corruption is reputed to be low in both countries. Managers in Uganda and Mozambique spend quite a bit more time dealing with regulations, and anecdotal evidence suggests that harassment and corruption are common. In Uganda, small domestic businesses are subjected to three times as many regulatory visits than large and foreign-owned businesses, with negative implications for broad-based growth and poverty reduction. In Zambia, the number of inspection visits per year is staggering at 96 on average, and bribes are usually expected. In Nigeria, probably the worst of all the Africa ICA countries in this regard, state and local governments impose myriad arbitrary taxes, permit requirements, and licenses and often visit with local military or police to coerce more money out of firms. Madagascar’s firms also suffer badly from bureaucratic burdens; one garment producer estimates that he spends 20-25 percent of his time dealing with government-related issues, and complaints about capricious law enforcement, regulation, and corruption are widespread (Cadot and Nasir 2001). When compared with China and India, the objective data on regulatory burden in Africa are not particularly bad, but perceptions of corruption and regulatory quality are a different story (see table 21). 41 Information on time and costs required for these additional procedures is more scarce. A new proclamation prescribes that waiting time for the import/export permit be reduced from 30 days to 5, which may improve the situation. In addition, certain areas of the economy are off limits to foreign investors, further reducing investment and entry.

39

Table 19. Business Regulation Days to

start business*

Cost of starting business, % of per capita GDP*

Licensing as major / severe obstacle, %

Inspections per year, mean (median)

% senior mgmt time dealing with regulation

Eritrea 3 14 (6) 5.0 Ethiopia 44 421.6 8 13 (4) 2.9 Mozambique 153 99.6 28 6.8 (5) 11.3 Nigeria 44 92.3 4 Uganda 36 135.1 10 13 (4) 15.5 Zambia 40 24.1 10 96 (37) 13.4 Botswana 97 36.1 Kenya 61 54.0 15 22 (15) 13.5 Madagascar 67 62.8 India 88 49.8 13 (5) 16.0 China 46 14.3 16 31 (9) 7.3 Morocco 31 19.1 ** Bolivia 67 167 *from Doing Business 2004 **Data were reported in hours: 38 mean, 10 median. Judicial Systems Enforcement of property rights and contracts at a low-cost are at the heart of a properly functioning market economy. However, many African countries have serious deficiencies in their judicial systems, due to lack of resources and human capital, weak capacity, and corruption and nepotism. Bigsten et al. (1999) documents the tendency of African manufacturers, suppliers, and clients to rely on long-term contracting relationships rather than formal legal institutions; this reliance on relationships likely reduces efficiency and creates significant barriers to entry, but it is a rational response to a dysfunctional or corrupt institutional environment. Some countries like Mozambique have established alternative dispute resolution institutions in the last few years, attempting to provide a basic level of service while they restructure their failed judicial institutions. Uganda is the most notable success story in the ICA sample, with better court outcomes than most competitors (including China, India, and Morocco). Table 20 provides some limited data from the ICA surveys and a look at some comparative indicators from Doing Business 2004.

40

Table 20. Judicial System Indicators Days to resolve a

business dispute in commercial court*

Cost of resolving dispute in court, % of p.c. GDP*

Average response to “court system will uphold my rights”, 1 (fully agree) to 6 (fully disagree)

Weeks for court to resolve dispute over payments, mean (median)

Eritrea Ethiopia 895 34.6 Mozambique 540 9.1 Nigeria 730 6.6 Uganda 99 10.0 3.0 28 (12) Zambia 188 15.8 3.9 65 (52) Botswana 56 Kenya 255 49.5 3.6 59 (52) Madagascar 166 120.2 South Africa 84 16.7 Bolivia 464 5.3 31 (17) Morocco 192 9.1 China 180 32.0 2.4 7.1 India 106 95.0 *Doing Business 2004 Governance As is evident from the above discussions, governance issues cut through all areas of the investment climate, particularly those that deal with direct interactions between businesses and representatives of the government. Governance encompasses a broad range of themes, from corruption to the protection of public order to the quality and predictability of policy. Relative to China, every African country surveyed except Eritrea boasts a large share of firms emphasizing the shortcomings of their government on these grounds. Table 21. Percentage of Firms NotingGovernance-Related Issues as Major or Severe Obstacle Eritrea Ethiopia Kenya Moz. Nigeria* Uganda Zambia ChinaCorruption 3 38 73 64 38 46 22 Security, fraud, crime, disorder

1 9 69 54 27 49 16

Economic and regulatory policy uncertainty

29 38 51 58 28 57 54

*Nigerian surveys asked respondents to list the top three constraints to their business operations: 32% included issues directly related to governance (including corruption, policy uncertainty, bureaucratic burden, and so forth), and 15% included security and crime.

41

Corruption takes many forms, from the petty to the grand and political, and its effects are far reaching. Given the results in McArthur and Teal (2002), which indicate that firms operating in economies where bribes are pervasive are on average only one-third as productive as their counterparts elsewhere, these are very serious issues.42 Kenya stands out in the data as suffering enormously from corruption, with 73 percent of firms citing corruption as a major or severe problem. On average, Kenyan firms estimate that typical firms in their industry pay 3.8 percent of sales in “unofficial payments” or bribes, and that winning public sector contracts requires such payments on the order of 7.5 percent of the contract value (table 22). By all accounts, Nigeria is also one of the worst in the sample concerning corruption, with firms paying 5 percent of sales on average in unofficial payments, as firms are confronted by myriad layers of bureaucrats and inspectors whose official positions exist for their own benefit. Nigerian managers repeatedly stated that most government agencies have no capacity to adequately perform their roles, and that they function only as a source of graft and control. The Nigerian case also demonstrates how governance is tightly related to shortcomings in infrastructure, with the prime example of NEPA, the government electricity monopoly. Here the World Bank Institute (WBI) corruption rating of –1.35 seems appropriate (see table 24). Uganda, Zambia, and Mozambique also suffer badly from corruption, as evidenced by firm perceptions data (especially Mozambique), the score of –1 on the WBI rating for corruption, and reports of large unofficial payments (Uganda and Zambia). Ethiopia and Eritrea seem to do better on the indicators of corruption, with relatively low bribe levels (closer to 1 percent of sales) and WBI corruption ratings that are closer to the midpoint for all countries in the WBI sample (zero). However, as shown in table 21, nearly 40 percent of Ethiopian firms do rate corruption as a major or serious obstacle. The perceptions data from Eritrea indicate that corruption is not a major problem, although anecdotal evidence suggests otherwise in a number of ways. For instance, opaque discretionary powers of the government often drive access to scarce resources (especially foreign exchange, credit, and land). Of course, existing firms may be the beneficiaries of these powers in cases of nepotism and rent sharing.

42 Their results also reject the endogeneity of corruption, or the idea that firm inefficiency stimulates corruption. These estimates are very high but are probably upper bounds of actual values, because the corruption data are likely correlated with other unobserved business environment variables that affect productivity.

42

Table 22. Corruption Country Unofficial payments to “get things

done,” % of firm sales, average % contract value in informal payments required to secure contract, average

Eritrea 1.5 Ethiopia 1.6 Mozambique 3.6 5.9 Nigeria 5.0 Uganda 2.4 3.6 Zambia 2.4 3.7 Kenya 3.8 7.5 India China 1.8 2.1 *52% of Bolivian firms reported that tax administrators offered to lower their taxes in exchange for a bribe; 29% reported that a court official offered a more favorable judgment in exchange for a bribe. Security issues are an additional concern, related to governance through the quality of law enforcement and police protection. Security costs can be very high, as illustrated in table 23; the cost of security problems in Kenya (in terms of expenditures on security and losses to crime) approach a staggering 9 percent of sales, or three-quarters of total labor costs. Zambian firms also report very high costs related to security, on the order of 7 percent of sales. Although data on losses caused by crime are not available for Nigeria, the ICA describes security issues vividly; Nigerian firms are plagued by excessive security costs, the inability to travel easily at night, a higher cost of attracting and housing expatriates, high risks to keeping cash on hand, and difficulties in extending distribution areas due to robbery. Chinese firms, by contrast, are very rarely concerned with security, fraud, crime or disorder, and like their Indian and Moroccan counterparts spent relatively little money on security precautions. Table 23. Security Indicators Country Cost of crime, % of sales % sales spent on securityEritrea Ethiopia 1.0 0.9 Mozambique 1.9 0.9 Nigeria 1.6* Uganda 1.7 2.1 Zambia 4.5 2.5 Kenya 6.1 2.8** India 0.8 China 0.3 0.8 Morocco 0.8 Bolivia 0.2 *Nigerian firms also gave a median response of 3 on a scale of 1 (very small problem) to 5 (very large problem) when asked to evaluate the magnitude of the problem posed by security. Nigerian firms were not asked about the cost of crime and vandalism, but anecdotal evidence implies that it is quite high. **The Kenya surveys noted a further 0.58% of sales on average spent on reducing employee pilferage.

43

Another key dimension of the quality of governance is the stability and predictability of economic and regulatory policy. A study of FDI in Uganda highlights the role of the unpredictability of investment-related policies and the opaque, ad hoc role of the minister of finance in providing exemptions and changing policies at will in discouraging investors (Obwona 2001) The available ICA perceptions data (table 21) suggest that policy uncertainty is a comparable problem in Eritrea and an even more serious problem in Mozambique, Zambia, Kenya, and Nigeria. WBI’s related indices, such as government effectiveness, regulatory quality, and the rule of law, support these conclusions. Interestingly, policy and regulatory uncertainty appears to be a major problem in China, even though its advantage on WBI indices implies that this is a tentative result (table 24). Data on risk levels—economic, financial, and political—also suggest that India, China, Morocco, and Chile, all major manufacturing powers of other developing regions, hold a major advantage in stability and risk over African countries. Table 24. WBI Governance Indicators Voice and

accountability Political stability

Government effectiveness

Regulatory quality

Rule of law

Control of corruption

Average

Eritrea -2.05 -0.25 -0.44 -1.17 -0.51 0.04 -0.73 Ethiopia -1.03 -1.20 -0.89 -1.00 -0.44 -0.35 -0.82 Kenya -0.58 -0.86 -0.85 -0.50 -1.04 -1.05 -0.81 Mozambique -0.26 -0.27 -0.41 -0.64 -0.65 -1.01 -0.54 Nigeria -0.70 -1.49 -1.12 -1.18 -1.35 -1.35 -1.20 Uganda -0.77 -1.46 -0.41 -0.01 -0.84 -0.92 -0.74 Zambia -0.40 -0.02 -0.93 -0.60 -0.52 -0.97 -0.57 Botswana 0.73 0.75 0.87 0.81 0.72 0.76 0.77 Mauritius 0.80 0.99 0.53 0.46 0.89 0.53 0.70 Madagascar -0.05 0.30 -0.38 -0.26 -0.19 0.14 -0.07 China -1.38 .022 0.18 -.41 -0.22 -0.41 -0.37 India 0.38 -0.84 -0.13 -0.34 0.07 -0.25 -0.19 Morocco -0.30 -0.14 0.07 0.02 0.11 -0.04 -0.05

44

4. Overall Benchmarking: Comparison of a Simple Investment Climate Index and CPIA Ratings We conclude this analysis with some overall stocktaking. Any index-based benchmarking exercise has its problems, but it is nonetheless interesting and valuable to attempt to aggregate various data series into broader subindices for areas such as finance, infrastructure, and so forth. Each category score below is constructed from at least two and as many as four key data series, and ranges from 0 (worst) to 1 (best). Because of issues of how one compares relative scores on different types of data indicators, the index is constructed using country ranks on the different indicators (see the appendix to this report for details). Table 25 should be considered suggestive, not definitive, and the focus should be on the subindices that provide a way to compare the countries surveyed here on the different dimensions of the investment climate discussed above. The broad benchmarks illustrate the patterns fleshed out in more detail in the previous sections. Morocco, China, and India all do substantially better on most categories. The overall gaps are probably smallest in the regulatory issues as measured here (labor and customs, and to a lesser extent business regulation), whereas the gaps are enormous in finance, macrostability, infrastructure, labor force skills, and governance. More market structure data would be useful, but the gap is potentially very large there as well. The overall ratings show the African ICA countries clustered between 0.3 and 0.5 (compared with between 0.6-0.8 for Morocco, China, and India), with Uganda and Ethiopia at the top, and Kenya and Tanzania close behind. Zambia and Eritrea43 fall in the middle, each with some strong points (finance, customs, and governance for Eritrea; customs and—suspiciously, given other findings—business regulations for Zambia) and weak points (macrostability for both, infrastructure and worker skills for Eritrea, finance and governance for Zambia). Nigeria and Mozambique are last in the overall rankings. 43 Some of the Eritrea data is missing, and this plus and other consistency issues render the Eritrea ratings least reliable of the set of countries.

45

Table 25. Benchmarking Exercise, Various Areas, scored from 0 (worst) to 1 (best), and Comparison to CPIA Index

Country Macro Stability Finance

Market Structure Infrastructure Skills Customs Labor

Business Regulation Governance

Simple Average CPIA #8

Eritrea 0.18 0.48 0.30 0.28 0.27 0.55 0.50 0.57 0.39 3.00 Ethiopia 0.61 0.68 0.58 0.35 0.21 0.18 0.90 0.34 0.47 0.48 3.00 Kenya 0.49 0.55 0.31 0.37 0.58 0.32 1.00 0.39 0.25 0.47 4.00 Mozambique 0.23 0.08 0.34 0.41 0.12 0.14 0.36 0.31 0.41 0.27 3.50 Nigeria 0.23 0.10 0.40 0.41 0.48 0.05 0.49 0.37 0.22 0.31 2.50 Uganda 0.45 0.24 0.59 0.45 0.58 0.68 0.30 0.74 0.30 0.48 4.50 Tanzania 0.55 0.59 0.61 0.22 0.18 0.23 0.49 0.51 0.58 0.44 4.00 Zambia 0.00 0.18 0.31 0.47 0.39 0.73 0.37 0.53 0.28 0.36 3.50 China 0.88 0.89 0.73 1.00 0.82 0.59 0.60 0.62 0.74 0.76 3.50 India 0.65 0.90 0.58 0.61 0.82 0.41 0.25 0.58 0.90 0.63 4.00 Morocco 0.87 0.67 0.73 0.91 0.73 1.00 0.83 0.80 0.94 0.83 3.50 Bolivia 0.86 0.70 0.63 0.50 0.97 0.55 0.34 0.23 0.82 0.62 3.50 Note: Some data are missing, so not every score is perfectly comparable. It is very interesting to compare the simple average of the area indices with the Bank’s annual Country Policy and Institutional Assessment (CPIA). This exercise draws on staff expertise to score all active countries on twenty specific areas in four broad categories (economic management, structural policies, social inclusion and equity, governance, and public sector management). Area #8 (under structural policies) is designated “competitive environment for the private sector” and corresponds to the focus areas of the World Bank’s private sector activity in all regions. The comparison between the CPIA rankings and the IC rankings is quite striking. China, India, and Morocco, and to a lesser extent Bolivia, dominate most African countries on most dimensions of the business environment as measured by IC Index. However, the CPIA rankings present quite a different picture. Uganda scores better than all comparators, with Tanzania and Kenya matching India and surpassing China, Morocco, and Bolivia. Mozambique and Zambia match China, Morocco, and Bolivia in terms of the quality of their business environment, as ranked by the CPIA exercise. This suggests that the subjectively determined CPIA rankings suffer from a lack of comparability across regions. Few analysts will argue that Kenya’s business environment is actually better than China’s. The objective IC data strongly suggest the reverse and reflect a relative ranking that corresponds somewhat better to generally held views.

46

5. Conclusion The obstacles to private sector development in Africa, as indicated by this first round of ICAs, are clearly many and varied. Manufacturing growth in African countries has been mostly stagnant; of the two recently more successful cases in this sample, Mozambique’s growth is founded on capital-intensive mega-projects and is questionable in terms of sustainability and poverty impact, and Uganda’s growth has faltered in recent years. On one hand, the six countries all significantly lag China, India, and Morocco, three major competitors in the market for labor-intensive manufactures, on most indicators of the investment climate. The shortcomings of African countries create a high-cost environment that depresses competitiveness and growth. This is the negative aspect of the story, and it demands a vastly increased effort at reform across the spectrum of investment climate issues. On the other hand, the ICAs contain very persuasive stories of the ability of African countries to sharply improve the quality of at least some aspects of their investment climates. Mozambique, and to a lesser extent Uganda, have made excellent progress in telecommunications through private sector participation in cellular phone and Internet services. Mozambique’s roads are of poor quality but are improving to the point that freight forwarders sending goods from Beira to Maputo are shifting from sea to land transport. Eritrea has streamlined investment and business start-up procedures into an effective one-stop-shopping experience. Uganda has managed to maintain a fairly flexible labor market environment and boasts quick judicial turnover and faster customs clearance than China and India. Most (though not all) of the conditions necessary for competitiveness and private sector development can be found individually in one or more of the six countries surveyed, but broader progress is necessary in each country to realize the competitive potential of their manufacturing sectors.44 The next steps for research in this area are clear. This summary paper has provided a broad sense of the quality of different dimensions of the business environment in a comparative framework, but much more in-depth work is needed on the magnitude of the impact of these different dimensions on different firm-level outcome variables. The most important of these is firm-level productivity, which theoretically should be a key element of competitiveness and which empirically has been linked to investment levels and the propensity to export. Good comparative research in these areas will enable the construction of a much more meaningful benchmarking exercise based on the relative

44 It is worth mentioning one final point. The obstacles to competitiveness across African economies are clearly very large and multi-dimensional. Systematic improvements are necessary but realistically will not happen overnight,even if governments are committed to improving business climates. However, it may be more manageable to create special zones (like EPZs) with much-improved business climates and thus stimulate the development of clusters that can bring much-needed foreign direct investment, skills, and capital into these countries.

47

impact of different business climate areas on productivity. This will in turn enable greater prioritization and sophistication in planning for reforms.

48

Appendix: The Benchmarking Exercise

The methodology used to construct overall and category benchmarks is very simple. A few key indicators were chosen for each category, and the countries were rank-ordered numerically (1, 2, 3, …) on each, in the direction indicated—that is, interest rate (-) indicates that lower interest rates are ranked higher. Once the rank-orderings were completed, each country’s rank on each indicator was divided by the maximum rank given on that indicator (that is, if six countries had data and each had a distinct rank—no ties—then each country’s rank would be divided by 6). The results were subtracted from 1 to get a number that ranged from 0 to 1, with better ranks giving higher results. These results were averaged across the different indicators in each category to give the final category score, and the category scores were averaged to give the overall score. Table A.1. Benchmarking Data Finance Interest rate (-) % with loan (+) % capital loan-financed (+) Macroeconomic stability Inflation (-, excluding Ethiopia b/c of disinflation)

er volatility (-) ii rating (+) Market structure % sales oligopoly (-) % sales SOE (-) average tariff (-) Infrastructure energy % firm costs (-) % roads paved (+) fixed / mobile lines per 1000 (+) Labor force skills primary enrollment, gross rates adjusted (see Table 15) (+) secondary enrollment, “ (+) tertiary enrollment, “ (+) Customs import days (-) export days (-)

Labor regulations % retaining extra workers* (1-optimal workforce as share of total) (-)

doing business firing index (-) Business regulations inspection days (-) days to start business (-) $ to start business (-) days resolve court case (-) Governance Informal payments to get things done (-)

49

security cost and cost of crime, total (must have both) (-) average WBI (+)

50

References Azam, Jean-Paul, Marie-Françoise Calmette, Catherine Loustalan, and Christine Maurel

2002. “Domestic Competition and Export Performance of Manufacturing Firms in Côte d’Ivoire.” CSAE WPS/2001-1. Centre for the Study of African Economies, University of Oxford, Department of Economics, Oxford, United Kingdom.

Bigsten, Arne, et al. 1997. “Investment in Africa’s Manufacturing Sector: A Four

Country Panel Data Analysis.” CSAE WPS/97-11. Centre for the Study of African Economies, University of Oxford, Department of Economics, Oxford, United Kingdom.

———. 1999. “Contract Flexibility and Dispute Resolution in African Manufacturing.”

CSAE WPS/99-20. Centre for the Study of African Economies, University of Oxford, Department of Economics, Oxford, United Kingdom.

———. 2000. “Credit Constraints in Manufacturing Enterprises in Africa.” CSAE

WPS/2000-24. Centre for the Study of African Economies, University of Oxford, Department of Economics, Oxford, United Kingdom.

Cadot, Olivier, and John Nasir. 2001. “Incentives and Obstacles to Growth: Lessons

from Manufacturing Case Studies in Madagascar.” RPED Paper 117. World Bank, Regional Program on Enterprise Development, Washington, D.C.

Cadot, Olivier and Nasir, John. 2001. “Incentives and obstacles to growth: lessons from

manufacturing case studies in Madagascar.” RPED paper no. 117, World Bank. Chete, Louis, and Adeola Adenikinju. 2002a., “Productivity, Market Structure and

Trade Liberalization in Nigeria.” AERC Research Paper 126. African Economics Research Center, Nairobi.

———. 2002b. “Productivity Growth in the Nigerian Manufacturing Sector and Its

Correlation to Trade Policy Regimes and Indexes, 1962–1985. AERC Research Paper 127. African Economics Research Center, Nairobi.

Chirwa, Ephraim.2000. “Structural Adjustment Programs and Technical Efficiency in

the Malawian Manufacturing Sector.” Abidjan, Côte d’Ivoire: African Development Bank.

———. 2001. “Privatization and Technical Efficiency: Evidence from the Manufacturing

Sector in Malawi.” Abidjan, Côte d’Ivoire: African Development Bank.

51

Collier, Paul, and Jan Gunning. 1999. “Explaining African economic performance.” Journal of Economic Literature , 37, 1.

———.1999. “Explaining African Economic Performance.” Journal of Economic Literature

37(1): 64–111. Fosu, Augustin. 2003. “Political Instability and Export Performance in Sub-Saharan

Africa.” Journal of Development Studies 39(4): 68–82. Gelb, Alan and Tidrick, Gene. 2000. “Growth and job creation in Africa.” Proceedings of

Gaborone conference on Economic Policy in Labor Surplus Economies. World Bank press.

Grossman, Gene and Helpman, Elhanan. 1994. “Endogenous innovation in the theory

of growth.” Journal of Economic Perspectives, 8, 1. Hay, Donald, and Guy Liu. 1997. “The Efficiency of Firms: What Difference Does

Competition Make?” Economic Journal 107(442): 597–617. Hinkle, Lawrence, Alberto Herrou-Aragon, and Keiko Kubota. 2003. “How Far Did

Africa’s First Generation Trade Reforms Go?” AFR Working Paper 58a. World Bank, Africa Region, Washington, D.C.

Limao, Nuno and Venables, Anthony. 2001. “Infrastructure, Geographical

Disadvantage and Transport Costs.” World Bank Economic Review (15)3: 451–79. Lindauer, D. and Velenchik, A.. 1994. “Can African Labor Compete?,” in Lindauer, D.

and M. Roemer (eds.), Asia and Africa: Legacies and Opportunities in Development, San Francisco, ICS Press: 269-304

Marchat, Jean-Michel.1997. “The Impact of Tax Regulations on Firm Entry in Côte

d’Ivoire.” RPED Discussion Paper 79. World Bank, Regional Program for Enterprise Development, Washington, D.C.

McArthur, John, and Francis Teal. 2002. “Corruption and Firm Performance in Africa.”

CSAE WPS/2002-10. Centre for the Study of African Economies, University of Oxford, Department of Economics, Oxford, United Kingdom.

Morrison, Catherine, and Amy Schwartz. 1996. “State Infrastructure and Productive

Performance.” American Economic Review 86(5): 1095–111.

52

Obwona, Marios. 2001. “Determinants of FDI and their impact on economic growth in Uganda.” African Development Bank.

Olofin, S. 2002. “Trade and competitiveness of African economies in the 21st century.”

African Development Bank. Onjala, Joseph. 2002. “Total Factor Productivity in Kenya: Links with trade policy.”

AERC Research Paper #118. Soderbom, Mans, and Francis Teal. 2000. “Skills, investment and exports from

manufacturing firms in Africa.” CSAE WPS/2000-8 ———. 2002. “Size and Efficiency in African Manufacturing Firms: Evidence from Firm-

Level Panel Data.” CSAE WPS/2002-07. Centre for the Study of African Economies, University of Oxford, Department of Economics, Oxford, United Kingdom.

———. 2003. “Are Manufacturing Exports the Key to Economic Success in Africa?”

Journal of African Economies 12(1): 1–29. Soderbom, Mans, Francis Teal, and Anthony Wambugu. 2002. “Does Firm Size Really

Affect Earnings?” CSAE WPS/2002-8. Centre for the Study of African Economies, University of Oxford, Department of Economics, Oxford, United Kingdom.

Teal, Francis. 1996. “The Size and Sources of Economic Rents in a Developing Country

Manufacturing Labor Market.” Economic Journal 106(437): 963–76. ———. 1999. “Why Can Mauritius Export Manufactures and Ghana Not?” CSAE

WPS/99-10. Centre for the Study of African Economies, University of Oxford, Department of Economics, Oxford, United Kingdom.

Transparency International. 2003, “Public finance management in Zambia,” available at

http://www.tizambia.org.zm/reports.htm van de Walle, Nicolas. 2001, African Economies and the Politics of Permanent Crisis, 1979-

1999. Cambridge: Cambridge University Press. World Business Environment Survey Interactive Dataset, World Bank Group. Available

at http://info.worldbank.org/governance/wbes/index1.html Weinhold, Diana, and James Rauch. 1999. “Openness, Specialization and Productivity

Growth.” Canadian Journal of Economics 32(4): 1009–27.

53

Wood, Adrian. 1994. North-South Trade, Employment and Inequality. Oxford University

Press. Wood, Adrian and Berge, Kersti. 1997. “Exporting manufactures: human resources,

natural resources and trade policy.” Journal of Development Studies (UK), 34: 35-59. Wood, Adrian and Mayer, Jorg. 1998. “Africa’s export structure in a comparative

perspective.” Geneva: United Nations. World Bank. 2004, Doing Business in 2004: Understanding Regulation. New York: Oxford

University Press.