Chapter 6: Other aspects of the investment climate: functioning of the labor market, micro enterprises, and gender differences.To what extent are enterprises in Nigeria constrained by labor market regulations and skills availability? Do micro firms or firms managed by female entrepreneurs face different constraints? The Investment Climate Survey can provide some guidance in response to these.
An overwhelming majority of firms in Nigeria do not perceive either a shortage of skilled workers or labor regulations to be a major or very severe impediment to growth. Only about 1 percent of all manufacturing firms report either constraint to be a major or very severe impediment. The same holds true for the retail and services sector.
Labor skills. As table 6.1 shows nearly half of manufacturing firms in Nigeria report that their typical worker has more than 12 years of schooling. This is higher than all the comparator countries. However, for most countries the typical manufacturing sector worker has between 7 and 12 years. In contrast, only 31 percent of Nigerian manufacturing firms have workers with that level of schooling. Relative to its comparators, only about a fifth of Nigerian firms' typical workers have fewer than six years of schooling.
About 26 percent of firms provide training to their workers. In the firms that provide training, nearly 60 percent of skilled workers and about 23 percent of unskilled workers received training. Among manufacturing firms, a firm that provides training has a value added per worker that is nearly 25 percent higher than firms that do not. However, this effect is driven largely by the size of the firm. Figure 6.1 shows the proportion of firms with on-the-job training and the percentage of workers trained across a range of firm characteristics. There is a modest "firm size-training provision" correlation: firms with 100 plus employees are more than twice as likely to provide training as firms with fewer than 20 workers. Holding other factors constant, only the firm-size correlation is significant. Unlike results from similar analyses in South and East Africa, firms that are active in HIV prevention or testing of their workers appear no more likely to provide training (Ramachandran and others 2005). There was also no evidence for a particular state having a particular effect on training.
Conditional on providing training, firms in Nigeria compare favorably with comparator countries with respect to the proportion of the skilled workforce that is trained. Only Kenya reports a higher proportion. It is important to point out once again, that the data used in table 6.2 are unable to illustrate any differences in the quality of training provided.
Labor regulations. Labor regulations are considered even less of an impediment. Less than 1 percent of all sampled firms find labor regulations to be a major constraint: manufacturing (1.3), retail (0.4), and services (0.1). Just over 2 percent of firms reported that labor regulations had affected hiring or firing decisions. This is consistent with other evidence. The Doing Business report collects detailed information on how labor regulations affect hiring, firing, and rigidity of employment. On the basis of these regulations, the report calculates measures of labor regulation. Nigeria is ranked in the top one-third of all countries with respect to labor regulations. This ranking is considerably higher than that of all other comparators.
[FIGURE 6.1 OMITTED]
Wage comparisons across firms in Nigeria. Understanding the wage-setting mechanisms operating in the labor market is vital to the design of policies to improve the performance of the labor market. Table 6.3 shows tentative evidence that very large firms pay wages for production workers that are nearly 70 percent higher than firms with fewer than 20 employees. The same is true of nonproduction worker remuneration which is twice as much in large firms relative to smaller firms.
The location of a firm exerts an important effect on compensation. Consistent with the literature on agglomeration, firms located in the more industrialized states pay nearly 35 percent more for production workers and 49 percent more for nonproduction workers than firms in the less industrialized states.
Constraints to business. Table 6.4 indicates that the main obstacles faced by micro firms (1) are the same as those faced by firms in the formal sector: (2) electricity, access to finance, and cost of finance followed by corruption, transportation, and crime.
There is a significant variation in these results across states (table 6.5). For instance, 92 percent of firms in Anambra perceive electricity to be a significant constraint, whereas in Ogun, Sokoto, and Cross River about 60 percent of firms do. The variation across states is higher when we look at some of the other main constraints: 79 percent of firms in Abia perceive access to finance as a significant constraint, compared with only 20 percent of firms in Sokoto; 73 percent of firms in Abia and Anambra perceive the cost of finance to be a significant constraint, versus only 13 percent of firms in Sokoto; and no firms in Sokoto identify corruption as a major problem, whereas it is ranked as significant by 77 percent in Bauchi. As for transportation, it is reported to be a significant constraint by 14 percent of firms in Kaduna and by 53 percent of firms in Bauchi.
The impact of some of these constraints on micro firms' costs is similar to that seen in the formal economy. The breakdown of indirect costs amounts to approximately 12 percent of total sales (table 6.6). Electricity (7.5 percent of sales) and production lost while in transit (2 percent of sales) are the two main drivers of such costs. These affect different types of firms in different ways. Electricity is more of a problem for manufacturing micro firms (8 percent). As for the production lost while in transit, which represents a loss of 2.1 percent of sales, it affects registered firms in particular (2.8 percent versus 1.5 percent) and firms located in the less industrialized states (3.1 percent of sales versus 1.1 percent). Bribes represent a loss of 1.4 percent of sales. Finally, theft, robbery, and arson are responsible for a loss of 1.1 percent of sales, varying according to the level of industrialization (1.4 percent in the less industrialized states versus 0.7 percent in the remaining).
Comparison between formal sector and micro firms. As we can see from figure 6.2 and figure 6.3, there are minor differences between firms in the formal sector and micro firms in the identification of their main constraints and in regard to indirect costs.
Micro firms and firms in the formal sector are equally affected by power outages ( table 6.7). The most significant difference is that more firms in the formal sector have generators (86 percent versus 53 percent of micro firms).
[FIGURE 6.2 OMITTED]
On Regulatory Burden
Not surprisingly, firms from the formal sector also face a heavier regulatory burden. They spend a higher percentage of senior management time with regulations, and they have a higher probability of being visited by officials. Table 6.8 shows that, on average, 4.5 percent of senior management time of micro firms is spent with government regulations. Obviously this burden falls more heavily on registered firms. State/local government-level regulation appears to be slightly more of a burden than federal-level regulation. Even though the cost associated with regulations, as a percentage of annual sales, is relatively stable across states, it reaches its maximum in Enugu (4.7 percent of sales) and its minimum in Sokoto (0.8 percent). It is higher for registered firms and for those located in states with a better regulatory environment. On average close to 77 percent of all firms were visited by officials, and on average this occurred 3.8 times each year. The probability of having been visited is higher for registered firms. This probability also varies across states, ranging from 44 percent in Enugu to 93.8 percent in Abia. The number of visits per year is higher for registered firms.
[FIGURE 6.3 OMITTED]
The percentage of annual sales spent on gifts/informal payments, as well as the percentage of the contract value paid, are higher for firms in the formal sector (table 6.9). However, government officials are held in higher regard in the formal sector, where 43.5 percent of firms believe them to have a consistent and predictable interpretation of the law, compared with 32.5 percent of micro firms.
On average, micro firms identify the difficulty of getting information on what needs to be done to register a business as the most significant obstacle, followed by the time needed to complete registration procedures (38 percent and 33 percent, respectively). The financial cost of completing registration is a lesser burden (table 6.10). On average, only 30 percent of micro firms complain about registration costs. An even lower percentage identify the minimal capital requirements for registration (25 percent) and the financial burden of taxes on registered enterprises (19 percent) as the most significant obstacle.
Women Entrepreneurs in Nigeria
National levels of participation. In Nigeria, about 20 percent of formal enterprises are run by women--14 percent of all manufacturing firms and 26 percent of firms operating in the services sector. As such, Nigeria does not rank high in comparison with other African countries, as figure 6.4 shows. The share of women entrepreneurs is higher in Nigeria than in Niger, Mauritius, DRC, and Mauritania, but it is lower than in Madagascar, Angola, Uganda, and Cameroon, not to mention Botswana and Cape Verde.
Sector characteristics. A fundamental difference between men and women entrepreneurs exists in the type of sector in which they operate. Women operating in the formal sector are highly concentrated in a few specific activities--mostly retail (23 percent) and the garment industry (37 percent). Men are more evenly distributed across industrial sectors. Women are almost absent from sectors such as wood, metal, chemicals, construction, and transport, areas in which men dominate.
[FIGURE 6.4 OMITTED]
Regional variations. The level of female participation in entrepreneurship varies widely across regions of Nigeria (table 6.11). The states that are part of the southeast region (Abia, Anambra, Enugu), which is traditionally a region of traders rather than farmers, as well as the capital state of Abuja and Nigeria's biggest city, Lagos, are all characterized by high rates of female entrepreneurship in the formal sector--in manufacturing, services, or both. At the other extreme, Bauchi, in the northeast, is the state with the lowest share of formal businesses run by women (manufacturing and services combined). Low rates of female entrepreneurship are also found in the north central states, such as Kaduna and Kano. Table 6.12 provides more sub-sector detail. It shows the percentage of female entrepreneurs in the garment industry and retail by state, it is evident that in the northern states, the percentage of entrepreneurs operating in the garment industry who are women is lower than the national average, at 7 percent in Sokoto, 13 percent in Kaduna, and 17 percent in Bauchi. Similarly, the percentage of women entrepreneurs in retail in the northern states tends to be lower than the national average.
However, as table 6.11 portrays, female entrepreneurship is not systematically higher in more or less industrialized regions (20 percent versus 21 percent). The micro enterprise sector is different. At 30 percent, the rate of female entrepreneurship is higher than it is in the formal sector and rates of female entrepreneurship in the micro sector are higher in more industrialized states (36 percent versus 23 percent).
Age and education levels. Male and female entrepreneurs operating in the formal sector do not differ much with respect to their personal traits, such as age and education. Women are only slightly younger than men, and there are no remarkable differences in education (see table 6.13). In the micro sector, although the education level is lower than in the formal sector for both men and women, women have a higher education level than men. Although 31 percent of men do not go beyond the primary education level in the micro sector, this percentage is only 21 percent among women, with a higher share of women in this sector with vocational training. Moreover, unlike for men, the percentage of women with a graduate degree is as high in the micro sector as in the formal sector.
Gender Differences in Investment Climate Constraints
Figure 6.5 shows the percentage of male and women entrepreneurs who believe that a constraint is "major" or "very severe," for the formal sector (manufacturing and services combined) (3) and the micro sector. In the formal sector, men and women tend to agree on the level of severity of many constraints. Electricity, access to finance, and cost of finance stand out as the three most severe constraints for both men and women. In the micro sector, the most severe constraints are the same as in the formal sector--electricity, access to finance, and cost of finance. Moreover, corruption and crime are relatively more important than in the formal sector, and this is true for both men and women.
[FIGURE 6.5 OMITTED]
The results presented in figure 6.5, although giving a summary picture of the differences in perceived constraints by gender of the business owner, do not take into account that women and men entrepreneurs are not all the same--as noted, they operate in different industrial sectors and have different personal characteristics. This can affect their opinions about the severity of the obstacles they face. Controlling for these variables, the gender gap in the formal sector is usually small in percentage points. The gender gap in perceptions (adjusted for individual and firm-level characteristics) is very different in the micro sector.
In the micro sector men judge almost all constraints as more severe than women do, and the gender gap for several constraints is larger than in the formal sector. The biggest differences exist for corruption, crime, and cost of finance (10 or more percentage points difference), but substantial gaps are also found for tax administration, access to finance, access to land, and macro and political instability.
Because perceptions could be misleading, in what follows we provide some evidence of the difference between men and women business owners in "objective" measures of the quality of the business environment, focusing on those constraints that in the opinion of the entrepreneurs are the most pressing ones--electricity, access to finance, and cost of finance.
Electricity. Both men and women are extremely likely to have experienced a power outage. Ownership of a generator is similar for men and women in manufacturing, whereas in the micro sector the percentage of female entrepreneurs owning a generator is much lower (45 percent vs. 56 percent). Although women operating in manufacturing experienced on average 10 hours a month longer (or +4 percent) power outages than did men in the same sector, they do not appear to have been more affected by those power outages in regard to average percentage of sales lost (table 6.14). However, in the garment subsector, in which a large percentage of female entrepreneurs operate, women do indeed claim larger losses than men because of power outages (10.7 percent vs. 8.2 percent of sales, on average). In looking at retail--which is another "female-intensive" sector--there are differences depending on whether this activity is formal or informal (micro). In the formal retail sector women appear to have experienced lower losses, whereas in the informal, micro sector women experienced larger losses than men as a consequence of power outages.
Access to finance. Men and women rely largely on internal funds and retained earnings for operating capital (66 percent-67 percent in manufacturing, 72 percent-76 percent in services, 76 percent in the micro sector) as well as credit from suppliers and using advance payments from customers (about 30 percent in manufacturing and about 20 percent in services and the micro sector) (see table 6.15). An extremely small minority uses the formal financial sector (less than 1 percent), and only 9 percent of men and 8 percent of women in the manufacturing and service sector applied for a loan in 2006.
For long-term finance, there is again very little difference between men and women (see table 6.16). Both rely almost exclusively on internal funds and retained earnings in manufacturing, services, and the micro sector. The only small difference is that women are more likely in manufacturing and the micro sector to rely on family, friends, and informal networks.
The evidence also indicates that the percentages of men and women with an overdraft or line of credit are extremely small (see table 6.17), with little differences in the formal manufacturing and services sectors. However, in the micro sector, women are much less likely than men to have overdrafts (eight times less) and lines of credit (about three times less). For those who considered access to finance to be a very serious problem, men were equally divided across three main reasons--high interest rates, lack of collateral, and complex application procedures. Conversely, women were far more likely to blame the complexity of the application procedures (about 35 percent vs. 26 percent of men). Women are also more likely to indicate that they did not believe the loan would have been approved when they decided not to apply for it.
Gender Differences in Productivity
In those activities in which women's participation levels are high, there are no substantial differences between the performance of female-owned and male-owned enterprises. Figure 6.6 shows the ratio of the value added per worker in male-owned over female-owned enterprises. In food and retail this ratio ranges between 0.9 and 1; in garments it is more than 1.2, that is, female-owned enterprises have on average a 20 percent higher value added per worker than male-owned enterprises. This suggests that female-owned enterprises are no less efficient than male-owned enterprises. Women may be capital constrained, but it affects the selection of the type of activity, not the productivity of the firm once the business has been set up.
To verify this, total factor productivities in manufacturing are also estimated, using one-step Cobb-Douglas production functions. (4) The results further confirm that there are no significant differences in productivity between male- and female-owned manufacturing enterprises. But that is not the case at the state level. In three states (Bauchi, Kano, and Sokoto) female-owned enterprises are significantly and substantially less productive than male-owned enterprises.
This chapter has analyzed a range of other variables affecting firm performance and investment climate differences. Clearly labor market regulations are a minor issue relative to other investment climate constraints. The results for labor skills merit further analysis--looking in more depth at the sector and industry context. The similarities in the ranking of constraints between informal and formal firms and "lack of information" constraints to registration provide important insights for prioritizing reform agendas and designing implementation arrangements. The most relevant differences between men and women entrepreneurs in Nigeria are threefold: (i) propensity to become entrepreneurs, given that only 2 of 10 entrepreneurs are women; (ii) the regional differentials between the southern and northern regions and the concentration of women in specific sectors--essentially garments and retail (in both the formal and micro sectors); and (iii) although women may have greater hurdles entering into business, they do at least as well as men once the enterprise is established.
[FIGURE 6.6 OMITTED]
(1.) Micro firms are firms with fewer than five full-time employees.
(2.) Formal sector consists of small, medium, and large firms.
(3.) The differences between manufacturing and services in the levels and the gender gap of the business constraints are very small, so we pooled the two sectors in the descriptive analysis.
(4.) With the logarithm of the value added as the dependent variable as a function of labor (logarithm of the number of permanent employees) and capital (logarithm of the book value of assets).
Table 6.1 Percent of Firms Saying That the Average Worker in the Firm Has Completed Different Levels of Schooling 0-6 years 7-12 years >12 years Kenya (2006) 15 68 17 South Africa (2003) 10 78 12 Brazil (2003) 33 59 8 India 2002 26 55 19 Nigeria (2007) 21 31 48 Source: Investment Climate Surveys. Note: Cross-country comparisons are only for manufacturing enterprises. Comparable data are unavailable for the other comparator countries. Table 6.2 Firm-Based Training: Prevalence and Percent of Workers Trained % firms offer % production % nonproduction Country training workers trained workers trained India 2005 16 7 6 Indonesia 2003 23 -- -- Kenya 2006 41 66 50 Venezuela 2006 49 -- -- Nigeria 2006 26 58 24 South Africa 2003 64 45 47 China 2003 72 48 25 Source: Investment Climate Surveys. Note: Cross-country comparisons are only for manufacturing enterprises. Table 6.3 Median Monthly Wages by Occupation in 2005 U.S. Dollars Production Nonproduction Firm Category workers workers <20 70 86 20-99 91 109 >99 120 179 Domestic 77 98 Foreign 151 116 Total 78 98 Note: All wages are converted to 2005 dollars using the exchange rate from the World Development Indicators. Table 6.4 Major or Very Severe Constraints as Reported by Micro Firms State Registered Constraint TOTAL Yes No Electricity 72% 68% 75% Access to finance (e.g., collateral) 64% 66% 62% Cost of finance (e.g., interest rates) 56% 58% 54% Corruption 35% 39% 33% Transportation 33% 32% 33% Crime, theft, and disorder 32% 35% 29% Tax rates 25% 33% 18% Access to land for expansion / relocation 24% 22% 26% Macroeconomic environment 20% 25% 15% Tax administration 19% 26% 13% Business licensing and permits 14% 14% 14% Political environment 14% 16% 12% Practices of competitors in informal sector 14% 20% 9% Customs and trade regulations 8% 10% 7% Inadequately educated workforce 5% 6% 4% Telecommunications 4% 6% 3% Labor regulations 2% 2% 3% Industry Constraint Manuf. Retail Other Electricity 82% 68% 80% Access to finance (e.g., collateral) 66% 63% 69% Cost of finance (e.g., interest rates) 59% 54% 60% Corruption 35% 35% 40% Transportation 41% 32% 24% Crime, theft, and disorder 39% 30% 36% Tax rates 36% 24% 18% Access to land for expansion / relocation 27% 23% 25% Macroeconomic environment 25% 18% 22% Tax administration 29% 17% 18% Business licensing and permits 17% 14% 4% Political environment 11% 14% 13% Practices of competitors in informal sector 14% 14% 18% Customs and trade regulations 5% 10% 2% Inadequately educated workforce 4% 5% 7% Telecommunications 6% 4% 4% Labor regulations 2% 2% 4% More Less Constraint industrialized industrialized Electricity 66% 78% Access to finance (e.g., collateral) 61% 67% Cost of finance (e.g., interest rates) 52% 60% Corruption 34% 38% Transportation 30% 35% Crime, theft, and disorder 29% 35% Tax rates 25% 26% Access to land for expansion / relocation 25% 23% Macroeconomic environment 23% 16% Tax administration 19% 20% Business licensing and permits 14% 14% Political environment 14% 13% Practices of competitors in informal sector 17% 11% Customs and trade regulations 11% 5% Inadequately educated workforce 7% 3% Telecommunications 4% 5% Labor regulations 3% 2% State Better Worse regulatory regulatory Constraint environment environment Electricity 72% 71% Access to finance (e.g., collateral) 58% 70% Cost of finance (e.g., interest rates) 50% 60% Corruption 36% 35% Transportation 31% 34% Crime, theft, and disorder 26% 37% Tax rates 22% 28% Access to land for expansion / relocation 24% 24% Macroeconomic environment 22% 18% Tax administration 19% 19% Business licensing and permits 11% 17% Political environment 16% 12% Practices of competitors in informal sector 16% 12% Customs and trade regulations 7% 9% Inadequately educated workforce 4% 6% Telecommunications 5% 3% Labor regulations 4% 1% Source: Investment climate survey in Nigeria. Table 6.5 Major or Very Severe Constraints as Reported by Micro Firms--by State State Constraint TOTAL Abia Abuja Electricity 72 79 64 Access to finance (e.g., collateral) 64 79 68 Cost of finance (e.g., interest rates) 56 73 56 Corruption 35 29 28 Transportation 33 29 32 Crime, theft, and disorder 32 42 16 Tax rates 25 23 12 Access to land for expansion/ relocation 24 17 20 Macroeconomic environment 20 8 44 Tax administration 19 19 16 Business licensing and permits 14 10 4 Political environment 14 10 20 Practices of competitors in informal sector 14 2 28 Customs and trade regulations 8 0 24 Inadequately educated workforce 5 0 12 Telecommunications 3 2 0 Labor regulations 2 2 20 State Constraint Anambra Bauchi Electricity 92 83 Access to finance (e.g., collateral) 71 63 Cost of finance (e.g., interest rates) 73 57 Corruption 25 77 Transportation 35 53 Crime, theft, and disorder 35 13 Tax rates 21 30 Access to land for expansion/ relocation 27 30 Macroeconomic environment 8 3 Tax administration 17 20 Business licensing and permits 15 0 Political environment 6 27 Practices of competitors in informal sector 21 0 Customs and trade regulations 6 3 Inadequately educated workforce 0 0 Telecommunications 2 7 Labor regulations 2 0 State Constraint Cross River Enugu Kaduna Electricity 61 80 62 Access to finance (e.g., collateral) 76 60 48 Cost of finance (e.g., interest rates) 67 44 46 Corruption 43 40 14 Transportation 22 48 14 Crime, theft, and disorder 33 54 24 Tax rates 43 18 20 Access to land for expansion/ relocation 31 18 24 Macroeconomic environment 29 28 20 Tax administration 39 8 16 Business licensing and permits 16 24 2 Political environment 18 12 18 Practices of competitors in informal sector 12 20 10 Customs and trade regulations 8 2 4 Inadequately educated workforce 4 10 0 Telecommunications 6 8 4 Labor regulations 0 4 0 State Constraint Kano Lagos Ogun Electricity 75 68 58 Access to finance (e.g., collateral) 65 73 52 Cost of finance (e.g., interest rates) 62 59 32 Corruption 43 43 32 Transportation 24 46 36 Crime, theft, and disorder 24 41 32 Tax rates 29 32 22 Access to land for expansion/ relocation 31 25 20 Macroeconomic environment 22 25 16 Tax administration 32 14 10 Business licensing and permits 16 21 20 Political environment 13 19 4 Practices of competitors in informal sector 25 14 10 Customs and trade regulations 7 19 8 Inadequately educated workforce 3 16 8 Telecommunications 4 5 2 Labor regulations 4 0 0 Constraint Sokoto Electricity 60 Access to finance (e.g., collateral) 20 Cost of finance (e.g., interest rates) 13 Corruption 0 Transportation 20 Crime, theft, and disorder 0 Tax rates 13 Access to land for expansion/ relocation 0 Macroeconomic environment 7 Tax administration 13 Business licensing and permits 7 Political environment 0 Practices of competitors in informal sector 0 Customs and trade regulations 13 Inadequately educated workforce 0 Telecommunications 0 Labor regulations 0 Source: Investment climate survey in Nigeria. Table 6.6 Indirect Costs--Micro Firms Indirect costs Registered Industry as % sales TOTAL Yes No Manuf. Retail Other Electricity 7.5 8.2 6.9 8.4 7.1 9.5 Production lost while in transit 2.1 2.5 1.5 1.8 2.1 2.5 Bribes 1.4 1.7 1.2 1.7 1.3 1.3 Theft, robbery, or arson 1.1 1.1 1.0 1.2 1.0 0.9 Total indirect costs 12.1 13.8 10.5 13.1 11.5 14.2 State Indirect costs More in Less indus- as % sales industrialized trialized Electricity 7.8 7.2 Production lost while in transit 1.1 3.1 Bribes 1.1 1.7 Theft, robbery, or arson 0.7 1.4 Total indirect costs 10.8 13.5 Source:Investment climate survey in Nigeria. Table 6.7 Infrastructure Perceptions--Formal Sector versus Micro Firms Quality measure Formal Micro Electricity % firms experienced power outages 96 98 Average duration of outages per month (hours) 196 207 % firms with own generator 66 53 % electricity coming from own generator 61 60 Source: Investment climate survey in Nigeria. Table 6.8 Regulatory Burden--Micro Firms Registered Quality measure TOTAL Yes No % senior man- agement time spent with regulations 4.5 5.4 3.6 at the state/local government level 2.7 3.3 2.2 at the federal level 1.8 2.1 1.4 Cost associated with regula- tions (% annual sales) 2.3 3.0 1.8 at the state/local government level 1.4 1.7 1.2 at the federal level 0.9 1.3 0.6 % firms visited by officials 77 86.2 69.1 Number of inspection vis- its (last 12 months) 3.8 4.2 3.3 Industry Quality measure Manuf. Retail Other % senior man- agement time spent with regulations 4.0 4.3 6.1 at the state/local government level 2.5 2.6 3.6 at the federal level 1.5 1.7 2.5 Cost associated with regula- tions (% annual sales) 2.5 2.1 3.6 at the state/local government level 1.3 1.4 1.8 at the federal level 1.2 0.7 1.8 % firms visited by officials 77.1 77.2 75.6 Number of inspection vis- its (last 12 months) 3.5 3.9 3.4 State More Less Quality measure industrialized industrialized % senior man- agement time spent with regulations 4.1 5.0 at the state/local government level 2.4 3.1 at the federal level 1.7 1.9 Cost associated with regula- tions (% annual sales) 2.1 2.7 at the state/local government level 1.1 1.8 at the federal level 1.0 0.9 % firms visited by officials 76.6 77.5 Number of inspection vis- its (last 12 months) 3.5 4.2 Source: Investment climate survey in Nigeria. Table 6.9 Perception of Government and Regulations--Formal Sector versus Micro Firms % firms that agree with statement Formal Micro Consistent and predictable interpretation of the law 43.5 32.5 Informal payments/gifts commonplace 33.2 30.0 Advance knowledge of informal payment/gift 24.6 20.0 Percentage of annual sales spent on informal payments/gifts 2.0 1.4 Percentage of contract value paid to secure contract 5.3 4.3 Source:Investment climate survey in Nigeria. Table 6.10 Percentage of Firms Reporting Major or Very Severe Obstacles to Registering a Business--Micro Firms Registered Industry Obstacle TOTAL Yes No Manuf. Retail Other Difficulty of get- ting information on what you need to do to register 38% 34% 41% 37% 38% 33% Time to complete registration procedures 33% 24% 40% 33% 23% 38% Financial cost of completing registration 30% 27% 34% 29% 31% 31% Minimum capital requirements for registered enterprises 25% 21% 28% 24% 24% 31% Financial burden of taxes on registered enterprises 19% 18% 19% 17% 20% 13% Administrative burden of com- plying with all tax laws 15% 7% 22% 13% 15% 16% Other administra- tive burdens imposed on registered businesses 15% 10% 18% 14% 16% 7% Strict labor mar- ket rules regis- tered businesses must comply with 12% 13% 11% 12% 12% 11% State Better Worse Obstacle regulatory regulatory Difficulty of get- environment environment ting information on what you need to do to register 45% 31% Time to complete registration procedures 42% 24% Financial cost of completing registration 39% 22% Minimum capital requirements for registered enterprises 30% 20% Financial burden of taxes on registered enterprises 24% 14% Administrative burden of com- plying with all tax laws 16% 15% Other administra- tive burdens imposed on registered businesses 17% 12% Strict labor mar- ket rules regis- tered businesses must comply with 16% 8% Source:Investment climate survey in Nigeria. Table 6.11 Percentage of Formal Firms Owned by Women, by State and Sector Region * Manufacturing Services Sokoto NC 9.0 24.7 Kaduna NC 9.7 21.6 Kano NC 12.8 19.4 Bauchi NE 10.3 16.2 Abuja MB 14.1 42.9 Lagos SW 14.1 25.5 Ogun SW 15.3 23.1 Cross River SS 13.4 20.6 Anambra SE 12.0 25.9 Enugu SE 22.2 27.9 Abia SE 21.7 23.7 All 13.8 24.7 More industrialized states ([dagger]) 13.3 25.3 Less industrialized states 15.0 24.0 Number of observations 898 900 Formal (manufac- turing and services) Micro Sokoto 21.0 35.7 Kaduna 15.9 49.0 Kano 15.9 23.9 Bauchi 13.5 17.2 Abuja 30.8 36.4 Lagos 20.1 25.0 Ogun 19.7 50.0 Cross River 18.2 20.4 Anambra 21.1 22.9 Enugu 25.9 30.6 Abia 22.9 18.8 All 20.2 29.5 More industrialized states ([dagger]) 19.7 35.5 Less industrialized states 21.0 23.2 Number of observations 1,798 485 Source: Investment climate survey in Nigeria. Note: The sample does not include public and foreign-owned enterprises. Percentages in italics calculated for samples with less than 30 obs. States are ordered according to their north-south location. * NC: north central; NE: northeast; MB: midbelt; SW: southwest; SS: south south; SE: southeast. ([dagger]) More industrialized states are Lagos, Abuja, Kano, Kaduna, Ogun. Table 6.12 Percentage of Female Entrepreneurs by State and Selected Subsectors State Garment Retail Sokoto 7.1 17.6 Kaduna 12.5 13.9 Kano 31.3 18.9 Bauchi 16.7 10.5 Abuja 33.3 28.6 Lagos 53.8 37.7 Ogun 66.7 29.0 Cross River 30.0 22.9 Anambra 60.0 20.0 Enugu 64.0 18.6 Abia 40.0 14.8 All Nigeria 37.3 23.1 Source:Investment climate survey in Nigeria. Table 6.13 Education Level of the Business Owner, by Industrial Sector Formal (manufacturing and services) Male-owned Female-owned Up to primary 13.3 14.4 High school 42.7 41.6 Vocational 37.0 40.5 Graduate degree 7.0 3.5 Total 100.0 100.0 Micro Male-owned Female-owned Up to primary 30.8 20.9 High school 48.8 48.5 Vocational 18.7 27.6 Graduate degree 1.8 3.0 Total 100.0 100.0 Table 6.14 Percent of 2006 Sales Lost as a Consequence of Power Outages, by Industrial Sector and Sex of the Business Owner Male Female Manufacturing 10.1 9.4 Services 8.9 7.2 Micro 8.6 8.6 Selected industrial sectors: Garment industry 8.2 10.7 Retail (formal sector) 8.6 6.4 Retail (micro sector) 8.1 8.6 Source: Investment climate survey in Nigeria. Table 6.15 Composition of Working Capital, by Sector and Sex of Business Owner Manufacturing Services Male Female Male Female Internal funds 66.9 65.6 72.3 76.4 Purchases on credit/advances from customers 28.9 30.8 22.4 18.7 Borrowed from: private commercial banks 0.8 0.1 1.2 0.7 state-owned banks 0.1 0.0 0.0 0.0 nonbank institutions 0.1 0.0 0.0 0.0 family and friends 2.9 3.3 3.6 3.7 informal sources 0.4 0.2 0.4 0.4 Other 0.0 0.0 0.1 0.0 Total 100.0 100.0 100.0 100.0 Micro Male Female Internal funds 75.7 76.0 Purchases on credit/advances from customers 19.6 19.3 Borrowed from: private commercial banks 0.6 0.2 state-owned banks 0.0 0.0 nonbank institutions 0.0 0.0 family and friends 3.7 4.4 informal sources 0.4 0.1 Other 0.0 0.0 Total 100.0 100.0 Source: Investment climate survey in Nigeria. Table 6.16 Purchase of Fixed Assets and Sources of Long--Term Financing, by Sector and Gender Manufacturing Services Micro Male Female Male Female Male Female % purchasing fixed assets 47.3 45.5 40.9 32.3 24.9 15.4 Sources of financing Internal funds 91.6 90.3 93.0 93.9 94.4 88.2 Purchases on credit/advances from customers 2.6 2.5 1.8 1.8 3.5 5.5 Borrowed from: private commercial banks 0.7 0.6 1.1 1.4 0.0 0.0 state-owned banks 0.3 0.0 0.1 0.3 0.1 0.0 nonbank 0.2 0.0 0.1 0.0 0.0 0.0 institutions family and friends 4.1 5.9 3.0 2.4 2.0 5.5 informal sources 0.3 0.3 0.5 0.3 0.0 0.9 Issued new equity 0.2 0.2 0.0 0.0 0.0 0.0 Issued new debt 0.0 0.1 0.0 0.0 0.0 0.0 Other 0.0 0.0 0.4 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: Investment climate survey in Nigeria. Table 6.17 Percentage of Entrepreneurs with Overdraft and Line of Credit, by Sector and Sex of the Business Owner Manufacturing Services Male Female Male Female Overdraft 5.9 4.2 8.5 8.3 Line of credit 2.6 2.8 4.0 3.8 Micro Male Female Overdraft 5.6 0.7 Line of credit 4.1 1.4 Source: Investment climate survey in Nigeria.