1 Business Environment and Firm performance: The Case of Retailing Firms in Cameroon Pierre E Nguimkeu Andrew Young School of Policy Studies - Georgia State University, 14 Marietta Street NW, Atlanta, GA 30303, USA [email protected]October 2013 Abstract This paper examines the impact of business environment on the productivity of retail firms in Cameroon, which represent more than 50% of all firms. Using data from the 2009 Enterprise Surveys an overview of retail activities allows to identify the main factors characterizing the environment in which firms operate, i.e. access to credit, regulatory burden, illicit trade, administrative delays, infrastructure and quality of labour. A Structural econometric analysis is used to quantify the impact of these factors over firm performance. Results are used to suggest policy reforms that would improve the business climate and enhance firms’ productivity. Keywords: Cameroon, Retail trade, Business climate, Productivity, Econometric analysis, Maximum Likelihood, Bootstrap. JEL Classification: C31, C35, C51, D73, O14, O17, L25, L26, L81.
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Business Environment and Firm performance: The Case of Retailing Firms in Cameroon
Pierre E Nguimkeu Andrew Young School of Policy Studies - Georgia State University, 14
This paper examines the impact of business environment on the productivity of retail firms in Cameroon, which represent more than 50% of all firms. Using data from the 2009 Enterprise Surveys an overview of retail activities allows to identify the main factors characterizing the environment in which firms operate, i.e. access to credit, regulatory burden, illicit trade, administrative delays, infrastructure and quality of labour. A Structural econometric analysis is used to quantify the impact of these factors over firm performance. Results are used to suggest policy reforms that would improve the business climate and enhance firms’ productivity.
Keywords: Cameroon, Retail trade, Business climate, Productivity, Econometric analysis, Maximum Likelihood, Bootstrap.
1 Introduction It is well documented that trade is an important channel for growth and development; see e.g., Balassa (1998), Berg and Krueger (2003). However, this growth channel can only be effective so long as the necessary economic and institutional conditions in the domestic market are fulfilled (Winters et al. 2004). Unfortunately, the domestic trade sector in Africa is dominated by the informal sector and suffers from several dysfunctional ailments (Taiwo and Moyo 2011). The case of Cameroon is particularly salient because domestic trade firms represent an impressive share of nearly 52 % of all firms and a workforce of more than 40 % of the service sector jobs, yet produce only less than 18% of the country’s GDP (INS 2009). A central ground for the underperformance of this activity can be found in the nature of the business environment, sometimes also referred to as the investment climate (Stern, 2002).
The purpose of this paper is therefore to analyze and quantify the impact of business environment on firm performance, with a focus on retail firms in Cameroon, in order to find specific solutions that could allow firms to be more productive and competitive both internally and externally. Using data from the 2009 Enterprise surveys conducted by the World Bank an overview of the retail trade sector allows to identify the main factors characterizing the environment in which firms operate. The analysis identifies several factors that negatively affect the well functioning of this activity in Cameroon. The main barriers identified are taxation, illicit trade, lack of infrastructure, lack of access to credit, administrative delays and incompetence of labour. A comparison of the domestic trade indicators of Cameroon with other African countries and the rest of the world shows that in several dimensions, such as the quality of transport used to facilitate the circulation of goods and services, the speed of administrative procedures related to import and export, access to bank loans to pre-finance the purchase of goods, and training opportunities for workers, Cameroon is lagging.
A Structural econometric analysis of the performance of retail firms is conducted by measuring the impact of each of these business environment factors on the gross margins of traders. For this purpose, we estimate the production function of firms using a regression model with multiplicative heteroskedasticity, and the method of quasi-maximum likelihood. The bootstrap method is applied to estimate standard deviations and test parameters’ statistical significance. The estimated model also serves as a basis to evaluate the role of the business structure and market characteristics over the productivity of retail businesses. The results clearly show that the above-mentioned business climate factors create significant shortfalls in the annual gross margins of domestic traders ranging from 4.94 million CFA
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francs for the lack of infrastructure, to 9.72 million CFA francs for the lack of competence of the workforce in a formal retail enterprise with average characteristics. On the other hand, the qualifications of the entrepreneur, the business structure and the adoption of practices such as computerized management, the use of Internet, or membership to a trade group prove very beneficial for the activity. In contrast, gains from being a member of a union or of a large group of traders are quite limited. The results suggest some policy recommendations that can be prioritized and implemented to improve the business climate, the productivity of businesses and thus the competitiveness of domestic trade business in Cameroon.
Studies that have highlighted the business environment problems related to firm performance in Cameroon are quasi inexistent, especially with regard to the trade sector. The most recent one conducted by the Ministry of Commerce has identified the weakness of exports, illicit trade, a market for goods and services dominated by the informal sector, the weakness of the consumer protection, and an environment not conducive to the development of trade (MINCOMM 2010). These problems albeit enumerated, remained very general and the document does not identify or prioritize specific solutions regarding trade activities. Moreover, the methodological approach used is purely qualitative and does not permit to quantify the phenomenon. Other documents that address these concerns are the executive report of the 2009 general enterprise census (INS 2009) and the country summary of the 2009 Enterprise Surveys (World Bank 2009). In this work, we use both a qualitative and a quantitative approach to analyze the performance of domestic traders in Cameroon and propose some solutions. This study is therefore complementary to the abovementioned works.
There are several other studies that have addressed the impact of business environment on firm performance in the economic literature, most of which have focused on a cross-country context (Limao and Venables 2001, Bastos and Nasir 2004, Dollar et al. 2005, Eifert et al. 2005, Escribano and Guasch 2005). A notable exception that focuses on a within-country context is Hallward-Driemeier et al. (2006) who studied investment climate impact on firm performance in China. In these studies, the business environment factors are introduced as aggregate indices for the country (Dollar et al. 2005, Knack et al. 1995) or industry (Hallward-Driemeier et al. 2006). Although such analyses explain what factors affect aggregated macro indicators on average, they fail to pinpoint which factors may be important within different countries, different sectors or different categories of firms.
In the present study, we take an approach that is original in several respects: first, it focuses on firm-level data as well as entrepreneurs’ own perception of the environment. It thus integrates the fact that these factors affect firms in
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different ways (even among firms sharing the same industry), as well as the fact that entrepreneurs, who have heterogeneous abilities and opportunities, could perceive environmental challenges differently. Hence this framework better captures heterogeneity across firms and among business managers in a more refined and disaggregated context. Second, in contrast to previous work our analysis is based on a structural econometric approach which allows not only to quantify the magnitude of the phenomena in terms of monetary shortfalls, and to perform some tests of economic constructs within the retail sector such as economies of scale in production, but could also be used as a base to evaluate the impact of business environment on welfare in a general equilibrium modelling framework. Third, this study departs from most existing ones that are usually more oriented towards intermediary sectors like manufacturing (e.g. Dollar et al. 2006, Eifert et al. 2007, Kinda et al. 2009), but rather focuses on domestic trade which has not received much attention, in spite of having an overwhelming importance in some countries like Cameroon (as explained above). Extrapolating the results from other sectors to the retail sector is not straightforward, particularly because the way some key components, e.g., output and capital are measured in retail is different from how it is done in other sectors (see Baily and Solow 2001, and the discussion in section 3 below).
The rest of the paper is organized as follows. In the second section we present an overview of the trade business in Cameroon and describe its major obstacles. A comparative analysis of the case of Cameroon with that of other regions, particularly sub-Saharan Africa and the rest of the world is also presented. The third section analyses the impact of business environment on the performance of business enterprises through structural econometric modelling. Recommendations and conclusions are given in the fourth and the fifth sections, respectively.
2 The trade business in Cameroon and the main obstacles In this section, we give an overview of the retail trade business in Cameroon and we identify the main obstacles and compare some of its indicators with those of other countries. We use the terms retailing, trade and commerce interchangeably.
2.1 Overview of the trade business in Cameroon
The business of trade includes food retail and general merchandize retail. Trade firms include shops in urban or rural markets, eligible shops in neighborhoods, supermarkets and other stores selling and distributing goods, etc. Since very few firms do exclusively wholesaling in the data and wholesalers usually do retailing as well, we consider wholesaling as an option
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in the retail activity. Trade is part of the tertiary sector, which includes, besides trade, business services to companies or individuals, and which is the most widespread economic sector in Cameroon with a concentration of 85% of companies that gather 68% of all the permanent jobs (INS 2009).
Compared to other activities of the private sector, trade covers about 61.4% of the service sector. It has been the dominant activity in all regions for more than three decades. More than half of the companies engaged in this activity are located in the cities of Douala and Yaoundé (see Figure 1). Both cities hold about 55.7% of Cameroon’s retail activities (INS 2009).
Figure 1: Distribution of commercial enterprises by region
Source: General Enterprise Census 2009 (INS Cameroon)
A classification of commercial businesses on the basis of turnover and number of permanent employee at the consolidated company headquarters, shows that the Cameroon economy is strongly dominated by microenterprises (ME), that is, those that employ less than 5 people and have an annual turnover not exceeding 15 million CFA francs. The latter represent about 78.6% of all commercial enterprises identified in 2009. In contrast, large firms (LE) are less present and represent a fraction of only 0.4% of all commercial enterprises surveyed (see Figure 2).
33.9$
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4.0$2.8$ 2.5$ 3.3$
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Centre$except$Yde$
East$
FarANorth$
LiForal$except$Dla$
North$
NorthAWest$
West$
South$
SouthAWest$
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Figure 2: Distribution of commercial entreprises by size
Source: General Enterprise Census 2009 (INS Cameroon)
The fact that up to 97.1% of trade businesses are either micro or small size enterprises immediately urge one to ask themselves why do business traders concentrate around small and microenterprises? Is this a jurisdictional problem, a lack of access to credit, a lack of human capital, or are there others factors underpinning such a concentration? The next section discusses some possible answers to these questions.
2.2 Barriers to trade business in Cameroon
Business environment, market characteristics and the degree of optimism of business owners and entrepreneurs are key factors in entrepreneurial choice. The 2009 Enterprise Survey raised the opinion of entrepreneurs on their business environment, their relationships with the government and the obstacles they face in carrying out their activities. The responses of business owners surveyed on their views on the business environment showed that 56.3% of business owners of the retail industry are pessimistic, while only 24.2% of them are optimistic (see Figure 3). A comparison with the views obtained in other sectors of the economy shows that entrepreneurs of the retail sector are more pessimistic than others.
78.6%&
18.5%&
2.4%&0.4%&
Micro&Enterprises&(ME)&
Small&Entreprises&(SE)&
Medium&Size&Entreprises&(MSE)&
Large&Entreprises&(LE)&
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Figure 3: General opinion of business owners of retail firms about their business environment (in %)
In order to identify the main obstacles hindering the well functioning of this sector we consider the opinions of the Business owners themselves (or the top managers of the firms). Since they are the ones taking the risks they are best suited to understand and provide us with the more pragmatic views of the business environment. Figure 4 reports the main obstacles indicated by entrepreneurs of the trade sector in the decreasing order of importance. The main obstacles enumerated are taxation, corruption, access to credit, administrative delays and paperwork, illegal competition, infrastructure, financing costs, the public/private dialogue, energy, transportation and justice. Taxation is a major concern for 54.8% of entrepreneurs interviewed in the trade sector. Excessive taxation and customs administrations tend to block or delay the entry and circulation of goods in the country, as well as occasional harassment and arbitrary inspections from the part of the authorities. For about 43.3% of firms, corruption is a major problem that has worsened over time. However, compared to other sectors of the economy, business owners seem to be less worried by corruption practices. Nevertheless, business owners mentioned unfair competition, which includes the phenomenon of smuggling, illicit trade and the commercialization of counterfeit products, which is somewhat related to corruption. About 27.6% of them consider this as a serious obstacle to the well functioning of their business. It is worth noting that, in fact, the last few years have witnessed these phenomena contributing to the downfall of many businesses, the layoffs
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Good$ Fairly$Good$ Bad$ Indifferent$ N.A$
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of hundreds of employees and even the disappearance of many commercial enterprises.
Figure 4: Main obstacles to Trade in Cameroon (in % of business owners’ opinions)
One of the most important obstacles mentioned by entrepreneurs was also the lack of access to credit. There are 33.5% of business owners who consider it as a major obstacle. Credit rationing, transaction costs and high interest rates, as well as excessive collateral requirement have a very negative effect on access to long-term credit. Also among business owners, 29.1% reported that paperwork and other administrative delays are major barriers to their activities. Administrative procedures are relatively complex for government customers, a situation often reinforced by the inconsistency of some administrative regulations. Difficulties related to infrastructure are very common. In fact, 14.8% of entrepreneurs surveyed reported that their activities are hampered by problems related to poor roads, ports, airports and insecurity. In addition to that, there are concerns related to physical transport (12.7%), water supply (5.1%) and opportunities (5.3%). As for water and electricity, the supply network is insufficient and thus forced some companies
0.3$
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0$ 10$ 20$ 30$ 40$ 50$ 60$
No$obstacle$
Concessionary$schemes$
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Supplying$
Sales$outlets$
Competence$and$training$
Labor$legislaDon$
JusDce$
Energy$et$Water$
Transport$
Lack$of$public/private$dialogue$
Infrastructures$
Coût$du$financement$
Illegal$compeDDon$$
AdministraDve$delays$and$paperwork$
Access$to$credit$
CorrupDon$
TaxaDon$
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to install emergency generators, thereby increasing their production costs and making their products relatively less competitive.
2.3 A comparative analysis with other countries There are many criteria that are often used for cross-country comparisons. In this study, we consider a few indicators, which are enough on their own, to compare the business environment and the structures that affect the development of Trade in Cameroon and other countries, including infrastructure development, factors related to the import/export of goods and the financing of entrepreneurship. The lack of road, railroad, maritime infrastructure and other physical methods that impede trade is relatively important within the country compared to other regions. According to the rural accessibility index of the World Bank only 27% of the rural population of Cameroon live within 2 km of an accessible route in any season, against 30% for Saharan Africa. Similarly, Cameroon have a relatively low urban connectivity, with 70 meters of road per 100 000 inhabitants and a road density of 72 kilometres of road per 1,000 squared km, of which only 8.3% are paved.
Figure 5: Transport quality index in some African countries
Source: Africa infrastructure country diagnostic (AICD, 2008)
Figure 5 presents a comparison of the quality of the transport service of some African countries, as measured by the index of logistics performance. The higher the value of the index, the higher is the quality of transport. According to this index, the quality of transport is higher in Kenya and Uganda and lowest in Chad and Burkina Faso, compared to Cameroon.
0.32 0.38 0.33
0.25
0.6
0.45 0.42
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
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Table 1: Comparison of credit access indicators
Indicator Cameroun Sub-Sahara Africa
Rest of the World
Value of the collateral required for a loan (in % of the loan) 213.1 155.2 163.3
Proportion of loans requiring collateral (in % of total loans) 83.2 80.5 78
Proportion of firms requiring a loan (in % of all firms) 82.6 65.1 60.6
Access to credit is a crucial factor for entrepreneurship. It can be seen in Table 1 that not only the proportion of bank loans requiring collateral is higher in Cameroon, but also the value of the collateral needed to obtain such loans is also higher. The collateral requirement is estimated at about 2.13 times the value of the requested loan in Cameroon, while it is 1.55 times in Sub-Saharan Africa and 1.63 times in the rest of the world. This suggests that while domestic trade entrepreneurs are more financially constrained in Cameroon (see the last row of Table 1) they have on average more difficulties in obtaining bank loans than the other regions considered.
Table 2: Comparison of import/export related indicators
Indicator Cameroun Sub-Sahara Africa
Rest of the World
Proportion of firms for which customs is a major constraint 26.3 21.7 17.7
Number of days to clear imports 23.9 13.4 11.3 Number of days to clear exports 15.1 7.5 7.1 Proportion of firms exporting at
Given that the trade business sometimes involves exporting or buying goods from foreign countries to resale in domestic market the functioning of the ports of entry in the country has an important impact on the domestic trade business. Table 2 presents some indicators related to the import and exports of good in Cameroon, in comparison to the other regions. It appears that the time to adjust to clear exports and imports of goods are relatively longer in Cameroon. These delays are on average 15 days for exports and 24 days for imports and are twice as long as the average in the rest of the world. Moreover, the proportion of firms identifying customs regulations as a major obstacle is higher in Cameroon than in other regions.
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Another factor that crucially impacts the performance of retailing firms is the quality of the workforce. In fact, productivity gains from an improved business environment can only be fully realized by firms that hire more highly skilled workers or at least adopt organizational training programs that help improve the skills of workers. However, only 25.5% of trade firms offer a formal training opportunity to their workers in Cameroon, compared to 30.3% in Sub-Saharan Africa and 35.1% for the rest of the world (World bank, 2009).
3 Econometric Analysis of the Performance of Retail Firms in Cameroon
In this section, we use an econometric approach to measure the impact that the business environment as characterized by the various factors identified in the above sections may have on the performance of entrepreneurs in the trade sector. For this purpose, we specify a linear regression model with multiplicative heteroskedasticity and use the method of quasi-maximum likelihood to estimate the model parameters and the bootstrap method to estimate their standard errors and significance.
3.1 Estimating the performance of Commercial firms
To estimate the productivity of firm i, we postulate a relationship between its output Yi and its inputs, capital Ki, and labour Li
Yi=θi f(Ki,Li) (1) Where θi captures the productivity factor of the firm (unobserved by the econometrician). The productivity θi depends on several elements including the environmental factors, firm characteristics and entrepreneur’s ability. Assuming a Cobb-Douglas production function, i.e., f(K,L)=KβK LβL, we have a log-linear relationship:
lnYi= βK lnKi + βLlnLi + lnθi (2) The output Yi is taken as the gross annual margin (or value-added) of the trade firm, that is, the difference between the sales and the cost of goods sold (see, e.g. McAnally 1963). Baily and Solow (2001) explain that value-added generated by retailers provides the best simple measure of retailing output. This measure has three components: the quantity and assortment of goods sold, the selling price of goods sold, and acquisition costs of goods sold. Each of these components may be affected by the characteristics of the firm and the quality of service delivery, by firm operating practices, and the adoption of new information technologies and related business practices. In this analysis we consider two inputs: capital that we approximate with the sales area of the
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store (see Baily and Solow 2001). Although this variable is not a perfect measure, it is strongly correlated with the elements that make up the capital of traders such as the cost of energy storage, refrigeration equipment, lighting, shelving and display equipment monitoring and equipment procurement and delivery. The second component is the labour factor that includes the total number of permanent and temporary workers, which is proportional to the total annual number of hours worked by permanent and temporary employees. In fact, preliminary analysis with aggregated labour hours indicated that both measures could be used alternatively without loss of explanatory power.
The productivity θi is unobserved by the econometrician. We assume that it depends on the characteristics of the firm and the market (see Park and Sauer 2013, King and Park 2004) and the observable characteristics of the entrepreneur (as in Paulson et al. 2006, Nguimkeu 2013). In this study, we generalize these authors by assuming that the productivity factor also depends on the business environment; in particular, it is affected by environmental barriers to trade as noted in the previous sections. We can therefore express the logarithm of the productivity θi of firm i as follows:
lnθi = β0 + Xi’γ + Zi
’δ +Σj αj Fji + εi, (3)
Where Fji is a dummy variable that indicates whether the business owner of firm i perceives factor j as a major obstacle to its operations; Xi is a vector of variables that controls for the entrepreneur’s specific characteristics such as his level of education, experience, gender and status (foreign or not); Zi is the vector of firm-specific characteristics that includes the age of the firm, the type of management (computerized or not), whether the firm is part of a commercial group, whether the firm does wholesaling, whether or not employees are members of a union, the firm’s location (big city or not, size of the locality). The terms εi can be seen as measurement errors or as a zero-mean productivity shocks, which we assume to be independently and normally distributed across firms. Combining equations (2) and (3), we obtain a comprehensive form of the model, which can be written as:
lnYi = β0 + βK lnKi + βLlnLi + Xi’γ+ Zi
’δ + Σj αj Fji + εi. (4)
Given the wide variance in the sizes and types of stores (as evidenced by the descriptive statistics below), and the heterogeneity of businesses, the standard assumption of constant variance of the stochastic error term in this model is likely to be violated. We therefore assume heteroskedasticity by expressing the error variance as a multiplicative function of the explanatory variables (Harvey 1976), i.e.,
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εi∼N(0,σi2) with σi
2=σ2exp(Wi’ψ),
where Wi=[lnKi lnLi Xi’ Zi’ Fi’]’ is the vector of all covariates and Fi=[F1i F2i, …FJi]’ is the vector of business environment factors.
The model parameters are estimated by the method of maximum likelihood. The log-likelihood of the model is given by
Given the size of our sample (described below), the standard errors may not be correctly estimated if we use the asymptotic variance-covariance matrix. We therefore apply the bootstrap method (see Efron and Tibshirani 1986) to accurately estimate the standard deviations of the estimators and test the significance of the coefficients.
3.2 Descriptive Statistics and Empirical Model
The definitions of the variables used and their summary characteristics including sample averages and standard deviations are presented in Table 3. Our sample of formal retail firms represents a total of 153 firms of the retail module of the 2009 Enterprise Survey. For the econometric analysis we also grouped some of the environmental factors (depicted in Figure 4) into single factors, particularly those that could be thought of as describing somewhat similar phenomena and are highly correlated according to our preliminary cross-correlation examination. For example, customs regulations, labour legislation and administrative delays are merged into a single factor called “Regulation” (denoted REGUL); Likewise, crime and political instability are represented by a single factor called “Safety” (denoted SAFETY), etc; see Table 3 for details.
Some features of this data are worth noticing. Companies realize an average annual gross margin of 157 million CFA francs and employ an average of 71 workers per year. Business owners have average years of schooling corresponding to secondary education, and an average of 16 years of work experience. The proportion of female entrepreneurs is very low in the retail trade sector in Cameroon, representing only 16% of entrepreneurs in the sample, and perhaps suggesting the existence of gender barriers to entrepreneurship in Cameroon. The firms in the sample have on average been operating for many years. They have 16 years of age on average and more than 30% of them have an employee’s unionization rate of more than 25%.
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Table 3: Variable description and summary statistics
Variable Description Mean Standard deviation
GM Gross Margin (annual in millions of FCFA) 156.73 433.12 Production factors SAREA Selling Area (in squared meters) 191.88 327.69 LABOR Total number of workers 71.098 485.05 Characteristics of the business owner EDU Education (years of schooling) 15.745 2.644 EXP Experience (years of experience) 16.199 9.317 GENDER Gender, 1=female, 0=male 0.163 0.371 FOREIGN Origin, 1=Foreigner, 0=Cameroonian 0.111 0.315 Characteristics of the firm and the market TYPE Type of activity, 1=wholesale, 0=retail only 0.137 0.345 AGE Age (number of years of operation) 16.56 12.28 MEMBR Membership to a group 1=yes, 0=no 0.235 0.426 GSIZE Group size (number of stores) 1.229 1.061 UNION >25% employees are unionized, 1=yes, 0=no 0.320 0.468 INTRNET Internet connection available, 1=yes, 0=no 0.281 0.451 LOCSIZE Location size of the firm 1.739 0.657 Business environment (Major factors) TAX Taxation 1=yes, 0=no 0.288 0.454 ACCESS Access to credit or to land, 1=yes, 0=no 0.157 0.365 REGUL Customs, licenses, regulations, 1=yes, 0=no 0.039 0.195 CORRUP Justice, corruption, no dialogue, 1=yes 0=no 0.085 0.280 INFRAST Infrastructure, transport, energy, 1=yes, 0=no 0.059 0.236 COMPET Competition of informal, 1=yes, 0=no 0.268 0.444 SAFETY Crime, political instability, 1=yes, 0=no 0.098 0.298 WORKFR Competence of the workforce, 1=yes, 0=no 0.007 0.081
3.3 Results The parameter estimates of the production function of trade margins are presented in Table 4. The coefficient of the selling area is estimated at 0.281. This means that a 10% increase in the sales area is associated with a 2.8% increase in gross margins. The coefficient of labour is estimated at 0.727. This means that a 10% increase in the number of workers is associated with an increase of 7.27% of gross margins. The sum of the coefficients of the two factors of production, selling area (SAREA) and total number of workers (LABOR) is close to unity both numerically and statistically, since the null
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hypothesis of constant returns to scale could not be rejected at the 5% significance. This implies that despite current trends toward larger store formats, optimal store size depends on market setting and organizational structure, but small stores can compete effectively with larger ones.
Estimates of productivity parameters related to the entrepreneur show that the level of education (EDU) and experience (EXP) of the entrepreneur are positively correlated with the gross margins of the company, and that foreign companies tend to make more margins than domestic firms. These results are consistent with those made by other studies that have shown the positive role of education and experience in the performance of Cameroonian firms (see, e.g., Nguetse 2009, Nguimkeu 2013). As for a comparative advantage that foreign trade enterprises seem to get, it is possible that this result is, for example, related to product differentiation. The binary variable that controls for the gender of the business owner (GENDER) is negative but not significant and therefore does not permit to conclude whether businesses run by women are significantly less efficient.
The results also show that firm characteristics such as age (AGE), type (TYPE), membership to a business group (MEMBER), high rate of unionization of employees (UNION) and computerized management (INTERNET) are positively correlated with trade margins. In particular, companies doing wholesaling activities (whether partly or exclusively) make margins that are on average 2.3 times higher than the margins of the retail-only companies, all else being equal. It should also be noted that the binary variable representing the unionized workforce UNION has a significant positive effect on margins. This result is consistent with the descriptive statistics of King, Jacobson, and Seltzer (2002) who reported that the amount of sales per worker and gross margins are higher in stores with unionized workers, and moreover these stores offer also relatively higher wages. Farber and Saks (1980) emphasize that unionization generally increases the mean and decreases the variance of the wage distribution within firms. It therefore benefits workers who are at the bottom of the wage scale. An interpretation of the positive sign of this coefficient would then be that unionization has a positive effect on wages, which in turn have a positive impact on the overall productivity of trade firms, as measured by gross margins.
Of the two variables describing the group membership (MEMBER) and group size (GSIZE), the first coefficient is positive and significant at 10%. This suggests that consortium brings productivity gains associated with, for instance, economies of scale in terms of supply, advertising, and concentration of certain managerial functions, etc. However, the gains from group membership are quite limited. Moreover, the insignificance of group
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size does not allow to inferring about the importance of the size of the consortium on the related trade margins.
Business environment, as shown by the estimated coefficients of the binary factors reflecting the views of business owners, significantly influence the performance of trade companies. The only binary variable whose coefficient is not significant is the SAFETY variable measuring the effect of crime and political instability on the gross margins of traders. This result is not surprising, given the fact that Cameroon is a country with a relatively stable political and social environment (see, e.g., AEO 2007). The results show that the lack of access to credit and land (ACCESS), administrative delays and
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poor regulation (REGULATION), corruption and shortcomings of the judicial system (CORRUPT), lack of infrastructure (INFRAST) and incompetence of labor (WORKFR) negatively affect the gross margins of trade businesses, at the 10% statistical threshold. The sensitivity of the gross margin to these factors is not necessarily uniform throughout the factors. We note for example that the gross margins are more elastic to corruption than infrastructure, and more to the quality of the workforce than to access to credit.
It is important to note that although the competition of the informal sector (COMPET) is perceived by owners of formal enterprises as an obstacle to their operation, our estimates show, perhaps surprisingly, that this perception is associated with a rather positive gross margins. Indeed, companies that perceive the informal sector as a major obstacle for their activity realize on average 1.03 times more gross margins than other companies, all else being equal. Competition from informal trade businesses seems to have a beneficial effect on the performance of their formal sector counterparts. This could be explained by the fact that competition has incentive effects on effort productivity, as argued by the theoretical results of Etro and Cella (2012) and the empirical findings of Ennasri and Willinger (2011). Finally, the adequacy of the empirical model is assessed using the Wald test statistic for the overall significance and the Lavergne and Nguimkeu (2011) statistic (denoted LN) for the specification test. For the latter, we use the bootstrap version of the test, which is convenient for small and moderate samples. Both statistics confirm that the model is not at odds with the data (the value of the Wald statistic is 2350.8 and the p-values of the LN test is 0.091, thus failing to reject the model at 5%).
4 Implications and Recommendations The above analysis suggests that there are several dimensions in which the business environment of trade firms can be improved. Our aim here is to examine the implications in terms of payoff loss and propose some recommendations that could improve the business environment and the functioning of trade based on the facts and findings above. We prioritize those that according to our results appear to be currently the most salient. The first two recommendations are oriented to the public policy makers. The last three recommendations concern both the state and actors of the private sector. (i) Improving infrastructure and increasing the supply of clean water and energy Roads and communication, transportation and electric power are key component for the well functioning of the trade sector in Cameroon.
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Improving the infrastructure does not only improve the circulation of people (buyers and sellers) and goods within the country but also allow to fully exploiting the opportunities and trade-related capacities. Our estimates show that the lack or inadequacy of infrastructure creates an average shortfall of about 3.2% in annual gross margins of commercial firms, that is roughly 4.94 millions CFA, all else equal.
(ii) Reducing regulatory burden and extreme taxation This reform includes simplifying procedures required to clear export or imports at the customs, and reducing administrative procedures required to open a formal commercial enterprise. The latter is one of the objectives aimed at encouraging entrepreneurship in the formal trade sector. While trade is the most common economic activity in Cameroon, only an extremely small fraction of this activity is formal. The rate of informality in trade is relatively higher than in all other sectors. The government should adopt a policy to facilitate the licensing process for the creation of formal commercial firms and more importantly provide conditions that allow a smooth transition from informal trade activity to formality. (iii) Fighting against corruption and illicit trade.
Clearly, this reform would yield the biggest payoff in terms of gross margins gains. This recommendation is in line with the general framework of the fight against corruption which is the impediment most mentioned by entrepreneurs after taxation (see Figure 4). Illicit trade, which involves fraud, smuggling and the presence of counterfeit products in the market, creates inefficiencies, distortions and unfair competition. It is the source of customs and tax loss for the state, loss of market share for legal firms, and loss of jobs for workers. Our estimates show that reducing corruption would improve the average gross margins of the otherwise exposed traders by 7.6%. This reform can be implemented starting by frequent awareness campaigns, direct police interventions, and the media. But, more importantly by instilling a culture of integrity and citizenship.
(iv) Revising credit access conditions for retailers Descriptive statistics show that credit access conditions in Cameroon are relatively stronger compared to other countries of sub-Saharan Africa and the rest of the world. Our estimates show that the lack of access to credit represents an average shortfall of 4.3% in annual average gross margin in commercial enterprises, representing about 6.27 millions CFA in a firm with average characteristics. The conditions for granting credit to businesses should therefore be revised and improved. Two pillars could be mobilized for this purpose, i.e. the banks and the microfinance institutions. The role of the
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central bank, through the management of interest rate could allow commercial banks to provide economic operators with financial resources at minimum cost. This recommendation is also featured in the executive summary of the 2009 general enterprise census (INS 2009).
(v) Enhancing human capital Our results show that education and training have a significant impact on the productivity of trade firms. On the other hand, more than 5% of trade sector entrepreneurs complain about the lack of competence of the workforce as a major obstacle to the well functioning of their business. Our estimates also confirm that firms suffering from workforce incompetence annually lose on average 6.4% in gross margins (that is 9.72 millions CFA) compared to their counterparts who do not suffer from this impediment. Given the critical role of business training on firm performance (see, e.g. McKenzie and Woodruff 2012), trade firms should hire more qualified workers and frequently organize seminars and training workshops for their employees. This would, for example, enhance their knowledge base on key topics such as accounting, taxation, inventory management, procurement, the use of ICT, the use of statistics, the use of research results, the merger and acquisition of assets, customer service, business and family, the ethics of business, etc.
5 Conclusion
With a representation of about 52% of all companies, the retail trade business is one of the most prominent activities in Cameroon and could be a major asset for the emergence of the country, if properly harnessed. This study provides an overview of the retail trade activity in Cameroon and presents the main obstacles to its well functioning. A structural econometric analysis of the performance of retail firms using data from the 2009 Enterprise Surveys is also presented. The study reveals that several factors obstruct the well functioning of domestic trade in Cameroon. The major barriers identified are illicit trade, lack of access to credit, infrastructure, regulatory burden, and lack of competence of the workforce. Their impacts on trade activity have important consequences on firm performance in terms of gross margins shortfalls. In fact, apart from the political instability that has a rather negligible effect on the performance of the firms (since Cameroon is in fact a relatively politically stable country), all other identified factors related to business environment have important repercussions on the gross margins of firms. Our results show that retail companies are making significant monetary shortfalls due to poor business environment in Cameroon. We therefore use our results to make some recommendations that could improve the business environment, strengthen the capacity of economic operators in the trade
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sector and contribute to make Cameroon a more competitive country in terms of domestic trade. The framework also allows to testing economies of scales in the retail industry, as well as evaluating the effects of market characteristics and enterprise structure on firm productivity. Despite the new trend towards large selling areas like supermarkets, we found that there are constant returns to scale in the retail trade business in the Cameroon formal sector. Business orientation (wholesale or retail-only), group membership and use of information and communication technologies are important productivity drivers. Unionization of the workforce is also associated with higher levels of annual gross margin though the gains are quite limited, compared to other factors. Although it is usually argued that the informal sector takes its toll on government tax revenues, our results suggest that competition imposed by this sector to formal trade firms stimulates the efforts of the latter, thereby improving their performance.
6 References
AEO (2007), African Economic Outlook, African Development Bank. Baily, M.N. and R.M. Solow (2001), International Productivity Comparisons Built from the Firm Level, Journal of Economic Perspectives 15(3), 151–172. Balassa, B. (1978), Exports and economic growth: further evidence, Journal of Development Economics, 5, 181-89 . Bastos, F., Nasir, J. (2004), Productivity and the investment climate: What matters most? Policy Research Working Paper No. 3335. Washington, DC: World Bank.
Berg, A., Krueger, A. (2003), Trade, Growth and Poverty : A selective survey, IMF working paper, wp/03/30.
Dollar, D., Hallward-Driemeier, M., Mengistae, T. (2005), Investment climate and firm performance in developing economies, Economic Development and Cultural Change, 54, 1-31 Efron, B., Tibshirani, R. (1986), Bootstrap methods for standard errors, confidence intervals and other measures of statistical accuracy, Statistical Science, 1(1), 54-75
Eifert, B., Gelb, A., and Ramachandran, V. (2007), The Cost of Doing Business in Africa : Evidence from Enterprise Survey Data, World Development, 36 (9), 1531-1546.
21
Eifert, B., Gelb, A., Ramachandran, V. (2005), Business environment and comparative advantage in Africa: Evidence from the investment climate data, Working Paper No. 56. Washington, DC: Center for Global Development Ennasri, A., Willinger M. (2011), Managerial incentives under competitive pressure: Experimental investigation, Working Paper, Laboratoire Montpelliérain d’Economie Théorique et Appliquée, n°2011-12.
Escribano, A., Guasch, L. (2005), Assessing the impact of the investment climate on productivity using firm-level data: Methodology and the cases of Guatemala, Honduras and Nicaragua, Policy Research Working Paper No. 3621. Washington, DC: World Bank.
Etro, F., Cella, M. (2012), Equilibrium Principal-Agent Contracts: Competition and R&D Incentives, Working Paper University of Venice.
Farber, H.S. and D.H. Saks 1980, Why Workers Want Unions: The role of Relative Wages and Job Characteristics, Journal of Political Economy, 88(2) 349-369. Hallward-Driemeier, M., Wallsten, S. and Xu, L.C. 2006, Ownership, investment climate and firm performance Evidence from Chinese firms, Economics of Transition, 14(4), 629 – 647.
Harvey, A.C. (1976), Estimating Regression Models with Multiplicative Heteroskedasticity, Econometrica 44(3),461-465.
INS (2009), Rapport principal du Recensement General des Entreprises, Institut National de la Statistique, Cameroun.
Kinda, T., Plane, P., Véganzonès-Varoudakis, M-A. (2009), Firms’ Productive Performance and the Investment Climate in Developing Economies: An Application to MENA Manufacturing, The World Bank Policy Research Working Paper No 4869.
King, R.P., Park, T. (2004), Modeling Productivity in Supermarket Operations, Journal of Food Distribution Research, 35 (2), 42-55.
King, R. P., E.M. Jacobson, J.M. Seltzer (2002), The 2002 Supermarket Panel: Annual Report, The Food Industry Center, Department of Applied Economics, University of Minnesota, St, Paul, MN. Knack, Steven and Philip Keefer (1995), Institutions and Economic Performance: Cross-Country Tests Using Alternative Measures, Economics and Politics, 7, 207-227.
Lavergne, P., Nguimkeu, P. (2011), A Hausman Specification Test of Conditional Moment Restrictions, Working Paper, Georgia State University.
22
Limao, N., Venables, A. (2001), Infrastructure, geographical disadvantage, transport costs and trade, The World Bank Economic Review, 15(3), 451–479. McKenzie, D. and Woodruff, C., 2012, What Are We Learning from Business Training and Entrepreneurship Evaluations around the Developing World?, IZA Discussion Papers 6895, Institute for the Study of Labor (IZA).
MINCOMM 2010, Document de Stratégie du Sous-secteur Commerce au Cameroun, Ministère du Commerce, Cameroun.
Nguetse, P. (2009), Estimating Return to Education in the Cameroun Informal Sector, International Institute of Statistics.
Nguimkeu, P. (2013), A structural Econometric Analysis of the Informal Sector Heterogeneity, Working Paper, Georgia State University.
Park, T.A., Sauer, J. (2013), Evaluating food retailers using dual elasticities of substitution, Journal of Productivity Analysis 39(2), 111-122.
Paulson, A., R. Townsend, A. Karaivanov (2006), Distinguishing Limited Commitment from Moral Hazard in a Model of Entrepreneurship, Journal of Political Economy, 144(1), 100-44. Taiwo, O., Moyo, N. (2011), Eliminating Barriers to Internal Commerce to Facilitate Intraregional Trade, Working Paper, Brookings Africa Growth Initiative.
