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REGULATIVE ENVIRONMENT AND ENTREPRENEURIAL ACTIVITY: INSIGHTS FROM SUB-SAHARAN AFRICA
Introduction The ever expanding prominence of entrepreneurship as a powerful driver of economic activities is undeniable. The entrepreneurship discipline has come a long way since Baumol, Kirzner, and Schumpeter, among others, penned some of the influential articles on the subject matteri. As testament to its importance, entrepreneurship is now represented on a global scale through the Global Entrepreneurship Summit (GES). Starting in 2009, the GES has become one of the most vibrant fora where academics, entrepreneurs, researchers, and policymakers engage in an exchange of ideas, mentoring, and collaboration on various aspects pertinent to entrepreneurship. The sixth annual GES was held on 25-26 July, 2015, in Nairobi where the US President gave the keynote speech outlining the drivers, barriers, and benefits of entrepreneurship. One excerpt of his address, which is pertinent to this Chapter, was his description of entrepreneurship (The White House, Office of the Press Secretary, 2015, para. 4): Entrepreneurship creates new jobs and new businesses, new ways to deliver basic services, new ways of seeing the world -- it’s the spark of prosperity. It helps citizens stand up for their rights and push back against corruption. Entrepreneurship offers a positive alternative to the ideologies of violence and division that can all too often fill the void when young people don’t see a future for themselves.
Worded carefully to align with the Sub-Saharan context, much of the keynote address highlighted not only the economic benefits but the social and geopolitical implications of entrepreneurial activities. In committing another $1 billion USD towards funding projects around
the world, the US President warned business leaders and policymakers to ensure that institutional reforms were in place to encourage entrepreneurs to take that first step. It is this connection between the regulative institutional environment and the capacity of entrepreneurs to ‘take that first step’, which forms the core of this Chapter.
The purpose of this Chapter is to examine the factors underlying entrepreneurial activity in SubSaharan Africa. The theoretical framework used in the Chapter derives from institutional theory. Specifically, the Chapter investigates the influence of the regulative institutional environment on entrepreneurial activity for a group of Sub-Saharan countries belonging to the Southern African Development Community (SADC). The selection of the SADC region as the context of this research is based on two reasons; first, examining the SADC region is relevant for enhancing knowledge in entrepreneurship given that traditionally, and even in recent years, Africa’s emerging markets have remained marginalized in mainstream research. Second, from a practitioner’s perspective, the SADC region is an integrated economic bloc with vast economic potential that remains largely untapped.
This Chapter seeks to contribute to both knowledge and policy development at various levels. From a scholarly level the Chapter investigates whether the relationship between institutional quality and entrepreneurial activities, developed predominantly from industrialized and nonAfrican emerging markets, translates to the African context. This is fundamental for painting a more informative picture on the generalizability of theory to emerging market contexts. For business leaders and policymakers, the Chapter identifies factors that impede or enable entrepreneurial activities and lays the platform from which institutional reforms can emanate.
The Chapter provides various indicators of regulative quality, drawing an empirical relationship between these factors and the level of entrepreneurial activities. The empirical results of this Chapter are positioned to provide definitive answers regarding the forms of institutional reforms the SADC region requires to compete, both regionally and globally. The subsequent section provides an overview of the literature on drivers of entrepreneurship which culminates in the construction of the theoretical framework linking the regulative institutional environment to entrepreneurial activity.
Drivers of Entrepreneurship: An Overview This paraphrased literature review on the drivers of entrepreneurship is not designed to serve as an exhaustive discussion of the various facets of this multidimensional phenomenon; rather, it has been structured to outline some key themes and employ these as a prelude to the theoretical framework. The practice of entrepreneurship is considered to trace back to beginning of time and the study of entrepreneurship goes back almost a century but attempts to create nomenclature on the drivers of entrepreneurial activities are fairly recent. Among some of the papers that have helped guide this substream of entrepreneurship literature are the studies by Gartner (1985), Covin and Slevin (1991), and Low and MacMillan (1988).
Gartner (1985) argued that new venture formation was a multifaceted phenomenon that involved individuals, the organization, process, and the environmentii. A venture could be described in terms of the attributes of its founders, the type of entity it morphed into, the process from which it culminated, and also how the environment shaped or molded it. Gartner discussed individual characteristics as elements of an entrepreneur’s personal and behavioral profiles. The
organization was conceptualized as referring to the type or nature of the firm and how it fit into an entrepreneurial ecosystem. ‘Process’ related mainly to how an entrepreneur set about to discover opportunities, mobilize resources, and create products necessary to exploit those opportunities. Similarly, in drawing a distinction between environmental determinism and strategic choice, Gartner defined the environment as a plethora of non-controllable exogenous elements that influence venture creation.
Covin and Slevin (1991) expanded Gartner’s (1985) theorization and outlined a conceptual model of entrepreneurship comprising external variables, top management values and philosophies, business practices and competitive strategies, organizational structure, and entrepreneurial posture. There are parallels between Covin and Slevin’s external variables and Gartner’s description of the environment. Likewise, organizational structure in Covin and Slevin’s model is conceptually similar to Gartner’s perspective. However, Covin and Slevin sought to develop a deeper approach for encapsulating Gartner’s individual and process variables, which they split into three elements in an effort to distinguish firm-wide competitive strategy from its entrepreneurial posture and also top management values and philosophies.
Another informative study published around the same time was Low and MacMillan’s (1988) conceptual paper on the numerous theoretical perspectives from which entrepreneurship could be studied. In essence, Low and Macmillan proposed a way of organizing the myriad variables according to theory-based themes such as social-cultural, network, finance, economic, and population ecology perspectives. Gartner’s (1985) individual factors align with the ‘trait approach’ to entrepreneurship and the assertion that ‘entrepreneurs are born, not made’
(Brockhaus, 1980, 1982; McClelland, 1961). It is also congruous with the social development model of venture creation wherein Gibb and Ritchie (1982) claim that multitudinous social factors (e.g. class structure, lifestyle, occupation choice and career development, work history, family origin, education) drive venture formation (Cooper & Dunkelberg, 1986; O’Farrell & Pickles, 1989). A myopic focus on theory-based themes driven by individual-level factors is deficient as it fails to address exogenous drivers of new venture formation.
Entrepreneurship and new venture creation comprises a bifurcation of phenomena; nascent exploitable opportunities and enterprising individuals (Venkataraman, 1997). This is supported by Cooper’s (1981) assertion that the strategic drivers of venture formation are the entrepreneur (including their unique background influencing motivations, skills, knowledge and perceptions) and the influence of environmental factors exogenous to the individual that influence the salience of the business environment and formation endeavors. Baumol (1996) has also articulated a relation between the institutional environment and enterprising individuals who are willing to create firms. Milne and Thompson (1982) claim that venture growth is not solely derivative of static personal traits extant at start-up; indeed, individual factors adapt in response to engaging with the dynamic external context within which the new venture operates. An example of this is firm restructuring and redundancy events which act as psychological ‘trigger’ events, ‘pushing’ individuals to form new ventures (Binks & Jennings, 1986; Birley & Westhead, 1994; Storey, 1982).
It must be stressed that no singular factor can articulate the complex drivers contributing toward nascent ventures (Westhead, 1990). Reciprocal interactions may exist between the institutional
environment and individual characteristics; the environment likely influences individual, process, and organization factors, and entrepreneurs likely engage in behaviors that impact the external environment (Shane, Locke, & Collins, 2003).
The specific focus of this Chapter is on the population ecology perspective. This perspective aligns with the external variables/environment in that it suggests the very existence or survival of a species is intertwined with the vagaries of the broader ecosystem (Aldrich, 1990). We adopt this perspective to examine if, and how, entrepreneurial activity is connected to the broader external environment.
Institutional Environment and Entrepreneurial Activities The theoretical framework for this Chapter is constructed around Gartner’s (1985, p. 700) description of the institutional environment as the ‘relatively fixed conditions imposed on a new venture from without’. According to Shane and Kolvereid (1995), the institutional environment dictates the level of resource endowment in the market (munificence), the magnitude of dynamism (volatility), the intensity of competitive rivalry (hostility), and the assortment of issues the venture must face (complexity). As such, Aldrich and Wiedenmayer (1993) contend that the quality of the institutional environment has an effect on entrepreneurial activities.
Scott (1995) pointed out that a way to capture this relationship involves separating the institutional environment into three components; normative, cognitive, and regulative, as shown in Figure 1. Stenholm, Acs and Wuebker (2013) describe the normative dimension in the context
of beliefs, attitudes and norms regarding entrepreneurial activities. According to Spencer and Gomez (2003), the normative perspective takes into account the general cultural values and individual traits that may be linked to entrepreneurial proclivity. The cognitive dimension is associated with the mental frameworks entrepreneurs use to process and interpret information on relevant phenomena (Stenholm, Acs & Wuebker, 2013). Elements of the cognitive dimension include, knowledge, skills, and information entrepreneurs in a particular country possess or have access to (Kiss & Danis, 2008).
The regulative dimension is an amalgamation of formally sanctioned rules, regulations, and procedures that influence entrepreneurial activities (Scott, 1995), and constitutes the primary focus of this Chapter. Not only does the regulative environment facilitate or constrain entrepreneurial activities, it creates institutional embeddedness which induces ventures to pursue strategies that align with such an environment. Likewise, Stenholm et al. (2013) explain that the institutional environment can impact both the level and the type of entrepreneurial activity, in particular the capacity to exploit international opportunities (Kiss & Danis, 2008). This Chapter combines these perspectives and addresses the question of how the restraining or enabling role of the institutional environment may influence the level of entrepreneurial activity (Stenholm et al., 2013).
Building on North’s (1990) work on institutional theory, a compelling line of enquiry arguing that the institutional environment can influence entrepreneurship has emerged (see Aldrich, 1990; Baumol, Litan & Schramm, 2009; Bruton, Ahlstrom & Li, 2010; Gnyawali & Fogel,1994; Hwang & Powell, 2005; Shane & Kolvereid, 1995; Scott, 1995; Stenholm et al., 2013). The
remainder of this discussion is confined to an overview of some of the key factors limiting or expediting entrepreneurial activities. For a detailed discussion of the myriad regulative factors and their impacts on entrepreneurial activities, refer to Bruton et al.’s (2010) review.
The economic/political branch of the regulative dimension of institutional theory forms the basis of the conceptual framework (Baumol et al., 2009; Bruton et al., 2010; Scott, 1995). Entrepreneurs are discouraged from starting new ventures if formal rules and regulations are restrictive or non-existent, a situation which creates voids that are filled by informal regulations (Bruton et al., 2010). Conversely, entrepreneurs are encouraged by transparent regulations which are favorable to entrepreneurial activity (Campbell & Rogers, 2007). Thus the rules, regulations, procedures, documentation, cost, and time which set the parameters for ventures to operate, have an impact on entrepreneurial activity (Estrin, Aidis & Mickiewicz, 2007). The propensity to establish a new venture is heightened if entrepreneurs are confronted with fewer hurdles in the start-up phase, as dictated by the characteristics of the regulative regime, indicating that Government policy can affect the development of an environment to support, or constrain, entrepreneurship (Dana, 1987; Dana, 1990; Young & Welsch, 1990). This need for a conducive regulative environment may be greater in emerging market economies and developing countries (El-Namaki, 1988; Segura, 1988). In line with past studiesiii, this Chapter theorizes that:
H1: The better the quality of the regulative institutional environment the higher the level of entrepreneurial activity
The Sub-Saharan Context Because one of the things that we have come to understand - and this is particularly relevant to Africa - is that in order to create successful entrepreneurs, the government also has a role in creating the transparency, and the rule of law, and the ease of doing business, and the anti-corruption agenda that creates a platform for people to succeed. (The White House, Office of the Press Secretary, 2015, para. 8).
An interesting case in point is Soto’s (2000) observation on how registering a new firm in SubSaharan Africa can take two to three months as opposed to a day or two in countries such as Hong Kong. These disparities may explain differences in relative levels of entrepreneurial activities observed around the world (Spencer & Gomez, 2003). Keefer and Knack (1997) have gone as far as arguing that such discrepancies account for why some developing countries may never emerge, while Soto has used the same premise to illustrate why Western capitalism fails in countless jurisdictions around the world.
Against this backdrop, the Chapter contributes to the body of knowledge on the relationship between the regulative institutional environment and levels of entrepreneurial activity by examining this from an African context. The general underrepresentation of studies focusing on African emerging markets is a reverberating theme in entrepreneurship research. It is the reason Kshetri and Dholakia (2011) have implored researchers to investigate more emerging markets beyond members of Brazil, Russia, India, China, and South Africa (BRICS). Not only do Bruton, Ahlstrom and Obloj (2008) view the underrepresentation of emerging markets as disappointing, they consider the current situation untenable.
African economies have been commended by Ernst and Young (2015), the McKinsey Institute (see Roxburgh et al., 2010), and The Economist (2011) for making considerable strides over the last two decades. Among the highlights of the McKinsey report are, consumer spending of nearly $1 billion USD, 316 million mobile phone users since 2000, a collective GDP of $2.6 trillion USD by 2020, and a labor pool of over 1 billion employees by 2040 (Roxburgh et al., 2010). Despite these advances, major structural and regulative challenges persist. This reported growth comes against the milieu of significant trials including economic and social upheavals, unstable political environments, suppression of personal and economic freedoms, corruption, and unfavorable conditions for investment and entrepreneurship (The Economist, 2011). Given the impetus to investigate emerging markets beyond BRICS, it is appropriate to focus this Chapter on the regulative dynamics of African economies, specifically, the Southern African Development Community (SADC).
SADC was formed in 1992 and comprises Angola, Botswana, Democratic Republic of Congo (DRC), Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia, and Zimbabwe. Its origins trace back to 1980, when members of the then Frontline States created the Southern African Development Coordination Conference (SADCC) following the Lusaka Declaration. The specific mandate of SADC is to foster regional integration, eradicate poverty, promote peace, and enhance economic development (SADC, n.d.)iv. Economic development is very much a headliner on SADC’s agenda given that ten of its 15 members have a per capita GDP of less than $5,000 USD (SADC, 2011), yet the entrepreneurial potential of this economic bloc is self-evident. Global
Entrepreneurship Monitor’s (GEM) work on Sub-Saharan Africa, a region which encompasses all SADC members, illustrates that there are high rates of total early-stage entrepreneurial activity (TEA), yet somewhere along the entrepreneurial pipeline this potential is lost, with only a small proportion of this capacity actually translating to established ventures (Herrington & Kelley, 2013, p. 8). In extending the pipeline metaphor, it is unclear as to whether the entrepreneurial pipeline is clogged or leaking. This Chapter seeks to contribute to SADC’s economic development goal by examining the institutional level factors that hinder or assist entrepreneurial activity.
Finally, although cross-national comparisons can be informative for purposes of isolating country-level differences (Busenitz, Gomez & Spencer, 2000), treating countries within a particular region as a collective is valid and justifiable, especially where such countries share economic, political, and historical ties (Bruton et al., 2008). This study considers the 15 member SADC bloc as a collective and investigates governance-level indicators underpinning the level of entrepreneurial activities. The results of this study are vital for highlighting issues to SADC policymakers, in order to encourage entrepreneurial activity. This is imperative given that entrepreneurial activities, whether domestic or cross-border, are the lifeblood of economic growth (Herrington & Kelley, 2013).
Methods and Measures This Chapter adopts North’s (1990) perspective on how the regulative institutional environment ‘sets the rules of the game’ for participants. As such, the formally sanctioned rules, regulations, and procedures that constrain or enable start-ups are conceptualized as antecedents of the level of
entrepreneurial activities. Among the predictors used in past research are general policies affecting entrepreneurship, macroeconomic factors, and governance indicators (see Campbell & Rogers, 2007; Estrin et al., 2007; Spencer & Gomez, 2003). For this study, we employ the World Bank’s Ease of Doing Business Index (EDBI) as proxy for the nature and types of rules, regulations, and procedures influencing new start-ups. Preference for the EDBI is based on the fact that it is a reliable and standardized governance indicator, and has been adopted in some recent studies including Morris and Aziz (2011) and Stenholm et al. (2013).
The EDBI comprises ten primary categories - starting a business, dealing with construction permits, getting electricity connected, registering property, getting credit, protecting minority investors, paying taxes, trading across borders, enforcing contracts, and resolving insolvency. Further, there are 31 individual indicators associated with these elements. The variables used in this study, and the categories from which they were selected, are listed in Table 1. The foremost primary factors that are relevant to the level of entrepreneurial activity comprise ease of starting a business, dealing with construction permits, registering property, getting electricity connected, obtaining credit information, paying taxes, and enforcing contracts. Protecting investors, trading across borders, and resolving insolvency were not considered for this research as they are applicable mainly in the post start-up phase as opposed to inception. From each of these seven primary categories, we drew specific indicators which were then modelled as antecedents of entrepreneurial activity.
The number of new start-ups was used as an indicator of entrepreneurial activity. Specifically, we adopted the World Bank Group’s Entrepreneurship Survey which tracks the level of entrepreneurial activities using business entry density. The business entry density measures the number of newly formed limited liability firms per 1,000 individuals of working age (i.e. aged between 15 and 64). Overall, the methodology used in this Chapter is consistent with Campbell and Rogers (2007), Estrin et al. (2007), and Stenholm et al. (2013).
Data and Analysis The Chapter focused on the entire period (2004-2015) covered by the EDBI. Over this 12 year period the 15 SADC countries generated 180 possible data points. Angola, Mozambique, Seychelles, Swaziland, Tanzania, and Zimbabwe do not have data on business entry density across the relevant period which eliminated 72 data points from the initial 180. Further, the data on business entry density cover the period 2004 to 2012, which meant the period 2013 to 2015 was omitted from the analysis. This resulted in the elimination of an additional 27 data points from the analysis. Thus, the effective sample size for this study comprised 81 data points covering nine SADC countries over the nine year period (2004-2012). Aside from a few missing cases for DRC, Madagascar and Malawi, data were complete across all independent and dependent variables.
Data analysis was conducted using the linear modelling variant of linear regression, designating the 19 EDBI elements as predictor variables and business entry density as the outcome variable. Choice of this approach was motivated by the need to account for multi-collinearity, missing data, and outliers. The linear model also adopts a stepwise procedure which allows the resultant
model to include only the variables considered ‘important’. This approach was fundamental for improving the overall validity and reliability of the resultsv.
Results The results section is organized as follows: First, we provide some descriptive statistics on the performance of the SADC countries across the selected variables. Second, we provide an overview of model fit for the linear technique chosen focusing on residuals and prediction accuracy. Finally, we identify the most important EDBI variables that predict business entry density while enlightening the reader vis-à-vis the relationship between each of these important variables and business entry density.
Table 2 shows the averages for 2015 across the 19 indicators chosen for this Chapter, together with the statistics for the top and bottom performers for each indicator. To give a more complete picture to the reader, this portion of the results has used all 15 SADC countries instead of the smaller group of nine on which hypothesis testing will be based.
Botswana is the top performer regarding cost of construction, depth of credit information and procedures for enforcing contracts while South Africa excels at cost of starting a business, time requirements for dealing with constructions permits, and number of tax payments per year. Similarly, Mauritius leads the group for the time required to start a business, time required to register property and depth of credit information. However, this group of SADC countries
appears to have regulative institutional environments that dissuade entrepreneurial activities. Averages that draw the readers’ attention include time delays for starting a business (53 days), getting construction permits (244 days), getting electricity connected (145 days), and enforcing contracts (586 days). This extends to the number of procedures for starting a business (9) and dealing with construction permits (13), and the cost of enforcing contracts (39% of claim). The remainder of this results section focuses on how these elements of the regulative institutional environment influence entrepreneurial activity.
The linear model provided in this Chapter appears to carry better than modest power in explaining the predictors of business entry density. Appendix 1 shows residuals associated with the explanatory power of the model. The deviation between expected and observed cumulative probability appears negligible and the residuals plot is virtually identical to the approximation of best fit denoted by the dotted lines. Appendix 2 displays the overall strength of the linear modelling-based regression analysis. As a collective, the predictors improve our understanding of the aspects underlying business entry density to 71.8%. Stated differently, the model explains nearly 72% of the variability in business entry density within the SADC region.
As shown in Figure 2, the most important variables predicting business entry density within the SADC region are starting a business (procedures and time), procedures relating to securing construction permits and enforcing contracts, total tax on profit, strength of legal rights, and depth of credit information. The point estimates for individual importance range from 0.321
(procedures associated with starting a business) to a low of 0.067 (depth of credit information). It is noteworthy that three of these seven variables pertain to procedures with the remainder being a combination of cost, time, and information. To offer additional insights to the reader, we provide Figure 3, which depicts the significance tests and coefficients for each of the predictor variables.
Figure 3 shows that all seven variables designated as important by the linear model are statistically significant at the p
