2

2. Public Policy and Science, Technology and Innovation (STI)
In the words of Dye (2013) public policy is defined as the actions and inactions of government. These actions and inactions are reactive response to societal challenges created as a result of market failures. It is worth noticing that there is no unifying definition for the concepts science, technology and innovation, but the closest the research community have come is adopting explanation formulated by researchers. Thus Weimer and Vining (1989) are of the view the concept is a representation of the set of actions that governments can take to deal with a range of problems in the intersecting and complementary domains of science, technology and innovation to achieve a clearly defined (national) objective when private incentives provided by free markets systematically perform poorly. STI policies are classified under the following: vertical (sectoral), horizontal and mixed policies. Sectoral policies reflect government-identified national development priorities. Horizontal STI policies are of generic in nature and thus cut across sectors and bridges sectoral dichotomy by dealing with the shortcomings of vertical policies (UNECA, 2016: p.83).
Sundbo (2003) explains innovation as the blend of knowledge that result in products that are new, processes, input and output markets, or organization including technical ones but also organizational and managerial innovations, new sources of supply, new markets, financial innovations, and new combinations (Perlman and Heertje, 1991). Padilla-Perez and Gaudin (2014) advances that innovation is an interactive and slow process, that hinges on communication and the exchange of knowledge. Carayannis et al. (2006) argues that in a knowledge-based economy, innovation through the creation, dissemination and use of knowledge has become a catalyst in the build up to economic growth. Rycroft and Kash (1999) is of the view that innovation policy is a complex process, not a single product, but as a result of a set of programs and policies, including institutions.
Nonetheless, innovation takes different forms and facades. Therefore innovation is not just hi-tech but expression of creative ideas. According to Lepage (2017), innovation involves 5% hi-tech and 95% imaginary thinking. The other aspect of innovation (industrial innovation) includes manufacturing, management, technical design and commercial activities used in the marketing of a new (or improved) product or the first commercial use of a new process or equipment (Freeman 1982). Huang et al. (2007) are of the view that the factors required for industrial innovation are in diverse and may include technical knowledge, manpower, market information, financial resources, research and development (R&D) environments, an international and domestic markets (Rothwell and Zegveld, 1982). Many researchers have proven and made a case that indeed, industrial innovation can increase overall economic development (see Barro, 1990; Mcmillan & Rodrik, 2011; Rothwell & Zegveld, 1982). Finding the right measure of innovation has given rise to intellectual argument. Huang et al. (2007) objected to the assertion of using R&D tax credit as a measure of innovation and pointed out that such macro measures are not effective and pointless, and that policies must be designed to influence particular economic sectors. In a narrow sense, product innovation may differ from the generic concept, as it is basically the introduction of new good or service or the significant improvement of existing product based on its characteristics and intended use (Ayyagari et al. 2012; Barasa et al. 2017). But Salmenkaita and Salo (2002) differed and stressed that there are no straightforward answers to the question of what should constitute an innovation policy.
According to Lundvall et al. (2009), the national system of innovation (NSI) refers to systems that encompass the interactions both within and between organizations, institutions and socio-economic structures, which defines the direction, rate of innovation and technological capability building. National Innovation Policy (NIP) differs from NSI in that , innovation systems are made up of components (e.g. private enterprises, universities, research centers and government among others), and the relationship among them including the role of institutions (Padilla-Perez & Gaudin, 2014). A distinctive feature of NSI is that, the concept does not necessarily suggest a structure designed and built in a formal and conscious manner, but rather includes institutions, organisations and individuals whose interactions determines their overall innovative performance (see Abubarkari et al. 2018: pp.57).
Padilla-Perez and Gaudin (2014) on explicating on governments’ role as far as innovation system is concern identified government involvement in two dimensions. The first dimension focuses on how government generate and disseminate new knowledge through public research centers, universities and enterprises. The second dimension focuses on how government creates and modify institutions that supports science, technology innovation (STI). Government achieves this through an avalanche of policy instruments such as trade policies, public investment, and support for small and medium scale enterprises, training and education and regional development.
STI can be studied and grouped through diverse approaches, but three can be inferred from the literature. First, some researchers (Lundvall ; Borrás, 2005) are of the view that STI policies have a dual nature (policy instruments to promote specific areas – science, technology or innovation), but their implementation and design should follow a systematic strategy. The second approach proposed by Elder and Georghiou (2007), distinguishes between supply and demand policies that comprise of finance and services support (e.g. tax incentives, support for public research etc.). The third approach distinguishes between linear and non-linear STI policies. Cimoli et al. (2005) explains linear policies as the ones that are either supply-push or demand-pull oriented characterized by a strong governmental role through active policies, by signaling out innovation priorities and providing direct support. The demand-pull on the other hand assign key role to private actors and markets in pushing through and defining main technology and innovation strategies. The non-linear policies are not based on either private technology demand or public technology supply, but rather characterized by adopting a systemic approach to innovation processes (Cimoli et al. 2005). However, these classifications of STI have been criticized. Critics have contended the taxonomy shows inadequacies for studying certain context-based situations and that there is the need for modification. In applying this, Padilla-Perez and Gaudin (2014) classified STI under three key areas: (1) institutional framework and general policies to promote STI (creating public organizations such as secretariats, councils and ministries: developing national, regional and sectoral plans among others), (2) the second group focuses on financing. Public financial support provided through a well-designed R;D tax incentives or incentives indirectly to be used for that purpose, and (3) promoting greater interaction among actors of the system and disseminating technology knowledge.

3. Innovation Policy: Does Institutional Quality Matter?
In the words of de la Mothe (2004), institutions are the channel through which ideas are formed and allowed to flow, from government laboratories, firms (both large and small), universities, and agencies, providing community services, and developing the notion of what he called ‘constructed advantage’ (Bingab et al. 2018; Bingab et al. 2016; Abubarkari et al. 2018).
The quality of institution is significantly related to how innovation is spurred. There are a number of studies that have looked at the link between these two variants. For instance, scholars such as Lundvall and Borrás (2005) and in most recently Lundvall et al. (2009) and Rasiah et al. (2016) have one way or the other contributed to enrich this discourse. Thus, Rasiah et al. (2016) theorizing on this purported link have examined the relationship between host-site institutional support, innovation capabilities and exports with the observation that innovation capabilities correlates with institutional support, and that it also enjoys a positive relationship with export.
At the micro level, specifically the firm level, Barasa et al. (2017) demonstrates that firm-level resources may not necessarily be the same depending on the institutional environment and that regional institutional quality positively moderates the effects of the firm-level resources. Moreover a properly designed institution can inspire productive behaviors, although institutions that are frail and dysfunctional may often lead to unproductive behaviors (Greif 2006; Dollar ; Kraay 2003). Costs of transaction and uncertainty as well as to ease coordination among agents depends on the facilitating role of institutions which could lead to a drastic reduction in these costs component (Alonso ; Garcimartin, 2013). Institutional quality comprises of government’s capacity to effectively formulate and implement sound policies; the process by which a government is selected, monitored and replaced and the economic and social interactions between citizens and the state including how they are governed (Kaufmann & Mastruzzi, 2013). Thus the institutional setting can affect the tendency of firms to innovate in a variety of ways (North, 1993). This can be appreciated through this anecdote. Thus weak enforcement of regulations and the absence of intellectual property rights may obstruct entrepreneurial tendency (innovation). Countries in Africa have consistently performed poorly as against its counterparts in the Middle East, Southeast Asia, Latin America and the North Africa in upholding the rule of law, regulatory quality, control of corruption and government effectiveness (Alence 2004; Forson 2016b).