The impact of innovation on economic growth among G7 and BRICS countries: A GMM style panel vector autoregressive approach
Introduction
Several important factors support economic growth. According to Bayarcelik and Taşel (2012) among them are the three most important factors namely Capital accumulation, Growth in population, and Technological Progress. At present, new growth theories have emphasized the importance of innovation as a source of economic growth. Some theories and history support the view that innovation is one of the main drivers of economic growth and development in the global economy. The concept of innovation and economic growth has become an attractive field of research for scholars (Pece et al., 2015; Bayarcelik and Taşel, 2012). Economic growth represents a slow and progressive change of the economic system, resulting from exogenous factors of the economic system (Pece et al., 2015; Schumpeter, 1934). It is an increase in economic capacity to create goods and services, comparing one period with another (Broughel and Thierer, 2019). Innovation illustrates the drive for economic growth, progress, and competitiveness for both developed and developing economies (Franco and de Oliveira, 2017). Countries and firms need to enhance indigenous innovation and increase knowledge spillover to decrease their production technology (Long et al., 2019; Zhu et al., 2020). Because of this, innovation has become a central point for maintaining better performance, creating competitive advantage, economic development, and most importantly for achieving economic growth in today's global world (Sesay et al., 2018).
In recent years, innovation has been extraordinary and has contributed to the overall economic growth of the country, especially the BRICS and G7 countries (Stiglingh, 2015). The development of large investments in R&D expenses, trademarks, and patents in BRICS and G7 countries strengthens their innovation capacity (Sesay, et al., 2018; Stiglingh, 2015). The extent to which the BRICS and G7 countries have reallocated to innovation can be reflected in their research allocation trends, as reflected in spending levels for R&D, trademarks, and patents on their GDP per capita (Sesay et al., 2018; Stiglingh, 2015). Also, the majority of research efforts are concentrated in developed and industrial countries specifically in the G7 countries. The G7 countries are recognized as countries with a strong culture of producing knowledge and research because of high traditional growth rates and past developments. In the same vain, Inglesi-Lotz et al. (2015) for BRIC and Inglesi-Lotz and Pouris (2013) for South Africa, among others highlighted the relationship between innovation and economic growth. In this model, they asserted that economic growth is influenced by the level of innovation growth, which is exogenously determined. The creation of BRICS reflects the objective revival of new world actors, developed and developing countries (Sadovnichiy et al., 2016). Most developing countries do not have innovation and strong policies to provide the necessary economic results. However, the BRICS economy has proven itself effective in competing with developed countries such as the G-7 countries. Over the next few years, the growth generated by BRICS through innovation will probably become a more important force in the world economy (World Bank, 2011). Although the BRICS recently described strong economic growth, they continue to experience a significant trend of their economic stability towards innovation. Thus, BRICS has the prospect of forming an economic bloc that influences the current separation of G-7 status (Chang and Caudill, 2005).
Several good empirical studies have shown that there is a positive relationship between innovation and economic growth, and innovation has now become a major component of economic growth worldwide (Sesay et al., 2018; Castano, Méndez, and Galindo, 2016; Dittrich and Duysters, 2007; Schumpeter, 1934). Literature shows the relationship between economic growth, innovation consisting of R&D expenditures, trademarks, and patents making references to developed and developing countries, using macroeconomic and microeconomic data (Sesay et al., 2018; Franco, and de Oliveira, 2017; Rabiei, 2011). There is the acceleration of BRICS economic growth, however, whether the relationship between innovation and economic growth in BRICS is comparable to G-7 countries is still unclear (Stiglingh, 2015). Most of these studies employed mean-based econometric estimators including vector error-correction (VEM) model, pooled ordinary least square (POLS) and fully modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS) estimators. These estimators use averages to predict outcomes but do not permit the relationship to be witnessed over the time frame. In many cases, inconclusive findings may emerge from different periods and mean-based approaches used by these authors. Therefore, this study used a panel vector autoregressive model (PVAR) that accounts for heterogeneity and endogeneity as well as time-invariant non-observed fixed effects. Unlike the mean-based estimators, the PVAR, through its variance decomposition and impulse response function allows the behavior of the variables to be observed over a while. Hence, detail and trend results could be revealed and that will be useful for policy decisions. Again, though, BRICS and G7 countries have been widely studied, there is limited research that compares these two country blocks which creates a gap hence this research. Therefore, comparative studies on the subject through a systematic and analytical research approach will contribute significantly to the current body of knowledge in this field (Mostafa and Mahmood, 2015).
The overall objective of this study is to investigate the impacts of R&D, trademark, and a patent on the economic growth among BRICS and G7 countries. This objective has been separated into two sub-objectives. (1) to examine how the economic growth of BRICS and G7 react to shocks from R&D, trademark, and patent by applying a PVAR approach over the period 2000–2017. (2) to investigate whether the reaction of economic growth to shocks from R&D, trademark, and patent differ between BRICS and G7 countries.
The contribution of this study to literature and knowledge is as follows. First, this study adds to the literature on innovation and growth by giving empirical data on how R&D, trademark, and patent impact economic growth. This research, on the other hand, presents a comparative analysis for the G7 (advanced group) and the BRICS (emerging group) during a given period. This allows for a comparison of the behavior of innovation in terms of growth results in the BRICS and G7 nations. Second, this study implemented the PVAR model in the Generalized Method of Moments (GMM) style to investigate the topic. Unlike other mean-based estimators (OLS, POLS, DOLS, VCM) commonly employed in innovation-growth studies, the PVAR estimator gives both mean-based and trend findings for a better understanding of the issue. For instance, through the variance decomposition and impulse response function of the PVAR estimator, this study revealed that the marginal impact of R&D for G7 and BRICS for the early 2000s. However, the G7′s marginal influence stayed steady from the mid-2000s forward, whereas the BRICS' marginal impact dropped during the same period. This finding suggests that the impact of R&D on G7 economic growth is likely to be stable in the future while that of BRICS is likely to reduce in the future. Unlike mean-based estimators, which may have produced a mean result, the PVAR yields fascinating results and allows the series' behavior to be monitored (Love and Zicchino, 2006).
The rest of the study was in this manner: Section 2 presents the literature review related to the study, Section 3, deals with the methodology. It covers variables and data, a test of normality, econometric modeling, and endogeneity check. Section 4 deals with results and discussions. It presents the results based on the objectives of the study. Finally, Section 5 present the conclusion, potential policy recommendations and limitations, and further research directions.
Section snippets
Literature review
Innovation is essential for sustainable growth and economic development (Gerguri and Ramadani, 2010), as a result, the connection between economic growth and innovation has become a great interest for researchers, this concept is well-debated literature. This concept has its origin in the research realized by (Solow, 1956), who pointed out the existence of a long-term relationship between economic growth and innovation. (Schumpeter, 1912, 1939) makes the distinction between economic growth and
Variables
Our variables of interest are economic growth and innovation. This research proxied economic growth as GDP per capita and innovation as research and development (rd), trademark (tradmk), and patent. This follows the methodologies of Vuckovic (2016), Pece et al. (2015), Sandner (2009), Greenhalgh et al. (2005) that broadly proxied innovation as R&D, patent, and trademark. In addition, this satisfies the theoretical arguments surrounding economic growth (Vuckovic, 2016; Pece et al., 2015).
Unit roots tests
In other to implement the PVAR model, there is the need to establish the stationarity of the variables by performing unit roots tests. Among the proposed panel unit roots test, the authors used Im–Pesaran–Shin (IPS) (2003) and Fisher-type (Maddala and Wu, 1999; Choi, 2001) tests to check for stationarity of the series. These tests are suitable for our dataset for two main reasons. First, unlike the other panel unit roots tests, these tests handle unbalanced datasets. Second, they allow for
Conclusion, possible policy recommendations and limitation, and further research directions
It has been realized that innovation is essential for economic growth and development in this globalized economic (Castano et al., 2016; Schumpeter, 1934). The objective of this study is to examine the impacts of innovation on economic growth among G7 and BRICS countries using the GMM style panel vector autoregressive (panel var) approach over the period 2000-2017. the authors conclude that conditioning on innovation determinants, an increase in the initial values of R&D, trademark, and GDP per
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