Innovation on Economic Growth, FDI, and Self-Employment: History
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Contributor:
Juan Dempere
,
Muhammad Qamar
,
Hesham Allam
,
Sabir Malik

Innovation positively influences GDP, domestic institutional framework, local infrastructure, local knowledge and technology, and creative outputs. In contrast, innovation negatively correlates with domestic self-employment, often associated with necessity-driven entrepreneurship. Gross domestic product (GDP) per capita measures a country’s economic output, self-employment assesses entrepreneurial activity, and foreign direct investment (FDI) indicates confidence in a country’s economic prospects and innovation trends. 

  • innovation
  • FDI
  • entrepreneurship
  • Global Innovation Index
  • Self-Employment
  • necessity-driven entrepreneurship
  • Foreign Direct Investment

1. Introduction

The importance of innovation as a primary driver of economic progress and development has been widely recognized by policymakers. Most national governments worldwide consider innovation performance critical to competitiveness and national progress. According to the United Nations’ 2030 Agenda for Sustainable Development, private business investment and innovation are the primary drivers of productivity, holistic economic growth, and job creation. Additionally, the United Nations Conference on Trade and Development emphasizes that new strategies for innovation are emerging worldwide, and policymakers support such approaches to expand innovation’s benefits for most people. The UNCTAD suggests that governments should promote the scaling up and dissemination of successful innovations with civil society’s active participation, particularly in the private sector, to make innovative outcomes available to marginalized and vulnerable communities (Sirimanne et al. 2018; UNCTAD 2021; United Nations 2022).
The COVID-19 crisis has posed a significant challenge to national innovation systems worldwide. The Organization for Economic Cooperation and Development (OECD) warns that the pandemic’s impact on the normal functioning of national innovation systems can endanger critical domestic production and innovation capabilities, exacerbating the gaps between large and small businesses and geographical locations. The International Monetary Fund has cautioned about the potential technological decoupling between China and the United States resulting from rising political, economic, and military tensions and its damaging impact on innovation capacity and economic growth worldwide (OECD 2020; IMF 2021).
The central hypothesis of this research project is that countries with superior innovation should exhibit high-caliber economic performance. The GII and its constituent factors measured innovation in this study. This index measures countries’ capabilities for and success in innovation worldwide. The research sheds light on how innovation directly affects critical national macroeconomic variables. Specifically, the article analyzes the impact of innovation on GDP per capita, self-employment, and FDI.

2. Innovation and Economic Growth

The academic literature studying the relationship between innovation and economic growth is extensive. Some articles have focused on the positive relationships between economic and innovation-related dimensions at the firm level, such as between innovation and firm productivity and exports (Cassiman et al. 2010) and between research and development (R&D) and productivity (Tsai and Wang 2004; Zhang et al. 2012). Other articles have focused on the positive relationship between economic growth and innovation at the country level (Castellacci and Natera 2016).
However, not all previous studies have found a positive and significant relationship between innovation and economic growth. For example, Afzal and Gauhar (2020) studied the relationship between financial innovation and economic growth among 164 countries from 1990 to 2017 and found that these variables are negatively and significantly associated. Likewise, Mohamed et al. (2021) found a significant, negative relationship between innovation and long-term Egyptian economic growth. In the same way, Freel and Robson (2004) studied the impacts of business innovation activities and company growth performance in Scotland and Northern England. They found a short-term, negative relationship between product innovation and sales growth or productivity. Correspondingly, Coad et al. (2021) also suggested innovation’s adverse economic impact through excessive patent protection and monopoly powers, harming economic progress and consumer welfare by boosting social inequality.
Similarly, Benavente (2006) found a lack of significant short-run relationship between Chilean companies’ productivity and innovative results or R&D expenditures. Equally, Carvalho and Avellar (2017) found an insignificant relationship between innovation and the productive performance of Brazilian companies. Likewise, Correa (2012) studied the relationship between competition and innovation among US firms and found mixed results: a positive relationship from 1973 to 1982 but no relationship from 1983 to 1994. Correspondingly, Suzuki (2020) proposed a model in which competition and innovation can be either inverted-U-shaped or negatively related. He also showed that strong intellectual property protection does not necessarily improve national innovation. In the same way, Ma et al. (2022) validated the vital role of scientific and technical activities in attaining sustainable economic growth and emphasized the need for nations to synergize their efforts to promote and enhance their scientific potential, incorporate scientific progress into innovative activities, and raise the quality of life of their citizens.
All the previous articles with contradicting results justified the scientific legitimacy of analyzing the relationship between innovation and economic growth again, using a novel global sample of 120 countries with data from 2013 to 2019. Additionally, no previous articles employed generalized linear models and panel-corrected standard error models with reliable results, supporting this study’s original contribution.

3. Innovation and FDI

Many previous academic articles have found a significant relationship between FDI and innovation. Indeed, Khalatur et al. (2019) studied 39 European countries and found that FDI net inflows and domestic loans directly influence the national GII. Similarly, Yang et al. (2020) found that outward FDI positively affects green innovation for emerging markets and developed economies. Equally, Smith and Thomas (2017) verified a significantly positive relationship between FDI and innovation in Russia. Likewise, Ascani et al. (2020) studied the relationship between FDI and innovation in Italian provinces and found a positive relationship in some specific FDI categories but a negative relationship in other FDI sectors. Correspondingly, Girma et al. (2009) found a positive association between inward FDI at the firm level and innovative activity but a negative association with inward FDI at the sector level. In the same way, Tang and Beer (2021) found that regional technical supply and intellectual property flexibility allow regions to retain FDI. Similarly, Huan and Qamruzzaman (2022) found a positive and statistically significant relationship between innovation, grouped into technological, financial, and environmental categories, and FDI inflows, suggesting that fostering innovation can boost FDI inflows both in the short and long terms.
Additional examples include Wong et al. (2020), who found that natural resources, industrialization level, and regional innovation have significant impacts on the FDI inflows of Western China. Similarly, Jungmittag and Welfens (2020) found that FDI and its corresponding induced and related innovation dynamics positively impact Germany and the EU. Likewise, Huang and Zhang (2020) found that inward and outward FDI significantly positively affected firms’ innovation activities in the Chinese province of Shandong from 2002 to 2007. Equally, Olabisi (2017) found that Chinese companies receiving FDI tend to engage in product innovation activities. In the same way, Li et al. (2018) found that differences in FDI inflows determine local variations in Chinese innovation efficiency. Correspondingly, Nyeadi et al. (2020) found that FDI positively impacts firm innovation in Nigeria but has no impact in South Africa.
Similarly, Smith and Thomas (2015) found that FDI significantly positively impacts innovation outcomes in Russia from 1997 to 2010. Additionally, Ali (2017) found that FDI has a negative impact on related variety in export diversification, while it has no significant relationship with overall variety and unrelated variety, which could have implications for innovation in related industries. Equally, Ye and Zhao (2023) examined the impact of China’s outward FDI and found that it promotes regional capabilities of sustained innovation and is mediated by regional human capital accumulation. In the same way, Zeng et al. (2021) found that FDI stimulates technological innovation with technology trades.
All the previous articles confirmed the scientific correctness of analyzing the relationship between innovation and FDI again, using an original sample and time framework and a distinct methodology.

4. Innovation and Entrepreneurship

Numerous prior academic articles have found a significant relationship between innovation and different types of entrepreneurship. Wong et al. (2005) studied the difference between technology-based innovation and new business creation by analyzing the four types of entrepreneurial activities measured by the Global Entrepreneurship Monitor’s (GEM) Total Entrepreneurial Activity (TEA) rates. They found that only high growth potential TEA significantly influences economic growth. Similarly, Crecente-Romero et al. (2019) studied 19 European countries from 2012 to 2016 using GEM data and found that necessity-driven entrepreneurship prevails during an economic recovery. They also found that innovation determines the surge of opportunity entrepreneurship after the economy recovers. Likewise, Khyareh and Amini (2021) studied 64 countries from 2010 to 2018 using GEM data and found that opportunity-driven entrepreneurship is positively related to the innovation-driven economies’ growth and that necessity-driven entrepreneurship is negatively related to the factor- and efficiency-driven nations’ economic growth.
In the same way, Valliere and Peterson (2009) found that necessity-driven entrepreneurship in most emerging countries only provides personal employment, which does not contribute significantly to economic growth. Similarly, Venáncio and Pinto (2020) analyzed whether the entrepreneurial activity of 67 countries contributes to achieving sustainable development goals (SDGs) and found that necessity and non-innovative entrepreneurship are responsible for the lack of entrepreneurial contributions to SDGs. Equally, Edoho (2016) concluded that opportunity entrepreneurship in Nigeria is superior at promoting economic growth, creating jobs, and alleviating poverty. He suggested that entrepreneurship policy should considerably reduce the Nigerian informal sector, while aggressively promoting the formal sector, enhancing innovations, nurturing economic growth, and generating jobs.
Likewise, Block and Sandner (2007) found that necessity-driven entrepreneurs remain in self-employment for less time than opportunity-driven entrepreneurs. Additionally, Venáncio and Pinto (2020) explored the relationship between entrepreneurship and SDGs in 67 countries and evaluated whether FDI strengthens or reduces these relationships. The authors found that entrepreneurship contributes negatively to achieving SDGs, particularly in the people, prosperity, and partnership dimensions, with necessity and non-innovative entrepreneurship having the most significant adverse effects and FDI helping to diminish such harmful effects. Correspondingly, Dempere and Pauceanu (2022) suggested that necessity-driven entrepreneurship can drive high self-employment rates in low-income countries.
None of the articles summarized above provided an inclusive view of the global relationships among innovation, economic growth, FDI, and self-employment. The current article is the most inclusive analysis regarding time and geographical locations, with a sample of 120 countries and data from 2013 to 2019. The limited existing analysis of this topic may explain some of the mixed and contradicting results referenced above. Additionally, no previous articles have provided robust results from different methodologies yielding consistent outcomes. This study is the first to apply generalized linear and panel-corrected standard error models with reliable results. These facts allow us to derive meaningful inferences from the results and fill the gap arising from the previous studies’ small samples, limited methodologies, and use of short periods.

This entry is adapted from the peer-reviewed paper 10.3390/economies11070182

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