Abstract
The paper examines the long-run relationship between innovation and per capita economic growth in the 19 European countries over the period 1989–2014. This study uses six different indicators of innovation: patents-residents, patents-non-residents, research and development expenditure, researchers in research and development activities, high-technology exports, and scientific and technical journal articles to examine this long-run relationship with per capita economic growth. Using cointegration technique, the study finds evidence of long-run relationship between innovation and per capita economic growth in most of the cases, typically with reference to the use of a particular innovation indicator. Using Granger causality test, the study finds the presence of both unidirectional and bidirectional causality between innovation and per capita economic growth. These results vary from country to country, depending upon the types of innovation indicators that we use in the empirical investigation process. Most importantly, the study finds that all these innovation indicators are considerably linked with per capita economic growth. This particular linkage is either supply-leading or demand-following in some occasions, while it is the occurrence of both in some other occasions. The policy implication of this study is that countries should recognize the differences in innovation and per capita economic growth in order to maintain sustainable development in these countries.
Highlights
Why do some regions grow continuously for many years whereas others stagnate? Why do some regions grow faster than others? The theoretical breakthrough in answering these questions started by Solow (1956) and Romer (1990) has lost its momentum, leaving some important questions unanswered
The results indicate that innovation (INN: PAR, PAN, research and development expenditure (RDE), research and development activities (RRD), high-technology exports (HTE), and scientific and technical journal articles (STJ)) and per capita economic growth (GDP) are non-stationary at the level data but are stationary at the first difference
The findings suggest that both innovation and per capita economic growth are integrated of order one [i.e. I (1)], which unbolts the possibility of cointegration between the two
Summary
Why do some regions grow continuously for many years whereas others stagnate? Why do some regions grow faster than others? The theoretical breakthrough in answering these questions started by Solow (1956) and Romer (1990) has lost its momentum, leaving some important questions unanswered. Innovation is considered as one of the key drivers of the economy (Andergassen et al 2009; Bae and Yoo 2015; Mansfield 1972; Nadiri 1993; Romer 1986; Santacreu 2015; Solow 1956), since the seminal work of Schumpeter (1911). It affects the economy in multiple channels, such as economic growth, global competitiveness, financial systems, quality of life, infrastructure development, employment, trade openness, and spawns high economic growth.. We would like to assess the importance of innovation-economic growth linkage, by investigating whether the level of innovation has contributed to economic growth, or whether the extension of the innovation is a consequence of rapid economic growth
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