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Does research and development expenditure impact innovation? theory, policy and practice insights from the Greek experience

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Abstract

This study empirically investigates the causal relationship between research and development (R&D) expenditure and innovation in Greece, during the period 1981–2009. It uses time series analysis, the theoretical background of the endogenous knowledge-based growth theories and the annual number of patent applications to the European Patent Organization as proxy of innovation activity. The Johansen method is applied to examine the possibility of co-integration. The results confirm the presence of a long-run relationship between R&D expenditure and innovation. The total and private R&D expenditure appear to have a positive effect on total and business innovation. In addition, the public R&D expenditure has a positive influence on business and total innovation, which indicates the existence of significant externalities of public sector research. The long-run elasticity of innovation with respect to R&D expenditure is estimated to be, on average, 1.9. Implications for public policies and related practices are formulated.

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Notes

  1. Ministry of Development, General Secretariat for Research and Technology, Research & Development in Greece.

  2. For the years before 1990, missing points have been completed on the basis of the data provided in the appendix of the paper of Coe and Helpman (1995) for the R&D expenditure in Greece (1995). As they presented information only for the business R&D, it was assumed that the total R&D expenditure followed a similar trend with that of the business sector in order to complete the missing values. For the period after 1990, the missing points were completed with linear interpolation.

  3. The stationarity of the time series is tested with the Augmented Dickey–Fuller (ADF), Dickey–Fuller GLS (DF-GLS) (Dickey and Fuller 1979) and Phillips–Perron (Phillips and Perron 1988) tests. The tests are carried out in the level and in the first difference for each variable. Cointegration tests are based on the methodology developed by Johansen (1991, 1995). Two alternative tests are used, namely the Trace test and the Maximum Eigenvalue test. The selected cointegration model has linear trend in the data, but no trend in the cointegrating equation. The selection of the appropriate number of lags is based on the minimization of the Schwarz and Akaike information criteria. Error correction models are used for the examination of the short-term relationship of cointegrated variables. Granger-causality tests (Granger 1969, 1988) are performed on the basis of the error correction models.

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Authors and Affiliations

  1. Bank of Greece, 21 E. Venizelos Avenue, 102 50, Athens, Greece

    Ioannis Voutsinas

  2. School of Environment, Geography and Applied Economics, Harokopio University, El. Venizelou 70, Kalithea, 176 71, Athens, Greece

    Constantinos Tsamadias

  3. School of Business, George Washington University, Washington, DC, 20052, USA

    Elias Carayannis

  4. School of Business Administration, Athens University of Economics and Business, Derigni 12, 104 34, Athens, Greece

    Christos Staikouras

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  1. Ioannis Voutsinas
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  2. Constantinos Tsamadias
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  3. Elias Carayannis
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  4. Christos Staikouras
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Correspondence to Elias Carayannis.

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Voutsinas, I., Tsamadias, C., Carayannis, E. et al. Does research and development expenditure impact innovation? theory, policy and practice insights from the Greek experience. J Technol Transf 43, 159–171 (2018). https://doi.org/10.1007/s10961-015-9454-3

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