Abstract
This paper follows the dual‐cost function methodology and develops a theoretical specification that assesses the contribution of public R&D capital to the productivity growth. The empirical application focuses on the Greek food and beverages industry. For this purpose it employs a micro‐aggregated annual data set over the period 1976–2002. The regression analysis shows that publicly‐funded R&D capital is a productive input as 8.7% and 7.3% of the total factor productivity growth in the food industry and in the beverages industry respectively is attributed to the publicly‐funded R&D capital. The relationship between publicly‐funded R&D and privately‐purchased inputs is also examined.
Acknowledgements
The author wishes to thank the Editor, Professor Malcolm Sawyer, for his valuable comments on earlier versions of the paper, also the author is thankful to two anonymous referees for their helpful suggestions.
Notes
1. However, note that the performance of the food and beverages industry compares poorly to the average growth performance of the Greek economy, of close to 4% for the same period.
2. Previous studies find that industries that are capital intensive are technologically more advanced compared with labour intensive industries (see Kaskarelis Citation1997). This results to higher productivity growth and enhances their competitiveness.
3. In addition to this data source, whenever was necessary our data set was cross‐checked with time series available from the Monthly Statistical Bulletin of the Bank of Greece, the Ministry of National Economy Net Capital Stocks Publications, and the Centre of Planning and Economic Research (KEΠE).
4. In the Annual Industrial Survey those industries are mentioned as ‘large scale manufacturing’.
5. Strict monotonicity is satisfied since the fitted shares for labour and intermediates inputs are all positive. Strict quasi‐concavity is also satisfied as the matrix of substitution elasticities is negative semi‐definite. Strict quasi‐concavity I is tested with the eigenvalues of the above matrix and its LDL factorisation using TSP 4.4.