6.4  The separate effects of public and private R&D funding

In this section we report the results of an attempt to isolate the separate contributions of public and private domestic research using both the PIM and Koyck models. The data for this are set out in Appendix 2.

An OECD report (OECD 2005) found that domestic private R&D and foreign R&D stocks impacted positively on productivity in all of the 16 OECD countries used in their panel estimation. However, domestic public R&D had a positive impact on productivity in only 12 of the 16 OECD countries. Johnson (2000b) looked at the contribution from private and public R&D in 9 industries in New Zealand. He found that private R&D was positively related to changes in TFP in 7 out of the 9 cases, while public R&D was positively related to changes in TFP in 4 out of the 9 cases. In the agricultural sector he found that public R&D was negatively related to changes in TFP. However, in another study by Johnson (2000a), he finds that the return to public R&D in the agricultural sector is positive depending on how the lags on R&D expenditure are dealt with in the estimation. The positive relationship was found when he used Almon distributed lags, while the negative relationship was estimated using the perpetual inventory method to construct a public R&D stock variable.

Tables 9 and 10 summarise our results when we include domestic R&D separately as private and public spending. Once again the dummy variable is significant in both the Koyck and PIM models. The weather variable is again not significant in any of the models and the extension variable continues to be mostly negative and sometimes significant.

In all of the models tested under both approaches, the coefficient for domestic public research is only significant in two specifications (model 5 under the PIM approach and model 7 under the Koyck Transformation are discussed below). The coefficient on domestic private R&D is significant in all 4 specifications of the perpetual inventory stock models, but is never significant in the Koyck models (except for model 8, discussed below). The elasticities with respect to the stock of private domestic R&D (see Table 8) therefore ranges from 0.14 to 0.63, with the implied rate of return ranging from 176% to 771% (assuming a Private R&D to GDP ratio equal to the average over our sample period).

The multicollinearity problem also arises between the public and private R&D expenditure variables, with a correlation coefficient of 0.96.[33] Therefore we may not be picking up the significance of domestic private and public R&D spending due to their high correlation with each other and with other variables in the model (both private and public R&D spending are also highly correlated with human capital). When we remove both human capital and private R&D expenditure from the regression models, domestic public R&D becomes significant in both the Koyck model and the PIM model (see model 5 in Table 9 and model 7 in Table 10). When we remove both human capital and public R&D expenditure from the Koyck regression model, we see a significant coefficient on the private R&D expenditure (see model 8 in Table 10). The corresponding rate of return to domestic public R&D in the Koyck model is 26%, and to domestic private R&D the corresponding rate of return is 32%.

Note: The asterisks indicate the degree of significance of the estimated coefficient; *** = 1%; ** = 5%; * = 10% and an absence of asterisks indicates the coefficient was only significant at more than 10%.

Note: The asterisks indicate the degree of significance of the estimated coefficient; *** = 1%; ** = 5%; * = 10% and an absence of asterisks indicates the coefficient was only significant at more than 10%.