What are the studies measuring?

It is important to have a clear understanding of what the R&D return studies are measuring. This section provides a descriptive summary, while a more mathematical treatment can be found in the annex. The two key parameters measured are (a) the rate of return to R&D, and (b) the elasticity of output/value-added with respect to the knowledge R&D stock.[13] Empirical studies broadly estimate one of these two parameters, defined mathematically as:

Empirical studies attempt to measure the relationship between R&D expenditure and value-added, measured as either a rate of return or an elasticity.

The rate of return is the ratio of the change in value-added (“what you get out”) to the flow of R&D (“what you put in”). This parameter can therefore be thought of intuitively as a rate of return. The elasticity of output with respect to the knowledge R&D stock gives a measure of the responsiveness of value-added to increases in the stock.

For those studies estimating the rate of return, the “social rate of return” is generally the measured “total” return of increases in productivity at an industry/national/international level for a given increase in aggregate R&D. The “private rate of return” is based on measured increases in productivity at the firm level for a given increase in firm R&D. As alluded to earlier, the important point from a policy perspective is the difference between estimates of the private and social returns. While this gap of itself does not tell us how much R&D should be performed, the fact that the gap as measured in many empirical studies is relatively large suggests that we may be some way below the social optimum.

The majority of studies estimating elasticity show a strong link between the knowledge R&D stock and output, with elasticities of around 0.05–0.10. Given the knowledge R&D stock to output ratio, these elasticities can be converted to a rate of return. Whether it is a social or private rate of return depends on whether output and knowledge stock has been measured at the firm level or the economy-wide level.

Relevance of the empirical literature to New Zealand

An obvious question is to what extent the literature on returns to R&D is relevant to New Zealand. There have been very few studies on the returns to R&D in New Zealand, and the majority of the available studies have been carried out in the USA and some European countries, which are very different economies to New Zealand in some respects. The available New Zealand studies include Johnson, Razzak, and Stillman’s (2005), who found some evidence of positive spillovers to the rest of the economy from industry R&D, and Scobie & Eveleens (1987), who found high returns to R&D (around 30%) in the agricultural sector[14]. Work is currently underway within Treasury that should provide some more up-to-date findings for the agricultural sector.

Relevant evidence available from cross-country studies gives mixed guidance on whether returns to R&D are likely to be higher or lower in New Zealand. On one hand, Englander and Gurney (1994), in an OECD study of productivity determinants, conclude that the correlation between R&D and productivity growth is weaker in small countries. They interpret this as consistent with the view that large countries benefit from their own R&D, while small countries benefit largely from R&D done elsewhere. This could be because small countries lack the wider capacity to capitalise on domestic R&D – either production capacity, or size of market, or access to other markets.

On the other hand, Griffith, Redding and Van Reenen (2004) conclude that returns to R&D are likely to be larger in countries that are further away from the technology frontier.[15] The intuition is that in non-frontier countries, there is the potential for innovation to generate productivity growth from both “genuine” innovation (ie, knowledge creation) and knowledge transfer (absorption), whereas countries at the frontier can only raise productivity through knowledge creation. New Zealand’s productivity is at the lower end of the OECD range, suggesting that this result is likely to be relevant for New Zealand. However, relative productivity may vary between sectors, and some New Zealand sectors (eg, agriculture) are likely to be at or close to the frontier. In addition, New Zealand’s low productivity could be partly due to other factors (eg, a lack of economies of scale) rather than a lower level of technology.

Taken together, these findings suggest that New Zealand’s small size may act to reduce returns to R&D, while our distance from the technology frontier may increase them. The combined impact of these two factors on returns to R&D is unclear, as is the effect on the gap between private and social rates of return[16].