ظرفیت های نوآوری در اقتصادهای پیشرفته: عملکرد نسبی اقتصادهای باز کوچک

This paper offers an empirical examination of the determinants of a nation's ability to produce commercially viable innovations, measured as Patents Granted across a sample of 23 advanced economies. The approach employed is based on estimating National Innovative Capacity that focuses on the long-run ability of economies to produce and/or commercialise innovative technologies, in the spirit of Furman et al. (2002). The time period of our analysis covers 1993 to 2005 and employs panel estimation. Motivated by differences in the rate of innovation between economies with different economic structures we examine the Small Open Economies (SOEs) in our country sample to assess whether there is a significant difference between the determinants of Innovative Capacity in SOEs and the other larger developed economies. We find that advanced SOEs and larger economies do not differ substantially in their determinants of producing innovative technologies and, notwithstanding the limitations of Patents as measures of innovative activity, we conclude that policy choice and variation plays a key role in determining the productivity of R&D, when measured as patenting activity.

Innovative capacity lies at the heart of factors affecting every nation's future competitiveness particularly for advanced modern economies, since under a Solow (1956) type growth framework such economies are likely to have exhausted their ability to generate increased output from further investments in capital. In this paper we assess whether the factors that drive this vital innovation in Small Open Economies (SOEs) are significantly different to that of larger economies. We use Patents Granted by the United States Patents and Trademarks Office (USPTO) as a measure of national innovative output. As with any economic definition of success, innovative success requires elaboration and explanation. Undoubtedly Patents Granted are an imperfect proxy of the innovative capacity of an economy, yet they represent the only directly observable and comparative measure of innovative output over time suitable for the analysis conducted here for the sample of countries considered over the time period selected for consideration. Their suitability and a fuller definition of the measure are discussed in more detail in Section 4.1. Our method employs the National Innovative Capacity framework developed by Furman et al. (2002) which uses (i) a country's infrastructure, (ii) the prevalence of industrial clusters and (iii) the quality of links between the two to examine determinants of innovative capacity. This provides a model of how a country can produce commercially valuable innovation over the long term, drawing together earlier work by Romer (1990), Porter (1990) and Nelson (1993) to inform the three constituent elements. The variation in the ability of countries to produce new-to-world technologies is striking. Some countries consistently outperform others by a large margin. For example, Canada, the US, Finland, Switzerland and Japan produced well over 100 patents per year per million of population in 2008, while most other advanced economies average approximately 60 patents per million and still others such as Spain, Portugal, New Zealand and Italy all may be considered to ‘underperform’ with less than 25 patents per million. Such variation in patenting outcomes is not explained by larger economies performing better or smaller, more nimble economies generating better results. There is, nevertheless, a strong patenting bias in those countries which have a history of patenting such as the US and Switzerland (due to path dependency and the importance of the history of resource commitments). However, other ‘new’ innovative countries’ rates of growth in patents per million have been nothing short of phenomenal: Singapore, for example, has an average annual patent growth rate of 30% between 1981 and 2008, going from just over 1 patent per million in 1981 to 84 in 2008 (Fig. 1). Full-size image (36 K) Fig. 1. Patents Granted per Million Population (2008), Ranked by 2008 GDP ($). Source: IMF WEO, USPTO. Figure options Such performance begs analysis and raises the question for us in this paper as to whether smaller economies are supported or hindered by their relatively low scale, or low critical mass in economic terms, in achieving innovative success. We also examine whether an SOE's innovative capacity is optimised by an emphasis on certain factors or if the same basic mix of factors is found to be effective offering findings of relevance from a policy perspective. The issues considered in this paper focus, firstly, on whether the mix of drivers of Innovative Capacity varies across advanced economies when categorised by their SOE status. Thus, this paper addresses possible heterogeneities that may exist in relation to different economy structures. We examine the extent to which a set of factors drive a nation's Innovative Capacity, as previously found in the literature, and question whether or not the mix of policy choices, in terms of the factors mentioned above, for an SOE are significantly different from other economies. While some limited literature on innovative capacity examines specific SOEs, such as consideration of New Zealand in Marsh (2000), it tends to concentrate on an individual industry rather than adopting a broader international perspective which is the chosen perspective offered here. This question, therefore, addresses a gap in the literature by targeting our assessment on the relative performance of SOEs. We set out the background to the National Innovative Capacity (NIC) approach and underlying model in Section 2, and potentially relevant measures that determine (NIC). In Section 3 possible reasons for the SOE heterogeneity relative to larger economies are considered. In Section 4 the data selected for analysis is described. Empirical results for a number of various specifications are examined in Section 5 with Section 6 providing our conclusions.

This paper examines the drivers of National Innovative Capacity using a new dataset of a shorter time frame but with an increased cross-sectional element relative to other earlier similar studies to permit focus on whether and to what extent, if any, SOEs exhibit drivers of innovative capacity in line with those of larger economies. While a series of more basic models were estimated, the extended National Innovative Capacity models (Eqs. (3.1) and (3.2) in Table 4 and Table 5, respectively) provide most explanatory power, as measured by R2. While many of our findings reinforce those of earlier papers, a number of differences are notable. Our results indicate that the coefficient Aggregate Personnel Employed in R&D was consistently insignificant and reduced in magnitude once the R&D Expenditure variable was included. This contrasts with the findings of Furman et al. (2002) where R&D human capital and R&D personnel were both found to be significant in the production of Patents Granted. A number of explanations are possible. One is the more recent data used in this study. This could mean that there has been a change or structural break in the way Patents Granted have been produced in the more recent time-frame, requiring more sophisticated capital and making the number of researchers relatively less important in generating Patents Granted. A possible support for this argument is that as time goes on, the year fixed-effects decline in the estimates, implying that it becomes increasingly difficult to generate Patents Granted. This gap may well be bridged more easily by more advanced technology as higher end researchers are in short and inelastic supply. Another possibility is that the variable is simply too broadly defined. If it only included researchers and engineers it may again become significant. This is an area that requires further study. The hypothesis that larger economy types benefit from scale effects is supported by the positive relationship between population and Patents Granted for non-SOEs. The negative impact of scale for SOEs, exhibited in terms of Population in Table 4 and in terms of Patent Stock in Table 5, points to inherent barriers to SOEs engaging in growing their innovative capacity as their scale impacts on, for example, their capacity to benefit from knowledge spillovers one which their openness does not counter. Further investigations around the definition of SOE and steps such as using an extended data set to include a broader range of countries can consider the extent to which this finding is repeated across other country samples. Where SOEs in the sample have addressed their scale weaknesses, it was through a mixture of the share of R&D expenditure by private companies and through the share of R&D conducted by Universities. The identification of the mechanisms through which this was achieved and how it was achieved requires further research. It is in relation to these variables that SOEs managed to enhance their innovative capacity, measured here as Patents Granted, over and above and statistically significantly relative to the measured determinants of innovative capacity for all countries in the sample.