Environmental regulations in private and mixed duopolies: Taxes on emissions versus green R&D subsidies

In this article, we compare two kinds of environmental regulations—emissions taxes and green R&D subsidies—in private and mixed-duopoly markets in the presence of R&D spillovers. We show that a green R&D subsidy is better (worse) than an emissions tax when the green R&D is efficient (inefficient), irrespective of R&D spillovers, whereas the existence of a publicly owned firm encourages the government to adopt a subsidy policy. We also show that the optimal policy choice depends on R&D efficiency and spillovers. In particular, when green R&D is inefficient and the spillover rate is low (high), the government should choose an emissions tax and (not) privatize the state-owned firm. When green R&D is efficient, however, an R&D subsidy is better, but a privatization policy is not desirable for society, irrespective of spillovers.     

Learning from R&D outsourcing vs. learning by R&D outsourcing

We analyze how research and development (R&D) outsourcing influences product innovation. We propose a separation between learning from R&D outsourcing, whereby the firm improves its ability to innovate by using outsourced R&D directly in new products, from learning by R&D outsourcing, whereby the firm indirectly uses outsourced R&D by integrating it with internal R&D to create new products. Building on the knowledge-based view, we argue that learning from R&D outsourcing is likely to have an inverse U-shaped relationship with product innovation, because the initial benefits of using outsourced component R&D knowledge to innovate products is eventually outweighed by the hollowing out of the firm's ability to innovate. In contrast, we propose that learning by R&D outsourcing is likely to have a U-shaped relationship with product innovation, because the initial challenges of integrating internal and external R&D are eventually overcome, resulting in more innovations. Finally, we distinguish between domestic and foreign R&D outsourcing and propose a liability of foreignness in R&D outsourcing as it has a lower impact on new products than domestic R&D outsourcing. The empirical analysis shows that outsourced R&D has an inverted U-shaped relationship with the number of new products, while the interaction between outsourced R&D and internal R&D has a U-shaped relationship with the number of new products. It also shows that domestic outsourced R&D has a higher positive impact on the number of new products than foreign outsourced R&D.     

Governance and effects of public R&D subsidies: Evidence from China

This study examines the effects of public research and development (R&D) subsidies and the governance of such subsidies on firm productivity based on the analysis of a firm-level panel dataset between 1998 and 2007 in China. It is found that public R&D subsidies tend to support more productive firms and the productivity of these government-backed firms is improved further after they get the government support. Less attention is paid to the observable or measurable performance measurements in ex-ante project selection, and the ex-post effects are stronger when the governance of the public R&D subsidies becomes more decentralized due to an exogenous policy change. In other words, better decentralization of governance is associated with more pronounced effects of R&D subsidies. Identification concerns are addressed with various approaches to confirm the treatment effect of public R&D subsidies and the governance of such subsidies.     

The relationship between R&D,innovation and productivity in emerging economies: CDM model and alternatives

CDM (Crépon, Duguet and Mairesse, 1988) is a workhorse model in the economics of innovation, which explains productivity in a three-stage procedure driven initially by R&D and leads to patents and then to productivity improvements. Based on the logic of this model, an increasing number of papers applies it to emerging economies but modifies the original model without being explicit about the nature and implications of this modification. We argue in this paper that, in its original form, CDM does not capture stylized facts of the determinants of productivity in emerging economies and that we need alternative models. Accordingly, we are critical of papers that try to maintain the validity of the model but actually change it. For that purpose, we test the original CDM model and its two alternatives: investment and production capability–driven models. Our research is based on a large sample of firms in Central and Eastern Europe, former Soviet republics and Turkey, and we show that the alternative models are much closer to the stylized facts of innovation activities and technology upgrading in these and other emerging economies. Our conclusions have important policy implications, which we discuss.     

Mining external R&D

Open Innovation presses the case for timely and thorough intelligence concerning research and development activities conducted outside one’s organization. To take advantage of this wealth of R&D, one needs to establish a systematic “tech mining” process. We propose a 5-stage framework that extends literature review into research profiling and pattern recognition to answer posed technology management questions. Ultimately one can even discover new knowledge by screening research databases.Once one determines the value in mining external R&D, tough issues remain to be overcome. Technology management has developed a culture that relies more on intuition than on evidence. Changing that culture and implementing effective technical intelligence capabilities is worth the effort. P&G's reported gains in innovation call attention to the huge payoff potential.     

From mind to market: A global,dynamic analysis of R&D

Existing models of R&D are not easily reconciled with four observable aspects of R&D: initial technologies (ideas) need to be developed further, only a minority of initial ideas are successfully brought to the market, production and process innovations take place simultaneously (whereby, initially, there is no production at all), and process innovations are implemented for technologies that are destined to leave the market. We present a detailed bifurcation analysis for a dynamic model of R&D that captures these observations in one, unifying framework. As we provide a global analysis, we do not limit initial technologies to carry marginal costs that are below the choke price. We show that there always exists a critical value of initial marginal cost above which the firm does not initiate any (R&D) activity; the path to the saddle-point steady state is never globally optimal. We also sketch some tentative policy implications of our analysis.     

R&D and aggregate fluctuations

Empirical observations raise interesting questions regarding the sources of the excessive volatility in the R&D sector as well as the nature of the relation between the sector and aggregate fluctuations. Using US data for the period 1959–2007, we identify sectoral technology and capital investment-specific shocks by employing a Vector Autoregression. The identifying assumptions are motivated by a two-sector dynamic general equilibrium model. Controlling for real and nominal factors, we find that capital investment-specific shocks explain 70 percent of fluctuations of R&D investment, while R&D technology shocks explain 30 percent of the variation of aggregate output, net of R&D investment. Technology shocks jointly explain almost all the variation of output in the R&D sector and 78 percent of the variation of output in the rest of the economy. They also constitute the main factor of the procyclicality of R&D investment.     

Industry evolution and R&D externalities

R&D externalities can imply ranges of aggregate increasing returns to scale in R&D. As a consequence several equilibria can exist involving different numbers of firms and different R&D investment levels. In a theoretical model the equilibrium dynamics are analyzed, showing that cyclical fluctuations of the number of firms and R&D investment may be expected, and that the long-run equilibrium is highly sensitive to investors' initial beliefs. The model is tested empirically using a unique database comprising competing firms in various R&D races.     

Issues in Assessing the Effect of Interindustry R&D Spillovers

This paper aims to clarify three issues concerning the weighting methodol ogy generally used to evaluate interindustry R&D spillovers. These issues concern the likely nature of the spillovers estimated through different types of supporting matrices; the similarity between input–output (IO), technology flows and technological proximity matrices; and the relevance of the assumption that a single matrix can be used for different countries. Data analyses of weighting components show that technology flows matrices are in an intermediate position between IO matrices and technological proximity matrices, but closer to the former. The various IO matrices, as well as the three technological proximity matrices, are very similar to each other. The panel data estimates of the effect of different types of interindustry R&D spillovers on industrial productivity growth in the G7 countries reject the hypotheses that a technology flows matrix can be approximated by an IO matrix and that a single IO matrix can be usedfor different countries. By transitivity, the procedure that comprises using a single technology flow for several countries is not reliable. The international comparison shows that each country benefits from different types of R&D externality. In Japan and, to a lesser extent, in the US, the rate of return to direct R&D is very high and is likely to compensate for relatively weak interindustry R&D spillover effects. In the five other industrialized countries, the reverse observation is true: strong social rates of return to R&D counterbal ance the poor performances of direct R&D.     

企业研发决策、政府资助方案及最优资助配比

本文对企业和政府在企业研发决策中研发组织方式进行了理论分析,研究了不同市场和不同决策下的政府的资助方案及最优资助配比。研究发现,在独立研发的情况下,封闭市场需要政府资助诱导企业私人研发的投入,且最优配比为1:2;出口导向型市场政府资助对企业私人研发的投入无诱导作用;进口导向型市场企业无需政府资助亦会进行私人研发投入。在产学研合作的情况下,封闭市场中支付学研机构的研发费用率k和政府资助s满足(1+s)(1-k)=1.5时达最优资助配比。     

The R&D knowledge base in city-agglomerations and knowledge searching in product innovative SMEs

ABSTRACT

This paper looks at the relation between the R&D knowledge base of city-agglomerations and knowledge sourcing in product innovative small and medium-sized enterprises (SMEs). The small open Belgian economy is used as a test case. The characteristics of the city-agglomeration’s R&D knowledge are posited to be instrumental for SMEs’ reliance on particular sources of information for innovation. The R&D knowledge base is studied as a multidimensional concept consisting of R&D capacity, R&D specialization and R&D diversification. A representative sample of product innovative SMEs drawn from two waves of the Community Innovation Survey between 2008 and 2012 reveals that a strong R&D capacity at city-agglomeration level favours private external information sources for innovation, but has no influence on the likelihood to rely on public sources for innovation. Accordance between specialization of the private R&D knowledge base and the SME’s activities positively influences the use of clients as information sources for innovation, whereas under these circumstances supplier responsiveness turns out to be less frequently solicited for. A more diversified private R&D environment reduces the reliance on universities and public research organizations as information sources for innovation. A public R&D knowledge base specialized in natural sciences or engineering favours information sources from universities.     

Introduction: Input–Output Analysis of Interindustry R&D Spillovers

As an introduction to this special issue on intersectoral R&D spillovers, I shall first explain what these spillovers are and how economists try to estimate them. I shall then describe the seven papers selected for this issue from the expanding literature on R&D spillovers, summarize their major results and suggest further avenues of research in this area.     

Technology ladders and R&D in dynamic Cournot markets

Motivated by dramatic and unpredictable technological advances in energy production (for instance drilling and extraction of shale oil), we extend Cournot models of competition to incorporate research and development (R&D) that can lead to (stochastic) drops in production costs. Our model combines features of patent racing with dynamic market structure, capturing the interplay between the immediate competition in terms of production rates and the long-term competition in R&D. The resulting Markov Nash equilibrium is found from a sequence of one-step static games arising between R&D successes, and several numerical examples and extensive analysis of the emerging comparative statics are presented. Analyzing the relationship between current market dominance and the level of R&D investments, we find that market leaders tend to invest more, which in some sense makes oligopoly dynamically unstable. We show that anticipated market transitions have long-term impact; for example the potential of future monopoly can spur R&D investment now, even if the firm is presently uncompetitive and not actively producing. We also show that, surprisingly, random innovations have an ambiguous effect on R&D. This feature, which is driven by the Cournot framework, contrasts with the common situation whereby uncertainty lowers innovation and delays R&D investments. Finally, we demonstrate that increased competition may actually increase efforts to innovate through higher desire to achieve dominance. This would match the anecdotal evidence that the threat of market entrants forces incumbents to maintain high R&D.     

Contributions and Channels of Interindustry R&D Spillovers: An Estimation for Japanese High-tech Industries

This paper estimates the contributions of R&D spillovers to four high-tech industries in Japan—general machinery, electrical machinery, transportation machinery and chemicals—by estimating the trans-log cost and share functions that include the R&D stock variables of own and spillover-source industries. The candidates for spillover- source industries are selected on the basis of large R&D flow or R&D proximity. The R&D flow measures the spillover embodied in purchased intermediate goods using input–output coefficients. The R&D proximity measures the extent of similarity between a pair of industries of the distribution of R&D expenditures across research fields, and is expected to show the likelihood of spillover at the R&D stage. The results suggest that electrical machinery benefited from R&D in the chemical industry, through the purchase of intermediate goods, whereas general machinery and transportation machinery benefited from R&D in the metal products industry, through R&D proximity. There was no evidence of the chemical industry benefiting from R&D spillovers. These results clearly imply that the contributions and the channels of R&D spillovers are diverse, casting doubt on earlier studies that used weighted sums of R&D expenditures (or their stocks) of other industries as aggregate spillover variables.     

Globalisation,industrial diversification and productivity growth in large European R&D companies

This paper aims to assess the impact of both geographic and industrial diversification of economic activities on the productivity performance of large European R&D Multinational Enterprises (MNEs). Based on the worldwide subsidiaries of these firms, we measure the performance of the firms according to their level of industrial diversification and globalisation that we proxy with the presence and importance of subsidiaries in the EU, North America and Asia–Pacific regions. The sample consists of large R&D firms that represent about 80 % of total European R&D. In general, the results indicate a positive impact from globalisation on firms’ R&D productivity, especially in the US, while a negative impact for industrial diversification is found.     

Abatement R&D,market imperfections,and environmental policy in an endogenous growth model

We develop an endogenous growth model featuring environmental externalities, abatement R&D, and market imperfections. We compare the economic performances under three distinct regimes that encompass public abatement, private abatement without tax recycling, and private abatement with tax recycling. It is found that the benefit arising from private abatement will be larger if the degree of the firms’ monopoly power is greater. With a reasonably high degree of monopoly power, a mixed abatement policy by which the government recycles environmental tax revenues to subsidize the private abatement R&D is a plausible way of reaching the highest growth rate and welfare.     

R&D subsidies and export performance of manufacturing industries

One of the main purposes of government R&D subsidies is to give domestic enterprises a competitive edge in international trade of high technology products. The empirical evidence, however, is disappointing: cross-section regression approach for six industries and five countries yielded a negative impact of R&D subsidies on exports of research intensive goods. An analysis of the distribution of public funds suggests that this poor performance could at least partially be explained by the high concordance of national technology policies and the concentration of public funds on big science projects.     

Impact of R&D and Technology Diffusion on Productivity Growth: Empirical Evidence for 10 OECD Countries

This paper examines the empirical evidence on the impact of performed R&D and of R&D embodied in intermediate and capital goods on productivity performance in 10 major OECD countries over the last two decades. To quantify intersectoral and international technology flows, industry-level embodied R&D variables were constructed from an input–output (IO) R&D embodiment model. The productivity variables used are discrete Divisia growth indexes of total factor productivity (TFP), which were estimated from an IO growth accounting model. The results from pooled regressions indicate that the rates of return of the R&D variables were positively significant and increasing in the 1980s. In particular, embodied R&D is an important source for TFP growth in services, indicating very high social returns of the flows of capital-embodied technology into this sector. Moreover, the information and communi-cation technology (ICT) cluster of industries played a major role in the generation and cquisition of new technologies at the international level.     

Optimal R&D investment for a risk-averse entrepreneur

Entrepreneurs investing in R&D projects face technical uncertainty associated with the cost to completion of the project, which is idiosyncratic and inherently unhedgeable. We extend existing real options models of R&D investment to incorporate the cost of bearing this unhedgeable risk and find it decreases risk-averse entrepreneurs’ valuations of R&D projects and increases the minimum NPVs required for continued investment in R&D (threshold NPVs) relative to ‘unpriced risk’ values and threshold NPVs. As in the ‘unpriced risk’ case, for less risk-averse entrepreneurs with small R&D projects, threshold NPVs remain negative and decrease with technical uncertainty. However, for sufficiently risk-averse entrepreneurs with sufficiently large R&D projects, threshold NPVs can become positive and increase with technical uncertainty.     

Size and value effects in high-tech industries: The role of R&D investment

We use monthly US stock data over 55 years from 1962 to 2017 to show that the R&D intensity at firms adds another important dimension to the size and value effects in describing stock returns, especially for small high-tech firms. A trading strategy that double sorts on R&D intensity and size or book-to-market ratio outperforms a simple small-minus-big (SMB) or high-minus-low (HML) strategy in producing higher and more significant portfolio returns. The most profitable schemes involve triple sorts by size, BM, and R&D intensity: the payoffs of buying high-BM/R&D-Active portfolio and selling low-BM/R&D-Inactive portfolio in the small-size/high-tech group and that of buying high-tech/high-BM and selling low-tech/low-BM in the small-size/R&D-active group generate a return of more than 2% on a monthly basis. Our results are robust to alternative classification method of assigning stocks in portfolios.