Jacques Mairesse

Research, Innovation And Productivity: An Econometric Analysis At The Firm Level

This paper studies the links between productivity, innovation and research at the firm level. We introduce three new features: (i) A structural model that explains productivity by innovation output, and innovation output by research investment: (ii) New data on French manufacturing firms, including the number of European patents and the percentage share of innovative sales, as well as firm-level demand pull and technology push indicators; (iii) Econometric methods which correct for selectivity and simultaneity biases and take into account the statistical features of the available data: only a small proportion of firms engage in research activities and/or apply for patents; productivity, innovation and research are endogenously determined; research investment and capital are truncated variables, patents are count data and innovative sales are interval data. We find that using the more widespread methods, and the more usual data and model specification, may lead to sensibly different estimates. We find in particular that simultaneity tends to interact with selectivity, and that both sources of biases must be taken into account together. However our main results are consistent with many of the stylized facts of the empirical literature. The probability of engaging in research (R&D) for a firm increases with its size (number of employees), its market share and diversification, and with the demand pull and technology push indicators. The research effort (R&D capital intensity) of a firm engaged in research increases with the same variables, except for size (its research capital being strictly proportional to size). The firm innovation output, as measured by patent numbers or innovative sales, rises with its research effort and with the demand pull and technology indicators, either directly or indirectly through their effects on research. Finally, firm productivity correlates positively with a higher innovation output, even when controlling for the skill composition of labor as well as for physical capital intensity.

Financial Factors and Investment in Belgium, France, Germany, and the United Kingdom: A Comparison Using Company Panel Data

We construct company panel data sets for manufacturing firms in Belgium, France, Germany, and the United Kingdom, covering the period 19781989. These data sets are used to estimate empirical investment equations, and to investigate the role played by financial factors in each country. A robust finding is that cash flow and profits terms appear to be both statistically and quantitatively more significant in the United Kingdom than in the three continental European countries. This is consistent with the suggestion that financial constraints on investment may be relatively severe in the more market-oriented U.K. financial system.

Accounting for Innovation and Measuring Innovativeness: An Illustrative Framework and an Application

The purpose of this paper is to propose and illustrate an accounting framework for innovation. We characterize the intensity of innovation by a sales-weighted measure of innovation: the share of sales in innovative products, but other output indicators of innovation could be considered as well. Comparing statistics on the share of innovative sales across countries, industries, or firms measures but does not explain the intercountry, interindustry, or interfirm differences in innovation intensity. To have a more meaningful basis of comparison we need a model. If an exact model of innovation in its various dimensions existed and if we knew it, we would be able to understand fully why innovation differs among countries, industries, or firms. Of course, such a model does not exist. Nevertheless it is worth trying to account for innovation differences, if only very roughly. In such an endeavor, what remains to be explained is as important to consider as what can be explained, because it reflects the extent of innovative ability or capacity, or “innovativeness.” To motivate our approach better and make it more explicit, we find it appealing to draw a comparison with the standard framework for growth accounting and the underlying model of a production function. Production output is viewed as resulting from a process of transformation of inputs into output that can be represented and analyzed in terms of a production function. Based on the production function, an accounting framework can be constructed in which changes in output between periods (years, decades) or differences between spatial units (firms, industries, countries) are ascribed to changes or differences in the inputs and in a residual that is known as total factor or multifactor productivity (TFP or MFP) or simply productivity. Likewise, innovation output can be viewed as resulting from innovation inputs, such as R&D efforts, and other contextual determinants, such as the pressure of competition. This linkage can be represented in terms of an innovation function and an innovation accounting framework, on the basis of which changes in innovation output between periods or differences between spatial units can be ascribed to changes or differences in the factors of innovation and in a residual that we call innovativeness, or the unexplained ability to turn innovation inputs into innovation output. Innovativeness is thus to innovation what TFP is to production. Innovativeness is conditional on a model of an innovation function and a set of factors of innovation, just as TFP is conditional on an assumed specification of the production function and measured factors of production. Both correspond to omitted factors of performance such as technological, organizational, cultural, or environmental factors (and to other sources of misspecification errors), although TFP is commonly interpreted as being mainly an indicator of technology. The produc-

Empirical Studies of Innovation in the Knowledge Driven Economy

This introduction to a special issue of EINT surveys a collection of ten papers that study various aspects of innovation and knowledge management and their impact on performance at the firm level for a number of countries. These studies have been conducted using data drawn from innovation surveys combined with data from a number of other sources. The issue illustrates the value of these surveys in improving our understanding of innovation in firms and raises a number of questions for future work in this area.

Do Product Market Regulations in Upstream Sectors Curb Productivity Growth? Panel Data Evidence for OECD Countries

We identify the impact of intermediate goods markets imperfections on productivity downstream. Our empirical specification is based on a model of multifactor productivity (MFP) growth in which the effects of upstream competition can vary with distance to frontier. This model is estimated on a panel of fifteen OECD countries and twenty industries over 1985 to 2007. Competitive pressures are proxied with industry product market regulation data. We find evidence that anticompetitive upstream regulations have significantly curbed MFP growth over the past fifteen years, and more strongly so for observations that are close to the productivity frontier.

Firm Level Investment and R&D in France and the United States: A Comparison

This paper is a contribution to the small but growing literature that compares the investment and RD the major differences are between countries.

Panel-Data Estimates of the Production Function and the Revenue Function: What Difference Does it Make?

The lack of individual firm information on output prices is a major problem in the econometrics of production. In particular, it may be expected to account for a significant share of the large discrepancies found between the cross-sectional and time-series estimates of capital and scale elasticities. However, taking advantage of two panel-data samples for which we had such information, we find that estimating the revenue function (using a nominal output measure) or the production function proper (using a real output measure) makes very little difference for our results. The biases due to other sources of specification errors are probably more important.

The Economics and Econometrics of Innovation

Overview. Part I: The Macroeconomic Effects of Innovation. 1. On the Macroeconomic Effect of Major Technological Change P. Aghion, P. Howitt. 2. On Knowledge Diffusion, Patents Lifetime and Innovation Based Endogenous Growth P. Michel, J. Nyssen. 3. Endogenous Growth and the Labor Market F. Cerisier, F. Postel-Vinay. Part II: Publicly Funded Science. 4. Research Productivity in a System of Universities J.D. Adams, Z. Griliches. 5. Reputation and Competence in Publicly Funded Science: Estimating the Effects on Research Group Productivity A. Arora, et al. 6. The Impact and Organization of Publicly Funded Research and Development in the European Community M.P. Feldman, F.R. Lichtenberg. 7. An Auction Model of Intellectual Property Protection: Patent Versus Copyright M. Waterson, N. Ireland. 8. Information Disclosure and the Renewal of Patents C. Crampes, C. Langinier. 9. Appropriation Strategy and the Motivations to Use the Patent Systems: An Econometric Analysis at the Firm Level E. Duguet, I. Kabla. 10. Patents and R&D, An Econometric Investigation Using Applications for German, European and US Patents by German Companies G. Licht, K. Zoz. Part III: Network Goods and Standardization. 11. Equilibrium Coalition Structures in Markets for Network Goods N. Economides, F. Flyer. 12. Does Standardization Really Increase Production? H. Stahn. Part IV: Investment and Productivity in R&D. 13. Accumulation of R&D Capital and Dynamic Firm Performance: A Not-So-Fixed Effect Model T.J. Klette, F. Johansen. 14. Are there Financing Constraints for R&D and Investment in German Manufacturing Firm? D. Harhoff. Part V: Profits from Innovation. 15. The Commercial Success of Innovations: An Econometric Analysis at the Firm Level in French Manufacturing C. Barlet, et al. 16. Incentives for Cost Reducing Innovations under Quantitative Import Restraints C.C. Cabral, et al. 17. The Size Distribution of Profits from Innovation F.M. Scherer. Part VI: Spillovers. 18. Looking for International Knowledge Spillovers: A Review of the Literature with Suggestions for New Approaches L. Branstetter. 19. Factor Intensities, Rates of Return, and International R&D Spillovers: The Case of Canadian and U.S. Industries J. Bernstein. 20. Exploring the Spillover Impact on Productivity of World-Wide Manufacturing Firms H. Capron, M. Cincera. 21. Innovation Spillovers and Technology Policy Y. Katsoulacos. Index of Names. Index of Subjects.

Chapter 24 – Measuring the Returns to R&D

We review the econometric literature on measuring the returns to R&D. The theoretical frameworks that have been used are outlined, followed by an extensive discussion of measurement and econometric issues that arise when estimating the models. We then provide a series of tables summarizing the major results that have been obtained and conclude with a presentation of R&D spillover returns measurement. In general, the private returns to R&D are strongly positive and somewhat higher than those for ordinary capital, while the social returns are even higher, although variable and imprecisely measured in many cases.

The Importance of R&D for Innovation: A Reassessment Using French Survey Data

This paper compares the contribution of R&D to innovation in terms of the various innovation output measures provided by the third Community Innovation Survey (CIS 3) for French manufacturing firms and in terms of accounting for interindustry innovation differences.