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APPROPRIABILITY AND PUBLIC SUPPORT OF R&D IN CANADA
Abstract
This paper investigates the extent to which considerations of inappropriability, a form of market failure, guide federal support to private industrial R&D in Canada. Statistics of the overall allocation of subsidies between grants and tax credits show little evidence at an inappropriability rationale. Econometric analysis of grant distributions, using a recently proposed operational concept of inappropriability, supports this conclusion at an aggregate level, but gives different results when a particular grant program is probed.
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NOTES AND REFERENCES
Palda K.. 1984. . Industrial Innovation: Its Place in the Public Policy Agenda . , p. 168 Vancouver : : The Fraser Institute. .
Noll R.. 1977. . “‘Government policy and technological innovation,’. ”. In Innovation, Economic Change and Technology Policies . , Edited by: Storetman K.. Basel : : Birkhauser. .
Tarasofsky A.. 1984. . The Subsidisation of Innovation Projects by the Government of Canada . , Ottawa : : Economic Council of Canada. .
Grossman G.. 1990. . ‘Promoting new industrial activities: A survey of recent arguments and evidence,’. . OECD Economic Studies . , Vol. 14: Spring;: 88––125. .
Noll, op.cit.
Recent reasoning by D. Mowery and N. Rosenberg (Technology and the Pursuit of Economic Growth, Cambridge University Press, 1989) and others tend to weaken this assertion.
Bernstein J.. 1985. . “‘Research and development, patents, and grant and tax policies in Canada,’. ”. In Technological Change in Canadian Industry . , Edited by: McFetridge D. G.. p. 1––42. . Toronto : : University of Toronto Press. .
B. Bozeman and W. Link, ‘Tax incentives for R&D: A critical evaluation,’ Research Policy, 1984, pp. 21–31. See also K. Woodside, “Tax incentives vs subsidies: political considerations in governmental choice,’ Canadian Public Policy, 1979, pp. 248–56.
D. Usher, The Benefits and Costs of Firm-Specific Investment Grants, Queen's University (Canada) Discussion Paper, January 1983.
Cohen W. and Levinthal D.. 1989. . ‘Innovation and learning: The two faces of R&D,’. . Economic Journal . , Vol. 99((397)): 569––96. .
I. Henriquez, Do Firms Free Ride on Their Rivals’ R&D Expenditures?, Queen's University, Kingston, Ontario, Doctoral Dissertation, 1990.
Grant statistics are derived from Statistics Canada surveys of research-performing private and crown-owned firms. The reports by recipients do not always match the figures of the granting ministries or agencies, perhaps chiefly due to timing discrepancies. Tax statistics refer to tax credit claims, rather than refunds. These have also been compiled from surveys, but only until 1985. From 1985 on they are compiled by Revenue Canada on the basis of income tax returns rather than R&D performance surveys. It is impossible to say how this more comprehensive reading affects the consistency of the tax claim series. Claims, in the absence of taxable profits, may be carried forward against (quite remote) tax liabilities. In addition, not all claims may of course be allowed. Knowledgeable sources estimate that ten or fifteen per cent of the claims --- not of the total sums --- are disallowed.
D. McFetridge, On the Adequacy of the Information Provided to Parliament Regarding the Scientific Research Tax Credit: An Analysis of the Public Record, April 1983-January 1984, Unpublished report to the Auditor General, Ottawa, 1986.
Among the references consulted were the Science Council of Canada, Reaching for Tomorrow-Science and Technology Policy in Canada 1991, Ottawa, 1992; S. McInness, ‘Setting science and technology policies in Canada”, in B. Grousse et al. (eds), Science and Technology Policy Evaluation, Presses Laval, Québec, 1990 and The Budget, tabled February 16, 1991, Ch. 7.
A. Harvie, Notes for Opening Remarks to the Legislative Committee on Bill C-22, Consumer and Corporate Affairs Canada, 1986.
Industry, Science and Technology Canada (ISTC), Support For Technology Development, Ottawa, 1989, p. 9.
Tarasofsky, op. cit., p. 40.
Atkinson M. and Powers R.. 1987. . ‘Inside the industrial policy garbage can: Selective subsidies to business in Canada’. . Canadian Public Policy . , Vol. 13((2)): 208––17. .
D. Horsley et al, Industrial Assistance Programs in Canada, Toronto: CCH Canadian Limited, 1985, 80-560 and 80-575 and Office Consolidation, Industrial and Regional Development Act and Regulations, Ottawa, February 1985.
Griliches Z.. 1979. . ‘Issues in assessing the contribution of research and development to productivity growth’. . Bell Journal of Economics . , Vol. 10((1)): 92––116. .
The innovator would capture all returns to his innovation if he could extract the total consumer surplus through perfect price discrimination. Price discrimination is, however, usually infeasible for legal or practical lessons.
For the United States, consult N. Terleckyj, ‘Direct and indirect effects of industrial research and development on the productivity growth of industries’, in J.W. Kendrick and B. Vaccara (eds), New Development in Productivity Measurements, Chicago University Press for NBER, Studies in Income and Wealth, 44, Chicago, 1980 and F. Scherer, ‘Inter-industry technology flows in the United States’, Research Policy, 11, 1982, pp. 227–45. For Canada, see H. Postner and L. Wesa, Canadian Productivity Growth Analysis, Economic Council of Canada, Ottawa, 1983; P. Hanel, ‘L’effet des dépenses en R&D sur la productivityé du travail au Québec’, L'Actualité économique, 64, 3, 1988, pp.396–415.
Z. Griliches, op. cit.
The means of access to new technology vary from completely legal exchange of scientific information or personal contacts and mobility, through reverse engineering and copying, down to illegal industrial espionage.
The spillovers are commonly estimated in a cost function model c = C(y,v,S), where c is the cost of production, y the vector of factor prices and S a vector of spillover variables. Factors include own R&D capital. The interindustry spillover is Si =Σ WijRj where Rj, is the stock of knowledge available in other industries j, and Wij the weighing function, i.e. the actual fraction of knowledge originating in industry j and borrowed by industry i. The intra-industry spillover is defined in an analogical manner.
The existence of inter-industry differences in propensity to patent documented by F. Scherer, ‘The propensity to patent’, International Journal of Industrial Organisation, 1983, pp. 107–8 and an international comparison based on Canadian patent data by A. Englander et al., ‘R&D, innovation and the total factor productivity slowdown’, OECD Economic Studies, Autumn 1988, pp. 7–42 indicates that the patent spillovers matrices are a very imperfect proxy for technology flows in general and for R&D spillovers in particular. This led I. Cockburn and Z. Griliches, ‘Industry effects and appropriability measures in the stock market's valuation of R&D and patents’, American Economic Review, Papers & Proceedings, 78,2, 1988, pp. 419–23, to the conclusion that the data on R&D measures are stronger measures of input than patents are of output of the innovaton process. In spite of statistical shortcomings of patent data, the patent classification represents the richest source of technical information and, therefore, can be used to characterise the firm's position in the technology space. Assuming that firms patenting in the same patent classes are technologically close, A. Jaffe, ‘Technological opportunity and spillovers of R&D: Evidence from firm's patents, profits and market value’, American Economic Review, 76, 5,1986, pp. 984–1001, characterised a firm's position in the space of patent classes. He found that R&D productivity is increased by the R&D of “technological neighbours”, though neighbours’ R&D lowers the profits and market value of low R&D intensity firms. Firms are shown to adjust the composition of their R&D in ?response to technological opportunity.
L. Séguin-Dulude, ‘Les flux technologiques interindustriels: une analyse exploratoire du potentiel canadien’, L'Actualité économique, 58, 1, 1982, pp. 259–83.
J. Hartwick and B. Ewen, On Gross and Net Measures of Sectoral R&D Intensity for the Canadian Economy, Queen's University (Canada), Discussion Paper no. 547.
J. Berstein, ‘Cost of production, intra and interindustry R&D spillovers: Canadian evidence’, Canadian Journal of Economics, 21, 2, 1988, pp. 324–43. The advantage of this method is that it does not single out one particular form of spillover. On the other hand, when coefficients Wij are estimated in this manner, they act as a “catch all” variable and ascribe to spillovers of technology effects of omitted or mismeasured variables.
Mansfield E.. 1977. . ‘Social and private rates of return from industrial innovations’. . Quarterly Journal of Economics . , Vol. 91((2)): 221––40. .
P. Hanel, op. cit., p. 411.
F. Scherer (1982) op. cit. and N. Terleckyj, op. cit.
Owing to the very limited number of industries for which the amount of federal grants is disclosed (12 out of 21 manufacturing industries) the grants had to be lumped together with federal R&D contracts in order to increase the number of usable observations to 20. Even though the increase of the sample size is desirable for statistical purposes, by adding federal contracts to grants we commit a specification error, because R&D contracts are more likely to be awarded for “public service” reasons rather than as a remedy to market imperfections. The grant cum contract dependent variable is therefore an inferior specification for a test of appropriability and other types of market failure. Source: Statistics Canada, Industrial Research and Development Statistics, 1987, Catalog No. 88-202 Annual.
The information from annual reports on Industrial and Regional Development Programs was supplemented by a custom-made computer listing kindly made available by the Department of Industry, Science and Technology.
Mansfield E.. 1980. . ‘Basic research and productivity increase in manufacturing’. . American Economic Review . , Vol. 70((5)): 863––73. .
D. McFetridge and R. Corvari, ‘Technology diffusion: A survey of Canadian evidence and the public policy issues’, in Donald McFetridge, co-ordinator, Technological Change in Canadian Industry, vol. 3, Research Studies for the Royal Commission on the Economic Union and Development Prospects for Canada, Canada Supply and Services, Ottawa, 1985.
L. Ducharme and P. Mohnen, R&D Spillovers and Social Rates of Return on R&D, Paper presented at the Congrés de la Société canadienne de science économique, Mount Gabriel, Québec, 24-26 May 1989.
L. Séguin-Dulude, op. cit. pp.278–79. This variable takes into account only the spillovers to first users; ideally, it should be possible to take into account the interindustry ramifications in order to include the total downstream effect. Another limitation of variable DUL is that it is based on the judgement of experts in the patent office rather than observed facts. For a significant proportion of patents, especially for very pathbreaking inventions, the industries most likely to produce and/or to use them may not even exist and cannot be determined.
R. Levi, A. Klevorick, R. Nelson and S. Winter, Appropriating the returns from industrial research and development’, Brookings Papers on Economic Activity 3, 1987, pp. 783–831.
In their overview of the survey, Cockburn and Griliches (op. cit.) demonstrated that for an analysis on the industry level, the response to the question about the effectiveness of patents to prevent competitors to duplicate the new produce provides more variance among industries. Responses about other means of appropriation, such as information about process innovations and sales and service efforts, are less industry specific and also harder to interpret.
McFetridge D.. 1977. . Government Support of Scientific Research and Development: An Economic Analysis . , p. 16––23. . Toronto : : Ontario Economic Council Research Studies. .
Note that in order to avoid duplication, we excluded “Basic Research” from the R&D expenditures aimed at “Radical Change”. Statistics Canada kindly provided a special tabulation of the 1987 R&D data for variables BRD and RAD.
Arrow K.. “‘Economic welfare and the allocation of resources for invention’. ”. In The Rate and Direction of Inventive Activity . , p. 609––25. . Princeton : : Princeton University Press. .
L. Switzer, Lorne, Etude des répercussions des mesures fiscales et des dépenses publiques sur les investissements du secteur privé en recherche et développement, Gouvernement du Québec, Ministère de l'enseignement supérieur, de la science et de la technologie, Québec, 1986.
Levy D. and Terleckyj N.. 1983. . ‘Effect of government R&D on private R&D investment and productivity: A macroeconomic analysis’. . Bell Journal of Economics . , Vol. 14:: 551––61. .
D. McFetridge, op. cit., A. Tarasofsky, op. cit.
Lichtenberg F.. 1988. . ‘The private R&D investment response to Federal design and technical competitions’. . American Economic Review . , Vol. 78((3)): 550––59. .
Lichtenberg F.. 1990. . ‘US Government subsidies to private military R&D investment: The Defence Department's independent R&D policy’. . Defense Economics . , Vol. 1:: 149––58. .
The results do not change significantly whether contributions made under the Defence Industry Productivity Program are included or not. The relative size of the industry is not a factor either.
The DUL variable for the other electrical products category includes also electronic parts and other electronic equipment.
J. Hartwick, op. cit.; J. Bernstein, op. cit.; P. Hanel, op. cit.; to cite only a few.
The effectiveness of patents to prevent imitation of process innovations PADC was never statistically significant and results are not presented in Table 6.
ELIM is positively correlated with C4 concentration ratio but subsidies are not. ELIM = 116.6 (.22) + 20.9 C4(2.1)b R2adj. = .13 (F=4.2) n=22 IRDP% = 0.02(.95) - 0.001 C4(−.19) + 2.1E-0.5 ELIM(2.0)b R2adj. = .11 (F=2.3) n=22