SURVEY OF SCIENTIFIC RESEARCH AND EXPERIMENTAL DEVELOPMENT CLAIMANTS

SURVEY OF SCIENTIFIC RESEARCH AND EXPERIMENTAL DEVELOPMENT CLAIMANTS June 1996 Project Report Prepared by ABT Associates of Canada for Department of Finance and Revenue Canada

SURVEY OF SCIENTIFIC RESEARCH AND EXPERIMENTAL DEVELOPMENT CLAIMANTS June 1996

Copies of this report may be obtained from: Distribution Centre Department of Finance 300 Laurier Avenue West Ottawa, Ontario K1A 0G5 Telephone: (613) 995-2855 Facsimile: (613) 996-0518 Also available on the Internet at http://www.fin.gc.ca/ Cette publication est également disponible en français.

TABLE OF CONTENTS EXECUTIVE SUMMARY... i I INTRODUCTION... 1 A. Overview...1 B. The Survey Sample...1 C. Structure of this Report...1 II DESIGN OF THE SURVEY OF SR&ED CLAIMANTS... 3 III CHARACTERISTICS OF SR&ED CLAIMANTS...5 A. Overall Characteristics...5 B. Industrial Distribution...6 C. Research Activities...6 D. Areas of Research...7 E. Contract and Shop-Floor R&D...9 F. Decision Criteria for SR&ED Expenditures...10 G. Product and Process Innovation...11 H. Types of Innovation Supported...11 I. Ranking Elements of Government Support for R&D...12 J. Impacts of SR&ED Incentives on Other Investment Spending...13 IV INCREMENTALITY, COST-EFFECTIVENESS AND IMITATION... 15 A. Overview...15 B. Incrementality...15 C. Determinants of Incrementality...16 D. Cost-Effectiveness...21 E. Imitation Effects...21 V ADMINISTRATIVE ISSUES... 25 A. Findings from the Survey of Firms...25 B. Survey of Accountants and Consultants...29 VI CONCLUSIONS... 37 A. SR&ED Tax Incentives Have a Large Incremental Impact...37 B. SR&ED Tax Incentives are Cost-Effective...37 C. Competitive Advantage is the Major Reason for SR&ED Spending...37 D. Most Work is in Applied Research and Experimental Development...38 E. Development of New Products and Processes is Most Important...38 F. SR&ED In Information Technology and Manufacturing Dominate Total Claimants...38 G. R&D Plays a Key Business Strategy Role...38 H. The Federal SR&ED Tax Credit is the Most Important Influence on R&D Spending Among Forms of Government Support...38 I. Imitation is Not Reported to be a Major Problem...38 J. Views Differ on Revenue Canada s SR&ED Administration...39 APPENDIX A... 43 APPENDIX B... 49 APPENDIX C... 69 APPENDIX D... 83 APPENDIX E... 86

EXECUTIVE SUMMARY A. OVERVIEW This report provides our analysis of the data from the survey of firms that have claimed either deductions or credits for scientific research and experimental development (SR&ED) expenditures. In addition, it provides the results of a companion survey of accounting firms and consultants who specialize in assisting firms with their SR&ED claims. This report is a background study to a broader evaluation study of income tax support for SR&ED that is being conducted jointly by the Department of Finance and Revenue Canada. B. THE SURVEY SAMPLE Many of the evaluation issues require information that can be provided best through a survey of firms that have made SR&ED claims. A telephone survey was determined to be the best option to obtain this information. The sample of firms to be contacted in the survey was developed from Revenue Canada s listing of 7,438 firms claiming SR&ED credits or deductions in 1992. The sample that we developed, using data obtained from the Department of Finance and Revenue Canada, is a stratified sample with random selection within two of the three strata that we used. We selected, as potential respondents, all firms from among the top 300 claimants and then sampled randomly to obtain quotas from the medium and small categories of claimants. Interviews were completed with a total of 501 claimants, with 129 respondents in the large claim category, 206 medium claimants, and 166 small claimants. The results were then weighted to represent the universe of SR&ED claimants. C. THE CHARACTERISTICS AND EXPERIENCE OF CLAIMANTS 1. Classification of SR&ED Spending The SR&ED spending of claimant firms can be characterized as follows: Firms carrying out SR&ED work are represented in many sectors of the economy, but the largest numbers are located in the manufacturing sector and the service sector. Most research by responding firms is in applied research and experimental development (96%). Developing new products or processes accounted for 61% of total SR&ED expenditure, while improving existing products or processes accounted for 34% of expenditures. Firms doing SR&ED work in Canada focus heavily on product rather than process innovations. Only 25% of their SR&ED work was in the process area the remaining 75% was accounted for by work on new or improved products. Approximately 44% of respondents reported carrying out at least some SR&ED in the area of information technology (IT). i

The amount of SR&ED tax credits claimed by our sample firms varies substantially across all firms and within size categories. Within the small size class, claims ranged from $577 to $104,000. For the medium firms, the claims ranged from $106,000 to $384,000. The largest size category contained claims of more than $385,000. Respondents also varied in terms of taxpayer status. In the large claimant category, 54% of respondents were taxpayers, compared with 46% in the medium category and 45% in the small category. 2. Firms Seek Competitive Advantage Through New Product Development Our results show a dominant focus on developing new products. To the extent that this process is successful, firms will be able to capture new markets or consolidate shares in existing ones. This is reflected in the survey responses to a series of questions dealing with the reasons for undertaking SR&ED work. In the survey, firms clearly identified creating a competitive advantage over competitors products and processes as the major reason why they spend money on SR&ED activities. Internal cash flow is also important and government tax and non-tax support appears to exert its influence through its effect on cash flow rather than through its effect on the after-tax rate of return. 3. The SR&ED Tax Credit is the Key Component of Government Support The firms in our sample identified government support as a key determinant of spending. The survey then asked these firms about the relative importance of different elements of the overall system of government support, including direct grants and research contracts, intellectual property protection and provincial tax incentives. Among these features of the current system of support, the federal tax credit for SR&ED was rated most highly. 4. Imitation is Not Important for Most Respondents The goal of SR&ED is to create knowledge. Knowledge is likely to be under-provided in a market environment because it is imperfectly appropriable. That is, the benefits of SR&ED activities are likely to spill over and benefit firms that have not paid to conduct this work. Firms do try to protect the results of their SR&ED activities through patents, copyrights, and trade secrecy, but they still report the loss of potential profits in spite of protection efforts. For example, even though patent and copyright regimes have been established for this purpose, it may be difficult for the originator of some technological advance to protect his or her property rights from imitators. While other forms of spillovers associated, for example, with losses of key employees to competitors can also be important, we asked respondents only about imitation. Most of the firms in our sample do not report that imitation is a significant concern. Imitation, however, appears somewhat more likely for IT firms than for non IT firms and is more likely for firms in the smaller size categories of SR&ED claims. ii

Both intellectual property protection and trade secrecy are used more in the IT sector than in the non IT sector. Although eligibility requirements for patent and copyright protection may also differ between these sectors, this finding implies that these spillovers would be more of a problem in the IT sector in the absence of the protection measures that are used. D. INCREMENTALITY AND COST-EFFECTIVENESS 1. Incrementality Survey respondents indicated that the system of tax incentives has a substantial impact on their SR&ED activity. We calculated the degree of incrementality weighted by the SR&ED expenditure of each firm. Incrementality is defined as the extent to which the incentives increased SR&ED expenditures. The extent of incrementality includes the responses of those reporting no incremental effect as well as the amount of incrementality reported by other firms. Weighted incrementality for all firms was 32%. For firms reporting lower SR&ED expenditures in the absence of incentives, the reported reductions in SR&ED expenditures are large. These reductions would have taken a variety of forms including cancelling projects, delaying projects and stretching out time frames to completion. Fewer firms would reduce technological objectives and shift work outside Canada. Regression analysis found that there are no statistically significant differences between IT and non IT firms. Consequently, results are presented only for a pooled regression model of both IT and non IT firms. In the pooled model, incrementality was reported to be higher for firms that ranked after-tax return on investment and cash flow as key determinants of SR&ED spending. Incrementality was reported to be lower for firms for whom R&D is a key component of their overall business strategy. The regression model variables that were significant are opinions of firms as compared with observable characteristics such as firm size. Opinion variables of this kind are not normally available to policy-makers. As a result, we developed a regression model with only observables included. In this regression model, only the percentage of SR&ED devoted to developing new (as opposed to improved) products and the percentage of SR&ED results protected by intellectual property laws were significantly related to incrementality. All other observable characteristics, including sales revenue, ownership, age and R&D intensity are insignificant. The implication is that any attempt to increase the cost-effectiveness of the incentive by discriminating according to one or more of the observable characteristics would likely be ineffective. 2. Cost-effectiveness We used the incrementality data together with an estimate of the tax costs of the SR&ED incentives to provide an estimate of the cost-effectiveness of the system. This cost-effectiveness measure is defined as the ratio of incremental SR&ED expenditures to the estimated tax costs of generating those expenditures. This measure indicates the amount of incremental SR&ED expenditure per dollar of foregone tax revenue. A ratio greater than one indicates that the tax incentive is cost-effective. Overall, this cost-effectiveness ratio is 1.38. iii

E. ADMINISTRATIVE ISSUES Responding firms rated a number of aspects of Revenue Canada s administration of the SR&ED system highly. Services of science advisors, the consistency of scientific reviews and financial audits, and Revenue Canada s information sources all received good ratings. Concerns about timeliness, particularly in processing claims, were very evident, especially for IT firms. The survey of accounting firms that do SR&ED-related work provides a different perspective particularly on the issue of consistency of financial audits and scientific reviews. The accountants, who see a wider range of judgements and appear to be better placed to judge consistency, rated Revenue Canada much lower than did the responding firms for the consistency of both financial audits and scientific reviews. First time claimant services and information seminars provided by Revenue Canada were less frequently used but were perceived as very useful by those who did use them. General services such as providing brochures, circulars and answering general inquiries were less likely to be described as very useful but were rated as fairly useful by a large number of the respondents who used these services. Firms and the accountants/consultants we interviewed reported that the ongoing cost of compliance, as a percentage of the SR&ED credit claimed, is around 10%. This estimate ranged from 5% for larger claimants to 15% for smaller claimants. The initial claim, however, involves higher compliance costs, typically 13% of the claim. The costs to comply for initial claims range from 8% for large claims to 21% for small claims. F. CONCLUSIONS The results of the analysis of the survey respondents are captured in the following observations. 1. Federal SR&ED tax incentives are reported to have a significant incremental impact on private sector expenditures. 2. There is no statistically significant difference between the degree of incrementality in the IT sector and the non IT sector. 3. The regression analysis shows that firms ranking after tax return on investment and cash flow as important determinants of SR&ED spending had a higher degree of incrementality. The extent of incrementality was lower for firms that ranked R&D as a key component of their overall business strategy. 4. The opinion variables of firms that are described in point 3 above are not routinely available to policy-makers. As a result, we estimated a model based only on observable data. These regression results show that there are few significant differences in the determinants of incrementality based on the observable characteristics of responding firms. As a result, any attempt to increase the cost-effectiveness of the incentives by discriminating on the basis of any of the observable characteristics would likely be ineffective. iv

5. The federal SR&ED tax credit is the most highly ranked source of public support for R&D. 6. The federal tax incentive system is cost-effective. 7. R&D is a key component in the development of business strategy among respondents. 8. Most work is in applied research and experimental development. 9. Creating a competitive advantage is the major decision factor in SR&ED spending. 10. The impact of imitation by competitors is not a significant concern. 11. Perceptions of Revenue Canada s administration of the SR&ED system differ among respondents. Responding firms rate many aspects of Revenue Canada s administration of the SR&ED system relatively highly. Accounting firms and consultants, however, were more critical than respondents from claimant firms. v

I INTRODUCTION A. OVERVIEW In this report, we provide a description and analysis of the results of a survey of Canadian firms that have claimed either income tax deductions or investment tax credits for scientific research and experimental development (SR&ED) expenditures. This report is a background study for a broader evaluation study of Canada s system of income tax support for SR&ED that is being carried out jointly by the Department of Finance and Revenue Canada. B. THE SURVEY SAMPLE The data in this study consist of responses from 501 Canadian firms who were surveyed by Canadian Facts during the fourth quarter of 1995. In addition, Abt Associates carried out interviews with accounting firms specialized in assisting firms with their claims for SR&ED expenditures. The analysis in this report highlights differences in the sample based on IT versus non IT firms, region, claim size, industry sector, and tax-paying status where they are significant. The sample that we selected was a stratified random sample over-representing the large claimants who account for a high fraction of total SR&ED expenditures. However, our conclusions are all based on weighted data that are representative of the universe of SR&ED claimants. C. STRUCTURE OF THIS REPORT The following chapter provides some background information about the survey of SR&ED claimants. In Chapter III, we discuss the main findings of the survey, highlighting differences among types of respondents, based primarily on the size of claims, region and whether or not the SR&ED activities of the claimants were in the information technology (IT) area. For purposes of describing firms on the basis of responses to the survey, we defined IT to mean the use and development of communication technology and computer software to conduct, process, store and disseminate information. Chapter IV focuses on the areas of incrementality of SR&ED spending, the extent of imitation of SR&ED outputs and the cost-effectiveness of the Canadian system of support for SR&ED activities. The final chapter provides the overall conclusions of the study. Appendices contain a detailed description of our sampling procedures, the survey instrument for the survey of firms, the methods that we use to estimate cost-effectiveness, the results of the regression analysis that we have carried out, and the interview guide for the survey of accountants and consultants. 1

II DESIGN OF THE SURVEY OF SR&ED CLAIMANTS Many of the evaluation issues require information that can be provided best through a survey of firms that have made SR&ED claims. To generate this information, Revenue Canada and the Department of Finance contracted with Abt Associates to develop and implement a survey of a representative sample of SR&ED claimants. To meet the information requirements of this study most effectively, it was decided to use a telephone survey to gather the data. The sample of firms to be contacted in the survey was developed from Revenue Canada s listing of 1992 SR&ED claimants 1. The 1992 file of claimants was selected because corporate tax return amendments frequently continue well after the end of a particular tax year. This meant that 1992 was the most recent year for which an essentially complete set of returns was available. The sample is a stratified sample with random selection within two of the three strata that were used. The plan that we developed with the assistance of the Department of Finance and Revenue Canada for stratification and sample selection is as follows: Include all of the top 300 claimants in the sample frame, termed the large claim firms. We aimed at 175 completions. For claimants in the medium size category (rank from 301 to 1000 by size of 1992 claim), we randomly selected 555 firms for the sample frame. The target was 200 completions. For claimants in the small category by size of claim (rank 1001 to end of file), we randomly selected 590 firms. The target was 165 completions. We developed this stratified sampling plan because the distribution of dollar value of claims is very skewed in the direction of many small claimants. A non-stratified random sample would have substantially under-represented the firms in the medium and large size categories that constitute most of the dollar value of SR&ED claims. Actual completions by strata were as follows: Large 129 Medium 206 Small 166 TOTAL 501 1 More detailed information on the sample selection procedures that we followed can be found in Appendix A to this report. 3

Using the sampling weights for each size category, we weighted the responses to reflect the complete distribution of 1992 claimants (see Appendix A). However, in the tables that are presented we scale the weighted results back to the base of the sample of 501 firms rather than the sample population of 5,124 firms. That is, although the results are representative of the population, we based all statistical measures on the actual number of observations. In this way, the appropriate sample sizes are preserved for calculating tests of statistical significance, reflecting the fact that the results are based on a sample and not a complete census of firms. 4

III CHARACTERISTICS OF SR&ED CLAIMANTS This chapter presents information on the characteristics of SR&ED claimants based on responses from 501 Canadian firms that were interviewed by Canadian Facts during the fourth quarter of 1995. 2 It describes, among other things, their research activities and their perceptions of the importance of various factors affecting their R&D decisions. A. OVERALL CHARACTERISTICS Exhibit III-1 provides summary data on the characteristics of the firms in our sample. On average, respondents had claimed SR&ED tax incentives for seven years. Most firms in the sample are not subsidiaries of a larger firm, although being a subsidiary is more typical of firms with the largest SR&ED claims (40%). Dedicated R&D subsidiaries are rare. The proportion of non-canadian ownership is relatively low, over all firms, but the proportion of non-canadian ownership increases with the size category of SR&ED claims. The weighted sample represents firms in terms of their actual geographic distribution. Firms located in Ontario account for 39% of the total, firms in Quebec account for 27%, and firms in the rest of Canada account for the remaining 34%. The average number of employees at 203 reflects the mix of small, medium and large firms in our sample. Firm size and size of SR&ED claims are strongly correlated: 50% of the small claim size category have 1 to 15 employees compared to 3% in this range for the large claim category. One-quarter of firms in the highest claim category have more than 1,000 employees. In terms of tax credits, the upper bound of the small claim category is $104,000 with an upper bound for the medium category of $384,000. In terms of taxpayer status, in the large firm category, 54% of respondents were taxpayers compared with 46% in the medium category and 45% in the small category. More than half of the firms in the sample report employment growth for the period from 1992 to 1994. IT firms in the medium sized claim category are most likely to report employment increases. For other claimants, employment growth rates are similar among firm types, classified by IT and non IT and size of SR&ED claim. In addition, respondents indicate that approximately 30% of work time of employees is devoted to SR&ED activities; this mean for the sample as a whole varied little across IT and non IT firms or size category of SR&ED claim. 2 The Survey Instrument for Claimant Firms is in Appendix B. The survey instrument was prepared for computer-assisted telephone interviewing (CATI). 5

EXHIBIT III-1 Characteristics of Firms in Sample (Base is 501 Responding Firms) Number of Years Claiming SR&ED Tax Incentives 7 Subsidiary of Larger Organization 17% Special Purpose R&D Subsidiary 3% Proportion of Non-Canadian Ownership 11% Average Number of Employees in Canada 203 Percentage Reporting Employment Growth, 1992 to 1994 53% Percentage of Work Time Devoted to SR&ED 30% There is substantial variation in how long respondent firms have been operating in Canada. More than 23% of respondents started operations before 1970, 20% started between 1970 and 1979, 43% started between 1980 and 1989 and 11% started in 1990 or later. B. INDUSTRIAL DISTRIBUTION The industrial distribution of the firms in our sample is shown in Exhibit III-2. Among respondents, 51% identified the primary industrial classification of their firm as manufacturing. The service sector accounted for 13% of respondents, with small numbers in most of the remaining industries that were identified. C. RESEARCH ACTIVITIES There is strong agreement among respondents that R&D plays a very important role in the strategy of their company. Nearly 81% of respondents provided this answer. Respondents were asked to classify their research activities into the categories of Basic Research, Applied Research and Experimental Development. These terms were defined as follows: Basic Research is pure research where there is no specific application in mind. Applied Research is research where there is a practical application. Experimental Development is work to overcome technological uncertainty and to achieve technological improvement in a product or process. 6

EXHIBIT III-2 The Industrial Distribution of the Sample Industrial Sector Number % Agricultural, Forestry, and Fishing 48 10 Mining, Oil and Gas 19 4 Construction 5 1 Manufacturing 257 51 Transportation 8 2 Wholesale Trade 12 2 Retail Trade 3 1 Finance, Insurance, & Real Estate Services 1 Services 64 13 Other 84 17 Total 501 100 Note: The other category includes the following responses: software, communications, engineering and biotechnology. Applied research and experimental development were said to be equally important. Few firms reported conducting basic research. The responses to the distribution of activities among these categories is as follows: Basic Research; 4%. Applied Research; 50%. Experimental Development; 46%. The patterns of responses did not vary by size of claim or by the IT/non IT distinction. D. AREAS OF RESEARCH We asked respondents about the fraction of their SR&ED activities accounted for by work in different areas of research. Exhibit III-3 shows the areas of research in which the firms in our sample said they were making SR&ED expenditures. Information technology, mentioned by 254 respondents, was the largest category, followed by manufacturing which was mentioned by 188 respondents. 7

EXHIBIT III-3 Areas of Research (% of all mentions) Other 11.53% Pharma. 2.31% Energy 4.61% IT 34.46% Environmental 6.78% Biotech 2.99% Manufacturing 25.51% Materials 11.80% Note: The responses in the other category include medical, software, forestry, electronic and engineering. Multiple mentions are possible. Some firms conduct SR&ED activity that is exclusively within information technology. Others are predominantly engaged in SR&ED activity that is not within information technology, and some firms SR&ED is a mix of both. Later, we capture this complexity in various classifications of firms depending on the aspect of the SR&ED phenomenon we wish to understand. For descriptive purposes, Exhibit III-4 shows the three types of firm described above according to the proportion of their 1994 tax incentive eligible R&D that was typically allocated to work on IT. 8

EXHIBIT III-4 Percentage of 1994 Tax Incentive Eligible R&D that was Typically Allocated to Work Predominantly on Information Technology Base: Total Respondents Predominantly IT Predominantly Non IT Both Number of Respondents 151 273 72 Percentage of SR&ED Expenditure on IT % % % None 0 88 0 Up to 15% 0 9 0 15%-25% 0 2 46.5 26%-50% 0 0 29.8 51%-75% 0 0 14.4 76%-85% 0 0 9.3 86%-100% 97 0 0 Don t Know/Refused 3 0.5 0 Percentage of all firms 30 55 14 In terms of the extent of SR&ED undertaken in the IT area, we assign firms to one of the following categories: Predominantly IT firms with 85% or more of their SR&ED work in the IT area. These firms provided a single incrementality response that we apply to all of their SR&ED. A comparable category of non IT firms with 85% or more of their work outside the IT area. A mixed group of firms who do more than 15% of their SR&ED work in IT and more than 15% in non IT. For these firms, we assign their SR&ED expenditures on IT and their incrementality response on IT to the IT category. Their non IT work is similarly broken out and assigned to the non IT category. E. CONTRACT AND SHOP-FLOOR R&D SR&ED activities may be undertaken for firms through contracts with other R&D performers. In addition to establishing the extent of contracting, we asked about the extent of SR&ED activities that are carried out on the shop floor that is, undertaken together with production activities. Our survey results show the following: Respondents reported that they contracted approximately 6% of their SR&ED work to, or carried out collaborative work with, educational or other not-for-profit institutions. Firms with relatively small SR&ED claims were less likely than others to have any contracts. 9

Respondents said that they contracted approximately 12% of their SR&ED work to organizations other than educational or not-for-profit institutions. Again, smaller claimants were the least likely to contract. Shop floor R&D, carried out in conjunction with production activities, accounted for 31% of the SR&ED work of responding firms. IT firms were less likely to conduct such R&D. F. DECISION CRITERIA FOR SR&ED EXPENDITURES The economic literature on factors influencing R&D spending decisions has identified a number of variables that may influence firms decisions. Many statistical studies have attempted to estimate the impact of a series of variables on R&D expenditures. Another perspective on this issue is provided by the opinions of firms about the importance of different factors. We asked respondents to this survey to provide us with their assessments of a number of potential determinants of R&D spending. The responses to these questions are shown in summary form in Exhibit III-5. For each of the six possible influences, respondents were asked to rate their importance on a scale of 1 to 10, where 1 is not at all important and 10 is extremely important. We have calculated the mean score on this scale for each factor. The factor identified as most important in these ratings is creating a competitive advantage over competitors products or processes, followed by cash flow position and government tax and non-tax support. Approximately 53% of the respondents ranked competitive advantage as a 10. EXHIBIT III-5 Factors Influencing SR&ED Expenditures By Rank Order of Mean Scores Mean Scores Creating a Competitive Advantage 8.7 Cash Flow Position 7.2 Government Tax and Non Tax Support 7.0 Payback Period on R&D Investments 6.4 After-Tax Return on R&D 6.0 Maintaining Ratio of R&D to Sales 4.4 Note: Scores shown above are an average of responses reported on a scale of 1 to 10. Presentation of these items in the interview was rotated randomly to avoid order bias in responses. 10

Overall, these responses can be summarized as follows: The decision rule is profit or net worth-oriented (competitive advantage) but explicit rate of return calculations are less important. Internal cash flow is important and government support appears to exert its influence through its effect on cash flow rather than through its effect on after-tax rate of return. Simplistic rules of thumb, such as maintaining a constant ratio of R&D to sales, are much less important. From these results, it appears that the R&D decision is characterized by respondents as one of pursuit of competitive advantage subject to an internal cash flow constraint which is assisted by government support. The pattern of responses was not significantly different between IT and non IT firms and was not related to the size of the SR&ED claim. Quebec firms, however, with a mean of 8.1, were more inclined to rank highly the importance of government tax and non-tax support for R&D and the payback period on investments in SR&ED with a mean of 7.1. G. PRODUCT AND PROCESS INNOVATION SR&ED work is typically characterized as either product or process innovation. Product innovation involves the development of new goods and services or improvements to existing ones. Process innovation involves changes and improvements to the production process. Respondents to this survey reported that product innovation accounted for most of their SR&ED spending. They indicated that 75% of their spending was on new products and only 25% on process innovation. No significant pattern was evident by firm type. H. TYPES OF INNOVATION SUPPORTED For all of their SR&ED expenditures, respondents were asked to categorize the innovations that their firms were developing as follows: Developing new products or processes. Making improvements in existing products or processes. Imitating existing processes or products. The respondents indicated that new products or processes constituted the largest category, accounting for 61% of total SR&ED expenditures. Making improvements in existing products or processes accounted for 34% of expenditures while activities described as imitating existing products or processes accounted for only 5% of expenditures. 11

No differences were evident in the responses of any of the categories of firms in terms of the allocation of SR&ED to developing new products or making improvements in existing processes or products. However, predominantly non IT firms indicated that 7.0% of their SR&ED expenditures were devoted to imitation compared to 1.2% for predominantly IT firms. I. RANKING ELEMENTS OF GOVERNMENT SUPPORT FOR R&D A number of elements make up the system of government support for R&D that has been developed in Canada. Exhibit III-6 provides a summary of how the respondents in this survey rated the importance of each of these elements. EXHIBIT III-6 The Importance of Different Forms of Government SR&ED Support By Rank Order of Mean Scores Mean Scores Federal Tax Credit for SR&ED 7.8 Refundability of the Federal Tax Credit 7.7 Intellectual Property or Trade Secrecy Protection 6.3 Expensing of Capital Expenditures for SR&ED 5.9 Provincial Tax Incentives for R&D 5.8 Government Grants and Contracts for R&D 5.1 Note: These are average scores from responses provided on an importance scale ranging from 1 to 10. Presentation of these items in the interview was rotated randomly to avoid order bias in responses. The federal tax credit for SR&ED expenditures was rated as the most important component in the system of government support. Government grants and contracts received the lowest rating on this scale. Firm rankings of the various elements of government support for R&D were tabulated in terms of the size of the SR&ED claim and by region. Claim size was categorized as large (in the top 300 by claim size), medium (rank 301 to 1,000) or small (rank 1,001 to end of file). Region was coded as Ontario, Quebec and the Rest of Canada because most provinces outside Ontario and Quebec had too few observations to classify separately. There are remarkably few response differences to any of the questions based on the size of the claim. The only notable difference is found in responses to the refundability question. This was rated much lower by large claimants (especially larger IT claimants) presumably because most are ineligible for this component of the incentive package. 12

Differences by region are shown in Exhibit III-7. In general, responses provide lower numerical scores from respondents in Ontario with the highest scores coming from respondents in Quebec. Higher ratings in Quebec for provincial tax incentives and government R&D grants and contracts may reflect a greater degree of availability of these incentives in that province. This finding is consistent with the discussion of the data in Exhibit III-5 in which Quebec firms were more likely to rank government support more highly. EXHIBIT III-7 Regional Differences in Assessments of Government Support Mean Scores Ontario Quebec Rest of Canada Federal Tax Credit for SR&ED 7.4 8.4 7.7 Refundability of Federal Tax Credit 7.0 8.3 7.8 Intellectual Property, Trade Secrecy 6.1 6.9 5.9 Expensing of R&D Capital 5.2 6.1 6.4 Provincial Tax Incentives 6.1 6.9 5.9 Government R&D Grants and Contacts 4.3 6.1 5.4 J. IMPACTS OF SR&ED INCENTIVES ON OTHER INVESTMENT SPENDING Support for SR&ED may affect additional spending in other areas if the decision to conduct R&D is related to other spending decisions. We asked respondents about the extent to which federal SR&ED tax incentives influenced their other investment spending, which we assume to mean primarily machinery and equipment. If SR&ED capital and other capital equipment are complements, then measures that promote SR&ED spending will also promote spending on related capital. The survey asked firms to consider their 1994 investment spending in areas other than SR&ED in the hypothetical case of no federal R&D tax incentives. In their responses, firms provided the following information: 36% said that other investment spending was higher as a result of all the tax incentives. 58% said that other investment spending would have been about the same. 4% of respondents said other investment spending was lower and 3% were unable to answer. Generally, there were no differences among categories of firms except that Quebec firms were most inclined (45%) to say that other investments would be lower. 13

IV INCREMENTALITY, COST-EFFECTIVENESS AND IMITATION A. OVERVIEW This study provides information about a variety of elements of the Canadian tax incentive system to support Scientific Research and Experimental Development. Two elements are, however, of particular importance. These are the degree of incrementality and the extent of imitation. In our analysis, we also link the amount of incremental SR&ED spending by each firm with the dollar amount of tax concessions to that firm to indicate the relative cost-effectiveness of the tax incentives. This measure is the amount of incremental R&D spending per dollar of tax concessions granted. The imitation analysis focuses on the extent to which the R&D outputs of responding firms are used elsewhere without compensation. Note that throughout this section we use the 1992 SR&ED expenditures of each firm as a base together with the corresponding survey response on incrementality in 1994. Note also that this chapter contains data from one large firm that did not complete the full survey questionnaire but did provide answers to the incrementality questions. These responses are used only in the incrementality and cost-effectiveness calculation. B. INCREMENTALITY The overall impact of federal tax incentives for SR&ED on expenditure levels is a central question in the evaluation of this system. To pursue this issue, we asked each firm in the survey about the incrementality of the SR&ED activities for which they received tax credits or deductions. Specifically, firms were asked to estimate the impact of the federal tax incentives on their SR&ED expenditures. For firms indicating that their SR&ED expenditures would have been lower or higher in the absence of the federal SR&ED tax incentives, we asked by what percentage their spending on SR&ED would have been different. The results on this issue, for the respondents in our sample, are shown in Exhibit IV-1. The key point in these data is that respondents indicate that the SR&ED tax incentives have had a substantial impact on their SR&ED activity. Respondents indicated that the reductions in SR&ED expenditures would be accomplished in a variety of ways. Reducing the scale of expenditures, cancellation of projects, postponement of projects and stretching out projects are all reported by most respondents. Fewer firms would reduce technological objectives and shift work outside Canada. To arrive at an overall incrementality estimate, we calculated the weighted extent of incrementality for all firms in the sample. Incrementality is defined in percentage terms as the extent to which SR&ED expenditures were larger as a result of the tax incentives. This measure of incrementality, which reflects differences among firms in SR&ED expenditures, is calculated as follows: WEIGHTED INCREMENTALITY = Σ[INCi*(SR&EDi/Σ(SR&EDi)] 15

EXHIBIT IV-1 Impacts of Federal SR&ED Tax Incentives Percentage of firms reporting reduced SR&ED expenditures in the absence of federal tax 57% incentives Percentage of firms reporting no effect on expenditures 38% Forms of Reductions Reported (Among Firms Reporting Reductions) Cancellation of some SR&ED work 80% Postponing the start of some SR&ED work 86% Across the board or proportional cuts 74% Stretching out some SR&ED work 69% Reducing technological objectives 53% Shifting SR&ED work outside Canada 25% Note: Respondent firms were asked these questions about both their IT and non IT expenditures. The responses in Exhibit IV-1 are weighted averages of the responses of the firms in these two categories. In this calculation, all incrementality responses including zero and a few responses that spending would have increased are included. Using this weighted approach to incrementality, which reflects the impact of the tax incentives on total SR&ED expenditures, we found that weighted incrementality is 32%. That is, reported SR&ED expenditures were 32% higher as a result of the federal SR&ED tax incentives. The 95% confidence interval on this weighted incrementality estimate ranges from 30% to 35%. C. DETERMINANTS OF INCREMENTALITY 1. Overview The survey results for each firm in our sample provide information on the extent of incrementality and on the characteristics of the firm. In this section, we assess the extent to which there may be significant patterns in the incrementality responses. For example, firms with larger amounts of SR&ED expenditure might have different incrementality responses than other firms. Another example is that incrementality may differ between IT and non IT firms. We use the statistical technique of multiple regression analysis to determine whether there are differences of this kind apparent in the data. Full details of the regression results are provided in Appendix C. 2. Regression Models The underlying assumption of the regression analysis is that it is reasonable to expect the response to SR&ED tax incentives to vary from firm to firm. The SR&ED incentives increase the after-tax rate of return on an investment in R&D. They also increase after-tax cash flow. Projects that might not have been sufficiently profitable on an after-tax basis without the incentive become profitable. Greater cash flow is available to finance projects that may have been profitable but could not be financed in the absence of the incentive. 16

Firms are likely to differ both in the extent to which they have R&D opportunities that would be extramarginal in the absence of the incentive and in the extent to which their investment activity is cash flow constrained. As a consequence, some firms are likely to be more responsive to the incentive than others. Targeting the incentive on this group would then increase its cost-effectiveness. That is, if the incentive could be directed toward the more responsive firms, aggregate additional R&D induced per dollar of tax revenue foregone could be increased. The question is then whether there is a systematic relationship between measurable characteristics of firms and their responsiveness to the incentive. Regression analysis is used to determine the extent and nature of this relationship. In the regression models, we assess the following firm characteristics that may influence responsiveness: Firm size: It has been argued that smaller firms are both more innovative and more likely to be cash flow constrained and thus potentially more responsive to R&D incentives. This may, however, be more a function of age and line of business than of size per se. Any size relationship is likely to be non-linear. That is, there is little reason to expect a size-related difference in responsiveness among larger firms. Size is measured as gross revenue. Foreign Ownership: It has long been argued that foreign owned firms are less R&D intensive than their Canadian counterparts. Others have found that these differences in R&D intensity disappear if size is held constant. Whether there is an ownership effect on the responsiveness to R&D incentives is a different question. Foreign owned firms may be less responsive because their R&D is confined to certain routine shop floor or quality control activities or because they are less likely to be cash flow constrained. On the other hand, foreign firms may shift the location of their R&D internationally in response to incentives and this could make them more responsive. Age: It is generally argued that the class of firms that is potentially most responsive to R&D incentives is start-up and threshold firms. These firms are thought to have proportionately more opportunities and proportionately less favourable access to finance. The age effect should be non-linear. That is, there is little reason to believe that age differences should be important among older firms. Percentage ED: The development end of the SR&ED spectrum is supposed to be more influenced by immediate commercial (rate of return) considerations. ED-oriented firms may be more responsive to R&D incentives. It may also be the case, however, that ED is essential to remain competitive and it is the SR end of the spectrum which is discretionary and therefore more sensitive to R&D incentives. Compliance Costs: Responsiveness should be lower among firms with higher marginal compliance costs. Higher average compliance cost per dollar of SR&ED will not necessarily imply higher marginal compliance costs. Percentage Innovation: The responsiveness to the incentive may be greater among the innovative firms as opposed to the imitative/adaptive firms. Imitative and adaptive R&D may be more likely to be inframarginal, driven possibly by the innovations of others. Note that if 17

imitative R&D were more responsive to the incentive, the equilibrium effect of the incentive would be less positive than the impact effect. Influence of Cash Flow: Survey respondents indicated the importance of this variable in determining their SR&ED expenditures. This provides an indicator of the extent to which financing constraints may differ among firms. Influence of After-Tax Return on Investment: This variable was provided by survey respondents. In standard economic models, this is a key determinant of SR&ED spending. R&D Considered Important: This survey response variable provides information on how important R&D is in the overall corporate strategy of the firm. Our hypothesis is that firms in which R&D is more important will have a lower degree of incrementality. Manufacturer: There may be industry effects on responsiveness. They should reflect inter-industry differences in technical opportunity. Greater technical opportunity may imply that there are proportionately more extra-marginal projects that become profitable with the incentive. This need not be the case. High-tech industries may require higher levels of R&D but this may be an all or nothing proposition leaving relatively little that is dependent on the tax environment. This may be the same kind of result as with the R&D Important variable. Under these circumstances, the response to the incentive is not so much within the firm as it is with the size of the industry. The incentive does not significantly change what inframarginal firms do but it attracts more firms to the industry. R&D Intensity: The arguments regarding R&D intensity, defined as SR&ED expenditures as a fraction of sales revenues, have been covered above. R&D intensity may be associated with more or less responsiveness at the margin. It implies greater technical opportunity but it also implies greater exploitation of these opportunities. This is also a jointly dependent variable so that the impact effect may be biased. Percentage Innovations Protected by Intellectual Property (IP): The effect of IP on responsiveness is also ambiguous. It may or may not imply that there are proportionately more extra-marginal R&D opportunities that become profitable with the incentive. This depends on the distribution of R&D opportunities. IT: This variable distinguishes IT from non IT firms. The variable is a categorical (0,1) variable to distinguish the two types of firms. The measurable characteristics described above are proxies for the underlying determinants of responsiveness at the firm level. Responsiveness depends on the distribution of opportunities (the marginal product of R&D capital) and on financial constraints (adjustment costs in neo-classical economic models). Firms evaluations of the respective importance of after-tax rates of return and cash flow provide direct evidence on potential responsiveness. These variables are used as independent variables in the regression models to explain differences among firms in the degree of incrementality of their SR&ED expenditures. 18

3. Regression Results a) Incrementality: IT and Non IT Firms This section reports the results of the statistical analysis of incrementality. Specifically, our initial test is to determine if there is a difference between IT and non IT firms in terms of the responsiveness of incrementality to the explanatory variables. In the multivariate analysis of incrementality, firms are maintained in the sample only if they are either predominantly IT or predominantly non IT. The statistical model that we use contains a complete set of interaction terms to test for differences in regression coefficients between IT and non IT firms. A Tobit estimate of the interaction model described above is reported as Tobit regression 1 in Appendix C. A Tobit model is used here because the dependent variable is either zero or a positive response. It is apparent in this regression that none of the α coefficients is statistically significant at the five per cent significance level. The implication is that the coefficients of the regression model do not differ between IT and non IT firms. Hence there is no analytical reason to distinguish between the two groups of firms. Accordingly, the following subsections are based on incrementality models that are common to IT and non IT firms. b) Effects of Firm Characteristics on Incrementality The results described in the previous sub-section show that we can reject the hypothesis that firm incrementality responses differ between the IT and non IT sectors. As a result, the investigation of systematic influences on the degree of incrementality should be pursued in a common statistical model. The estimated ß coefficients in this model apply to both IT and non IT firms. Estimates of the ß coefficients are reported as Tobit regression 2 in Appendix C. We find that three coefficients are statistically significant. These are: Firms that ranked after tax return on investment as a key determinant of SR&ED spending had a higher degree of incrementality. Firms that ranked cash flow as an important determinant of SR&ED spending had a higher degree of incrementality. Firms reporting higher degrees of importance of R&D in their overall business strategy reported lower degrees of incrementality. The interpretation of this effect is that some firms operate in competitive environments that make R&D essential regardless of tax incentives. The three statistically significant variables reflect firm strategies or operating approaches. Firms for which after-tax rate of return and cash flow considerations are relatively important tend to be more responsive to the incentive. This is understandable given that the effect of the incentive is to increase the after-tax rate of return on SR&ED and to increase cash flow. Similarly, firms regarding R&D as crucial to their success are less responsive to the incentive. They have to do the R&D to stay in business. As suggested above, responsiveness to the incentive may result in a change in the number of firms in the industry rather than changing the R&D decisions of existing firms. 19