Master Thesis in Economics “An analysis of the effectiveness of government R&D policies on business R&D expenditure” doc

The Royal Institute of Technology Master’s program in Economics of Innovation and Growth (Professor Stefan Fölster) Master Thesis in Economics “An analysis of the effectiveness of government R&D policies on business R&D expenditure” Written by Kaifeng Li (kaifeng_baoding@yahoo.com.cn) June 2010 ABSTRACT This thesis investigates the effectiveness of government R&D policies in 13 OECD countries from 1985 to 2007 R&D plays an important role in the world economy, and business-funded R&D accounts for the majority in total R&D spending Policy-makers design various R&D policies to stimulate business R&D expenditure Since the existence of R&D policies, researchers highly contributed their enthusiasm on the analysis of the efficiency of those R&D policies, but the validity of government intervention still received considerable controversy Thereby, the purpose of this thesis is tried to follow the historical arguments and investigates the effectiveness of government R&D policies on business-funded R&D Three questions are mainly addressed: Does the leverage effect of public funding on business R&D really exist? How those different policy instruments influence firms’ R&D behavior? How those policy instruments interact with each other? The thesis searched the answers for the three questions, and concluded that the optimal policy tool for government to stimulate private R&D is tax incentives, and government cannot affect much to firms’ R&D investment decisions Key words: Business-funded R&D, government funding of R&D performed in business, tax incentive, government research, university research, crowding-out effect, crowding-in effect II ACKNOWLEDGEMENTS I would like to express my gratitude to my supervisor Professor Stefan Fölster for the valuable guidance, the precious help, and the constructive advices he provided to me during the entire process Special thanks go to the Professor Hans Lööf for the data analysis guidance, without his generous support and unlimited patience, it is surely that I cannot go this far I would also like to thank Professor Kristina Nyström for the grammar checking and constructive suggestions, I am sincerely appreciated to her kindness At last, I would like to show my deepest gratitude to my mom, whom extremely eliminates my pressure with her love, and her tough support strongly encouraged my thesis working In a word, I would like to extend my sincere gratitude to everyone for kind helps III Table of Contents ABSTRACT II ACKNOWLEDGEMENTS III INTRODUCTION THE THEORETICAL BACKGROUND 3 EMPIRICAL LITERATURE REVIEW 3.1 Empirical Literature Studies on Tax Incentives 3.2 Empirical Literature Studies on Government Direct Financial Support 3.3 Empirical Literature Studies on Public Research 12 ECONOMIC BACKGROUND 13 4.1 Trends of R&D Expenditure 14 4.2 Tax Concessions 15 4.3 Changes of Government R&D Budget 16 DATA AND METHODOLOGY 18 EMPIRICAL RESULTS 20 CONCLUDING REMARKS 27 REFERENCE 30 APPENDIX 32 A The B-Index 32 B Tax subsidy rate for USD of R&D, large firms and SMEs, 2008 35 C Trends of B-index from 1985 to 2007 35 D The Effectiveness of R&D Policy Tools on Business-funded R&D in Country level analysis 36 E The Interaction between Various R&D Policy Tools in Country-level Analysis 37 IV INTRODUCTION In the past few decades, the importance of technical change has received increasing attention both from researchers and policymakers, because of the change stimulate a country’s long-run rate of economic growth A key factor dominating technical change is that the knowledge accumulation through expenditure on research and development (Becker and Pain, 2003) In 1994, R&D was defined by Frascati Manual as “Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society and the use of this stock of knowledge to devise new applications” Despite the recognition of the importance attached to R&D now for long-run economic growth and living standards, it is commonly argued that social optimal R&D level cannot be reached without government intervention Schumpeter (1942), Nelson (1959) and Arrow (1962) firstly argued the rationale of government R&D intervention They hold such a conceptual idea that knowledge is non-rival good Therefore, the private return on R&D investment will hardly be appropriated, which leads to an under-provision of R&D investment in the economy (Lööf and Hesmati, 2004) Guellec and van Pottelsberghe (2000) argued that imperfect appropriability and diffusion of knowledge uncontrolled caused innovators cannot fully appropriate the benefits of their innovations, which implied that the rate of private return to R&D is lower than its social return Becker and Pain (2003) emphasized that market failures can provide a rational for government intervention to support private R&D They mentioned that the expenditure on R&D should be lower than social optimal level if the private rate of return is lower than social rate of return, and if firms experience the significant external financial constrains, the R&D expenditure will also be lower than social optimal level Streicher, Schibany and Gretzmacher (2004) claimed that pure markets will not be efficient in stimulating innovation due to the inherent characteristics of R&D “In most situations the market will fail to provide sufficient incentives to invest in R&D since firms face appropriability problems The reason is that R&D has some characteristics of a public good, so that the private returns on innovation will be lower than its social return” Since the government R&D policy performed, lots of researchers have been contributed their effort to the evidence searching of the effectiveness of government intervention Although most of them observed positive effects in this field, but the validity of government intervention still received considerable controversy Some researchers argued that the existing econometric evidence of the substitutability or complementarity effects of public R&D funding is very inconclusive (Becker and Pain (2003), David, Hall and Toole (1999)) I wish this thesis will contribute about new implications and evidence to the current literature The purpose of this thesis is try to follow the historical arguments and investigates the effectiveness of government R&D policies on business-funded R&D in OECD countries from 1985 to 2007 However, because of the limitation of data collection, only 13 OECD countries have been found that can qualified the thesis’ observation period requirement, which those OECD countries are United States, United Kingdom, France, Italy, German, Japan, Spain, Ireland, Belgium, Portugal, Denmark, Finland, and the Netherlands In the thesis, three questions are mainly addressed: Does the leverage effect of public funding on business R&D really exist? How those different policy instruments affect firms’ R&D expenditure behavior? Do those policy instruments interact with each other? The analysis in this thesis implements a previous analytical model published by Gullec and van Pottelsberghe (2000) From my best knowledge, they are the only researchers whom organized all categories of government R&D policy tools within a single analytical model, which eliminate comparison issues by the heterogeneity of the empirical models used Besides, they also got reasonable results However, in contrast to their analysis, this thesis implemented more advanced regression technique and extended the analysis area to provide more details with country-level studies The observation period is also ten years longer than Gullec and van Pottelsberghe’s analysis The remaining part of this thesis is structured as follows: The next section will provide the theoretical background, and section reviews the empirical literature of the effectiveness of R&D policies In section 4, the thesis will introduce the economic background of the 13 OECD countries Moreover, in the following two sections, this thesis will describe the data set and the analytical model, and state the empirical results The final conclusion will be provided in the section THE THEORETICAL BACKGROUND Historically, there are various policy tools available for government to stimulate business-funded R&D The empirical literature summarizes those policy tools into three main categories: Firstly, government can encourage business R&D activities through favorable tax treatment The R&D tax may increase R&D that is marginally profitable for the firm, but only if the elasticity of R&D with respect to costs is high Government implements this policy tool to decrease firms’ R&D risk through tax breaks based on the level of R&D expenditure Currently, there are many forms of tax treatment of R&D, like accelerated depreciation of investment, tax credit In contrast to the other R&D policy tools, this one is more transparent, and this policy tool is a more market-oriented approach The policy tool leaves decisions on the level and timing of R&D expenditure to the private sector, and meanwhile, it gives a government the option to pay for R&D that is otherwise not profitable at all for the firm, but may be socially worthwhile Guellec and van Pottelsberghe (2000) argued that tax concessions were not conditional on the type of recipient’s R&D performance Therefore, tax incentives will not affect the R&D composition Secondly, government can directly fund business R&D through granting or/and procuring private R&D projects The previous mentioned Frascati Manual identified that the government direct funds to business R&D into two categories, one is specifically for procurements of R&D (the R&D result is government property) The other category is that government commits grants or subsidies to the R&D performer (the R&D results belong to the recipient) Yong (1998) argued that government procurements, grants, and fiscal incentives account for the bulk of government support to business R&D In this category, the government funds will be purposed for the specific technical projects which seem to have higher rate of social return Public investors wish that additional research projects will take place in contrast to the ones that would have been done without the public support through the performance of this policy tool Although the government funded R&D and performed by business primarily includes procurement and grants, it is worth to remind that some other forms of direct R&D support still exist, like loan guarantees, conditional loans, and convertible loans At last, through funding public research (public laboratories and universities) government may indirectly support private R&D Due to the main purpose of public institutions is generating basic knowledge to meet public needs But the knowledge may directly employ by private firms to improve their private return on R&D investment Besides, basic research may also open new opportunities to business research, which in turn affects productivity Hence, this policy has a possibility to trigger higher business R&D expenditures through technology spillover effects When government commits their funds with the purpose to encourage private R&D expenditures, they may aim directly to fund business R&D through granting or/and procuring private R&D projects to reduce the private R&D cost, or indirectly to support private R&D by providing technological opportunities available to firms If those policies works well, then public and private funding will be complementary, which means increase the intensity of one will enhance the other However, empirically, those policy tools have been challenged by four main grounds: full crowding-out effect, partial crowing-out effect, no influence, and allocative distortion Streicher, Schibany and Gretzmacher (2004) argued that R&D expenditure and the reaction of R&D subsidies were the result of firms’ internal decisions Therefore, government policy tools cannot (or only partially) influence private R&D directly The figure is used to graphically describe part of the five main effects on public support to business-funded R&D Figure The effects of R&D subsidies on total R&D expenditures (Source: Input Additionality Effects of R&D Subsidies in Austria 2004) Firstly, for crowding-out effects, the full crowding-out effects implies firms may use government money as “windfall gains” They just use that money simply to substitute their own spending Moreover, government spending may increase the cost of R&D to crowd out private money Goolsbee (1998) and David and Hall (1999) both had been observed that government funding significantly raised the wage of researchers For instance, government funding may increase the salary of researchers, although the total amount of R&D costs looks higher, but nothing actually changes, and the real amount of R&D may be even lower than before The partial crowding-out effect means that firms may raise their R&D expenditure, but less than the amount of government support Secondly, public support has no influences on private R&D occurs when firms maintain the level of their R&D expenditures, but by use of full amount of the subsidy extends total research Because of firms would like to more R&D than they can afford to enhance their advantage in market, but banks are reluctant to provide financial support Thirdly, the crowding-in effect reflects the stimulating effect of public support on private R&D expenditure, which means with one unit of public R&D spending will induce higher amount of business R&D expenditure than government support In the empirical literatures, some authors use “substitutability” to imply crowding-out effect, and taken “complementarity” to imply crowding-in effect Like David, Hall and Toole (1999) At last, the reasons of inducing allocative distortions is that government funds allocated to a project in the less efficient way than market force will If government funding is directed towards those projects that firms will undertake anyway, thus this will leads to a misallocation of resources Furthermore, in the imperfect market, when government provides their financial assistance to a firm, government may help the recipient even it is initially inferior to alternatives (0.106) (0.098)* 0.0088987 0.0198639 -0.0163153 (0.889) ΔHEi,t-1 (0.088)* (0.748) (0.816) ΔRGt-1*ΔBt-1 -1.3839360 (0.023)** ΔRGt-1*ΔGOVRDt-1 0.0483093 (0.889) ΔRGt-1*ΔHERDt-1 -0.0565775 (0.771) Note: The estimates cover 13 OECD countries over 1985-2007, each variable is expressed in first differences of logarithms In the table, the values displayed in parentheses are p-values The notation of “*”, “**”, and “***” separately indicates the estimates that are significantly different from zero at 10%, 5%, and 1% For the interactive effect between the various policy instruments, the results are displayed in column and column in the table The interaction between government funding of R&D implemented in business and tax incentives is shown as “ΔRGt-1*ΔBt-1”, the interaction between government funding of R&D implemented in business and government intramural R&D expenditure displayed as “ΔRGt-1*ΔGOVRDt-1”, and the relationship between government funding of R&D implemented in business and higher education R&D outlays denoted as “ΔRGt-1*ΔHERDt-1” From table we can see that there are not any interactive effects between government funding of R&D implemented in business and public research But government direct R&D support and fiscal incentives showed as a complementary effect for each other, which implies independently increasing the intensity of government direct funding (tax incentives) which will increase the stimulating effect of tax incentives (government direct funding) on business-funded R&D Moreover, the regression result of interaction between government direct R&D support and fiscal incentives is lower than -1 The interpretation for this is countries that mix the two policies to try to get a greater positive effect on business-funded R&D than countries that use only one of those 24 policies5 The regression results on table are somewhat difference with the empirical results from Guellec and Van Pottelsberghe (2000) In their paper, all of the R&D policy instruments had observed significant impacts on business-funded R&D Government direct support contributed positive effect on private R&D, and both government research and university research had partially crowed out business R&D expenditure Moreover, government direct R&D support and fiscal incentives showed as a substitute effect for each other, and government direct support was complementary to university research No interactive impact had been found between government direct support and government research For the country-level analysis, all the estimate results are shown at appendix D The table summarized those estimated results: Table 6: Summarize the analysis of each of the 13 OECD countries Business sector value-added ΔVA Crowding-in effect Crowding-out effect total Government funding of R&D implemented in business ΔRG Rate of tax subsidies for one dollars of R&D (B-Index) ΔB Government intramural R&D expenditure ΔGOV Higher education R&D outlays ΔHE 3 1 6 In the country-level analysis, business sector value-added showed the significant impact in OECD countries, which are United States, France, Italy, German, If the regression result for the interaction between two R&D policies is lower than but greater than (or the regression result between -1 and o), then the interpretation is countries than avoid to mix R&D policies to try to get the best stimulating effects on business-funded R&D 25 Japan, Spain, Ireland, Portugal, and Denmark Among those countries, except Ireland appeared to have negative effect for value-added, all the rest of countries displayed the positive effect within the observation period The policy of government funding of R&D implemented in business appeared to have significant effect in countries, positive (Spain, Ireland, and Belgium) and negative (United States, France, and Germany) Tax incentives contributed its significant impact on countries This policy instrument displayed stimulating impact in United States, Portugal, and the Netherlands, but tax incentives contributed negative impact in Japan Government intramural R&D expenditure is also contributed significant effect on business-funded R&D in countries Among those countries, the positive results are found in Italy and Japan, but the negative results are observed in Ireland, Belgium, Denmark, and the Netherlands For the higher education R&D outlays, countries had been observed significant effect of this policy instrument Except France showed the positive effect, all the rest of countries (United States, Italy, Japan, Ireland, and the Netherlands) indicated that this policy instrument crowded out private R&D expenditure Recall the results at table 6, unfortunately, there is not any policy instruments have been found that can contributed its effect over half amount of the 13 observed countries at country-level analysis The analysis results for the interactive impact between various R&D policy instruments within each of the 13 OECD countries displayed in appendix E The conclusion of those empirical results in appendix E displayed in table Table Summarize the interaction between various R&D policies in country-level study ΔRGt-1*ΔBt-1 ΔRGt-1*ΔGOVRDt-1 ΔRGt-1*ΔHERDt-1 0 Substitutability 0 Complementarity Total 0 26 There is not much regression results have been captured for the interactive impact between various R&D policy instruments, due to the data colinearity As seen from table 7, the interactive impact between government funding of R&D implemented in business and tax incentives has been observed in OECD countries (Portugal and Spain), and the mixed of those two policy tools displayed complementary effect in both of those two countries Furthermore, the regression result showed that these two countries both tried to mix their R&D policies to get a greater positive effect on business-funded R&D However, the interaction between government direct financial support and public research had not showed to contribute any significant effect among the 13 observed OECD countries CONCLUDING REMARKS Research and development plays an important role in economic growth, and business-funded R&D accounts for the majority in total R&D expenditure Each country’s government contributed much effort to stimulate business-funded R&D through various policy tools This thesis analyzed the effectiveness of government R&D policy tools on private R&D expenditure, and the analysis covered aggregate level, country-level, dynamic viewpoint and non-dynamic viewpoint However, it seems that not all of the R&D policy tools worked correctly as their initial wishes Compare with historical literatures’ results, the empirical analysis in this thesis showed is somewhat difference Firstly, the results in section of this thesis indicate that government funding of business R&D just have short-term and crowding-out effect for business-funded R&D With 1% of government direct R&D support increase will leads to approximately 6% of business R&D expenditure decrease This policy tool is irrelevant to the long-run business-funded R&D behavior Goolsbee (1998) have been argued this situation He used CPS (Current Population Survey) data on 27 wages of scientific personnel in United States to estimate the elasticity of the R&D personnel wage with respect to government R&D spending, and concluded that government R&D spending raised wages significantly Furthermore, OECD Science, Technology and Industry 2009 indicated that except economic downturns, business researchers have grown faster than total industrial workers since the early 1980s In 2006, around million researchers engaged in R&D in the OECD area, and about 7.4 researchers per 1000 employees There is a significant increase from the 1997 level of 6.2 per 1000 Next, this thesis found that public research contributed strongly crowding-in effect in contemporaneous, and university research contributed stronger positive impact than public laboratories With 1% of government spending increase on government research and university research, that will leads to business funded R&D increases approximately by 26% and 41% The public research is not only contributed negative impact on private R&D expenditure Besides, the regression results of public research in this thesis are not only somewhat different to the results from Guellec and van Pottelsberghe (2000), but also partly overthrow the arguments from Kealey (1996) Because he argued that the kind of science produced by public research facilities was irrelevant to the business sector Given the results presented in this thesis, the empirical results clearly indicated that different policy methods can have quite different effects on economic growth With the purpose to stimulate business R&D expenditure in the long-run, it is better to perform tax incentives This is the only way to reach the purpose for government Furthermore, it seems that government R&D policy tools had not affected firms’ R&D investment decisions much Because no policy tools have been found that can contribute its effect over half amount of the 13 observed countries in country-level analysis The perception for those results is as the words from Streicher, Schibany and Gretzmacher (2004): “The level of R&D expenditures is the result of an internal decision process within in the firm; so are 28 the reactions to R&D subsidies Therefore, subsidies not (or only partially) influence R&D directly, but rather indirectly” In the future R&D policy proposal, the results may worth policy-makers to adopt in their consideration Finally, I will use a famous statement from Rothwell and Zegveld (1988) to describe the ultimate purpose of this thesis: “a little bit less a matter of faith and a little bit more a matter of understanding” In the future, researchers may consider performing country-level analysis like what the thesis doing to check whether government intervention really cannot affect firms’ R&D behavior much, and of course, the amount of the collect countries should be that the more the better Moreover, comparing the results in this thesis with the analysis results from Guellec and van Pottelsberghe (2000), different observation period of data tend to have different analysis results Therefore, it would be interesting in a future research to identify the optimal policy tools to stimulate private R&D expenditure 29 REFERENCE Arrow, K (1962), “Economic welfare and the allocation of resources for innovation,” In R Nelson ed., The rate and direction of economic activity, New York: Princeton University Press Austan Goolsbee (1998), Does Government R&D Policy Mainly Benefit Scientists and Engineers? University of Chicago, GSB, American Bar Foundation, and National Bureau of Economic Research Presented at the A.E.A Meetings, Chicago, Illinois January, 1998 Benavent, J.M.(2002) The Impact of Public Financing and Research Groups on Innovative Activities in Chilean Industry Second draft Bent Mulkay and Jacques Mairesse (2003), The Effect of the R&D Tax Credit in France, Preliminary Draft February 14, 2003 Bettina Becker and Nigel Pain (2003) What Determines Industrial R&D Expenditure in the UK? National Institute of Economic and Social Research April 2003, pp.2-3, 9-11 Bronwyn H Hall (1992) R&D tax policy during the 1980s: Success or failure? NBER Working paper, No 4240, Cambridge, MA Bronwyn H Hall and John van Reenen (1999), How Effective are Fiscal Incentives for R&D? A New Review of the Evidence Research Policy 29 (2000) 449-469 CESifo DICE Report 2/2009, pp.54 Dominique Guellec and Bruno Van Pottelsberghe (2000) The impact of public R&D expenditure on business R&D, STI working papers 2000/4 Dominique Guellec and Bruno Van Pottelsberghe de la Potterie (1997) Does government support stimulate Private R&D? OECD economic studies No.29, 1997/II, pp.102-107 Elias Einiö (2009) The effect of Government Subsidies on private R&D: Evidence from the ERDF Population-Density Rule Job Market Paper August 22, 2009 Gerhard Streicher, Andreas Schibany, Nikolaus Gretzmacher (2004) Input Additionality Effects of R&D Subsidies in Austria Empirical Evidence 30 from Firm-level Panel Data March 2004 Pp.9-11 Hans Lööf and Almas Hesmati (2004) The Impact of Public Funding on Private R&D investment New Evidence from a Firm Level Innovation Study.(Additionality or Crowding Out? On the effectiveness of R&D subsidies) July 2004, Revised March 2005 Jacek Warda (2005), Measuring the Value of R&D Tax Provisions, A Primer on the B-index Model for Analysis and Comparisons, Brussels, June 28, 2005, pp.2-5 José Miguel Benavente H, Leonardo González R, and Jocelyn Olivari N (2007) The Effect of Public R&D Subsidies on Private R&D Spending in Chilean Manufacturing Firms 17 August 2007 Kealey Terence (1996), The Economic Laws of Scientific Research McMillan Press, London Mansfield Edwin (1964) Industrial Research and Development Expenditure, Journal of Political Economy, 72, August, pp 319-340 Nelson, R.R (1959), The simple economics of basic scientific research, Journal of Finance 49(3), pp.1015-1040 Nicholas Bloom, Rachel Griffith and John Van Reenen (2000) DP2415 Do R&D Credits Work? Evidence From A Panel Of Countries 1979-97, Discussion Paper No 2415, April 2000 OECD Secretariat Intangible Investment in the Statistical Frameworks for the Collection and Comparison of Science and Technology Statistics.OECD 1998 PP.4 OECD Science, Technology and Industry Scoreboard 2009 Paul A David and Bronwyn H Hall (1999), Heart of Darkness: Public-private Interactions inside the R&D Black Box, Economic Discussion Paper, No 1999-W16, Nuffield college Oxford, June Paul A David, Bronwn H Hall and Andrew A Toole (1999), Is Public R&D a Complement or Substitute for Private R&D? A Review of the Econometric Evidence Prepared for a special issure of Research Policy on technology policy issues, forthcoming in the year 2000 under the guest-editorship of Albert N Link 25 August 1999 31 Rothwell, R And W Zegveld (1998), “An Assessment of Government Innovation Policy”, in J Roessner (ed.), Government Innovation Policy: Design, Implementation, Evaluation, St Martin’s, New York Russell Thomson (2009) Tax Policy and Globalisation of R&D Working Papers in Trade and Development, No.2009/03, pp 59-61 Schumpeter, J (1942), “Capitalism, Socialism and Democracy,” New York: Harper and Row Scott J Wallsten (2000), The Effects of Government-Industry R&D Programs on private R&D: The Case of the Small Business Innovation Research Program RAND Journal of Economics March 22, 2000 Tax Subsidies Reward Job Cutters, Majority in Congress votes to expand loopholes as corporations step up layoffs Citizens for Tax Justice (Washington DC), Sept 19, 1996 William W McCutchen (1993), Estimating the Impact of the R&D Tax Credit on Strategic Groups in the Pharmaceutical Industry (1993) 22(4) Research Policy 337 Young Alison (1998), Measuring Government Support for Industrial Technology, OECD, Paris, mimeo APPENDIX A The B-Index In 1996, Jacek Warda designed a tool which so called “B-index” which can be used to reflect fiscal tax generosity of R&D, and Warda defined the B-index as the present value of before-tax income necessary to cover the initial cost of R&D investment and to pay the corporate income tax So it becomes profitable for a firm to perform R&D activities The B-index usefully solved the international comparison problems (because different countries may implements different R&D tax incentive policies), and provided a synthetic view of tax generosity However, its "synthetic" nature does not allow for distinguishing the relative importance of the various policy tools it takes into 32 account (e.g depreciation allowances, special R&D allowances, tax credit, CITR) The generic formula for B-index is: B index equals to the after-tax cost of an expenditure of USD on R&D divided by one minus the corporate income tax rate The after-tax cost is the net cost of investing in R&D, taking into account all the available tax incentives Where A is the net present discounted value of depreciation allowances, tax credits and other R&D tax incentives available (i.e., after-tax cost) τ denotes the corporate income tax rate If a country with full write-off of current R&D expenditure and no R&D tax incentive scheme, then A will equals to τ So consequently, the B-index will equal to The more generous a country's R&D tax treatment, the lower the B index will be The B-index computation requires some simplifying assumptions Therefore it should be examined together with a set of other -relevant policy indicators B-index vs Tax-subsidy Ratio B-index describes the minimum benefit to cost ratio in which an R&D investment becomes profitable given a jurisdiction’s income tax treatment for firms’ R&D performing The name of B-index is rather cryptic, however, for those using the index Thus other transformations of the B-index have evolved that help to better understand the nature of the index Among them is a tax-subsidy ratio (i.e the value of the B-index subtracted from unity), which has been extensively used by the OECD Including Direct Subsidies 33 In general, subsidies can be included in the B-index in a relative straightforward manner: The generic formula is: Bs = B(1-Ps) Where Bs denotes the B-index adjusted to the subsidy component, B is the unadjusted B-index (incorporating only the impact of R&D tax treatment), and Ps equals the proportion of industrial R&D in a country covered by subsidies The B-index methodology can also be extended to cover government R&D grants and subsidies, like government direct support measures This methodology will lower the B-index, and make a subsidized R&D project relatively more attractive to the firm The replacement of € of private R&D expenditure with € of subsidy reduces the after-tax cost of a € R&D project to zero Since the B-index is expressed as the before-tax income required to cover € of R&D investment, a 100 per cent cost subsidy will reduce the B-index to zero In the case of a 50 per cent subsidy, the R&D project’s after-tax cost will be reduced by a half, thus allowing the B-index to fall by a half of its before-subsidy value 34 B Tax subsidy rate for USD of R&D, large firms and SMEs, 2008 Large Country SMEs France 0.425 0.425 Spain 0.349 0.349 Portugal 0.281 0.281 Denmark 0.138 0.138 Italy 0.117 0.117 Japan 0.159 0.116 Ireland 0.109 0.109 United Kingdom 0.179 0.105 Belgium 0.089 0.089 Netherlands 0.242 0.071 United States 0.066 0.066 Finland -0.008 -0.008 Germany -0.020 -0.020 firms C Trends of B-index from 1985 to 2007 1,1 United States United Kingdom France Italy 0,9 Germany Japan 0,8 Spain Ireland 0,7 Belgium Portugal 0,6 Denmark Netherlands 0,5 2007 2005 2003 2001 1999 1997 1995 1993 1991 1989 1987 1985 Finland 35 D The Effectiveness of R&D Policy Tools on Business-funded R&D in Country level analysis Country Business sector value added ΔVA Government funding of R&D implemented in business ΔRG Rate of tax subsidies for one dollars of R&D (B-Index) ΔB Government intramural R&D expenditure ΔGOV Higher education R&D outlays ΔHE United States 5.878049 -0.7890171 -2.240356 0.7660587 -2.039875 (0.000)*** (0.000)*** (0.000)*** (0.142) (0.001)*** 1.243295 0.012793 0.2084257 -0.0930996 -0.6057861 (0.255) (0.931) (0.872) (0.822) (0.233) 0.8453107 -0.0944092 0.0941443 -0.0145968 0.4379904 (0.007)*** (0.055)* (0.818) (0.936) (0.000)*** 1.152437 0.0448446 -0.6077241 1.203871 -0.7646397 (0.019)** (0.223) (0.484) (0.000)*** (0.000)*** 0.9611311 -0.1101591 -1.286626 -0.333548 0.2427425 (0.005)*** (0.021)** (0.246) (0.245) (0.388) 1.232553 0.0472919 0.3646254 0.8769748 -0.3887691 (0.080)* (0.654) (0.074)* (0.000)*** (0.001)*** 1.816758 0.3185766 -0.1358928 -0.2743773 -0.1452494 (0.083)* (0.024)** (0.664) (0.449) (0.321) -0.9294282 0.0409812 -0.5581244 -0.1997054 -0.687477 (0.000)*** (0.000)*** (0.208) (0.000)*** (0.000)*** Dropped 0.4812408 Dropped -0.6885365 Dropped United Kingdom France Italy Germany Japan Spain Ireland Belgium (0.000)*** Portugal (0.001)*** -0.081396 -0.6432018 -0.1384609 -0.0055813 (0.001)*** Denmark 2.250427 (0.101) (0.001)*** (0.547) (0.983) 0.375196 Dropped Dropped -1.609984 Dropped (0.014)** Netherlands Dropped 0.0611436 -0.4363976 -0.3035707 -0.2427795 (0.245) Finland Dropped (0.005)*** (0.099)* (0.011)** (0.003)*** -0.2570519 Dropped 0.0159787 Dropped (0.110) (0.934) Note: The estimates based on 13 OECD countries over 1985-2007, each variable are expressed in first differences of logarithms In the table, the values displayed in parentheses are p-values The notation of “*”, “**”, and “***”, 36 separately indicates the estimates that are significantly different from zero at 10%, 5%, and 1% E The Interaction between Various R&D Policy Tools in Country-level Analysis Country United States ΔRGt-1*ΔBt-1 ΔRGt-1*ΔGOVRDt-1 ΔRGt-1*ΔHERDt-1 Dropped Dropped 0.3678418 (0.718) United Kingdom Dropped Dropped Dropped France Dropped Dropped Dropped Italy Dropped Dropped Dropped Germany -27.2813 (0.238) Dropped 1.177698 (0.306) 0.0622312 (0.819) Dropped 2.681676 (0.150) Dropped -0.1902075 (0.6000) Dropped Dropped Japan Spain Ireland -5.570754 (0.000)*** Dropped Dropped Belgium Dropped Portugal Dropped Dropped Denmark -2.199491 (0.003)*** Dropped Dropped Dropped Netherland Dropped Dropped Dropped Finland Dropped Dropped Dropped Dropped Note: The estimates based on 13 OECD countries over 1985-2007, each variable are expressed in first differences of logarithms In the table, the values 37 displayed in parentheses are p-values The notation of “*”, “**”, and “***”, separately indicates the estimates that are significantly different from zero at 10%, 5%, and 1% 38 ... section reviews the empirical literature of the effectiveness of R&D policies In section 4, the thesis will introduce the economic background of the 13 OECD countries Moreover, in the following... enthusiasm on the analysis of the efficiency of those R&D policies, but the validity of government intervention still received considerable controversy Thereby, the purpose of this thesis is tried... results in section of this thesis indicate that government funding of business R&D just have short-term and crowding-out effect for business- funded R&D With 1% of government direct R&D support increase