Building the Knowledge Stock: Lags,Depreciation, and Uncertainty in R&D Investment and Link with Productivity Growth

The search for an appropriate methodology to investigate the relation between R&D investment, knowledge stock and productivity growth is the main purpose of the paper. In analogy with physical assets, we present a model of knowledge capital formation which allows the calculation of the relevant user cost, as well. The proposed model accumulates R&D investment based on a stochastic gestation lag and a geometric depreciation of the stock. The basic parameters underlying the lag structure differ according to the types of research expenditure. The approach is applied to public R&D investment in Italian agriculture; the results provide interesting information about the economic structure of public research effort in Italian agriculture and plausible estimates of its internal rate of return.     

The negative impact of R&D capitalization: A value relevance approach

Abstract

Accounting for R&D costs is an open issue. SFAS N°2 mandates that all R&D costs must be immediately expensed. IAS 38 requires capitalization of R&D costs if they meet certain criteria. Recent research papers show the value relevance of capitalized R&D. We test the value relevance of R&D reporting in a sample of 197 French firms between 1993 and 2002. The French context provides an interesting field for R&D value relevance studies because both accounting treatments of R&D costs (expensing and capitalization) are allowed. Unlike previous studies, we find that capitalized R&D is negatively associated with stock prices and returns. This negative coefficient on capitalized R&D implies that investors are concerned with and react negatively to capitalization of R&D. We also find that the firms choosing to capitalize (successful) R&D are smaller, more highly leveraged, less profitable and have less growth opportunities. Taking into account these characteristics, our robustness checks confirm that capitalized R&D is not associated with higher prices and is related to lower returns.     

Real options game models of R&D competition between asymmetric firms with spillovers

Using real options game models, we consider the characterization of strategic equilibria associated with an asymmetric Research and Development (R&D) race between an incumbent firm and an entrant firm in the development of a new innovative product under market and technological uncertainties. The random arrival time of the discovery of the patent protected innovative product is modeled as a Poisson process. Input spillovers on the R&D effort are modeled by the change in the leader’s hazard rate of success of innovation upon the follower’s entry into the R&D race. Asymmetry between the two competing firms include sunk costs of investment, stochastic revenue flow rates generated from the product, and hazard rates of arrival of success of R&D efforts of the two firms. Under asymmetric duopoly, we obtain the complete characterization of the three types of Markov perfect equilibria (sequential leader–follower, preemption and simultaneous entry) of the firms’ optimal R&D entry decisions with respect to various sets of model parameters. Our model shows that under positive input spillover, preemptive equilibrium does not occur in the R&D race due to the presence of dominant second mover advantage. The two firms choose optimally to enter simultaneously if the sunk cost asymmetry is relatively small; otherwise, sequential equilibrium would occur. When the initial hazard rate is low relative to the level of input spillover, simultaneous entry would occur as an optimal decision, signifying another scenario of dominant second mover advantage. On the other hand, when the initial hazard rate is sufficiently high so that the first mover advantage becomes more significant, simultaneous equilibrium does not occur even under high level of positive input spillover.     

Interindustry R&D Spillovers for Electrical and Electronic Products: The Canadian Case

This paper estimates the effects of interindustry R&D spillovers on the cost and production structure for 10 Canadian manufacturing industries. Because of their high-tech nature and productivity performance, spillovers from electrical and electronic products are distinguished from other spillover sources. Generally, spillovers from electrical and electronic products generate cost reductions and render production processes for Canadian manufacturing industries more capital intensive (i.e. either more physical or R&D capital intensive). Social rates of return for R&D capital are calculated for all 10 industries. The social rates are 5–11 times greater than are the private rates. Indeed, the social rates are high for all the industries. This implies that the electrical and electronic products industry is an important interindustry spillover source but, like other industries, a major spillover-using industry.     

中国行业层面研究与试验发展资本存量核算

研究目标：测算中国八大行业门类研究与试验发展（Research and Development，R&D）资本存量。研究方法：基于SNA2008的GDP核算框架，厘清R&D支出的资本化核算框架；再利用美国BEA方法测算R&D资本存量。研究发现：1990~2015年，中国R&D资本存量不到美国R&D资本存量的1/4；然而，自1994年后，中国R&D资本存量年均增长率达24.79%，而美国仅为4.86%，中美两国R&D资本存量差距呈逐渐缩小趋势；制造业R&D资本存量占全国R&D资本存量的比例呈上升趋势，从1990年的17.41%增长到2015年的68.08%，这与中国加快制造业转型升级的事实相符。研究创新：给出完整的R&D支出资本化核算过程，首次测算中国八大行业门类的R&D资本存量。研究价值：为分析技术进步对经济增长的影响提供了行业层面R&D投资和资本存量数据序列。     

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

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

Rates of return to public agricultural research in 48 US states

The internal rate of return to public investment in agricultural R&D is estimated for each of the continental US states. Theoretically, our contribution provides a way of obtaining the returns to a local public good using Rothbart’s concept of virtual prices. Empirically, a stochastic cost function that includes own knowledge capital stock as well as spillover capital stock variables is estimated. Stochastic spatial dependency among states generated by knowledge spillovers is used to define the ‘appropriate’ jurisdictions. We estimate an average own-state rate of 17% and a social rate of 29% that compare well to the 9 and 12% average returns of the S&P500 and NASDAQ composite indexes during the same period.     

Short-term R&D bias,competition on cost rather than innovation,and time to market

Mounting evidence indicates that capital markets often apply short-term pressure on firms to gain short-term results by focusing primarily on reported financial performance. As a result of short termism, it has been argued that companies are likely to cut expenditure on R&D which might otherwise improve longer-term performance. As there is a growing consensus that R&D is critically important to both organizational and national performance, short termism may have significant detrimental organizational consequences. One implication arising from a short-term R&D bias, and examined in this paper, is its effect on market time reduction. Arguments are examined that suggest a dominant R&D strategy is to reduce product time to market. Concerns have been expressed, however, that such a strategy is applicable in specific circumstances only. A review of the literature suggests that analyst and shareholder bias against high-risk, long-term research in favor of lower-risk, short-term product R&D influences organizations to reduce the time it takes to get a product to market when the emphasis in the marketplace is on cost competition rather than product innovation. The findings of the study suggest that when the emphasis on competition on cost rather than innovation is low, short-term R&D bias does not affect market time. In contrast, when the emphasis on competition on cost rather than innovation is high, the results indicate that short-term R&D bias positively influences market time reduction. The study concludes with suggestions for further research.     

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

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

Firms' human capital,R&D and performance: a study on French and Swedish firms

This paper studies the effects of human and technological capital on productivity in a sample of large French and Swedish firms. While the role of technological capital as measured by R&D has been intensively investigated, almost no work has been done on the role of human capital as measured by firm-sponsored training and even less its interaction with technological capital. The level of intangible capital may also have a lasting effect on productivity growth, as emphasised by some endogenous growth models in a macroeconomic setting.The study uses data from two panels of large French and Swedish firms for the same period (1987–1993). It constructs measures of a firm's human capital stock, based on their past and present training expenditures. The results confirm that firm-sponsored training and R&D are significant inputs in the two countries, although to a different extent, and have high returns. However, except for managers and engineers in France, we do not find evidence of positive interactions between these two types of capital. Finally, growth effects at the firm level do not appear.     

How to optimize the allocation of research resources? An empirical study based on output and substitution elasticities of universities in Chinese provincial level

Although significant progress has been made in China's basic research in recent years, there remains a wide gap between research in China and that from developed countries. How to optimize the allocative efficiency of research resources is of great importance for increasing research output. In this paper, using the fixed effect stochastic frontier model based on the translog production function, we estimate output and substitution elasticities of research and development (R&D) inputs at universities in China's provincial level during 2009–2016. We find that the R&D technical efficiency of China's universities, after a rapid growth, has tended to become relatively stable. Improvements of internationalization degree and exogenous R&D capabilities are conducive to promoting R&D technical efficiency, whereas expenditures from government grants inhibit the promotion of R&D technical efficiency; the effects of R&D capital deepening and internet penetration are not evident. The output elasticity of R&D capital is much higher than that of R&D personnel, suggesting that R&D capital is the main driving force of research output. The substitution elasticity between R&D capital and personnel has experienced a change from substitution to complementary since 2014. To realize sustained growth of research output, we should increase R&D input with positive output elasticity or reduce R&D input with negative output elasticity, making the necessary trade-offs according to the substitution relationship between the two R&D inputs.     

An approach to the R&D value based upon real option method

This paper aims to build up feasible models based upon the real option method (ROM) to assess R&D. In this paper we built eight models integrating with three conditions to assimilate the real situation an R&D project may encounter. We utilized both numerical and statistical illustration based upon an empirical case to exhibit the correctness of our models. We diverged our discussion into either expense or capital viewpoint to react with current accounting debate. The results shed us the light: our models in both expense and capital viewpoint can correctly asses R&D; the selected conditions play essential roles to influence the correctness of our models.     

The dark side of stock market liberalization: Perspectives from corporate R&D activities in China

This study explores how stock market liberalization impacts corporate research and development (R&D) activities and examines the impact channels. Based on a quasi-natural experiment on the Shanghai-Hong Kong Stock Connect, we report a significantly negative relationship between stock market liberalization and R&D activities in non-state-owned enterprises (non-SOEs) using a difference-in-difference approach. For one thing, a decrease in analyst coverage will reduce the supervision of R&D activities; for another, the alleviation of financing constraints will heighten corporate financialization, resulting in a greater crowding-out effect on R&D activities. Furthermore, R&D activities in SOEs, which are guided by government policies, are not significantly affected by stock market liberalization.     

Trade and product innovations as sources for productivity increases: an empirical analysis

Increases in total factor productivity (TFP) are commonly associated with technological innovations measured by the stock of R&D. Empirical evidence seems to corroborate this relationship. However, in trading countries like The Netherlands, productivity increases, even in industry, can also be the result of innovations in the way transactions are managed. These innovations reduce transaction costs and exploit the welfare gains from (further) international division of labour. Such innovations are only partly included in R&D data. Consequently there is not much attention for these ‘trade innovations’—as we label them—in policy. In an empirical analysis this paper compares the influence of trade innovations with the influence of the stock of R&D on TFP in The Netherlands. The regression results show that in this country trade innovations are as important for TFP as technological innovations which directly affect the efficiency of production, which we label ‘product innovations’.      

R&D, Investment, and Industry Dynamics

We present a model of industry evolution where the dynamics are driven by a process of endogenous innovations followed by subsequent embodiments in physical capital. Traditionally, the only distinction between R&D and physical investment was one of labeling: the first process accumulates an intangible stock, knowledge, while the second accumulates physical capital. Both stocks affect output in a symmetric fashion. We argue that the story is not that simple, and that there is more to it than differences in the object of accumulation. Our model stresses the causal relationship between past R&D expenditures and current investments in machinery and equipment. This causality pattern, which is supported by the data, also explains the observed higher volatility of physical investment relative to that of R&D expenditures.     

Innovation dynamics and fiscal policy: Implications for growth,asset prices,and welfare

We study the equilibrium implications of different fiscal policies on macroeconomic quantities and welfare by utilizing an endogenous growth model that matches asset pricing data well. The fiscal instruments of interest are (i) subsidies to R&D expenditure, consumption and capital investment, and (ii) cuts in labor and corporate tax rates. Our equilibrium analysis provides new insights on the interplay of innovation dynamics and fiscal policy. Importantly, we find growth and welfare to be inversely related when changing R&D subsidies. However, this depends on how well the model reproduces asset pricing dynamics. Moreover, only subsidies to capital investments and cuts in the corporate tax rate have the potential to increase both growth and welfare.     

Do investments in intangible customer assets affect firm value?

This paper develops a simple model of investment by service firms in intangible customer assets, and tests whether the model identifies some critical drivers of firms’ stock returns. Similar to firms with significant research and development (R&D) expenditures, we argue that firms in fast-growing service industries with few tangible assets can increase firm value by investing in customer acquisition and service (A&S) expenditure. Using a unique hand-collected data set, we show that per-customer changes in firms’ revenues, customer acquisition costs, and customer service costs help to explain their abnormal stock returns.     

R&D and aggregate fluctuations

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

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

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

Carpooling and driver responses to fuel price changes: Evidence from traffic flows in Los Angeles

We examine carpooling and driver responses to fuel price changes. Using a simple theoretical model, we show that traffic flows in mainline lanes unambiguously decrease when fuel prices increase, and this effect is stronger when the presence of a carpool lane provides a substitute to driving alone. In contrast, in carpool (HOV) lanes flow can either increase or decrease. These predictions are tested using 8 years of traffic flow data for 1700 locations in Los Angeles. In our preferred specification, the mean elasticity of flow with respect to fuel price is 0.136 for HOV lanes. For a 10% increase in fuel price this implies 10 additional carpools per hour, $8.8 million per year in additional congestion costs for carpoolers and $11.3 million lower costs for mainline drivers. For mainline lanes, flow elasticities are −0.083 and −0.050 for highways with and without an HOV lane. These estimates imply that the mean highway with an HOV lane experiences a 30% larger decrease in hourly flow compared to the mean highway without an HOV lane. Flows in HOV lanes show an immediate decrease following a price increase but respond positively to price increases over time, which suggests time is an important input to carpool formation.