Knowledge Spillovers,ICT and Productivity Growth

This paper looks at the channels through which intangible assets affect productivity growth. The econometric analysis exploits a new data set on intangible investment (INTAN‐Invest) in conjunction with EUKLEMS productivity estimates for 10 EU member states from 1998 to 2007. We find that (a) the output elasticity of intangible capital depends upon ICT intensity, consistent with complementarities between ICT and intangible capital; (b) non‐R&D intangible capital has a higher estimated output elasticity than its factor share, as does (c) an index of labour composition. The last two findings are consistent with growth spillovers from investments in knowledge‐based/intangible capital and skills.     

Intangible investment in people and productivity

Organizational activity, information and communication technology work, and research and development (R&D) can be classified as work that creates intangible capital. We measure the returns to these three types of labor input by accounting for differences in their productivity compared with other labor inputs using Finnish firm-level data from 1998 to 2008. We apply a novel idea to use hiring as one proxy for productivity and demand shocks. We find that organizational workers increase total factor productivity and improve the profitability of high-productivity firms. R&D workers account for a large share of intangible capital; however, the returns to R&D are low. Investments in organizational competence are more likely to result in more rapid productivity growth. Firms with performance-related pay or domestically owned firms with extensive foreign activities have been among the highest performers with respect to the use of organizational work.     

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.     

Intangible capital in the pharmaceutical and chemical industry

We investigate whether measures of intangible capital based on advertising and R&D can explain variation in Tobin's Q ratio for the pharmaceutical and chemical industry. The study is motivated by prior literature studying this relation in other industries, recent literature investigating intangible capital in this industry, and the larger controversy about whether stock valuations have been high due to irrational investors or large investment in intangible capital. We find that our measures of intangible capital are statistically significant determinants of Q and explain 20% of the variation in our sample. When age and industry are incorporated into the model our explanatory power reaches 25%.     

The R&;D and productivity relationship of Korean listed firms

This study analyzes the relationship between R&D investment and the productivity of Korean R&D-engaged firms. An interdependent chain of equations including the propensity to invest, R&D investment and productivity are estimated in a multi-step procedure accounting for selectivity and simultaneity biases. Using Korean firm level panel data of listed firms from 1986 to 2002, we find four main empirical results. First, there is a two-way causal relationship between R&D investment and productivity for Korean listed firms. Second, Chaebol firms were associated with lower R&D growth as well as lower labor productivity growth in comparison to non-Chaebol firms. Third, there was a substantial reduction in growth rates both in R&D investment and labor productivity in 1997-1998, immediately following the Asian financial crisis. Fourth, considering the positive feedback effect from productivity growth to R&D growth, a decrease in R&D investment growth after the Asian financial crisis should have been harmful by further decreasing productivity growth.     

Investment in Fixed Capital Stock: Testing for the Impact of Sectoral and Systemic Uncertainty*

This paper applies current theory recognizing the irreversibility of investment, in order to test for the impact of uncertainty on investment expenditure for a middle income country. The contribution of the paper is unique in two respects. First, it employs dynamic heterogeneous panel estimation techniques not previously applied to investment functions. Secondly, it explicitly tests for the impact of both sectoral and systemic uncertainty on investment expenditure. We find that both sectoral (as measured by output volatility) and systemic uncertainty (as measured by political instability) have a negative impact on investment rates in a middle income country context. Liquidity constraints and growth in total factor productivity are found to have no impact on investment, while trade liberalization has the impact predicted by Heckscher‐Ohlin trade theory. Finally, we find complementarity effects between physical capital and skilled human capital, suggesting that South African educational policies may have hampered investment in physical capital as well as the growth performance of the economy. Policy implications emphasize the importance of lowering uncertainty for investors, and the need for sound human capital investment.     

管理层持股、研发投入与股权资本成本

企业研发投入具有风险性,会导致资本成本提高,研发融资负担加重,进而对企业研发活动的积极性产生负面影响。利用2007—2013年中国A股上市公司数据,对研发投入的资本成本效应和公司治理机制缓解研发投入资本成本效应的作用进行研究,结果显示：企业研发投入与股权资本成本之间显著正相关,研发投入的资本成本效应明显;提高高级管理者、董事会与监事会成员等管理层的持股比例有助于降低研发投入的资本成本效应。进一步研究发现,研发企业的信息披露程度对高级管理者持股降低研发投入资本成本效应具有替代作用;研发投入带来的收益率增加有助于抵消研发投入导致的股权资本成本提高。     

The contribution of research and innovation to productivity

This paper examines the impact of investment in research and innovation on Australian market sector productivity. While previous studies have largely focused on a narrow class of private sector intangible assets as a source of productivity gains, this paper shows that there is a broad range of other business sector intangible assets that can significantly affect productivity. Moreover, the paper pays special attention to the role played by public funding for research and innovation. The empirical results suggest that there are significant spillovers to productivity from public sector R&D spending on research agencies and higher education. No evidence is found for productivity spillovers from indirect public funding for the business enterprise sector, civil sector or defence R&D. These findings have implications for government innovation policy as they provide insights into possible productivity gains from government funding reallocations.     

The growth of information workers in the US economy, 1950–2000: the role of technological change,computerization, and structural change

Using data from the decennial US Censuses of 1950, 1960, 1970, 1980, 1990, and 2000, I construct matrices of employment by 267 occupations and 64 industries and then aggregate the occupations into four categories: (i) knowledge producers; (ii) data processors; (iii) service workers; and (iv) goods-processing workers. I find that information workers (the sum of the first two categories) increased from 37% of the workforce in 1950 to 59% in 2000. Then, using an input–output decomposition analysis, I find that the growth in information workers was driven not by a shift in tastes toward information-intensive goods and services (as measured by the composition of final demand) but rather by a roughly equal combination of the substitution of information workers for goods and service workers within the structure of production of industries and the unbalanced growth effect (from differential rates of industry productivity growth). Finally, on the basis of regression analysis, I find that R&D expenditures and computer investment are positively associated with the growth in knowledge workers but negatively associated with the growth of data workers.     

Spillovers,Linkages and Technical Change

Using US input–output data for the period 1958–87, I find strong evidence that industry total factor productivity (TFP) growth is significantly related to the TFP performance of the supplying sectors, with an elasticity of almost 60%. R&D intensity is also found to be a significant determinant of industry TFP growth, with an estimated return of about 10–13% and the return to embodied R&D is estimated at 43%. Direct productivity spillovers, from the technological progress made by supplying sectors, appear to be more important than spillovers from the R&D performed by suppliers. They also play a key role in explaining changes in manufacturing TFP growth over time. Changes in the contribution made by direct productivity spillovers to TFP growth account for almost half of the slowdown in TFP growth in manufacturing from 1958–67 to 1967–77, and for 20% of the TFP growth recovery in this sector from 1967–77 to 1977–87. Changes in R&D intensity and embodied R&D are relatively unimportant in explaining movements in manufacturing TFP growth over these three periods.     

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.     

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.     

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.     

Impact of R&D and Technology Diffusion on Productivity Growth: Empirical Evidence for 10 OECD Countries

This paper examines the empirical evidence on the impact of performed R&D and of R&D embodied in intermediate and capital goods on productivity performance in 10 major OECD countries over the last two decades. To quantify intersectoral and international technology flows, industry-level embodied R&D variables were constructed from an input–output (IO) R&D embodiment model. The productivity variables used are discrete Divisia growth indexes of total factor productivity (TFP), which were estimated from an IO growth accounting model. The results from pooled regressions indicate that the rates of return of the R&D variables were positively significant and increasing in the 1980s. In particular, embodied R&D is an important source for TFP growth in services, indicating very high social returns of the flows of capital-embodied technology into this sector. Moreover, the information and communi-cation technology (ICT) cluster of industries played a major role in the generation and cquisition of new technologies at the international level.     

R&D,Interindustry and International Technology Spillovers and the Total Factor Productivity Growth of Manufacturing Industries in Canada, 1974-1989

The paper presents new econometric evidence on the relationship between total factor productivity growth and the R&D expenditures of Canadian manufacturing industries in the presence of interindustry and international spillovers of technology. In contrast to studies that presume that international spillovers are incorporated in imports of intermediate and/or capital equipment goods, the present paper assumes that the principal channel of transmission of new technology is foreign direct investment. Three original proxies for international spillovers use information on patenting, the size and the origin of foreign ownership in the host country and the R&D expenditures in the country of origin. The results suggest that the nexus between industry's own R&D expenditures and the TFP growth is significant and positive, especially for the process-related R&D. Domestic interindustry spillovers of new technology have a larger effect on TFP than industry's own R&D expenditures. All three proxies for international technology spillovers are associated positively and significantly with TFP growth. However, international spillovers contribute to TFP growth less than domestic interindustry spillovers and less than own process-related R&D.     

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。     

Measuring and valuing intangible capital in the wireless communications industry

We investigate the measurement and valuation of intangible capital in the wireless telecommunications industry. Four specific sources of intangible capital are investigated: advertising, research and development (R&D), radio spectrum licenses, and measures of installed customer base. All four sources of intangible capital explain a statistically significant portion of the variation in Tobin’s q, but the variation explained by R&D is subsumed by that explained by licenses. Together, licenses and advertising explain over 60% of the variation in q, and licenses are the much more powerful predictor of the two. The industry average q exceeds ten, and it appears that the failure of financial accounting statements to reasonably value licenses plays a substantial role in causing these extraordinarily high q ratios.     

高新技术企业研发投入与内部资金相关性的实证分析

本文从理论与实地调研及国外实证研究等方面分析表明：高新技术企业研发投入与内部资金具有较强的相关性，但通过对我国2003年-2005年上市公司采用回归分析法检验却发现，二者之间相关性不显著，由此认为仅有研发强度等考核指标不能全面反映企业实际研发投入的相对水平，不利于推动、考核企业实际的研发投入，应增设企业研发投入与内部资金之间系列考核指标。     

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.