Estimation of the most influential science and technology factors for economic growth forecasting by soft computing technique

Economic growth may be developed on the basis on combination of different factors. In this investigation was analyzed the economic growth forecasting based on the different factors. The main goal was to analyze the influence of science and technology factors on the economic growth. Gross domestic product (GDP) was used as economic growth indicator. The method of adaptive neuro fuzzy inference system (ANFIS) was applied to the data in order to select the most influential factors for the GDP growth rate forecasting. Ten inputs are considered: research and development (R&D) expenditure in GDP, scientific and technical journal articles, patent applications for nonresidents, patent applications for residents, trademark applications for nonresidents, trademark applications for residents, total trademark applications, researchers in R&D, technicians in R&D and high-technology exports. The ANFIS process for variable selection was also implemented in order to detect the predominant factors affecting the forecasting of GDP growth rate.     

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.     

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.     

Economic conditions for innovation: Private vs. public sector

The Hicks induced innovation hypothesis states that a price increase of a production factor is a spur to invention. We propose an alternative hypothesis restating that a spur to invention requires not only an increase of one factor but also a decrease of at least one other factor to offset the companies’ cost. We illustrate the need for our alternative hypothesis in a historical example of the industrial revolution in the United Kingdom. Furthermore, we econometrically evaluate both hypotheses in a case study of research and development (R&D) in 29 OECD countries from 2003 to 2017. Specifically, we investigate the dependence of investments to R&D on the economic environment represented by average wages and oil prices using panel regression. We find that our alternative hypothesis is supported for R&D funded and/or performed by business enterprises while the original Hicks hypothesis holds for R&D funded by the government and R&D performed by universities. Our results reflect that the business sector is significantly influenced by market conditions, unlike the government and higher education sectors.     

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.     

R&D performance assessment of industrial enterprises in China: A two-stage DEA approach

With the growing expenditure on the R&D activities of industrial enterprises above designated size (IEDSs) in China, it is important to evaluate the R&D efficiency of the Chinese IEDSs. However, few studies about R&D efficiency measurement of Chinese IEDSs have considered the internal structure of the R&D production process. To fill this gap, this paper investigates the R&D performance of IEDSs of 30 sample provinces on China's mainland from 2009 to 2014, based on a two-stage data envelopment analysis (DEA) model. The major findings from the empirical results are shown as follows: (i) serious imbalance exists in the R&D resources among Chinese IEDSs of 30 provinces; (ii) there is a decline in the average overall efficiencies after 2012; (iii) there are great differences regarding the performances of R&D activities among the Chinese IEDSs of 30 provinces; (iv) high attention to the R&D activities or strong scientific research atmosphere may promote the R&D efficiency of Chinese IEDSs; and (v) the IEDSs with the relatively high profitability or high government support in terms of R&D activities have relatively poor performance. Based on these findings, several policy suggestions are proposed for the R&D activities of Chinese IEDSs.     

Environmental regulations in private and mixed duopolies: Taxes on emissions versus green R&D subsidies

In this article, we compare two kinds of environmental regulations—emissions taxes and green R&D subsidies—in private and mixed-duopoly markets in the presence of R&D spillovers. We show that a green R&D subsidy is better (worse) than an emissions tax when the green R&D is efficient (inefficient), irrespective of R&D spillovers, whereas the existence of a publicly owned firm encourages the government to adopt a subsidy policy. We also show that the optimal policy choice depends on R&D efficiency and spillovers. In particular, when green R&D is inefficient and the spillover rate is low (high), the government should choose an emissions tax and (not) privatize the state-owned firm. When green R&D is efficient, however, an R&D subsidy is better, but a privatization policy is not desirable for society, irrespective of spillovers.     

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.     

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.     

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.     

An investigation into international assignment directions of R&D MNE employees: evidence from Greece

In this study, we explore the effects of the roles of research and development (R&D) laboratories, roles of subsidiaries and level of technological intensity of the sector in which multinational enterprise (MNE) subsidiaries operate on international assignment directions of R&D employees. International assignments are an underinvestigated issue in the international human resource management literature despite its significant research and managerial importance. In particular, to the best of our knowledge, no prior research on international assignments of R&D employees has been undertaken and so the current study aims at filling this void in the literature. Based on a large quantitative research on MNE subsidiaries operating in Greece, the findings suggest that variables of the aforementioned categories of factors influence different international assignment directions, with roles of the R&D subsidiary exerting the most crucial effect. Researchers may examine the unexplored issue of R&D employee international assignments to a larger extent, while MNE management can particularly take into account the micro (laboratory) context of R&D international assignees when developing effective international human resource management programmes.     

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.     

From R&D to Productivity Growth: Do the Institutional Settings and the Source of Funds of R&D Matter?

This paper presents estimates of the long-term impact of various sources of knowledge (R&D performed by the business sector, the public sector and foreign firms) on multifactor productivity growth of 16 countries from 1980 to 1998. The main results show that the three sources of knowledge are significant determinants of long-term productivity growth. Further evidence suggests that several factors determine the extent to which each source of knowledge contributes to productivity growth. These factors are the absorptive capability, the origin of funding, the socioeconomic objectives of government support, and the type of public institutions that perform R&D.     

Adoption,diffusion, and public R&D

This paper studies the impact of public RD&D (Research, Development, and Demonstrations) on the market penetration of a new government-sponsored technology. First, the technology adoption behavior of a firm under uncertainty is reviewed. Secondly, the diffusion of the new technology in a competitive industry that benefits from learning-by-doing is analyzed. Numerical simulations are conducted to determine the effect that variations in government R&D policies have on the rate and level of market penetration. Productive R&D investments affect thelevel of diffusion and R&D demonstrations therate of diffusion.     

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.     

Stochastic Technical Change and Procyclical TFP The Case of Italian Agriculture

The paper questionsthe use of Total Factor Productivity (TFP) measures as a proxyfor the technological level in Italian agriculture. TFP growthreveals a cyclical behaviour and a short-run component due toshocks on both the demand and supply sides. In order to identifyreal long-run technological change, a Kalman filter procedureis applied to a stochastic process depicting the generation oftechnical change induced by R&D and Extension expenditure.The empirical evidence reveals that short-term shocks greatlyaffect the traditional measure of productivity. A better indicatorof technological progress can be obtained by estimating the long-runcomponent of productivity, which seems to be significantly inducedby R&D-Extension public expenditure.     

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.     

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.     

Technology ladders and R&D in dynamic Cournot markets

Motivated by dramatic and unpredictable technological advances in energy production (for instance drilling and extraction of shale oil), we extend Cournot models of competition to incorporate research and development (R&D) that can lead to (stochastic) drops in production costs. Our model combines features of patent racing with dynamic market structure, capturing the interplay between the immediate competition in terms of production rates and the long-term competition in R&D. The resulting Markov Nash equilibrium is found from a sequence of one-step static games arising between R&D successes, and several numerical examples and extensive analysis of the emerging comparative statics are presented. Analyzing the relationship between current market dominance and the level of R&D investments, we find that market leaders tend to invest more, which in some sense makes oligopoly dynamically unstable. We show that anticipated market transitions have long-term impact; for example the potential of future monopoly can spur R&D investment now, even if the firm is presently uncompetitive and not actively producing. We also show that, surprisingly, random innovations have an ambiguous effect on R&D. This feature, which is driven by the Cournot framework, contrasts with the common situation whereby uncertainty lowers innovation and delays R&D investments. Finally, we demonstrate that increased competition may actually increase efforts to innovate through higher desire to achieve dominance. This would match the anecdotal evidence that the threat of market entrants forces incumbents to maintain high R&D.     

U.S. productivity in agriculture and R&D

This paper examines the impact of R&D on multifactor productivity in the U.S. agricultural sector over the 1910–1990 period. We use the Bennet–Bowley indicator to measure agricultural productivity based on a multiple output-multiple input technology. We demonstrate the relationship between the price dependent Bennet–Bowley indicator and the Luenberger productivity indicator which is constructed from directional distance functions without requiring price information. These performance measures are dual to the profit function which arguably makes them especially useful in the agricultural setting. We employ time-series techniques to investigate the effect of R&D on the pattern of productivity growth. We find that we cannot reject the presence of a cointegrating relationship between the two series and that productivity growth in the U.S. agriculture responds positively to R&D expenditure with a lag of between four and ten periods.