Transitional dynamics in an R&D-based growth model with natural resources

In this paper, we prove the existence and uniqueness of the optimal path for a resource endowed economy with R&D. This path converges to an optimal steady state, which is a saddle point, for each type of resources (renewable or non-renewable). In this steady state, a finite size resource sector coexists with other continuously growing sectors. In comparison, the corresponding decentralized equilibrium is suboptimal and there is either over- or under-investment in R&D from the social planner’s perspective. At optimum, positive long-run growth will be sustained regardless type of resources used.     

混合所有制改革背景下政府最优减排研发补贴政策研究

通过构建两阶段异质产品减排博弈模型,文章研究了混合所有制改革背景下最优的企业减排研发投资及研发补贴政策,并进一步讨论了最优减排研发补贴政策下政府实施国企混合所有制改革的环境和经济效果。结论表明：政府应主动实施减排研发补贴政策,最优减排研发补贴受技术溢出率、产品差异程度以及混合所有制改革程度的影响。当减排研发效率较低时,随着技术溢出率增大,最优的减排研发补贴水平不断提高,当减排研发效率较高时,随着技术溢出率增大,最优的减排研发补贴水平不断下降;随着产品差异化程度提高,最优减排研发补贴水平不断提高;混合所有制改革程度加深将使得最优减排研发补贴水平下降。最优减排研发补贴政策下,政府实施国企混合所有制改革能够降低整个行业的污染排放、提高行业的利润和社会福利水平,从而能够取得经济和环境的双赢。最后,结合相关结论,本文给出了混合所有制改革背景下减排研发补贴政策设计的相关建议,为政府决策提供一定参考。     

含公共开支的两部门内生经济增长模型

本文研究了一个含公共开支的两部门的内生经济增长模型 ,其生产函数具有最一般的形式 .用于两部分的三要素—物质资本 ,人力资本 ,有效劳动的份额正相关 ,产出用于公共开支的份额与用于生产部门的三要素的份额负相关 ,经济增长极大地依赖于生产弹性 .并给出均衡值为正的条件和经济系统沿二维稳定流形收敛于稳定点的条件     

OPTIMAL R&D FOR NONRENEWABLE RESOURCES: THE CASE OF COST REDUCING TECHNOLOGY

A model is developed to determine optimal R&D spending and completion time when R&D results in lower extraction costs of a nonrenewable resource deposit. Examples of R&D projects for which the model is designed are in-situ leaching for mining and carbon dioxide injection in petroleum. The model is a combined R&D/nonrenewable resource model (CM). Results from the CM are compared to simulations of an R&D model which ignores the nonrenewable resource. The comparison demonstrates the importance of including resource parameters in the R&D spending model. The CM extends the literature by considering R&D spending and exhaustible natural resource production simultaneously. It demonstrates the importance of including the resource deposit when R&D affects the deposit. This is important because more accurate models of R&D will increase the profitability of the R&D projects.     

Optimal Dynamics of Innovation in Models of Economic Growth

A nonlinear model of economic growth which involves production, technology stock, and their rates as the main variables is considered. Two trends (growth and decline) in the interaction between the production and R&D investment are examined in the balanced dynamics. The optimal control problem of R&D investment is studied for the balanced dynamics and the utility function with the discounted consumption. The Pontryagin optimality principle is applied for designing the optimal nonlinear dynamics. An existence and uniqueness result is proved for an equilibrium of the saddle type and the convergence property of the optimal trajectories is shown. Quasioptimal feedbacks of the rational type for balancing the dynamical system are proposed. The growth properties of the production rate, R&D, and technology intensities are examined on the generated trajectories.     

一般Rebelo增长模型的动态分析

在本文中，我们考虑一个一般Rebelo增长模型：虽然在这一般模型中要求均衡增长轨道与均衡值是更困难的，但我们通过精巧的计算和动态分析，引出了唯一可行轨道及均衡值，且分析了参数对它的影响，当时间偏好率（折现因子增大时，分配在物资生产部门的物资资本与人力资本的比重会增大。而物资资本，人力资本及总生产量的增长率都会相应减少。     

TO LEARN OR TO CHANGE: OPTIMAL R&D INVESTMENTS UNDER UNCERTAINTY IN THE CASE OF CLIMATE CHANGE

When studying R&D investments in technologies that address potential damage from climate change (termed as “research to change” or RTC), current literature overlooks the effects of purchased learning (i.e., learn through scientific research, termed as “research to learn” or RTL) about climate change. We investigate interactions between optimal R&D investments in RTC and RTL under uncertainty in climate change and research outcomes, while accounting for the positive impact that successful RTL may have on RTC outcome. We find that simultaneously investing in both RTL and RTC may be optimal when the probability that climate change imposes a specific level of damage is either moderate or very high and when RTL cost is relatively low. Whenever RTL and RTC are conducted simultaneously, then they substitute. However, when it is not optimal to conduct RTC and RTL simultaneously, then an increase in RTC cost decreases, at least weakly, RTL investment (i.e., RTL and RTC complement). When the probability that climate change imposes damage increases, then the optimal RTL investment may first decrease and then increase. Moreover, we identify conditions under which either the precautionary principle or the learn‐then‐act principle should be followed regarding R&D investments.     

合同能源管理项目中的节能补贴分配问题研究

政府节能补贴是有效推进合同能源管理项目发展的一个关键要素。围绕合同能源管理项目,以优化资源配置为目的,通过构建“委托-代理”模型研究了项目中的节能补贴分配问题。研究发现:①当仅给予项目中的用能方或节能服务公司中任何一方节能补贴时,项目最优节能量主要取决于节能补贴标准;②当节能补贴由项目双方共享时,项目最优节能量不但受节能补贴标准影响,还受项目双方节能补贴讨价还价能力影响;③当节能补贴全部给予节能服务公司时,项目可实现最优节能量。④当节能补贴全部给予项目中的任何一方时,获补贴方的节能收益达到最优。     

Impact of Technology Assimilation on Investment Policy: Dynamic Optimization and Econometric Identification

The paper introduces a dynamic model of optimization of R&D intensity under the effect of technology assimilation. The model involves R&D investments, technology stock, production, and technology productivity as main variables. The model characterizes the “growth” and “decline” trends that describe the interaction between R&D investments and transformation process of production factors. The technology stock is constructed as a function of indigenous and exogenous technology stocks and their growth rates. The research focuses on the issue of a reasonable balance between the indigenous technology stock and assimilated technology flow. Econometric linearization of the technology assimilation effect is used to construct a reasonable optimal control model. The existence of the value function for the problem of the optimal economic growth on the infinite horizon is proved and the basic features of the value function are outlined. The property of strong invariance for the main proportions of the model such as technology productivity and R&D intensity is proved. The model is calibrated on the aggregate data of the Japanese automotive industry. The research was sponsored by the SIMOT Program of the Japanese Ministry of Education, Science and Technology. The second author was supported by the Russian Fund for Basic Research, Grants 05-01-00601, 05-01-08034, by the Russian Fund for Humanities, Grant RFH 05-02-02118a, and by the Program for the Sponsorship of Leading Scientific Schools, Grant NSCH-791.2003.1.     

A Differential R&D Game: Implications for Knowledge-Based Growth Models

This paper compares the outcomes of strategic and nonstrategic research and development (R&D). Firms undertake cost-reducing R&D in an environment where benefits accrue from their rivals' R&D via a common pool of knowledge. We demonstrate that multiple suboptimal equilibria exist; under these conditions, growth models which do not consider strategic interactions will overestimate or underestimate the growth rate.     

Real R&;D options with time-to-learn and learning-by-doing

We model R&D efforts to enhance the value of a product or technology before final development. Such efforts may be directed towards improving quality, adding new features, or adopting technological innovations. They are implemented as optional, costly and interacting control actions expected to enhance value but with uncertain outcome. We examine the interesting issues of the optimal timing of R&D, the impact of lags in the realization of the R&D outcome, and the choice between accelerated versus staged (sequential) R&D. These issues are also especially interesting since the history of decisions affects future decisions and the distributions of asset prices and induces path-dependency. We show that the existence of optional R&D efforts enhances the investment option value significantly. The impact of a dividend-like payout rate or of project volatility on optimal R&D decisions may be different with R&D timing flexibility than without. The attractiveness of sequential strategies is enhanced in the presence of learning-by-doing and decreasing marginal reversibility of capital effects.     

Urban public pension, replacement rates and population growth rate in China

This paper uses an overlapping generations model to investigate the urban public pension in China. It examines the effects of the replacement rates and population growth rate on the capital–labor ratio, pension benefits, consumption and utility, and finds the optimal replacement rate. It is shown that raising the individual account benefit replacement rate only induces the increase in the individual account benefits. Raising the social pool benefit replacement rate induces the increase in the social pool benefits and retirement-period consumption, while the decrease in the capital–labor ratio, individual account benefits, working-period consumption and utility. The fall in the population growth rate leads to the increase in the capital–labor ratio, social pool benefits, individual account benefits, working-period consumption and utility, and leads to a decrease in the retirement-period consumption. The optimal social pool benefit replacement rate depends on the individual discount factor, social discount factor, capital share of income and population growth rate, and it decreases in the case of falling population growth rates. It will do more good than harm to raise the individual account benefit replacement rate, reduce the social pool benefit replacement rate and strictly implement China’s population policy.     

Strategic optimization in R&D investment

We use d'Aspremont and Jacquemin's strategic optimal R&D investment in a duopoly Cournot competition model to construct myopic optimal discrete and continuous R&D dynamics. We show that for some high initial production costs, the success or failure of a firm is very sensitive to small variations in its initial R&D investment strategies.     

基于吸收能力的企业合作研发的动态模型

竞争还是合作,是企业研发投资时所面临的选择,本文应用最优控制论建立了一个考虑吸收能力的企业合作研发的动态模型,分析了双寡头垄断企业在竞争和合作两种情况下的均衡研发投资,并与D＇aspremont ＆ J＇aquemin的静态模型的结果进行了比较.     

Climate change and optimal energy technology R&D policy

Public policy response to global climate change presents a classic problem of decision making under uncertainty. Theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy, especially technology policy. However, theory also shows that the specific impacts of uncertainty are ambiguous. In this paper, we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development (R&D) policy in response to global climate change. We find that, given a budget constraint, the composition of the optimal R&D portfolio is highly diversified and robust to risk in climate damages. The overall optimal investment into technical change, however, does depend (in a non-monotonic way) on the risk in climate damages. Finally, we show that in order to properly value R&D, abatement must be included as a recourse decision.     

Comparative evaluation of performance of national R&D programs with heterogeneous objectives: A DEA approach

The strategic importance of performance evaluation of national R&D programs is highlighted as the resource allocation draws more attention in R&D policy agenda. Due to the heterogeneity of national R&D programs’ objectives, however, it is intractably difficult to relatively evaluate multiple programs and, consequently, few studies have been conducted on the performance comparison of the R&D programs. This study measures and compares the performance of national R&D programs using data envelopment analysis (DEA). Since DEA allows each DMU to choose the optimal weights of inputs and outputs which maximize its efficiency, it can mirror R&D programs’ unique characteristics by assigning relatively high weights to the variables in which each program has strength. Every project in every R&D program is evaluated together based on the DEA model for comparison of efficiency among different systems. Kruskal–Wallis test with a post hoc Mann–Whitney U test is then run to compare performance of R&D programs. Two alternative approaches to incorporating the importance of variables, the AR model and output integration, are also introduced. The results are expected to provide policy implications for effectively formulating and implementing national R&D programs.     

MODELING DYNAMICS OF FISHERY HARVEST REALLOCATIONS: AN ANALYSIS OF THE NORTH CAROLINA RED DRUM FISHERY

The interactive dynamics of red drum stock growth and two-sector harvest are modeled as a system of differential equations. The dynamic effects of commercial harvest restrictions on stock growth and recreational catch and effort are simulated. The simulation shows that a reallocation of the North Carolina red drum stock from the commercial sector to the recreational sector will not only increase benefits to the recreational sector, but will also be stock enhancing. Stock growth in the years immediately following the reallocation is quite rapid, with complete transition to the final steady-state taking between 23 and 46 years. Parameters important to the behavior of the system are identified through sensitivity analysis, and are used to establish critical areas for further research.     

A fuzzy approach to R&D project portfolio selection

A major advance in the development of project selection tools came with the application of options reasoning in the field of Research and Development (R&D). The options approach to project evaluation seeks to correct the deficiencies of traditional methods of valuation through the recognition that managerial flexibility can bring significant value to projects. Our main concern is how to deal with non-statistical imprecision we encounter when judging or estimating future cash flows. In this paper, we develop a methodology for valuing options on R&D projects, when future cash flows are estimated by trapezoidal fuzzy numbers. In particular, we present a fuzzy mixed integer programming model for the R&D optimal portfolio selection problem, and discuss how our methodology can be used to build decision support tools for optimal R&D project selection in a corporate environment.     

Complex joint R&D projects: From empirical evidence to managerial implications

At present, the role of joint R&D projects becomes fundamental for understanding the process of innovation. An extensive bibliography exists on the study of the organizations; however, the networks for the development of joint R&D projects themselves as a new form of organization are still a growing field of study. The aim of this article is to provide empirical evidence on joint R&D projects management. To approach this question the starting point will be that joint R&D projects are complex phenomena whose complexity derives from the heterogeneity of agents to take part, the technological process developed and from the organizational form that supports R&D projects. The empirical evidence through European R&D Programs shows the multidimensional character of the joint R&D project concept and allows analyze their different subsystems that is, technological, structural, and governance subsystem. This study not only offers a conceptual framework to help manage these projects, but also discusses practical guidelines that may be useful for its running and management. © 2009 Wiley Periodicals, Inc. Complexity, 2009     

Technological change,population dynamics,and natural resource depletion

In this paper, we integrate fertility and educational choices into a scale-invariant model of directed technological change with non-renewable natural resources, in order to reveal the interaction between population dynamics, technological change, and natural resource depletion. In line with empirical regularities, skill-biased technological change induces a decline in population growth and a transitory increase in the depletion rate of natural resources. In the long-run, the depletion rate also declines in the skill intensity. A decline in population growth is harmful for long-run productivity growth, if R&D is subject to diminishing technological opportunities. The effectiveness of economic policies aimed at sustained economic growth thus hinges on its impact on long-run population growth given the sign of intertemporal spillovers in R&D with respect to existing technological knowledge. We demonstrate that an increase in relative research productivities or an education subsidy enhances long-run growth, if R&D is subject to diminishing technological opportunities, while an increase in the teacher–student ratio is preferable in terms of positive intertemporal knowledge spillovers.