The relationship between R&D,innovation and productivity in emerging economies: CDM model and alternatives

CDM (Crépon, Duguet and Mairesse, 1988) is a workhorse model in the economics of innovation, which explains productivity in a three-stage procedure driven initially by R&D and leads to patents and then to productivity improvements. Based on the logic of this model, an increasing number of papers applies it to emerging economies but modifies the original model without being explicit about the nature and implications of this modification. We argue in this paper that, in its original form, CDM does not capture stylized facts of the determinants of productivity in emerging economies and that we need alternative models. Accordingly, we are critical of papers that try to maintain the validity of the model but actually change it. For that purpose, we test the original CDM model and its two alternatives: investment and production capability–driven models. Our research is based on a large sample of firms in Central and Eastern Europe, former Soviet republics and Turkey, and we show that the alternative models are much closer to the stylized facts of innovation activities and technology upgrading in these and other emerging economies. Our conclusions have important policy implications, which we discuss.     

THEORY AND EVIDENCE IN PSYCHOLOGY AND ECONOMICS ABOUT MOTIVATION CROWDING OUT: A POSSIBLE CONVERGENCE?

The empirical relevance of motivation crowding out is a controversial issue in economics and psychology. As already pointed out by Frey and Jegen ( 2001 ), this is partly due to the historical development of two distinct and parallel strands of literature that stem from different theoretical traditions, have radically different tenets and therefore, are difficult to reconcile. In this survey, we go back to the details of the debates that took place independently among psychologists and economists, and sketch an integrative interdisciplinary approach likely to favor a more fruitful collaboration between economics and psychology. From this perspective, experimental economics (both field and laboratory) is viewed as a major research field shedding new light on the conditions of relevance of motivation crowding out.     

发展金融理论:一个文献综述

伴随着经济金融化和金融实践的蓬勃发展,发展金融理论在20世纪的最后几十年走上了经济学的舞台。作为一个新兴的学术领域,发展金融理论既继承了发展经济学以研究发展中国家为对象的优秀传统,又扩展和提升了金融发展理论的分析视角和研究内容。继麦金农和肖之后,发展金融理论的后期研究逐渐表现出"深"和"广"两大特征,并已经成为专门探讨发展中国家金融发展问题的基本理论框架和模型。本文沿着发展金融理论的萌芽、形成和发展这一演进顺序系统地梳理和评述该领域的主要文献,并提出亟需破解的两难命题。     

Parametric Value-at-Risk analysis: Evidence from stock indices

We evaluate the performance of several volatility models in estimating one-day-ahead Value-at-Risk (VaR) of seven stock market indices using a number of distributional assumptions. Because all returns series exhibit volatility clustering and long range memory, we examine GARCH-type models including fractionary integrated models under normal, Student-t and skewed Student-t distributions. Consistent with the idea that the accuracy of VaR estimates is sensitive to the adequacy of the volatility model used, we find that AR (1)-FIAPARCH (1,d,1) model, under a skewed Student-t distribution, outperforms all the models that we have considered including widely used ones such as GARCH (1,1) or HYGARCH (1,d,1). The superior performance of the skewed Student-t FIAPARCH model holds for all stock market indices, and for both long and short trading positions. Our findings can be explained by the fact that the skewed Student-t FIAPARCH model can jointly accounts for the salient features of financial time series: fat tails, asymmetry, volatility clustering and long memory. In the same vein, because it fails to account for most of these stylized facts, the RiskMetrics model provides the least accurate VaR estimation. Our results corroborate the calls for the use of more realistic assumptions in financial modeling.     

物流理论综述

由于各个国家或地区经济社会发展水平的不同,人们对物流存在着不同的认识。作者主要采用文献研究法,首先介绍了物流的多种定义,并给出了自己的观点;其次,近几十年来国内外学者对物流理论的研究视角相当广阔,观点繁多,但已形成了一定的共识,对以上物流理论进行梳理,指出了物流理论是经济学领域中的重要研究课题,在实践中存在着巨大的尚待挖掘的潜能。     

A re-examination of the “zero is enough” hypothesis in the emergence of financial stylized facts

In recent years, a growing literature has claimed that the market microstructure is sufficient to generate the so-called stylized facts without any reference to the behaviour of market players. Indeed, qualitative stylized-facts can be generated with zero-intelligence traders (ZITs) but we stress that they are without any quantitative predictive power. In this paper we show that in most of the cases, such qualitative stylized facts hide unrealistic price motions at the intraday level and ill-calibrated return processes as well. To generate realistic price motions and return series with adequate quantitative values is out-of-reach using pure ZIT populations. To do so, one must increasingly constrain agents?? choices to a point where it is hard to claim that their behaviour is completely random. In addition we show that even with highly constrained ZIT agents, one cannot reproduce real time series from these. Except in a few cases, first order moments of ZITs never equal real data ones. We therefore claim that stylized facts produced by means of ZIT agents are useless for financial engineering.     

经济学的定性分析与定量分析:争论与融合

定性分析和定量分析是经济学研究的两种基本手段。前者是对经济事物本质及其属性的分析;后者是对经济事物进行量的考察。学术界对两者存在较严重的分歧,以致形成不同学派的论战;文章就定量分析与定性分析的发展及其发展过程中的争论和融合进行研究,得出结论:经济学的科学性和人文性决定了经济学研究方法必须做到定性分析和定量分析相结合。     

WHAT'S TO KNOW ABOUT LABORATORY EXPERIMENTATION IN ECONOMICS?

Abstract Experimental economics has grown as a discipline from near non‐existence 50 years ago to a full‐fledged field within economics in the present. Much of experimental economics research involves experimental methods as a tool, applied to problems in other fields of economics. However, some of this research is inward looking, focusing on questions of the methodology of experimental economics. In this note, I briefly discuss two methodological issues in experimental economics that might benefit from meta‐analysis: the pool from which experimental participants are drawn (university undergraduate students versus other populations) and the scale of monetary incentives faced by participants (large, small or hypothetical).     

高校科研管理绩效评价中数据包络分析模型研究

目前在高校科研管理绩效评价研究中使用了数据包络分析,但现有模型与高校科研现状有一定差距,在学科差异、学校差异和指标选取方面存在一定不足。本研究提议引入加权DEA模型、交互基准群DEA模型、非期望产出DEA模型加以完善。     

山西省煤炭物流中铁路运输与公路运输协同发展评价

从系统的角度出发,分析山西省煤炭物流发展过程中铁路运输与公路运输的关系,运用改进的DEA方法,结合2005年到2009年实际数据进行实证研究,在计算煤炭铁路运输与公路运输两者之间协同效度与发展效度的基础上,综合评价了山西省煤炭物流发展过程中铁路运输与公路运输的协同发展程度,并提出相应的建议。     

Different dimensions of knowledge in cooperative R&D projects of university scientists

An increasing speed of new knowledge generation and a growing specialization of individuals in specific fields make cooperative R&D projects indispensable to stay abreast of the latest technological developments. However, studies targeting this field of research have almost exclusively focused on industrial cooperation projects, neglecting the importance of academic R&D collaboration.We attempt to address this research gap by investigating completed R&D cooperation projects of 376 German professors of the chemical and biological sciences. Based on their evaluation, we can distinguish between successful and less successful projects mainly involving explicit or tacit knowledge. We further characterize these groups by identifying significant group differences regarding trust, the interdependency between partners, the frequency of communication and the closeness of partners. Overall, our study presents new empirical evidence that the codification of knowledge plays an important role for the success of cooperative R&D projects.     

System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach

In areas from medicine to climate change to economics, we are faced with huge challenges and a need for accurate forecasts, yet our ability to predict the future has been found wanting. The basic problem is that complex systems such as the atmosphere or the economy can not be reduced to simple mathematical laws and modeled accordingly. The equations in numerical models are therefore only approximations to reality, and are often highly sensitive to external influences and small changes in parameterisation — they can be made to fit past data, but are less good at prediction. Since decisions are usually based on our best models of the future, how can we proceed? This paper draws a comparison between two apparently different fields: biology and economics. In biology, drug development is a highly inefficient and expensive process, which in the past has relied heavily on trial and error. Institutions such as pharmaceutical companies and universities are now radically changing their approach and adopting techniques from the new field of systems biology to integrate information from disparate sources and improve the development process. A similar revolution is required in economics if models are to reflect the nature of human economic activity and provide useful tools for policy makers. We outline the main foundations for a theory of systems economics.     

The Low‐Quality Advantage in Vertical Product Differentiation

By assuming a triangular distribution of consumers' willingness to pay for quality, this paper makes use of the stylized fact that low‐income households are more numerous than high‐income households, and thus, income distributions are right‐skewed. Accordingly, we present a straightforward two‐firm, two‐stage vertical product differentiation model with quality‐dependent marginal production costs, where the firm offering the low‐quality product has the larger market share and profit than the top‐quality competitor. This can be termed low‐quality advantage and may explain the success of large retailers serving the masses by offering low‐quality products. Copyright © 2016 John Wiley & Sons, Ltd.     

Epistemology of data envelopment analysis and comparison with other fields of OR/MS for relevance to applications

Periodically, professionals in a given field must reflect and assess where the field has been, where it is heading, and what if anything, should be done to change that field's course. This article discusses statistical trends within the data envelopment analysis (DEA) literature. The number of articles published per year in refereed journals over the entire lifespan of the field, authorship and publishing outlets-of-choice statistics are used to indicate DEA's vitality, relevance, diffusion to other disciplines/professions and its worldwide acceptance. Lastly, based on published meta reviews, comparisons are made with other OR/MS sub-disciplines.     

Exploring the operating efficiency of Technology Development Programs by an intellectual capital perspective—A case study of Taiwan

Government supported technological research and development can help the private sector to compete globally. A more accurate evaluation system considering multi-factor performance is highly desired. This study offers an alternative perspective and characterization of the performance of Technology Development Programs (TDPs) via a two-stage process that emphasizes research and development (R&D) and technology diffusion. This study shall employ a sequential data envelopment analysis (DEA) with a non-parametric statistical analysis to analyze differences in intellectual capital variables among various TDPs. The results reveal that R&D performance is better than technology diffusion performance for the TDPs. In addition, the “Mechanical, Mechatronic, and Transportation field” is more efficient than the other fields in both R&D and technology diffusion performance models. The findings of this study point to the importance of intellectual capital in achieving high levels of TDP efficiency. The potential applications and strengths of DEA and intellectual capital in assessing the performance of TDP are also highlighted.     

Productivity dispersion: facts,theory, and implications

This paper discusses the stylized facts, the theory, and the remaining problems of productivity dispersion, which is essentially related to the concept of equilibrium in the neoclassical theory. Empirical study of data relating to Japanese firms shows that they all obey the Pareto law, and also that the Pareto index decreases with the level of aggregation. In order to explain these two stylized facts we propose a theoretical framework built on the basic principle of statistical physics and on the concept of superstatistics, an approach that accommodates fluctuations of aggregate demand. We show that the allocation of production factors depends crucially on the level of aggregate demand, and that the higher the level of aggregate demand, the closer the economy is to the frontier of the production possibility set.     

Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA

Since the original Data Envelopment Analysis (DEA) study by Charnes et al. [Measuring the efficiency of decision-making units. European Journal of Operational Research 1978;2(6):429–44], there has been rapid and continuous growth in the field. As a result, a considerable amount of published research has appeared, with a significant portion focused on DEA applications of efficiency and productivity in both public and private sector activities. While several bibliographic collections have been reported, a comprehensive listing and analysis of DEA research covering its first 30 years of history is not available.This paper thus presents an extensive, if not nearly complete, listing of DEA research covering theoretical developments as well as “real-world” applications from inception to the year 2007.A listing of the most utilized/relevant journals, a keyword analysis, and selected statistics are presented.     

Transdisciplinary Research in Sustainable Operations – An Application to Closed‐Loop Supply Chains

This contribution provides implications for academic research and practitioners, as it identifies the lack, necessity and major benefits of transdisciplinary research and the collaboration of academics and industry in order to fulfill the goals of a sustainable supply chain. Closed‐loop supply chain management is a major contributor to implementing sustainable operations. An essential prerequisite for successful realization is the expertise and cooperation of representatives from engineering, management and natural sciences as well as practice. We identify a need for transdisciplinary collaboration within two steps. First, a literature review points out that various research disciplines as well as practice mostly operate in isolation. Second, we develop a framework that highlights the benefits of collaboration between these research areas. This paper provides an overview to better understand current trends in this complex field, which is a rich area for research that is still in its infancy. Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment     

A link between random coefficient autoregressive models and some agent based models

An agent based model (ABM), where each agent makes decisions by using the sum of two signals, is proposed. The first is related to the fundamental information while the second comes from trader’s idiosyncratic noise. This model entails the switching between two groups called fundamentalist and noise traders. Additionally, if the price impact function is log-linear, then the dynamic of log asset prices belongs to the class of random coefficient autoregressive RCA(p) models, which are known to share important stylized facts of financial prices.