区域知识产权保护发展的空间格局及结构体系研究

以我国各省知识产权保护制度为研究对象，创新性地将探索性空间数据分析方法与社会网络分析方法相结合，基于地理邻近视角，验证了区域知识产权保护的空间相关性、空间集聚特征和空间溢出效应。同时，突破地理近邻效应的局限，解析区域知识产权保护的空间关联特征。结果表明：我国各省知识产权保护具有全局自相关性，相似地区间存在空间集聚效应，不同发展程度地区的空间关联性质不同；网络化后的区域知识产权保护各节点间联系紧密、网络结构稳定，并且可以确定核心行动者和边缘行动者角色；长三角、珠三角、环渤海等较发达地区与其它地区之间存在较多溢出关系。     

Permit markets,carbon prices and the creation of innovation clusters

Innovation clusters combining public and private effort to develop breakthrough technologies promise greater technological advances to slow down climate change. We use a multi-country model with an emission trading system to examine whether and how international climate policy can incentivize countries to create such innovation clusters. We find that a minimal carbon price is needed to attract applied research firms, but countries may nevertheless fail to invest in complementary research infrastructure. We construct a mechanism that leads to innovation clusters when emissions targets are set before uncertainty surrounding technological developments is resolved. It is a combination of low permit endowments for the country with the lowest costs to build the needed infrastructure, compensation for this country by profits from permit trade, and maximal possible permit endowments for the remaining countries. We outline how the EU-ETS can be further refined according to this mechanism.     

Accounting practice,fiscal decentralization and corruption

In prior studies, accounting and decentralization corruption solutions have so far been analysed in isolation. In this article, we connect these two strands of literature on corruption. Understanding this connection is important because weak financial accounting and reporting systems can inhibit monitoring incentives and thus reduce decentralization benefits in countering corruption. We argue that the effectiveness of decentralization as an anti-corruption barrier is complemented by the quality of the accounting practice in a country. Using multiple sources of data, we find that decentralization has a positive and increasing effect on reducing corruption among countries with a high-quality accounting practice. In contrast, decentralization has a negative and decreasing effect on reducing corruption among countries with weak-quality accounting practices. These findings are robust to alternative measures of accounting, decentralization and corruption and to endogeneity tests. Our findings demonstrate the crucial information role of accounting in enhancing decentralization monitoring mechanisms and in thereby reducing corruption.     

Cognitive ability and human behavior in experimental ultimatum games

Recent researches have shed light on the effect of cognitive ability on economic decision-making. By measuring cognitive ability applying Raven's progressive matrix test, we obtain two significant results that this effect affects decision-making in two types of experimental ultimatum games. First, the higher the cognitive ability, the larger the amount a sender offers when the offer is smaller than or equal to the half split. Second, the higher the responders’ cognitive ability, the smaller the offer they accept, when they accept it or not with the strategy method. This study not only finds new factors that affect decision-making in experimental ultimatum games, but also provides more evidences that cognitive ability influences economic decision-making.     

Blockchain in Additive Manufacturing and its Impact on Supply Chains

Additive manufacturing (AM) appears to be a particularly attractive use case for blockchain. This research combines inductive in‐depth interviews with the Delphi method to explore what potentials blockchain technology in AM creates, which adoption barriers firms need to overcome, and how supply chains will be affected by the integration of these two potentially disruptive technologies. The results suggest opportunities that are related to intellectual property (IP) rights management, the monitoring of printed parts throughout their lifecycle, process improvements, and data security. The most important barriers for blockchain adoption in AM are an absence of blockchain‐skilled specialists on the labor market, missing governance mechanisms, and a lack of firm‐internal technical expertise. By addressing important limitations of AM, blockchain is expected to improve the competitiveness of AM in parts’ production, catalyzing the trend toward more decentralized manufacturing resulting in more agile, resilient, and flexible supply chains and reduced logistics costs. Beyond that, blockchain‐based AM platforms are expected to enhance supply chain visibility, drive supply chain digitalization, support supply chain finance, and contribute to the emergence of shared factory systems.     

Risk aversion,prudence and temperance: An experiment in gain and loss

We characterize the individual's attitude towards risk, prudence and temperance in the gain and loss domains. We analyze the links between the three features of preferences for a given domain and between domains for each feature of preferences. Consequently, the reflection effect, the mixed risk aversion and the risk apportionment, are key concepts of our study. We also display some determinants for risk aversion, prudence and temperance in each domain. To do this, we conducted a lab experiment with students eliciting risk aversion, prudence and temperance in the two domains, and collected information about each subject's characteristics.     

Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

Farm size and productivity growth in the United States Corn Belt

In recent decades, agricultural production in the U.S. has continued to shift to large-scale operations, raising concerns about the economic viability of small and midsized farms. To understand whether economies of size provided an incentive for the consolidation of production, the study estimates the total factor productivity (TFP) of five size classes of grain-producing farms in the U.S. Heartland (Corn Belt) region. Using quinquennial Agricultural Census data from 1982 to 2012 the study also compares TFP growth rates across farm sizes to gain insight into whether observed productivity differences are likely to persist. The finding of a strong positive relationship between farm size and TFP suggests that consolidation of production has contributed to recent aggregate productivity growth in the crop sector. The study estimates the extent to which sectoral productivity growth can be attributed to structural change versus other factors including technological change. The study also explores some tradeoffs associated with policies that raise the productivity of small versus large farms.     

Are USDA reports still news to changing crop markets?

This study investigates whether major USDA reports still provide important news to changing crop markets. The news component of each report, or market “surprise,” is measured as a difference between the USDA estimate and its private expectation in corn, soybeans, and wheat markets. Changes in the relevance of USDA information are assessed by examining changes in the magnitude of market surprises and shifts in the futures price reaction to these surprises, which isolates the impact of each report. The stable size of market surprises over time suggests that competition from alternative data sources has not reduced the news component of USDA crop reports. Increasing price reaction to most reports, including those facing competition from alternative information sources, suggests that value of public information may be enhanced in uncertain markets affected by structural changes.     

The impact of research collaboration on academic performance: An empirical analysis for some European countries

The aim of this paper is to investigate the impact of internal and external research collaborations on the scientific performance of academic institutions. The data are derived from the international SCOPUS database. We consider both quantity (the number of publications) and quality indicators (the field-weighted citation impact and the share of publications in the 10% most-cited articles) to evaluate universities' performance in some European countries (Germany, France, Italy, the UK and Russia). To this end, we develop a non-overlapping generations model to evidence the theoretical idea of research externalities between academic institutions. Moreover, we implement an empirical model to determine the extent to which the impact of internal and external collaborations on universities' performance is sensitive to the geographical dimension of the data.