金融支持国防知识产权成果转化问题及策略研究

国防知识产权成果转化应用是国防科技创新体系建设落地见效的关键环节，引入现代金融体系能够有效促进国防知识产权成果转化。目前我国国防知识产权转化工作在组织管理体制、工作运行体系、法规政策制度和信息化建设等方面初显成效，但仍面临整体转化形势不容乐观、金融支持体系尚未成熟等问题，根本原因在于国防知识产权与发明人割裂导致一般金融产品难以通过审核，使融资渠道狭窄；其保密性进一步加大了与金融机构间的信息不对称，使得金融资源配置效率低下；国防知识产权专用性较强，相应抬高了融资成本。为有效解决上述问题，提出3条改进措施，以实现对国防知识产权转化的金融支持，即①从顶层设计上优化解密脱密流程，明确发明人与知识产权的权属关系，细化财税优惠等支持措施；②加强政府财政税收政策支持，引导创新利用多元社会资本进入支持转化领域；③建立各主体参与的金融服务协调保障机制、监测评估体系，启动国防知识产权转化的金融支持试点工作，构建符合国情的国防知识产权转化金融支持体系。     

A truly global crisis? Evidence from contagion dependence across international REIT markets

This study examines the global nature of the recent crisis under bivariate Markov-switching models for pre- and post-crisis periods using the breakpoint of August 9, 2007. It quantifies international synchronization of boom-bust regime switches to investigate contagion-type dynamic comovements of Real Estate Investment Trusts (REITs). Global REIT markets display persistent bust regimes from September 2008 to May 2009, whereas the regime-switching patterns are not significant in the pre-crisis period. The results provide new evidence for global REIT contagion phenomena and suggest greater difficulties in diversifying risks across global REIT markets during the post-crisis period.     

Is it still economic to build a new coal-fired power plant in the U.S.? A real option analysis

In the U.S., virtually no new coal-fired power plants have been built in recent years. Both industry experts and academics seem to believe that no rational firm will build a new coal-fired plant. Will such a trend continue in the future? To provide insights into this question, we investigate the optimal decision of an electricity company with an irreversible and deferrable opportunity to build either a new coal-fired or natural gas-fired power plant as its new base-load resource. According to our real option analysis, the optimal decision depends on the location. In the case of the eastern U.S., it is optimal to choose a natural gas plant if a firm is given a choice among a new natural gas plant, a new coal plant and deferring the investment. However, contrary to the common sentiment in the industry and academia, building a new coal plant in the western U.S. is still more economical than building a new natural gas plant in the absence of emission pricing. Furthermore, introducing carbon pricing to western U.S. states, as California did, can substantially increase the probability that a firm will optimally choose a natural gas plant over a coal plant.     

Characteristics and implications of Chinese macroeconomic data revisions

The research examining macroeconomic data for developed economies suggests that an understanding of the nature of data revisions is important both for the production of accurate macroeconomic forecasts and for forecast evaluation. This paper focuses on Chinese data, for which there has been substantial debate about data quality for some time. The key finding in this paper is that, while it is true that the Chinese macroeconomic data revisions are not well-behaved, they are not very different from similarly-timed U.S. macroeconomic data revisions. The positive bias in Chinese real GDP revisions is a result of the fast-growing service sector, which is notably hard to measure in real time. A better understanding of the revisions process is particularly helpful for studies of the forecast errors from surveys of forecasters, where the choice of the vintage for outcomes may have an impact on the estimated forecast errors.     

On credit and output: Is the supply of credit relevant?

The consensus that changes in the supply of credit were irrelevant to making monetary policy decisions existed among macroeconomists during the second half of the twentieth century. Transmission of shocks to the real economy through changes in the supply of credit, however, played an important role in the recent U.S. financial crisis. This paper explores the extent to which policymakers should consider changes in the supply of credit when making forecasts and monetary policy decisions. More specifically, it considers whether a measure of real credit balances offers consistent and stable information, beyond that of a real interest rate and real money balances, about future output gaps during the U.S. post-war era. Results yield evidence that changes in real credit balances are the only variable, among those considered, to provide consistent and stable information about future output gaps over the entire sample period. Each information variable, however, provides relatively little value added for forecasting future output gaps, beyond a simple autoregressive model. To improve upon forecasts and monetary policy decisions, policymakers therefore should consider a broader range of information variables and occasionally reassess the relative weightings assigned to each.     

Irreversible investment,ambiguity and equity default swaps

We study the impact of ambiguity on the pricing and timing of the option to invest. There is a funding gap to undertake the investment, which is covered by entering into an equity-for-guarantee swap. Our model predicts that the more ambiguity-averse the agents, the less the option value, the later the investment and the higher the guarantee cost and the leverage. If the entrepreneur is more ambiguity-averse than the insurer, the investment threshold slightly rises as the perceived ambiguity increases, and on the contrary, if the entrepreneur is less ambiguity-averse than the insurer, the investment threshold increases sharply as the perceived ambiguity rises.     

Unemployment and econometric learning

We apply well-known results of the econometric learning literature to the Mortensen and Pissarides real business cycle model. Agents can always learn the unique rational expectations equilibrium (REE), for all possible well-defined sets of parameter values, by using the minimum-state-variable solution to the model and decreasing gain learning. From this perspective the assumption of rational expectations in the model could be seen as reasonable. But using a parametrisation with UK data, simulations show that the speed of convergence to the REE is slow. This type of learning dampens the cyclical response of unemployment to small structural shocks.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

期权型资源配置对企业竞争优势的影响

旨在打开资源基础观中组织黑箱，丰富资源配置研究成果，探讨在新竞争时代何种资源配置方式能更有效地促进企业创新特别是探索式创新，从而建立或强化企业竞争优势。通过梳理西方最新研究成果，基于我国146家企业样本，利用回归分析法检验期权型资源配置对企业竞争优势的促进作用，采取因果逐步回归法检验探索式创新在该过程中的中介作用。研究表明：期权型资源配置既能强化企业竞争优势，又能促进探索式创新；探索式创新在期权型资源配置与竞争优势间发挥部分中介作用；相对于创新的资源投入，资源配置方式对竞争优势的作用更强。