An Application of the Dynamic Network DEA Model: The Case of Banks in Taiwan

ABSTRACT

In this study, we apply the dynamic network slack-based measure data envelopment analysis model (DNSBM) to measure the efficiency of Taiwanese banks during the period 2005–11. Using the network structure, we define intellectual capital creation capability as one of the production stages. In order to capture the dynamics of the transformation process, the nonperforming loans and loan loss reserves are defined as carryover items. This study offers sufficient information for managers to understand not only the overall performance of their banks but also the efficiency of each production stage and the dynamic changes of the overall and divisional efficiencies.     

How collaborative routines improve dynamic innovation capability and performance in tourism industry? A path-dependent learning model

Current results of direct relationships between collaboration and innovation capability on performance in tourism contexts are inconsistent. This research is to uncover roles of collaborative routines on promoting relationships between internal and service innovation capabilities as two distinct mechanisms, and performance. The study also examines the contingent effect of knowledge search on performance. Survey data from 181 samples from the Thai tourism industry are gathered for analyses. Findings demonstrate that knowledge search and internal innovation capability have a direct impact on performance, whereas the effect of service innovation capability on performance is significant only in the presence of collaborative routines.     

房地产企业工程造价的管理与控制

随着国家的宏观调控,房地产市场的暴利时代已经逝去。而以定位准确、服务至上、提高品质、品牌等为核心的"价值回归"的理念,正在得到业界越来越多的关注和认同。因此,房地产行业在未来的发展过程中,如何通过工程造价的管理与控制,来提高自己的核心竞争力已是重中之重。笔者现结合实际工作的一些体会,就房地产企业在开发过程中工程造价的管理与控制谈一些个人的观点。希望能为工程造价合理、有效的管理和控制提供一定参考。     

Bond Pricing with a Time‐Varying Price of Risk in an Estimated Medium‐Scale Bayesian DSGE Model

New Keynesian model in which households have Epstein–Zin preferences with time‐varying risk aversion and the central bank has a time‐varying inflation target can match the dynamics of nominal bond prices in the U.S. economy well. The model generates a large steady‐state term spread and its fitting errors for bond yields are comparable to those obtained from a nonstructural three‐factor model, and one‐third smaller than in models with a constant inflation target or risk aversion. Including data on interest rates has large effects on variance decompositions, making investment technology shocks much less important than found in other recent papers.     

A Framework for the Simultaneous Measurement of Spatial Variation and Temporal Movement in Prices in a Heterogeneous Country: The Dynamic Household Regional Product Dummy Model

This paper contributes to the growing literature on spatial prices in large heterogeneous countries. While the literatures on spatial variation and temporal movement in prices have grown in parallel, this study marks a departure by providing a unified treatment and proposing a comprehensive framework that allows both approaches. The proposed model is based on twin extensions of the household version of the “country product dummy model” by allowing for a dynamic stochastic specification and interdependence of spatial prices of geographically adjacent regions. Tests of temporal stability and regional independence of the estimated spatial prices are proposed and applied in this paper. The paper shows that the introduction of an autoregressive error process of order one, AR(1), improves the efficiency of the estimates of parameters, urban‐rural and temporal price indices under certain conditions. The Indian application points to a rich potential for using the proposed framework in cross country comparisons such as the International Comparison Program (ICP) exercises.     

Unrelated question model with two decks of cards

In this paper, we propose a new unrelated question model for estimating the prevalence of a sensitive characteristic within a population by utilizing two decks of cards. The resultant estimator is then compared to its competitors as to efficiency and as to protection of respondents. A real data application analyzing e-cigarette use among college students is considered.     

Is there a profit premium for market-oriented firms? A panel data investigation

ABSTRACT

This paper provides an empirical investigation of the impact of market orientation on firms' economic performance during the period 1998–2012 using a panel of Italian manufacturing firms. We introduce a dynamic concept of market orientation, in that we define a market-oriented firm as one that persistently undertakes product and marketing innovation, while at the same time introducing organizational changes and training efforts to manage and improve its knowledge assets over the long term. This notion of market orientation is therefore crucially related to the so-called dynamic capability approach. The related empirical model shows that being a market-oriented firm significantly affects profitability, in a framework in which this latter is simultaneously estimated with productivity, thus allowing for more precise estimates of the profit premium which is earned accordingly.     

利用频移动态特征的辐射源目标盲分选

利用辐射源目标的频移动态特征进行盲分选时，针对已有的分选方法不能很好解决非合作接收数据非周期、间断、交叠的问题，提出了一种改进的逻辑回归分选算法,将信号分选转化为轨迹分类的问题来处理。首先，借鉴多目标航迹起始模型中的M/N逻辑法的框架，设计新的数据关联门限，以建立目标起始曲线；其次，采用最小二乘拟合方法替代卡尔曼滤波，设计新的外推规则，建立载频变化预测曲线；分析新的接收数据与预测曲线的关联性，不断迭代回归或形成新的分支，最后获得目标分选结果。仿真与实测试验表明，利用逻辑回归分选算法，对不同运动目标搭载的同频辐射源可进行自动分选，4个仿真目标与2个真实目标的分选正确率达到100%。同时，该方法拓展了辐射源目标盲分选中的动态频移特征应用，为辐射源个体识别提供了新的支持。     

Do Cryptocurrencies Increase the Systemic Risk of the Global Financial Market?

The advance of cryptocurrencies has sparked wide concern over their interplay with the existing global financial market. This paper analyzes the risk spillover relation between cryptocurrencies and major financial assets, and unravels how cryptocurrencies could influence global financial systemic risk. We find that cryptocurrencies function as a separate risk source from traditional assets. Major legislative, financial and technological events in the cryptocurrency market may affect risk spillover dynamics. Although the overall penetration of cryptocurrencies is not yet deep, introducing cryptocurrency can significantly increase the systemic risk to traditional markets during low risk level episodes.     

Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix

This paper studies a robust continuous‐time Markowitz portfolio selection problem where the model uncertainty affects the covariance matrix of multiple risky assets. This problem is formulated into a min–max mean‐variance problem over a set of nondominated probability measures that is solved by a McKean–Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman–Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.