The economic burden of depression among adults with rheumatoid arthritis in the United States

Aims: Depression is the most frequent comorbidity reported among patients with rheumatoid arthritis (RA). Comorbid depression negatively impacts RA patients’ health-related quality-of-life, physical function, mental function, mortality, and experience of pain and symptom severity. The objective of this study was to assess healthcare utilization, expenditures, and work productivity among patients with RA with or without depression.

Materials and methods: Data from adult patients who had at least two visits each related to RA and depression over a 1-year period were extracted from the Truven Health MarketScan research databases. Outcomes comprised healthcare resource utilization, work productivity loss, and direct healthcare costs comparing patients with RA with depression (n?=?3,478) vs patients with RA without depression (n?=?43,222).

Results: Patients with RA and depression had a significantly greater relative risk of hospitalization and number of all-cause and RA-related hospitalizations, utilization of emergency services, days spent in the hospital, physician visits, and RA-related surgeries compared with RA patients without depression. Patients with RA and depression had a higher risk of and experienced more events and days of short-term disability compared with patients without depression. The incremental adjusted annual all-cause and RA-related direct costs were $8,488 (95% CI = $6,793–$10,223) and $578 (95% CI = –$98–$1,243), respectively, when comparing patients with RA and depression vs RA only.

Limitations: The current analysis is subject to the known limitations of retrospective studies based on administrative claims data.

Conclusions: This study suggested increased healthcare utilization, work productivity loss, and economic burden among RA patients due to comorbid depression. These findings emphasize the importance of managing depression and including depression as a factor when devising treatment algorithms for patients with RA.     

Fuzzy modelling of static system optimum traffic assignment problem having multi origin-destination pair

Traffic congestion is an unpreventable problem to avoid in a transportation network and it has negative effects on traffic accident, time wasting, traffic delay and safety problem. Besides, in transportation networks, drivers do not want to deal with traffic jam while traversing between specified origin-destination pair. Therefore, traffic assignment (TA) is imperative to improve traffic management, transportation safety, time, and cost savings. System Optimum Traffic Assignment Problem (SOTAP) is a kind of TA model which aims to minimize the total system travel time on the network, and satisfies the flow conservation constraints. To model the SOTAP more realistically, the imprecise parameters can be taken as fuzzy. Therefore, in this paper, we focus on converting the conventional SOTAP to a fuzzy quadratic programming problem (QPP) which is named System Optimum Fuzzy Traffic Assignment Problem (SOFTAP). Here, link travel time is expressed with BPR function as generally used in the literature by converting to fuzzy except link-dependent parameters. Thus, the nonlinear objective function of SOFTAP is expressed in terms of fuzzy link flows and fuzzy link travel times. A solution approach from the literature is modified to the reconstructed SOFTAP.     

Non-linear Gaussian sovereign CDS pricing models

Prior literature indicates that quadratic models and the Black–Karasinski model are very promising for CDS pricing. This paper extends these models and the Black [J. Finance 1995, 50, 1371–1376] model for pricing sovereign CDS’s. For all 10 sovereigns in the sample quadratic models best fit CDS spreads in-sample, and a four factor quadratic model can account for the joint effects on CDS spreads of default risk, default loss risk and liquidity risk with no restriction to factors correlation. Liquidity risk appears to affect sovereign CDS spreads. However, quadratic models tend to over-fit some CDS maturities at the expense of other maturities, while the BK model is particularly immune from this tendency. The Black model seems preferable because its out-of-sample performance in the time series dimension is the best.     

Predictive regressions under asymmetric loss: Factor augmentation and model selection

This paper discusses the specifics of forecasting using factor-augmented predictive regressions under general loss functions. In line with the literature, we employ principal component analysis to extract factors from the set of predictors. In addition, we also extract information on the volatility of the series to be predicted, since the volatility is forecast-relevant under non-quadratic loss functions. We ensure asymptotic unbiasedness of the forecasts under the relevant loss by estimating the predictive regression through the minimization of the in-sample average loss. Finally, we select the most promising predictors for the series to be forecast by employing an information criterion that is tailored to the relevant loss. Using a large monthly data set for the US economy, we assess the proposed adjustments in a pseudo out-of-sample forecasting exercise for various variables. As expected, the use of estimation under the relevant loss is found to be effective. Using an additional volatility proxy as the predictor and conducting model selection that is tailored to the relevant loss function enhances the forecast performance significantly.     

信息技术提高企业组织敏捷性的作用机理

从考察企业组织的敏捷性与交易成本的相互关系入手,对企业组织敏捷性的影响因素进行了剖析。详细分析了信息技术(IT)对提高企业组织敏捷性的作用机理。指出IT正是通过降低企业内、外部的交易成本、缩短流程时间、提高人的认识理性、扼制机会主义、促进企业组织结构、决策方式     

Is Volatility the Best Predictor of Market Crashes?

The objective of this paper is to determine the best predictor of equity market crashes by focusing particularly on volatility and market liquidity. In finance, volatility has traditionally been regarded as the best measure of market risk. However, this paper shows that the forecast value of market liquidity, in particular our modified calculated market depth, predicts equity market crashes much more accurately than does the forecast values of EGARCH or Implied Volatility.     

Generating Enhanced Fishery Rents by Internalizing Product Quality Characteristics

This paper demonstrates howadditional rents are generated in a fisherycharacterized by intraseasonal variation infish characteristics, including size,condition, and composition. Based on anexpanded conceptual model of the optimalharvest rule, fish characteristics affect preand post harvest production yields and outputprices. A dynamic empirical model, which uses asystem of quality characteristics and anhedonic equation, illustrates the complexrelationships and management choices associatedwith internalizing seafood qualitycharacteristics in a hake fishery. The modelretains the regulated open access managementsystem, but controls intertemporal andintersectoral quotas, production portfolios,and total allowable catch. Results demonstratethat including revenue-side effects frominternalizing fish quality can generatesignificantly greater rents and reduce therelative benefits of increased productionyields. If excluded, bioeconomic models canunderestimate the level of regulatory rentdissipation and overemphasize managementobjectives such as full utilization, whichcould misdirect processing decisions and resultin a suboptimal resource management plan.Implications for data collection,multidisciplinary analysis, and improvements inmarine resource management are discussed.     

论当代中国私营资本原始积累的社会功效

伴随中国私营经济而发生的私营资本原始积累,对中国的经济社会发展,对加速中国的社会主义现代化建设,是功绩卓著的。中国之所以能在20世纪末达到小康,私营资本原始积累是立下汗马功劳的。在中国今后的全面小康社会建设中私营资本原始积累必将发挥越来越大的功效。     

从功能出发进行对外汉语语法教学的研究与实践

该文系统地总结了作者进行对外汉语语法教学的实践经验——从功能出发进行对外汉语语法教学，具体从三个方面入手：一、语法教学和词汇教学相结合；二、句法结构和语义结构相结合；三、语法知识和语言环境相结合。     

浅议如何充分发挥银行内部审计建设性职能

目前，中国建设银行已建立了总行垂直管理的内部审计体制，内部审计的地位得到了进一步的巩固和加强，管理层对内部审计也提出了更高的要求。本文就如何发挥审计的建设性职能，最大程度地做好审计增值服务，促进银行价值和运作效率的提升，实现审计职能从查错防弊向防护决策和建设性方面转变做初步探讨。