欧元国际地位发展探析

欧元自1999年正式启动以来,在国际市场中的使用稳步成长,在第三国的使用日益广泛,已成为有信誉、稳定的第二大国际货币。但欧元国际地位的发展在各市场部分中具有一定的不平衡,地域性显著,尚不具备全球性。欧元国际地位的这种发展状态是历史性和变革性因素以及欧元主要使用者共同作用的结果,在诸多有利因素的支持下,欧元作为第二国际货币的地位在未来将得到进一步加强。     

Scaling up CBOs for second‐order devolution in welfare reform

The Personal Responsibility and Work Opportunity Act of 1996 created a paradigm shift in the financing, organization, and delivery of welfare programs in the United States. The act shifted revenue and authority to states, giving them great discretion to determine the specifics of their programs. First‐order devolution, combined with time limits and work requirements, set in motion a chain of events that moved Temporary Assistance to Needy Families (TANF) recipients into the labor force and off state welfare rolls. Second‐order devolution shifted revenue and authority to community‐based organizations (CBOs) to help former recipients remain employed, advance to higher paying jobs, and move their families toward economic self‐sufficiency. Early findings from project innovations in Texas and other states raise doubts about the capacity of these organizations to achieve these goals. State funders will need to provide ongoing technical assistance and support to “scale up” the capacity of CBOs to plan, implement, and manage local innovations in welfare reform.     

An alternative to model selection in ordinary regression

The weaknesses of established model selection procedures based on hypothesis testing and similar criteria are discussed and an alternative based on synthetic (composite) estimation is proposed. It is developed for the problem of prediction in ordinary regression and its properties are explored by simulations for the simple regression. Extensions to a general setting are described and an example with multiple regression is analysed. Arguments are presented against using a selected model for any inferences.     

Successful collaboration between the nonprofit and public sectors

Public and private funding sources often require nonprofit organizations to provide evidence of partnership with a governmental entity before financing a project. However, the circumstances under which working partnerships between the nonprofit and public sectors are forged and sustained have not been fully studied. This article presents the findings of a case study of land trusts and local governments and identifies conditions that foster successful collaboration. Social factors such as experience on the part of key personnel in working with the opposite entity and genuine affection for each other are more important than economic benefits. This suggests that a nonprofit agency interested in creating a viable partnership to improve a project should give careful consideration to assigning staff.     

The Access/Impact Problem and the Green and Gold Roads to Open Access

The research access/impact problem arises because journal articles are not accessible to all of their would-be users; hence, they are losing potential research impact. The solution is to make all articles Open Access (OA; i.e., accessible online, free for all). OA articles have significantly higher citation impact than non-OA articles. There are two roads to OA: the “golden” road (publish your article in an OA journal) and the “green” road (publish your article in a non-OA journal but also self-archive it in an OA archive). Only 5% of journals are gold, but over 90% are already green (i.e., they have given their authors the green light to self-archive); yet only about 10–20% of articles have been self-archived. To reach 100% OA, self-archiving needs to be mandated by researchers' employers and funders, as the United Kingdom and the United States have recently recommended, and universities need to implement that mandate.     

Goodness‐of‐fit methods for matched case‐control studies

The authors propose graphical and numerical methods for checking the adequacy of the logistic regression model for matched case‐control data. Their approach is based on the cumulative sum of residuals over the covariate or linear predictor. Under the assumed model, the cumulative residual process converges weakly to a centered Gaussian limit whose distribution can be approximated via computer simulation. The observed cumulative residual pattern can then be compared both visually and analytically to a certain number of simulated realizations of the approximate limiting process under the null hypothesis. The proposed techniques allow one to check the functional form of each covariate, the logistic link function as well as the overall model adequacy. The authors assess the performance of the proposed methods through simulation studies and illustrate them using data from a cardiovascular study.     

Loss functions for estimation of extrema with an application to disease mapping

It is often of interest to find the maximum or near maxima among a set of vector‐valued parameters in a statistical model; in the case of disease mapping, for example, these correspond to relative‐risk “hotspots” where public‐health intervention may be needed. The general problem is one of estimating nonlinear functions of the ensemble of relative risks, but biased estimates result if posterior means are simply substituted into these nonlinear functions. The authors obtain better estimates of extrema from a new, weighted ranks squared error loss function. The derivation of these Bayes estimators assumes a hidden‐Markov random‐field model for relative risks, and their behaviour is illustrated with real and simulated data.     

Consistent maximum likelihood estimation of a unimodal density using shape restrictions

It is well known that the unimodal maximum likelihood estimator of a density is consistent everywhere but at the mode. The authors review various ways to solve this problem and propose a new estimator that is concave over an interval containing the mode; this interval may be chosen by the user or through an algorithm. The authors show how to implement their solution and compare it to other approaches through simulations. They show that the new estimator is consistent everywhere and determine its rate of convergence in the Hellinger metric.