工业劳动力流动、资本创造与经济地理空间均衡

资本创造模型（CC模型）忽视了要素流动对产业空间分布的影响。而发展的新的资本创造模型则认为资本集聚的过程必然伴随着工业劳动力的流动过程。另外，是资本的实际收益而不是名义收益决定资本是否创造。研究结果表明，随着贸易自由度、工业品支出份额及资本贴现率的变大，替代弹性及资本折旧率的变小，将降低对称结构的稳定性，而提高中心-外围结构的稳定性；经济地理空间的产业均衡是集聚力和分散力相互作用的结果。当企业生产工业品的规模报酬递增程度足够显著，或者工业品支出份额很高时，市场拥挤效应将彻底消失，并转化成为促进产业集聚的动力；突破点与持续点的大小比较可以形成不同的关系，这意味着随着贸易自由度的变化，本文发展的资本创造模型可以体现出多样化的产业空间动态演化行为。     

局部平稳部分线性面板数据模型的统计推断

部分线性模型是一类非常重要的半参数回归模型,由于它既含有参数部分又含有非参数部分,与常规的线性模型相比具有更强的适应性和解释能力。文章研究带有局部平稳协变量的固定效应部分线性面板数据模型的统计推断。首先提出一个两阶段估计方法得到模型中未知参数和非参数函数的估计,并证明估计量的渐近性质,然后运用不变原理构造出非参数函数的一致置信带,最后通过数值模拟研究和实例分析验证了该方法的有效性。     

农户地权诉求视角下农地制度的创新

目前我国农户的地权诉求已经发生了很大的变化，即由地权稳定、自主经营向农地资源的优化配置和高效利用转化。这一变化的内在动力是农户急切希望改变承包地过于细碎化以及改善农业生产经营基本条件。考察我国农地制度的发展史可以发现，我国农地制度变迁的基本逻辑就是农户的地权诉求决定农地制度的发展方向，这一点在当下一些地方的农地制度创新试验和经验中再次得到证明。今后我国农地制度创新必须遵循这一逻辑，根据我国农户地权诉求的变化，实施农户自愿前提下的承包地连片重划,争取国家对承包地重划制度的支持,强化农民集体民主决策制度,地方政府也要给予必要的支持。     

农用承包地流转意愿的实证研究--基于福建省六地市农户问卷调查

从农户意愿角度，以福建省农民的农用承包地为研究对象，对影响农户承包地流转的因素进行分析，通过实地调查和问卷调查的形式收集到影响农户流转承包地的样本数据，并对通过建立二元Logistic模型对各个因素的显著性进行检验。通过实证研究发现，户主受教育程度、户主的职业、农户家庭的人口、家庭的收入主要来源、承包地面积和农户流转承包地的租金水平是农户流转承包地的显著性影响因素，其中户主受教育程度、家庭的收入主要来源、承包地面积和租金水平是正向影响，户主的职业和农户家庭的人口是负向影响。根据研究的结论提出相应的政策建议。     

论民族自治地方政府机构改革的深化——基于新中国成立初期探索的思考

民族自治地方政府在新一轮机构改革中进行了历史性变革和系统性重塑，然而顶层设计与分层对接机制优化、机构设置细化与整合、运转协同和效能提升仍未完全到位。回溯机构改革史，中华人民共和国成立初期作为政府顶层设计和系统性构建阶段，是民族自治地方政府机构建设最富成效的历史时期之一。这一时期的民族自治地方政府机构建设强调权能配置和人员构成的民族性，逐步差异化设置机构、探索单一制下政府机构平衡设置等历史经验，可以为进一步深化政府机构改革提供有益借鉴。在新的历史起点上深化民族自治地方政府机构改革应以新时代中国特色社会主义思想为引领，合理汲取历史养分，进一步深化理论研究，完善法制体系，明晰特殊性职权和民族性职能，健全顶层设计与分层对接机制，创新改革模式，强化地方参与性，切实破解改革难题，推动政府自身建设持续走向深入。     

Negotiating Accessibility for Electronic Resources

Abstract

Accessibility of library electronic resources is a must. Its importance derives from professional ethics of librarianship, rising total costs of acquisition, and mounting legal challenges to colleges and universities that fail to provide resources accessible to users with disabilities. Library staff are responsible for ensuring the accessibility of vendor-licensed eresources. This column reviews the accessibility clauses of nine model license agreements for electronic resources. It describes terms that should go into an optimal accessibility clause and creates a composite model clause. It also provides guidance for library staff seeking to negotiate stronger accessibility language into vendor license agreements. Finally, it addresses the impact of accommodation requests on the total cost of acquiring library eresources, concluding with a call to redouble efforts to advocate for greater accessibility and educate both vendors and library staff about its importance.     

A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

Noninformative priors for the between-group variance in the unbalanced one-way random effects model with heterogeneous error variances

For the unbalanced one-way random effects model with heterogeneous error variances, we propose the non-informative priors for the between-group variance and develop the first- and second-order matching priors. It turns out that the second-order matching priors do not exist and the reference prior and Jeffreys prior do not satisfy a first-order matching criterion. We also show that the first-order matching prior meets the frequentist target coverage probabilities much better than the Jeffreys prior and reference prior through simulation study, and the Bayesian credible intervals based on the matching prior and reference prior give shorter intervals than the existing confidence intervals by examples.     

A Graphical Tool for Interpreting Regression Coefficients of Trinomial Logit Models

Multinomial logit (also termed multi-logit) models permit the analysis of the statistical relation between a categorical response variable and a set of explicative variables (called covariates or regressors). Although multinomial logit is widely used in both the social and economic sciences, the interpretation of regression coefficients may be tricky, as the effect of covariates on the probability distribution of the response variable is nonconstant and difficult to quantify. The ternary plots illustrated in this article aim at facilitating the interpretation of regression coefficients and permit the effect of covariates (either singularly or jointly considered) on the probability distribution of the dependent variable to be quantified. Ternary plots can be drawn both for ordered and for unordered categorical dependent variables, when the number of possible outcomes equals three (trinomial response variable); these plots allow not only to represent the covariate effects over the whole parameter space of the dependent variable but also to compare the covariate effects of any given individual profile. The method is illustrated and discussed through analysis of a dataset concerning the transition of master’s graduates of the University of Trento (Italy) from university to employment.