工业化城镇化对农民增收影响的空间计量分析——基于安徽省县域数据

基于2000-2010年安徽省县域农民人均纯收入数据,利用探索性空间数据分析方法测度农民收入空间相关性和局部集聚空间格局演变,分别建立2000年、2005年和2010年农民收入空间杜宾模型和空间滞后模型,研究工业化城镇化发展对农民增收的影响程度及变化趋势。研究结果表明:安徽农村居民收入存在明显的地域差异,呈正的空间自相关性,低收入集聚区沿安徽西侧边境向西南和西北部转移,高收入集聚区沿皖江城市带从苏皖边境向皖中地区扩张;空间计量模型能够分离出收入空间溢出效应,避免经典回归对工业化城镇化影响程度的高估;工业化发展促进农民增收作用增强,但可能出现虹吸效应;不完全的城镇化发展对农民增收作用减弱,应发挥其扩散效应;农业现代化促进农民增收效果不明显。     

Small area estimation of mean price of habitation transaction using time-series and cross-sectional area-level models

In this paper, a new small domain estimator for area-level data is proposed. The proposed estimator is driven by a real problem of estimating the mean price of habitation transaction at a regional level in a European country, using data collected from a longitudinal survey conducted by a national statistical office. At the desired level of inference, it is not possible to provide accurate direct estimates because the sample sizes in these domains are very small. An area-level model with a heterogeneous covariance structure of random effects assists the proposed combined estimator. This model is an extension of a model due to Fay and Herriot [5], but it integrates information across domains and over several periods of time. In addition, a modified method of estimation of variance components for time-series and cross-sectional area-level models is proposed by including the design weights. A Monte Carlo simulation, based on real data, is conducted to investigate the performance of the proposed estimators in comparison with other estimators frequently used in small area estimation problems. In particular, we compare the performance of these estimators with the estimator based on the Rao–Yu model [23]. The simulation study also accesses the performance of the modified variance component estimators in comparison with the traditional ANOVA method. Simulation results show that the estimators proposed perform better than the other estimators in terms of both precision and bias.     

A Non‐Parametric Estimator of the Spectral Density of a Continuous‐Time Gaussian Process Observed at Random Times

Abstract. In numerous applications data are observed at random times and an estimated graph of the spectral density may be relevant for characterizing and explaining phenomena. By using a wavelet analysis, one derives a non‐parametric estimator of the spectral density of a Gaussian process with stationary increments (or a stationary Gaussian process) from the observation of one path at random discrete times. For every positive frequency, this estimator is proved to satisfy a central limit theorem with a convergence rate depending on the roughness of the process and the moment of random durations between successive observations. In the case of stationary Gaussian processes, one can compare this estimator with estimators based on the empirical periodogram. Both estimators reach the same optimal rate of convergence, but the estimator based on wavelet analysis converges for a different class of random times. Simulation examples and an application to biological data are also provided.     

Sparse Approximations of Fractional Matérn Fields

We consider fast lattice approximation methods for a solution of a certain stochastic non‐local pseudodifferential operator equation. This equation defines a Matérn class random field. We approximate the pseudodifferential operator with truncated Taylor expansion, spectral domain error functional minimization and rounding approximations. This allows us to construct Gaussian Markov random field approximations. We construct lattice approximations with finite‐difference methods. We show that the solutions can be constructed with overdetermined systems of stochastic matrix equations with sparse matrices, and we solve the system of equations with a sparse Cholesky decomposition. We consider convergence of the truncated Taylor approximation by studying band‐limited Matérn fields. We consider the convergence of the discrete approximations to the continuous limits. Finally, we study numerically the accuracy of different approximation methods with an interpolation problem.     

Spatial autoregression with repeated measurements for social networks

Spatial autoregressive model (SAR) is found useful to estimate the social autocorrelation in social networks recently. However, the rapid development of information technology enables researchers to collect repeated measurements for a given social network. The SAR model for social networks is designed for cross-sectional data and is thus not feasible. In this article, we propose a new model which is referred to as SAR with random effects (SARRE) for social networks. It could be considered as a natural combination of two types of models, the SAR model for social networks and a particular type of mixed model. To solve the problem of high computational complexity in large social networks, a pseudo-maximum likelihood estimate (PMLE) is proposed. The asymptotic properties of the estimate are established. We demonstrate the performance of the proposed method by extensive numerical studies and a real data example.     

Ruin problem of a two-dimensional fractional Brownian motion risk process

This paper investigates ruin probability and ruin time of a two-dimensional fractional Brownian motion risk process. The net loss process of an insurance company is modeled by a fractional Brownian motion. The two-dimensional fractional Brownian motion risk process models the surplus processes of an insurance and a reinsurance company, where the net loss is divided between them in some specified proportions. The ruin problem considered is that of the two-dimensional risk process first entering the negative quadrant, that is, the simultaneous ruin problem. We derive both asymptotics of the ruin probability and approximations of the scaled conditional ruin time as the initial capital tends to infinity.     

存在自相关时检验和估计方法的改进——基于自回归分布滞后模型的自相关检验和参数估计

存在自相关时的自相关检验和参数估计是基础计量经济学的一个重要内容,并且存在自相关时的原模型已转化为自回归分布滞后模型。讨论存在自相关时的自相关检验和参数估计问题,提出了一种基于自回归分布滞后模型的自相关检验法,并同时给出了相应的参数估计。     

具有多重势的分数阶非线性Schrodinger方程解的适定性

讨论了具有多重势的分数阶非线性Schrodinger方程的周期边值问题,利用能量估计和Faedo—Galerkin方法证明了该问题光滑解的整体存在唯一性     

按份共有人优先购买权若干争议问题探析

按份共有人优先购买权与按份共有关系相始终,无需公示就具有对抗第三人的效力。在所有权以外的其他财产权的准按份共有关系中,除地役权和担保物权的准按份共有之外,均得适用按份共有人优先购买权制度。行使该权利的结果,可使权利人优先于第三人取得被出卖的共有份额。在多数按份共有人依多数决原则出卖共有物时,不同意出卖的共有人对同意出卖的共有人所持的共有份额不享有优先购买权。     

贸易开放与环境污染内在关系研究

揭示我国贸易开度与环境污染之间的内在关系。在Stem（2002）模型的基础上,以SO2排放量表征环境污染水平,对2000—2009年间我国30个省、自治区及直辖市（西藏由于数据不全）的面板数据进行普通和空间面板回归分析,结果显示SO2污染物质的排放存在空间自相关和误差自相关,研究发现经济规模扩大、第二产业结构和出口变动会加剧环境污染,而FDI、进口则会降低我国的环境污染,并估算五要素对环境污染影响的各自实际贡献率。对完善我国贸易开放和环境保护政策,促进经济社会环境可持续发展战略具有重要的指导意义。