利润最大化区位理论与广州高房价的根源

本文利用利润最大化区位理论,建立房价模型,实证研究广州房价持续上涨的根源。发现影响房价的主要因素是住房供给的短缺,次要原因是高成本以及严重的贫富分化。其体制根源在于自由竞争的地产需求市场与计划经济的地产供给市场之间的矛盾,政策根源在于政府变为“经济人”,一味经营城市,经济根源在于因竞争和权力垄断所导致的产业分化,社会根源在于广州市民不合理的住房消费习惯。因而,近期来讲,加大土地供给、改革土地出让方式、实行房地产累进累退税是抑制房价的关键,从长远来讲,要建立自由竞争的地产供给市场,变“经济人”政府为服务性政府,优化产业结构,取消“国字头”行业特权。     

Statistical inference for the quintile share ratio

In recent years, the Quintile Share Ratio (or QSR) has become a very popular measure of inequality. In 2001, the European Council decided that income inequality in European Union member states should be described using two indicators: the Gini Index and the QSR. The QSR is generally defined as the ratio of the total income earned by the richest 20% of the population relative to that earned by the poorest 20%. Thus, it can be expressed using quantile shares, where a quantile share is the share of total income earned by all of the units up to a given quantile. The aim of this paper is to propose an improved methodology for the estimation and variance estimation of the QSR in a complex sampling design framework. Because the QSR is a non-linear function of interest, the estimation of its sampling variance requires advanced methodology. Moreover, a non-trivial obstacle in the estimation of quantile shares in finite populations is the non-unique definition of a quantile. Thus, two different conceptions of the quantile share are presented in the paper, leading us to two different estimators of the QSR. Regarding variance estimation, [Osier, 2006] and [Osier, 2009] proposed a variance estimator based on linearization techniques. However, his method involves Gaussian kernel smoothing of cumulative distribution functions. Our approach, also based on linearization, shows that no smoothing is needed. The construction of confidence intervals is discussed and a proposition is made to account for the skewness of the sampling distribution of the QSR. Finally, simulation studies are run to assess the relevance of our theoretical results.     

On the importance of being smooth

This paper makes the proposition that the only statistical analyses to achieve widespread popular use in statistical practice are those whose formulations are based on very smooth mathematical functions. The argument is made on an empirical basis, through examples. Given the truth of the proposition, the question ‘why should it be so?’ is intriguing, and any discussion has to be speculative. To aid that discussion, the paper starts with a list of statistical desiderata, with the view of seeing what properties are provided by underlying smoothness. This provides some rationale for the proposition. After that, the examples are considered. Methods that are widely used are listed, along with other methods which, despite impressive properties and possible early promise, have languished in the arena of practical application. Whatever the underlying causes may be, the proposition carries a worthwhile message for the formulation of new statistical methods, and for the adaptation of some of the old ones.     

模糊数据的回归模型结构分析

本文在给出对称三角模糊数样本基础上,提出模糊数据回归分析模型的一般结构。在使用线性规划LP方法进行模糊回归系数估计时,根据模糊集合的择近原则,给出了利用样本平均贴近度评价模型拟合效果的一个准则。通过实例计算,比较了模糊样本回归模型未知参数估计的FLP方法和FLS 方法。     

Interpretation of Canonical Discriminant Functions,Canonical Variates,and Principal Components

Canonical discriminant functions are defined here as linear combinations that separate groups of observations, and canonical variates are defined as linear combinations associated with canonical correlations between two sets of variables. In standardized form, the coefficients in either type of canonical function provide information about the joint contribution of the variables to the canonical function. The standardized coefficients can be converted to correlations between the variables and the canonical function. These correlations generally alter the interpretation of the canonical functions. For canonical discriminant functions, the standardized coefficients are compared with the correlations, with partial t and F tests, and with rotated coefficients. For canonical variates, the discussion includes standardized coefficients, correlations between variables and the function, rotation, and redundancy analysis. Various approaches to interpretation of principal components are compared: the choice between the covariance and correlation matrices, the conversion of coefficients to correlations, the rotation of the coefficients, and the effect of special patterns in the covariance and correlation matrices.     

General lack of fit tests based on families of groupings

Lack of fit tests based on groupings of the observations are developed. These tests are first applied to models with replication. In this case, the classic Fisher test assumes that the true model is contained in the one-way ANOVA model. However, Christensen [(2003). Significantly insignificant F tests. Amer. Statist. 57, 27–32] has noted that small values of the F-statistic may indicate lack of fit due to features which are not part of the proposed model. Such model inadequacy is called within-cluster lack of fit, whereas the standard Fisher lack of fit is called between-cluster lack of fit. Typically, lack of fit exists as a combination of these two pure types, and can be extremely difficult to detect depending on the nature of the mixture. In this paper, the one-way ANOVA model is embedded in larger models using groupings of the observations, which provides tests with good power for detecting all of the above types of model inadequacies, including mixtures. In particular, several such tests are considered, each based on a different grouping of the observations, and the multiple testing approach of Baraud et al. [(2003). Adaptive tests of linear hypotheses by model selection. Ann. Statist. 31, 225–251] is followed. More generally, the preceding testing procedure based on families of groupings is extended to the case of nonreplication. For this case, it is proposed that such families be determined by linear orders on the predictors based on disjoint parallel tubes in predictor space. Test statistics follow the cluster-based regression lack of fit tests presented by Christensen [(1989). Lack of fit based on near or exact replicates. Ann. Statist. 17, 673–683; (1991). Small sample characterizations of near replicate lack of fit tests. J. Amer. Statist. Assoc. 86, 752–756], by considering the groupings as determining special types of clusterings. In order to detect general lack of fit, several such tests are again considered, each based on a different grouping of the observations, and the multiple testing approach given by Baraud et al. [(2003). Adaptive tests of linear hypotheses by model selection. Ann. Statist. 31, 225–251] is followed. Simulation results illustrating the power of the proposed testing procedure are given.     

流动人口女性个体的生育间隔影响因素研究——基于2016年全国流动人口动态监测调查数据

本文采用2016年全国流动人口动态监测调查数据,运用半参数Cox回归对我国流动人口的生育间隔进行分析。结果发现：第一,不仅人口流动会延迟女性的生育时间,而且受教育水平的提高对女性的婚育间隔、第一次生育间隔均有显著的延迟效应。第二,结婚年龄越大,婚后越有可能选择尽早生育,且不同初婚时间对生育间隔的影响差异明显。同时,参加医疗保险对婚育间隔存在显著的缩短效应,而参加生育保险对生育间隔存在显著的延迟效应。越有经济实力以及在工作中担任重要职位的女性越有可能扩大生育间隔;而随着婚育间隔的扩大,第一次生育间隔反而会缩短。第三,初育子女的性别对第一次生育间隔的影响存在显著差异,即若初次生育为女性,则第一次生育间隔会缩短。第四,根据生育政策效果分析发现,放开生育政策虽无法促使女性缩短婚育间隔,但会明显缩短第一次生育间隔。     

Properties of bagged nearest neighbour classifiers

Summary.  It is shown that bagging, a computationally intensive method, asymptotically improves the performance of nearest neighbour classifiers provided that the resample size is less than 69% of the actual sample size, in the case of with-replacement bagging, or less than 50% of the sample size, for without-replacement bagging. However, for larger sampling fractions there is no asymptotic difference between the risk of the regular nearest neighbour classifier and its bagged version. In particular, neither achieves the large sample performance of the Bayes classifier. In contrast, when the sampling fractions converge to 0, but the resample sizes diverge to ∞, the bagged classifier converges to the optimal Bayes rule and its risk converges to the risk of the latter. These results are most readily seen when the two populations have well-defined densities, but they may also be derived in other cases, where densities exist in only a relative sense. Cross-validation can be used effectively to choose the sampling fraction. Numerical calculation is used to illustrate these theoretical properties.     

A comparison of recent nonparametric methods for testing effects in two-by-two factorial designs

The two-way two-levels crossed factorial design is a commonly used design by practitioners at the exploratory phase of industrial experiments. The F-test in the usual linear model for analysis of variance (ANOVA) is a key instrument to assess the impact of each factor and of their interactions on the response variable. However, if assumptions such as normal distribution and homoscedasticity of errors are violated, the conventional wisdom is to resort to nonparametric tests. Nonparametric methods, rank-based as well as permutation, have been a subject of recent investigations to make them effective in testing the hypotheses of interest and to improve their performance in small sample situations. In this study, we assess the performances of some nonparametric methods and, more importantly, we compare their powers. Specifically, we examine three permutation methods (Constrained Synchronized Permutations, Unconstrained Synchronized Permutations and Wald-Type Permutation Test), a rank-based method (Aligned Rank Transform) and a parametric method (ANOVA-Type Test). In the simulations, we generate datasets with different configurations of distribution of errors, variance, factor's effect and number of replicates. The objective is to elicit practical advice and guides to practitioners regarding the sensitivity of the tests in the various configurations, the conditions under which some tests cannot be used, the tradeoff between power and type I error, and the bias of the power on one main factor analysis due to the presence of effect of the other factor. A dataset from an industrial engineering experiment for thermoformed packaging production is used to illustrate the application of the various methods of analysis, taking into account the power of the test suggested by the objective of the experiment.     

Whither jackknifing in stein-rule estimation

In multi-parameter ( multivariate ) estimation, the Stein rule provides minimax and admissible estimators , compromising generally on their unbiasedness. On the other hand, the primary aim of jack-knifing is to reduce the bias of an estimator ( without necessarily compromising on its efficacy ), and, at the same time, jackknifing provides an estimator of the sampling variance of the estimator as well. In shrinkage estimation ( where minimization of a suitably defined risk function is the basic goal ), one may wonder how far the bias-reduction objective of jackknifing incorporates the dual objective of minimaxity ( or admissibility ) and estimating the risk of the estimator ? A critical appraisal of this basic role of jackknifing in shrinkage estimation is made here. Restricted, semi-restricted and the usual versions of jackknifed shrinkage estimates are considered and their performance characteristics are studied . It is shown that for Pitman-type ( local ) alternatives, usually, jackkntfing fails to provide a consistent estimator of the ( asymptotic ) risk of the shrinkage estimator, and a degenerate asymptotic situation arises for the usual fixed alternative case.     

政府统计生态环境建设的系统分析

为了提高统计数据质量, 除了统计系统内部的努力以外,提出了政府统计生态环境建设的新命题。从系统分析的角度,研究了政府统计生态环境的内涵和外延,并分析了政府统计的思想观念环境、体制制度环境、社会信用环境、法制环境、国际环境、社会舆论环境建设的基本问题。     

Sojourning With the Homogeneous Poisson Process

In this pedagogical article, distributional properties, some surprising, pertaining to the homogeneous Poisson process (HPP), when observed over a possibly random window, are presented. Properties of the gap-time that covered the termination time and the correlations among gap-times of the observed events are obtained. Inference procedures, such as estimation and model validation, based on event occurrence data over the observation window, are also presented. We envision that through the results in this article, a better appreciation of the subtleties involved in the modeling and analysis of recurrent events data will ensue, since the HPP is arguably one of the simplest among recurrent event models. In addition, the use of the theorem of total probability, Bayes’ theorem, the iterated rules of expectation, variance and covariance, and the renewal equation could be illustrative when teaching distribution theory, mathematical statistics, and stochastic processes at both the undergraduate and graduate levels. This article is targeted toward both instructors and students.     

城市群经济网络与经济增长——基于大数据与网络分析方法的研究

借助大数据时代下获得的海量数据,本文分析了长三角城市群的经济网络特征,重点研究了城市群经济网络的增长效应。首先,构建了长三角城市群的人口流动网络、企业组织网络与电子商务网络,对其各自的网络结构特征进行了对比。其次,将网络分析方法与空间计量模型结合起来,使用扩展的J检验方法对不同网络结构下的模型设定方法进行了识别,考察了经济网络带来的溢出效应对于城市群经济增长的影响。分析结果显示,三种经济网络下长三角城市群均呈现出了“中心-外围”的网络结构,其中上海、杭州、苏州、南京及无锡位于城市群经济网络的核心圈层。对网络结构的模型识别结果显示,中心城市在长三角城市群经济网络的溢出效应中扮演着重要角色。具体而言,在人口流动网络下,资本、政府行为存在显著为负的网络溢出效应;在企业组织网络下,人口规模、对外开放呈现出显著为正的网络溢出效应;在电子商务网络下,政府行为存在显著为负的网络溢出效应,对外开放呈现出显著为正的网络溢出效应。     

Nontraditional Approaches to Assessing Journal Importance: Case Study of Russian Journals on Earth Sciences

Abstract

Currently, a broad set of bibliometric indices for evaluation of journal quality, the level of its internationalization, and interactions between serials are available. However, some cases require one to obtain more precise methods to assess journals, e.g., when estimating new journals, selecting them into international citation databases, increasing their rank, broadening their readership, or optimizing editorial policy. To cope with new challenges, new approaches have been introduced including altmetrics and various analyses of editorial board composition and impact. Analyzing altmetrics and studying geographic diversity on editorial boards, comparing these data with that of journal authors, and evaluating research efficiency of editorial board members enables one to use new approaches to assess the rank of serials. This paper considers current research reports on altmetrics, geographic diversity, and publication activity of editorial board members of top journals on Earth Sciences published in the Russian Federation and recognized as international serials. It was found that such altmetrics as abstract views, full text views, and a number of viewed papers are now available as additional metrics to evaluate journal quality. Furthermore, provided that the data on altmetrics are complete, they can be considered as a specific predictor for future citations and other citation-based indices. Editorial board analyses demonstrate a correlation of bibliometric indices of editorial board members with that of a journal. As for geographic diversity, only half of the analyzed journals demonstrate a strong correlation between the number of foreign members on editorial boards and geographic representativeness of a journal, mainly due to the local nature of geosciences and trade secret mode in much of mining research. Generally, the obtained findings highlighted the efficiency of new approaches to evaluate journal quality both in the case of the absence of citation-based journal metrics and as an additional tool to traditional indices.     

Improved estimation of the stable laws

Fitting general stable laws to data by maximum likelihood is important but difficult. This is why much research has considered alternative procedures based on empirical characteristic functions. Two problems then are how many values of the characteristic function to select, and how to position them. We provide recommendations for both of these topics. We propose an arithmetic spacing of transform variables, coupled with a recommendation for the location of the variables. It is shown that arithmetic spacing, which is far simpler to implement, closely approximates optimum spacing. The new methods that result are compared in simulation studies with existing methods, including maximum-likelihood. The main conclusion is that arithmetic spacing of the values of the characteristic function, coupled with appropriately limiting the range for these values, improves the overall performance of the regression-type method of Koutrouvelis, which is the standard procedure for estimating general stable law parameters.     

中国城乡价格水平差异研究—基于1995~2005年省级面板数据

中国依然处于社会主义初级阶段,必须不断提高国内经济的市场化程度。但是,二元经济特征是中国经济的特殊国情。在考虑二元经济特征的情况下,应用一价定律理论,以居民消费价格指数和商品销售价格指数作为衡量指标,分别考察了城市部门和农村部门的市场化程度。通过面板数单位根检验,城市部门和农村部门的样本数据均具有良好的稳定性,说明一价定律在国内市场成立。通过标准方差模型和Jarque-Bera模型检验,验证了城市部门较农村部门的市场化程度高。分别比较居民消费价格指数和商品销售价格指数的各种检验结果,充分验证商品销售价格指数增强了一价定律成立,说明增强交易商品的流动性,降低交易成本有利于一价定律的成立,有利于提高国内经济的市场化程度。     

增加值贸易视角下我国区际贸易成本的测算与分解

本文在Novy（2013）的基础之上，利用1997年、2002年与2007年区域间投入产出表，首次基于增加值贸易视角进行了中国区际贸易成本变动的测算与分解。结果显示：首先，不同于传统贸易流量的测度，基于增加值贸易视角的测度表明，1997-2007年的区际贸易成本不仅未有上升，反而大幅下降。其次，尽管当前的区际贸易成本有所下降，但是这种下降主要体现为以内陆地区和初级产品带动的低端化整合。最后，进一步地利用双边分解，本文发现低端化整合的迹象可能在于邻区偏少、产业同构度过高与政策缺失下，东部沿海更多利用国外需求进行替代所致。随着东部沿海的对外依赖程度提升，区际分工整合将会面临“初级产品分工整合加快→服务行业过度出口→遭受出口俘获→初级产品分工整合进一步加快”的恶性循环。因此，进一步转变发展观念、扭转市场分割激励、加快基础设施建设，才能从根本上提升区际整合质量。     

创新试点政策能够引领企业创新吗?———来自国家创新型试点城市的微观证据

本文在理论分析的基础上,以国家创新型试点城市设立为“准自然实验”,采用2005-2016年沪深两市A 股上市公司为样本,利用双重差分法检验了国家创新型城市试点政策对企业创新的影响。研究结果表明:国家创新型城市试点政策显著提高了企业创新水平,并且所得结论经过一系列的稳健性检验依然成立。试点政策不存在时滞效应,且具有持续的促进作用,但因企业规模、技术水平、控股性质和城市规模不同存在显著差异,具体表现为创新试点政策对于中小规模企业、高新技术企业、民营控股企业和大城市企业的创新具有显著的促进作用。作用机制检验表明,创新型城市试点政策主要通过政府财政补贴、提高企业集聚程度、降低制度交易成本作用于企业创新。本文的研究为合理评估国家创新型城市试点政策效应提供了微观证据以及进一步推进企业创新有着重要的政策启示意义。     

Hellinger distance estimation of general bilinear time series models

In the present paper, minimum Hellinger distance estimates for parameters of a bilinear time series model are presented. The probabilistic properties such as stationarity, existence of moments of the stationary distribution and strong mixing property of the model are well known (see for instance [J. Liu, A note on causality and invertibility of a general bilinear time series model, Adv. Appl. Probab. 22 (1990) 247–250; J. Liu, P.J. Brockwell, On the general bilinear time series model, J. Appl. Probab. 25 (1988) 553–564; D.T. Pham, The mixing property of bilinear and generalised random coefficients autoregressive models, Stoch. Process Appl. 23 (1986) 291–300]). We establish, under some mild conditions, the consistency and the asymptotic normality of the minimum Hellinger distance estimates of the parameters of the model.