Comment: Sequential Moment Restrictions in Panel Data

We present a three-stage, nonparametric estimation procedure to recover willingness to pay for housing attributes. In the first stage we estimate a nonparametric hedonic home price function. In the second stage we recover each consumer's taste parameters for product characteristics using first-order conditions for utility maximization. Finally, in the third stage we estimate the distribution of household tastes as a function of household demographics. As an application of our methods, we compare alternative explanations for why blacks choose to live in center cities while whites suburbanize.     

Some Properties of the Normalized Periodogram of a Fractionally Integrated Separable Spatial ARMA (FISSARMA) Model

In this article, we study the properties of the normalized periodogram of the Fractionally Integrated Separable Spatial ARMA (FISSARMA) models. In particular, we establish the asymptotic mean of the normalised periodogram and the asymptotic second-order moments of the normalised Fourier coefficients. We also establish the asymptotic distribution of the normalised periodogram. Some numerical results are also provided.     

乡村振兴战略下农村金融服务差异化监管体系构建

乡村振兴战略释放出强劲的农村金融需求，且呈现多元化发展格局。然而，目前农村金融资金供给与需求之间的不平衡问题突出，因此要充分拓宽农村金融供给渠道，解决乡村振兴的金融服务供给问题。再者农村金融市场易受骗子和谣言影响，新型农村金融机构资金来源渠道狭窄，农村金融市场存在的隐忧和风险不容小觑，建立健全适合农村特征的具有差异化的农村金融管制体系迫在眉睫。     

Globally intensity-reweighted estimators for K- and pair correlation functions

We introduce new estimators of the inhomogeneous K-function and the pair correlation function of a spatial point process as well as the cross K-function and the cross pair correlation function of a bivariate spatial point process under the assumption of second-order intensity-reweighted stationarity. These estimators rely on a ‘global’ normalisation factor which depends on an aggregation of the intensity function, while the existing estimators depend ‘locally’ on the intensity function at the individual observed points. The advantages of our new global estimators over the existing local estimators are demonstrated by theoretical considerations and a simulation study.     

A few statistical principles for data science

In any other circumstance, it might make sense to define the extent of the terrain (Data Science) first, and then locate and describe the landmarks (Principles). But this data revolution we are experiencing defies a cadastral survey. Areas are continually being annexed into Data Science. For example, biometrics was traditionally statistics for agriculture in all its forms but now, in Data Science, it means the study of characteristics that can be used to identify an individual. Examples of non-intrusive measurements include height, weight, fingerprints, retina scan, voice, photograph/video (facial landmarks and facial expressions) and gait. A multivariate analysis of such data would be a complex project for a statistician, but a software engineer might appear to have no trouble with it at all. In any applied-statistics project, the statistician worries about uncertainty and quantifies it by modelling data as realisations generated from a probability space. Another approach to uncertainty quantification is to find similar data sets, and then use the variability of results between these data sets to capture the uncertainty. Both approaches allow ‘error bars’ to be put on estimates obtained from the original data set, although the interpretations are different. A third approach, that concentrates on giving a single answer and gives up on uncertainty quantification, could be considered as Data Engineering, although it has staked a claim in the Data Science terrain. This article presents a few (actually nine) statistical principles for data scientists that have helped me, and continue to help me, when I work on complex interdisciplinary projects.     

坍缩分化与“模块式”应答：对城市社区“碎片化”的反思——兼论一种社区治理的视角转向

社区治理是当今学界的一个热点话题，其中，研究对象类似但结论南辕北辙一直是一个颇为有趣的现象。本文认为，观点矛盾的背后是当下城市社区面临着两种“自然分化”，一方面，在高异质性的城市社区中，“趋同”的人类本能会在社区内部坍缩出各种“小团块”；另一方面，情感辐射递减的特性会让社区利益分化成为常态，因此城市社区并非统一和均质的概念，由此而产生类型差异和研究结论差异是必然结果，进一步细分为“模块”不仅可能而且需要出现在研究中。     

Spatial Optimization of Future Urban Development with Regards to Climate Risk and Sustainability Objectives

Future development in cities needs to manage increasing populations, climate‐related risks, and sustainable development objectives such as reducing greenhouse gas emissions. Planners therefore face a challenge of multidimensional, spatial optimization in order to balance potential tradeoffs and maximize synergies between risks and other objectives. To address this, a spatial optimization framework has been developed. This uses a spatially implemented genetic algorithm to generate a set of Pareto‐optimal results that provide planners with the best set of trade‐off spatial plans for six risk and sustainability objectives: (i) minimize heat risks, (ii) minimize flooding risks, (iii) minimize transport travel costs to minimize associated emissions, (iv) maximize brownfield development, (v) minimize urban sprawl, and (vi) prevent development of greenspace. The framework is applied to Greater London (U.K.) and shown to generate spatial development strategies that are optimal for specific objectives and differ significantly from the existing development strategies. In addition, the analysis reveals tradeoffs between different risks as well as between risk and sustainability objectives. While increases in heat or flood risk can be avoided, there are no strategies that do not increase at least one of these. Tradeoffs between risk and other sustainability objectives can be more severe, for example, minimizing heat risk is only possible if future development is allowed to sprawl significantly. The results highlight the importance of spatial structure in modulating risks and other sustainability objectives. However, not all planning objectives are suited to quantified optimization and so the results should form part of an evidence base to improve the delivery of risk and sustainability management in future urban development.     

Modelling and classification of species abundance: a case study in the Barro Colorado Island plot

Quantifying and modelling the effect of environmental variables on the abundance of species is of great importance in plant ecology and forestry. In this paper, using a log-additive model, the effect of environmental variables on distribution of five species in the Barro Colorado Island plot is modelled. The fitted log-additive models are examined and compared with conventional log-linear models. Finally, a cluster analysis is employed to classify species into groups with similar habitat preferences.     

多尺度下区域绿色交通发展时空演化及影响因素实证研究

为研究影响绿色交通发展的主要影响因素，基于DPSIR（驱动力 压力 状态 影响 响应）模型构建城市绿色交通发展模型框架，以关中平原城市群为研究对象，利用2009～2018年关中平原城市群面板数据，构建城市绿色交通评价指标体系，从城市群和城市尺度下对关中平原城市群绿色交通发展水平进行评价，结合空间自相关法分析其时空演化特征并讨论其影响因素。研究认为，城市群尺度下关中平原绿色交通水平发展速度较为缓慢，存在明显的空间分布差异，呈现“中间高，边缘低”的空间格局，城市尺度下各城市绿色交通发展水平不均衡，且主要影响因素存在明显差异；因此，要充分发挥西安市核心城市作用，推动绿色交通一体化发展，推进和完善城市立体化公共交通体系建设，还要针对城市所处绿色交通发展不同阶段制定持续稳定的响应举措，并随着城市绿色交通发展水平的变化进行调整。     

邯郸市旅游景点空间格局及其多尺度特征分析

城市旅游景点的空间分布格局及其多尺度特征，是城市旅游发展规划的重要依据。以邯郸市466个旅游景点以及29个A级景点为研究对象，借助ArcGIS10.2和Crimatat 3.3软件，运用平均最近邻指数、Ripley''s L函数、核密度分析、空间等级聚类分析方法研究旅游景点的空间分布格局及其多尺度特征。结果表明：（1）邯郸市旅游景点在多尺度空间上均属于聚类分布，空间特征尺度为6.1 km；而A级景区则主要表现为随机分布，邯郸市旅游业的发展仍存在一定的差距；（2）邯郸市旅游景点形成了以主城区为中心，多个热点区在周围环绕的旅游景点空间分布格局；A级景点则在西北部的武安、西南部的涉县以及中部主城区形成三个热点区；而东部广平、馆陶界内的温泉度假景区的建设，仍未形成聚集规模，需要加大发展力度。