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Modeling Endogenous Mobility in Earnings Determination

收入决定中的内生工作流动建模

We evaluate the bias from endogenous job mobility in fixed-effects estimates of worker- and firm-specific earnings heterogeneity using longitudinally linked employer–employee data from the LEHD infrastructure file system of the U.S. Census Bureau. First, we propose two new residual diagnostic tests of the assumption that mobility is exogenous to unmodeled determinants of earnings. Both tests reject exogenous mobility. We relax exogenous mobility by modeling the matched data…

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Intrinsic Gaussian Processes on Complex Constrained Domains

复杂约束域上的内蕴高斯过程

Summary We propose a class of intrinsic Gaussian processes (GPs) for interpolation, regression and classification on manifolds with a primary focus on complex constrained domains or irregularly shaped spaces arising as subsets or submanifolds of R, R2, R3 and beyond. For example, intrinsic GPs can accommodate spatial domains arising as complex subsets of Euclidean space. Intrinsic GPs respect the potentially complex boundary or interior conditions as well as the intrinsic…

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Differential Markov random field analysis with an application to detecting differential microbial community networks

差异马尔可夫随机场分析及微生物群落网络差异检测

Micro-organisms such as bacteria form complex ecological community networks that can be greatly influenced by diet and other environmental factors. Differential analysis of microbial community structures aims to elucidate systematic changes during an adaptive response to changes in environment. In this paper, we propose a flexible Markov random field model for microbial network structure and introduce a hypothesis testing framework for detecting differences between networks,…

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Randomization tests of causal effects under interference

干扰下因果效应的随机化检验

Many causal questions involve interactions between units, also known as interference, for example between individuals in households, students in schools, or firms in markets. In this paper we formalize the concept of a conditioning mechanism, which provides a framework for constructing valid and powerful randomization tests under general forms of interference. We describe our framework in the context of two-stage randomized designs and apply our approach to a randomized…

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Sequential change-point detection based on nearest neighbors

基于最近邻的序贯变点检测

We propose a new framework for the detection of change-points in online, sequential data analysis. The approach utilizes nearest neighbor information and can be applied to sequences of multivariate observations or non-Euclidean data objects, such as network data. Different stopping rules are explored, and one specific rule is recommended due to its desirable properties. An accurate analytic approximation of the average run length is derived for the recommended rule, making…

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Identification and estimation of linear social interaction models

线性社会互动模型的识别与估计

This paper has two parts. The first part derives the identification conditions for higher-order social interaction models. In the case where social effects depend on the distance between individuals, the upper bounds on the network diameters for non-identified models are derived. Many network properties of non-identified models in the literature can be derived from these upper bounds. This part analyzes which fixed effect elimination methods require less restrictive…

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A weak law for moments of pairwise stable networks

两两稳定网络矩的弱大数定律

This paper studies the dependence structure of sparse networks realized according to a strategic model of network formation with homophilous agents. We argue that equilibrium selection and chains of indirect dependence generated by strategic interactions are the main drivers of network dependence. Drawing on results in random-graph theory, we derive weak-dependence conditions under which a law of large numbers holds for a general class of network moments. A key condition…

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Who Wants Affordable Housing in Their Backyard? An Equilibrium Analysis of Low-Income Property Development

谁愿意让保障性住房建在自家附近?低收入住房开发的均衡分析

We nonparametrically estimate spillovers of properties financed by the Low Income Housing Tax Credit (LIHTC) onto neighborhood residents by developing a new difference-in-differences style estimator. LIHTC development revitalizes low-income neighborhoods, increasing house prices 6.5 percent, lowering crime rates, and attracting racially and income diverse populations. LIHTC development in higher-income areas causes house price declines of 2.5 percent and attracts…

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Modeling systemic risk with Markov Switching Graphical SUR models

用马尔可夫转换图结构SUR模型刻画系统性风险

We propose a Markov Switching Graphical Seemingly Unrelated Regression (MS-GSUR) model to investigate time-varying systemic risk based on a range of multi-factor asset pricing models. Methodologically, we develop a Markov Chain Monte Carlo (MCMC) scheme in which latent states are identified on the basis of a novel weighted eigenvector centrality measure. An empirical application to the constituents of the S&P100 index shows that cross-firm connectivity significantly…

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Testing for Trends in High-Dimensional Time Series

高维时间序列的趋势检验

The article considers statistical inference for trends of high-dimensional time series. Based on a modified L2 distance between parametric and nonparametric trend estimators, we propose a de-diagonalized quadratic form test statistic for testing patterns on trends, such as linear, quadratic, or parallel forms. We develop an asymptotic theory for the test statistic. A Gaussian multiplier testing procedure is proposed and it has an improved finite sample performance. Our…

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Probabilistic Community Detection With Unknown Number of Communities

社区数量未知时的概率社区检测

A fundamental problem in network analysis is clustering the nodes into groups which share a similar connectivity pattern. Existing algorithms for community detection assume the knowledge of the number of clusters or estimate it a priori using various selection criteria and subsequently estimate the community structure. Ignoring the uncertainty in the first stage may lead to erroneous clustering, particularly when the community structure is vague. We instead propose a…

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Statistical Inference in a Directed Network Model With Covariates

含协变量的有向网络模型中的统计推断

Ting Yana http://orcid.org/0000-0001-9830-6646, Binyan Jiangb, Stephen E. Fienbergc* & Chenlei Lengd*a Department of Statistics, Central China Normal University, Wuhan, Chinab Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, Chinac Department of Statistics, Heinz College, Machine Learning Department, Cylab, Carnegie Mellon University, Pittsburgh, PAd Department of Statistics, University of Warwick and Alan Turing Institute, Coventry, UKCONTACT…

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Combinatorial inference for graphical models

图模型的组合推断

We propose a new family of combinatorial inference problems for graphical models. Unlike classical statistical inference where the main interest is point estimation or parameter testing, combinatorial inference aims at testing the global structure of the underlying graph. Examples include testing the graph connectivity, the presence of a cycle of certain size, or the maximum degree of the graph. To begin with, we study the information-theoretic limits of a large family of…

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Portal nodes screening for large scale social networks

大规模社交网络中的门户节点筛选

Network autoregression model (NAM), as a powerful tool to study user social behaviors on large scale social networks, has drawn great attention in recent years. In this paper, we are interested in identifying the influential users (i.e., portal nodes) in a social network under the framework of NAM. Especially, we consider the autoregression model that allows to have a heterogeneous and sparse network effect coefficients. Therefore, the portal nodes take influential powers…

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ESTIMATION OF SPATIAL AUTOREGRESSIONS WITH STOCHASTIC WEIGHT MATRICES

随机权重矩阵下空间自回归模型的估计

We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weight matrices. Allowing a general spatial linear process form for the disturbances that permits many common types of error specifications as well as potential ‘long memory’, we provide sufficient conditions for consistency and asymptotic normality of instrumental variables, ordinary least squares, and pseudo maximum likelihood estimates. The implications of popular weight matrix…

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NETS: Network estimation for time series

NETS:时间序列网络估计

Summary We model a large panel of time series as a vector autoregression where the autoregressive matrices and the inverse covariance matrix of the system innovations are assumed to be sparse. The system has a network representation in terms of a directed graph representing predictive Granger relations and an undirected graph representing contemporaneous partial correlations. A LASSO algorithm called NETS is introduced to estimate the model. We apply the methodology to…

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Identification and Estimation of Dynamic Games When Players’ Beliefs Are Not in Equilibrium

参与者信念不处于均衡时动态博弈的识别与估计

This article deals with the identification and estimation of dynamic games when players’ beliefs about other players’ actions are biased, that is, beliefs do not represent the probability distribution of the actual behaviour of other players conditional on the information available. First, we show that an exclusion restriction, typically used to identify empirical games, provides testable non-parametric restrictions of the null hypothesis of equilibrium beliefs in dynamic…

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Constrained likelihood for reconstructing a directed acyclic Gaussian graph

通过约束似然重建高斯有向无环图

Directed acyclic graphs are widely used to describe directional pairwise relations. Such relations are estimated by reconstructing a directed acyclic graph's structure, which is challenging when the ordering of nodes of the graph is unknown. In such a situation, existing methods such as the neighbourhood and search-and-score methods have high estimation errors or computational complexities, especially when a local or sequential approach is used to enumerate edge directions…

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Dividend payments as a response to peer influence

股利支付对同业影响的响应

I show dividend policies have peer effects. My estimates indicate that firms speed up the time taken to make a dividend change by about 1.5 quarters and increase payments by 16% in response to peer changes. The peer effects matter in increases but not decreases. In contrast to dividends, repurchases show no peer effects. In addition, announcement returns indicate that investors partially anticipate the consequences of peer effects. Overall, peer interdependencies account for…

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A critical threshold for design effects in network sampling

网络抽样设计效应的临界阈值

Web crawling, snowball sampling, and respondent-driven sampling (RDS) are three types of network sampling techniques used to contact individuals in hard-to-reach populations. This paper studies these procedures as a Markov process on the social network that is indexed by a tree. Each node in this tree corresponds to an observation and each edge in the tree corresponds to a referral. Indexing with a tree (instead of a chain) allows for the sampled units to refer multiple…

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GEL estimation and tests of spatial autoregressive models

空间自回归模型的广义经验似然估计与检验

This paper considers the generalized empirical likelihood (GEL) estimation and tests of high order spatial autoregressive (SAR) models by exploring an inherent martingale structure. The GEL estimator has the same asymptotic distribution as the generalized method of moments estimator explored with same moment conditions for estimation, but circumvents a first step estimation of the optimal weighting matrix with a preliminary estimator, and thus can be robust to unknown…

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Culture and Taxes

文化与税收

We propose a difference-in-differences strategy to identify the existence of interjurisdictional tax competition. Our strategy rests on differences between desired tax levels determined by culture-specific preferences and equilibrium tax levels determined by fiscal externalities and by preferences. While preferences differ systematically between French-speaking and German-speaking Swiss municipalities, local income tax burdens exhibit smooth spatial gradients. To qualify the…

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Group SLOPE – Adaptive Selection of Groups of Predictors

Group SLOPE:预测变量组的自适应选择

Damian Brzyskiab*, Alexej Gossmannc, Weijie Sud & Małgorzata Bogdanea Department of Epidemiology and Biostatistics, Indiana University, Bloomington, INb Institute of Mathematics, Jagiellonian University, Cracow, Polandc Bioinnovation PhD Program, Tulane University, New Orleans, LAd Department of Statistics, University of Pennsylvania, Philadelphia, PAe Institute of Mathematics, University of Wroclaw, Wroclaw, PolandCONTACT Damian Brzyski dbrzyski@iu.edu Department of…

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Spatially Dependent Multiple Testing Under Model Misspecification, With Application to Detection of Anthropogenic Influence on Extreme Climate Events

模型误设下的空间相依多重检验及极端气候归因应用

The Weather Risk Attribution Forecast (WRAF) is a forecasting tool that uses output from global climate models to make simultaneous attribution statements about whether and how greenhouse gas emissions have contributed to extreme weather across the globe. However, in conducting a large number of simultaneous hypothesis tests, the WRAF is prone to identifying false “discoveries.” A common technique for addressing this multiple testing problem is to adjust the procedure in a…

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