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工资支付违约中的互补性与惯例AI 解读

We present and estimate a model with strategic complementarities in firms' choices of on-time or delayed wage payment. Linked employer-employee panel data from Russia facilitate identification of the endogenous interactions through fixed effects for firms, workers, and local labor markets, and instrumental variables based on policy interventions. The estimated reaction function displays strongly positive neighborhood effects, and the estimated feedback loops-worker quits,…

自适应变系数时空模型AI 解读

Summary We propose an adaptive varying-coefficient spatiotemporal model for data that are observed irregularly over space and regularly in time. The model is capable of catching possible non-linearity (both in space and in time) and non-stationarity (in space) by allowing the auto-regressive coefficients to vary with both spatial location and an unknown index variable. We suggest a two-step procedure to estimate both the coefficient functions and the index variable, which is…

异质总体数据的加权正态空间扫描统计量AI 解读

In geographical spatial epidemiology and disease surveillance, all the existing spatial scan methods for cluster detection using continuous data are designed for evaluating clusters of individuals and analyzing individual-level data. Motivated by growing demands to study the spatial heterogeneity of continuous measures in population data, such as mortality rates, survival rates, average body mass indexes and pollution at state, county, and census tract levels, we propose a…

计量经济学估计量的偏度与峰度AI 解读

We derive the approximate results for two standardized measures of deviation from normality, namely, the skewness and excess kurtosis coefficients, for a class of econometric estimators. The results are built on a stochastic expansion of the moment condition used to identify the econometric estimator. The approximate results can be used not only to study the finite sample behaviour of a particular estimator, but also to compare the finite sample properties of two…

非齐次空间点过程的两步估计AI 解读

Summary The paper is concerned with parameter estimation for inhomogeneous spatial point processes with a regression model for the intensity function and tractable second-order properties (K-function). Regression parameters are estimated by using a Poisson likelihood score estimating function and in the second step minimum contrast estimation is applied for the residual clustering parameters. Asymptotic normality of parameter estimates is established under certain mixing…

风险的Granger因果关系与金融市场极端风险溢出检验AI 解读

Controlling and monitoring extreme downside market risk are important for financial risk management and portfolio/investment diversification. In this paper, we introduce a new concept of Granger causality in risk and propose a class of kernel-based tests to detect extreme downside risk spillover between financial markets, where risk is measured by the left tail of the distribution or equivalently by the Value at Risk (VaR). The proposed tests have a convenient asymptotic…

干预与因果关系：利用动态贝叶斯网络预测交通流AI 解读

Real-time traffic flow data across entire networks can be used in a traffic management system to monitor current traffic flows so that traffic can be directed and managed efficiently. Reliable short-term forecasting models of traffic flows are crucial for the success of any traffic management system. The model proposed in this article for forecasting traffic flows is a multivariate Bayesian dynamic model called the multiregression dynamic model (MDM). This model is an…

内禀自回归时空模型及其在汇总出生结局中的应用AI 解读

A class of hierarchical Bayesian models is proposed for adverse birth outcomes such as preterm birth, which are assumed to follow a conditional binomial distribution. The log-odds of an adverse outcome in a particular county, logit(pi), follow a linear model that includes observed covariates and normally-distributed random effects. Spatial dependence between neighboring regions is allowed for by including an intrinsically autoregressive (IAR) prior or an IAR convolution…

古代森林制图：利用化石花粉记录推断森林组成的时空趋势AI 解读

Ecologists use the relative abundance of fossil pollen in sediments to estimate how tree species abundances change over space and time. To predict historical forest composition and quantify the available information, we build a Bayesian hierarchical model of forest composition in central New England, USA, based on pollen in a network of ponds. The critical relationships between abundances of taxa in the pollen record and abundances as actual vegetation are estimated for the…

用于基因关联分析的对数线性模型AI 解读

We describe a class of log-linear models for the detection of interactions in high-dimensional genomic data. This class of models leads to a Bayesian model selection algorithm that can be applied to data that have been reduced to contingency tables using ranks of observations within subjects, and discretization of these ranks within gene/network components. Many normalization issues associated with the analysis of genomic data are thereby avoided. A prior density based on…

动态 PET 数据的非参数残留函数分析：健康受试者脑部 FDG 研究AI 解读

Kinetic analysis is used to extract metabolic information from dynamic positron emission tomography (PET) uptake data. The theory of indicator dilutions, developed in the seminal work of Meier and Zierler (1954), provides a probabilistic framework for representation of PET tracer uptake data in terms of a convolution between an arterial input function and a tissue residue. The residue is a scaled survival function associated with tracer residence in the tissue. Nonparametric…

利用联合稀疏回归模型估计偏相关AI 解读

In this paper, we propose a computationally efficient approach -space(Sparse PArtial Correlation Estimation)- for selecting non-zero partial correlations under the high-dimension-low-sample-size setting. This method assumes the overall sparsity of the partial correlation matrix and employs sparse regression techniques for model fitting. We illustrate the performance of space by extensive simulation studies. It is shown that space performs well in both non-zero partial…

从实验数据推断最优同伴分配AI 解读

This article studies the problem of optimally dividing individuals into peer groups to maximize social gains from heterogeneous peer effects. The specific setting analyzed here concerns efficient ways of allocating roommates in college dormitories. Using confidential data on a sample of Dartmouth College freshmen who were randomly assigned to be roommates, the article derives efficient roommate pairing rules, based on demographic and academic background, which maximize…

随机场阵列的中心极限定理与一致大数定律AI 解读

Over the last decades, spatial-interaction models have been increasingly used in economics. However, the development of a sufficiently general asymptotic theory for nonlinear spatial models has been hampered by a lack of relevant central limit theorems (CLTs), uniform laws of large numbers (ULLNs) and pointwise laws of large numbers (LLNs). These limit theorems form the essential building blocks towards developing the asymptotic theory of M-estimators, including maximum…

通过社会网络识别同伴效应AI 解读

We provide new results regarding the identification of peer effects. We consider an extended version of the linear-in-means model where interactions are structured through a social network. We assume that correlated unobservables are either absent, or treated as network fixed effects. We provide easy-to-check necessary and sufficient conditions for identification. We show that endogenous and exogenous effects are generally identified under network interaction, although…

利用积分嵌套拉普拉斯近似进行潜在高斯模型的近似贝叶斯推断AI 解读

Summary Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalized) linear models, (generalized) additive models, smoothing spline models, state space models, semiparametric regression, spatial and spatiotemporal models, log-Gaussian Cox processes and geostatistical and geoadditive models. We consider approximate Bayesian inference in a popular subset of structured additive…

因子 GARCH 模型的渐近理论AI 解读

This paper investigates the asymptotic theory for a factor GARCH (generalized autoregressive conditional heteroskedasticity) model. Sufficient conditions for asymptotic stability and existence of moments are established. These conditions allow for volatility spillover and integrated GARCH. We then show the strong consistency and asymptotic normality of the quasi–maximum likelihood estimator (QMLE) of the model parameters. The results are obtained under the finiteness of the…

非齐次空间点过程的快速分块方差估计AI 解读

We introduce two new variance estimation procedures that use non-overlapping and overlapping blocks, respectively. The non-overlapping blocks estimator can be viewed as the limit of the thinned block bootstrap estimator recently proposed in Guan Loh (2007), by letting the number of thinned processes and bootstrap samples therein both increase to infinity. The non-overlapping blocks estimator can be obtained quickly since it does not require any thinning or bootstrap steps,…

实数空间上不规则间隔数据的傅里叶分析AI 解读

Summary The purpose of the paper is to propose a frequency domain approach for irregularly spaced data on Rd. We extend the original definition of a periodogram for time series to that for irregularly spaced data and define non-parametric and parametric spectral density estimators in a way that is similar to the classical approach. Introduction of the mixed asymptotics, which are one of the asymptotics for irregularly spaced data, makes it possible to provide asymptotic…

图数据与不规则多维数据的多尺度方法AI 解读

Summary For regularly spaced one-dimensional data, wavelet shrinkage has proven to be a compelling method for non-parametric function estimation. We create three new multiscale methods that provide wavelet-like transforms both for data arising on graphs and for irregularly spaced spatial data in more than one dimension. The concept of scale still exists within these transforms, but as a continuous quantity rather than dyadic levels. Further, we adapt recent empirical…

具有社会互动的同步博弈中的统计推断AI 解读

This paper studies inference in a continuous time game where an agent's decision to quit an activity depends on the participation of other players. In equilibrium, similar actions can be explained not only by direct influences but also by correlated factors. Our model can be seen as a simultaneous duration model with multiple decision makers and interdependent durations. We study the problem of determining the existence and uniqueness of equilibrium stopping strategies in…

空间依赖的大样本推断AI 解读

We consider cross-sectional data that exhibit no spatial correlation, but are feared to be spatially dependent. We demonstrate that a spatial version of the stochastic volatility model of financial econometrics, entailing a form of spatial autoregression, can explain such behaviour. The parameters are estimated by pseudo-Gaussian maximum likelihood based on log-transformed squares, and consistency and asymptotic normality are established. Asymptotically valid tests for…

工作场所的社会关系与激励：来自人事数据的证据AI 解读

We present evidence on the effect of social connections between workers and managers on productivity in the workplace. To evaluate whether the existence of social connections is beneficial to the firm's overall performance, we explore how the effects of social connections vary with the strength of managerial incentives and worker's ability. To do so, we combine panel data on individual worker's productivity from personnel records with a natural field experiment in which we…

友谊的经济模型：同质性、少数群体与隔离AI 解读

We develop a model of friendship formation that sheds light on segregation patterns observed in social and economic networks. Individuals have types and see type-dependent benefits from friendships. We examine the properties of a steady-state equilibrium of a matching process of friendship formation. We use the model to understand three empirical patterns of friendship formation: (i) larger groups tend to form more same-type ties and fewer other-type ties than small groups,…