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英国部门放缓：传导概率与经济联系的证据AI 解读

Summary This paper studies spillovers across macroeconomic sectors in the United Kingdom, using data from the Bank of England's Flow of Funds statistics. We combine two different approaches to quantify the spread of economic deterioration to assess whether sectors with large bilateral economic linkages as measured through network data have a greater statistical likelihood of spillovers between them. The combination of both approaches reveals the Monetary Financial…

可能误设下逻辑回归的稀疏网络渐近理论AI 解读

Consider a bipartite network where N consumers choose to buy or not to buy M different products. This paper considers the properties of the logit fit of the N × M array of “ i ‐buys‐ j ” purchase decisions, Y = [ Y i j ] 1 ≤ i ≤ N , 1 ≤ j ≤ M , onto a vector of known functions of consumer and product attributes under asymptotic sequences where (i) both N and M grow large, (ii) the average number of products purchased per consumer is finite in the limit, (iii) there exists…

空间单位根与伪回归AI 解读

This paper proposes a model for, and investigates the consequences of, strong spatial dependence in economic variables. Our findings echo those of the corresponding “unit root” time series literature: Spatial unit root processes induce spuriously significant regression results, even with clustered standard errors or spatial HAC corrections. We develop large‐sample valid unit root and stationarity tests that can detect such strong spatial dependence. Finally, we use…

群组形成实验中同伴效应的随机化检验AI 解读

Measuring the effect of peers on individuals' outcomes is a challenging problem, in part because individuals often select peers who are similar in both observable and unobservable ways. Group formation experiments avoid this problem by randomly assigning individuals to groups and observing their responses; for example, do first‐year students have better grades when they are randomly assigned roommates who have stronger academic backgrounds? In this paper, we propose…

团队中的生产与学习AI 解读

To what extent is a worker's human capital growth affected by the quality of his coworkers? To answer this question, we develop and estimate a model in which the productivity and the human capital growth of an individual depend on the average human capital of his coworkers. The measured production function is supermodular: The marginal product of a more knowledgeable individual is increasing in the human capital of his coworkers. The measured human capital accumulation…

具有投影一致性、稀疏性与可学习性的潜在位置网络模型AI 解读

When modeling network data using a latent position model, it is typical to assume that the nodes’ positions are independently and identically distributed. However, this assumption implies the average node degree grows linearly with the number of nodes, which is inappropriate when the graph is thought to be sparse. We propose an alternative assumption—that the latent positions are generated according to a Poisson point process—and show that it is compatible with various…

度修正随机块模型的调整卡方检验AI 解读

We propose a goodness-of-fit test for degree-corrected stochastic block models (DCSBM). The test is based on an adjusted chi-square statistic for measuring equality of means among groups of n multinomial distributions with d1,…,dn observations. In the context of network models, the number of multinomials, n, grows much faster than the number of observations, di, corresponding to the degree of node i, hence the setting deviates from classical asymptotics. We show that a…

非线性网络自回归AI 解读

We study general nonlinear models for time series networks of integer and continuous-valued data. The vector of high-dimensional responses, measured on the nodes of a known network, is regressed nonlinearly on its lagged value and on lagged values of the neighboring nodes by employing a smooth link function. We study stability conditions for such multivariate process and develop quasi-maximum likelihood inference when the network dimension is increasing. In addition, we…

具有高阶空间或社会网络交互的联立方程模型AI 解读

This paper develops an estimation methodology for network data generated from a system of simultaneous equations, which allows for network interdependencies via spatial lags in the endogenous and exogenous variables, as well as in the disturbances. By allowing for higher-order spatial lags, our specification provides important flexibility in modeling network interactions. The estimation methodology builds, among others, on the two-step generalized method of moments…

如何避免相关性检验中的零功效陷阱AI 解读

In testing for correlation of the errors in regression models, the power of tests can be very low for strongly correlated errors. This counterintuitive phenomenon has become known as the “zero-power trap.” Despite a considerable amount of literature devoted to this problem, mainly focusing on its detection, a convincing solution has not yet been found. In this article, we first discuss theoretical results concerning the occurrence of the zero-power trap phenomenon. Then, we…

黎曼流形上空间点过程强度函数的非参数估计AI 解读

Summary This paper is concerned with nonparametric estimation of the intensity function of a point process on a Riemannian manifold. It provides a first-order asymptotic analysis of the proposed kernel estimator for Poisson processes, supplemented by empirical work to probe the behaviour in finite samples and under other generative regimes. The investigation highlights the scope for finite-sample improvements by allowing the bandwidth to adapt to local curvature.

异质信念下大型贝叶斯博弈的计量推断AI 解读

Econometric models of strategic interactions among people or firms have received a great deal of attention in the literature. Less attention has been paid to the role of the underlying assumptions about the way agents form beliefs about other agents. We focus on a single large Bayesian game with idiosyncratic strategic neighborhoods and develop an approach of empirical modeling that relaxes the assumption of rational expectations and allows the players to form beliefs…

随机实验中溢出效应的识别与估计AI 解读

I study identification, estimation and inference for spillover effects in experiments where units’ outcomes may depend on the treatment assignments of other units within a group. I show that the commonly-used reduced-form linear-in-means regression identifies a weighted sum of spillover effects with some negative weights, and that the difference in means between treated and controls identifies a combination of direct and spillover effects entering with different signs. I…

工具相关性时变下美国货币政策冲击的汇率效应与溢出识别AI 解读

Summary We propose a novel econometric approach to estimating time‐varying policy effects using external instruments in the presence of time‐varying instrument relevance in a factor‐augmented VAR model with data on the United States, Canada, Germany, Japan, and the United Kingdom. We find that US monetary policy shocks are an important driver of the exchange rate movements, with no delayed overshooting. We show that estimates of spillover effects of US monetary policy shocks…

对《两个数据集的故事：网络样本推断的代表性与可推广性》的讨论AI 解读

I congratulate the authors on their timely and insightful article. Since the advent of network analysis, there has been the question of the meaning of sample size in a network setting, which in the...

小型网络中的检验功效与多重共线性：关于网络样本推断的评论AI 解读

The recent work by Krivitsky, Coletti & Hens [KCH] provides an important new contribution to the Exponential-Family Random Graph Models [ERGMs], a start-to-finish approach to dealing with multi-network ERGMs. Although multi-network ERGMs have been around for a while (mostly in the form of block-diagonal models and multi-level ERGMs, see Duxbury and Wertsching (2023), Wang et al. (2013), Slaughter and Koehly (2016)), not much care has been given to the estimation and…

两个数据集的故事：网络样本推断的代表性与可推广性AI 解读

The last two decades have seen considerable progress in foundational aspects of statistical network analysis, but the path from theory to application is not straightforward.Two large, heterogeneous samples of small networks of within-household contacts in Belgium were collected using two different but complementary sampling designs: one smaller but with all contacts in each household observed, the other larger and more representative but recording contacts of only one person…

关于《两个数据集的故事：网络样本推断的代表性与可推广性》的讨论AI 解读

The notions of sample and population have been at the heart of statistics since R.A. Fisher and others distinguished sample quantities from population quantities. While sample-to-population inferen...

协变量引导的潜在交互模型：校正鸟类与植物互动预测的地理及分类偏差AI 解读

Reductions in natural habitats urge that we better understand species’ interconnection and how biological communities respond to environmental changes. However, ecological studies of species’ interactions are limited by their geographic and taxonomic focus which can distort our understanding of interaction dynamics. We focus on bird–plant interactions that refer to situations of potential fruit consumption and seed dispersal. We develop an approach for predicting species’…

快速黎曼优化下的广义低秩加稀疏张量估计AI 解读

We investigate a generalized framework to estimate a latent low-rank plus sparse tensor, where the low-rank tensor often captures the multi-way principal components and the sparse tensor accounts for potential model mis-specifications or heterogeneous signals that are unexplainable by the low-rank part. The framework flexibly covers both linear and generalized linear models, and can easily handle continuous or categorical variables. We propose a fast algorithm by integrating…

通过分类实现 Metropolis–Hastings 后验采样AI 解读

This article develops a Bayesian computational platform at the interface between posterior sampling and optimization in models whose marginal likelihoods are difficult to evaluate. Inspired by contrastive learning and Generative Adversarial Networks (GAN), we reframe the likelihood function estimation problem as a classification problem. Pitting a Generator, who simulates fake data, against a Classifier, who tries to distinguish them from the real data, one obtains…

多层随机块模型中的偏差校正谱聚类AI 解读

We consider the problem of estimating common community structures in multi-layer stochastic block models, where each single layer may not have sufficient signal strength to recover the full community structure. In order to efficiently aggregate signal across different layers, we argue that the sum-of-squared adjacency matrices contain sufficient signal even when individual layers are very sparse. Our method uses a bias-removal step that is necessary when the squared noise…

极稀疏网络的一般成对比较模型AI 解读

Statistical estimation using pairwise comparison data is an effective approach to analyzing large-scale sparse networks. In this article, we propose a general framework to model the mutual interactions in a network, which enjoys ample flexibility in terms of model parameterization. Under this setup, we show that the maximum likelihood estimator for the latent score vector of the subjects is uniformly consistent under a near-minimal condition on network sparsity. This…

含离散节点协变量的大型随机区块模型谱估计AI 解读

In many applications of network analysis, it is important to distinguish between observed and unobserved factors affecting network structure. We show that a network model with discrete unobserved link heterogeneity and binary (or discrete) covariates corresponds to a stochastic blockmodel (SBM). We develop a spectral estimator for the effect of covariates on link probabilities, exploiting the correspondence of SBMs and generalized random dot product graphs (GRDPG). We show…