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超高维异质分类数据的类别自适应变量筛选AI 解读

The populations of interest in modern studies are very often heterogeneous. The population heterogeneity, the qualitative nature of the outcome variable and the high dimensionality of the predictors pose significant challenge in statistical analysis. In this article, we introduce a category-adaptive screening procedure with high-dimensional heterogeneous data, which is to detect category-specific important covariates. The proposal is a model-free approach without any…

用 V-learning 估计移动健康中的动态处理策略AI 解读

The vision for precision medicine is to use individual patient characteristics to inform a personalized treatment plan that leads to the best possible health-care for each patient. Mobile technologies have an important role to play in this vision as they offer a means to monitor a patient's health status in real-time and subsequently to deliver interventions if, when, and in the dose that they are needed. Dynamic treatment regimes formalize individualized treatment plans as…

离散结果 Copula 回归模型的非参数估计AI 解读

Multivariate discrete outcomes are common in a wide range of areas including insurance, finance, and biology. When the interplay between outcomes is significant, quantifying dependencies among interrelated variables is of great importance. Due to their ability to accommodate dependence flexibly, copulas are being applied increasingly. Yet, the application of copulas on discrete data is still in its infancy; one of the biggest barriers is the nonuniqueness of copulas, calling…

采用异方差反演 Copula 的实时宏观经济预测AI 解读

There is a growing interest in allowing for asymmetry in the density forecasts of macroeconomic variables. In multivariate time series, this can be achieved with a copula model, where both serial and cross-sectional dependence is captured by a copula function, and the margins are nonparametric. Yet most existing copulas cannot capture heteroscedasticity well, which is a feature of many economic and financial time series. To do so, we propose a new copula created by the…

两种含内生性的分位数模型比较AI 解读

This article studies the relationship between the two most-used quantile models with endogeneity: the instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen 2005) and the local quantile treatment effects (LQTE) model (Abadie, Angrist, and Imbens 2002). The key condition of the IVQR model is the rank similarity assumption, a restriction on the evolution of individual ranks across treatment states, under which population quantile treatment effects…

匹配调查与行政数据中的收入动态和测量误差AI 解读

This article analyzes earnings dynamics and measurement error using a matched longitudinal sample of individuals’ survey and administrative earnings. In line with previous literature, the reported differences are characterized by both persistent and transitory factors. Estimating a model consistent with past results, survey errors are mean-reverting when administrative reports are assumed correct, but not when this assumption is relaxed. Although most reported earnings…

用于分析金融泡沫与崩盘的双问题调查指标AI 解读

This article proposes a new double-question survey whereby an individual is presented with two sets of questions; one on beliefs about current asset values and another on price expectations. A theoretical asset pricing model with heterogeneous agents is advanced and the existence of a negative relationship between price expectations and asset valuations is established, and is then tested using survey results on equity, gold, and house prices. Leading indicators of bubbles…

金融时间序列尾部依赖结构差异的检测AI 解读

An accurate assessment of tail inequalities and tail asymmetries of financial returns is key for risk management and portfolio allocation. We propose a new test procedure for detecting the full extent of such structural differences in the dependence of bivariate extreme returns. We decompose the testing problem into piecewise multiple comparisons of Cramér–von Mises distances of tail copulas. In this way, tail regions that cause differences in extreme dependence can be…

处理状态与中介变量均内生的随机前沿模型AI 解读

Government policies are frequently used to promote productivity. Some policies are designed to enhance production technology, while others are meant to improve production efficiency. An important issue to consider when designing and evaluating policies is whether a mediator is required or effective in achieving the desired final outcome. To better understand and evaluate the policies, we propose a new stochastic frontier model with a treatment status and a mediator, both of…

文字成为新数字：基于新闻的商业周期同步指数AI 解读

I construct a daily business cycle index based on quarterly GDP growth and textual information contained in a daily business newspaper. The newspaper data are decomposed into time series representing news topics, while the business cycle index is estimated using the topics and a time-varying dynamic factor model where dynamic sparsity is enforced upon the factor loadings using a latent threshold mechanism. The resulting index classifies the phases of the business cycle with…

高斯 Copula 是否合适？AI 解读

We derive computationally simple and intuitive expressions for score tests of Gaussian copulas against generalized hyperbolic alternatives, including symmetric and asymmetric Student t, and many other examples. We decompose our tests into third and fourth moment components, and obtain one-sided Likelihood Ratio analogs, whose standard asymptotic distribution we provide. Our Monte Carlo exercises confirm the reliable size of parametric bootstrap versions of our tests, and…

基于多元高斯过程的灵活混合物配比与总量模型AI 解读

Many products and services can be described as mixtures of components whose proportions sum to one. Specialized models have been developed for relating the mixture component proportions to response variables, such as the preference, quality, and liking of products. If only the mixture component proportions affect the response variable, mixture models suffice to analyze the data. In case the total amount of the mixture also affects the response variable, mixture-amount models…

条件外生匹配下平均匹配函数的识别与效率界AI 解读

Consider two heterogenous populations of agents who, when matched, jointly produce an output, Y. For example, teachers and classrooms of students together produce achievement, parents raise children, whose life outcomes vary in adulthood, assembly plant managers and workers produce a certain number of cars per month, and lieutenants and their platoons vary in unit effectiveness. Let W∈W={w1,…,wJ}$W\in \mathbb {W}=\lbrace w_{1},\ldots,w_{J}\rbrace $ and X∈X={x1,…,xK}$X\in \mathbb {X}=\lbrace x_{1},\ldots,x_{K}\rbrace $…

多元波动模型条件相关结构的变点检测AI 解读

We propose semiparametric CUSUM tests to detect a change-point in the correlation structures of nonlinear multivariate models with dynamically evolving volatilities. The asymptotic distributions of the proposed statistics are derived under mild conditions. We discuss the applicability of our method to the most often used models, including constant conditional correlation (CCC), dynamic conditional correlation (DCC), BEKK, corrected DCC, and factor models. Our simulations…

学习与指数期权收益AI 解读

Little is known about the economic sources that may generate the abnormal returns observed in put index options. We show that the learning process followed by investors may be one such source. We develop an equilibrium model under partial information in which a rational Bayesian learner prices put option contracts. Our model generates put option returns similar to the empirical returns of S&P 500 put index options. This result is not obtained when we analyze alternative…

识别假设检验的警示：真人秀真的降低了青少年生育率吗？AI 解读

Evaluating policy changes that occur everywhere at the same time is difficult because of the lack of a clear counterfactual. Hoping to address this problem, researchers often proxy for differential exposure using some observed characteristic in the pretreatment period. As a cautionary tale of how difficult identification is in such settings, we re-examine the results of an influential paper by Melissa Kearney and Phillip Levine, who found that the MTV program 16 and Pregnant…

马尔可夫切换三遍回归滤波器AI 解读

We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes. The new method, denoted as Markov-switching three-pass regression filter (MS-3PRF), is suitable for datasets with large cross-sectional dimensions, since estimation and inference are straightforward, as opposed to existing…

GARCH 模型中遗漏乘法型长期成分的检验AI 解读

We consider the problem of testing for an omitted multiplicative long-term component in GARCH-type models. Under the alternative, there is a two-component model with a short-term GARCH component that fluctuates around a smoothly time-varying long-term component which is driven by the dynamics of an explanatory variable. We suggest a Lagrange multiplier statistic for testing the null hypothesis that the variable has no explanatory power. We derive the asymptotic theory for…

用于稀疏且具有重叠社区结构图的可交换随机测度AI 解读

Summary We propose a novel statistical model for sparse networks with overlapping community structure. The model is based on representing the graph as an exchangeable point process and naturally generalizes existing probabilistic models with overlapping block structure to the sparse regime. Our construction builds on vectors of completely random measures and has interpretable parameters, each node being assigned a vector representing its levels of affiliation to some latent…

时变随机对象的函数型模型AI 解读

Summary Functional data analysis provides a popular toolbox of functional models for the analysis of samples of random functions that are real valued. In recent years, samples of time-varying object data such as time-varying networks that are not in a vector space have been increasingly collected. These data can be viewed as elements of a general metric space that lacks local or global linear structure and therefore common approaches that have been used with great success…

右奇异向量投影图：潜在混杂下的快速高维协方差估计AI 解读

Summary We consider the problem of estimating a high dimensional p × p covariance matrix Σ, given n observations of confounded data with covariance Σ+ΓΓT, where Γ is an unknown p × q matrix of latent factor loadings. We propose a simple and scalable estimator based on the projection onto the right singular vectors of the observed data matrix, which we call right singular vector projection (RSVP). Our theoretical analysis of this method reveals that, in contrast with…

基于轴对齐随机投影的稀疏主成分分析AI 解读

Summary We introduce a new method for sparse principal component analysis, based on the aggregation of eigenvector information from carefully selected axis-aligned random projections of the sample covariance matrix. Unlike most alternative approaches, our algorithm is non-iterative, so it is not vulnerable to a bad choice of initialization. We provide theoretical guarantees under which our principal subspace estimator can attain the minimax optimal rate of convergence in…

Sumca：蒙特卡洛辅助的二阶无偏均方预测误差估计AI 解读

Summary We propose a simple, unified, Monte-Carlo-assisted approach (called ‘Sumca’) to second-order unbiased estimation of the mean-squared prediction error (MSPE) of a small area predictor. The MSPE estimator proposed is easy to derive, has a simple expression and applies to a broad range of predictors that include the traditional empirical best linear unbiased predictor, empirical best predictor and post-model-selection empirical best linear unbiased predictor and…

分类未观测混杂下双重负控调整的多重稳健因果推断AI 解读

Summary Unmeasured confounding is a threat to causal inference in observational studies. In recent years, the use of negative controls to mitigate unmeasured confounding has gained increasing recognition and popularity. Negative controls have a long-standing tradition in laboratory sciences and epidemiology to rule out non-causal explanations, although they have been used primarily for bias detection. Recently, Miao and colleagues have described sufficient conditions under…