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交互网络的边可交换模型AI 解读

Many modern network datasets arise from processes of interactions in a population, such as phone calls, email exchanges, co-authorships, and professional collaborations. In such interaction networks, the edges comprise the fundamental statistical units, making a framework for edge-labeled networks more appropriate for statistical analysis. In this context, we initiate the study of edge exchangeable network models and explore its basic statistical properties. Several…

高维分位数回归中变点的预言式估计AI 解读

In this paper, we consider a high-dimensional quantile regression model where the sparsity structure may differ between two sub-populations. We develop $\ell_1$-penalized estimators of both regression coefficients and the threshold parameter. Our penalized estimators not only select covariates but also discriminate between a model with homogeneous sparsity and a model with a change point. As a result, it is not necessary to know or pretest whether the change point is…

分位数最优治疗规则AI 解读

Finding the optimal treatment regime (or a series of sequential treatment regimes) based on individual characteristics has important applications in areas such as precision medicine, government policies and active labor market interventions. In the current literature, the optimal treatment regime is usually defined as the one that maximizes the average benefit in the potential population. This paper studies a general framework for estimating the quantile-optimal treatment…

多协变量与异方差线性回归模型中的推断AI 解读

The linear regression model is widely used in empirical work in economics, statistics, and many other disciplines. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroscedasticity. Our results are obtained using high-dimensional approximations, where the number of included covariates is allowed to grow as fast as the sample size. We find that…

利用随机森林估计异质性处理效应并进行统计推断AI 解读

Many scientific and engineering challenges -- ranging from personalized medicine to customized marketing recommendations -- require an understanding of treatment effect heterogeneity. In this paper, we develop a non-parametric causal forest for estimating heterogeneous treatment effects that extends Breiman's widely used random forest algorithm. In the potential outcomes framework with unconfoundedness, we show that causal forests are pointwise consistent for the true…

主观生存曲线的获取：部分识别的启示AI 解读

When analyzing data on subjective expectations of continuous outcomes, researchers have access to a limited number of reported probabilities for each respondent from which to construct complete distribution functions. Moreover, reported probabilities may be rounded and thus not equal to true beliefs. Using survival expectations elicited from a representative sample from the Netherlands, we investigate what can be learned if we take these two sources of missing information…

货币政策效应的半参数估计：重新审视“推绳子”理论AI 解读

We develop flexible semiparametric time series methods for the estimation of the causal effect of monetary policy on macroeconomic aggregates. Our estimator captures the average causal response to discrete policy interventions in a macrodynamic setting, without the need for assumptions about the process generating macroeconomic outcomes. The proposed estimation strategy, based on propensity score weighting, easily accommodates asymmetric and nonlinear responses. Using this…

基于最小距离的实用 Kolmogorov–Smirnov 检验：韩国顶端收入份额的应用AI 解读

We study Kolmogorov–Smirnov goodness-of-fit tests for evaluating distributional hypotheses where unknown parameters need to be fitted. Following the work of Pollard (1980), our approach uses a Cramér–von Mises minimum distance estimator for parameter estimation. The asymptotic null distribution of the resulting test statistic is represented by invariance principle arguments as a functional of a Brownian bridge in a simple regression format for which asymptotic critical…

分组数据下收入分布估计与检验的统一方法AI 解读

We propose a unified approach that is flexibly applicable to various types of grouped data for estimating and testing parametric income distributions. To simplify the use of our approach, we also provide a parametric bootstrap method and show its asymptotic validity. We also compare this approach with existing methods for grouped income data, and assess their finite-sample performance by a Monte Carlo simulation. For empirical demonstrations, we apply our approach to…

工具变量识别不同局部平均处理效应时的 2SLS 一致方差估计量AI 解读

Under treatment effect heterogeneity, an instrument identifies the instrument-specific local average treatment effect (LATE). With multiple instruments, two-stage least squares (2SLS) estimand is a weighted average of different LATEs. What is often overlooked in the literature is that the postulated moment condition evaluated at the 2SLS estimand does not hold unless those LATEs are the same. If so, the conventional heteroscedasticity-robust variance estimator would be…

一般趋势与横截面相关的固定 T 面板单位根推断AI 解读

This article proposes a new panel unit root test based on the generalized method of moments approach for panels with a possibly small number of time periods, T, and a large number of cross-sectional units, N. In the model that we consider the deterministic trend function is essentially unrestricted and the errors obey a multifactor structure that allows for rich forms of unobserved heterogeneity. In spite of these allowances, the GMM estimator considered is shown to be…

非参数加性工具变量估计：组收缩估计视角AI 解读

In this article, we study a nonparametric approach regarding a general nonlinear reduced form equation to achieve a better approximation of the optimal instrument. Accordingly, we propose the nonparametric additive instrumental variable estimator (NAIVE) with the adaptive group Lasso. We theoretically demonstrate that the proposed estimator is root-n consistent and asymptotically normal. The adaptive group Lasso helps us select the valid instruments while the dimensionality…

断点回归中的近似置换检验与诱导次序统计量AI 解读

In the regression discontinuity design (RDD), it is common practice to assess the credibility of the design by testing whether the means of baseline covariates do not change at the cut-off (or threshold) of the running variable. This practice is partly motivated by the stronger implication derived by Lee (2008), who showed that under certain conditions the distribution of baseline covariates in the RDD must be continuous at the cut-off. We propose a permutation test based on…

具有交互固定效应的非参数面板数据模型AI 解读

This article studies non-parametric panel data models with multidimensional, unobserved individual effects when the number of time periods is fixed. I focus on models where the unobservables have a factor structure and enter an unknown structural function non-additively. The setup allows the individual effects to impact outcomes differently in different time periods and it allows for heterogeneous marginal effects. I provide sufficient conditions for point identification of…

惩罚化间接推断AI 解读

Parameter estimates of structural economic models are often difficult to interpret at the light of the underlying economic theory. Bayesian methods have become increasingly popular as a tool for conducting inference on structural models since priors offer a way to exert control over the estimation results. Similarly to Bayesian estimation, this paper proposes a penalized indirect inference estimator that allows researchers to obtain economically meaningful parameter…

二阶识别下 GMM 与间接推断的渐近性质AI 解读

This paper presents a limiting distribution theory for GMM and Indirect Inference estimators when local identification conditions fail at first-order but hold at second-order. These limit distributions are shown to be non-standard, but we show that they can be easily simulated, making it possible to perform inference about the parameters in this setting. We illustrate our results in the context of a dynamic panel data model in which the parameter of interest is identified…

离散选择模型的广义间接推断AI 解读

This paper develops and implements a practical simulation-based method for estimating dynamic discrete choice models. The method, which can accommodate lagged dependent variables, serially correlated errors, unobserved variables, and many alternatives, builds on the ideas of indirect inference. The main difficulty in implementing indirect inference in discrete choice models is that the objective surface is a step function, rendering gradient-based optimization methods…

长期风险资产定价模型的两步间接推断估计AI 解读

The long-run consumption risk model provides a theoretically appealing explanation for prominent asset pricing puzzles, but its intricate structure presents a challenge for econometric analysis. This paper proposes a two-step indirect inference approach that disentangles the estimation of the model’s macro-economic dynamics and the investor’s preference parameters. A Monte Carlo study explores the feasibility and efficiency of the estimation strategy. We apply the method to…

外生变量内生性随机缺失下的间接推断AI 解读

We consider consistent estimation of parameters in a structural model by Indirect Inference (II) when the exogenous variables can be missing at random (MAR) endogenously. We demonstrate that II procedures that simply discard sample units with missing observations can yield inconsistent estimates of the true structural parameters. By inverse probability weighting (IPW) the “complete case” observations, i.e., sample units with no missing variables for the observed and…

基于辅助统计量的模拟估计：ABC与模拟最小距离的联系AI 解读

The frequentist method of simulated minimum distance (SMD) is widely used in economics to estimate complex models with an intractable likelihood. In other disciplines, a Bayesian approach known as Approximate Bayesian Computation (ABC) is far more popular. This paper connects these two seemingly related approaches to likelihood-free estimation by means of a Reverse Sampler that uses both optimization and importance weighting to target the posterior distribution. Its hybrid…

价格灵活性与企业杠杆AI 解读

The frequency with which firms adjust output prices helps explain persistent differences in capital structure across firms. Unconditionally, the most flexible-price firms have a 19% higher long-term leverage ratio than the most sticky-price firms, controlling for known determinants of capital structure. Sticky-price firms increased leverage more than flexible-price firms following the staggered implementation of bank deregulation across states and over time, which we use in…

局部依赖观测的图一致性度量AI 解读

This paper introduces a simple measure of a concordance pattern among observed outcomes along a network, that is, the pattern in which adjacent outcomes tend to be more strongly correlated than nonadjacent outcomes. The graph concordance measure can be generally used to quantify the empirical relevance of a network in explaining cross-sectional dependence of the outcomes, and as shown in the paper, it can also be used to quantify the extent of homophily under certain…

分量分别删失的复合终点半参数回归分析AI 解读

Composite endpoints with censored data are commonly used as study outcomes in clinical trials. For example, progression-free survival is a widely used composite endpoint, with disease progression and death as the two components. Progression-free survival time is often defined as the time from randomization to the earlier occurrence of disease progression or death from any cause. The censoring times of the two components could be different for patients not experiencing the…

按估计倾向得分修剪的观察性研究中因果效应的渐近推断AI 解读

Causal inference with observational studies often relies on the assumptions of unconfoundedness and overlap of covariate distributions in different treatment groups. The overlap assumption is violated when some units have propensity scores close to |$0$| or |$1$|⁠, so both practical and theoretical researchers suggest dropping units with extreme estimated propensity scores. However, existing trimming methods often do not incorporate the uncertainty in this design stage and…