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On two-stage estimation of structural instrumental variable models

结构工具变量模型的两阶段估计

Two-stage least squares estimation is popular for structural equation models with unmeasured confounders. In such models, both the outcome and the exposure are assumed to follow linear models conditional on the measured confounders and instrumental variable, which is related to the outcome only via its relation with the exposure. We consider data where both the outcome and the exposure may be incompletely observed, with particular attention to the case where both are…

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Double instrumental variable estimation of interaction models with big data

大数据交互模型的双重工具变量估计

The factor analysis of a (n,m) matrix of observations Y is based on the joint spectral decomposition of the matrix squares YY′ and Y′Y for Principal Component Analysis (PCA). For very large matrix dimensions n and m, this approach has a high level of numerical complexity. The big data feature suggests new estimation methods with a smaller degree of numerical complexity. The double Instrumental Variable (IV) approach uses row and column instruments to estimate consistently…

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Rationalization and identification of binary games with correlated types

私人类型相关的二元博弈:模型相容性与识别

This paper studies the rationalization and identification of binary games where players have correlated private types. Allowing for type correlation is crucial in global games and in models with social interactions as it represents correlated private information and homophily, respectively. Our approach is fully nonparametric in the joint distribution of types and the strategic effects in the payoffs. First, under monotone pure Bayesian Nash Equilibrium strategy, we…

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Functional linear regression with functional response

函数型响应的函数线性回归

In this paper, we develop new estimation results for functional regressions where both the regressor Z(t) and the response Y(t) are functions of Hilbert spaces, indexed by the time or a spatial location. The model can be thought as a generalization of the multivariate regression where the regression coefficient is now an unknown operator Π. We propose to estimate the operator Π by Tikhonov regularization, which amounts to apply a penalty on the L2 norm of Π. We derive the…

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SEMIPARAMETRIC ESTIMATION OF RANDOM COEFFICIENTS IN STRUCTURAL ECONOMIC MODELS

结构经济模型中随机系数的半参数估计

This paper discusses nonparametric estimation of the distribution of random coefficients in a structural model that is nonlinear in the random coefficients. We establish that the problem of recovering the probability density function ( pdf ) of random parameters falls into the class of convexly-constrained inverse problems. The framework offers an estimation method that separates computational solution of the structural model from estimation. We first discuss nonparametric…

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Direct and Indirect Treatment Effects–Causal Chains and Mediation Analysis with Instrumental Variables

直接与间接处理效应:工具变量下的因果链与中介分析

Summary The paper discusses the non-parametric identification of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the treatment and the outcome, as well as the unmediated direct effect of the treatment by using distinct instruments for the endogenous treatment and the endogenous mediator. We…

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Joint Non-Parametric Correction Estimator for Excess Relative Risk Regression in Survival Analysis with Exposure Measurement Error

暴露测量误差下超额相对风险回归的联合非参数校正估计

Summary Observational epidemiological studies often confront the problem of estimating exposure–disease relationships when the exposure is not measured exactly. We investigate exposure measurement error in excess relative risk regression, which is a widely used model in radiation exposure effect research. In the study cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies a generalized version of the classical…

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Robust Estimation of Encouragement Design Intervention Effects Transported Across Sites

跨站点迁移鼓励设计干预效应的稳健估计

Summary We develop robust targeted maximum likelihood estimators (TMLEs) for transporting intervention effects from one population to another. Specifically, we develop TMLEs for three transported estimands: the intent-to-treat average treatment effect (ATE) and complier ATE, which are relevant for encouragement design interventions and instrumental variable analyses, and the ATE of the exposure on the outcome, which is applicable to any randomized or observational study. We…

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Bootstrapping the GMM overidentification test under first-order underidentification

一阶局部欠识别下 GMM 过度识别检验的自助法

The main contribution of this paper is to study the applicability of the bootstrap to estimating the distribution of the standard test of overidentifying restrictions of Hansen (1982) when the model is globally identified but the rank condition fails to hold (lack of first-order local identification). An important example for which these conditions are verified is the popular test of common conditionally heteroskedastic features proposed by Engle and Kozicki (1993). As…

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The triangular model with random coefficients

随机系数三角模型

The triangular model is a very popular way to allow for causal inference in the presence of endogeneity. In this model, an outcome is determined by an endogenous regressor, which in turn is first caused by an instrument. We study the triangular model with random coefficients and additional exogenous regressors in both equations, and establish non-identification of the joint distribution of random coefficients. This implies that counterfactual outcomes are not identified…

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An endogenously clustered factor approach to international business cycles

国际经济周期的内生聚类因子方法

Summary Factor models have become useful tools for studying international business cycles. Block factor models can be especially useful as the zero restrictions on the loadings of some factors may provide some economic interpretation of the factors. These models, however, require the econometrician to predefine the blocks, leading to potential misspecification. In Monte Carlo experiments, we show that even a small misspecification can lead to substantial declines in fit. We…

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A discrete‐choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance

带交互固定效应的大型异质面板离散选择模型:公司债发行决定因素

Summary What is the effect of funding costs on the conditional probability of issuing a corporate bond? We study this question in a novel dataset covering 5610 issuances by US firms over the period from 1990 to 2014. Identification of this effect is complicated because of unobserved, common shocks such as the global financial crisis. To account for these shocks, we extend the common correlated effects estimator to settings where outcomes are discrete. Both the asymptotic…

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Latent indices in assortative matching models

同类匹配模型中的潜在指数

A large class of two-sided matching models that include both transferable and non-transferable utility result in positive assortative matching along a latent index. Data from matching markets, however, may not exhibit perfect assortativity due to the presence of unobserved characteristics. This paper studies the identification and estimation of such models. We show that the distribution of the latent index is not identified when data from one-to-one matches are observed.…

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A note on identification of discrete choice models for bundles and binary games

组合离散选择模型与二元博弈的识别札记

We study nonparametric identification of single-agent discrete choice models for bundles (without requiring bundle-specific prices) and of binary games of complete information. We show that these two models are quite similar from an identification standpoint. Moreover, they are mathematically equivalent when we restrict attention to the class of potential games and impose a specific equilibrium selection mechanism in the data generating process. We provide new identification…

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Identification of time and risk preferences in buy price auctions

一口价拍卖中时间偏好与风险偏好的识别

Buy price auctions merge a posted price option with a standard bidding mechanisms, and have been used by various online auction sites including eBay and General Motors Assistance Corporation. A buyer in a buy price auction can accept the buy price to win with certainty and end the auction early. Intuitively, the buy price option may appeal to bidders who are risk averse or impatient to obtain the good, and a number of authors have examined how such mechanisms can increase…

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Dynamic skill accumulation, education policies, and the return to schooling

动态技能积累、教育政策与 schooling 回报

Using a dynamic skill accumulation model of schooling and labor supply with learning-by-doing, we decompose early life-cycle wage growth of U.S. white males into four main sources: education, hours worked, cognitive skills (Armed Forces Qualification Tests scores), and unobserved heterogeneity, and evaluate the effect of compulsory high school graduation and a reduction in the cost of college. About 60 percent of the differences in slopes of early life-cycle wage profiles…

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Quantifying an Adherence Path-Specific Effect of Antiretroviral Therapy in the Nigeria PEPFAR Program

尼日利亚 PEPFAR 项目中抗逆转录病毒治疗经依从性传导的路径特定效应

Since the early 2000s, evidence has accumulated for a significant differential effect of first-line antiretroviral therapy (ART) regimens on human immunodeficiency virus (HIV) viral load suppression. This finding was replicated in our data from the Harvard President's Emergency Plan for AIDS Relief (PEPFAR) program in Nigeria. Investigators were interested in finding the source of these differences, i.e., understanding the mechanisms through which one regimen outperforms…

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General Forms of Finite Population Central Limit Theorems with Applications to Causal Inference

有限总体中心极限定理的一般形式及其因果推断应用

Frequentists’ inference often delivers point estimators associated with confidence intervals or sets for parameters of interest. Constructing the confidence intervals or sets requires understanding the sampling distributions of the point estimators, which, in many but not all cases, are related to asymptotic Normal distributions ensured by central limit theorems. Although previous literature has established various forms of central limit theorems for statistical inference in…

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PLEMT: A Novel Pseudolikelihood-Based EM Test for Homogeneity in Generalized Exponential Tilt Mixture Models

PLEMT:广义指数倾斜混合模型的拟似然 EM 同质性检验

Motivated by analyses of DNA methylation data, we propose a semiparametric mixture model, namely the generalized exponential tilt mixture model, to account for heterogeneity between differentially methylated and non-differentially methylated subjects in the cancer group, and capture the differences in higher order moments (e.g. mean and variance) between subjects in cancer and normal groups. A pairwise pseudolikelihood is constructed to eliminate the unknown nuisance…

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Multivariate Seasonal Adjustment, Economic Identities, and Seasonal Taxonomy

多变量季节调整、经济恒等式与季节性分类

This article extends the methodology for multivariate seasonal adjustment by exploring the statistical modeling of seasonality jointly across multiple time series, using latent dynamic factor models fitted using maximum likelihood estimation. Signal extraction methods for the series then allow us to calculate a model-based seasonal adjustment. We emphasize several facets of our analysis: (i) we quantify the efficiency gain in multivariate signal extraction versus univariate…

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More Data or Better Data? A Statistical Decision Problem

更多数据还是更好数据?一个统计决策问题

Abstract When designing data collection, crucial questions arise regarding how much data to collect and how much effort to expend to enhance the quality of the collected data. To make choice of sample design a coherent subject of study, it is desirable to specify an explicit decision problem. We use the Wald framework of statistical decision theory to study allocation of a budget between two or more sampling processes. These processes all draw random samples from a…

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Confounder adjustment in multiple hypothesis testing

多重假设检验中的混杂因素调整

We consider large-scale studies in which thousands of significance tests are performed simultaneously. In some of these studies, the multiple testing procedure can be severely biased by latent confounding factors such as batch effects and unmeasured covariates that correlate with both primary variable(s) of interest (e.g., treatment variable, phenotype) and the outcome. Over the past decade, many statistical methods have been proposed to adjust for the confounders in…

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Identification of peer effects through social networks using variance restrictions

利用方差限制识别社会网络中的同伴效应

This paper presents a novel method to identify peer effects through exploiting fluctuations in the variances and covariances of outcomes over a social network. Endogenous and contextual peer effects can be disentangled by contrasting the covariances of the outcomes of peers with the covariances of the outcomes of peers of peers. Correlated effects are incorporated by allowing for unrestricted network level heterogeneity. The method is applied to the Project STAR data to…

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Bayesian moment-based inference in a regression model with misclassification error

二元协变量误分类回归中的贝叶斯矩条件推断

We present a Bayesian analysis of a regression model with a binary covariate that may have classification (measurement) error. Prior research demonstrates that the regression coefficient is only partially identified. We take a Bayesian approach which adds assumptions in the form of priors on the unknown misclassification probabilities. The approach is intermediate between the frequentist bounds of previous literature and strong assumptions which achieve point identification,…

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