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工具变量不足时多内生变量三角模型的识别与估计AI 解读

We develop a novel identification method for a partially linear model with multiple endogenous variables of interest but a single instrumental variable, which could even be binary. We present an easy-to-implement consistent estimator for the parametric part. This estimator retains n-convergence rate and asymptotic normality even though we have a generated regressor in our setup. The nonparametric part of the model is also identified. We also outline how our identification…

内生误报下的处理效应估计AI 解读

Participation in social programs is often misreported in survey data, complicating the estimation of treatment effects. We propose a model to estimate treatment effects under endogenous participation and endogenous misreporting. We present an expression for the asymptotic bias of both OLS and IV estimators and discuss the conditions under which sign reversal may occur. We provide a method for eliminating this bias when researchers have access to information regarding…

断点回归设计中的处理效应异质性检验AI 解读

Treatment effect heterogeneity is frequently studied in regression discontinuity (RD) applications. This paper proposes, under the RD setup, formal tests for treatment effect heterogeneity among individuals with different observed pre-treatment characteristics. The proposed tests study whether a policy treatment (1) is beneficial for at least some subpopulations defined by pre-treatment covariate values, (2) has any impact on at least some subpopulations, and (3) has a…

民主确实促进增长AI 解读

We provide evidence that democracy has a positive effect on GDP per capita. Our dynamic panel strategy controls for country fixed effects and the rich dynamics of GDP, which otherwise confound the effect of democracy. To reduce measurement error, we introduce a new indicator of democracy that consolidates previous measures. Our baseline results show that democratizations increase GDP per capita by about 20 percent in the long run. We find similar effects using a propensity…

文化与税收AI 解读

We propose a difference-in-differences strategy to identify the existence of interjurisdictional tax competition. Our strategy rests on differences between desired tax levels determined by culture-specific preferences and equilibrium tax levels determined by fiscal externalities and by preferences. While preferences differ systematically between French-speaking and German-speaking Swiss municipalities, local income tax burdens exhibit smooth spatial gradients. To qualify the…

对 PENCOMP 的讨论AI 解读

We would like to congratulate Zhou, Elliott, and Little (henceforth referred to as ZEL) on an interesting article in an important area of research. ZEL propose a new approach for causal inference u...

用于处理比较的倾向得分惩罚样条方法AI 解读

Valid causal inference from observational studies requires controlling for confounders. When time-dependent confounders are present that serve as mediators of treatment effects and affect future treatment assignment, standard regression methods for controlling for confounders fail. Similar issues also arise in trials with sequential randomization, when randomization at later time points is based on intermediate outcomes from earlier randomized assignments. We propose a…

考虑发热杀灭寄生虫与测量误差的疟疾归因发热比例估计AI 解读

Malaria is a major health problem in many tropical regions. Fever is a characteristic symptom of malaria. The fraction of fevers that are attributable to malaria, the malaria attributable fever fraction (MAFF), is an important public health measure in that the MAFF can be used to calculate the number of fevers that would be avoided if malaria was eliminated. Despite such causal interpretation, the MAFF has not been considered in the framework of causal inference. We define…

治疗选择下的存活遵从者效应：及时入住重症监护室的应用AI 解读

Pretreatment selection or censoring (“selection on treatment”) can occur when two treatment levels are compared ignoring the third option of neither treatment, in “censoring by death” settings where treatment is only defined for those who survive long enough to receive it, or in general in studies where the treatment is only defined for a subset of the population. Unfortunately, the standard instrumental variable (IV) estimand is not defined in the presence of such…

处理效应变异的分解AI 解读

Understanding and characterizing treatment effect variation in randomized experiments has become essential for going beyond the “black box” of the average treatment effect. Nonetheless, traditional statistical approaches often ignore or assume away such variation. In the context of randomized experiments, this article proposes a framework for decomposing overall treatment effect variation into a systematic component explained by observed covariates and a remaining…

存在样本选择的断点回归设计AI 解读

This article extends the standard regression discontinuity (RD) design to allow for sample selection or missing outcomes. We deal with both treatment endogeneity and sample selection. Identification in this article does not require any exclusion restrictions in the selection equation, nor does it require specifying any selection mechanism. The results can therefore be applied broadly, regardless of how sample selection is incurred. Identification instead relies on smoothness…

含内生解释变量的部分变系数模型的估计与推断AI 解读

In this article, we propose a new class of semiparametric instrumental variable models with partially varying coefficients, in which the structural function has a partially linear form and the impact of endogenous structural variables can vary over different levels of some exogenous variables. We propose a three-step estimation procedure to estimate both functional and constant coefficients. The consistency and asymptotic normality of these proposed estimators are…

分布偏效应的估计与推断：理论及应用AI 解读

This article considers nonparametric and semiparametric estimation and inference of the effects of a covariate, either discrete or continuous, on the conditional distribution of a response outcome. It also proposes various uniform tests following estimation. This type of analysis is useful in situations where the econometrician or policy-maker is interested in knowing the effect of a variable or policy on the whole distribution of the response outcome conditional on…

引入协变量的最优面板单位根检验AI 解读

Summary This paper provides asymptotic optimality results for panel unit root tests with covariates by deriving the Gaussian power envelope. The main conclusion is that the use of covariates holds considerable promise in the panel data context, much more so than in the time series context. In fact, the use of the covariates not only leads to increased power, but can actually have an order effect on the shrinking neighbourhoods around unity for which power is non-negligible.

系统重要性金融机构的尾部事件驱动网络AI 解读

The interdependence, dynamics and riskiness of financial institutions are the key features frequently tackled in financial econometrics. We propose a Tail Event driven Network Quantile Regression (TENQR) model which addresses these three aspects. More precisely, our framework captures the risk propagation and dynamics in terms of a panel quantile autoregression involving network effects that are quantified through a time-varying adjacency matrix. To reflect the risk content…

带状时空自回归模型AI 解读

We propose a new class of spatio-temporal models with unknown and banded autoregressive coefficient matrices. The setting represents a sparse structure for high-dimensional spatial panel dynamic models when panel members represent economic (or other type) individuals at many different locations. The structure is practically meaningful when the order of panel members is arranged appropriately. Note that the implied autocovariance matrices are unlikely to be banded, and…

利用簇随机化估计簇内溢出效应：印度农村知识扩散应用AI 解读

Summary Spillover effects within randomized clusters pose a challenge for identifying impacts of an individualized treatment. The paper proposes a solution. Longitudinal and intra‐household observations are combined in estimating the direct knowledge gain from watching an info‐movie in rural India, while randomized village assignment identifies knowledge sharing. Simulations on synthetic data and econometric tests provide support for the estimation method. We find evidence…

存在溢出时的研发私人回报：再考察AI 解读

Summary This is both a replication of Eberhardt et al. ( Review of Economics and Statistics , 2013, 95 (2), 436–448) using different software, and a critical extension and diagnostic reassessment of the original results. The main findings of the paper are confirmed and sometimes reinforced. We point out some inconsistencies, in particular in the calculation of standard errors for the common correlated effects pooled model; we extend the diagnostic checks; lastly, in the…

卡特尔效应起止时间的判定AI 解读

Summary The begin and end dates of cartels are often ambiguous, despite competition authorities stating them with precision. The legally established infringement period(s) from documentary evidence need not coincide with the period(s) of actual cartel effects. In this paper, we show that misdating cartel effects leads to a (weak) overestimation of but‐for prices and an underestimation of overcharges. Total overcharges based on comparing but‐for prices to actual prices are a…

采矿对本地住宅价值的影响：半参数空间分位数自回归AI 解读

Summary Rock mining operations, including limestone and gravel production, have considerable adverse effects on residential quality of life due to elevated noise and dust levels resulting from dynamite blasting and increased truck traffic. This paper provides the first estimates of the effects of rock mining—an environmental disamenity—on local residential property values. We focus on the relationship between a house's price and its distance from a nearby rock mine. Our…

有限期离散选择动态规划模型的近似求解AI 解读

Summary The estimation of finite‐horizon discrete‐choice dynamic programming (DCDP) models is computationally expensive. This limits their realism and impedes verification and validation efforts. Keane and Wolpin ( Review of Economics and Statistics , 1994, 76 (4), 648–672) propose an interpolation method that ameliorates the computational burden but introduces approximation error. I describe their approach in detail, successfully recompute their original quality…

动态随机效用AI 解读

We provide an axiomatic analysis of dynamic random utility, characterizing the stochastic choice behavior of agents who solve dynamic decision problems by maximizing some stochastic process ( U t ) of utilities. We show first that even when ( U t ) is arbitrary, dynamic random utility imposes new testable across‐period restrictions on behavior, over and above period‐by‐period analogs of the static random utility axioms. An important feature of dynamic random utility is that…

理性行为的动态分位数模型AI 解读

This paper develops a dynamic model of rational behavior under uncertainty, in which the agent maximizes the stream of future τ ‐quantile utilities, for τ ∈ (0,1). That is, the agent has a quantile utility preference instead of the standard expected utility. Quantile preferences have useful advantages, including the ability to capture heterogeneity and allowing the separation between risk aversion and elasticity of intertemporal substitution. Although quantiles do not share…

动态二元选择面板模型中的排除限制：评《无严格外生回归变量的半参数二元选择面板模型》AI 解读

In this note we revisit the use of exclusion restrictions in the semiparametric binary choice panel data model introduced in Honore and Lewbel (2002). We show that in a dynamic panel data setting (where one of the pre-determined explanatory variables is the lagged dependent variable), the exclusion restriction in Honore and Lewbel (2002) implicitly re- quires serial independence condition on an observed regressor, that if violated in the data will result in their procedure…