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非可分面板数据模型识别假设的检验AI 解读

Recent work on nonparametric identification of average partial effects (APEs) from panel data require restrictions on individual or time heterogeneity. Identifying assumptions under the “generalized first-differencing” category, such as time homogeneity (Chernozhukov et al., 2013), have testable equality restrictions on the distribution of the outcome variable. This paper proposes specification tests based on these restrictions. The bootstrap critical values for the…

截面与面板数据中的格兰杰因果和结构因果AI 解读

Granger noncausality in distribution is fundamentally a probabilistic conditional independence notion that can be applied not only to time series data but also to cross-section and panel data. In this paper, we provide a natural definition of structural causality in cross-section and panel data and forge a direct link between Granger ( G –) causality and structural causality under a key conditional exogeneity assumption. To put it simply, when structural effects are well…

计算机模型校准的频率学派方法AI 解读

Summary The paper considers the computer model calibration problem and provides a general frequentist solution. Under the framework proposed, the data model is semiparametric with a non-parametric discrepancy function which accounts for any discrepancy between physical reality and the computer model. In an attempt to solve a fundamentally important (but often ignored) identifiability issue between the computer model parameters and the discrepancy function, the paper proposes…

识别两样本差异的概率多分辨率扫描AI 解读

Summary We propose a multi-resolution scanning approach to identifying two-sample differences. Windows of multiple scales are constructed through nested dyadic partitioning on the sample space and a hypothesis regarding the two-sample difference is defined on each window. Instead of testing the hypotheses on different windows independently, we adopt a joint graphical model, namely a Markov tree, on the null or alternative states of these hypotheses to incorporate spatial…

结构不稳定高维因子模型的识别与估计AI 解读

This paper tackles the identification and estimation of a high dimensional factor model with unknown number of latent factors and a single break in the number of factors and/or factor loadings occurring at unknown common date. First, we propose a least squares estimator of the change point based on the second moments of estimated pseudo factors and show that the estimation error of the proposed estimator is Op(1). We also show that the proposed estimator has some degree of…

潜在结果联合分布泛函的部分识别AI 解读

In this paper, we present a systematic study of partial identification of two general classes of functionals of the joint distribution of two “potential outcomes” when a bivariate sample from the joint distribution is not available to the econometrician. Assuming the identification of the conditional marginal distributions of potential outcomes and the distribution of the covariate vector, we show that the identified sets for functionals in both classes are intervals and…

似然比有序约束下的两样本密度估计AI 解读

In this paper, we propose a method for estimating the probability density functions in a two-sample problem where the ratio of the densities is monotone. This problem has been widely identified in the literature, but effective solution methods, in which the estimates should be probability densities and the corresponding density ratio should inherit monotonicity, are unavailable. If these conditions are not satisfied, the applications of the resultant density estimates might…

小单位中的群体隔离测度：部分识别分析AI 解读

We consider the issue of measuring segregation in a population of small units, considering establishments in our application. Each establishment may have a different probability of hiring an individual from the minority group. We define segregation indices as inequality indices on these unobserved, random probabilities. Because these probabilities are measured with error by proportions, standard estimators are inconsistent. We model this problem as a nonparametric binomial…

竞买人不对称的升价拍卖AI 解读

We present a partial identification approach for ascending auctions with bidder asymmetries, where bidders' asymmetric types may be unobservable to the econometrician. Our approach yields sharp bounds and builds on and generalizes other recent bounds approaches for correlated private values ascending auctions. When bidder identities are observable, our approach yields tighter bounds than previous approaches that ignore asymmetry, demonstrating that bidder asymmetries can…

异质性家庭分配规则识别札记AI 解读

In this note, we address nonparametric identification of a collective model of household behavior in the presence of additive unobserved heterogeneity in the sharing rule. We show that the (nonstochastic part of the) sharing rule is nonparametrically identified. Moreover, under independence assumptions, individual Engel curves and the random distributions are identified except in special cases (i.e., linear Engel curves).

向量移动平均表示的基本性检验AI 解读

We propose a test for invertibility or fundamentalness of structural vector autoregressive moving average models generated by non-Gaussian independent and identically distributed structural shocks. We prove that in these models and under some regularity conditions the Wold innovations are a martingale difference sequence (mds) if and only if the structural shocks are fundamental. This simple but powerful characterization suggests an empirical strategy to assess…

矩不等式模型中部分识别参数的子向量及其他函数推断AI 解读

This paper introduces a bootstrap-based inference method for functions of the parameter vector in a moment (in)equality model. These functions are restricted to be linear for two-sided testing problems, but may be nonlinear for one-sided testing problems. In the most common case, this function selects a subvector of the parameter, such as a single component. The new inference method we propose controls asymptotic size uniformly over a large class of data distributions and…

不等时间间隔动态面板数据的识别与估计AI 解读

We propose conditions under which parameters of fixed-effect dynamic models are identified with unequally spaced panel data. Under predeterminedness, weak stationarity, and empirically testable rank conditions, AR(1) parameters are identified given the availability of “two pairs of two consecutive time gaps”, which generalizes “two pairs of two consecutive time periods”. This result extends to models with multiple covariates, higher-order autoregressions, and partial…

非高斯结构向量自回归的识别与估计AI 解读

Conventional structural vector autoregressive (SVAR) models with Gaussian errors are not identified, and additional identifying restrictions are needed in applied work. We show that the Gaussian case is an exception in that a SVAR model whose error vector consists of independent non-Gaussian components is, without any additional restrictions, identified and leads to essentially unique impulse responses. Building upon this result, we introduce an identification scheme under…

基于大量条件矩不等式的统计推断AI 解读

We construct confidence sets for models defined by many conditional moment inequalities/equalities. The number of conditional moment restrictions can be up to infinitely many. To deal with the vast number of moment restrictions, we exploit the manageability (Pollard (1990)) of the class of moment functions. We verify this condition in five examples from the recent partial identification literature.

企业声望对高管薪酬的影响AI 解读

We show that chief executive officers (CEOs) of prestigious firms earn less. Total compensation is on average 8% lower for firms listed in Fortune’s ranking of America’s most admired companies. We suggest that CEOs are willing to trade off status and career benefits from working for a publicly admired company against additional monetary compensation. Our identification strategy is based on matched sample analyses, difference-in-differences regressions, and a regression…

金融契约与组织形式：来自贸易信贷监管的证据AI 解读

ABSTRACT We present evidence that restrictions to the set of feasible financial contracts affect buyer‐supplier relationships and the organizational form of the firm. We exploit a regulation that restricted the maturity of the trade credit contracts that a large retailer could sign with some of its small suppliers. Using a within‐product difference‐in‐differences identification strategy, we find that the restriction reduces the likelihood of trade by 11%. The retailer also…

异质性与工具变量测量误差下的工具变量方法AI 解读

We study the consequences of substituting an error-laden proxy W for an instrument Z on the interpretation of Wald, local instrumental variable (LIV), and instrumental variable (IV) estimands in an ordered discrete choice structural system with heterogeneity. A proxy W need only satisfy an exclusion restriction and that the treatment and outcome are mean independent from W given Z . Unlike Z , W need not satisfy monotonicity and may, under particular specifications, fail…

工具变量分位数回归的平滑估计方程AI 解读

The moment conditions or estimating equations for instrumental variables quantile regression involve the discontinuous indicator function. We instead use smoothed estimating equations (SEE), with bandwidth h . We show that the mean squared error (MSE) of the vector of the SEE is minimized for some h > 0, leading to smaller asymptotic MSE of the estimating equations and associated parameter estimators. The same MSE-optimal h also minimizes the higher-order type I error of a…

协变量缺失回归模型的识别与推断AI 解读

This paper examines the problem of identification and inference on a conditional moment condition model with missing data, with special focus on the case when the conditioning covariates are missing. We impose no assumption on the distribution of the missing data and we confront the missing data problem by using a worst case scenario approach. We characterize the sharp identified set and argue that this set is usually too complex to compute or to use for inference. Given…

非线性约束经验似然比检验的二阶改进AI 解读

In this paper, we investigate the second‐order properties of empirical likelihood ratio (ELR) tests of general nonlinear parametric restrictions for over‐identified moment restriction models. We derive the stochastic expansion of the ELR statistic for this very large class of testing problems and its formal distributional expansion. We show that we can improve the size properties of the ELR tests via either Bartlett correction or pseudo observation adjustment. Monte Carlo…

条件处理效应的一致检验AI 解读

We construct tests for the null hypothesis that the conditional average treatment effect is non‐negative, conditional on every possible value of a subset of covariates. Testing such a null hypothesis can provide more information than the sign of the average treatment effects parameter. The null hypothesis can be characterized as infinitely many of unconditional moment inequalities. A Kolmogorov–Smirnov test is constructed based on these unconditional moment inequalities, and…

Instrumental variables are widely used for estimating causal effects in the presence of unmeasured confounding. The discrete instrumental variable model has testable implications for the law of the observed data. However, current assessments of instrumental validity are typically based solely on subject-matter arguments rather than these testable implications, partly due to a lack of formal statistical tests with known properties. In this paper, we develop simple procedures…

分层数据中的 lasso 回归建模AI 解读

We consider the estimation of regression models on strata defined using a categorical covariate, in order to identify interactions between this categorical covariate and the other predictors. A basic approach requires the choice of a reference stratum. We show that the performance of a penalized version of this approach depends on this arbitrary choice, and propose an approach that bypasses this at almost no additional computational cost. Regarding model selection…