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A persistence‐based Wold‐type decomposition for stationary time series

平稳时间序列基于持续性的 Wold 型分解

This paper shows how to decompose weakly stationary time series into the sum, across time scales, of uncorrelated components associated with different degrees of persistence. In particular, we provide an Extended Wold Decomposition based on an isometric scaling operator that makes averages of process innovations. Thanks to the uncorrelatedness of components, our representation of a time series naturally induces a persistence‐based variance decomposition of any weakly…

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Indirect inference with(out) constraints

有约束与无约束的间接推断

Indirect Inference (I‐I) estimation of structural parameters θ requires matching observed and simulated statistics, which are most often generated using an auxiliary model that depends on instrumental parameters β . The estimators of the instrumental parameters will encapsulate the statistical information used for inference about the structural parameters. As such, artificially constraining these parameters may restrict the ability of the auxiliary model to accurately…

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Inference on breakdown frontiers

失效边界的统计推断

Given a set of baseline assumptions, a breakdown frontier is the boundary between the set of assumptions which lead to a specific conclusion and those which do not. In a potential outcomes model with a binary treatment, we consider two conclusions: First, that ATE is at least a specific value (e.g., nonnegative) and second that the proportion of units who benefit from treatment is at least a specific value (e.g., at least 50%). For these conclusions, we derive the breakdown…

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Simple and honest confidence intervals in nonparametric regression

非参数回归中简单且诚实的置信区间

We consider the problem of constructing honest confidence intervals (CIs) for a scalar parameter of interest, such as the regression discontinuity parameter, in nonparametric regression based on kernel or local polynomial estimators. To ensure that our CIs are honest, we use critical values that take into account the possible bias of the estimator upon which the CIs are based. We show that this approach leads to CIs that are more efficient than conventional CIs that achieve…

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On optimal inference in the linear IV model

线性工具变量模型中的最优推断

This paper considers tests and confidence sets (CSs) concerning the coefficient on the endogenous variable in the linear IV regression model with homoskedastic normal errors and one right‐hand side endogenous variable. The paper derives a finite‐sample lower bound function for the probability that a CS constructed using a two‐sided invariant similar test has infinite length and shows numerically that the conditional likelihood ratio (CLR) CS of Moreira (2003) is not always…

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Measuring quality for use in incentive schemes: The case of “shrinkage” estimators

激励机制中的质量测度:收缩估计量的经济后果

Researchers commonly “shrink” raw quality measures based on statistical criteria. This paper studies when and how this transformation's statistical properties would confer economic benefits to a utility‐maximizing decision‐maker across common asymmetric information environments. I develop the results for an application measuring teacher quality. The presence of a systematic relationship between teacher quality and class size could cause the data transformation to do either…

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Quantile treatment effects in difference in differences models with panel data

面板双重差分模型中的分位数处理效应

This paper considers identification and estimation of the Quantile Treatment Effect on the Treated (QTT) under a straightforward distributional extension of the most commonly invoked Mean Difference in Differences Assumption used for identifying the Average Treatment Effect on the Treated (ATT). Identification of the QTT is more complicated than the ATT though because it depends on the unknown dependence (or copula) between the change in untreated potential outcomes and the…

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Identification of average effects under magnitude and sign restrictions on confounding

混杂效应幅度与符号限制下的平均效应识别

This paper studies measuring various average effects of X on Y in general structural systems with unobserved confounders U , a potential instrument Z , and a proxy W for U . We do not require X or Z to be exogenous given the covariates or W to be a perfect one‐to‐one mapping of U . We study the identification of coefficients in linear structures as well as covariate‐conditioned average nonparametric discrete and marginal effects (e.g., average treatment effect on the…

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Identification of games of incomplete information with multiple equilibria and unobserved heterogeneity

多重均衡与不可观测异质性下不完全信息博弈的识别

This paper deals with identification of discrete games of incomplete information when we allow for three types of unobservables: payoff‐relevant variables, both players' private information and common knowledge, and nonpayoff‐relevant variables that determine the selection between multiple equilibria. The specification of the payoff function and the distributions of the common knowledge unobservables is nonparametric with finite support (i.e., finite mixture model). We…

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Identification‐ and singularity‐robust inference for moment condition models

矩条件模型中对识别强度与奇异性稳健的推断

This paper introduces a new identification‐ and singularity‐robust conditional quasi‐likelihood ratio (SR‐CQLR) test and a new identification‐ and singularity‐robust Anderson and Rubin (1949) (SR‐AR) test for linear and nonlinear moment condition models. Both tests are very fast to compute. The paper shows that the tests have correct asymptotic size and are asymptotically similar (in a uniform sense) under very weak conditions. For example, in i.i.d. scenarios, all that is…

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Improved inference on the rank of a matrix

矩阵秩的改进推断

This paper develops a general framework for conducting inference on the rank of an unknown matrix Π 0 . A defining feature of our setup is the null hypothesis of the form H 0 : rank ( Π 0 ) ≤ r . The problem is of first‐order importance because the previous literature focuses on H 0 ′ : rank ( Π 0 ) = r by implicitly assuming away rank ( Π 0 ) < r , which may lead to invalid rank tests due to overrejections. In particular, we show that limiting distributions of test…

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Semiparametric estimation of the canonical permanent‐transitory model of earnings dynamics

收入动态中经典永久—暂时模型的半参数估计

This paper presents identification and estimation results for a flexible state space model. Our modification of the canonical model allows the permanent component to follow a unit root process and the transitory component to follow a semiparametric model of a higher‐order autoregressive‐moving‐average (ARMA) process. Using panel data of observed earnings, we establish identification of the nonparametric joint distributions for each of the permanent and transitory components…

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Inference under covariate‐adaptive randomization with multiple treatments

多处理协变量自适应随机化下的推断

This paper studies inference in randomized controlled trials with covariate‐adaptive randomization when there are multiple treatments. More specifically, we study in this setting inference about the average effect of one or more treatments relative to other treatments or a control. As in Bugni, Canay, and Shaikh (2018), covariate‐adaptive randomization refers to randomization schemes that first stratify according to baseline covariates and then assign treatment status so as…

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Estimation and inference with a (nearly) singular Jacobian

雅可比矩阵近乎奇异时的估计与推断

This paper develops extremum estimation and inference results for nonlinear models with very general forms of potential identification failure when the source of this identification failure is known. We examine models that may have a general deficient rank Jacobian in certain parts of the parameter space. When identification fails in one of these models, it becomes underidentified and the identification status of individual parameters is not generally straightforward to…

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Food for fuel: The effect of the US biofuel mandate on poverty in India

粮食用于燃料:美国生物燃料强制政策对印度贫困的影响

More than 40 % of US grain is used for energy due to the Renewable Fuel Mandate (RFS). There are no studies of the global distributional consequences of this purely domestic policy. Using micro‐level survey data, we trace the effect of the RFS on world food prices and their impact on household level consumption and wage incomes in India. We first develop a partial equilibrium model to estimate the effect of the RFS on the price of selected food commodities—rice, wheat, corn,…

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HIP, RIP, and the robustness of empirical earnings processes

异质与随机收入剖面及经验收入过程的稳健性

The dispersion of individual returns to experience, often referred to as heterogeneity of income profiles (HIP), is a key parameter in empirical human capital models, in studies of life‐cycle income inequality, and in heterogeneous agent models of life‐cycle labor market dynamics. It is commonly estimated from age variation in the covariance structure of earnings. In this study, I show that this approach is invalid and tends to deliver estimates of HIP that are biased…

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Normality tests for latent variables

潜在变量的正态性检验

We exploit the rationale behind the Expectation Maximization algorithm to derive simple to implement and interpret LM normality tests for the innovations of the latent variables in linear state space models against generalized hyperbolic alternatives, including symmetric and asymmetric Student t s. We decompose our tests into third and fourth moment components, and obtain one‐sided likelihood ratio analogues, whose asymptotic distribution we provide. When we apply our tests…

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On uniform asymptotic risk of averaging GMM estimators

GMM 平均估计量的一致渐近风险

This paper studies the averaging GMM estimator that combines a conservative GMM estimator based on valid moment conditions and an aggressive GMM estimator based on both valid and possibly misspecified moment conditions, where the weight is the sample analog of an infeasible optimal weight. We establish asymptotic theory on uniform approximation of the upper and lower bounds of the finite‐sample truncated risk difference between any two estimators, which is used to compare…

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Nonstationary dynamic models with finite dependence

具有有限依赖的非平稳动态模型

The estimation of nonstationary dynamic discrete choice models typically requires making assumptions far beyond the length of the data. We extend the class of dynamic discrete choice models that require only a few‐period‐ahead conditional choice probabilities, and develop algorithms to calculate the finite dependence paths. We do this both in single agent and games settings, resulting in expressions for the value functions that allow for much weaker assumptions regarding the…

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Dynamic selection and distributional bounds on search costs in dynamic unit‐demand models

动态单位需求模型中的动态选择与搜寻成本分布界限

This paper develops a dynamic model of consumer search that, despite placing very little structure on the dynamic problem faced by consumers, allows us to exploit intertemporal variation in price distributions to estimate the distribution from which consumer search costs are initially drawn. We show that static approaches to estimating this distribution may suffer from dynamic sample selection bias. This can happen if consumers are forward‐looking and delay their purchases…

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A more powerful subvector Anderson Rubin test in linear instrumental variables regression

线性工具变量回归中更有功效的子向量 Anderson–Rubin 检验

We study subvector inference in the linear instrumental variables model assuming homoskedasticity but allowing for weak instruments. The subvector Anderson and Rubin (1949) test that uses chi square critical values with degrees of freedom reduced by the number of parameters not under test, proposed by Guggenberger, Kleibergen, Mavroeidis, and Chen (2012), controls size but is generally conservative. We propose a conditional subvector Anderson and Rubin test that uses…

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Jump factor models in large cross‐sections

大横截面中的跳跃因子模型

We develop tests for deciding whether a large cross‐section of asset prices obey an exact factor structure at the times of factor jumps. Such jump dependence is implied by standard linear factor models. Our inference is based on a panel of asset returns with asymptotically increasing cross‐sectional dimension and sampling frequency, and essentially no restriction on the relative magnitude of these two dimensions of the panel. The test is formed from the high‐frequency…

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Identification of a nonseparable model under endogeneity using binary proxies for unobserved heterogeneity

利用未观测异质性的二元代理识别内生非可分模型

In this paper, I study identification of a nonseparable model with endogeneity arising due to unobserved heterogeneity. Identification relies on the availability of binary proxies that can be used to control for the unobserved heterogeneity. I show that the model is identified in the limit as the number of proxies increases. The argument does not require an instrumental variable that is excluded from the outcome equation nor does it require the support of the unobserved…

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Bayesian inference on structural impulse response functions

结构脉冲响应函数的贝叶斯推断

I propose to estimate structural impulse responses from macroeconomic time series by doing Bayesian inference on the Structural Vector Moving Average representation of the data. This approach has two advantages over Structural Vector Autoregressions. First, it imposes prior information directly on the impulse responses in a flexible and transparent manner. Second, it can handle noninvertible impulse response functions, which are often encountered in applications. Rapid…

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