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The Macroeconomic Impact of Microeconomic Shocks: Beyond Hulten's Theorem

微观冲击的宏观影响:超越 Hulten 定理

We provide a nonlinear characterization of the macroeconomic impact of microeconomic productivity shocks in terms of reduced‐form nonparametric elasticities for efficient economies. We also show how microeconomic parameters are mapped to these reduced‐form general equilibrium elasticities. In this sense, we extend the foundational theorem of Hulten (1978) beyond the first order to capture nonlinearities. Key features ignored by first‐order approximations that play a crucial…

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Equivalence of Stochastic and Deterministic Mechanisms

随机机制与确定性机制的等价性

We consider a general social choice environment that has multiple agents, a finite set of alternatives, independent types, and atomless type distribution. We show that for any Bayesian incentive compatible mechanism, there exists an equivalent deterministic mechanism that (1) is Bayesian incentive compatible; (2) delivers the same interim expected allocation probabilities and the same interim expected utilities for all agents; and (3) delivers the same ex ante expected…

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Inference in Group Factor Models With an Application to Mixed‐Frequency Data

分组因子模型的推断及其混频数据应用

We derive asymptotic properties of estimators and test statistics to determine—in a grouped data setting—common versus group‐specific factors. Despite the fact that our test statistic for the number of common factors, under the null, involves a parameter at the boundary (related to unit canonical correlations), we derive a parameter‐free asymptotic Gaussian distribution. We show how the group factor setting applies to mixed‐frequency data. As an empirical illustration, we…

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Confidence Intervals for Projections of Partially Identified Parameters

部分识别参数投影的置信区间

We propose a bootstrap‐based calibrated projection procedure to build confidence intervals for single components and for smooth functions of a partially identified parameter vector in moment (in)equality models. The method controls asymptotic coverage uniformly over a large class of data generating processes. The extreme points of the calibrated projection confidence interval are obtained by extremizing the value of the function of interest subject to a proper relaxation of…

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Power in High‐Dimensional Testing Problems

高维检验问题中的功效

Fan, Liao, and Yao (2015) recently introduced a remarkable method for increasing the asymptotic power of tests in high‐dimensional testing problems. If applicable to a given test, their power enhancement principle leads to an improved test that has the same asymptotic size, has uniformly non‐inferior asymptotic power, and is consistent against a strictly broader range of alternatives than the initially given test. We study under which conditions this method can be applied…

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Identification With Additively Separable Heterogeneity

加法可分异质性下的识别

This paper provides nonparametric identification results for a class of latent utility models with additively separable unobservable heterogeneity. These results apply to existing models of discrete choice, bundles, decisions under uncertainty, and matching. Under an independence assumption, such models admit a representative agent. As a result, we can identify how regressors alter the desirability of goods using only average demands. Moreover, average indirect utility…

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A Distributional Framework for Matched Employer Employee Data

雇主—雇员匹配数据的分布分析框架

We propose a framework to identify and estimate earnings distributions and worker composition on matched panel data, allowing for two‐sided worker‐firm unobserved heterogeneity and complementarities in earnings. We introduce two models: a static model that allows for nonlinear interactions between workers and firms, and a dynamic model that allows, in addition, for Markovian earnings dynamics and endogenous mobility. We show that this framework nests a number of structural…

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Insurgency and Small Wars: Estimation of Unobserved Coalition Structures

叛乱与小规模战争:不可观测联盟结构的估计

Insurgency and guerrilla warfare impose enormous socio‐economic costs and often persist for decades. The opacity of such forms of conflict is an obstacle to effective international humanitarian intervention and development programs. To shed light on the internal organization of otherwise unknown insurgent groups, this paper proposes two methodologies for the detection of unobserved coalitions of militants in conflict areas. These approaches are based on daily geocoded…

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On Heckits, LATE, and Numerical Equivalence

Heckit估计、局部平均处理效应与数值等价性

Structural econometric methods are often criticized for being sensitive to functional form assumptions. We study parametric estimators of the local average treatment effect (LATE) derived from a widely used class of latent threshold crossing models and show they yield LATE estimates algebraically equivalent to the instrumental variables (IV) estimator. Our leading example is Heckman's (1979) two‐step (“Heckit”) control function estimator which, with two‐sided non‐compliance,…

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Estimation of an Equilibrium Model With Externalities: Post‐Disaster Neighborhood Rebuilding

含外部性的均衡模型估计:灾后邻里重建

We study the optimal design of subsidies in an equilibrium setting, where the decisions of individual recipients impose externalities on one another. We apply the model to the case of post‐Katrina rebuilding in New Orleans under the Louisiana Road Home rebuilding grant program (RH). We estimate the structural model via indirect inference, exploiting a discontinuity in the formula for determining the size of grants, which helps isolate the causal effect of neighbors'…

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Consistent Pseudo-Maximum Likelihood Estimators and Groups of Transformations

相合伪极大似然估计量与变换群

In a transformation model yt=c[a(xt,β),ut], where the errors ut are i.i.d. and independent of the explanatory variables xt, the parameters can be estimated by a pseudo‐maximum likelihood (PML) method, that is, by using a misspecified distribution of the errors, but the PML estimator of β is in general not consistent. We explain in this paper how to nest the initial model in an identified augmented model with more parameters in order to derive consistent PML estimators of…

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Monte Carlo Confidence Sets for Identified Sets

识别集的蒙特卡洛置信集

It is generally difficult to know whether the parameters in nonlinear econometric models are point‐identified. We provide computationally attractive procedures to construct confidence sets (CSs) for identified sets of the full parameter vector and of subvectors in models defined through a likelihood or a vector of moment equalities or inequalities. The CSs are based on level sets of “optimal” criterion functions (such as likelihoods, optimally‐weighted or…

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Nonparametric Analysis of Random Utility Models

随机效用模型的非参数分析

This paper develops and implements a nonparametric test of random utility models. The motivating application is to test the null hypothesis that a sample of cross‐sectional demand distributions was generated by a population of rational consumers. We test a necessary and sufficient condition for this that does not restrict unobserved heterogeneity or the number of goods. We also propose and implement a control function approach to account for endogenous expenditure. An…

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The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages

排序效应法:揭示平均值之外的异质效应

The partial (ceteris paribus) effects of interest in nonlinear and interactive linear models are heterogeneous as they can vary dramatically with the underlying observed or unobserved covariates. Despite the apparent importance of heterogeneity, a common practice in modern empirical work is to largely ignore it by reporting average partial effects (or, at best, average effects for some groups). While average effects provide very convenient scalar summaries of typical…

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Identifying Effects of Multivalued Treatments

多值处理效应的识别

Multivalued treatment models have typically been studied under restrictive assumptions: ordered choice, and more recently, unordered monotonicity. We show how treatment effects can be identified in a more general class of models that allows for multidimensional unobserved heterogeneity. Our results rely on two main assumptions: treatment assignment must be a measurable function of threshold‐crossing rules, and enough continuous instruments must be available. We illustrate…

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Long Memory via Networking

通过网络连接产生的长记忆

Many time series exhibit “long memory”: Their autocorrelation function decays slowly with lag. This behavior has traditionally been modeled via unit roots or fractional Brownian motion and explained via aggregation of heterogeneous processes, nonlinearity, learning dynamics, regime switching, or structural breaks. This paper identifies a different and complementary mechanism for long‐memory generation by showing that it can naturally arise when a large number of simple…

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Overidentification in Regular Models

正则模型中的过度识别

In the unconditional moment restriction model of Hansen (), specification tests and more efficient estimators are both available whenever the number of moment restrictions exceeds the number of parameters of interest. We show that a similar relationship between potential refutability of a model and existence of more efficient estimators is present in much broader settings. Specifically, a condition we name local overidentification is shown to be equivalent to both the…

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Using Instrumental Variables for Inference About Policy Relevant Treatment Parameters

利用工具变量推断政策相关处理参数

We propose a method for using instrumental variables (IV) to draw inference about causal effects for individuals other than those affected by the instrument at hand. Policy relevance and external validity turn on the ability to do this reliably. Our method exploits the insight that both the IV estimand and many treatment parameters can be expressed as weighted averages of the same underlying marginal treatment effects. Since the weights are identified, knowledge of the IV…

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Measuring Ambiguity Attitudes for All (Natural) Events

测量所有自然事件中的模糊态度

Measurements of ambiguity attitudes have so far focused on artificial events, where (subjective) beliefs can be derived from symmetry of events and can be then controlled for. For natural events as relevant in applications, such a symmetry and corresponding control are usually absent, precluding traditional measurement methods. This paper introduces two indexes of ambiguity attitudes, one for aversion and the other for insensitivity/perception, for which we can control for…

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A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models

高维线性回归变量选择的逐协变量多重检验方法

This paper provides an alternative approach to penalized regression for model selection in the context of high‐dimensional linear regressions where the number of covariates is large, often much larger than the number of available observations. We consider the statistical significance of individual covariates one at a time, while taking full account of the multiple testing nature of the inferential problem involved. We refer to the proposed method as One Covariate at a Time…

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Alternative Asymptotics for Cointegration Tests in Large VARs

大维VAR协整检验的替代渐近分析

Johansen's (1988,1991) likelihood ratio test for cointegration rank of a vector autoregression (VAR) depends only on the squared sample canonical correlations between current changes and past levels of a simple transformation of the data. We study the asymptotic behavior of the empirical distribution of those squared canonical correlations when the number of observations and the dimensionality of the VAR diverge to infinity simultaneously and proportionally. We find that the…

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Long-Run Covariability

长期共同变动性

We develop inference methods about long‐run comovement of two time series. The parameters of interest are defined in terms of population second moments of low‐frequency transformations (“low‐pass” filtered versions) of the data. We numerically determine confidence sets that control coverage over a wide range of potential bivariate persistence patterns, which include arbitrary linear combinations of I(0), I(1), near unit roots, and fractionally integrated processes. In an…

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Kernel-Based Semiparametric Estimators: Small Bandwidth Asymptotics and Bootstrap Consistency

基于核的半参数估计量:小带宽渐近与自助法一致性

This paper develops asymptotic approximations for kernel‐based semiparametric estimators under assumptions accommodating slower‐than‐usual rates of convergence of their nonparametric ingredients. Our first main result is a distributional approximation for semiparametric estimators that differs from existing approximations by accounting for a bias. This bias is nonnegligible in general, and therefore poses a challenge for inference. Our second main result shows that some (but…

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Estimating Both Supply and Demand Elasticities Using Variation in a Single Tax Rate

利用单一税率变动估计供给与需求弹性

We show how an insight from taxation theory allows identification of both the supply and demand elasticities using only one instrument. Most models of taxation since Ramsey (1927) assume that a tax levied on the demand side only affects demand through the price after taxation. Econometrically, we show that this assumption acts as an exclusion restriction. Under the Ramsey Exclusion Restriction (RER), a single tax reform can serve to simultaneously identify the demand and…

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