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Fixed‐Effect Regressions on Network Data

网络数据的固定效应回归

This paper considers inference on fixed effects in a linear regression model estimated from network data. An important special case of our setup is the two‐way regression model. This is a workhorse technique in the analysis of matched data sets, such as employer–employee or student–teacher panel data. We formalize how the structure of the network affects the accuracy with which the fixed effects can be estimated. This allows us to derive sufficient conditions on the network…

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Nonparametric Inference on State Dependence in Unemployment

失业状态依赖的非参数推断

This paper is about measuring state dependence in dynamic discrete outcomes. I develop a nonparametric dynamic potential outcomes (DPO) model and propose an array of parameters and identifying assumptions that can be considered in this model. I show how to construct sharp identified sets under combinations of identifying assumptions by using a flexible linear programming procedure. I apply the analysis to study state dependence in unemployment for working age high school…

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Measuring Group Differences in High‐Dimensional Choices: Method and Application to Congressional Speech

高维选择中的群体差异测度:方法及国会演讲应用

We study the problem of measuring group differences in choices when the dimensionality of the choice set is large. We show that standard approaches suffer from a severe finite‐sample bias, and we propose an estimator that applies recent advances in machine learning to address this bias. We apply this method to measure trends in the partisanship of congressional speech from 1873 to 2016, defining partisanship to be the ease with which an observer could infer a…

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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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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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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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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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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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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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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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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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Hurdles and steps: Estimating demand for solar photovoltaics

门槛与阶梯:太阳能光伏需求的估计

This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros, unobserved heterogeneity, and endogeneity of price. Our results imply a price elasticity of demand for solar PV systems of −0.65. Counterfactual policy simulations indicate that reducing state financial incentives in half would have led to 9% fewer new installations in Connecticut in 2014.…

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Strong convergence and dynamic economic models

强收敛与动态经济模型

Morton and Wecker (1977) stated that the value iteration algorithm solves a dynamic program's policy function faster than its value function when the limiting Markov chain is ergodic. I show that their proof is incomplete, and provide a new proof of this classic result. I use this result to accelerate the estimation of Markov decision processes and the solution of Markov perfect equilibria.

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Inference in dynamic discrete choice problems under local misspecification

局部误设下动态离散选择问题的推断

Single‐agent dynamic discrete choice models are typically estimated using heavily parametrized econometric frameworks, making them susceptible to model misspecification. This paper investigates how misspecification affects the results of inference in these models. Specifically, we consider a local misspecification framework in which specification errors are assumed to vanish at an arbitrary and unknown rate with the sample size. Relative to global misspecification, the local…

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Partial identification by extending subdistributions

通过扩展子分布实现部分识别

I show that sharp identified sets in a large class of econometric models can be characterized by solving linear systems of equations. These linear systems determine whether, for a given value of a parameter of interest, there exists an admissible joint distribution of unobservables that can generate the distribution of the observed variables. The joint distribution of unobservables is not required to satisfy any parametric restrictions, but can (if desired) be assumed to…

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