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Nonparametric identification of first-price auction with unobserved competition: A density discontinuity framework

未观测竞争下的第一价格拍卖非参数识别:密度断点框架

We consider nonparametric identification of independent private value first-price auction models, in which the analyst only observes winning bids. Our benchmark model assumes an exogenous number of bidders N. We show that, if the bidders observe N, the resulting discontinuities in the winning bid density can be used to identify the distribution of N. The private value distribution can be nonparametrically identified in a second step. This extends, under testable…

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Economies of Scale to Consumption in Collective Households

集体家庭消费中的规模经济

ABSTRACT Browning et al. (2013) model collective‐household economies of scale in goods consumption by having each good be partly shared, instead of each good being public or private. We modify their model to achieve simple point identification and estimation of the economies of scale of consumption of each good, and we provide a new index of household level economies of scale. Our model has a linear form, permits households of varying composition, including children, and…

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A Panel Data Estimator for the Distribution and Quantiles of Marginal Effects in Nonlinear Structural Models with an Application to the Demand for Junk Food

非线性结构模型中边际效应分布与分位数的面板估计:垃圾食品需求应用

In this paper, we propose a framework to estimate the distribution of marginal effects in a general class of structural models that allow for very general nonlinearities, high dimensional heterogeneity, and unrestricted correlation between the persistent components of this heterogeneity and all covariates. The main idea is to form a derivative dependent variable using two periods of the panel and use differences in outcome variables of nearby subpopulations to obtain the…

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Comment on ‘Selection and Comparative Advantage in Technology Adoption’ by Suri (2011)

对 Suri (2011)《技术采纳中的选择与比较优势》的评论

This paper illustrates and addresses weak identification in the correlated random coefficient (CRC) model that Suri (2011) uses to study agricultural technology adoption. Using the publicly available dataset, which differs slightly from the version used in Suri (2011), we obtain different point estimates for the paper’s main CRC model. To understand why these differences are as large as they are, we recast the CRC model as a more general random coefficient model in which the…

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Extreme Value Theory with Heterogeneous Agents

异质性主体下的极值理论

Extreme value processes feature in any economic model in which agents receive a number of draws from some distribution and we examine the behavior of the maximum in the limit as the number of draws becomes large. This paper asks: Do the average outcomes of such processes change when different agents receive a different number of draws? To answer this, we allow the number of draws an agent receives from the underlying distribution (e.g. of productivities, ideas, or utility…

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Information Based Inference in Models with Set-Valued Predictions and Misspecification

集合值预测与模型误设下的信息推断

This paper proposes an information-based inference method for partially identified parameters in incomplete models that is valid both when the model is correctly specified and when it is misspecified. Key features of the method are: (i) it is based on minimizing a suitably defined Kullback-Leibler information criterion that accounts for incompleteness of the model and delivers a non-empty pseudotrue set; (ii) it is computationally tractable; (iii) its implementation is the…

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Why Are the Wealthiest So Wealthy? New Longitudinal Empirical Evidence and Implications for Theories of Wealth Inequality

最富者为何如此富有?新的纵向经验证据及其对财富不平等理论的启示

We study the lifecycle dynamics of wealth inequality using 1993-2019 Norwegian administrative panel data on wealth and income. Employing a novel budget-constraint approach, we decompose the excess wealth of the top 0.1% households relative to the median between ages 45 and 64 into higher saving rates (36%), inheritances (31%), returns (28%), and labor income (5%). One-quarter of the wealthiest—the “New Money”—start with negative wealth on average but accumulate rapidly…

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Production Function Estimation with Factor-Augmenting Technology: An Application to Markups

含要素增强型技术的生产函数估计:加成率的应用

I develop a new method for estimating production functions with laboraugmenting technology and apply it to markup estimation. The method imposes limited parametric restrictions and generalizes prior approaches that rely on the CES production function. I first extend the canonical Olley-Pakes framework assumptions to multidimensional productivity and then develop an identification strategy based on a control variable approach and first-order conditions. I use this method to…

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The Design of Defined Contribution Plans

固定缴费养老金计划的设计

Defined contribution plans are a major vehicle for retirement savings in the US, holding almost $10 trillion in assets under management. In recent years, the quality and availability of these plans has been the subject of active policy attention and of several major lawsuits. This paper studies how employers and plan providers design these plans. We argue that low plan quality and limited provision can come from two sources. First, employer willingness to pay may be…

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Scaling Agricultural Policy Interventions

农业政策干预的规模化效应

Policies to raise agricultural productivity have been central in the fight against global poverty. Their impacts are often measured in experiments that provide strong causal identification but may be too small-scale to capture general equilibrium effects that arise when policies are scaled up. We develop a quantitative model of agricultural trade, featuring a granular economic geography, that combines parameters estimated from small-scale experiments with rich administrative…

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The Efficient Deployment of Police Resources: Theory and New Evidence from a Randomized Drunk Driving Crackdown in India

警力资源的有效部署:来自印度随机酒驾严打的理论与新证据

Should police activity be narrowly focused and high force, or widely dispersed but of moderate intensity? Critics of intense “hotspot” policing argue it primarily displaces, not reduces, crime. But if learning about enforcement takes time, the police may take advantage of that period to intervene intensively in the most productive location. We propose a multi-armed bandit model of criminal learning and structurally estimate its parameters using data from a randomized…

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Testable Implications of Parametric Assumptions in Ordered Random Utility Models

有序随机效用模型中参数假设的可检验含义

We establish the testable implications of ordered random utility models under nonparametric, semi-nonparametric, and parametric assumptions. After characterizing these models in a continuous setting and in the absence of fundamental parametric restrictions, we show that assumptions about the type distribution alone are immaterial, while assumptions about the map linking types to utilities are relevant only insofar as they restrict the class of utilities at stake.…

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Finite-Sample Auction Inference Using Transaction Prices

利用成交价格进行有限样本拍卖推断

We first provide inference on the quantile function of the bid distribution in firstprice or descending auctions, and the quantile function of the value distribution in second-price or ascending auctions, with a known number of bidders with symmetric independent private values. Specifically, we provide finite-sample, nonparametric, tuning parameter-free, uniform confidence bands for these quantile functions when observing only the transaction price. We also show how these…

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Finite-State Markov-Chain Approximations: A Hidden Markov Approach

有限状态马尔可夫链近似:一种隐马尔可夫方法

This paper proposes a novel finite-state Markov chain approximation method for Markov processes with continuous support, providing both an optimal grid and a transition probability matrix. The method can be used for multivariate processes and processes with time-varying components. It is based on minimizing the information loss between a Hidden Markov Model and the true data-generating process. We provide sufficient conditions under which this information loss can be made…

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Worker-Side Discrimination: Beliefs and Preferences

劳动者侧歧视:信念与偏好

When agents choose among options with unobserved attributes to maximize expected utility, their choices conflate preferences with beliefs about those attributes. We develop a novel theory-driven identification strategy for such settings, showing that compensating differentials separately identify beliefs from preferences. Noting that workers’ preferences and beliefs shape labor market outcomes, yet remain understudied, we apply our method to provide the first evidence on the…

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Estimating individual responses when tomorrow matters

未来预期重要时的个体反应估计

We propose an approach to estimate how individuals’ expectations influence their responses to a counterfactual change. The approach relies on average partial effects, which recover counterfactual impacts under conditions that we specify. We propose a three-step estimation method that relies on panel data on subjective expectations. We illustrate our approach in a model of consumption and saving, focusing on the impact of an income tax that not only changes current income but…

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Incorporating Micro Data into Differentiated Products Demand Estimation with PyBLP

使用 PyBLP 将微观数据纳入差异化产品需求估计

We delineate a general framework for incorporating many types of micro data from summary statistics to full surveys of selected consumers into Berry, Levinsohn, and Pakes (1995)-style estimates of differentiated products demand systems. We extend recommended practices for BLP estimation in Conlon and Gortmaker (2020) to the case with micro data and implement them in our open-source package PyBLP. Monte Carlo experiments and empirical examples suggest that incorporating micro…

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A User’s guide for inference in models defined by moment inequalities

矩不等式模型推断的实用指南

Models defined by moment inequalities have become a standard modeling framework for empirical economists, spreading over a wide range of fields within economics. From the point of view of an empirical researcher, the literature on inference in moment inequality models is large and complex, including multiple survey papers that document the non-standard features these models possess, the main novel concepts behind inference in these models, and the most recent developments…

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Bayesian Model Averaging in Causal Instrumental Variable Models

因果工具变量模型中的贝叶斯模型平均

ABSTRACT Instrumental variables are a popular tool to infer causal effects under unobserved confounding, but choosing suitable instruments is challenging in practice. We propose gIVBMA, a Bayesian model averaging procedure that addresses this challenge by averaging across different sets of instrumental variables and covariates in a structural equation model. This allows for data‐driven selection of valid and relevant instruments and provides additional robustness against…

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HIGHER-ORDER DEBIASED ESTIMATORS FOR GENERAL TREATMENT MODELS

一般处理模型的高阶去偏估计量

We have witnessed tremendous progress in developing the foundation for econometrics and causal inference in the past decades. The most popular paradigm is the classical (first-order) semiparametric theory, in which a key building block is the (first-order) influence function. However, it is well known that estimators based on influence functions can be sub-optimal in various settings. To address this issue, higher-order influence functions (HOIF) are developed. However, most…

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Estimating Network Externalities in Undirected Link Formation Games

无向连接形成博弈中的网络外部性估计

ABSTRACT This paper explores the existence of network externalities in link formation games of incomplete information. It extends the structural estimation method in Leung (2015) to games where links are undirected and proposals are only partially observed. We provide an econometric characterization of the proposed two‐step estimator and document its performance through a simulation exercise. When the estimation method is applied to data on risk‐sharing arrangements in a…

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Identification and estimation in a time-varying endogenous random coefficient panel data model

时变内生随机系数面板模型的识别与估计

This paper proposes a correlated random coefficient linear panel data model, where regressors can be correlated with time-varying and individual-specific random coefficients through both a fixed effect and a time-varying random shock. I develop a new panel data-based method to identify the average partial effect and the local average response function. The identification strategy employs a sufficient statistic to control for the fixed effect and a control variable for the…

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Semi-nonparametric models of multidimensional matching: An optimal transport approach

多维匹配的半非参数模型:最优传输方法

This paper develops a set of empirically tractable and flexible sieve estimators for semi-nonparametric multidimensional matching models with transferable utility, focusing on worker-job matching. We generalize the parametric quadratic-Gaussian framework employed by Bojilov and Galichon (2016) and Lindenlaub (2017), which relies on joint normality of observed characteristics. We allow unrestricted distributions of characteristics and show identification of the production…

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Likelihood specification in simultaneous equation models for discrete data

离散数据联立方程模型的似然设定

In this article, we examine the foundations of a rich and diverse literature in economics and derive the likelihood function of simultaneous equation models for discrete data as the invariant distribution of a suitably specified Markov process. This formulation offers a well-defined reduced form of the model and dispenses with the need for controversial recursivity requirements and ad hoc indeterminacy rules. The derivation resolves puzzling paradoxes highlighted in earlier…

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