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Non-Parametric identification of stationary dynamic discrete choicemodels 平稳动态离散选择模型的非参数辨识
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2025-12-10 DOI: 10.1016/j.jeconom.2025.106164
Adam Dearing
{"title":"Non-Parametric identification of stationary dynamic discrete choicemodels","authors":"Adam Dearing","doi":"10.1016/j.jeconom.2025.106164","DOIUrl":"10.1016/j.jeconom.2025.106164","url":null,"abstract":"<div><div>We provide new non-parametric identification results for stationary dynamic discrete choice models, where both the flow utilities and the distribution of unobserved shocks are fully non-parametric. Our main identification result establishes that a multinomial choice model is non-parametrically identified when there is a special regressor that (i) has a known derivative in the utility function (e.g., enters utility quasi-linearly); (ii) only affects the evolution of the other variables indirectly through the policy function; and (iii) exhibits a type of bounded persistence. To our knowledge, this is the first non-parametric identification result for stationary models that does not require any state variable to exhibit a form of serial independence. Our identification arguments map conditional choice probabilities and the state transition process into structural primitives, and they can be applied to models with persistent unobserved heterogeneity. Our identification results have broad applicability in practice, since candidate variables for the special regressor are already common in the empirical literature.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106164"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Dynamic panel data quantile regression with network-linked fixed effects 具有网络关联固定效应的动态面板数据分位数回归
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2026-01-19 DOI: 10.1016/j.jeconom.2026.106188
Shiwei Huang , Yu Chen , Jie Hu , Weiping Zhang
{"title":"Dynamic panel data quantile regression with network-linked fixed effects","authors":"Shiwei Huang ,&nbsp;Yu Chen ,&nbsp;Jie Hu ,&nbsp;Weiping Zhang","doi":"10.1016/j.jeconom.2026.106188","DOIUrl":"10.1016/j.jeconom.2026.106188","url":null,"abstract":"<div><div>This paper introduces a <strong>d</strong>ynamic panel data <strong>q</strong>uantile <strong>r</strong>egression model with <strong>n</strong>etwork-linked <strong>f</strong>ixed <strong>e</strong>ffects, named DQR-NFE, in which unobserved individual heterogeneity is structured through an underlying network. The corresponding estimator is derived by incorporating a <strong>q</strong>uantile <strong>n</strong>etwork <strong>c</strong>ohesion (QNC) penalty into the dynamic panel quantile regression framework. This penalty encourages connected units within the network to exhibit similar conditional quantiles, with a particularly increased capacity to capture tail network dependence. Relative to conventional fixed-effects specifications, the proposed framework improves the estimation of unobserved heterogeneity and enables more accurate prediction in cold-start settings where training data are unavailable. We establish the consistency and asymptotic normality of the DQR-NFE estimators within a general nonlinear structural framework. These theoretical guarantees hold under both correctly specified and misspecified network structures, with an explicit characterization of their dependence on the network topology. Simulation studies and empirical applications reveal that the proposed estimator outperforms competing approaches in terms of both estimation accuracy and out-of-sample forecasting.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106188"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A simple, robust identification approach for first-price auctions 一种简单、可靠的首价拍卖识别方法
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2026-01-19 DOI: 10.1016/j.jeconom.2025.106173
Serafin Grundl , Yu Zhu
{"title":"A simple, robust identification approach for first-price auctions","authors":"Serafin Grundl ,&nbsp;Yu Zhu","doi":"10.1016/j.jeconom.2025.106173","DOIUrl":"10.1016/j.jeconom.2025.106173","url":null,"abstract":"<div><div>This paper proposes a new approach to the identification of first-price auctions that is robust to overbidding, but at the same time remains contiguous with the canonical point-identification approach of Guerre et al. (2000) (GPV) and its simple estimators. We show that a weak identifying restriction allows us to reinterpret the GPV estimates as a bound. We demonstrate that the identifying restriction holds in a set of commonly used auction models that can generate overbidding and is satisfied in the bid data from a laboratory experiment. We illustrate the approach in applications to laboratory data and field data. We recommend that practitioners continue to follow the GPV approach, but interpret the estimates as a bound in applications where they are concerned about overbidding.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106173"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Robustness to missing data: breakdown point analysis 对缺失数据的稳健性：分解点分析
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2025-12-26 DOI: 10.1016/j.jeconom.2025.106151
Daniel Ober-Reynolds
{"title":"Robustness to missing data: breakdown point analysis","authors":"Daniel Ober-Reynolds","doi":"10.1016/j.jeconom.2025.106151","DOIUrl":"10.1016/j.jeconom.2025.106151","url":null,"abstract":"<div><div>Missing data is pervasive in econometric applications, and rarely is it plausible that the data are missing (completely) at random. This paper proposes a methodology for studying the robustness of results drawn from incomplete datasets. Selection is measured as the divergence from the distribution of complete observations to the distribution of incomplete observations. The <em>breakdown point</em> is defined as the minimal amount of selection needed to overturn a given result. Reporting point estimates and lower confidence intervals of the breakdown point is a simple, concise way to communicate the robustness of a result. An estimator of the breakdown point is proposed and shown <span><math><msqrt><mrow><mi>n</mi></mrow></msqrt></math></span>-consistent and asymptotically normal. This estimator can be applied directly to conclusions drawn from any model identified with the generalized method of moments (GMM) that satisfies mild assumptions. Simulations demonstrate the finite sample performance of the breakdown point estimator on averages, linear regression, and logistic regression. The methodology is illustrated by estimating the breakdown point of conclusions drawn from several randomized controlled trails suffering from missing data due to attrition.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106151"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Nonparametric treatment effect identification in school choice 择校中的非参数治疗效果识别
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2026-01-05 DOI: 10.1016/j.jeconom.2025.106172
Jiafeng Chen
{"title":"Nonparametric treatment effect identification in school choice","authors":"Jiafeng Chen","doi":"10.1016/j.jeconom.2025.106172","DOIUrl":"10.1016/j.jeconom.2025.106172","url":null,"abstract":"<div><div>This paper studies nonparametric identification and estimation of causal effects in centralized school assignment. In many centralized assignment algorithms, students face both lottery-driven variation and regression discontinuity- (RD) driven variation. We characterize the full set of identified <em>atomic treatment effects</em> (aTEs), defined as the conditional average treatment effect between a pair of schools given student characteristics. Atomic treatment effects are the building blocks of more aggregated treatment contrasts, and common approaches to estimating aTE aggregations can mask important heterogeneity. In particular, many aggregations of aTEs put zero weight on aTEs driven by RD variation, and estimators of such aggregations put asymptotically vanishing weight on the RD-driven aTEs. We provide a diagnostic and recommend new aggregation schemes. Lastly, we provide estimators and asymptotic results for inference on these aggregations.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106172"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Five lessons for applied researchers from twenty years of common correlated effects estimation 二十年常见相关效应估计给应用研究人员的五点启示
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2025-11-13 DOI: 10.1016/j.jeconom.2025.106120
Artūras Juodis , Simon Reese
{"title":"Five lessons for applied researchers from twenty years of common correlated effects estimation","authors":"Artūras Juodis ,&nbsp;Simon Reese","doi":"10.1016/j.jeconom.2025.106120","DOIUrl":"10.1016/j.jeconom.2025.106120","url":null,"abstract":"<div><div>This article distills the vast literature on Common Correlated Effects (CCE), initiated by the seminal contribution of Pesaran (2006), into five practical lessons. We provide a concise overview of the CCE framework and describe the reasons for its popularity in empirical (macro-) panel data research. The lessons we draw focus on aspects that have received substantial methodological attention, but remain underappreciated in empirical work.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106120"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhancements of communication-efficient distributed statistical inference and its privacy preservation 提高通信效率的分布式统计推断及其隐私保护
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2025-11-13 DOI: 10.1016/j.jeconom.2025.106125
Miaomiao Yu , Jiaxuan Li , Yong Zhou
{"title":"Enhancements of communication-efficient distributed statistical inference and its privacy preservation","authors":"Miaomiao Yu ,&nbsp;Jiaxuan Li ,&nbsp;Yong Zhou","doi":"10.1016/j.jeconom.2025.106125","DOIUrl":"10.1016/j.jeconom.2025.106125","url":null,"abstract":"<div><div>In the modern era of big data, the vast amount of available data has brought more ways to analyze important economic and financial issues. For example, predicting the probability of individual default has become more accurate, as the number of defaulted individuals has increased year-on-year with the increase in data volume, leading to a more detailed characterization of the defaulted population. However, it presents new challenges and one of them is that all samples are separately stored in different machines and cannot be transferred directly for privacy considerations and limited data storage capacity. This paper develops an improved communication-efficient distributed algorithm in which more local summarized information is used to estimate the high-order derivatives of the loss function with lower communication cost. Furthermore, to protect the privacy in the interacted vector, we design a privacy-preserving algorithm based on the differential privacy constraint by adding a Laplace-distributed noise term in the parameters that can be extended to other cases beyond distributed architectures. Both non-private and private schemes, in which only local estimators are passed from the local machine to the central machine, are more theoretically and practically accurate and efficient than their counterparts. Then we suggest a bootstrap scheme to estimate the covariance matrix of the parametric estimators that is beneficial to effective inference. Finally, we find that the proposed method can effectively handle the practical activities that are, accurate probabilistic predictions of default risk and climate activity.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106125"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multi-horizon test for market frictions 市场摩擦的多视界检验
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2025-12-29 DOI: 10.1016/j.jeconom.2025.106171
Z. Merrick Li , Xiye Yang
{"title":"Multi-horizon test for market frictions","authors":"Z. Merrick Li ,&nbsp;Xiye Yang","doi":"10.1016/j.jeconom.2025.106171","DOIUrl":"10.1016/j.jeconom.2025.106171","url":null,"abstract":"<div><div>We test for the presence of market frictions that induce transitory deviations of observed asset prices from the underlying efficient prices. Our test is based on the joint inference of return covariances across multiple horizons. We demonstrate that a small set of horizons suffices to identify a broad spectrum of frictions, both theoretically and practically. Our method works for high- and low-frequency data under different asymptotic regimes. Extensive simulations show our method outperforms widely used state-of-the-art tests. Our empirical studies indicate that intraday transaction prices from recent years can be considered effectively friction-free at significantly higher frequencies.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106171"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145880565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Quasi-Bayesian estimation and inference with control functions 带控制函数的拟贝叶斯估计与推理
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2025-11-13 DOI: 10.1016/j.jeconom.2025.106126
Ruixuan Liu , Zhengfei Yu
{"title":"Quasi-Bayesian estimation and inference with control functions","authors":"Ruixuan Liu ,&nbsp;Zhengfei Yu","doi":"10.1016/j.jeconom.2025.106126","DOIUrl":"10.1016/j.jeconom.2025.106126","url":null,"abstract":"<div><div>This paper introduces a quasi-Bayesian method that integrates frequentist nonparametric estimation with Bayesian inference in a two-stage process. Applied to an endogenous discrete choice model, the approach first uses kernel or sieve estimators to estimate the control function nonparametrically, followed by Bayesian methods to estimate the structural parameters. This combination leverages the advantages of both frequentist tractability for nonparametric estimation and Bayesian computational efficiency for complicated structural models. We analyze the asymptotic properties of the resulting quasi-posterior distribution, finding that its mean provides a consistent estimator for the parameters of interest, although its quantiles do not yield valid confidence intervals. However, bootstrapping the quasi-posterior mean accounts for the estimation uncertainty from the first stage, thereby producing asymptotically valid confidence intervals</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106126"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145527584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Empirical welfare maximization with constraints 有约束的经验福利最大化
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-01-01 Epub Date: 2025-12-24 DOI: 10.1016/j.jeconom.2025.106169
Liyang Sun
{"title":"Empirical welfare maximization with constraints","authors":"Liyang Sun","doi":"10.1016/j.jeconom.2025.106169","DOIUrl":"10.1016/j.jeconom.2025.106169","url":null,"abstract":"<div><div>Empirical Welfare Maximization (EWM) is a framework that can be used to select welfare program eligibility policies based on data. This paper extends EWM by allowing for uncertainty in estimating the budget needed to implement the selected policy, in addition to its welfare. Due to the additional estimation error, I show there exist no rules that achieve the highest welfare possible while satisfying a budget constraint uniformly over a wide range of DGPs. This differs from the setting without a budget constraint where uniformity is achievable. I propose an alternative trade-off rule and illustrate it with Medicaid expansion, a setting with imperfect take-up and varying program costs.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"253 ","pages":"Article 106169"},"PeriodicalIF":4.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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