Journal of Econometrics最新文献

英文中文

Unobserved component models, approximate filters and dynamic adaptive mixture models 未观察组件模型，近似滤波器和动态自适应混合模型

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2025-11-28 DOI: 10.1016/j.jeconom.2025.106155

Leopoldo Catania , Enzo D’Innocenzo , Alessandra Luati

State estimation in unobserved component models with parameter uncertainty is traditionally performed through approximate filters, where Gaussian distributions with given moments are employed to replace otherwise intractable conditional densities. This paper re-examines signal-plus-noise models where parameter uncertainty is induced by a latent variable that may assume a fixed number of states. First, it is shown that, for these models, the approximate filters commonly adopted in the literature can be obtained as linear combinations of minimum variance linear unbiased estimators. Second, it is observed that they coincide with filters implied by a novel class of dynamic adaptive mixture models, where the parameters of a mixture of distributions evolve over time following a recursion that is based on the score of the one-step-ahead predictive distribution. Focusing on a robust specification, where the mixture components are Student’s t distributions, we prove existence, stationarity, and ergodicity of the data generating process as well as invertibility of the filter, and consistency and asymptotic normality of the maximum likelihood estimator of the static parameters. An application to energy spot prices is discussed, where the novel specification is compared with, and shown to outperform, robust score-driven filters and the related class of mixture autoregressive models.

具有参数不确定性的不可观测组件模型的状态估计传统上是通过近似滤波器进行的，其中使用具有给定矩的高斯分布来取代否则难以处理的条件密度。本文重新研究了信号加噪声模型，其中参数的不确定性是由可能具有固定数量状态的潜在变量引起的。首先，证明了对于这些模型，文献中常用的近似滤波器可以作为最小方差线性无偏估计量的线性组合得到。其次，观察到它们与一类新的动态自适应混合模型所隐含的过滤器相吻合，其中混合分布的参数随着时间的推移而演变，并遵循基于一步前预测分布得分的递归。关注一个鲁棒规范，其中混合成分是学生的t分布，我们证明了数据生成过程的存在性，平稳性和遍历性，以及滤波器的可逆性，以及静态参数的最大似然估计的一致性和渐近正态性。讨论了能源现货价格的应用，其中将新规范与鲁棒分数驱动滤波器和相关类别的混合自回归模型进行了比较，并表明其优于鲁棒分数驱动滤波器。

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引用次数: 0

Quantile approach to intertemporal consumption with multiple assets 多资产跨期消费的分位数方法

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2025-12-08 DOI: 10.1016/j.jeconom.2025.106161

Luciano de Castro , Antonio F. Galvao , Hirofumi Ota

This paper develops a novel economic model and econometric methods to jointly identify and estimate parameters related to intertemporal preference and risk attitude. We begin by formulating an intertemporal consumption model with multiple assets based on dynamic quantile preferences that account for elasticity of intertemporal substitution, risk attitude, and discount factor. We establish the properties of the model and obtain interesting explicit expressions for the value function, and the optimal consumption. In addition, we derive the quantile Euler equation. From this equilibrium condition, we show that, when at least two returns are available, one is able to separately identify the risk attitude, which is measured by the quantile τ, and the elasticity of intertemporal substitution and discount factor. We propose new econometric theory for estimating these parameters of interest and establish the statistical properties of the semiparametric two-step estimator. In particular, we show that the estimator is consistent, with a cubic-root rate of convergence, derive its limiting distribution, and suggest a subsampling procedure for inference. Finally, we empirically estimate the structural model, and results show evidence that discount factor is slightly smaller than one, the elasticity of intertemporal substitution is larger than one, and risk attitude is close to the median.

本文建立了一个新的经济模型和计量经济学方法来共同识别和估计与跨期偏好和风险态度有关的参数。首先，我们基于动态分位数偏好建立了一个跨期消费模型，该模型考虑了跨期替代的弹性、风险态度和贴现因子。我们建立了模型的性质，得到了价值函数和最优消费的显式表达式。此外，我们导出了分位数欧拉方程。从这一均衡条件出发，我们发现，当至少存在两种收益时，其中一种能够分别识别风险态度（由分位数τ衡量）和跨期替代和贴现因子的弹性。我们提出了新的计量经济学理论来估计这些感兴趣的参数，并建立了半参数两步估计量的统计性质。特别地，我们证明了估计量是一致的，具有三根的收敛速率，推导了它的极限分布，并提出了一种推断的子抽样方法。最后对结构模型进行实证估计，结果表明贴现因子略小于1，跨期替代弹性大于1，风险态度接近中位数。

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引用次数: 0

Bootstraps for dynamic panel threshold models 动态面板阈值模型的自举

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2025-11-24 DOI: 10.1016/j.jeconom.2025.106153

Woosik Gong , Myung Hwan Seo

This paper develops valid bootstrap inference methods for the dynamic short panel threshold regression. We show that the standard nonparametric bootstrap is inconsistent for the first-differenced generalized method of moments (GMM) estimator. The inconsistency arises from an

n^{1 / 4}

-consistent non-normal asymptotic distribution of the threshold estimator when the true parameter lies in the continuity region of the parameter space, which stems from the rank deficiency of the approximate Jacobian of the sample moment conditions on the continuity region. To address this, we propose a grid bootstrap to construct confidence intervals for the threshold and a residual bootstrap to construct confidence intervals for the coefficients. They are shown to be valid regardless of the model’s continuity. Moreover, we establish a uniform validity for the grid bootstrap. A set of Monte Carlo experiments compares the proposed bootstraps with the standard nonparametric bootstrap. An empirical application to a firm investment model illustrates our methods.

针对动态短面板阈值回归，提出了有效的自举推理方法。证明了一阶差分广义矩量法（GMM）估计量的标准非参数自举是不一致的。当真参数位于参数空间的连续区域时，阈值估计量的非正态渐近分布是n1/4一致的，这是由于样本矩条件在连续区域上的近似雅可比矩阵的秩不足造成的。为了解决这个问题，我们提出了一个网格自举来构建阈值的置信区间，一个残差自举来构建系数的置信区间。无论模型的连续性如何，它们都是有效的。此外，我们还建立了网格自举的统一有效性。一组蒙特卡罗实验将所提出的自举与标准非参数自举进行了比较。一个企业投资模型的实证应用说明了我们的方法。

引用次数: 0

Difference-in-Differences with compositional changes 差异中的差异与成分的变化

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2025-11-19 DOI: 10.1016/j.jeconom.2025.106147

Pedro H.C. Sant’Anna , Qi Xu

This paper studies Difference-in-Differences (DiD) setups with repeated cross-sectional data and potential compositional changes across time periods. We begin our analysis by deriving the efficient influence function and the semiparametric efficiency bound for the average treatment effect on the treated (ATT). We introduce nonparametric estimators that attain the semiparametric efficiency bound under mild rate conditions on the estimators of the nuisance functions, exhibiting a type of rate doubly robust (DR) property. Additionally, we document a trade-off related to compositional changes: We derive the asymptotic bias of DR DiD estimators that erroneously exclude compositional changes and the efficiency loss when one fails to correctly rule out compositional changes. We propose a nonparametric Hausman-type test for compositional changes based on these trade-offs. The finite sample performance of the proposed DiD tools is evaluated through Monte Carlo experiments and an empirical application. We consider extensions of our framework that accommodate double machine learning procedures with cross-fitting, and setups when some units are observed in both pre- and post-treatment periods. As a by-product of our analysis, we present a new uniform stochastic expansion of the local polynomial multinomial logit estimator, which may be of independent interest.

本文研究了具有重复横截面数据和跨时间段潜在成分变化的差异中的差异（DiD）设置。我们通过推导平均处理效应对被处理（ATT）的有效影响函数和半参数效率界开始分析。我们引入了非参数估计量，在温和速率条件下，在扰值函数的估计量上得到半参数效率界，并表现出一种速率双鲁棒性。此外，我们记录了与组成变化相关的权衡：我们推导了DR DiD估计器的渐近偏差，该估计器错误地排除了组成变化，并且当一个人未能正确排除组成变化时，效率损失。我们提出了一个基于这些权衡的成分变化的非参数hausman型检验。通过蒙特卡罗实验和经验应用评估了所提出的DiD工具的有限样本性能。我们考虑扩展我们的框架，以适应交叉拟合的双重机器学习过程，并在处理前后观察到一些单元时进行设置。作为我们分析的副产品，我们给出了局部多项式多项式对数估计量的一个新的一致随机展开式，它可能具有独立的意义。

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引用次数: 0

On generalized CCE estimation 关于广义CCE估计

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2026-01-14 DOI: 10.1016/j.jeconom.2026.106183

Xun Lu , Liangjun Su , Yinglong Ba

The widely-used common correlated effects (CCE) estimator, pioneered by Pesaran (2006), is computed using least squares applied to auxiliary regressions where the observed regressors are augmented with cross-sectional averages of the dependent variable and regressors. However, the CCE estimator requires a crucial rank condition and becomes inconsistent when this condition is violated and the factor loadings of the x- and y -equations are correlated, causing an endogeneity issue. This paper proposes a generalized CCE (GCCE) estimator by augmenting the regression with both cross-sectional and time-series averages of the regressors. We argue that the time-series average can serve as “control variables” to address the endogeneity issue. We show that the GCCE and CCE estimators are asymptotically equivalent when the rank condition holds, and the GCCE estimator remains consistent even when the rank condition is violated under our “control variable” condition. Therefore, our GCCE estimator is doubly robust, achieving consistency under either the rank condition or the “control variable” condition. Furthermore, we propose a leave-one-out jackknife method to conduct valid inferences regardless of whether the rank condition holds. Monte Carlo simulations demonstrate excellent performance of our estimators and inference methods in finite samples. We apply our new methods to two datasets to estimate the production function and gravity equation.

由Pesaran（2006）首创的广泛使用的共同相关效应（CCE）估计量是使用应用于辅助回归的最小二乘来计算的，其中观察到的回归量与因变量和回归量的横截面平均值相增强。然而，CCE估计器需要一个关键的秩条件，当这个条件被违反并且x-和y -方程的因子负载是相关的时，CCE估计器就会变得不一致，从而导致内质性问题。本文提出了一种广义CCE （GCCE）估计量，通过对回归量的横截面平均值和时间序列平均值进行扩充。我们认为时间序列平均值可以作为“控制变量”来解决内生性问题。我们证明了当秩条件成立时，GCCE和CCE估计量是渐近等价的，并且在我们的“控制变量”条件下，即使违反秩条件，GCCE估计量也保持一致。因此，我们的GCCE估计器是双鲁棒的，无论是在秩条件下还是在“控制变量”条件下都实现了一致性。此外，我们提出了一种不考虑秩条件是否成立的留一折刀方法来进行有效的推理。蒙特卡罗模拟证明了我们的估计器和推理方法在有限样本下的优异性能。我们将新方法应用于两个数据集来估计生产函数和重力方程。

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引用次数: 0

Estimation and inference for large-dimensional generalized matrix factor models 大维广义矩阵因子模型的估计与推理

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2026-01-04 DOI: 10.1016/j.jeconom.2025.106179

Xinbing Kong, Tong Zhang

This article introduces a nonlinear generalized matrix factor model, moving beyond the linear-Gaussian framework to accommodate a broader class of response models typically handled via logit, probit, Poisson, or Tobit structures. We introduce a novel Lagrange multiplier method carefully tailored to ensure that the penalized likelihood function is locally concave around the true factor and loading parameters. This leads to central limit theorems of the estimated factors and loadings which is nontrivial for nonlinear matrix factor modeling. We establish the convergence rates of the estimated factor and loading matrices for the generalized matrix factor model under general conditions that allow for correlations across samples, rows, and columns. We provide a model selection criterion to determine the numbers of row and column factors. Extensive simulation studies demonstrate the superiority in handling discrete and mixed-type variables of the generalized matrix factor model. An empirical data analysis of the company’s operating performance shows that the generalized matrix factor model does clustering and reconstruction well in the presence of discontinuous entries in the data matrix.

本文介绍了一个非线性广义矩阵因子模型，超越了线性-高斯框架，以适应通常通过logit、probit、泊松或Tobit结构处理的更广泛的响应模型。我们引入了一种新颖的拉格朗日乘子方法，以确保惩罚似然函数在真实因子和加载参数周围局部凹。这导致了估计因子和负荷的中心极限定理，这对于非线性矩阵因子建模是非平凡的。我们为广义矩阵因子模型在允许跨样本、行和列的相关性的一般条件下建立了估计因子和加载矩阵的收敛率。我们提供了一个模型选择标准来确定行和列因素的数量。大量的仿真研究证明了广义矩阵因子模型在处理离散变量和混合变量方面的优越性。对该公司经营业绩的实证数据分析表明，广义矩阵因子模型在数据矩阵中存在不连续条目的情况下，能够很好地进行聚类和重构。

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引用次数: 0

Decomposing informed trading in equity options 股票期权的信息交易分解

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2025-11-20 DOI: 10.1016/j.jeconom.2025.106131

Felipe Asencio , Alejandro Bernales , Daniel González , Richard Holowczak , Thanos Verousis

We develop a multi-asset model to decompose informed trading into the components concerning the underlying stock-value and the volatility in equity options. We isolate the stock-value and volatility components by characterizing their distinct intraday price responses in contracts with different option deltas and vegas, respectively. The stock-value (volatility) component represents on average 41 % (19 %) of the option spread, which remains substantial under various statistical validity analyses and robustness checks. In daily empirical applications, we also show that volatility-informed trading anticipates a 'Volmageddon' high-volatility event, and straddle trades are positively associated with volatility-informed trading.

我们开发了一个多资产模型，将知情交易分解为有关标的股票价值和股票期权波动率的组件。我们分别用不同的期权delta和vegas来描述它们不同的日内价格反应，从而分离出股票价值和波动性成分。股票价值（波动率）成分平均占期权价差的41%(19%)，在各种统计有效性分析和稳健性检查下，这一比例仍然很大。在日常经验应用中，我们还表明，波动率知情交易预测了“Volmageddon”高波动事件，而跨界交易与波动率知情交易呈正相关。

引用次数: 0

Strategic network formation with many agents 战略网络形成与许多代理商

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2025-12-31 DOI: 10.1016/j.jeconom.2025.106174

Konrad Menzel

We derive asymptotic approximations for models of strategic network formation, where limits are taken as the number of nodes (agents) increases to infinity. Our framework assumes a random utility model where agents have heterogeneous tastes over links, and payoffs allow for anonymous and non-anonymous interaction effects, and the observed network is assumed to be pairwise stable. Our main results concern convergence of the link intensity from finite pairwise stable networks to the (many-player) limiting distribution. The set of possible limiting distributions is shown to have a fairly simple form and is characterized through aggregate equilibrium conditions, which may permit multiple solutions. We illustrate how these formal results can be used to analyze identification of link preferences and estimate or bound preference parameters. We also derive an analytical expression for agents’ welfare (expected surplus) from the structure of the network.

我们导出了策略网络形成模型的渐近逼近，其中节点（智能体）的数量增加到无穷大时取极限。我们的框架假设了一个随机的实用模型，其中代理对链接有异质的品味，并且回报允许匿名和非匿名交互效应，并且假设观察到的网络是两两稳定的。我们的主要结果是关于链路强度从有限对稳定网络到（多参与者）极限分布的收敛性。可能的极限分布集具有相当简单的形式，并通过可能允许多个解的总平衡条件来表征。我们说明了如何使用这些形式化结果来分析链接偏好的识别和估计或绑定偏好参数。我们还从网络的结构中推导出代理福利（期望剩余）的解析表达式。

引用次数: 0

Identification in nonlinear dynamic panel models under partial stationarity 部分平稳下非线性动态面板模型的辨识

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2026-01-16 DOI: 10.1016/j.jeconom.2026.106185

Wayne Yuan Gao , Rui Wang

This paper provides a general identification approach for a wide range of nonlinear panel data models, including binary choice, ordered response, and other types of limited dependent variable models. Our approach accommodates dynamic models with any number of lagged dependent variables as well as other types of endogenous covariates. Our identification strategy relies on a partial stationarity condition, which allows for not only an unknown distribution of errors, but also temporal dependencies in errors. We derive partial identification results under flexible model specifications and establish sharpness of our identified set in the binary choice setting. We demonstrate the robust finite-sample performance of our approach using Monte Carlo simulations, and apply the approach to the empirical analysis of income categories using various ordered choice models.

本文为各种非线性面板数据模型提供了一种通用的识别方法，包括二元选择、有序响应和其他类型的有限因变量模型。我们的方法适应动态模型与任何数量的滞后因变量以及其他类型的内生协变量。我们的识别策略依赖于部分平稳条件，这不仅允许误差的未知分布，而且允许误差的时间依赖性。我们在灵活的模型规范下得到了部分识别结果，并在二元选择设置下建立了识别集的清晰度。我们使用蒙特卡罗模拟证明了我们方法的强大有限样本性能，并使用各种有序选择模型将该方法应用于收入类别的实证分析。

引用次数: 0

Testing for peer effects without specifying the network structure 在不指定网络结构的情况下测试对等效应

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2025-11-14 DOI: 10.1016/j.jeconom.2025.106124

Hyunseok Jung , Xiaodong Liu

This paper proposes an Anderson–Rubin (AR) test for the presence of peer effects in panel data without the need to specify the network structure. The unrestricted model of our test is a linear panel data model of social interactions with dyad-specific peer effect coefficients for all potential peers. The proposed AR test evaluates if these peer effect coefficients are all zero. As the number of peer effect coefficients increases with the sample size, so does the number of instrumental variables (IVs) employed to test the restrictions under the null, rendering a many-IV environment of Bekker (1994). By extending existing many-IV asymptotic results to panel data, we establish the asymptotic validity of the proposed AR test. Our Monte Carlo simulations show the robustness and improved performance of the proposed test compared to some existing tests with misspecified networks. We provide two applications to demonstrate its empirical relevance.

本文在不指定网络结构的情况下，提出了面板数据中对等效应存在的安德森-鲁宾（AR）检验方法。我们测试的无限制模型是一个线性面板数据模型，具有所有潜在同伴特定的同伴效应系数的社会互动。提出的AR检验评估这些对等效应系数是否都为零。随着样本量的增加，同伴效应系数的数量也会增加，用于检验null下限制的工具变量（IVs）的数量也会增加，从而呈现出Bekker（1994）的多iv环境。通过将现有的许多- iv渐近结果扩展到面板数据，我们建立了所提出的AR检验的渐近有效性。我们的蒙特卡罗模拟表明，与现有的一些错误指定网络的测试相比，所提出的测试具有鲁棒性和改进的性能。我们提供了两个应用程序来证明其经验相关性。

引用次数: 0

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