Journal of Econometrics最新文献

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When structural break meets threshold effect: Factor analysis under structural instabilities

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-02-20 DOI: 10.1016/j.jeconom.2025.105972

Chenchen Ma , Yundong Tu

Structural instability has been one of the central research questions in economics and finance over many decades. This paper systematically investigates structural instabilities in high dimensional factor models, which portray both structural breaks and threshold effects simultaneously. The observed high dimensional time series are concatenated at an unknown number of break points, while they are described by multiple threshold factor models that are heterogeneous between any two consecutive subsamples. Both joint and sequential procedures for estimating the break points are developed based on the second moment of the pseudo factor estimates that fully ignore the structural instabilities. In each separated subsample, the group Lasso approach recently proposed by Ma and Tu (2023b) is adopted to efficiently identify the threshold factor structure. An information criterion is further proposed to determine the number of break points, which also serves the purpose to distinguish the two types of instabilities. Theoretical properties of the proposed estimators are established, and their finite sample performance is evaluated in Monte Carlo simulations. An empirical application to the U.S. financial market dataset demonstrates the consequences when structural break meets threshold effect in factor analysis.

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引用次数: 0

Simple subvector inference on sharp identified set in affine models

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-02-14 DOI: 10.1016/j.jeconom.2025.105952

Bulat Gafarov

This paper studies a regularized support function estimator for bounds on components of the parameter vector in the case in which the identified set is a polygon. The proposed regularized estimator has three important properties: (i) it has a uniform asymptotic Gaussian limit in the presence of flat faces in the absence of redundant (or overidentifying) constraints (or vice versa); (ii) the bias from regularization does not enter the first-order limiting distribution; (iii) the estimator remains consistent for sharp (non-enlarged) identified set for the individual components even in the non-regular case. These properties are used to construct uniformly valid confidence sets for an element

θ_{1}

of a parameter vector

θ \in R^{d}

that is partially identified by affine moment equality and inequality conditions. The proposed confidence sets can be computed as a solution to a small number of linear and convex quadratic programs, leading to a substantial decrease in computation time and guarantees a global optimum. As a result, the method provides a uniformly valid inference in applications in which the dimension of the parameter space,

d

, and the number of inequalities,

k

, were previously computationally unfeasible (

d, k = 100

). The proposed approach can be extended to construct confidence sets for intersection bounds, to construct joint polygon-shaped confidence sets for multiple components of

θ

, and to find the set of solutions to a linear program. Inference for coefficients in the linear IV regression model with an interval outcome is used as an illustrative example.

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引用次数: 0

On time-varying panel data models with time-varying interactive fixed effects

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-02-07 DOI: 10.1016/j.jeconom.2025.105960

Xia Wang , Sainan Jin , Yingxing Li , Junhui Qian , Liangjun Su

This paper introduces a time-varying (TV) panel data model with interactive fixed effects where both the coefficients and factor loadings are allowed to change smoothly over time. We propose a local version of the least squares and principal component method to estimate the TV coefficients, TV factor loadings, and common factors simultaneously. We provide a bias-corrected local least squares estimator for the TV coefficients and establish the limiting distributions and uniform convergence of the bias-corrected coefficient estimators, estimated factors, and factor loadings in the large

N

and large

T

framework. Based on the estimates, we propose three test statistics to gauge possible sources of TV features. We establish the limit null distributions and the asymptotic local power properties of our tests. Simulations are conducted to evaluate the finite sample performance of our estimates and tests. We apply our theoretical results to analyze the Phillips curve using the U.S. state-level unemployment rates and nominal wages, and document significant TV behavior in both the slope coefficient and factor loadings.

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引用次数: 0

Three-dimensional heterogeneous panel data models with multi-level interactive fixed effects

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-02-03 DOI: 10.1016/j.jeconom.2025.105957

Sainan Jin , Xun Lu , Liangjun Su

We consider a three-dimensional (3D) panel data model with heterogeneous slope coefficients and multi-level interactive fixed effects consisting of latent global factors and two types of local factors. Our model nests many commonly used 3D panel data models. We propose an iterative estimation procedure that relies on initial consistent estimators obtained through a novel defactored approach. We study the asymptotic properties of our estimators and show that our iterative estimators of the slope coefficients are “oracle efficient” in the sense that they are asymptotically equivalent to those when the factors were known. Some specification testing issues are also considered. Monte Carlo simulations demonstrate that our estimators and tests perform well in finite samples. We apply our new method to the international trade dataset.

引用次数: 0

Penalized estimation of finite mixture models

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-02-03 DOI: 10.1016/j.jeconom.2025.105958

Sofya Budanova

Economists often model unobserved heterogeneity using finite mixtures. In practice, the number of mixture components is rarely known. Model parameters lack point-identification if the estimation includes too many components, thus invalidating the classic properties of maximum likelihood estimation. I propose a penalized likelihood method to estimate finite mixtures with an unknown number of components. The resulting Order-Selection-Consistent Estimator (OSCE) consistently estimates the true number of components and achieves oracle efficiency. This paper extends penalized estimation to models without point-identification and to mixtures with growing number of components. I apply the OSCE to estimate players’ rationality levels in a coordination game.

引用次数: 0

Identification and estimation of a search model with heterogeneous consumers and firms

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-01-30 DOI: 10.1016/j.jeconom.2025.105956

Mateusz Myśliwski , May Rostom , Fabio Sanches , Daniel Silva Jr , Sorawoot Srisuma

We propose a model of nonsequential consumer search where consumers and firms differ in search and production costs respectively. We characterize the equilibrium of the game. We first show the distribution of search cost can be identified by market shares and prices. Subsequently, we identify the production cost distribution using a similar strategy to Guerre, Perrigne and Vuong (2000) as the firms’ decision problems resemble bidders’ problems in a particular procurement auction. We prove the firm’s cost density can be estimated at the same convergence rate as the optimal rate in Guerre et al. uniformly over any fixed subset on the interior of the support. The uniform convergence rate over any expanding support is slower due to a pole in the price pdf that is a feature of the equilibrium. Our simulation study confirms the theoretical features of the model. Our identification and convergence rate results also apply to two generalizations of the baseline search model that allow for: (i) vertically differentiated products; (ii) an intermediary. We apply the latter model to study loan search using UK mortgage data.

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引用次数: 0

The robust F-statistic as a test for weak instruments

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-01-01 DOI: 10.1016/j.jeconom.2025.105951

Frank Windmeijer

For the linear model with a single endogenous variable, (Montiel Olea and Pflueger 2013) proposed the effective F-statistic as a test for weak instruments in terms of the Nagar bias of the two-stage least squares (2SLS) or limited information maximum likelihood (LIML) estimator relative to a benchmark worst-case bias. We show that their methodology for the 2SLS estimator applies to a class of linear generalized method of moments (GMM) estimators with an associated class of generalized effective F-statistics. The standard robust F-statistic is a member of this class. The associated GMMf estimator, with the extension “f” for first-stage, has the weight matrix based on the first-stage residuals. In the grouped-data IV designs of Andrews (2018) with moderate and high levels of endogeneity and where the robust F-statistic is large but the effective F-statistic is small, the GMMf estimator is shown to behave much better in terms of bias than the 2SLS estimator.

对于单一内生变量的线性模型，（Montiel Olea 和 Pflueger，2013 年）提出了有效 F 统计量，作为两阶段最小二乘（2SLS）或有限信息最大似然（LIML）估计器相对于基准最坏情况偏差的纳加尔偏差的弱工具检验。我们表明，他们针对 2SLS 估计器的方法适用于一类线性广义矩法 (GMM) 估计器，以及相关的一类广义有效 F 统计量。标准稳健 F 统计量就是这一类的成员。相关的 GMMf 估计器（扩展名为 "f "表示第一阶段）的权重矩阵基于第一阶段的残差。在 Andrews（2018）的分组数据 IV 设计中，具有中等和高等程度的内生性，且稳健 F 统计量较大但有效 F 统计量较小，GMMf 估计器在偏差方面的表现比 2SLS 估计器要好得多。

引用次数: 0

Bond risk premiums at the zero lower bound

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-01-01 DOI: 10.1016/j.jeconom.2024.105939

Martin M. Andreasen , Kasper Jørgensen , Andrew Meldrum

We document that the spread between long- and short-term government bond yields is a stronger predictor of excess bond returns when the U.S. economy is at the zero lower bound (ZLB) than away from this bound. The Gaussian shadow rate model with a linear or quadratic shadow rate is unable to explain this change in return predictability. The same holds for the quadratic term structure model and the autoregressive gamma-zero model that also enforce the ZLB. In contrast, the linear-rational square-root model explains our new empirical finding because the model allows for unspanned stochastic volatility as seen in bond yields.

我们发现，当美国经济处于零下限（ZLB）时，长短期政府债券收益率之间的利差对债券超额收益的预测作用比远离零下限时更强。具有线性或二次影子利率的高斯影子利率模型无法解释这种收益预测性的变化。同样执行 ZLB 的二次期限结构模型和自回归伽马-零模型也是如此。相比之下，线性理性平方根模型可以解释我们新的经验发现，因为该模型允许债券收益率中出现的非跨度随机波动。

引用次数: 0

Iterative estimation of nonparametric regressions with continuous endogenous variables and discrete instruments

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-01-01 DOI: 10.1016/j.jeconom.2025.105950

Samuele Centorrino , Frédérique Fève , Jean-Pierre Florens

We consider a nonparametric regression model with continuous endogenous independent variables when only discrete instruments are available that are independent of the error term. Although this framework is very relevant for applied research, its implementation is challenging, as the regression function becomes the solution to a nonlinear integral equation. We propose a simple iterative procedure to estimate such models and showcase some of its asymptotic properties. In a simulation experiment, we detail its implementation in the case when the instrumental variable is binary. We conclude with an empirical application to returns to education.

当只有独立于误差项的离散工具时，我们考虑了一个具有连续内生自变量的非参数回归模型。尽管这一框架与应用研究密切相关，但其实施却极具挑战性，因为回归函数变成了非线性积分方程的解。我们提出了一个简单的迭代程序来估计此类模型，并展示了它的一些渐近特性。在模拟实验中，我们详细介绍了在工具变量为二元变量的情况下该程序的实施。最后，我们将对教育回报进行实证应用。

引用次数: 0

Simulation error and numerical instability in estimating random coefficient logit demand models

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2025-01-01 DOI: 10.1016/j.jeconom.2025.105953

Daniel Brunner , Florian Heiss , André Romahn , Constantin Weiser

The nonlinear GMM-IV estimator of Berry, Levinsohn and Pakes (1995) can suffer from numerical instability resulting in a wide range of parameter estimates and economic implications. This has been reported to depend on technical details such as the choice of the optimization algorithm, starting values, and convergence criteria. We show that numerical approximation errors in the estimator’s moment function are the main driver of this instability. With accurate approximation, the estimation approach is well-behaved. We provide a simple method to determine the required number of simulation draws.

Berry、Levinsohn 和 Pakes（1995 年）的非线性 GMM-IV 估计器可能会出现数值不稳定的问题，导致参数估计和经济影响范围广泛。据报道，这取决于优化算法的选择、起始值和收敛标准等技术细节。我们的研究表明，估计矩函数中的数值近似误差是造成这种不稳定性的主要原因。在精确近似的情况下，估计方法就会表现良好。我们提供了一种简单的方法来确定所需的模拟抽样次数。

引用次数: 0

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