Journal of Econometrics最新文献_第4页

Conditional spectral methods 条件谱法

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-03-01 DOI: 10.1016/j.jeconom.2024.105863

Federico M. Bandi , Yinan Su

引用次数: 0

Long-run risk in stationary vector autoregressive models 平稳向量自回归模型的长期风险

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-03-01 DOI: 10.1016/j.jeconom.2024.105905

Christian Gourieroux , Joann Jasiak

引用次数: 0

Functional ecological inference 功能生态推断

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-03-01 DOI: 10.1016/j.jeconom.2024.105918

Christian Bontemps , Jean-Pierre Florens , Nour Meddahi

{"title":"Functional ecological inference","authors":"Christian Bontemps , Jean-Pierre Florens , Nour Meddahi","doi":"10.1016/j.jeconom.2024.105918","DOIUrl":"10.1016/j.jeconom.2024.105918","url":null,"abstract":"<div><div>In this paper, we consider the problem of ecological inference when one observes the conditional distributions of <span><math><mrow><mi>Y</mi><mo>|</mo><mi>W</mi></mrow></math></span> and <span><math><mrow><mi>Z</mi><mo>|</mo><mi>W</mi></mrow></math></span> from aggregate data and attempts to infer the conditional distribution of <span><math><mrow><mi>Y</mi><mo>|</mo><mi>Z</mi></mrow></math></span> without observing <span><math><mi>Y</mi></math></span> and <span><math><mi>Z</mi></math></span> in the same sample. First, we show that this problem can be transformed into a linear equation involving operators for which, under suitable regularity assumptions, least squares solutions are available. We then propose the use of the least squares solution with the minimum Hilbert–Schmidt norm, which, in our context, can be structurally interpreted as the solution with minimum dependence between <span><math><mi>Y</mi></math></span> and <span><math><mi>Z</mi></math></span>. Interestingly, in the case where the conditioning variable <span><math><mi>W</mi></math></span> is discrete and belongs to a finite set, such as the labels of units/groups/cities, the solution of this minimal dependence has a closed form. In the more general case, we use a regularization scheme and show the convergence of our proposed estimator. A numerical evaluation of our procedure is proposed.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105918"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526834","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

Identifying the volatility risk price through the leverage effect 通过杠杆效应识别波动风险价格

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-03-01 DOI: 10.1016/j.jeconom.2024.105943

Xu Cheng , Eric Renault , Paul Sangrey

{"title":"Identifying the volatility risk price through the leverage effect","authors":"Xu Cheng , Eric Renault , Paul Sangrey","doi":"10.1016/j.jeconom.2024.105943","DOIUrl":"10.1016/j.jeconom.2024.105943","url":null,"abstract":"<div><div>In asset pricing models with stochastic volatility, uncertainty about volatility affects risk premia through two channels: aversion to decreasing returns and aversion to increasing volatility. We analyze the identification of and robust inference for structural parameters measuring investors’ aversions to these risks: the return risk price and the volatility risk price. In the presence of a leverage effect (instantaneous causality between the asset return and its volatility), we study the identification of both structural parameters with the price data only, without relying on additional option pricing models or option data. We analyze this identification challenge in a nonparametric discrete-time exponentially affine model, complementing the continuous-time approach of Bandi and Renò (2016). We then specialize to a parametric model and derive the implied minimum distance criterion relating the risk prices to the asset return and volatility’s joint distribution. This criterion is almost flat when the leverage effect is small, and we introduce identification-robust confidence sets for both risk prices regardless of the magnitude of the leverage effect.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"248 ","pages":"Article 105943"},"PeriodicalIF":9.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526862","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 large confirmatory dynamic factor model for stock market returns in different time zones 不同时区股票市场收益的大验证性动态因子模型

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-02-25 DOI: 10.1016/j.jeconom.2025.105971

Oliver B. Linton , Haihan Tang , Jianbin Wu

引用次数: 0

Multiplicative factor model for volatility 波动率的乘因子模型

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-02-21 DOI: 10.1016/j.jeconom.2025.105959

Yi Ding , Robert Engle , Yingying Li , Xinghua Zheng

引用次数: 0

Tensor time series imputation through tensor factor modelling 通过张量因子建模的张量时间序列输入

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-02-21 DOI: 10.1016/j.jeconom.2025.105974

Zetai Cen , Clifford Lam

{"title":"Tensor time series imputation through tensor factor modelling","authors":"Zetai Cen , Clifford Lam","doi":"10.1016/j.jeconom.2025.105974","DOIUrl":"10.1016/j.jeconom.2025.105974","url":null,"abstract":"<div><div>We propose tensor time series imputation when the missing pattern in the tensor data can be general, as long as any two data positions along a tensor fibre are both observed for enough time points. The method is based on a tensor time series factor model with Tucker decomposition of the common component. One distinguished feature of the tensor time series factor model used is that there can be weak factors in the factor loading matrix for each mode. This reflects reality better when real data can have weak factors which drive only groups of observed variables, for instance, a sector factor in a financial market driving only stocks in a particular sector. Using the data with missing entries, asymptotic normality is derived for rows of estimated factor loadings, while consistent covariance matrix estimation enables us to carry out inferences. As a first in the literature, we also propose a ratio-based estimator for the rank of the core tensor under general missing patterns. Rates of convergence are spelt out for the imputations from the estimated tensor factor models. Simulation results show that our imputation procedure works well, with asymptotic normality and corresponding inferences also demonstrated. Re-imputation performances are also gauged when we demonstrate that using slightly larger rank then estimated gives superior re-imputation performances. A Fama–French portfolio example with matrix returns and an OECD data example with matrix of economic indicators are presented and analysed, showing the efficacy of our imputation approach compared to direct vector imputation.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"249 ","pages":"Article 105974"},"PeriodicalIF":9.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465008","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

When structural break meets threshold effect: Factor analysis under structural instabilities 当结构断裂满足阈值效应时：结构不稳定下的因子分析

IF 9.9 3区经济学

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

Chenchen Ma , Yundong Tu

{"title":"When structural break meets threshold effect: Factor analysis under structural instabilities","authors":"Chenchen Ma , Yundong Tu","doi":"10.1016/j.jeconom.2025.105972","DOIUrl":"10.1016/j.jeconom.2025.105972","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"249 ","pages":"Article 105972"},"PeriodicalIF":9.9,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445074","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

Simple subvector inference on sharp identified set in affine models 仿射模型中尖锐识别集的简单子向量推理

IF 9.9 3区经济学

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

Bulat Gafarov

{"title":"Simple subvector inference on sharp identified set in affine models","authors":"Bulat Gafarov","doi":"10.1016/j.jeconom.2025.105952","DOIUrl":"10.1016/j.jeconom.2025.105952","url":null,"abstract":"<div><div>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 <em>uniformly valid</em> confidence sets for an element <span><math><msub><mrow><mi>θ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> of a parameter vector <span><math><mrow><mi>θ</mi><mo>∈</mo><msup><mrow><mi>R</mi></mrow><mrow><mi>d</mi></mrow></msup></mrow></math></span> 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, <span><math><mi>d</mi></math></span>, and the number of inequalities, <span><math><mi>k</mi></math></span>, were previously computationally unfeasible (<span><math><mrow><mi>d</mi><mo>,</mo><mi>k</mi><mo>=</mo><mn>100</mn></mrow></math></span>). The proposed approach can be extended to construct confidence sets for intersection bounds, to construct joint polygon-shaped confidence sets for multiple components of <span><math><mi>θ</mi></math></span>, 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.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"249 ","pages":"Article 105952"},"PeriodicalIF":9.9,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422341","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

On time-varying panel data models with time-varying interactive fixed effects 具有时变交互固定效应的时变面板数据模型

IF 9.9 3区经济学

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

{"title":"On time-varying panel data models with time-varying interactive fixed effects","authors":"Xia Wang , Sainan Jin , Yingxing Li , Junhui Qian , Liangjun Su","doi":"10.1016/j.jeconom.2025.105960","DOIUrl":"10.1016/j.jeconom.2025.105960","url":null,"abstract":"<div><div>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 <span><math><mi>N</mi></math></span> and large <span><math><mi>T</mi></math></span> 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.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"249 ","pages":"Article 105960"},"PeriodicalIF":9.9,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349423","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