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To be or not to be: Roughness or long memory in volatility? 生存还是毁灭：波动中的粗糙还是长期记忆？
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-02-09 DOI: 10.1016/j.jeconom.2026.106193
Mikkel Bennedsen , Kim Christensen , Peter Korsbakke Christensen
{"title":"To be or not to be: Roughness or long memory in volatility?","authors":"Mikkel Bennedsen ,&nbsp;Kim Christensen ,&nbsp;Peter Korsbakke Christensen","doi":"10.1016/j.jeconom.2026.106193","DOIUrl":"10.1016/j.jeconom.2026.106193","url":null,"abstract":"<div><div>We develop a framework for composite likelihood estimation of parametric continuous-time stationary Gaussian processes. We derive the asymptotic theory of the associated maximum composite likelihood estimator. We implement our approach on a pair of models that have been proposed to describe the random log-spot variance of financial asset returns. A simulation study shows that it delivers good performance in these settings and improves upon a method-of-moments estimation. In an empirical investigation, we inspect the dynamic of an intraday measure of the spot log-realized variance computed with high-frequency data from the cryptocurrency market. The evidence supports a mechanism, where the short- and long-term correlation structure of stochastic volatility are decoupled in order to capture its properties at different time scales. This is further backed by an analysis of the associated spot log-trading volume.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106193"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171155","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
Convolution-t distributions Convolution-t分布
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-02-10 DOI: 10.1016/j.jeconom.2026.106212
Peter Reinhard Hansen , Chen Tong
{"title":"Convolution-t distributions","authors":"Peter Reinhard Hansen ,&nbsp;Chen Tong","doi":"10.1016/j.jeconom.2026.106212","DOIUrl":"10.1016/j.jeconom.2026.106212","url":null,"abstract":"<div><div>We introduce a family of multivariate heavy-tailed distributions, termed convolution-<em>t</em> distributions, constructed as convolutions of heterogeneous multivariate <em>t</em>-distributions. Unlike commonly used heavy-tailed distributions, this family captures nonlinear dependencies, accommodates heterogeneous marginal distributions, and reveals cluster structures prevalent in economic data. Importantly, convolution-<em>t</em> distributions admit simple closed-form densities that facilitate estimation and likelihood-based inference. The characteristic features of convolution-<em>t</em> distributions are shown to be important in an empirical analysis of realized volatility measures and help uncover their underlying factor structure.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106212"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171158","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
The informativeness of combined experimental and observational data under dynamic selection 动态选择下实验与观测资料相结合的信息量
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-02-26 DOI: 10.1016/j.jeconom.2026.106219
Yechan Park , Yuya Sasaki
{"title":"The informativeness of combined experimental and observational data under dynamic selection","authors":"Yechan Park ,&nbsp;Yuya Sasaki","doi":"10.1016/j.jeconom.2026.106219","DOIUrl":"10.1016/j.jeconom.2026.106219","url":null,"abstract":"<div><div>The Average Treatment Effect on the Treated Survivors (ATETS; Vikström et al., 2018) captures a composite effect of time-varying treatment and dynamic selection into the survivor population. We address the problem of identifying this treatment-effect parameter in the absence of long-term experimental data, utilizing available long-term observational data instead. This poses a nontrivial challenge in practice, as dynamic selection compounds static selection in observational data. We establish two theoretical results. First, it is impossible to obtain informative bounds without model restrictions or auxiliary data. Second, to overturn this negative result, we explore the recent econometric developments in combining experimental and observational data (e.g., Athey et al., 2025; 2024) as a promising avenue; we find that exploiting short-term experimental data can be informative without imposing classical model restrictions. Building on Chesher and Rosen (2017), we further explore how to systematically derive sharp identification bounds, leveraging both novel data-combination principles and classical model restrictions. Estimation and inference procedures are also provided. Applying the proposed method, we investigate what can be learned about the long-run effects of job training programs on employment in the absence of long-term experimental data.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106219"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384788","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
Estimating a conditional density ratio model for asset returns and option demand 估计资产收益和期权需求的条件密度比模型
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-02-11 DOI: 10.1016/j.jeconom.2026.106191
Jeroen Dalderop , Oliver Linton
{"title":"Estimating a conditional density ratio model for asset returns and option demand","authors":"Jeroen Dalderop ,&nbsp;Oliver Linton","doi":"10.1016/j.jeconom.2026.106191","DOIUrl":"10.1016/j.jeconom.2026.106191","url":null,"abstract":"<div><div>Option-implied risk-neutral densities are widely used for constructing forward-looking risk measures. Meanwhile, risk aversion introduces a multiplicative pricing kernel between the risk-neutral and true conditional densities of the underlying asset’s return. This paper proposes a simple local estimator of the pricing kernel based on inverse density weighting. We characterize the asymptotic bias and variance of the estimator and its multiplicatively corrected density forecasts. A local exponential linear variant is proposed to include conditioning variables. The estimator performs well in a simulation study, even when the risk-neutral densities are noisy and/or have missing tails. We apply our estimator to a demand-based model for S&amp;P 500 index options, and find U-shaped pricing kernels when end-users sell out-of-the-money options and volatility is high.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106191"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171107","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
Time-varying macroeconomic announcement risk 时变宏观经济公告风险
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-02-03 DOI: 10.1016/j.jeconom.2026.106194
Michael Johannes , Norman J. Seeger , Jonathan R. Stroud
{"title":"Time-varying macroeconomic announcement risk","authors":"Michael Johannes ,&nbsp;Norman J. Seeger ,&nbsp;Jonathan R. Stroud","doi":"10.1016/j.jeconom.2026.106194","DOIUrl":"10.1016/j.jeconom.2026.106194","url":null,"abstract":"<div><div>This paper examines an issue overlooked in the finance and economics literature: time variation in announcement volatility or event risk. To identify this, we combine long spans of high-frequency data with a flexible model of returns. The model allows us to separately identify conditional event risk from other factors like time-varying volatility, jumps and intraday periodicity, and long time spans of data are needed given the infrequency of most announcements. We focus on crude oil due to its economic importance, high volatility and complex announcement structure. Results indicate strong evidence for time-varying announcement volatility as announcement event risk varies by as much as a factor of 10 over time.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106194"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171154","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
Minimax rates of convergence for nonparametric location-Scale models 非参数位置尺度模型的极大极小收敛率
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-01-23 DOI: 10.1016/j.jeconom.2026.106187
Bingxin Zhao , Yuhong Yang
{"title":"Minimax rates of convergence for nonparametric location-Scale models","authors":"Bingxin Zhao ,&nbsp;Yuhong Yang","doi":"10.1016/j.jeconom.2026.106187","DOIUrl":"10.1016/j.jeconom.2026.106187","url":null,"abstract":"<div><div>This paper studies minimax rates of convergence for nonparametric location-scale models, which include mean, quantile, expectile and momentile regression settings. Under Hellinger differentiability on the error distribution and other mild conditions, we show that the minimax rate of convergence for estimating the regression function under the squared <em>L</em><sub>2</sub> loss is determined by the metric entropy of the nonparametric function class. Different error distributions, including asymmetric Laplace distribution, asymmetric connected double truncated gamma distribution, connected normal-Laplace distribution, Cauchy distribution and asymmetric normal distribution are studied as examples. Applications on low order interaction models and multiple index models are also given.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106187"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015887","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
GMM inference in the matrix exponential spatial specification 矩阵指数空间规范中的GMM推理
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-01-22 DOI: 10.1016/j.jeconom.2026.106181
Ye Yang , Wim P.M. Vijverberg
{"title":"GMM inference in the matrix exponential spatial specification","authors":"Ye Yang ,&nbsp;Wim P.M. Vijverberg","doi":"10.1016/j.jeconom.2026.106181","DOIUrl":"10.1016/j.jeconom.2026.106181","url":null,"abstract":"<div><div>This paper offers hypothesis and specification tests for the best generalized methods of moment estimator (BGMME) of the matrix exponential spatial specification (MESS) developed by Debarsy et al. (2015). First, as the BGMME is a two-step estimator, we formulate corrected standard errors using a modified version of the finite sample correction method in Windmeijer (2005) that accounts for the fact that the BGMME makes more extensive use of the first-stage estimator than the GMM model analyzed by Windmeijer. Second, since the BGMME uses different moment conditions under normal, non-normal, and heteroskedastic disturbances, we propose a pretest strategy to determine which set of moment conditions is most suitable for the data at hand. Third, we consider and examine the performance of test statistics that help choose between MESS(1,1), MESS(1,0) and MESS(0,1) models. The performance of these tools is examined with Monte Carlo experiments, which also allow for varying degrees of spatial correlation in the explanatory variables. The correction in the standard errors is especially useful when the sample size is small, such as in a study with state-level, provincial or country-level data: the corrected standard errors improve statistical inference, yielding better size properties. The pretest strategy is effective when the heteroskedasticity, if present, is correlated with explanatory variables in the model. Spatial lags in the outcome variable are more easily detected than those in the disturbance. An empirical study of housing prices illustrates the new tools.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106181"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015886","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
Semiparametric estimation of duration model with time-varying regressors and fixed effects 具有时变回归量和固定效应的持续时间模型的半参数估计
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-02-11 DOI: 10.1016/j.jeconom.2026.106195
Songnian Chen , Qian Wang
{"title":"Semiparametric estimation of duration model with time-varying regressors and fixed effects","authors":"Songnian Chen ,&nbsp;Qian Wang","doi":"10.1016/j.jeconom.2026.106195","DOIUrl":"10.1016/j.jeconom.2026.106195","url":null,"abstract":"<div><div>In this paper, we consider estimation of an accelerated failure time model with time-varying regressors and fixed effects for duration data. We propose computationally simple profiled estimators for both fixed and random censoring cases. Under regularity conditions, we establish consistency and asymptotic normality of the estimators. Simulation studies demonstrate that our estimators perform well in finite samples. Finally, we use data from the First Malaysian Family Life Survey to illustrate our proposed estimation method.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106195"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171159","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
Introduction to the Issue on High Frequency Econometrics 高频计量经济学问题导论
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2025-12-31 DOI: 10.1016/j.jeconom.2025.106175
Lukas Bauer , Roxana Halbleib , Richard Olsen , Torben G. Andersen , Ingmar Nolte
{"title":"Introduction to the Issue on High Frequency Econometrics","authors":"Lukas Bauer ,&nbsp;Roxana Halbleib ,&nbsp;Richard Olsen ,&nbsp;Torben G. Andersen ,&nbsp;Ingmar Nolte","doi":"10.1016/j.jeconom.2025.106175","DOIUrl":"10.1016/j.jeconom.2025.106175","url":null,"abstract":"","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106175"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399261","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
Testing for jumps in a discretely observed price process with endogenous sampling times 具有内生抽样时间的离散观察价格过程的跳跃检验
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2025-11-18 DOI: 10.1016/j.jeconom.2025.106132
Qiyuan Li , Yifan Li , Ingmar Nolte , Sandra Nolte , Shifan Yu
{"title":"Testing for jumps in a discretely observed price process with endogenous sampling times","authors":"Qiyuan Li ,&nbsp;Yifan Li ,&nbsp;Ingmar Nolte ,&nbsp;Sandra Nolte ,&nbsp;Shifan Yu","doi":"10.1016/j.jeconom.2025.106132","DOIUrl":"10.1016/j.jeconom.2025.106132","url":null,"abstract":"<div><div>This paper introduces a novel nonparametric high-frequency jump test for discretely observed Itô semimartingales. Based on observations sampled recursively at first exit times from a symmetric double barrier, our method distinguishes between threshold exceedances caused by the Brownian component and jumps, which enables the construction of a feasible, noise-robust statistical test. Simulation results demonstrate superior finite-sample performance of our test compared to existing methods. An empirical analysis of NYSE-traded stocks provides clear statistical evidence for jumps, with the results highly robust to spurious detections.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106132"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399601","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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