Journal of Econometrics最新文献_第10页

Heterogeneous treatment effect bounds under sample selection with an application to the effects of social media on political polarization 样本选择下的异质性处理效应边界，应用于社交媒体对政治极化的影响

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105856

Phillip Heiler

{"title":"Heterogeneous treatment effect bounds under sample selection with an application to the effects of social media on political polarization","authors":"Phillip Heiler","doi":"10.1016/j.jeconom.2024.105856","DOIUrl":"10.1016/j.jeconom.2024.105856","url":null,"abstract":"<div><p>We propose a method for estimation and inference for bounds for heterogeneous causal effect parameters in general sample selection models where the treatment can affect whether an outcome is observed and no exclusion restrictions are available. The method provides conditional effect bounds as functions of policy relevant pre-treatment variables. It allows for conducting valid statistical inference on the unidentified conditional effects. We use a flexible debiased/double machine learning approach that can accommodate non-linear functional forms and high-dimensional confounders. Easily verifiable high-level conditions for estimation, misspecification robust confidence intervals, and uniform confidence bands are provided as well. We re-analyze data from a large scale field experiment on Facebook on counter-attitudinal news subscription with attrition. Our method yields substantially tighter effect bounds compared to conventional methods and suggests depolarization effects for younger users.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"244 1","pages":"Article 105856"},"PeriodicalIF":9.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S030440762400201X/pdfft?md5=6a6addc12c3ac7b4b64d5b0fb4fdde73&pid=1-s2.0-S030440762400201X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

GMM estimation for high-dimensional panel data models 高维面板数据模型的 GMM 估算

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105853

Tingting Cheng , Chaohua Dong , Jiti Gao , Oliver Linton

{"title":"GMM estimation for high-dimensional panel data models","authors":"Tingting Cheng , Chaohua Dong , Jiti Gao , Oliver Linton","doi":"10.1016/j.jeconom.2024.105853","DOIUrl":"10.1016/j.jeconom.2024.105853","url":null,"abstract":"<div><p>In this paper, we study a class of high dimensional moment restriction panel data models with interactive effects, where the factors are unobserved and these factor loadings are nonparametrically unknown smooth functions of individual characteristic variables. We allow the dimension of the parameter vector and the number of moment conditions to diverge with the sample size. This is a very general framework and is closely related to many existing linear and nonlinear panel data models. In order to estimate the unknown parameters, factors and factor loadings, we propose a sieve-based generalized method of moments estimation method and we show that under a set of simple identification conditions, all those unknown quantities can be consistently estimated. Further we establish asymptotic distributions of the proposed estimators. In addition, we propose tests for over-identification, specification of factor loading functions, and establish their large sample properties. Moreover, a number of simulation studies are conducted to examine the performance of the proposed estimators and test statistics in finite samples. An empirical example on stock return prediction is studied to demonstrate both the empirical relevance and the applicability of the proposed framework and corresponding estimation and testing methods.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"244 1","pages":"Article 105853"},"PeriodicalIF":9.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0304407624001982/pdfft?md5=d3431c6c6b2ea9a2232bb95323a846ed&pid=1-s2.0-S0304407624001982-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Measuring diagnostic test performance using imperfect reference tests: A partial identification approach 利用不完善的参考测试衡量诊断测试的性能：部分鉴定方法

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105842

Filip Obradović

{"title":"Measuring diagnostic test performance using imperfect reference tests: A partial identification approach","authors":"Filip Obradović","doi":"10.1016/j.jeconom.2024.105842","DOIUrl":"10.1016/j.jeconom.2024.105842","url":null,"abstract":"<div><p>Diagnostic tests are almost never perfect. Studies quantifying their performance use knowledge of the true health status, measured with a reference diagnostic test. Researchers commonly assume that the reference test is perfect, which is often not the case in practice. When the assumption fails, conventional studies identify “apparent” performance or performance with respect to the reference, but not true performance. This paper provides the smallest possible bounds on the measures of true performance — sensitivity (true positive rate) and specificity (true negative rate), or equivalently false positive and negative rates, in standard settings. Implied bounds on policy-relevant parameters are derived: (1) Prevalence in screened populations; (2) Predictive values. Methods for inference based on moment inequalities are used to construct uniformly consistent confidence sets in level over a relevant family of data distributions. Emergency Use Authorization (EUA) and independent study data for the BinaxNOW COVID-19 antigen test demonstrate that the bounds can be very informative. Analysis reveals that the estimated false negative rates for symptomatic and asymptomatic patients are up to 3.17 and 4.59 times higher than the frequently cited “apparent” false negative rate. Further applicability of the results in the context of imperfect proxies such as survey responses and imputed protected classes is indicated.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"244 1","pages":"Article 105842"},"PeriodicalIF":9.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168782","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 option pricing models using a characteristic function-based linear state space representation 使用基于特征函数的线性状态空间表示法估算期权定价模型

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105864

H. Peter Boswijk , Roger J.A. Laeven , Evgenii Vladimirov

{"title":"Estimating option pricing models using a characteristic function-based linear state space representation","authors":"H. Peter Boswijk , Roger J.A. Laeven , Evgenii Vladimirov","doi":"10.1016/j.jeconom.2024.105864","DOIUrl":"10.1016/j.jeconom.2024.105864","url":null,"abstract":"<div><div>We develop a novel filtering and estimation procedure for parametric option pricing models driven by general affine jump-diffusions. Our procedure is based on the comparison between an option-implied, model-free representation of the conditional log-characteristic function and the model-implied conditional log-characteristic function, which is functionally affine in the model’s state vector. We formally derive an associated linear state space representation and the asymptotic properties of the corresponding measurement errors. The state space representation allows us to use a suitably modified Kalman filtering technique to learn about the latent state vector and a quasi-maximum likelihood estimator of the model parameters, for which we establish asymptotic inference results. Accordingly, the filtering and estimation procedure brings important computational advantages. We analyze the finite-sample behavior of our procedure in Monte Carlo simulations. The applicability of our procedure is illustrated in two case studies that analyze S&P 500 option prices and the impact of exogenous state variables capturing Covid-19 reproduction and economic policy uncertainty.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"244 1","pages":"Article 105864"},"PeriodicalIF":9.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An unbounded intensity model for point processes 点过程的无界强度模型

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105840

Kim Christensen , Aleksey Kolokolov

{"title":"An unbounded intensity model for point processes","authors":"Kim Christensen , Aleksey Kolokolov","doi":"10.1016/j.jeconom.2024.105840","DOIUrl":"10.1016/j.jeconom.2024.105840","url":null,"abstract":"<div><p>We develop a model for point processes on the real line, where the intensity can be locally unbounded without inducing an explosion. In contrast to an orderly point process, for which the probability of observing more than one event over a short time interval is negligible, the bursting intensity causes an extreme clustering of events around the singularity. We propose a nonparametric approach to detect such bursts in the intensity. It relies on a heavy traffic condition, which admits inference for point processes over a finite time interval. With Monte Carlo evidence, we show that our testing procedure exhibits size control under the null, whereas it has high rejection rates under the alternative. We implement our approach on high-frequency data for the EUR/USD spot exchange rate, where the test statistic captures abnormal surges in trading activity. We detect a nontrivial amount of intensity bursts in these data and describe their basic properties. Trading activity during an intensity burst is positively related to volatility, illiquidity, and the probability of observing a drift burst. The latter effect is reinforced if the order flow is imbalanced or the price elasticity of the limit order book is large.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"244 1","pages":"Article 105840"},"PeriodicalIF":9.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0304407624001854/pdfft?md5=93aab3c0b2d370e0d64aae438b804950&pid=1-s2.0-S0304407624001854-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142040253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Large Bayesian SVARs with linear restrictions 具有线性限制的大型贝叶斯 SVAR

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105850

Chenghan Hou

引用次数: 0

Threshold spatial autoregressive model 阈值空间自回归模型

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105841

Kunpeng Li , Wei Lin

{"title":"Threshold spatial autoregressive model","authors":"Kunpeng Li , Wei Lin","doi":"10.1016/j.jeconom.2024.105841","DOIUrl":"10.1016/j.jeconom.2024.105841","url":null,"abstract":"<div><p>In this paper, we consider the estimation and inferential issues of the threshold spatial autoregressive (TSAR) model, which is a hybrid of the threshold and spatial autoregressive models. We use the quasi maximum likelihood (QML) method to estimate the model. In addition, we prove the tightness and the Hájek–Rényi type inequality for a quadratic form and establish a full inferential theory of the QML estimator under the setup that threshold effect shrinks to zero as the sample size increases. We conduct hypothesis testing on the presence of the threshold effect, using three super-type statistics. Their asymptotic behaviors are studied under the Pitman local alternatives. A bootstrap procedure is applied to obtain the asymptotically correct critical value. We also consider hypothesis testing on the threshold value set equal to a prespecified one. We run Monte Carlo simulations to investigate the finite sample performance of the QML estimators and find that the estimators perform well. In an empirical application, we apply the proposed TSAR model to study the relationship between financial development and economic growth, and we find firm evidence to support the TSAR model.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"244 1","pages":"Article 105841"},"PeriodicalIF":9.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142097628","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 risk minimization for time series: Nonparametric performance bounds for prediction 时间序列的经验风险最小化：预测的非参数性能界限

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105849

Christian Brownlees , Jordi Llorens-Terrazas

{"title":"Empirical risk minimization for time series: Nonparametric performance bounds for prediction","authors":"Christian Brownlees , Jordi Llorens-Terrazas","doi":"10.1016/j.jeconom.2024.105849","DOIUrl":"10.1016/j.jeconom.2024.105849","url":null,"abstract":"<div><p>Empirical risk minimization is a standard principle for choosing algorithms in learning theory. In this paper we study the properties of empirical risk minimization for time series. The analysis is carried out in a general framework that covers different types of forecasting applications encountered in the literature. We are concerned with 1-step-ahead prediction of a univariate time series belonging to a class of location-scale parameter-driven processes. A class of recursive algorithms is available to forecast the time series. The algorithms are recursive in the sense that the forecast produced in a given period is a function of the lagged values of the forecast and of the time series. The relationship between the generating mechanism of the time series and the class of algorithms is not specified. Our main result establishes that the algorithm chosen by empirical risk minimization achieves asymptotically the optimal predictive performance that is attainable within the class of algorithms.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"244 1","pages":"Article 105849"},"PeriodicalIF":9.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0304407624001945/pdfft?md5=03c2f325f7afb91701d18b9a3b37813b&pid=1-s2.0-S0304407624001945-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification and estimation of unconditional policy effects of an endogenous binary treatment: An unconditional MTE approach 内生二元处理的无条件政策效应的识别和估计：无条件 MTE 方法

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105858

Julian Martinez-Iriarte , Yixiao Sun

引用次数: 0

Identification in discrete choice models with imperfect information 不完全信息离散选择模型的识别

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2024-08-01 DOI: 10.1016/j.jeconom.2024.105854

Cristina Gualdani , Shruti Sinha

引用次数: 0